diff --git a/neuroKit2.ipynb b/neuroKit2.ipynb new file mode 100644 index 0000000..2584a23 --- /dev/null +++ b/neuroKit2.ipynb @@ -0,0 +1,733 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## This code is uses NeuroKit2 to analyze EDA data for the KPE study\n", + "- We take event files and acq files for each subjects\n", + "- We preprocess them and generate epoch for each script (i.e. condition)\n", + "- We save a csv file of data for each subject for further analysis " + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [], + "source": [ + "import neurokit2 as nk\n", + "import pandas as pd\n", + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "import glob" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [], + "source": [ + "# set parameters\n", + "output_dir = '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/results'\n", + "ses = '1' # set session\n", + "acq_files = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe*/scan_%s/kpe*_scripts*.acq' %ses)\n", + "events_file = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/sub-*_ses-%s.csv' %ses)" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [], + "source": [ + "acq_files.sort()\n", + "events_file.sort() # sorting by sub number" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe008/scan_1/kpe008.1_scripts_2016-10-24T09_00_11.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1223/scan_1/kpe1223.1_scripts_2017-01-30T08_17_08.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1253/scan_1/kpe1253.1_scripts_2016-12-12T08_12_57.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1263/scan_1/kpe1263.1_scripts_2016-11-28T08_38_41.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1293/scan_1/kpe1293.1_scripts_2017-02-27T08_18_18.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1307/scan_1/kpe1307.1_scripts_2017-06-05T08_31_00.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1315/scan_1/kpe1315.1_scripts_2017-04-10T08_31_02.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1322/scan_1/kpe1322.1_scripts_2017-05-22T08_20_59.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1339/scan_1/kpe1339.1_scripts2017-07-24T08_27_26.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1343/scan_1/kpe1343.1_scripts_2017-09-18T08_15_53.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1351/scan_1/kpe1351.1_scripts_2017-11-27T08_28_54.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1356/scan_1/kpe1356.1_scripts_2017-12-04T08_38_09.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1364/scan_1/kpe1364.1_scripts_2018-01-22T08_21_12.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1369/scan_1/kpe1369.1_scripts_2018-02-05T08_11_38.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1387/scan_1/kpe1387.1_scripts_2018-09-10T08_39_24.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1390/scan_1/kpe1390.1_scripts_2018-04-30T08_27_00.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1403/scan_1/kpe1403.1_scripts_2018-06-04T08_21_30.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1419/scan_1/kpe1419.1_scripts_2019-12-02T08_22_41.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1464/scan_1/kpe1464.1_scripts_2019-01-14T08_27_28.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1468/scan_1/kpe1468.1_scripts_2019-04-08T08_27_29.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1480/scan_1/kpe1480.1_scripts_2019-05-06T08_20_54.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1499/scan_1/kpe1499.1_scripts_2019-06-03T08_23_06.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1561/scan_1/kpe1561.1_scripts_2019-09-23T08_13_58.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1573/scan_1/kpe1573.1_scripts2020-01-27T08_25_31.acq',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/kpe1578/scan_1/kpe1578.1_scripts_2020-02-03T08_39_36.acq']" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "acq_files" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "25" + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(acq_files)" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "008\n", + "Acq file 008\n", + "1223\n", + "Acq file 1223\n", + "1253\n", + "Acq file 1253\n", + "1263\n", + "Acq file 1263\n", + "1293\n", + "Acq file 1293\n", + "1307\n", + "Acq file 1307\n", + "1315\n", + "Acq file 1315\n", + "1322\n", + "Acq file 1322\n", + "1339\n", + "Acq file 1339\n", + "1343\n", + "Acq file 1343\n", + "1351\n", + "Acq file 1351\n", + "1356\n", + "Acq file 1356\n", + "1364\n", + "Acq file 1364\n", + "1369\n", + "Acq file 1369\n", + "1387\n", + "Acq file 1387\n", + "1390\n", + "Acq file 1390\n", + "1403\n", + "Acq file 1403\n", + "1419\n", + "Acq file 1419\n", + "1464\n", + "Acq file 1464\n", + "1468\n", + "Acq file 1468\n", + "1480\n", + "Acq file 1480\n", + "1499\n", + "Acq file 1499\n", + "1561\n", + "Acq file 1561\n", + "1573\n", + "Acq file 1573\n", + "1578\n", + "Acq file 1578\n" + ] + } + ], + "source": [ + "len(events_file)\n", + "for acq, file in zip(acq_files, events_file):\n", + " print(file.split('sub-')[1].split('_ses')[0])\n", + " print(f\"Acq file {acq.split('kpe')[1].split('/scan')[0]}\")\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [], + "source": [ + "# find epochs to match \n", + "# first read condition list from subjects' events file\n", + "\n", + "def readAnalyze_acq(file, ev_file):\n", + " # this function takes the acq file and events file and returns a data frame of \n", + " # trial type and max EDA\n", + " a = nk.read_acqknowledge(file, sampling_rate=100,\n", + " resample_method=\"interpolation\", impute_missing=True)\n", + " events_file = pd.read_csv(ev_file, sep='\\t')\n", + " condition_list = list(events_file.trial_type)\n", + "\n", + " # then use the events_find function to determine onset and duration of the events \n", + " #(here its going from 0 to 5, so threshold is above)\n", + " events = nk.events_find(event_channel=a[0].Script,\n", + " threshold_keep='above',\n", + " event_conditions=condition_list)\n", + "\n", + " # Preprocess the data (filter, find peaks, etc.)\n", + " processed_data, info = nk.bio_process(#ecg=a[0][\"ECG100C\"],\n", + " eda=a[0][\"GSR100C\"],\n", + " keep=a[0][\"Script\"],\n", + " sampling_rate=a[1])\n", + "\n", + "\n", + " # create epochs\n", + " epochs = nk.epochs_create(processed_data, events, sampling_rate=a[1], epochs_start=0,\n", + " epochs_end=10) # ends 10 as there might be some carryover\n", + " results = nk.bio_analyze(epochs, sampling_rate=a[1], method='interval-related')\n", + " return results" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "008\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/sub-008_ses-1.csv\n", + "1223\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/sub-1223_ses-1.csv\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/neurokit2/eda/eda_intervalrelated.py:116: RuntimeWarning: invalid value encountered in double_scalars\n", + " output[\"SCR_Peaks_Amplitude_Mean\"] = np.nansum(amplitude) / np.sum(peaks)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1253\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/sub-1253_ses-1.csv\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/neurokit2/eda/eda_intervalrelated.py:116: RuntimeWarning: invalid value encountered in double_scalars\n", + " output[\"SCR_Peaks_Amplitude_Mean\"] = np.nansum(amplitude) / np.sum(peaks)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1263\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/sub-1263_ses-1.csv\n", + "1293\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/sub-1293_ses-1.csv\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/neurokit2/eda/eda_intervalrelated.py:116: RuntimeWarning: invalid value encountered in double_scalars\n", + " output[\"SCR_Peaks_Amplitude_Mean\"] = np.nansum(amplitude) / np.sum(peaks)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1307\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/sub-1307_ses-1.csv\n", + "1315\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/sub-1315_ses-1.csv\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/neurokit2/eda/eda_intervalrelated.py:116: RuntimeWarning: invalid value encountered in double_scalars\n", + " output[\"SCR_Peaks_Amplitude_Mean\"] = np.nansum(amplitude) / np.sum(peaks)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1322\n", + 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output[\"SCR_Peaks_Amplitude_Mean\"] = np.nansum(amplitude) / np.sum(peaks)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1351\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/sub-1351_ses-1.csv\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/neurokit2/eda/eda_intervalrelated.py:116: RuntimeWarning: invalid value encountered in double_scalars\n", + " output[\"SCR_Peaks_Amplitude_Mean\"] = np.nansum(amplitude) / np.sum(peaks)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1356\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/sub-1356_ses-1.csv\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/neurokit2/eda/eda_intervalrelated.py:116: RuntimeWarning: invalid 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value encountered in double_scalars\n", + " output[\"SCR_Peaks_Amplitude_Mean\"] = np.nansum(amplitude) / np.sum(peaks)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1573\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/sub-1573_ses-1.csv\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/neurokit2/eda/eda_intervalrelated.py:116: RuntimeWarning: invalid value encountered in double_scalars\n", + " output[\"SCR_Peaks_Amplitude_Mean\"] = np.nansum(amplitude) / np.sum(peaks)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1578\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/sub-1578_ses-1.csv\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/neurokit2/eda/eda_intervalrelated.py:116: RuntimeWarning: invalid value encountered in double_scalars\n", + " output[\"SCR_Peaks_Amplitude_Mean\"] = np.nansum(amplitude) / np.sum(peaks)\n" + ] + } + ], + "source": [ + "for file, ev_file in zip(acq_files, events_file):\n", + " sub = file.split('kpe')[1].split('/')[0]\n", + " print(sub)\n", + " print(ev_file)\n", + " result = readAnalyze_acq(file, ev_file)\n", + " result['subject_id'] = sub\n", + " result.to_csv(output_dir + '/sub-' + sub + '_ses-' + ses + '.csv', index=False, sep = '\\t')" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " SCR_Peaks_N SCR_Peaks_Amplitude_Mean subject_id\n", + "1 1.0 0.042608 1561\n", + "2 0.0 NaN 1561\n", + "3 1.0 0.007511 1561\n", + "4 1.0 0.047930 1561\n", + "5 1.0 0.003172 1561\n", + "6 1.0 0.044502 1561\n", + "7 1.0 0.289602 1561\n", + "8 1.0 0.147923 1561\n", + "9 1.0 0.200464 1561" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "condition_list = ['sad1','trauma1','relax1', 'sad2','trauma2','']" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "You can cite NeuroKit2 as follows:\n", + "\n", + "- Makowski, D., Pham, T., Lau, Z. J., Brammer, J. C., Lesspinasse, F., Pham, H.,\n", + " Schölzel, C., & S H Chen, A. (2020). NeuroKit2: A Python Toolbox for Neurophysiological\n", + " Signal Processing. Retrieved October 25, 2020, from https://github.com/neuropsychology/NeuroKit\n", + "\n", + "\n", + "Full bibtex reference:\n", + "\n", + "@misc{neurokit2,\n", + " doi = {10.5281/ZENODO.3597887},\n", + " url = {https://github.com/neuropsychology/NeuroKit},\n", + " author = {Makowski, Dominique and Pham, Tam and Lau, Zen J. and Brammer, Jan C. and Lesspinasse,\n", + " Fran\\c{c}ois and Pham, Hung and Schölzel, Christopher and S H Chen, Annabel},\n", + " title = {NeuroKit2: A Python Toolbox for Neurophysiological Signal Processing},\n", + " publisher = {Zenodo},\n", + " month={Mar},\n", + " year = {2020},\n", + "}\n", + "\n" + ] + } + ], + "source": [ + "nk.cite()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.7.7 64-bit ('neuroAnalysis': conda)", + "language": "python", + "name": "python37764bitneuroanalysiscondaa23731adadc74dd9881a406adec17ad1" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/ridge_cpm.py b/ridge_cpm.py new file mode 100644 index 0000000..a3b088e --- /dev/null +++ b/ridge_cpm.py @@ -0,0 +1,96 @@ +''' +@Author: Or Duek +Using Ridge regression to run the CPM for the KPE study +''' +#%% Load libraries +from sklearn.linear_model import Ridge +from sklearn.model_selection import GridSearchCV +from sklearn.model_selection import cross_val_predict +from sklearn.model_selection import cross_val_score +from sklearn import linear_model +from sklearn.model_selection import KFold +from sklearn.model_selection import RepeatedKFold +from sklearn.model_selection import PredefinedSplit +from sklearn.feature_selection import SelectPercentile +from sklearn.feature_selection import f_regression +from sklearn.pipeline import Pipeline +from sklearn.model_selection import StratifiedKFold +from sklearn import metrics +import pandas as pd +import numpy as np +import scipy.io as sio +import h5py + +import time + + +#%% Load matrices and behaviour +# AAL +first = np.load('/home/or/kpe_task_analysis/trauma_ses1.npy') +second = np.load('/home/or/kpe_task_analysis/trauma_ses2.npy') +delta = np.subtract(second, first) + +# delta1 = np.delete(delta, mask, axis=2) +# delta1.shape +y = np.array([-2, 1, -30, -17, -28, -4, -30, -18, -22, -18, 1, -11, -2, -4, 16, -32, -8, -14, -20, -3, -23]) +delta.shape + +#%% turn matrix to array +vecs = [] +for i in range(delta.shape[2]): + mat = delta[:,:,i] + flat = mat.flatten() + vecs.append(flat) +vecs = np.array(vecs) +print(vecs.shape) +vecs_reshape = np.moveaxis(vecs,0,-1) +#%% Set parameters of the model +pct = 0.8 # percent of edges kept in feature selection +alphas = 10**np.linspace(10,-2,100)*0.5 # specify alphas to search +#%% +rg_grid = GridSearchCV(Ridge(normalize=False), cv=10, param_grid={'alpha':alphas}, iid=False) +# using LASSO regression instead of ridge +lasso = linear_model.Lasso +lasso_grid = GridSearchCV(lasso(normalize=False), cv=10, param_grid={'alpha':alphas}, iid=False) + +reg = Pipeline([ + ('feature_selection', SelectPercentile(f_regression, percentile=pct)), + ('regression', lasso_grid) +]) + +cv10 = KFold(n_splits=21)#, random_state=665) +rpcv10 = RepeatedKFold(n_splits=3,n_repeats=3, random_state=665) +# %% Run model +start = time.time() # time the function +all_pred = cross_val_predict(reg, vecs_reshape.T, y, cv=cv10, n_jobs=4) +#all_score = cross_val_score(reg, vecs_reshape.T, y, cv=rpcv10, n_jobs=1) # repeated kfolds +end = time.time() +print(end - start) # print function running time + +# %% +print(np.corrcoef(all_pred.T, y.T)) + +# %% +import scipy +scipy.stats.pearsonr(all_pred, y) +#%% plot +import seaborn as sns +import matplotlib.pyplot as plot +sns.regplot(all_pred, y) + + +#%% Try with shen parcellation +first = np.load('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/shen/trauma_ses1_shen.npy') +second = np.load('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/shen/trauma_ses2_shen.npy') +delta = np.subtract(second, first) + + +# %% +# lets plot with groups also +df = pd.DataFrame({'group': group_label, 'observed':y, 'predicted':all_pred}) + + +sns.lmplot('predicted','observed', hue='group', data= df) +print(f'Ketamine group correlation {scipy.stats.pearsonr(df.predicted[df.group==1], df.observed[df.group==1])}') +print(f'Midazolam group correlation {scipy.stats.pearsonr(df.predicted[df.group==0], df.observed[df.group==0])}') +# %% diff --git a/rs/.ipynb_checkpoints/difumo_extract_timeline-checkpoint.py b/rs/.ipynb_checkpoints/difumo_extract_timeline-checkpoint.py new file mode 100644 index 0000000..1d19e16 --- /dev/null +++ b/rs/.ipynb_checkpoints/difumo_extract_timeline-checkpoint.py @@ -0,0 +1,112 @@ +# %% +''' +@author: Or Duek +@date: Jul 16 2020 + +This is a sciprt that uses the nee DiFuMo dictionary +atlas (https://www.sciencedirect.com/science/article/pii/S1053811920306121#appsec7) + +In this file we will create a task based +''' +# %% import libraries +import pandas as pd +from nilearn.input_data import NiftiMapsMasker +from nilearn import connectome +from nilearn import datasets +import numpy as np +import nilearn.plotting +from sklearn.model_selection import StratifiedShuffleSplit +import os +import glob +from nilearn import connectome +import seaborn as sns +# %% Set output folder +output_dir = '/gpfs/gibbs/pi/levy_ifat/Or/kpe/results/resting' +# set session +ses= '3' # session is a string +# %% Functions +# extract RS data and create vector for each subject +def removeVars (confoundFile): + # this method takes the csv regressors file (from fmriPrep) and chooses a few to confound. You can change those few + import pandas as pd + confound = pd.read_csv(confoundFile,sep="\t", na_values="n/a") + finalConf = confound[['csf', 'white_matter', 'framewise_displacement', + 'a_comp_cor_00', 'a_comp_cor_01','a_comp_cor_02', 'a_comp_cor_03', + 'a_comp_cor_04', 'a_comp_cor_05', 'trans_x', 'trans_y', 'trans_z', + 'rot_x', 'rot_y', 'rot_z']] # can add 'global_signal' also ,, + # + # change NaN of FD to zero + finalConf = np.array(finalConf.fillna(0.0)) + return finalConf + + +# %% functional files + +func_template = '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-{sub}/ses-{session}/func/sub-{sub}_ses-{session}_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz' +confound_template = '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-{sub}/ses-{session}/func/sub-{sub}_ses-{session}_task-rest_desc-confounds_regressors.tsv' + +# get subject list +# from bids import BIDSLayout +# folder = '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/' +# layout = BIDSLayout(folder, validate=False) +# subject_list = layout.get_subjects() +# %% +# create a mean mask of all subjects +# load mask of brain + + +brainmasks = glob.glob('/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-*/ses-%s/func/sub-*_ses-%s_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz' %(ses,ses)) +print(brainmasks) +# %matplotlib inline +#for mask in brainmasks: + # nilearn.plotting.plot_roi(mask) + +mean_mask = nilearn.image.mean_img(brainmasks) +#nilearn.plotting.plot_stat_map(mean_mask) +group_mask = nilearn.image.math_img("a>=0.98", a=mean_mask) +#nilearn.plotting.plot_roi(group_mask) + +# %% fetch atlas +maps_img = '/gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz' +labels = pd.read_csv('/gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/labels_256_dictionary.csv') +#coords = nilearn.plotting.find_parcellation_cut_coords(labels_img=maps_img) +coords = nilearn.plotting.find_probabilistic_atlas_cut_coords(maps_img) +# generate time series +# +mask_params = { 'mask_img': group_mask, + 'detrend': True, 'standardize': True, + 'high_pass': 0.01, 'low_pass': 0.1, 't_r': 1, + 'smoothing_fwhm': 6., + 'verbose': 5} + +masker = NiftiMapsMasker(maps_img=maps_img, **mask_params) + +# %% +subject_list = ['1587'] + +# %% Generate npy files of timeseries for each subject per session +# we will use it later on, stratify to scripts etc. +# build a specific folder +try: + os.makedirs(output_dir) +except: + print('Folder already exist') + +subject_ts = [] +for sub in subject_list: + print(f' Analysing subject {sub}') + subject = sub + func = func_template.format(sub=subject, session=ses) + confound = confound_template.format(sub=subject, session=ses) + try: + signals = masker.fit_transform(imgs=func, confounds=removeVars(confound)) + save = np.save(output_dir + 'sub-' + subject + '_ses-' + ses, signals) + subject_ts.append(signals) + except: + print(f'Subject {sub} has no data') + + + + + +# %% diff --git a/rs/.ipynb_checkpoints/difumo_timeseries-checkpoint.py b/rs/.ipynb_checkpoints/difumo_timeseries-checkpoint.py new file mode 100644 index 0000000..758f787 --- /dev/null +++ b/rs/.ipynb_checkpoints/difumo_timeseries-checkpoint.py @@ -0,0 +1,340 @@ +# %% +''' +@author: Or Duek +@date: Jul 16 2020 + +This is a sciprt that uses the nee DiFuMo dictionary +atlas (https://www.sciencedirect.com/science/article/pii/S1053811920306121#appsec7) + +In this file we will create a task based +''' +# %% +# %config Completer.use_jedi = False + +# %% import libraries +import pandas as pd +from nilearn.input_data import NiftiMapsMasker + +from nilearn import datasets +import numpy as np +import nilearn.plotting +from sklearn.model_selection import StratifiedShuffleSplit +import os +import glob +from nilearn import connectome +import seaborn as sns +import matplotlib.pyplot as plt +import statsmodels.api as sm +# %% Set output folder +## condition labels (ketamine , midazolam) +# read file +medication_cond = pd.read_csv('/home/oad4/kpe_task/task_based_analysis/kpe_sub_condition.csv') +# remove 1315 (OCD), also remove for 2nd session remove 1578 +medication_cond1 = medication_cond[medication_cond.scr_id!='KPE1315'] # for 1st session +medication_cond2 = medication_cond[(medication_cond.scr_id!='KPE1315') & + (medication_cond.scr_id!='KPE1578')] # for 2nd session +medication_cond3 = medication_cond[(medication_cond.scr_id!='KPE1315') & + (medication_cond.scr_id!='KPE1253') & (medication_cond.scr_id!='KPE1468') & + (medication_cond.scr_id!='KPE1480') & (medication_cond.scr_id!='KPE1587') + ] # for 3rd session + +subject_list1 = np.array(medication_cond1.scr_id) +subject_list2 = np.array(medication_cond2.scr_id) +subject_list3 = np.array(medication_cond3.scr_id) +condition_label1 = np.array(medication_cond1.med_cond) +condition_label2 = np.array(medication_cond2.med_cond) +condition_label3 = np.array(medication_cond3.med_cond) +#group_label1 = list(map(int, condition_label)) + +# %% +medication_cond3 + +# %% +len(subject_list3) +#print(condition_label2) + +# %% fetch atlas +maps_img = '/gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz' +labels = pd.read_csv('/gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/labels_256_dictionary.csv') +#coords = nilearn.plotting.find_parcellation_cut_coords(labels_img=maps_img) +coords = nilearn.plotting.find_probabilistic_atlas_cut_coords(maps_img) +# plot atlas (only if we want) +nilearn.plotting.plot_prob_atlas(maps_img, draw_cross=False) +# %% read files and stratify to relevant script +# method to generate subject array of timeseries +def pooledTS(subject_list, ses): + rs_template = '/gpfs/gibbs/pi/levy_ifat/Or/kpe/results/restingsub-{sub}_ses-{ses}.npy' + sub_ts = [] + for sub in subject_list: + subject = sub.split('KPE')[1] + + # load the npy file (timeseries) + ts = np.load(rs_template.format(sub=subject, ses=ses), allow_pickle=True) + ts_script = ts[5:,:] # remove first five trs + sub_ts.append(ts_script) + return sub_ts +# %% +from nilearn import connectome +connectome = connectome.ConnectivityMeasure( + kind='partial correlation', vectorize=False) + +mat_ses1 = connectome.fit_transform(pooledTS(subject_list1, '1')) + + +# %% +mat_ses1.shape + +# %% plot mean matrix +# %matplotlib inline +nilearn.plotting.plot_matrix(connectome.mean_, + colorbar=True, labels= range(256), reorder='average') + +# %% lets run ses 2 +mat_ses2 = connectome.fit_transform(pooledTS(subject_list2, '2')) +# %matplotlib inline +nilearn.plotting.plot_matrix(connectome.mean_, + colorbar=True, labels= range(256), reorder='average') + +# %% +mat_ses3 = connectome.fit_transform(pooledTS(subject_list3, '3')) + +# %% +# fisher-z transformation +mat_ses1 = np.arctan(mat_ses1) +mat_ses2 = np.arctan(mat_ses2) +mat_ses3 = np.arctan(mat_ses3) + +# %% +## Generate matrix of just ROIs (amygdala, hippocampus, vmpfc and caudate) +# get index of each ROI + +labels_list = list(labels.Difumo_names) +amg = labels_list.index('Amygdala') +hippo_post = labels_list.index('Hippocampus posterior') +hippo_ant = labels_list.index('Hippocampus anterior') +vmPFC_ant = labels_list.index('Ventromedial prefrontal cortex anterior') +vmPFC = labels_list.index('Ventromedial prefrontal cortex') +index_list = np.array([amg, hippo_post, hippo_ant, vmPFC_ant, vmPFC])#, caudate_ant, caudate_inf, caudate_sup]) + +# set matrix for specific ROIs (as defined above) +mat1ROI = mat_ses1[: ,index_list,:] +mat1ROI = mat1ROI[:,:,index_list] + +mat2ROI = mat_ses2[: ,index_list,:] +mat2ROI = mat2ROI[:,:,index_list] + +mat3ROI = mat_ses3[: ,index_list,:] +mat3ROI = mat3ROI[:,:,index_list] + + + +# %% +mat2ROI.shape +labels = ['amygdala','hippoPost','hippoAnt','vmPFCAnt','vmPFC']#,'Ca_Ant','Ca_In','ca_sup'] +nilearn.plotting.plot_matrix((np.mean(mat2ROI, axis=0)), + colorbar=True, labels= labels, reorder='average') + +nilearn.plotting.plot_matrix((np.mean(mat1ROI, axis=0)), + colorbar=True, labels= labels, reorder='average') + +# %% +# show groups +ketSes1 = mat1ROI[condition_label1==1] +midSes1 = mat1ROI[condition_label1==0] + +ketSes2 = mat2ROI[condition_label2==1] +midSes2 = mat2ROI[condition_label2==0] + +ketSes3 = mat3ROI[condition_label3==1] +midSes3 = mat3ROI[condition_label3==0] + + + +# %% +midSes3.shape + +# %% +## First session +sns.heatmap(np.mean(ketSes1, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Ketamine") +plt.show() + +sns.heatmap(np.mean(midSes1, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Midazolam") + +# %% +sns.heatmap(np.mean(ketSes2, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Ketamine") +plt.show() + +sns.heatmap(np.mean(midSes2, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Midazolam") + + +# %% +sns.heatmap(np.mean(ketSes3, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Ketamine") +plt.show() + +sns.heatmap(np.mean(midSes3, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Midazolam") + +# %% +import scipy +t, p = scipy.stats.ttest_ind(ketSes3, midSes3) +tArr = np.array(t) + +thr = 0.05 +tArr[p>thr] = 0 +sns.heatmap(tArr,xticklabels = labels, yticklabels = labels, cmap='coolwarm', annot=True) + +# %% +tArr + +# %% +# run simple t test to show whats going on +t, p = scipy.stats.ttest_ind(ketSes2, midSes2) +tArr = np.array(t) +tArr[p>thr] = 0 +sns.heatmap(tArr, xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) + +# %% +# create delta arrays +ketDelta = np.subtract(ketSes2, ketSes1) +# removing 1578 (last one) from midazolam group +midDelta = np.subtract(midSes2, midSes1[0:11]) +sns.heatmap(np.mean(ketDelta, axis=0), + cmap='coolwarm', xticklabels=labels, + yticklabels=labels, annot=True, vmin = -1, vmax = 1) +plt.show() +sns.heatmap(np.mean(midDelta, axis=0), cmap='coolwarm', + xticklabels=labels, yticklabels=labels, annot=True, vmin=-1, vmax=1) +plt.show() + + +# %% +# create delta arrays 3 and one - so need to make everything like 3 for the midazolam group (they have only 9) +mat_sesM1 = connectome.fit_transform(pooledTS(subject_list3, '1')) +mat_sesM1 = np.arctan(mat_sesM1) +mat1ROIM = mat_sesM1[: ,index_list,:] +mat1ROIM = mat1ROIM[:,:,index_list] +midSes1M = mat1ROIM[condition_label3==0] + + +ketDelta = np.subtract(ketSes3, ketSes1) +# removing 1578 (last one) from midazolam group +midDelta = np.subtract(midSes3, midSes1M) +sns.heatmap(np.mean(ketDelta, axis=0), + cmap='coolwarm', xticklabels=labels, + yticklabels=labels, annot=True, vmin = -1, vmax = 1) +plt.show() +sns.heatmap(np.mean(midDelta, axis=0), cmap='coolwarm', + xticklabels=labels, yticklabels=labels, annot=True, vmin=-1, vmax=1) +plt.show() + + +# %% +import mne + +t, p = scipy.stats.ttest_ind(ketDelta, midDelta) +tArr = np.array(t) +# vectorize the p to include only the actual +pvec = np.concatenate(np.tril(p)) +print(pvec) +fdr = mne.stats.fdr_correction(pvec, alpha=0.8, method='indep') +print(fdr) +tArr[fdr[1]>.05] = 0 +#print(tArr) +sns.heatmap(tArr, xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) + +# %% +# lets run NBS +ketDeltaReshape = np.moveaxis(np.array(ketDelta),0,-1) +midDeltaReshape = np.moveaxis(np.array(midDelta),0,-1) + +ketSes2_reshape = np.moveaxis(np.array(ketSes2),0,-1) +midSes2_reshape = np.moveaxis(np.array(midSes2),0,-1) + +ketSes3_reshape = np.moveaxis(np.array(ketSes3),0,-1) +midSes3_reshape = np.moveaxis(np.array(midSes3),0,-1) +print(ketDeltaReshape.shape) +print(midDeltaReshape.shape) + +# difference between the sessions +mat1ROI_reshape = np.moveaxis(np.array(mat1ROI), 0, -1) +mat3ROI_reshape = np.moveaxis(np.array(mat3ROI), 0, -1) +mat2ROI_reshape = np.moveaxis(np.array(mat2ROI), 0, -1) + +from bct import nbs + +# we compare ket1 and ket3 +pval, adj, _ = nbs.nbs_bct(mat1ROI_reshape, mat2ROI_reshape, thresh=1.5, tail='both',k=1000, + paired=True, verbose = False) +print(pval) + +# %% +# ok lets threshold using adjacency +#tTresh = t[np.tril(adj)] +tTresh = t* adj +#tTresh[np.triu(tTresh)] = t +sns.heatmap(tTresh, xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) +plt.show() +sns.heatmap(np.mean(ketDelta, axis=0), xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) +plt.show() +sns.heatmap(np.mean(midDelta, axis=0), xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) + +# %% +labels + +# %% +# built data frame for each session +df_ses1 = pd.DataFrame( + {'subject': subject_list1, 'group': condition_label1, 'amg_hippPost1': mat1ROI[:,0,1], 'amg_vmPFC1': mat1ROI[:,0,4], 'amg_hippAnt1': mat1ROI[:,0,2], + 'amg_vmPFCant1': mat1ROI[:,0,3], 'hippAnt_vmPFC1': mat1ROI[:,2,4], 'hippPost_vmPFC1': mat1ROI[:,1,4], + 'hippAnt_vmPFCant1': mat1ROI[:,2,3], 'hippPost_vmPFCant1': mat1ROI[:,1,3]} +) + +df_ses1.to_csv('RS_conn_ses1.csv', index=False) + +# %% +df_ses1 + +# %% +# built data frame for each session +df_ses2 = pd.DataFrame( + {'subject': subject_list2, 'group': condition_label2, 'amg_hippPost2': mat2ROI[:,0,1], + 'amg_vmPFC2': mat2ROI[:,0,4], 'amg_hippAnt2': mat2ROI[:,0,2], + 'amg_vmPFCant2': mat2ROI[:,0,3], 'hippAnt_vmPFC2': mat2ROI[:,2,4], 'hippPost_vmPFC2': mat2ROI[:,1,4], + 'hippAnt_vmPFCant2': mat2ROI[:,2,3], 'hippPost_vmPFCant2': mat2ROI[:,1,3]} +) + +df_ses2.to_csv('RS_conn_ses2.csv', index=False) + +# %% +# built data frame for each session +df_ses3 = pd.DataFrame( + {'subject': subject_list3, 'group': condition_label3, 'amg_hippPost3': mat3ROI[:,0,1], + 'amg_vmPFC3': mat3ROI[:,0,4], 'amg_hippAnt3': mat3ROI[:,0,2], + 'amg_vmPFCant3': mat3ROI[:,0,3], 'hippAnt_vmPFC3': mat3ROI[:,2,4], 'hippPost_vmPFC3': mat3ROI[:,1,4], + 'hippAnt_vmPFCant3': mat3ROI[:,2,3], 'hippPost_vmPFCant3': mat3ROI[:,1,3]} +) + +df_ses3.to_csv('RS_conn_ses3.csv', index=False) + +# %% +# combine all three +dfAll = pd.merge(df_ses1, df_ses2, how='left') +dfAll = pd.merge(dfAll, df_ses3, how= 'left') +dfAll.to_csv('RS_conn_3Sessions.csv', index=False) diff --git a/rs/RS_conn_3Sessions.csv b/rs/RS_conn_3Sessions.csv new file mode 100644 index 0000000..84e1497 --- /dev/null +++ b/rs/RS_conn_3Sessions.csv @@ -0,0 +1,27 @@ +subject,group,amg_hippPost1,amg_vmPFC1,amg_hippAnt1,amg_vmPFCant1,hippAnt_vmPFC1,hippPost_vmPFC1,hippAnt_vmPFCant1,hippPost_vmPFCant1,amg_hippPost2,amg_vmPFC2,amg_hippAnt2,amg_vmPFCant2,hippAnt_vmPFC2,hippPost_vmPFC2,hippAnt_vmPFCant2,hippPost_vmPFCant2,amg_hippPost3,amg_vmPFC3,amg_hippAnt3,amg_vmPFCant3,hippAnt_vmPFC3,hippPost_vmPFC3,hippAnt_vmPFCant3,hippPost_vmPFCant3 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+KPE1419,1,0.0036258553402106044,0.0528591870570849,0.06939124975750201,-0.006829586775104861,-0.02569043359600344,0.044546100541345564,0.04609722373233334,-0.0023369615005843884 +KPE1464,1,0.04806805840324151,-0.03239020039064658,0.09850603539819947,-0.038835480521363645,0.03405283814450632,0.048851588082448855,-0.027947102250112578,0.0035074171712190785 +KPE1499,1,0.05483378578821521,0.07696981219077607,0.09746691257502031,0.03128487392131203,-0.017766276325337563,-0.01585928865281165,-0.06048632564544126,-0.027546581889462855 +KPE1561,0,0.05345221366477514,-0.025221320959006914,-0.0527394917749223,0.01781712681712585,-0.016542361316053463,0.11321437991748697,0.05629009008384234,-0.10033288532404354 +KPE1573,1,0.03821380698486875,0.01276507367712218,0.18403094642752552,-0.007282785104962499,0.010903278517998216,0.029609143525561956,-0.049703156834527425,0.05010911650466096 +KPE1578,0,0.026654127370215837,0.03643057083916986,0.057153750972754394,-0.022088845548162206,0.04262897869688118,0.026295366142924423,0.0004066315024179639,0.06778462966482993 +KPE1612,0,-0.08030260955791109,0.06399081466762871,0.07786981377254514,-0.029942361966344012,-0.06418203366500524,-0.003434054722786679,0.019017704935631142,0.015226819784463835 diff --git a/rs/changeCorrelation.png b/rs/changeCorrelation.png new file mode 100644 index 0000000..89632c2 Binary files /dev/null and b/rs/changeCorrelation.png differ diff --git a/rs/difumo_extract_timeline.py b/rs/difumo_extract_timeline.py new file mode 100644 index 0000000..1d19e16 --- /dev/null +++ b/rs/difumo_extract_timeline.py @@ -0,0 +1,112 @@ +# %% +''' +@author: Or Duek +@date: Jul 16 2020 + +This is a sciprt that uses the nee DiFuMo dictionary +atlas (https://www.sciencedirect.com/science/article/pii/S1053811920306121#appsec7) + +In this file we will create a task based +''' +# %% import libraries +import pandas as pd +from nilearn.input_data import NiftiMapsMasker +from nilearn import connectome +from nilearn import datasets +import numpy as np +import nilearn.plotting +from sklearn.model_selection import StratifiedShuffleSplit +import os +import glob +from nilearn import connectome +import seaborn as sns +# %% Set output folder +output_dir = '/gpfs/gibbs/pi/levy_ifat/Or/kpe/results/resting' +# set session +ses= '3' # session is a string +# %% Functions +# extract RS data and create vector for each subject +def removeVars (confoundFile): + # this method takes the csv regressors file (from fmriPrep) and chooses a few to confound. You can change those few + import pandas as pd + confound = pd.read_csv(confoundFile,sep="\t", na_values="n/a") + finalConf = confound[['csf', 'white_matter', 'framewise_displacement', + 'a_comp_cor_00', 'a_comp_cor_01','a_comp_cor_02', 'a_comp_cor_03', + 'a_comp_cor_04', 'a_comp_cor_05', 'trans_x', 'trans_y', 'trans_z', + 'rot_x', 'rot_y', 'rot_z']] # can add 'global_signal' also ,, + # + # change NaN of FD to zero + finalConf = np.array(finalConf.fillna(0.0)) + return finalConf + + +# %% functional files + +func_template = '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-{sub}/ses-{session}/func/sub-{sub}_ses-{session}_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz' +confound_template = '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-{sub}/ses-{session}/func/sub-{sub}_ses-{session}_task-rest_desc-confounds_regressors.tsv' + +# get subject list +# from bids import BIDSLayout +# folder = '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/' +# layout = BIDSLayout(folder, validate=False) +# subject_list = layout.get_subjects() +# %% +# create a mean mask of all subjects +# load mask of brain + + +brainmasks = glob.glob('/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-*/ses-%s/func/sub-*_ses-%s_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz' %(ses,ses)) +print(brainmasks) +# %matplotlib inline +#for mask in brainmasks: + # nilearn.plotting.plot_roi(mask) + +mean_mask = nilearn.image.mean_img(brainmasks) +#nilearn.plotting.plot_stat_map(mean_mask) +group_mask = nilearn.image.math_img("a>=0.98", a=mean_mask) +#nilearn.plotting.plot_roi(group_mask) + +# %% fetch atlas +maps_img = '/gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz' +labels = pd.read_csv('/gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/labels_256_dictionary.csv') +#coords = nilearn.plotting.find_parcellation_cut_coords(labels_img=maps_img) +coords = nilearn.plotting.find_probabilistic_atlas_cut_coords(maps_img) +# generate time series +# +mask_params = { 'mask_img': group_mask, + 'detrend': True, 'standardize': True, + 'high_pass': 0.01, 'low_pass': 0.1, 't_r': 1, + 'smoothing_fwhm': 6., + 'verbose': 5} + +masker = NiftiMapsMasker(maps_img=maps_img, **mask_params) + +# %% +subject_list = ['1587'] + +# %% Generate npy files of timeseries for each subject per session +# we will use it later on, stratify to scripts etc. +# build a specific folder +try: + os.makedirs(output_dir) +except: + print('Folder already exist') + +subject_ts = [] +for sub in subject_list: + print(f' Analysing subject {sub}') + subject = sub + func = func_template.format(sub=subject, session=ses) + confound = confound_template.format(sub=subject, session=ses) + try: + signals = masker.fit_transform(imgs=func, confounds=removeVars(confound)) + save = np.save(output_dir + 'sub-' + subject + '_ses-' + ses, signals) + subject_ts.append(signals) + except: + print(f'Subject {sub} has no data') + + + + + +# %% diff --git a/rs/difumo_timeseries.py b/rs/difumo_timeseries.py new file mode 100644 index 0000000..758f787 --- /dev/null +++ b/rs/difumo_timeseries.py @@ -0,0 +1,340 @@ +# %% +''' +@author: Or Duek +@date: Jul 16 2020 + +This is a sciprt that uses the nee DiFuMo dictionary +atlas (https://www.sciencedirect.com/science/article/pii/S1053811920306121#appsec7) + +In this file we will create a task based +''' +# %% +# %config Completer.use_jedi = False + +# %% import libraries +import pandas as pd +from nilearn.input_data import NiftiMapsMasker + +from nilearn import datasets +import numpy as np +import nilearn.plotting +from sklearn.model_selection import StratifiedShuffleSplit +import os +import glob +from nilearn import connectome +import seaborn as sns +import matplotlib.pyplot as plt +import statsmodels.api as sm +# %% Set output folder +## condition labels (ketamine , midazolam) +# read file +medication_cond = pd.read_csv('/home/oad4/kpe_task/task_based_analysis/kpe_sub_condition.csv') +# remove 1315 (OCD), also remove for 2nd session remove 1578 +medication_cond1 = medication_cond[medication_cond.scr_id!='KPE1315'] # for 1st session +medication_cond2 = medication_cond[(medication_cond.scr_id!='KPE1315') & + (medication_cond.scr_id!='KPE1578')] # for 2nd session +medication_cond3 = medication_cond[(medication_cond.scr_id!='KPE1315') & + (medication_cond.scr_id!='KPE1253') & (medication_cond.scr_id!='KPE1468') & + (medication_cond.scr_id!='KPE1480') & (medication_cond.scr_id!='KPE1587') + ] # for 3rd session + +subject_list1 = np.array(medication_cond1.scr_id) +subject_list2 = np.array(medication_cond2.scr_id) +subject_list3 = np.array(medication_cond3.scr_id) +condition_label1 = np.array(medication_cond1.med_cond) +condition_label2 = np.array(medication_cond2.med_cond) +condition_label3 = np.array(medication_cond3.med_cond) +#group_label1 = list(map(int, condition_label)) + +# %% +medication_cond3 + +# %% +len(subject_list3) +#print(condition_label2) + +# %% fetch atlas +maps_img = '/gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz' +labels = pd.read_csv('/gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/labels_256_dictionary.csv') +#coords = nilearn.plotting.find_parcellation_cut_coords(labels_img=maps_img) +coords = nilearn.plotting.find_probabilistic_atlas_cut_coords(maps_img) +# plot atlas (only if we want) +nilearn.plotting.plot_prob_atlas(maps_img, draw_cross=False) +# %% read files and stratify to relevant script +# method to generate subject array of timeseries +def pooledTS(subject_list, ses): + rs_template = '/gpfs/gibbs/pi/levy_ifat/Or/kpe/results/restingsub-{sub}_ses-{ses}.npy' + sub_ts = [] + for sub in subject_list: + subject = sub.split('KPE')[1] + + # load the npy file (timeseries) + ts = np.load(rs_template.format(sub=subject, ses=ses), allow_pickle=True) + ts_script = ts[5:,:] # remove first five trs + sub_ts.append(ts_script) + return sub_ts +# %% +from nilearn import connectome +connectome = connectome.ConnectivityMeasure( + kind='partial correlation', vectorize=False) + +mat_ses1 = connectome.fit_transform(pooledTS(subject_list1, '1')) + + +# %% +mat_ses1.shape + +# %% plot mean matrix +# %matplotlib inline +nilearn.plotting.plot_matrix(connectome.mean_, + colorbar=True, labels= range(256), reorder='average') + +# %% lets run ses 2 +mat_ses2 = connectome.fit_transform(pooledTS(subject_list2, '2')) +# %matplotlib inline +nilearn.plotting.plot_matrix(connectome.mean_, + colorbar=True, labels= range(256), reorder='average') + +# %% +mat_ses3 = connectome.fit_transform(pooledTS(subject_list3, '3')) + +# %% +# fisher-z transformation +mat_ses1 = np.arctan(mat_ses1) +mat_ses2 = np.arctan(mat_ses2) +mat_ses3 = np.arctan(mat_ses3) + +# %% +## Generate matrix of just ROIs (amygdala, hippocampus, vmpfc and caudate) +# get index of each ROI + +labels_list = list(labels.Difumo_names) +amg = labels_list.index('Amygdala') +hippo_post = labels_list.index('Hippocampus posterior') +hippo_ant = labels_list.index('Hippocampus anterior') +vmPFC_ant = labels_list.index('Ventromedial prefrontal cortex anterior') +vmPFC = labels_list.index('Ventromedial prefrontal cortex') +index_list = np.array([amg, hippo_post, hippo_ant, vmPFC_ant, vmPFC])#, caudate_ant, caudate_inf, caudate_sup]) + +# set matrix for specific ROIs (as defined above) +mat1ROI = mat_ses1[: ,index_list,:] +mat1ROI = mat1ROI[:,:,index_list] + +mat2ROI = mat_ses2[: ,index_list,:] +mat2ROI = mat2ROI[:,:,index_list] + +mat3ROI = mat_ses3[: ,index_list,:] +mat3ROI = mat3ROI[:,:,index_list] + + + +# %% +mat2ROI.shape +labels = ['amygdala','hippoPost','hippoAnt','vmPFCAnt','vmPFC']#,'Ca_Ant','Ca_In','ca_sup'] +nilearn.plotting.plot_matrix((np.mean(mat2ROI, axis=0)), + colorbar=True, labels= labels, reorder='average') + +nilearn.plotting.plot_matrix((np.mean(mat1ROI, axis=0)), + colorbar=True, labels= labels, reorder='average') + +# %% +# show groups +ketSes1 = mat1ROI[condition_label1==1] +midSes1 = mat1ROI[condition_label1==0] + +ketSes2 = mat2ROI[condition_label2==1] +midSes2 = mat2ROI[condition_label2==0] + +ketSes3 = mat3ROI[condition_label3==1] +midSes3 = mat3ROI[condition_label3==0] + + + +# %% +midSes3.shape + +# %% +## First session +sns.heatmap(np.mean(ketSes1, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Ketamine") +plt.show() + +sns.heatmap(np.mean(midSes1, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Midazolam") + +# %% +sns.heatmap(np.mean(ketSes2, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Ketamine") +plt.show() + +sns.heatmap(np.mean(midSes2, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Midazolam") + + +# %% +sns.heatmap(np.mean(ketSes3, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Ketamine") +plt.show() + +sns.heatmap(np.mean(midSes3, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Midazolam") + +# %% +import scipy +t, p = scipy.stats.ttest_ind(ketSes3, midSes3) +tArr = np.array(t) + +thr = 0.05 +tArr[p>thr] = 0 +sns.heatmap(tArr,xticklabels = labels, yticklabels = labels, cmap='coolwarm', annot=True) + +# %% +tArr + +# %% +# run simple t test to show whats going on +t, p = scipy.stats.ttest_ind(ketSes2, midSes2) +tArr = np.array(t) +tArr[p>thr] = 0 +sns.heatmap(tArr, xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) + +# %% +# create delta arrays +ketDelta = np.subtract(ketSes2, ketSes1) +# removing 1578 (last one) from midazolam group +midDelta = np.subtract(midSes2, midSes1[0:11]) +sns.heatmap(np.mean(ketDelta, axis=0), + cmap='coolwarm', xticklabels=labels, + yticklabels=labels, annot=True, vmin = -1, vmax = 1) +plt.show() +sns.heatmap(np.mean(midDelta, axis=0), cmap='coolwarm', + xticklabels=labels, yticklabels=labels, annot=True, vmin=-1, vmax=1) +plt.show() + + +# %% +# create delta arrays 3 and one - so need to make everything like 3 for the midazolam group (they have only 9) +mat_sesM1 = connectome.fit_transform(pooledTS(subject_list3, '1')) +mat_sesM1 = np.arctan(mat_sesM1) +mat1ROIM = mat_sesM1[: ,index_list,:] +mat1ROIM = mat1ROIM[:,:,index_list] +midSes1M = mat1ROIM[condition_label3==0] + + +ketDelta = np.subtract(ketSes3, ketSes1) +# removing 1578 (last one) from midazolam group +midDelta = np.subtract(midSes3, midSes1M) +sns.heatmap(np.mean(ketDelta, axis=0), + cmap='coolwarm', xticklabels=labels, + yticklabels=labels, annot=True, vmin = -1, vmax = 1) +plt.show() +sns.heatmap(np.mean(midDelta, axis=0), cmap='coolwarm', + xticklabels=labels, yticklabels=labels, annot=True, vmin=-1, vmax=1) +plt.show() + + +# %% +import mne + +t, p = scipy.stats.ttest_ind(ketDelta, midDelta) +tArr = np.array(t) +# vectorize the p to include only the actual +pvec = np.concatenate(np.tril(p)) +print(pvec) +fdr = mne.stats.fdr_correction(pvec, alpha=0.8, method='indep') +print(fdr) +tArr[fdr[1]>.05] = 0 +#print(tArr) +sns.heatmap(tArr, xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) + +# %% +# lets run NBS +ketDeltaReshape = np.moveaxis(np.array(ketDelta),0,-1) +midDeltaReshape = np.moveaxis(np.array(midDelta),0,-1) + +ketSes2_reshape = np.moveaxis(np.array(ketSes2),0,-1) +midSes2_reshape = np.moveaxis(np.array(midSes2),0,-1) + +ketSes3_reshape = np.moveaxis(np.array(ketSes3),0,-1) +midSes3_reshape = np.moveaxis(np.array(midSes3),0,-1) +print(ketDeltaReshape.shape) +print(midDeltaReshape.shape) + +# difference between the sessions +mat1ROI_reshape = np.moveaxis(np.array(mat1ROI), 0, -1) +mat3ROI_reshape = np.moveaxis(np.array(mat3ROI), 0, -1) +mat2ROI_reshape = np.moveaxis(np.array(mat2ROI), 0, -1) + +from bct import nbs + +# we compare ket1 and ket3 +pval, adj, _ = nbs.nbs_bct(mat1ROI_reshape, mat2ROI_reshape, thresh=1.5, tail='both',k=1000, + paired=True, verbose = False) +print(pval) + +# %% +# ok lets threshold using adjacency +#tTresh = t[np.tril(adj)] +tTresh = t* adj +#tTresh[np.triu(tTresh)] = t +sns.heatmap(tTresh, xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) +plt.show() +sns.heatmap(np.mean(ketDelta, axis=0), xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) +plt.show() +sns.heatmap(np.mean(midDelta, axis=0), xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) + +# %% +labels + +# %% +# built data frame for each session +df_ses1 = pd.DataFrame( + {'subject': subject_list1, 'group': condition_label1, 'amg_hippPost1': mat1ROI[:,0,1], 'amg_vmPFC1': mat1ROI[:,0,4], 'amg_hippAnt1': mat1ROI[:,0,2], + 'amg_vmPFCant1': mat1ROI[:,0,3], 'hippAnt_vmPFC1': mat1ROI[:,2,4], 'hippPost_vmPFC1': mat1ROI[:,1,4], + 'hippAnt_vmPFCant1': mat1ROI[:,2,3], 'hippPost_vmPFCant1': mat1ROI[:,1,3]} +) + +df_ses1.to_csv('RS_conn_ses1.csv', index=False) + +# %% +df_ses1 + +# %% +# built data frame for each session +df_ses2 = pd.DataFrame( + {'subject': subject_list2, 'group': condition_label2, 'amg_hippPost2': mat2ROI[:,0,1], + 'amg_vmPFC2': mat2ROI[:,0,4], 'amg_hippAnt2': mat2ROI[:,0,2], + 'amg_vmPFCant2': mat2ROI[:,0,3], 'hippAnt_vmPFC2': mat2ROI[:,2,4], 'hippPost_vmPFC2': mat2ROI[:,1,4], + 'hippAnt_vmPFCant2': mat2ROI[:,2,3], 'hippPost_vmPFCant2': mat2ROI[:,1,3]} +) + +df_ses2.to_csv('RS_conn_ses2.csv', index=False) + +# %% +# built data frame for each session +df_ses3 = pd.DataFrame( + {'subject': subject_list3, 'group': condition_label3, 'amg_hippPost3': mat3ROI[:,0,1], + 'amg_vmPFC3': mat3ROI[:,0,4], 'amg_hippAnt3': mat3ROI[:,0,2], + 'amg_vmPFCant3': mat3ROI[:,0,3], 'hippAnt_vmPFC3': mat3ROI[:,2,4], 'hippPost_vmPFC3': mat3ROI[:,1,4], + 'hippAnt_vmPFCant3': mat3ROI[:,2,3], 'hippPost_vmPFCant3': mat3ROI[:,1,3]} +) + +df_ses3.to_csv('RS_conn_ses3.csv', index=False) + +# %% +# combine all three +dfAll = pd.merge(df_ses1, df_ses2, how='left') +dfAll = pd.merge(dfAll, df_ses3, how= 'left') +dfAll.to_csv('RS_conn_3Sessions.csv', index=False) diff --git a/rs/extractTS_ses2.err b/rs/extractTS_ses2.err new file mode 100644 index 0000000..e3229c6 --- /dev/null +++ b/rs/extractTS_ses2.err @@ -0,0 +1,28 @@ + +CommandNotFoundError: Your shell has not been properly configured to use 'conda deactivate'. +To initialize your shell, run + + $ conda init + +Currently supported shells are: + - bash + - fish + - tcsh + - xonsh + - zsh + - powershell + +See 'conda init --help' for more information and options. + +IMPORTANT: You may need to close and restart your shell after running 'conda init'. + + +/gpfs/ysm/project/levy_ifat/oad4/conda_envs/py37_dev/lib/python3.7/site-packages/sklearn/utils/deprecation.py:143: FutureWarning: The sklearn.utils.testing module is deprecated in version 0.22 and will be removed in version 0.24. The corresponding classes / functions should instead be imported from sklearn.utils. Anything that cannot be imported from sklearn.utils is now part of the private API. + warnings.warn(message, FutureWarning) +/gpfs/ysm/project/levy_ifat/oad4/conda_envs/py37_dev/lib/python3.7/site-packages/sklearn/utils/deprecation.py:143: FutureWarning: The sklearn.datasets.base module is deprecated in version 0.22 and will be removed in version 0.24. The corresponding classes / functions should instead be imported from sklearn.datasets. Anything that cannot be imported from sklearn.datasets is now part of the private API. + warnings.warn(message, FutureWarning) +/gpfs/ysm/project/levy_ifat/oad4/conda_envs/py37_dev/lib/python3.7/site-packages/nilearn/plotting/cm.py:159: MatplotlibDeprecationWarning: +The revcmap function was deprecated in Matplotlib 3.2 and will be removed two minor releases later. Use Colormap.reversed() instead. + _cmaps_data[_cmapname_r] = _cm.revcmap(_cmapspec) +/gpfs/ysm/project/levy_ifat/oad4/conda_envs/py37_dev/lib/python3.7/site-packages/bids/layout/models.py:152: FutureWarning: The 'extension' entity currently excludes the leading dot ('.'). As of version 0.14.0, it will include the leading dot. To suppress this warning and include the leading dot, use `bids.config.set_option('extension_initial_dot', True)`. + FutureWarning) diff --git a/rs/extractTS_ses2.txt b/rs/extractTS_ses2.txt new file mode 100644 index 0000000..1f9525d --- /dev/null +++ b/rs/extractTS_ses2.txt @@ -0,0 +1,264 @@ +Running script +['/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1369/ses-3/func/sub-1369_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1351/ses-3/func/sub-1351_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1561/ses-3/func/sub-1561_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1578/ses-3/func/sub-1578_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1387/ses-3/func/sub-1387_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1499/ses-3/func/sub-1499_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1573/ses-3/func/sub-1573_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1364/ses-3/func/sub-1364_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1403/ses-3/func/sub-1403_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-008/ses-3/func/sub-008_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1343/ses-3/func/sub-1343_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1307/ses-3/func/sub-1307_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1419/ses-3/func/sub-1419_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1263/ses-3/func/sub-1263_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1322/ses-3/func/sub-1322_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1390/ses-3/func/sub-1390_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1223/ses-3/func/sub-1223_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1339/ses-3/func/sub-1339_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1293/ses-3/func/sub-1293_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1464/ses-3/func/sub-1464_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', '/gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1356/ses-3/func/sub-1356_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz'] +Folder already exist + Analysing subject 008 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +Resampling maps +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-008/ses-3/func/sub-008_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1223 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1223/ses-3/func/sub-1223_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1253 +Subject 1253 has no data + Analysing subject 1263 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1263/ses-3/func/sub-1263_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1293 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1293/ses-3/func/sub-1293_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1307 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1307/ses-3/func/sub-1307_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1315 +Subject 1315 has no data + Analysing subject 1322 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1322/ses-3/func/sub-1322_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1339 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1339/ses-3/func/sub-1339_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1343 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1343/ses-3/func/sub-1343_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1351 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1351/ses-3/func/sub-1351_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1356 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1356/ses-3/func/sub-1356_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1364 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1364/ses-3/func/sub-1364_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1369 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1369/ses-3/func/sub-1369_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1387 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1387/ses-3/func/sub-1387_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1390 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1390/ses-3/func/sub-1390_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1403 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1403/ses-3/func/sub-1403_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1419 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1419/ses-3/func/sub-1419_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1464 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1464/ses-3/func/sub-1464_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1468 +Subject 1468 has no data + Analysing subject 1480 +Subject 1480 has no data + Analysing subject 1499 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1499/ses-3/func/sub-1499_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1561 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1561/ses-3/func/sub-1561_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1573 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1573/ses-3/func/sub-1573_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals + Analysing subject 1578 +[NiftiMapsMasker.fit_transform] loading regions from /gpfs/gibbs/pi/levy_ifat/Or/DiFuMo_atlas/256/maps.nii.gz +[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image( +shape=(97, 115, 97), +affine=array([[ 2. , 0. , 0. , -96.5], + [ 0. , 2. , 0. , -132.5], + [ 0. , 0. , 2. , -78.5], + [ 0. , 0. , 0. , 1 +[NiftiMapsMasker.transform_single_imgs] Loading data from /gpfs/gibbs/pi/levy_ifat/Or/kpe/fmriprep/sub-1578/ses-3/func/sub-1578_ses-3_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz +[NiftiMapsMasker.transform_single_imgs] Smoothing images +[NiftiMapsMasker.transform_single_imgs] Extracting region signals +[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals diff --git a/rs/run_DifumoExtractTS.sh b/rs/run_DifumoExtractTS.sh new file mode 100644 index 0000000..54578f9 --- /dev/null +++ b/rs/run_DifumoExtractTS.sh @@ -0,0 +1,21 @@ +#!/bin/bash +#SBATCH --partition=general +#SBATCH --output=extractTS_ses2.txt +#SBATCH --error=extractTS_ses2.err +#SBATCH --job-name=extractTS_ses2 +#SBATCH --ntasks=1 +#SBATCH --cpus-per-task=8 +#SBATCH --mem-per-cpu=5G +#SBATCH --time=10:00:00 +#SBATCH --mail-type=ALL +#SBATCH --mail-user=or.duek@yale.edu + +echo "Running script" + + + +module load miniconda + +source activate py37_dev + +python /home/oad4/kpe_task/rs/difumo_extract_timeline.py diff --git a/task_based_analysis/.ipynb_checkpoints/Analyse_fsl-checkpoint.ipynb b/task_based_analysis/.ipynb_checkpoints/Analyse_fsl-checkpoint.ipynb index 2bfe7e4..eb9403a 100644 --- a/task_based_analysis/.ipynb_checkpoints/Analyse_fsl-checkpoint.ipynb +++ b/task_based_analysis/.ipynb_checkpoints/Analyse_fsl-checkpoint.ipynb @@ -2,91 +2,122 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 30, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/gpfs/ysm/project/levy_ifat/oad4/conda_envs/py37_dev/lib/python3.7/site-packages/sklearn/externals/joblib/__init__.py:15: DeprecationWarning: sklearn.externals.joblib is deprecated in 0.21 and will be removed in 0.23. Please import this functionality directly from joblib, which can be installed with: pip install joblib. If this warning is raised when loading pickled models, you may need to re-serialize those models with scikit-learn 0.21+.\n", - " warnings.warn(msg, category=DeprecationWarning)\n" - ] - } - ], + "outputs": [], "source": [ "from nilearn.plotting import plot_glass_brain\n", "import nilearn.plotting\n", "import glob\n", "import nibabel as nib\n", "from nilearn.image import mean_img\n", - "import nilearn.plotting as plotting" + "import nilearn.plotting as plotting\n", + "import numpy as np" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 31, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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" + "22" ] }, + "execution_count": 31, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "fig = nilearn.plotting.plot_stat_map('/home/oad4/scratch60/kpe_work/2nd_level/_cope_1/randomize/randomise_tstat1.nii.gz', alpha=0.5 )#, cut_coords=(0, 45, -7))\n", - "fig.add_contours('/home/oad4/scratch60/kpe_work/2nd_level/_cope_1/randomize/randomise_tfce_corrp_tstat1.nii.gz', levels=[0.95], colors='b')\n", - ",colorbar=True, threshold=2.2, display_mode='lyrz', black_bg=True)#, vmax=10); " + "mask_imgs = glob.glob('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-*/ses-1/func/sub-*_ses-1_task-Memory_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz')\n", + "len(mask_imgs)" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 2, "metadata": {}, "outputs": [ { - "data": { - "image/png": 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yZI3HxUyitvH7lcIYDDp6zDF9Hkndl3rvr16txvJerXrXX3y0eo+eoK/znfo78qM9MByjRo3i4osv5pprruH555//0m0PPXjMhgcPHjwclEgmk8RiWTu4z+fDp0NFo1EYdfjHLFrfnclnvEK6xxZe+Nvt1Ncrk4Btxxk//h3atavTZUsCGbNJVmh0W7WiYIlHhBTpkswUjUjx9zZ6m0KgqTnI75+4mE+2d1S92zFumPw3+petJx6LQekmXlvWQI4/SlVTLe+vO4t+vf7Y4oiRQDNtA83YWtgI+EUgVspXUgvCPj1WE5ckSWoyAvKu5yH7Oq3aat3WttpeEncoxXE1KvdETAvRx7H3uPrqq+natStLly5l0KBB/8aeBzu+pXk2ntGS6Cd6uTkz+YbrVuKGWz588+fPA8DnswmF1MQTqdjnU17VhtGo9kyq/PpNTYoqnDRJ2f+OHHq86lLHqJOrHwZ9H1YsWQBASHtpW5bKJ+84SnKPxYK61SNMJnXGtwTZh0Qenh66lZeC0lQrKnT8G2qM5eXH4GHfI3vdhfXKJcsWSEluMc/Jg1nbah/NGhTtkmuZXbqRzWXqynfB0YyYmdfyMJTqNkh2nkjYoDwX7XRbpdcKo1Esnev2UwBCrFZD1GuFV/uXfu7OLC8nnYbXXlMfxYEDoWdPPPybOPXUU1ssX3/99dx00000NytGY9H67lw/+Xnea3iJe+75FdFoKSec8C/at08TDMYJhXJRE0hNEtdVH3IRWBzto2EYKf27o9er7dNptV4YDtv2o95DkEj4WLjicMy4j3krBrGpsi0/Pf1hepVuIBJsJmw24Tq7FpwHy0pTHNlCIh3EEAajVSWMnTUlrPl0ALYNA3ssIzeYlp0BMsyH4Tg4joNDmkQiqceU0Jsqn4xgUPuX+BItzjudVg+VyDOm6de/f/Wc5aWlpVx00UXceOON/POf//zK/R088DKIevDg4RvG+vUwcSJ8qJ2hQiFVf2L06P06rIMKGzZs2O365mYYPeBjFqzvzqTJM0n0qmLRvb8lGi1i7NiZdOpUg9+vhAbD0PVKHGEyxHFSmz58IkSm9PYJ3YpTR0sbfIQYpUAs4eeuxy9g5WddAQjaCX512gMc1X01jdqkkUxrwUXvK9yBYaj/5aMSkGRehsGri05h2vxJmeO9u2QU1513L0V59aS1UGLq7VPqxAjQQE1KBBYdNutX52tlBJSoXlaKous26/O39HrZXl2fdetUhVl6KIajQTMcb+/GnLK7+/TXv/71c+sOfXzLmI2n9GRYndHIjtCtmkzvvqt8HEyzSrci+apJmpenJl847BAIqAlp2816W6UNGoaydzpOsd5Waaw1NSpsa9mSubpPpVomEk16O2XfLi5WVF6xrSoS5umH5zNHpQcOBjsBEIspvTGZDLJy5SIgSiql7O/ptLqp4lV91FEn6/MUDXW+btUYKirUGMrLZTsPXycqKl7X/4kvUAfdNkCuvicN4jvRmtFQyx9+uAiAdFqxB46Tp1tdeEo0OlvNF8NtmbPZTYh2Wq/3E38K8TmKZV6yQ4cO1uuExBbWRT0XpZk9qvTaaIvthSlMay1XGI4twM6afK44spZYws/1Z02nQ1ENv3t+EmNPLuTV121P4PiKOP10WLC+O7+a/AKxXpU89NAk6usLGDXqOTp1athzB18RqbTFn5+4gHWbOvPzSc9wfNeV+H0pDHfvvU7dVnMXYObSk5g2fxJH9VzEeSOfZntdR/784mX8/onvc913/05+6Vd3PvSwL/H1ZBA9cN2AD0AsX34Hy5ffsb+H4eFbiOXLb+WDD+7cr2OYtWAY1Q25VFz0CCcevpI+ZVu4eepDtC2s4dRTYc6c/Tq8gxrpNMydC8WFNbidN/L3v09g584CxoyZTrduOzDNz/TfFkxzCz7fJny+TVhWI5bViGG4GIaLaZr6L6X/EvqvCtOsosCsocCsIUf/BY2o+gO2bW7PRxu7ctWYlziz72K6mvV0cKIUxuMUxuMEk0mCySS+VApfKoXlOFjZ4iwUhXewuaYHKz8Zjm0Y+PTfrGUn0afjGq4a/xhtcxMc2eVTbjjrXhqbI/zxicuJ1uUScl1M9AdJK2k24LpNuG4TltWMZTVjmvWYZj3KR6Maw2jUfykMI4VppjHNND5fCp8vhW0nse0kgYBBIGAQDhcQDhewatV2Vq3aThUn6r9iqijm9ooKbv9Whrd+GSTPxhf97R0OeGbjPn3jNyMOOW11q5iLxYsVoxEOaycjfUY+n5KWbVtseA26rcPna9LbKMain6m2Ffv0fGeR/k9pd3l5ipmoq1PHisfn6L6UT0Zurtquj19poO196phycX3aQ/oTdrY4N7+/WNs1C3CkCmNa/EZUu2LFc2okCaUtH3nkULWvtr0ntD9ARcWjAJSXX4CHr46Kig36v8NV01azGEJaxNPQ8IxeaNRtvm7VXFy+XPk/iO1a7ObSmqb2rPfpapqG9so3Q7ofbY8PVtLQsALXbca2V5FOq7GJj5Hrmhlb9fvvqxTQjpPQv6kBt0Fpp1H9Ij/86KMBaNDrE5moLTX2bfr52qYdSEI0U5+28NtJOrbflrlOfSJR7p36EFc8NJVxJxdy+YWPcliXjdTQLjNH/2cPnv4elNvCv/4Fkyflc/MdPwIjzfHHP0bHjo173vlrgqP9ProW7/iP9j914IPsbCzjibcux2clObK3srW5jkHb/MrMfAfo1WEjvzr7H9z49Pe4+eFLqPjevQRzPYbjwMTXE43iMRsePHjYK+TnNdAcDzJt3ogW64siUc4YPp94ymbJin8vDbSHLCZOhCOH3EoovJUTTniOLl12YJrqz3HqcJw6clM71Z+7lVx3K7Zdrf9cbNvFNO0Wf0ordQgYSQJGkhzLIsey8Pt8+H0+kmaQpBkkBjRrliKeStGcSGDHYtixGJFEgkgiQb7+CyeThJNJcvQfjgOOg89s5sKjbyQ/XM37a0fS7Lo0uy4lBTt4d81Q3v+0G7XpNFHHIeo4HNZhI1ef/jjba4r5cH03cF1wXZKAY1lYloXPF8fni2NZTVhWE65b3+JPmRIbMIw4hhEnx5ckx5fEttPYdhqfL4HPl8CyklhWEp/PwedzCIdLCYdLWbRoI4sWbUSlSphIPV2pz4SDe1A4CJiN/6S64ed9MxSjMX++cuQJh5Um5vcr7a+wUPkuiFeyZYl0LNpjSrdVersdFFo6tMtUWlyJtpkXaQ10qKG0ufnGWr2PKuJjGGo/x9kEQCCgGJKuprqMJYayd4d1f82t6iWbZlr3J2OUcIMQIvc5jqFbNf5USm2bSChmZtUqFVUTi6nzOvLINrqPbgBUVGzWy6pmwt4kKjvYqhvuS4gPDK0TQ2+XvBViO/8Mcb5bvPhtAFxX3QvLUmyTOPOZZr7+PaB/V/fattN6WbWGIZR0XG+v+necZkzTwXWVv1E6rXw3CizN0AGVaTWXEwnFSCST6iUQ1PPH0g6FDdqxbuaSJQBUuzpfgdtAPBGhsao/VXWHEfLX0qfzK6DnbJdhxzLk6MVs2NyZR147hdWVJeRFGihAORW+Mn84vTpt5JQxMzUf6JDQfkYVFbcAkKN/ucZjOr4Qbdsupm3bxRQVHbm/h/Ifwe+LEwnVZ6JjAC4eex93vXAVd027nCE9lxDwuYwfMptubetpk6/83FJp64u69LDfsSdmI/Qlv2VxwJtRPHwzOJiqG3r4+hGL5zH33Zuoa+iKJL7bVt2fkYP+lBGSLcvhrLNexrZTLFw8uMX+/buv56fnPE31LpkuPew9xFwcCKiPrmFIkqqWpoV0Wt2LgI4MQQucfr983CXkOaC3V8Jk2ioBoFo7zAd9SgA29HYNbiPNOhw2Go9T39xM+7g6dlAfSwqpSfRITI8FUYx067guKdelNilpz6s579Q/8cLs77NyY2/qmwopiOygU+FccgNV5IaaeGrOGLp33kTbohr8hoHp82ECRQGlfFXHVV+uK5q0Hps2gRdZ6jxMbQYMaEWgOtW06xAz+wUCavvCwhK9Xq5fdwCe0Pfju55gzJ5roxxkwkZFxRP6vzN1q05u2TJVMrekRKXmzcZXS2iTOgWJ0Zb9RCsUL32xbxcZSXK1lhfUzIOkNZD8njGJEnDVxNzFB0r35det6qfGVRM6Xz+Ecd1W6/63Gfl6jBHdr+yfwjAMoIbWSWocR1dl1D4ntq2iCsT3xLbFp0NliIxGVUjXUUdJtlOVabSiQtnw9zYL6retumFFxQL9n3rJkKsZtUyEiSQLUvNu2TLlt5NO1+E41fp/9cISIisYlDwuqi/LEpauSC/n6FayHao56rqSM0E+MOLHk8YwXFwXDMPIMCXN2kEpZDYTdNUxJd+AMF+W2dxifVAnICgwTWKJMB99OI54IsyGbQNoirbh0uMr6NF2BW+uPpVXVlyCjcmEIbeyZsE7ANS5xZSVLaNjRzX3hw1TIYQhmqgkG83Sjh0EUc/OrAXD2F5dnEkrMvsVFVE1YNRwrrwSOkslAQ8HPVwXUmn7c+sj4Qa+f/qfSaZ8/Oq+O3B1wGzIH+c3372f8scv47cPX8xN378HX85XD7P08HViT9EohXvVywEjbHg4MPDtrm747UEsEebJWdexrbobfl8zATvKd47/Az1KVgBwbE+VxOyVFZfAIhg86A8ZhmNv4Tjw8MsTmLNoKKFADNNomeTptUXw9NMqiqVLl933cahDNOi3Fyih1wwr01M6LbR1S2WqXitRSVGUTHGMVx94KSkvVVDT6Vz9u1Je/H5RdFo6ITtOgpROoOUkkzjxOLU6kZYET7v6mD5tigvqVpJ4JS0fc1adx47azhzWZSExrXQlNQNiui5CyKSdNFHNfLQv3MgPxj/BH5+7lPWby+jT62NsyyIJBEJ63LqvVEqNKWKpjtra6ncxXUeFfdHH9CWVsO2k6/R1EcVPKQ+uq0yeq1Yps2K/fioA4aOMGd/DIZNno6Jilvon97sAvPfmewCELfWwFRSozAA5OcJkqM0lM17L+iLZZde1dSvJbHRWO9PMJo/RrWQtEEZje8Zfoo1uRXLz6z5VvgyJIKnREzmZUuxCUE/8lFmgjx3WrbwIJDFPvWY2YmRT4wT0b+IzENbnrc7DttV18ftrdKs1WJ20ZvFidT2PPHKs3l/n4/itWir/JbvFoV7dMOvLInVqhLHo0HK5oWU652XLlH+O46jII0PPGdP0IdEn6XRCr1N72rZiOnw+NU8sq0z9XqzvranvdXXLVKHZhEvq92wCxiCK5vXjOO2QuCnxT0qZ9ViuRC006TG4uicd4aI/MmG/n1g8xDOzr2FHTWd+cuL/MbjTMnL0nM/VSaKijkO/gW9g2TYvLbmA+sQfyM/dhi9nB716vUw6HWXr1mE8eK/yqbI1C9O2RJ17Emioz2PVJ9258Li3uPykWbRyYWLh5vb88uGLGDIwTt9unxD3hxg5cgV/+tNZHOqorob//m/okO5M364b97zDQYD3101k3pqzOLznbIYPfBH3S+IPEslAi2W/L/kFW3rY/3Ag3bTnzfaA/S5seDgw4FU3/HYgFg/x+GvXsqOmE9874S4Gd1r2pduP6jMdn5lk1prxNDYX0RgdRUNDOwoLV7Fs2X8R8Nfjs2IZUbmmSX1EXJR4dOYJs7h85FufEzQAepVt5bcXPcxt005j9addqGnI45NP2vHzn0P79l/raR9QqK6Gk0+GxYvBZ36X7wwtJ9JDOxH7RKGRtOOylxIaozrUPaFNubY20dq2uu6BgPrAi7lZzMlZ068wGnIcrfk7DinNBsRcl0bXZbM2vQlrIIK2Y7R0YpekdB/vGEJp/kbGHPeYMjGL9K23S6TTuKTp3GYdM5eeTNe2H9O380o2NpRw94yzCQejFJdsQT5rTUDKVucrqQ2SSaXYFWjhpECbmU0tmddotqReszJNSTWGPM3K2T6lRCSQ827Q/avrt2DB+wAMG6YYjl3T9H9r4SBZIL4S9ouwoezkOs1uWNH1i1ar3Bb+iNbADJlkksNfTQrDaFlAyHWF5MvVv/v0enEoEvu3av2GkXlYJOdAs56odbqvRFr5VqRSornKgys5/4P6d2FA1AMc1UxGMqWOHdCap6QQNk1hYePSoO8AACAASURBVMQJTMaWJOvYJQyNvBxEA5CoGoloUMfy+YTZEEZHtUt0tEEqpTTNYcMUQ1Rxm/q9/GfsFodadUPxWSGsfVaib7faQtI9K8bogw8+AMBxxEap5oRpig+NLJs4jqIWJYpE9pHqlZkXe4m+t910l4qUwq0S6kLmtES6tEw1nU6ncV0X1zVIpXz4fMKYyXH8iOdRrrkDxzFZuWwyVfVlGfbN0i/+uvoO1DSWcO1JdzOk8weU6Tkt5VYCkhNEb19imgzvP4cpA1T23EeWTOLV5WewcePx9Gy/jO8d/XtsK0mBfsk7UqXTcajRz1e1cZS6dqjvzl9eG8vRAz5gRMct9CrbyuNX/B2AVZ925iePns/AgVVcfvlj2LYaQ3n5jzhUIILGihXwizOe477XB/PMwgrOKL2Bgvyt+3t4ADQlwnve6Avg98Uy83J3MAy46JQ7+McrP+P+V6+grGQTVfWluK7BTy94gMK8BuKeDnxgwSH7ivoK2Od3dXfVDT0c2Pj2Vjc8+JF2LF6b81+s2zCMkoKNZE006sMd8kc57aQ7GdJ5xX/U//gjniNoN7OppgOThj2Inf736O/65jCvvXc0r713NLddej99O23K/Da4y0Z+Pn4GN714OlVVhbRr99VTJB9IEEHjg2Upbjv3KUb0XEdlbD73vfI7Gpv60rlDPU2W+tA7jig8olSpPoQhyv4urXqvBgKifEj4tKik4jAvJjq5b/JuTtK2ZCf5kWoemDeVSGEV3YrVvanTB/XrVhiOtBYsRTQWESMhg9UCq7zxhQnx+xu5YNytvPb+OTQ259G5Qz0nDnuF0rYNNLtqxrqZfpVyZNvSKmUrh5ZjkrGkMoxGSI9VO0z7tN+IVt6ctJh4pJaM+j03k1hMGdcPrRn4H8IlG0XxFbDPv/y7q25o25exYsV6ACKRdwEoSGt6UE8af44U2FGtYYjNXMWMZBkLyfvZMnujYSgbfA5KWxCvC8swM85VIqxFdeiO40i4mPh7iOYoHLCrt8tqnKp1W+wnjnQhRxGCpZas1wyKfozkMW8mhOiW4muSZT3ielmug+wlfcr26lamUsKEKG06ElHXZfXqjwDo06cXABUVKm9Eebnk6cjiUKhuWFHxnv5Pz4+oLIsvjDBIitFYtuzjFr9bltpPWCnDkJeS+A7ZOI4wXerexeM6w4TT0o/I1eGGkkrAEFu205KNEqc+uddSoTOZTOO6KVzXIJ1OEghE9HbiX2JiGI04jslbWtA448jHOLHvK7gStqhp9WIt7Is/ZokeSjqknfm0cGJG1JzvmFJtWY0u/GVZTDhiJr4cZShx2qmPYyql9kt9pK7TzmiSlD525XwVfbLZMGiMZ6tv/uz+S/FZKfp1+4SzT5rJiPbbSepnpzdNuJlKxw8AMBzl2zDuIKW0zzxTMRq3nfsUx/VcR5psfqADAaFAM5dN/j/uf+4n3PHyz/jZhNvoWLxpzzsCuNCcjOAzU3veFggFmpg06kEA7KCwi1+9MuvXibVruzBj+Wg2bOnAI3PhoYegU6f9Par9AAf46i4b+1bY+KLqhhUVaWCJXpKHTT79vlbLsRbLfs1BByQsUKeKTmuhQiReKTglFkoRF5rJugY2Z36V5FVybKtV2xqta4ALMn7beu/Ebscij5Y4pjYT3GVfOabcXRE6oq1+l4+lEOAtbbHZVsYo11lSpoujZJtDqrphRcU8/Z/MG7naYqKQ6ydvDbmO4pwp16uu1XrZT16mfrLXPucLtm3V1eZWm+nCayRyW/0gx5B75pKdwbuOURAj6DQxY9ZlrN0whClHPcWUnq8A2RktRyhu1WZ6FP9SmdpyOD0trUjLM3MlPYG49cj+Irxk/6VMtz4g7W/k1MOX88HmMj6rLiaV9rF8XU/Wby7jglNe45FXx1KSX0thUXXmiWjUQsZ8PcfnV9wHQHn5ZRxMWLAArrgCxhepcPWXli7FF+wLgGFZmLaNbbWs4qpKv2edkEXRySpCwmBU6v0kTb1MuqYW22efC7vFcq4ZJWjblJXU8ePTb+eOF3/K7dN/xpUTb6d7iSpUmZTS8aKsSRVYF6rq29MY684xRzxAvc7tEfJrB3udxDDqqEkSdNW7zKf7C2u/i5BeTqsTU+enz8cvZnA9alczdU0ZZ341FsntIRNTHOfFdyWZtPX1DOlWmD91vYJB9XV4Z3qEmQtOxXFtRvZfwfvzIpxwQpDZs7+FAsfBwmzsDh99tIbSUvUJFrtsPC70njxEe5dJ/Yutg+h+jM8vt1onx8w4PGk7toSbiT/EbvvaBWIfl36cVgk6zFY0ZKY0M8YukQctWZQvOp9MdI3bcozBoGI25KEKBtVDFQiox/TTTzcAsHPnQt3j8bs9zqGKtWuVkBWLKYYslZJ7LflM1CMhoYTCaLS+zpZl6YiULDWd1M5oyaRk/tQZRPWtdGU+pKXVg3Iy/+hjOrqfpB5rQvdlYhhGJrdMNiIL5s47m7WfDGHKsCcZ0/81nJjM5ZbzKFOnpdUcdDOhhZqGdzJhXy32NyWSxtL7S6ufY19I7ZdDAEtCHnVyKDORwAROL7uO08tgXaKUB967hapoGY3NYe55YTKlBTX8aupDBP2HZnSC37/nbfY3SvMrMwLHbc/9glTapnPJRq6f8kcsM2vWmbbgDN5fewyNzatxXIuh/Z5iYM/pRDMVqg9O1NaWMnPBjynO/4S7L/8XkVCcbZ+VcdUzl3HCCSpUu2PH/T3KbxAHA7OxO9TXpyksLMyUeZc3biLReigioYskL6mZ1UtR5PIC/ZKM6LZICwihVh92CXNtNM2MDTKr9Qq13jJZl2GIY6hsJ33KB0kyK0pIK3p77X2tS4KLDTNHbxDRbZPr4gK1JDMJnbJfIHE+FDOKeJWLLVI+IkKpl+ixhFrsJ9S83x/TY96u16vj1NTUU1h4YNGX/wmyZhNJKy5sgyrr/tFHSpuMx8XpV5w5xZtf7Mnq+lmWEoalrLukCJf7ZBjGLvOgpdNuSmctFKHDr+3uaEY6rYWIdFoSziX1/qKFqe2bm0XoUM6hpmni8wUzwog8E65bQySgzmd7QyGNyRQJfQwxLkak7oU4Rctzoefmdi0YVOr9CrWi3EUTahG/VgZkemqiKKmtT5u1wFWphbKUz6CdNtl0CutiiFF93s3qvOuMSr5z+O3cM/9PHNfnr7iRoYw57h2Mgjp2kn06Rexop5mfbZqblDTo5eX/w8GAVDLB8nkLSZ6ilp2cHBJa2E0YAaJGGMOV51fNX3Eql9bVIc7inCz8qAjLoqT4XZ38Tw6u73cTLX1AQpoxCBkGIZ1V03RdOrZp4Odn/IUbn/yl3t4i129hGBbV8QTPvPMd5nxwAr06LmNTZT1+u5lu/V+ninzChnC5kmhOzNLav0LfWcOnlnXyT1IS9eJm3/FhPT45jwxPKwkU9XKGB7fUu8zS72wxcWdNnuhleX+6+vpJJtZGotHuOK7NuKMfIRJSc/i0Tpvxf+c+Ln/0AkaPDn67BI6DgdmoqFCe/ZQcztqo0igLPv321ds4kDF1qrJ/DxlyjF4TBRRterC8xD3AiEEvEk+EeWuVyq8ypf99uw03PdBg6/wxeeHtjJ04fT+PZt9h40ZIp63PRWrU1KsPc7YuzoGDjzb3IpEKMLDLSn5y6v2Z+fTOh8cy54MTGNH/VcYOe4q/T9/25R0ddFD3or6phF1rghzRaTN/u+BRfvDMZUyeDAsXfsHuhxoO5GiUiopp+r9RAKxxVlOQVC6agYCk2xbaVkmi6bT2EnbETi0pnFUb1pJ6rjYfiO1YbNG5jtNifUzT3WK6CGip2W8YZB9r0Z0kbFacA4UeF6m4paOoMB+WJanTtUZgitab0megBKtqLRaKYSig+8lXByFKE9UZs5HaN0drMH7NpqSk1YxFMhMSKw6Mrc0rkhmwUY/N1WOt1OvVdS0sVAkN5s9XdvHhw0cjGomwBeXlR3OgoqLiX/o/mQliq1ba70cfKTohHpd7rNYHAhI+quaVaUryNPSyXEcpoia5BaSsexjDECdSrU3qBGvRaFQfU/VtBdW8MqWWBKKdqnsgWRGlHzHtxOPCtIEyoZhYlh/DENZPxuJQ56QZNOQxnHSSt1ZPIJZKMeaIB4lrs5C4VEhKffFg8ennZpse2zptRpEXQ5Xe/jA9dHm+JFx8i95/q27F+TpoGKT1NQxotqNA54Ao1esbfT6iOmog6POxeL7ytxElaujw4S2W5Qnpp98Nq7RD4QM6F8IlB6jj6MaNcMIJELSTnHX4cl5YpML8VyaH8PzM75OXt4MOHTaTTkcQX42sKVe/1zJh9LEWyzm6NkieJG0zWuadEAlBRByf0zITpNxPk6yJMBAIMHf5MB6ZPYVBXVdz/eRH8fssoinVy+aaEmwrwdDBj1GdhoQjh8rRreTlUD/4fGKCFNOkGlOuzpURklT6eiwyVpssP5nxZNPnJV8JeZdLlKOY5RMJMX/KO1xmkYxBuJLWUTnQocM6ivI38/K7V+BL/oaOJSvIGTqULsBxnTZzySXwj3/w7YHLwZtnw4MHD18/DANGDnoUgAVrJuBicPaQR/aa4dhY05nb5vw3KSdATqCOc466le551XveEYgn/cxeeSpzPxyHaTiMPWIa3xn4xl6PvS7aJlOW5lDDOedAVRX84cJHOKzdDqo3w8aa3jw9/1pCoQYmTPg/QqHP1xPZX5i7fBj/mKEEjZ9Pfgi/bzcRJoZ7UDBn/wn8/hhnjf09/3z1Ol5YUM6kYS2zKds2xGLw8cdw2N6VnDq4cSAzG1IEbNlOZScvsouwtyvRyBdUGrRIluIPIeF/WV8FEaV0mm4tofp0K35WIsFnPB1EktXLEodt7RLuGpOnJOOLoVoplCYhsBKLbhjiHaOjTCzVu20H9bIwG8KASBIvNaoqFM0oBiRx4C8wDFyULhPUumZM2+vDMm45r1YaSpQdADQb4rMvTIfS+tJp0Z7lFgvzUa/H1qzPQb3h8/IO19v1JBs/c+BiRiadunJwDfEWAM1aF/roI6XxJRJSDE2dr98vDIa63pKHIOszI/daWCq5W+pei+3XcazMPJAQVL9fHEXVtvG48h+xGpUGHgxKuLJmD3zaWdMVh2J95LRoZbrCZ8DSPiIutp3O3LvsbPCT0Pesyayk9+BnSBomC1efSsq2GX3U44R1WftMsUHdiuZYYxisa+xAY7yY7mVz2Fo1gPve+g3Rk39P26KNmQRdxVIfQz9nO9Np4kk/f531Uzbu6EeH4vVU1bfls6quGQ1WWBVxahJNtswwaNt2B92K1zJ75fc4M6+BPh3fp0nn5ZGQ2QGa4ZBgnnW6bafPZiMSzq0iqMrLf8CBhE8/he98BwZ1VObJFdGBPD3/l4SCDZw64WFycgwcR80RSdqXNavI1VNReIWa0Yjoa5hvBmiKhYkk1LW1U8LItXwvis+agUNOKJbx1RHfHclt8fbSITwy4wwGdV/Db854FL/PRQg5SUsghSZrMqGqal4L0yuRHcJ0SBi5sA95mp0pcAPEE35yxElb92ZaSYL+JBaf99UQHw1562XebpqV8Wl2sVaPoTEh/nfC9MZatK7b8l3vOPoZDVUzfuzvmf7KtbywoJyBvZ/krG7K/2tq81084LuE0aPDzJnzLRA40hycDqIePHjYtzAMGD7kcQCWfjiepR+enPnNMpOMHfovzhzw2uf221Gv6sQM7PkUffo+yZx3buTJN37BuWN+R8c2W77weM8tPJ/PdvZh8og76FG2mrte/P2XZpHcFT4zzY9P/D13zv5vnp33891uU/h2Pdd89wn8HQ4+34C1a6G2NhuFsuKzMp5+8zxyAnVMHPdHAjk5X97BlyCRtPnLC1NZ+Umvf2u/4wYu5sIJz2WUI8H2qmIeeVkJGv991mP4d5MzI5U22V7V+d8uytca6z7pweuzx7Np++fz0ltmissmvsgJR+zfytPhUD0TRv6Gl9/8Db9/8lxOu/ZP+H1p+pZW8trUhznlmSs47zzQMvGhiwPRQbSiQmnbC1cp9iKoJV0r6WKElF7iujv01hJFkQ0lVK1EX2SsykDWa140KnMXiRyy3smSbSKj74vXvV6OGgZNma3k9MU+KsyFnJEk6xJ5urX9VJIwicYqRbrEo1wdNaE1AFdrKRIhUKQ2IkQ2w8IOYWBanadoicJ4CLMTdZX2LMnAJLGY5PyXcuaSDCzXVR+NtCO2X3WykYjS4NfUbqX3gN6q803qXlVUrASgvLw/BwrmZ7I3KI2+OZO2TZ1/IqHml2UJ6yCl1tX5i+3bcdRMcV2JSMrVy8IbKpFe/DNkDjhOIMMwyByWF7B8WJJJiSrZpsci4bV+vdzy3oo2KoxHMqnrOdgupuliGC6mGWuV5h7Ah2FE9L76/vt8DD16HsVto9TXFyFcRt3Ojkx//xxcx2JEn9n4NZ0yc92xvP7Bd2jbdjlOXoqQHeD4kXfy9ls/5ok3fkHqpFspyttCnRXHMh0KJVQ2mWRnfQllhevoXrCKR16/nlTaZkyfuZ/L9CKjFbYxTzMdh0ccbhv7Z55cM4pYMkhMhwJL1M7CT0dz0wPnccMlj9Otw7aMy55457RDJazbxjAAKiqeAaC8/DvsT6xdC6NHg200cYTxIP/3eoyn3rlMfUwn3Ipb2EzUVO8G0bxlXmZLHCj2psxKU9tQQEgXhTTw8cSM01m1oTtTjplL21z9vOtjtw6gF5+vTytLeHnRcCzXYMrxs4laSQrzGkgCsSY1h84d/jbFdhqfo/aR61wXd3hg5sV8sqUfJxz1OK4r79HWR1XPjiR6cxyptKpYhE0b2vPosxdg4DL1pNfI074bMk/eXN2Xv784GcN1OX6Qqt2TlpBtvU24VevTc8rW7In46BVbkl8jW58FoElHgjVo5jctGff0LLUlcrAgzsBec5i76EJ2Jm3yfGlqgS7ttnP66fDG3lsKD14c2GYUDx487G8YBvTsqbRD11Wf6EInzktzL+WVhVN4ZeGUFtt367CE/kf+LcNKRCJVjB9zM6+8cT2PvvIbAPLDlXzvpD9QmJdlOkwzzabqXtz2yl+xrTiXnHgbvdp9TMtEZF+OHH+MUwfMALKJmRLa0faodjO4e/7v+O3DF/HLix6m8CBhOK68ErZsgT9e8jSdSyt5ZfHVAKQdHzPeP5uTT36ILymMmoHjGDz52tksXDm0xXoDh5+c9hwnHrE089HNmJdlX91KyHPCdSmINPLY3JOY+8FgAEYPfZezTnmZNRu7AmD7Ps9apB2TB2Z+jyXrhzB62JMM6f8G25L/vpON4xg88K/vUlJUxR8vfJC8cDTj2i3C6MhBC/nxPT/hby+dwZG915AT+urlzf9TuK7Blp29MHDxfUU256DFgcRsVPxRtYsblOe/Vaw1vWjWg99xlDaWTreW3EV707ZgPdGzmqWWTGXAjtjJ1fbioyHI1esl34b4aoibW9J1M6WPs7tKn+pyiAaazakgbItO0mRKzgspjpbQ+7X0IBem5IsSKyX0eSTJvgx2Sm6PDPOj9jE09+HTGqrYMn2O+ogktIQej6sx+3R1w0BAHau3HnOBjqwRgjLhl9eRZm0KcvkgqUKWDx+p/TjePPDC8mCEbj/TbQ8AVqxQLIxo+H5NM/h8SkPsZKrr1cYQra1Z96IYorirqj1KpkZ5bWc97IVBKsCyRCsNtNhWyv/4/eo5kOiUpiY1i3NyJIpJaYamKbbulnUtfD657kktALh6Lra8HypyQQrEtdOt0PPyglQsVY25lRGjnqZj2Upi8RyQnDBGkq5d5+M4BXrsmoWJ1DL+1L+w/dPepB0fy1aO5++v/5JLR1dQmrcFIxZjTO8HOKxE1dAZ3HU9nYo2YmJnHNgbxI9KtwFJeidn14rpyGvlZxWzGrlpdAXXzynnxgfO57SjrqdN/joGHXWUvjqQThuUNawBYGNuCMtyeaiigkTS4tL/vSGTA+ebxNVXqwRQt786jgsvfJIfH3cXW+rK2JroyoylYzFn20yY+ASm6eCaao6ETZPK6mLQUTo5Zg5vvH8sC1cOZsJR79CrrS7WZhh0KKrk8LLPwAW/vrbihSbvB/HVkNMPAVccP4cjOmygsjGPRZ91YebCEWzd3o41n3VjeO+V9Oz4GSnDoNYw2VxVSlXCZMZ7o1myfiATRk3j8IHzgAjBZnnPqbbQr4TA0pCae7W6jonksDHNKI5jEYsHOWbAB7QLq3MWf7xm18V14fE3T2JnXSGjj5xPKtBMvbtLztxWDLfwEZk8G3K++oYX2eJPoqvGamZjZ22EhmgOQal0Kwkd9bKlOZR5y0azduNwxvd/ivyAen6/BveFgwsHa1IvDx487F+YpkPfnu+oBf2SrdRhts5u5MqcnFqO6Ps6AAPaL+axN37JP+b8mu+N/l/a+NfTPn8DZUVK6CvKzf18B18D2uTs5JJjrueBeTfz4vybOX349ZnfGprC3PHwhWzargSttm0rueiiaWxuKuUPD1/Ik+/Ciy/CV3CP+I9w6qnwr3/B6ae35a23RnBZl//jsJJ1uPlLiQSaeHb+mXRd/SGH91sMqO/o62+ewpx3T/xcX+eMfIMpx8/JCBMZLWTvXGM+hyO7qdpUR/ZfQsgf56X3j2d475X87IynsEwXxzX42/TJzFqWZVMmjJrGyKFzqdlH5VxcFx6cczIvvjuKMUfO59xxL5HcBxEv7384kPteOhcnE5Tw5Rg3+EXG9/gncOCYkb9RHAjMRkWFmnVLjVUA5HZULxpHa8vpHdpnYVMQO9VSi8v6PUhUhNizVZ/iJ+Fou2Gztm1Waw90YThae1vb4vuhJVt5d9ZIfgHDYJe8ei2QSeWcaaXugGQxlex7QutJK1Eo0m9WI2WXUUqM+Ke7rDVQaWO2IV7o4uEtfQrroj4GDfqYlpx/WjKwStZKdR1yctR1KA2o9bk6w6Dk12y2le3XzsQj6CiglJ9ISLEqCzYuAGDYALGFrwagvLwP+wtij1dRM1msWPE+kI0U8vsVxSuFrrI2ce21L1ldM/SyX/8uMUNyz4XhkPshfjypTDpy6TvruyFz2dZjUL/H45IXQ7WBQK5uJWup0aI/ORfXTe4SnZDIMG6ZjIxpm3Ra/EBK9G/iwyL7RfR6dawGp1Lv29iiL0lrL34j4ofkatYvv3gH54z9PU+9eh33z/k1pw/+IyF/A6WRHfh9caISumCaNAq7qEdQLXUodFRDSD+rtkS46FZqZBTo6yd+V0E7yoCTb+aaN65n2vs3YyT+QMhfz+y1V7CjuojLxr4KwCMzT+SpBydQFw3jOCZzZjuMHPApb67o9o0LHBMnQiSniWTMplizbK5lcXr/+Tw7/0zqtnWiMbcOn2GwfH1f5iwYxUkDFnJc7w8B5bNVGG5keEfFYGRyUUhNEGFN9bWV5aS+tmkptSCskrBGermN6/DT0S8zoddierTfjuU6bHJ83D99EnOXDeW4o96mXeft5OQ00aHDdmppi+FX75T2IYnwUverR1vFCuaJH1jG30xF0uQYBkk9j2zXpV6fQ61mNP784pm8s3II7Yt2MKzPCrbsKKVNO1XLKSkZQ4Ul06a2KkmJL755mlYMi+OdnK9eXrR6IPe99B36dNzI6cPfyXxH5FmWZbk+hb4aBrT/BCOak/ESywh8BxhisRgjR44kHo+TSqWYMmUKFZmoPYV77rmHu+66C8uyiEQi/P3vf6dfv35f3rHHbHjw4GF/oLhgK+ee8L88OfvXPPHubwHID+3gouNuoDDyNXiSfQna5FRy2XG/4r63b+TpBf8LgN+X5LrznuDo7p8A0L3tdioe/y7hYIzyS/9B/Zb2/OZfZ3H77XDDDft0eHsN20piGmnmLDmeOUuy9YlOOWI+Pxz7PEGrpQC2L2EY0LvdJtAp0Vdv7MrcZUMZNWIu40a/RoNWgCTR2FeBaTjYviRL1/Vi0rB3CdhaaGjI552VQwDYWt2GWx6/FIDJJ7zOuGPf/MrHBRRb89IZdO+wmRvOeZiQP5FxkBalzZZW6holvpjGyc2F7dvhrbfg+AOgxFQgEGDWrFlEIhGSySTHHXcc48eP5+ijs0kZzzvvPK644goAXnzxRX72s58xY8aML+/4QGA25leryq0leUqbCury5mmteTVbSluOW3GsmLIpG4YKrxM/B9sWHwPJwqgmdHOzEqVkEggjslMzInlGq0mgJVeRbOu1diSSvsS2NJGHyKaZWPS0HEtJ4KlUtMX6VKplXYxksla3Ep0iEQ2Sr0PYG2FzlDpVr0uHR/ULpJ5CDAygJDMm0QLChvJ/ESlazlZsjs1aO2xMKm0pFtMZUv0qOiMcVpptk35pLRUOyGwZEZHNH6F8zp2Gpdhvq8gMv9ZyyTCpik3Yv97+opp+qFvR8qW2gRqzbSsvnWyeDH0PdDVMsXFnBfZC3U+J3k887Vv6bkh0i+PEMjk6so6QkvFT8q6oeREISHZD9DGU/0QyqSOD0hIFJb4cwlKIb1B8l7nXmPFzkqyIiUQAKXYpmXl9PvEnkoyJ8sHQkR5peclm4rT09tLqfA56zoofhV8/VzkllVwx4Ves3dyFZCrIrGUX8+A7NzPxqPuxfQmCpkFS+7kkMs+ZOnbQcuhQtJ72Otuj5O5oXZ9YYm5y9TPdVz/j4TbNjDj1N0zf2BUXg4LQOnKqtkB3xcCd0v0T+vzgHhL+OEW5TSRLqgi9NJHp07dwww3d+KZhoWafaNe4Lrl2nFvP/S3V0dzMNgFfglHtNmFGXbpKYcV8/YEPapagUM81fbGcTeo+bo6p+7hZfBD0ZPPr8u1BYTj0mMTnLSDPQWMjtTq/SW1ddwB69V6u8v4Y8u6Wd4a+X76W/hH1+j7JMxXT+xVrv6iA64KZ5oJTn+PBaVMof/J8Rg95BzdeR88Oq/nFaeU0J8J0yMvF7/fz4tKhPD/7ZEK4HH+MEjiEOavV9XWELR3ZBgAAIABJREFU4fDrY0f08x8Qplyft2MYOK5BPBngiO4fUWrHwVVvXshGr8j1kXMSpgOfjw0LFNN75DA1z8bZf+LFvKmMH1/KjBlw3HHsVxiGQSSiGMxkMkkymfxcsdC8vGwdrKamps/9vlt40SgePHjYn8gN19G7o0oyUJS/kWff/DVPzPnFXu3bs2wRPzjxHmxrN9kp9wL5wUYGlaljN+5G++xcXM3e5T7dt3jpJahvyiEc/HxERcei7bQrVE6VYoA197La9cGM4QNUOOuD06bw0Ubl2P3D0/5E/2Ll3N29qIhgMEjvThuIpm2enD2GIwcvICfU/IV97g+U5DZx99SH+eE/f84118B77+15n32NdDrNkCFDWLduHVdeeSXDdUK8XXHXXXdx2223kUgkmDVr1p473Z/pyisqVFG1fJ31LlSnNbJqHc2hhUFH+yHEjBgxbVM240rTlCp7Ekcu0QJ+v8RoC9ugljPZFKVCpqb8pP5CnSlVEpWknpvxt9CSuyHRHf5M/ZV0WvEdUo49mWzQxw7rVh07kVA5QrK1LJS9OxqV7H5ScVVXHLTE7h3Srbo+9Yasl9orIld3zGTbE75KtL32u3hqA2wWRkNrITGt0UqWvnBYsvW10f1J/oiWufiylUPFZl+lz3Ezjs5z4Nuh+ljyvHptDx48UPch2Ua/OdyibY9iNxVWb/Zi5Vxn6lontq1i+kOaAUtk9GU1X2I6GqdaayxVmo1w3ZbVdMX/RvJryHpXMyOm2ZSp25PNnNLyGot2FAiIP45ErYjOrq65MGoS6y/zMZHI1rlRUVwu0ajkzwTXlRwBxRkGQ6K9xNdpV18PtV7msLB1ai7n+NQ9ztVzNaT7zqNlXpe0VI0VjVGfW4cO2/jepP+hob6TuhKuS1SucUKOrZZjjf2Yt+wc7p9zJd874a5MDgXxK5DIAMkOLFWS80KqPUxfZ/E3WqHHtkxrnqO05imFzoXVLGYbFRXq2n8Tfkfnn/8sTz01mXa56zk89Gea02q8Ea2NFzkOIf085+hzzi1S1zWhI/qSmtkw9MkYh+nlSq2R6qQjqSo158QvpkFq3tR0ITfUSMcidd/FI0kYUxH1tsVibNmp/CMqq9ScaK6to9GuwshX70PbDrfYS3yUhA+Iu1JUTmcgdtWzU6kr0zY4yik11dxMWdd5DOjSng82HE/f0vfplphF/0rVX++8PPIMg7UWDOq+jvmr+5NOWphBN2PmcPWcatbXUuaOI2FH4sMhcw5lRgGVayMa1zWmxPellQ+gPMmhXSp2BzVr4t+lrEpJbiODB8O67GO5X2FZFkuXLqW2tpYzzjiDFStWMGDAgBbbXHnllVx55ZU8/vjj3HTTTTz00ENf3qnHbHjw4OFAQiRUR0lEO786DvX6w+CPS9i7Wi7pvI4tO3ux8rPBrN/ekzYdP9rnY8sNxliytgd9jq0lEvlm8iXMmnU8BQV1XDjoekJ2I1kT4DeDxesHce8blxEJNVFx/n2UFVfucZ9U2sfiT1Tl4GBw3wR5ui7MfvdUPthwPIN7zOS8w27F3MuMs18FBi45wSYWrh7ElMPnUZDTuOed9oCPtrVl7lw44oivYYBfIwoKChg9ejQzZsz4nLAhOPfcc/nBD/Yitb/D/vPZWLBAVS1s00aFAtlhpRVZPvF1UFKnX2toTgxSKa1pak3KspQ2Z5pq3xxTrdeCPY0B1UejflHlaM20yJCoASXBbrWUrG5mbPNyVdR+2bgT0eQThNLqmL6kOsYmnT8/kVASeyolLwWlE/l8Krbdb0qtCp3rQkv6UssilZKsneLhXKBbGZNqC3VZ7QajTjMv+WR99pWmWK0VlyItoUe05F2kX9hxvRzyq/Ns8stYt+nzTLU4tmgbol1n/VXUdUwm5RqESaV0xVnNMtm26nv+fJXievhwld+gouJOAMrLf8S+htxd4RBWLlH+QhF9PXJ1hlSpehnWXu/NhmIPVAy/QX1tR3ZUdcIQTcbXSJeOy2ly5EWsrqdl7dCt6PQJGhvz2LpV+Xb40hFSbg6lJWvxFYnunG7RSt4MwxB/HPEjkRyY6hkos+IkUzafbB5AKm0TCNTSpf3KTJ2chONg67w0RXZNhhdJIEmV7IzfkKkZP4mkEpVEWBhhsoRJNFNqDPk622OOft6CUoNIs3CSB0ZqaYhGLH4IuZbFjtr2bK5WPhE9260m4FfXMJP1V9+rBcvPYMOWwQw/bC6Hla4kmWqphUpkhauf8ZgptTPEf0E1YW2ZsLVfguw/TzMc4zXD0RH4yxnPc8lj5/HQQ36mTp1LRYW6B/uyorGbMunYdpsWNKBe+xlENJvRFvB30H4PER31o3OrJHX0k7tTt/X6GjZoxqpWs17b1fYNOudFk74fb60/nMdev4yObTZT3VBI+WOXMX7Em9gYHNt/GV1ylCAhUS3pYJBoIIcn5/0367YP4aQBd+JrXEFTI5iNOvNxkWJJC8Ka6ZDIv0y0nrB/8pSqNpFQbOD2ukZcF5a/NZKFa0/hyLKXmdjlL/TUPkuFvVW/oYiFHYbaKDQKM+26+Fw3897LRN3ouVKt/UMaTYkuU+9YiTaT5/28sffy4Ms/5LqnL+fHp/+ZGv3eNPXv4sOSL+9dYc5TqUy+mI36dT53eykVD11EYQncey/7HTt37sS2bQoKCmhubuaNN97guuuua7HN2rVr6dlT+d69/PLLmf+/FF40igcPew/XNXhj7gWsXHPs537r0/NNhg5//kvredTUlDB9+oXEYi21U9uOcsop91Na+tkX7LlnJFN+nnnjJ3y6NRuCNuLwFxky8JmDprLmx1v68tgbPyGZVsJsJFjHBSffQmlBy5oqiWSYd1dOoXeneZwz4h9ao933J3lMtw3cff7jfP+x83nooVFMnbqWSOQ/8xfZGzz1FOysKqbXYev32TG+DLOXnEpx/g5+MOUeahsLuOefV/DkGxMBCAXidDli0ef22VJzGB9tG8JxfR5gYJcZNH/N98V1YdGiCSxbO45+XV5jYo+/fOkzVxcNMXfRcPx2gmAg/oXb/TvoXraWiyfczYMv/5A7X7ya/5lwK3mhhj3vuBvMeH84yZSP2bMPjGJsW7duZerUqaTTaRzH4eyzz2bixIn8+te/ZujQoZx++unceeedvPHGG9i2TWFh4Z5NKLB/olEqKv4GZDMg2rbKGJGtayK2WfGE1+yC3ZDx0XC0BplMKi2vTGfd7Kz9G0q0JmVob2LRqMRtSrzhq3VbozVamYrZCAGFrKlJrJRp/FqzaNJ2v3hc9SW5PbLRJKI1ax8Gfcwy7Rne6JdcBMLoiM9Hgz5X0Sal8qC6Y0GdLdW0d+K4DvU4uK5ovXrcrtJa12nNPFNtU1/rDlqbkxz+cd13bVqxMFuR6q7iPyAPdUiPUZ17UlJDJ3S2xlg4s41kH5VIj9xcubbyAt23YY6CioraTDWbhcuUc5lkoZTrUrmtLzvqO+EPBejXeSm5BUqL+vSTwdRF8/lk62Gs/HgoJw2YxYkD5uBqv5S31hzDq8smEEgG6Np2LXHJBaGPZ1uWytXwwUT8ZpKfTvwtkWADZirFtub/Z++8w62orv7/mTn93F65Fy69g6IiCqIgoICiIjZiNNEkJjGWaGJMTN6Y8GLMm6ImamLX2GMXQQUEASsgIl26cOlc4PZy+pnfH3utuQUVNYjGH+t57jP3nDOzZ8+ePXtW+a7v8vP4u9fw+qzLmHjKLXhKDJbJssy9s22ts6KzVytNmnuab8dJJP289Pq1bN3Vm4tPfJRepWt5bcVpzF85ngwbxg58iYjjELAs0kCh30+Dm80Ukvb8qGesmfNDnwh1FatpohVlzTMQliq4YWVO1MqeMi+i+lmey7jiUKQPWbbNpp19eWrONRRm7+XHIx4gmghy75wreGL2b7hi7F8pzig35/R4aJJQQp/idWQoS6ucIyl9SEvbaTmnXm+9LHhh2ersc2S/BdvPwnFsOmYtpV3OFl4VD8fF4uG4sGs58Yuf5NonL+KpRzsxctBiHngAJk6EHDXGD4JMmQIXXwx9Om7j6lFz2LjaKGBhwbeotZwRsvFIRo5Vb7e+KF3c5WtHn19BvaYbJSujSTwaenLNykt7KMitwA7GyQ/uYeTAhbz01hiO67mGMUcuIaQeAhn7LNsmM8P4Dzt2qCCUl4enUVqtMV6gpnqzrlmS0ZCTJ1wuWidHPKLJZDkA9fXmYqqrPwJg8/ITWf7RaQxoP53TetxOOGDW+KRkUISbzE3YaUMi4uOnT36f3ZWFXHTBE8T9ceJAvI1nLSZ1p9JxM6/SabPd5VKuG69KIC0YwVSKYO4yzhl1Gy/OuY6bXv45R3RdQIYnzvE959FeeHlcTIucL5ZOs1e+05adlE1WKMITT9wGwKRJv+GrlAEDBrBUPL4t5aabbnL/v+OOOz5/w4c9G4flsBhZsWUMs1b+1P08b8U4rjrr77yzagRvrToFMHUkzjj2FSYc+wqW1QxWPOvYKXjsFDOWnsny8v2R2yq5GZVcefrf6JZtwlR2Mok3lOCKUX/grnm/49k5v+SU0f+kuLj8M/c7kfTz0uxr2L67NxcOf4iTehg4+4UnPk4knsGcFWdyylGvgH0QzIovSTbt7Mu/51xLUfZerjztFkrCZlW6Ydyt/Gn69dzz2q+YOOqPFOXuwHFgwZpzAcgO1Xxas59bXl0xnhnLTa0Xr+ciLhx8E0fmLd9vv0Fdy7nj4if52VPf5okZ43hiBtx3H8yeDfru/E/lup9tIS8nk5sufpJQIIFXwg4eMRDUYEgBnmoJT8mxqms0iEGiildIic1iUtxPSqJXepvDDC33t7CwLctVCue8fyIDumzglnOfwGM5ZAhQOiLPQRzoklmHbaVY9OG5HN1xB4lcUQZE6WgSpaNulzFoKuuMQaOl56urzbNRW/uR7G+A9QqCLd/9P9hWgqF9ZxHMzsQrSktUxmW1jEttMsnyrd3Yuqc9Eya8QFm3HcQFwK3p1Bqy90riQSxmFLl4vDUNgRaijAidvyMkkrnt13Paqbcze97VvLHMpPDn5e2jUxcDN9bwi6uypNMuqDwIbNzWgQVr+tK5XQUFByNV4+ssB/JsfEYt4gspGzI3WlQ9TbXZai0Ro1V6PDXu/1rLI1PjuEnxZIgllSkTrlSr7omHo072r24Tx1WDpNoxD4Drv9AsDuFPsC3VfBvcQk/7BKuREpS48mL4fJpFYtqKamVQaTvpVhQ01x/QOKt4Efaq9p1Ur4GOi+SjC7dBls+HY1lkUkmDy0qqHCAaIzcPU0R5SaRTIbECFcuRJw+0ktRExCtT79Fskxrp027pkywUcfOQxmI6PiH8/gwZB614Wi1tmD4uXGgW8SFDFO//ZcvzvL+qHIAUpiR1XsDgAco3n8yslVfTs90HTBh4F47VhXvm/JxbnvsdiZSf0UfOZfyxM2hvp8gIRMmRcVU8QMSy6Hvcq/zwyNdJpj1uVciUeL0USZOVkcRrp/DSjHb3ASUZVfxi1B+4Y86NzJl9NZedeivZ7Qy5lFbLdKu5AqmUl/UbTiYWC7Nt15Fs39OD7w17kCHdFyKha2wLOhaUs7R8EGCDbYNlmWfe43EXwOYkSU8LVlHFJtVJN6tl23a1UEyLVgUWfI5yQcg8apJ5FZfx0Iqtfq+XLbv7M+XNaynM3sMvTruVrFAD7cQn1C93N4Fxf+UP03/FM3Nv5MQ+r7Onpj3Lyocwuv9MTuq+glxBVCmWQz0YtR4PDdEslm86hqO7LXCXcuXryJK+1Sq2w7LYsLcX+VkVfP/UW3lkzjU8/d7vaTx+MmWFq3jxgw849thjyQX6Af26bqHLL28lGvexeGsn/vz8+Ywe7eWNNyBT0zX+A0mnbXJzaglJLY2l5UMpyd1G18zq/7zxzyi6fpj/jaejQ+FePPYnhy3a5ezj6lH/4h9zL+P+mT/lkrF/xWPvz1/fECvgo73DqUu1pyB7M7D4M/Vp3IDJTPngFh5/538Z0PENwiGbIb3eoCS4v4c0lRYG5KK9+/12sKR96VquvPCnVFR24d+v/v6ApGVVDUW8v3EUofIi3lwykOxwE9ee9wKVdQdh0nyd5UDZKNmf8lsLOezZOCz/1bJuuynINqT7q2QFa8jP3sQ1Y/7CvfN+zsBui7lo6FQs68B5ABlSgl6VjaTdWtnw2B9PcQ+QF67i2lNu5va5N/LQ69czcfRtdCjeP1afSnmZ8cbVlG83Rct8nhgXiKLRUvbVFfL22pFkhWrw2MmDES496FK+uz9T3ryewuwKLhvzV7JC+69G7XMq+N24v/LH137GrGXnYllpRvZ/lfMHPW/ChZ/w3quPZHPX7F+zu7aMdduP5McjHvzYl15LKcioZM2uI9ixrwsXjPwDz837HS+/N4mzBk+mZ+Gq/fYP+JIEfElO6LuOn589lVtePI+5c2H8+C8yGq2lc0El764YwPRV/dm5r5ApC0bQu2wJAzsbFGFMUiirPR6XVMktdKBGmEv1bbYuXbcYSntECdytxeoU6JlO8+6aUeyu6kCvjqvxYjH17dOJxIJ0yNvnKr4KvNSwRFrONbTnErY35fLiggvYU9eZ9oXbcITj3ZtIsLO6B08uvJFEOhvbipF2AmSFHiI7vJdEnVEMVq40BfFCEtxWA3BI/3zOP3ky09/7HxZvPp1k2seSzSdy/dm3U5hd6aYo727M5ql3T8Hvi1GcsZewE3Gnik8MOqU8UCO2yqOfzYvfJ0XglH5AU9kdp7XCFyRCoElgAD4fttybSBvPRl0yyeJtJ/PmmrPx2DFyMrfxv9+bxuZdpfz16W8D8MGa6Qwb/D4/nzSJb5QcSp6N6cJxsHix8OkXG54F2xavhMtJoEh+s/AodsNxHDcnOy2sinFBy9eqpaQoYNm2k8mk7kPlmVBmUJ2YinRXNgmN7dfJtsFdqk2f/FTTqBX+HOWkMEcrR0MgIBku0tdIxLTWFk7mIpfF+9KkrH3xYKvjk0nFPmisXXkEEjiOg4eWlqe+3sw+PhknZR21tXqhchDIopMnL0nNhNeHca1lMDLKnRGLmYczHo9J38Tz4zKLZrhMl+rZsSzlPDHekYyM1q+/yZPvBGDSpGv4cqSJLEdwMEFZwMT7csqwh6mZXcLT7/2Ki4ffRHZgM+0yPuLmiTdgWRDEBw6UyPiV+GVxlYdHa+bUteGPSMmikxSLPirj6165ZbkvAisWI9+7m2tH/oF/zL2RZ2ddz3E95oGd4uhub5Ofs5NkyssLb19F+Y6jOf/4RxjS8w2ybQvbdrAci4ZYBi9/OIZkysfS8uOJJwNcPPZW6qw09Y45bxpTQTVuqatYLbEIzW/uuPxW3WrbDDRVro/WbKdNLrWkbLW2kLzk017BesTr2L23NzPeuJ7crF1cNfL/yPQ0UJwyk6a7jF9GJgQaLXrm7qHDBb8h7dg0OWls28EjHr62lUmbgLpINne+/itqGgvp12seK9aP5C+vZVCYv42yjH0M7j2HLMn+0rUh4PNx8fHPsKuuPc+8cwVnD7+Tb435M/+edQPTFk0iNPi37Fq2jEpg2NFG0eso514FtC+W+hsHSav7/rjp7K3O4+7nz8ORAQ0H6w5w1H8mq7cfxaptxxBNhVi2aQj9uixn7OBpzFxwJrMXjWTsMQs57dj3PlNbBVkGU9TSOwKwt66Mp96dRMBTxZldzibgrWDR7pvZVNfuU4GeLSU/awc/O98U0auu7cY9r/yMW6f+nCM6feiO1dodvahryuHS8x8ifAiJvNLpT/dspKSy9kWjJ2BZsLPy29z27ES6l+wiMxhlyoxx+H1fR9PgP5TDPBuH5bBARqiO80b/iUdfuoUVW0ZwtIQwvoosjrxwFT8ddTP3vXM9720YRSrtZclHI/j2yFt4a+UENuw4hrOOf4QTexvWPk3fBli9sz+vrxiP1xMnK1TLZWNvJbdg66G/iM8g6zaPwONJMHH4ZDKDB84SsCzwWGmXpOuTpC6SzR0zjaJx0eg7CLdbQ27OLhYvm8CuPT1Zmgqws6oT3znugf14GYK+GFeMvp3/e+kmlm8YSc9OSxgzfDJTZv6DVdtPoXPxR5943vysesJh+N3vDOW01BP73HKrGGUdA/Dri5/kthfPJT+nlvdX9CblpGkUw6BKlat02gXX54lmnyFbNaI0nKVFy5SsSwsq7gRWfjSEaW//EJ83gs+boH+3dznn1KeJe1JsqigDoEeX9dQ6KdezoRKT8zemUtQ5DrUNOTy/8Fz8vgiJrGr2WJYbWttYOYxYIoOx3cYT8u3CBoaU3MjWhhCNkZwWdUSMAhsRdbJnN0MOWCAo3LBcY3bRdq4663aemPN9lpcrYSAE/TGuO/9f9Om4hUC6NXZFH2s1vpSUq94xxGEpW0sFaChctwqg1lR2sw1bFiVFUYL+CK8tOocju1SQn1VLhWJZxMhYs7Mji9acSlHudiyPB8uCt1ceScAf5+FLHyXoS3DefZezYtnRfOPkUGajvC83JhgUd5pMFrWGtTJkM4ZDJ7Te4IDL96CTPSFtqgXeJDVSKmVi71OrRVpSt5aLTNfJoNUMNRdfPgdlv2zlFZCMirBlsUddZRJssm3DQREIKBOo8ssL6ErAVGnH9KY2Lfz7em7pY0rQ5mHxlMRiWs1TKgp6tfaFXBNpHBwgLTVSmkWZH+PSetxRN6EApYTxUZEebqVM+awPdFAs3W1JU2ulJmEshX1pZTPNlz5q32z3wdSFMO3ua/oSCqlj9NBQK69atZh8uWedBDCktR8cxyEjGMfvi2F7vMSUkVExQFoFUuaDSwEQEdbK2tYMrarAKxNhQs6ri31L75Z6Q7Y2GTu5U/5eMrJqueEM40atqC/mrlm/4aGZBg1+wXH/4sSecwm2iQhEbJuIsIf+aPwkgjkGVyMUC8QoIOl4AQ9RpyMWrZ+llj7OZg9ZW+4D3UPvmWayqH9BPR3aOeEfsI1nJF/azQgGCdpe/N4YxRlRfHHzvfIUJNUjVO/BEm9LrlbeVGS/vmyVMdS2iSYC/P21G6huLGDimDtoX7qe3ekwvY94l26938JxYN2SU1i85gJsJ8K4Yx6iQ8hcQ5abDZcgL1RH2vGR7fWSlx3F54sSxc/uRIJVgHIv6VWWAWUZTUya+Ai/f/IiRo70s2jRf47dCAYS/PjbzwCweGWv/6yxT5H1W49m2ts/pEPxGs4acRvZwdb1mi4c9wwPPPdD7p16EVdOeJLhPVbv10Z9JIOn355AbTTIloquNEYzuHDcnYRDbUivxNMR9FS6X9lWGpskqS9ot3Ys3M5vL7zZtKWhEa/XZd09FBIONXHleQ9w9ws/4q9PX0W30i3u3NWw1qryfoSDdVw4+u/UySLhOBDyx8kKGYU7J7OBZOqzla3/r5LD2SiH5bB89fLainOZtdJkWFw09G6O7Trf/a0waw9XjfkTT777Y47r9hYn9njjY9vYW1fEy0vPIxSoJytc87XEaLSUdnnbWPHRMGYtu4hv93/0oHiRyvd1YU9Ney4ccT+dSvdnFLUsOK7fs9Q0lLJ8y8mMO+ahj22nY/525q07mcXrhlPSZTYFuVvZuG04nYrfoWe79z/x/J0K91KYXUd5eSFVVV9M2VCKNQ3xvvmehC0ch3QqSURIvZRZNeHxuKXQvVo4TF6yihVQUkOt/6KFyNSiX7F5IAF/A6NH/o2kN0FUC+9Ju4FgjIsmPsQTz1zG3S9dTO1Zj9Gv+4duCfqqaCZPPn85lVXFZGXV4AvGGXfKDMIlEEl3AaBRoM5ZRYbqYEHN/Yw+5ma2bFnPzprziKffJeDZ51KuN4uZyR0F85Ejir9S3mv4TCvbqsGU4/HgBbJoTnGPKsha9tmmYT5VZBWz4tH0ct2anlhSuNPjMfegSICyQaEl8JVu4Qfn3s+UuefwUUX7ZjiR/FNUsIVTjr8LfFUEtRw9xtOiplcjNqlDZIAdUjmUno08sZwCAWMWeuSGqsVuWdpMUr5Xng2tQOkhldJ6IKbXAXdfRbcbi0gtStWptZiS2m7KbJilmAXFfMjvTputYhhamHZkiHUcC6gWqladtqLIj0w5VK0/nVbGkq2ThzBDlgY3f95jsA2VXuUW0aqJmvWSIe22nJhtGR/NGGdZyrwqHiHpY0JqwSR8Zn/FGiiXv/JPZCsfhWy3SB8d24x/k1eBVFrVtBkNpJgWHR9le/X52o7HlyPnn/+gnK8LwYAhzSrw+3EcmLtmBBt39nQt1Gg8A5/HS1D6pi5dj1jajZo6qDUlUq09Grq4KzNhzB1vAeB5PKze0Z+31p0khzs0xEOU7xpAr87v0RTJ4akFP8EbijOs0wrALJaleVX88Yw/mTbEraxMlxFgb30xd7z2axIpP2eN+SsN3ggRSxFIMv5OO8yctIFuILUmLCvq7mdZefKdeHAcfYLUV6N1VvSe6jly5Xt9PhVbYCzgsGR5uc+ZZTGs/2zqG4qZv/ZMvJbFmcc8xR7JvIpJzZ6A10tAOXPUSylzT8dae5a0LJLSv0XrhrNhV29GHvsSRX5JtXS0sqeHjEADYOEPBNxKpgr+9QNXD3mKisZcps7/Hmd7Gjlv+L08Nft65n7wPxSd8Htel1o6wwYOBIzvNZ70cP1jl7C3NoeZs6BTJ76QrCvvDDh077z1kIbx/L4YXu8nI/iCgSiXnH8/jz3/Y558+RK6d9qAIx3cW1VEQ2M2Z531CO3bm7CdclW0lS5lqxh1wiPMXfA9XlpwB6R2UtV0Ij77GDL95Zi5+fWXWCzAgrXHsuajvvjtJGNOmEtR0RY6td/KZRcazgzFaDnKu5NIEIu0xo/EEvuDxhMJL47z1YRxvyw5SI6Nw56Nw/LfJY4D094fz8yl4yjI2odHgIsFWXvp2X7tl3ruBetPZNXWgRRmVZAG0g4M6jOdYcc+y6yFP2D7nj7UNeUesB2VvfXF3CmKxqWj/4KVv/3aUhphAAAgAElEQVTL6/xBFMuCM49/AguHt9acAcB3jnjsP1pgS3J20bFoEw2RbLbs6c7Wih5MHPsXMlqwO27acSwrN51Kl6J1n9iO35vkh6Pu4qbn/8y6rYPo2+U9Jgz/Iw9Ou48NuwdzauH+YYTN+wrZsacdl571MiNHnvWF+n/TTfCXR74HwKlDFjJx7GtkZGhasYXH43W5XarlpdXk8eCIMqyp+kpQpuRcCpwvkmNzJDzYIFsbwGlWql0PiWzV4s/0NPD9Cfcwdc5EqurySVkK5I0yZuyblJUlSSQMDWZzUUItdWDuQb2VQ+c+uziq6Qm2bDmJaKKEnJw3SMY3ECWtqjEapAoo9b/0TUPgmgGjCk9YlFC/pl17PKQcB5tmzMQ2LS0v49Mk+9bJNiqhb7U+UimjbCcSUlpClOYSJ5t/vHgJWyo607Gggt1NYe595kdcdOYddCjewu5kjhzfurBhKlVDsYRoc71elmwZyzsfHsGYI1e4kP7Rncu5/40R/OY38Kc/fXMUjoPk2PhsyoaGuT0elzlAtsoJoZUz1dJqlP3NNtMTwevVY9T9JXgG+VaR5br1KElNm46qR8NFsmsnNZVLU8fa9LSpRUxeCVvybXM9fvFQ6LK2La11JkrkOtQzIXF+S7NVhDFVXHPqRdF6q2VCxrRLzrMPrUuiV5PRwhJVi9JYc3li9+VYra3BRuEpUdCWpshtV7eoXKei7TvouMrik6MMkPL7ClstYINfSaUSpFJ6XzWBWmeAemZMm+8LQ+NxxzXTbB9MUY4In68jUb8Zn9dWncTMpeMY1u9dvjPiaXxW69gqUTOvbCEiSsmirIuS2n96B3T+FWtKoL4QFJjn1uUwLlPbSpETrqaseDUDj3wFsJj13g/58KNhnHb0NE7p8zZabaCjWo+y3SLn2OPxsLeuiNtfu4FEysfZY2/Bm7+DehlnC31JNVeiNXPPwbZjLbK/9D7lA1JpE63Douy1qTbf670Mt/m+NWWlViRu0srEUtNIeTbStsWgwf+mwYK31pzBur298fmi2MLzMaDsXc7v9gbQzJnjUfCji/mSGL3jkBeu4Yaz/gjAhp29uXv2tTz/2q/4yeg/Ew7Vs3VPT6bP/zml+Vv5yan3EA4E3DmsL3Gtf5GdThHyRdhe0YcXXv8laQfSaQ8+26ZWww8rjPep14ABzVWJvAmXJXnSpMv5rHL//TBpEpwyYDnhYIyXFw4hK6OR7LzmlNtYIvQpLRwaCQUiXDjO0FNXeY1qoHi1VMr/ice1lbKy9ykre5+NG42nc/vWT09L/rpILBbkH6/8hO17O/D7CY9wQs/V7KnM5Ibnr+KxV67higtuhtCBr2XJlrG8uuIqTui5nl+Pn+Z+/8Phb1LZkMlf/jKI4mK47rov82oOnRz2bByW/y8lkTQv2oAv5oK4DpUc1WkpexvyaYhmMXf5RKqjeSSTflZ+NIwTj5rGGcdM/VT+CJW9dUXcOcMoGpeOvQVf/hevq/JVimXBicf/m2Cgga07jiCRDGA7DtFYJq8svoKsRJixvad/7nZ7l67lytF3cPfsa7l31m/47pg/sXl3X1JpL98d/TfCgQOnQw7usoAlO44ilgji4NChYD092u1P5QzQMa+K/Oxanpx5Gt9t9yolJVUfu98nybx50LEj3DphKrblMH9NEe8vz+OCcUah69XxQ5asP4kFpeWMOGKOSxG+N5mksgV+A6CXFsATRSzYxkOh2SkaLnUsCyxIeYxhFPebJT0g9ANKQ6/05Kp6+sXyT9om/ObxZOM4GlJT41FfvK2Nyo1uPXUJfYvp51LZSxA8JuFopeWqlc8eS5VqxWFIYUoJv8csCyedpgGokv5vUgMwaVTMbCluZwnGxZc2YcFk0hhI8XhUPhvyv3zH5rmZV7G7soxrxz7IiB4bwYEOGfu4YfTj/PyFn1Gzu5Rk6Va51kwZF/G6+GNkBtIsWTecV1dcSr/2y/hh10nsWJKgbLBhHs634U/jXuXDhkHMm/fNUTYOqWdDp5xtGxSyYhuaMQ7xVlutMJnvmAnfwbJcb4Jb71Jj4dq2bK2WDxHNwCDdT5cZfWjaYpbtNt9r9FH39zqOy16qtXOK5Vy7tDZDwlhxH7lHKfRLK6kaT4ViVeqTagWa32u8xkeiKPlmf5COj6K5E+LZCLpX6JMaKcqcrH3Vm60jrtaYuiT1HFmK1ZDPJXJ8e3FllvrN3cySmgqbk+Z8lQlzxmTS72bfaOVQzVRR3hD1dHi9epYvVsiorUye/DYAy5cbgGAwaB54vz8Dj8dYYH0HzWZ3NJvXl48imoZLT3oByzK1HQDScp1a86VJtsq8mpKtesb0ipSVUutzaHaFZjcFgJM6L2Bw2Ts4Djy97CLmrh4HwLijp3HmMVPpiQMOdCqSJ0Zq6AS3S2aLZbG7rpjbZ/6SRMrH2NPvIJ6/l7h4JbSqqTLNNvvtGjAzOI1l1eF6B9PqFat1awKl0zpX1YOR1XprK0OojrqyxJp5YNu75Xtx09uGsTXimPnR5GJBZEZaPvofvYj+Ry+VvsRJp23eeXMCTy2/lGS4jjM6vmN6IDga168n90K9mG6mWjrNUYUruXLUbdw99xc8+foN9O9ssBbZwZiL/dD0UC1dr7WObGB8vxc5a8A0t6dxmQexJq1yLOy+gDeQ4JbvPcqvH7mURx89kyuvfJjPK6EQLjun1xNt9dvZJz1BNB7ihfe+zbvrTkYHPy3Bfa8nwXeOe4kjy/YP8XyaOA5EYt9w9sqDJM/O+Qm79nXiZ6c9yKBuK2nG5UHQ99kYqzZuO4JX3xVFY/gd+Gv3fwXbNoTDH3Pwf7EcJJqNw56Nw/LfJZYFI096gbDj8M7KUQQt+NaJLxzyPpw98GnC4Qa8niRj+s35TB6N3XXF/HH6L0mmfVx6+q3E8/cckv4earHtNKOG3cOTz/Zny96+IMrG55VeJWsZN2AqU5dOpHvpmoPcy9bSPr+aa8e/zI1PfIe9ewu/UBv6yrJtG9v2EFCvhN/mW2MeZt7ifeyrKXbxGQnHIY1DZVUZt82+mgvG3kuyTzkARQr0ljY19V8LUG63bGYsO5fy7UdxVL8Zbi0QDfHGxAvhS5k5pvABDTM3pqU0g2xtO8Mt16BhXiVlbC7aqEaFGktSgkIUzwwxrsrk1yoxDZuSQuLmqAlVKufUlHoJcXqMcbOD7STTSVJE3LCXmgdaQFBDZ47PGDz+1JHye4n02RgsqZQxHLfv7cbA3m/Rt9tKGmk2zmIeDzUKXPZ4CAQU1Ky0CObaPJ40m6pNgPRno+/F7/VQFDNjrobt/pV4vhmS5qAQiH42ZUNzDjQHvzn7pLXfQBHw6bTgDWSyllqWy/+Qq9kQ8vDsUXIW+V1z8LUWiiIZ1LFZIVu17Etlq3acxu41JUr7nilWT2VdHX6xqPwC4FIXplqzuFaxebgUw6BcIZGIsf58Ps0qMZapclZUWx0AqJdMEkfYL52oAQAGmqQORSBAVlYWe8hwrVm3ZkybcdGb3ZboUR//OvF5+NR7IsdrFoFHgOJOrjlPt1XmnuVUm3u0RwBRyWSeaylq1dpmfhBV2dWzZRanLvxnLH+TJ98j/5lZ4vHslfMpRqTe9aJFrTKwoP/QqdRi8/qKUSzePICgJ8nQPu9x1sDZWBZEJOOoRsZaK4tqxpDL1yJnbpv1FJP9tKquz2WdFe4Ij8XFA14DmhebQsWNqBkgusROyyGe9PKHGdeTTPsYe/o/SeRXgdO51ThodV13vuhcTntwnASOYxOLVbsAPrWQbTuC12uQQn5/Jxm79jJ2gv8Qj48669LJWhmWvbI17uNUarec24yXMozaQpakTMDNXkz1vujaYD6nfH5sT5KaeC414urWirLq2lfwo7bYqCEFfRn7/TQlzLHixKE2mk1uWPou98Qvx6m3Sj0maQUcOg5JjwcfUKcAQ0kpbRmhD7jsj0kmTzYVfCdN6snBEI8nzdghxtOimQ41qRQJxyEazeDVmdfz7Mwree2tekL+KNeOeYH+ZeUf25bjwIyl5zJ75Xj69nyDIYOeJfUVZYI4jkU8WQxYJJJ+LMth2c6/4rUbKW13s1sv6+sgTZ/gBapubB3WOZA0xjLxez++kGA84aGqCjp0+GJ9/DrKYc/GYfn/WiwLhg6dQlnmXrbv6UIsksuLC88mmfRzzvGvftXd209qotnUNhYwYehj5Ofv/Kq7c0ikb5dFfLB2NDOWn8PpR0353Mcv3nQCr394Ft3bf8jR3Rfw/rqT+deMX/CLcbeSHfpy6b+/iKjCalv6JwqtKD0xrxpnAhRPe/BikZkB51zwBIsWnUws5mP79m7c+MJlXDD+Xo4pNha6liWIpNLMWDKB2SvP4uge8xhy/MNYaYekW3hPcBRtMBqaWK8WfTptvAzNIPAgtqTDe6U8eyqlxpLRmqNRkwWUicn6KnQsPqyYTCxxNwBPzv9fPHaSnfX95RyZDCy9gfyIOWsiS01Fc26fT420LOl7tRy3TQyelKuQZuhvLrGqEEYKBYBtKyTeiMejBpExAHv3XMjK1SN5etE+Th08ww3Pb63syj9nfoe87Erad9tFo0/xKsjxCmbOpHOPVfiWn8ofZ1zP5Wf+jXjAGAdqbGxMeHjg6QvZsgX+/Ge+MXJIMRtq7TmOZlMYCzed1tx8Y9lq3n9I9CC1UKppUVBIHrykWBhqE0el3kOjtKVWil6kVm9F9ksJxsEv8CMFTKnuqtaSuiOzJDth5fbtbj2MTVJTul2RmfRBsYa7CDNhvVR1LY+al4M+jGXZUoHVJxkwYrn5xXr0eMy1JZOS2VBtjs/ea6i0/WJVZebn0yEUwk8tKXG5qseiRrEqbTw1mq2j41Pnepdao6jVKlbWRh0YofrADhuLPb9B6rmk1QdU0sLCNvcinVZLW9vWpcvcg/bSm9lC1zz6cxciMlb4smWGxjsQMAugunUh6lrUmokB7bEs6NB/IR36L6TIbmL6WxczbfHpvL7qpGYWW5cMKMFpxzzNSX2WAftn89Ai6wTAJ9/r6LqcqbJfnGYvms41pVBONZqtVA9nA7Cp0Sx6tXaS3JTmK6m/T/0r1WzYMITlS8eRSnvcueAAsdhCPN44qVSMzEzzVDR7nEJ4PO1kfI6SrXoa9OkVbIaA8PDrOZXXxXglU8I/Eotp6W6zVzLZ1KZd9XzoEypMvbE0s976Cfv2dXEZJ19bcQ55OXs4odsCoLmsuY6tjnlUXqj1qRQfbBnG04svp0vxWs4+9Z/4vHHOHnMHL826lltfvZ5LTv8rHr95Aam/LV+eoXSLe6Tj54hnQ2veJORcK4V3o+fAgYTEsg3Vhvms+PtkErZudafPF5ZQKMLJJ88EEjQ0ZPH8c5fx1Is/5UVfnMxQPT8edR9lBduMorHcKBpnDH6Yqs9Yk+RgiyOKxvbaieQE/xevJ8a2fb0BGNTud8RTuazY9wt2NYzCozUJbYv+/ecxePBHhzwtdNjQp0kk/cx5fxzvLBvpnj+e9JOXVcOl599NONREYzLrE9soLtrJ+ePv4YVpV3DfK9fxqxE3kRsyczAuisbaj7rz4EPwrW8diqs6NHI4G+WwHJYWYlkO44Y/SfuCCvbVFDenwqakOubeLjw7/0qCvgcZ1H3RIe3bzqoOPDjnp2SEq+jYfhXN8N/Wsn79CcyffzElRRspzN+KvkdSFpRvbaApksPMmT/jzDMfJPgxZbm/aonHg8yYfQV79nVhQPf5BOwkDhaRWCYdPkedlw+2DOPp96+mS8kaLh75dxKSNl9Wup4JY+5g6qxreWzGr7hhzJ8OqoejV+kuOrXbzb9ePYMLs7fQvXvDp+6fTMKll8L8+XDFaTNdwyjpgOW0qKyaNOqQX8C2Xm872aZQyHwyabbRqN+EXE57nNWrB5NIxNm69Rj+9urP6dVpMSs2jmBA93kMPfYBalKOW/sgW9LrQ1IVVUspqJKsKkkzmbamOKuWlMBxdE4pMFyv32gLeWkTYmtooWj0L7ibqG1wEZXyRjo29zkAiny72Bs9wj23nXEUS5eeQTavMXbwVKq9aqRqOFFIEp0mfE4cb4vr0LCwhj8b00JGaCtWZYu0IR6dVL1cgyjNTgFDT5pOceEO6uoLXCZSry/NwKPfxZPnUE8OQa8aODo+kuqdziGW9lHY3uG00x9nxoxL+MPc33PqqX+lIeHhgWe+xZqPevCD8VP5wQ/O5pskh9Szoc6vpBCeJJOqlmpWRr1szcLeIObzdkFcNAEVbSzHWpf3wtzcdMqY3rVpRV9IVoBbWEeBO8jWTNRUG+syuy1WQ7YB+T7PttlYXg7A6m0m5bBvTxOX7SUeji7ZxrIuFo9FrfjJ3vOZPpxcXNzi6qFRJnhSHsaKBvPQbttrxmPz6neBZiYEvcKydu3wptPk0ewF0se71sVsmHNZgpOIKceCAqbSipcxoK2YxND3iPWomf69halZPUz6aOryogyEhpdBvE9JrcGhvVIPh1rDhiinPQYn8PkSBmHy5Lny327pg+BLPGrzap+aWVyb3Zrq6TAQuj0pM7O6DHifLjSz1/rjxvJI1Kd5ad51PPrGj3nire+549BWskI1XHLqXfSUdNS22T+KUIg7juuaVle1+lx0jlek0yTTHu6adR22J8GpY+/DCln4/eae+nxBud5KVq06mvnzz6Bv5zXcOP5h/N6k2z6Wxc3PVhKNNrGzuh1PPvE7PHaaLh028/2zHqXB20BERt9xVspB6g5uTcykLxJ9VnUW23ZUthnSN/PkhMMSAoiZZzkSMatBIlEj7Zh7lGMnmTn/Evbs68K5I+7l1M4fuBiWKiDtWPx+6s1U1bXbLzLu98YYP/hxjus8nw82DRWPxmrOHPF3mjxxqiUN0SJMdkkFp51yGzPm/IJ/vnkF3zv1jy53TL4SYSkXiGI6LAtLOT3E+xGTl3S+4LOOBvAnuf2Sx7j+sUt46qmuXHvtW0yebMZz0qQjaSt/+xv8+9/wg1Ne55wh75EAGqMBGqP55Gf9ZwRt4XADgwbNIZWqoG/fN3j9tWtdRWPs4H/RlP7sHo2qunwenno5XTts5KThz7rPxucRx4HFH17MivUTcORp6J9/DwMK7mRR9ccf0yv7FXplv+L6XAcfP4TH37uEeUvHAnDcKcsOqYfDshyOPtKsOWFlQZZtyl2VDyylpVs5/fTHmD79u0yZ8jemSITw++OnMXzgMuCbpWwcUs+GFixLJr2ttvoy0IXftlunSDZoaMRqJNM2yoEWSFPLMyEvtESiUdrWl4igpX2lrdq0bRM28Xhag+j0dagFt5R2WvPS67UMfFaW++JQ9+vmDQYM5lcCqHrTdqGEWUoESKr766twhyK7hRGwssYswFtrzQK+etM+2dOMX4UoX5169DDXmJFBI5KapzTZckSc5gXWSLFcTk8Zryz5XC3jYmK7O1ImB74uaV7guwWMtkLJw2TRrZftbo+Oq7kGj2enG/e1baNUpFIaVtGXvxltT9K8eKKibGgB62F8VjHHL11qrN5w2IQalP1QkeDmnJoeqaDI1sRQ8bge01opiYpV7A1XcuaYf7B65Qhi8bAL/NSXUEoWvVUbj+f+Gddz+Wm30r5gm0uP74azWpDNaVqsph/rA6nkUrFkkqa4j4ZIHqcd+xylpfV4PF78flUAzHzYuaIXc+eewVFd1nLdhMdotGwanABpK4ltOxRilJ2iYIS/XHAXU9b3J570MXXlMB587jIuGnU7IcuEA5pS7+P1JNjuaCRZ4+GSdirxeL9f+ErcEGCe/K5EYpJJIZZhOCxKfNAcH41KGKXRxPODqRR1dUV0a7+aAZ0/IGRZFLaozJlIe9hTU0bHdmvJKVJV19yjioquPPvO5ayp6MOK9SdT1m41p598G1FvEg3MGjF9KijdTteuH7Brex/ijuMCRV0OiTb06EEdilzIbBIcRUxSoT3mXqxdblJ3TzzqGCaNnMelT3+buroIWVmfvMxu3gxFRXDhMGNMVEQD/N/j36ExkseAox+lKmbGNCBmhuOYtSydVs9G3K3Vodh0Db1Go8JdEfdi2zWMOfUmdlX058ieC2iwbJC1NiAKlhYqzMImFg/glTBRtDGbB6f+hLqmbPZUl2CnPJx30hT2WPLs2nF8vgSWleV6OTR8GrbMve3sjTBt4bksXz+agZ0WkundQEHGDk4sexvL6s4HS8x69/1RjxNP+hhabBSzDSuNota9a1dz30hz7fGPEvL5mL50LEG/jwnDZlLeHLw0Y2BZJCyLBpqVe/VfJeggfdSQvobzNssemq0iNWZSmsUi9zul7zBzjcm4Gb+gpKkHAmqm6n7mHiYSPpcfJZHIpLDQYfToR9i2rQ8FBR7KynZyXM+1BwVI+XWTQ+rZOCyH5ZsgPl+cIf1fBiBTFRqxcDUL6theb/Lo9F9y/8zr+dFpt5Gfv+XjG/uMYgvGYeYHF2AtOZchQ2YxdGhzufN9+wr496wL6FyylesmPMrLi0bwwoLROI5NdriOq899iMJ2O9z9jyrdSlGhOb5DyWrunn05Nz99Z6tz9ixbxNEnPODWKDqUYh0AQ9C9w0q6DJgnn8zCnkgkef31q1mxfiQdS1Zz1vDb8HnjJD61qNWXx1rZtnz9p0lLy/zx18aweVcpQ4bcSWnpcqDkoPUpM6OSnt3eapEJuL80RcM8+MJVbNndOsspHGjixvNvZ+nmI3hp0eksWHNCi18dTjjhTYYN+3jCM8eBaQvPZd7y0ZzccxbfGvQouyuNEdW2Lyf2WWj++ZSMbttyuOLkZ6lqyua190bRq+Mmwt0/wTXyNZe8vN3k5e2mV69DV6H2q5CvJBslLlqg3//xJeabLV+Nxak+FCaC0eajaXVxins7IWDSRK18ryWSFTyniGi15I2XIBAw3odGuc9KEqZ03Rrr0+i4llxPZGbSvbuh86r8yCzaRd1M2piGdnaJZ2K7pMsWlBqLRMuMrxDUXEQ03Z27jRdhW0StQZOn37WrWWw2b94qV2KuKZJjzrfXnyTo8VAPRN1ib+Y6bBcIqe5wM36xmMlij2i8M2KsJp9PfSLGBtgnMct6Ie3ScFPMNmEH29aiejnyWT0CETddTT1VKqlUQrbG3jzhuOMAeFd+b2Qwn08E5OuPybadbGUM5F1jWbEWRcf0Baqejrj0SS1Qtcyz5PqkQJ1Yfo7cw0a5d27ipuyXmb2Pi8bdwtPTf8kDM3/BVWNvpaxgq/tq03EMOo5Lna8PkYKdG8SbFPB4yPAkuXHsY1TU57FyT1cWLDidQvs1Thpg3O4Z3t10KNzFtooO3DH9QpasP4q+PVfQvt12Fq8YzG3PXc6Pz7mLiFjwC5qa8Mj8O6LgHX5xSgUrd/eEpBBbRXJ4a8sEkvPSnHn0zby/zYAy1erXp8pKZ5BKh+jQ0aD4nYw9+H1NxLOM5ZiVZazRUKhUxlHSV+W5zMgwI5LQtaBxn7lhjvFCJRyHqFv0z262mrHcOLime/v9XkaP/hc7yrvTtcti4iSJYxOVe+l1Q2jmnGEritdKYWFSmZUdU0vLZbsZr7IuBdJmXckBJ1NCKxIbrpJpE/JJwUKaadAK2d6i1U8WfVLXbEuTk7WRrl33AZ2wLDO28biyWyo1uDnC600RCKgXUddUZKtrqznW8WnhRQUHC/BdagN5E1k8Pu0KKqpKOO+EmWTL+uABBnVdQ8+c3ZxUvI1jC7axu66ApJxo9Z5uvL1gBLlWgkFDZ5mxEe9heweee/ss5i0fyYQBb3PjCVOwrGzEOeR6Tx6VtbdEFPhaKZlbLOHpWgHc1/pyaYxmULGjO0u29aVd4W4KS7bRIER0mjkSt0IkrAR7qSehYT9hN7WtUtlXw8fq6a6WcTF98/v1faH0BOLpiQo2Ru5ZMKgePwX9J+RemfdMLGbuWSKRRTotrKWW3gNzvesXm0rPJYMGATB5sim8OGnSb/gmiMMh5Nk4LIfl/yfJy97H5af/lftm/Iq7Xrueq8beSvu88i/c3qm9PwCg1hfk9hkTefndsbz87tj99luy/ihO6L+IMWOfw7YcevZewlPPXcGDU64iP/tefN79+Uy6F22gKOdDUHbOZJLizO08/+HVvLLsdxTl/bBVOAqgon4sq3bdQtrxgzhZLCvFiUfdS9cjv1zyrE8Sny9Orx5m0U4dwCGTTPqorOqI1z70npuW4vdDbS1srigiP7OB+sYOhIOVBz7wS5Bp75zFrqpSrhv/L47quo6wKAIaUlJteVg3UxMmLsr1eP9Cgr44M+aPprjTBjqVmXCE48Dz75zJzA+MovGzES9g/QdvnC1V3blv2o00xczLv0PBLn448X7CoQifDsM9LF+1HGLPhrFwk4IDiMXUitS4mZacN9t0WkFoiukIkU63ttQ1bTaREOxGwljkYUmrjLWhX04L050Sa+kCavuluJWQD6UdzR83x1dZ5uHPE607NyeH9vJ//0LjgaiSB1PLktfINiYauRI8xdSTIdiMDgIkLRKruT5trt8JmnYDAXOekhKTd+73Z7Ta1nlTNNg24AOn9a1wHMWutKabVq9Csl49GUouUynjouNmfg+3oYKOOlqgK1/ay5bPStqUbOEa9khbGu80+I54XLA4Uu6t0a1+oBiVT5fJk029jMWLDXw1J8eshGpVKApe549lJQhbZrrnagosysJoxiMh8yHqFZCy+CxCtCbziqdzaYxmkUzXkR2udlMgFTCqWI5MUTjunfFL/jnzes4dcRfZ4Wqy/Hvwe2PkO47rhUu0wWxExLPRQbA+vbWyp+XwyOnP8lj3tdRFQy5x3bvrB7Bqa0+O6bmc74x5lp3ytvWGGjl7woNMnXIZO/d1oKxgO422TbGkaBdKu750moBSdieT9ClchDf4AE9/8CPSnn8xbtCfqUmYMV27qg8rd95GYXAF3XOmukDqtfVjeGfZVezcdSPFuc+T1+04uTfGYszPNx61cOtSMREAACAASURBVFgxPplyz4TwLqcUPCHSvkZiOTnEGhvd56rRtt2Yr8eyyJR7aUuKdZrWad2KgbFkriZkmQo6UZJJH6/P+Sl79nXhRyfeT3vbpkhfrHKWpHAwJOOCr4kkDW9DqtmzVRdPyb6C95DHqZ5mD1UmkJDna/LkmQBMmnQaKtdcA88/D9c+eik5mQ1EYnkcPfBp/P6OMkYmFVSfm5QSqskaZsoCCMGgVm31ComcT1k8XYi7bCPStumwzyOeukgWpfm7GdpVuDB0DOUo9WxpKnyeUhBYDpcMepvZq44j3phBwHEIpx1eeedM5i4exdgj3+G3w5/DcnAZUQM5AqYUrFpQQOrFQqCnpGUJwbytaejH429fQyjUxIiTXsbrS9Or62oaQg4NaV+LshdmTbKs7m4IMJlUVaR1SU7LUpC6epMFwxKQRASZn6mUrnOtGUiTSV0vzb0ISTaP3qNYzFxjPG6e4XQ6H69XqQ32Sh8E2yL3Tp+lvIPiB/j6SIrDqa+H5bB8Lnlv5XDeXHwaDRGzkIw85lmOEQzHx0lB9j5+cPot/GvGL3ly1g0AZAar+c4pfyQ/+4sRc3lsh1P7GGLj3aJsnNR/Mbe89H2WbTiShR8OolPfhe7+2dk1XHDGPTz4tE1FTbvPfJ6TeswBC55e/CNWlo+jY4dn2bp7OMt23kBuaBmjyy7HZze6IYN22VN4a+c/2VRxE7kZb32ha/N6U+yrLKGhKYuDszy1lmTSx/Q5P2X7zn6MP+lhhnadf9DP8Xmke3dThG3IoBQVVfmccMLdFBevQ3JbDqn4vAkq6/LZUV1Ih7zPpvSrBCQUs3FLL/r1XMnmnV2Zu3gUY458lx+OfJ7/hMpj675uPD7nGsLBRr5z3l1kZ9Vgi6LTRPAARx+Wr4McUoCoXxA/Hs+uFqc3SGlo5s7X+Hgze5tqmXFsW1PvjIbqTZvFKCRehBzZ6vSLioW+y14nbRmN1OfTFCXxbLi99LTZGk22QTNpJMUvZdvkiMdCrYm0ZKFkydavRbgkAFjbYLTriGSpbFm8GIBeJ54IQGmuiSdmiqbf4JU0woAZJ0sZBCX7IGYp6tsnHoc4zZnwquVr/niWu6/5bNqwJbc9kTAAxnTa4EJCHuMXL5MXmVJDRzT7R+5DrbdC2lFPk6TYWmnXU+U4qu1rBoLpWZPrU2svPS4HwEMz8PHTxeBIgkFjITRnQph5FpY0TRcXbtkE26Q1Kn24a5mKRyJb7lmB8A3U1xbQEMli6c4evLrgHEpyKvjO0Cm8v+kI5i2diJX00rvDCgLBRgqy9zRTpMl5sjL38MMzb2L9zj6k0l7e+GAij825ke+NvIneeWYM1RLf15RJdUMRfgva520hSzI9lDhMbVQ3VVaL6HkT/Pnsf3HDi5fyxKyJjK1JUVa0iaZ0GgeL+UsuAOZQkFFJRixGL7nWQkkVtjI82CGh4a42o9bkOFwwaAnPfpAiEu9DZc1E5q/8Hp3y13Lp4FvI3WSeP41d++w4A3Ne4NXG4eSns9mxyeRKb8I88926HWHGtaALAPn5+XIP1dMRZvjwrTz33CCenPJLfj7xdtr7jCe0Ohp1U7vBoVD6n5Dx0kJsGhTxeRsoytnten4sIiSSfl6Yew07dvbl0mGPMLTnfIok3VkzhiIyMW2xlHWaWskk6VSKYBV4JHNOCdiUZDAu3pFK2pYV1Bnx8cpTr15w2eUPE40G2bOnHihzsQdaX0NxUWqNawG9VAqSScVQqRdPMr08mnUlBePiSqrWutTkLrn2IYNfY+22HvzPs1dywZhnCPhkDZLfQ06aTkXbaCeev1K57giQk1vJ2IFv89qSYWR7kuSGjTfn5H7zSTppdsjzH1ZuCk01Vgp8WXK91ZIZJ563NY39eHzOtQSCMc4+9xnICFGXDmE5rd8Xzam4us0W7EqR68FJp1WBUk+u+p/U45MnbQkmxy/3NS5F79Ja60RxYdJ1j2lX+UmqE+Z8STdCZ9rx+WwXt9RM4S9eqDaejYNTlvLrI4fpyg/LYTmALF13HM+//l0cUUkHdFnBdWMewOtJcXTnBXjsFHNXnsvclecCcObxjzGq/xv7tZMRqqdvV5PYW5K7gafn/JZH5/2ea075IyU5xsNRvrcHD879FTEhcBp95AsMaffZPQQBX5Lrx93HrdMvZ+aii1v9ZllpCnN2kh36/MuYzxvjgw0nAidSVrSOSwdNJuCNHvC4LyKdOlVxwQVv8MwzI5kxfwz9T3jsE/ddtHoUr79/PonUxyP5Txv4DAP7vQJAIunnuTnXUL6rL+cMe5ihPb9aj0ZbycxsIjOziT1fYV294oIKvnf+3Tzy/JU8NOXHH7tP5+ItTDr7bjKDrbE/lgXfGTmNpANzljYnrgdd0PkXk+nvfJuAP8q55/6brKw6WlKKHZb/HjkkANGVQj+9a5FhXDyiwGjhDaKRRtOaCWC0wnhCOPUlVppooQFmC4LXp7TiWtBKzqXZInpRDaJaNiTMYl4fUA58taSMtdAo9pAlRFN+DJmOT+lolYcjJXHzVIMbt9XsEy0Fr5amJR6OpFCcewWjoZprP9l6JAulRDwbJWLJ7pXYZqMWQZPzqTVVJdp5HBuP5cEGvG1oyJMSbW3mR9TrNuPk9RqNPJk01+s0GRruDtJOscZkXSZNuUfye5O4Ths96kFRLgMP6XSNHCL4kKTeZ/XI6CK0Sa6ju3z+9JfY5MnzW+2nVnGJWmEC+AvItStfhdey3BxDt0hXqnXM3aueD7E2Vomi0afDesYc9To5niR9SjZQ5DHHt/NZ3DTqEd7tMZd40s+ra0fwyqJL8FpwQp+5rqdEs5rc82Tv4MxTbublOb/ljjm/ZcTAh0im/Mz74DJCgVpGHHcHcxZdR3UizG7pU4a0odUwNUNKX7NBxQpV7uS3x03mBYKkHJ87mr272rz04T6suIVv924aFHIfNO17i714xLPhyzQzqE+1me/3nHMLFfX51NlpepdsoCiVAWRQ1M/M4vdWm7Lm22h2lVot+hYTP8ymTdtka2Ld/foNNOPYzliMWVnmGejUKUp2dozqRI4b28/y+UgIv4GNxbIPRzLjvYvpVFDOmcdMI+hmFphxenPDUGYu+Rak0wzpPZvn3jKKxqXDHuaEnvNdcrwsfb6UQ0bWncagznE5p2zDNHtCAwEprKcU83J/5y5cyIo95v8KIF+eyJZYjf2lvWzVc6HXo94QxQu4yAnZr9jN8EokNENnt/xmvH6plKwVccW/5UpbirUyV1Tps/DkwXcvncvevbkuxk0zA2trG3jzzbH877SruOqce8gKtmYa7YLDDSdP4ezeH1AV9ZMRiFCQs5tYGvYC2/Z2pLYpm9ysGo4oMn3UZ4S0rAu6jso6GImHKCn5iKwsG8glnVaPd+vyFpalGD8F1wZRtIl6yRXn0vyGSMkxmn3WGj8YiwmPhngoZEknkTDel0BAcHqynjal9T5oKY5sabc5t1lxdMrZod72bL1u2a8gabNiUzemT4chQyD/wAlNX2s57Nk4LIflEySdtnh63rfp3v4jrj79HgK+BNmuG7958fDYDv1KTJguL3c1N718B68u/hbH93qDT6N4yM3eyWkjbuK1N37P9Pm/ACAncxdnDZ9ERqiKYKCR8l1HUheZT3bo82EXfHaSzhkGs6FHtsvs+rnaaCld8nbRJW+XcLTSHMP52HObM26rO5PMwtu/MLtjIJBk+/YyKmpzaZdjXpYL1h0LgG0lmbboIvqULeenp9yF15NqpqSWbceiD9m4pw+vLZ/Iul0DKK/oy8STHuKEngs//oSHxZVwOEbnzhUusFQVnnR6HRkZ9bzyyoXMXzWUASe8vd+xlgV9S7e61XdrZK5s2tWN26eYeW6R5rJTnmJ4v/f2O/6wwPrtHbj9hXOpqM7nz/+GLl3gjTegc+cDHfn1lUOC2VAd0haMQ5FY7AWiySn3f5UyJio6X7a6iPhJIenthDUnXtoqlbbzNSdfzrlLVNKUaPSNwlqpmroyaiqJUECyMTppn2WrdDFKi9RABnGpkFgrfclx45qylevLldhjWLYh6etoYQBVRHdOT7MN1JltnbwltBqErtmqHSonaNSy8GDyTNzSXLLCK8nUCsfgIDY7yoyXK1slBzcWUIHsXyDfFmlM1qvF8sTq03EVroZGoVjXaty2neNaGppdFArpZ+XZMPsuWWKIgAYOVJKgA01Jc+DSpR8CkJ8v4ydxVo9lEYkF2by1F45jk5uzl7KibSSt5uLPSTeOb6RJmUDVunAcUmmLRMpPtw6r8VgRkkmw2tDau14FyyKe9PLgOz8lEg9z6uD7qEhGyRKeE53DtJnjdsY+zjzlGurqO5AGcrO3YHkiNCXhpKEPMHvez5n8/BWccvzr5HvTHNllPU0+M5fVD6ToowzBGlStMtk5ui4pnVhuOo0XY2V5vV4smYfhPLHcPTZWvVjGguMI5Zr73C1ixrx7VHASOi8kk6q0Tx8AVq9dS8fwu3TPeZ61VT+hu5WiZ+E/qNvvnprjV682fY3HzWQvLTXt5OXlM3r0Op59dgDXP/Vjzjl5FrW1eTz/5mh6d1rHkKPWMmuxTc+Oq3DsJAmn2TORcBySKQ8Pvn0ldZFcCrJ2Ul7Rl4tPepDjus8nQ86tWSuK31HrMyJrSpVs1QPkwcz/epoxDDnK5yPbiGYrCUcIQIQQzawb+4sWHly40DAQZ2aadSGR0GwqswI4bqaZ+mTU1E22wG8oz0ZIPutMNf0Kh5UXR0HCLmNKm89dZKvVXDVzIka3bmZO1CQDNLYpXJntOOTLg93QhpF1+z6TXTOo73wWrxnKg3MupibhY0JfQ/2tHrgGwS4oK6/HgiCWW81Vz6YswJox11z2QtVrXSn3ueUqmgsKaiFAuXr1aqkHMql4Qq1c2ySfzZqfSBhPsDLoOo5Z2xsTebK/rq96z1LyudbFyylbabZgGXU+PjOzkpcWX09uZpxfT3yWLE+KP02ZwIgRId58Ezrpy+m/TA4WXfl/WKvwsByWgycNkUzunvJzHp71Yx6Z/UPueOEGlqw/7nO3Y1kOAX+ElZsG0hDNOOD+728/mo0VAzj72Afp121/i++TJOBvpKhgPUX56/C1wEF0KP2Q0SP/zr6aQp6Yfgl3Tvse764+9nNfx6EWy3IY0u53dMl6hY8qryKe/PiCcQeSkpJ6LrxwBpFYiAenXchzb47liK4buWz8Q2QEm/B6Eiz/aDDRROtshGTKw/1vXMXq7QMZ2nsWlfXt6dVhGYO6fb0wGv/NEg42snrDAGobD/xcqGQEzatm8Zqh7ndvLh9x4HMFGtm0oxdVVQUH3PebIMu3jieezOD7o2cztN8ahvZez63ffZwdO+DOOw98/NdV1LPxSX+fVT7Vs7FRttma1y8Wg0c01wq1ltXak/3bFj3PtSzytCiSWNZ5mjUgbea1wRhUqoUvx6VjrYsrNYsgpeVTsI2m67juc8UmBIlKobhG0ckrRG/LEo1aXe5xuc48uX61IdSiCh5nrBBPQLwHEh/MkW03uRPqpdCKhdrHKGbMwkChtK12lIKhe8s25hhtekNK+UmEg0D4SWwZx6BYF1pErknGVSeFckAo74hHPEeW33g44p7aFuyFgmkRLIXiSqpd/IuOum4/Ph108uSn5D/JOBKshtcrcXM7SUMkk4en/pTK2iJ+Nvo+2udW8PD8b/HU3EupbyglQxDyapmmHIce7Tdi55hsCbdepVzf2SPv5YXXr+Zvr/6MK8b+lfyAoPllv6jyLaTT1Akzbknhciok5Uazd/La1PJJp9RiClAlL8uAYFyKZU7v2tmD4swtXP2931NdW8Qjz/2CuoSXXXJOnZF6zwNyzt7dDapj1UfG+houzLb1Ph9e28Zj22SEQjhyj6ujpt+puE1S8QvSpnrIMoWHJpUpMW6/6UNmvdmzOGVmXHdhe1y7YQNl4YWU159JhuOnGf2v1rgqVcaztnGjFn4z997jMR6Odu08XHfFLdQ3ZBOwHIoKKsmU5eaCsU/wzIxLuG3WdfTt8a47Hpu2HMOWHQMYOfgxBvSeR2Pay/INo5i65FzGHvO8+zyqb9NOq5UrnhGZ0zWynzI0eFqMua5R+py5zLryudayXGyVjwifhkPS2Z7jlwqjbGLTlmGkJKMsR1kr00nK2i0jEf5QxqidbItxHPMiTqXUw2Ha0uc7HDYKn89nLG6vt1CuOVPaUCyX69M0G59ccTxTfjdXfOb453jxxYv53bM/4RcT78UbllFyHIpkPAvaeA/P67WEk0q2UJtSjEaanHC9u7bq2tIo495Ovv/NiCf4zbRrmfriRYwdNJNGq/V7QnF1HmVNluPTwTj9ey2n0bPDxWR4BGvVzNeUI93WLD1tVT0guoaZ45VxOiRMo3FZwxIJpZRXLhTFbChztWZgJmj2Ehniu1DKYc3WQXwU89MhfxMn932cipp+3Dn1bApyavlu2U76dNjFb7ObM/n+G+VwifnD8o2RhkgmD029hsraIq4Ydw+D25uH+Rdn3Mvfp1/Oy+99PDgv4Ity4Rn/oKxk036/dSv7kHNG3cPzs69hefnx9O79xpd5Ca58WH46b6+8gszwPi45/24K8ioOfNDXTEJeE5JcW3UZVvFtXxi7EQpGCQWjrnKtb/wjei4HHuPZmd9h154e7v6WlWbEkMc5qrdxz48e/CjxRIh5q8Zzcv9XwPvlM4YmUn4WbDkbC4eMjM8Oi9tb2ZcFH9xAJPrx3qBQoIaTht9K9hfkZzlY0qlTOeee+yQvvXgRf3vucv54wX3khj+dw9OyoCSn0gU6a0gx9Sn4H4BO+bv50/g7uOHla3n+rYmfq59rNhzJmDNecOnHv25SU1PK1LlXUt9klHDbSnLWwD8x8YTf8MyCu3nx3RP57ree+4p7eXDkYGE2LKfZ9N9P+nXpAkBK1DLlOrBbWObQbGmo9ac6pse1EHBz6e1P2Edzt9XS0EyRhpR6KlRTVRY3zdE2GqhXcrd97sLWWuuOO8pf4aX5ihU1rouYMBEKalzj+hrXLa8y1lw3iXdniEfDCgpuwG2mNXufrtb6bCbafG45DmqZahd1H9XXm5SdTy1sxSJohUvZZrWJZ2vX3GyONlkWGmfFsppja23eMupTijtqhYmnJqieDTPaXbp0bHVcebm+cAUvENEKswnSaZuqylKSST9lBTsIByLuuOs8i6U8pNrM0mTaZltVKcm0l5KC7diS0UKL+ZVOe9ixpweFWXsozaxp0YNmD1oCqItks6u2lLKCj0gKQl7HVfvgnl7HzfEQicTk+gUJH8+mprEDIV8jsWQQy0qTHa6luqGQopx9FGSql8CIV+v4SG5/WjIkLInj6wMWtSzKa2vBsuiWl+dagCppmrMqXL+ftK3Pg3JRIPgYLXOrz66CAhslA6su0YlIsgSfdzdB31b+H3vnHSZFle7/T1VX557I5AAMGUSCiIgSJEpQBBTRdU0r6l0D5rDpevfqrjljzroGFBVUMkoQFVBQUXIamBmGYfJ0T0/Hqt8f55weGCQpq+vv+j5PP/V0d4VTp8459Ybv+31jylIkCpYNLd4KM2GT7sPvqKqPesMJxH88UbBrfz6FSMSGZemJiqeaFkPXTSxLZq5h4g+mUe/PpnXmFpy2/S1jtZYkJnSLPth3yFiAaUEgnITT3oRPMRArLI5lgaVRHhxBIPQvzjprDr17fweMBOCOOw4Mg02TmI21n1q8svQ2Uj31XHLa02S4xXNOle0qbvAxbcnNmJZG/46zadTidCxYTjQtit2ucByif6MybaKxUSg6Hk+W3Aokj2GoirHC06Fq1dhsXtkFKntDrZty3NuUQi6yjwK7XLw0cwpZKdX8afITFNoDZMoxkKSwd/KIBpXB1mLN8MvtnR98AMDDo4RRUKiy8eQavdtyEAh7EplwDlVfSJ4/Mcfk/u9tOZE3lp5Ft7YbKCoQmDX1TE3LIj2lkuxO6n6EZ0IxhirMRjSqmKdFrZ94XGTr6VERJtUVTkpTWJh82X9SeUjMMeXhaCIeF0q4s87i7cV/x6HHuaj/IyS7qnltxXWU1rbjrL7/5JuSKaQl+Xnhd28BMPzxO5g8GZ54gl+leDSNDof439GnD19J7qlDyX+o3vib/F+RcNhDNOYkO303HueBtT8ADFs8AfBUotugTUYZ2/e2pqExldTUPfsfZEGdP0Mef2i93JDUyLWBTJJ8JfsmrByV+JsycdiC5CfvJBJ3UtbQhtqAaIP9MG34TxOPsYemWCbRWAYu+67E76bppSncmYMuHfI2A0GTnMw9uJwH9x+LMF18H512/xBpPG4QCKaha/FEEbYfLRZUBzKpC7bCpkdpl7bzgGcSirkJhLIY0Pl5evc+shon23cV8srS80l21zJ19P2keOoTtHwqdGwZVdw07B88tPg2Fn4vOFS+2zaKIcPvI+3HwWJ+srQr2E67gm1sKu7Krr15FOZv/rddy26LkeZpSITBnC2UDWVoqWKIY/osQ9cs3lh2JuuLu/7gOftVf0L//p/829p8KPl+x1DCUS/Xj7qFrKRyTNPkikH/4P4F9/DVtvEYjv33LyyE6dPhyiuhR49fpMn7ybx587juuuuIx+NMmTKF22+//ZD7mxyaZ8NxiP/2lUMqG/deeikAtuJiANrJan4uiQfYIgdPsdy/Xm5VVC1DDqosy8KnalDIrVqCVJxVpUPslf8vk++dYDCRVQ+AV9ab8Hqlt0Uig3PkgPWqgau4NOS2xFTo48xEHRBVKVRVoE2SjJltpIavYpgqTn/H7NkATJXMoafKlcKXI2OOfolojyomVYmetylPhvhfVagNaxqapmHS7NlRGrVaBusUA6j8vUR6mYqlBVopvxvymajsnt7ye7bCZsjz1MoslN1yW60sfMWm6nDgUXVkbKo+i/IwiHNUymPLpXWQ2VqwS+ZIVpAr77iDfUXVlVDIih07xDPLdG/lu439mb/kIv449q90SBLPoa28ropCxyyL2oRHQWxVBd4r3vxvNM2ibeZqurZdTVZGCZal8fEXF1FSMYgze83j3JNmkt9CgaiVx9fJ7ftrRvLR1+dSkLOU4Sc9QUlYccQIy0dVfAyHxRgpLq6mZaZCqOllclqt4S8nCBOm0HARMe1E3U6cRiFhVctE9qNLMtL6ZLZPROIoyqV1q3AjTT4fDy5Zgs1m46+jRyfmSkTX+b6sK1/v7pzwljV7Nky6t/uKbukC/6GwPz557epYjKaok5e3jiAU8VAj67G0CotlZf3Ok7HraRxfcBnJ7irKcRIKdaKs5AVc9nrOzr8Cn31PwgulPGcdOnXCH07h6S/voqYuhWt+9yzOPIWXUsuNxMU0iTbX1Yl+sKwqQiEPJRuPJxZ3sHVHXww9mWtHPkj7rPaJl5ISNaaVVy66T0YJQEyuJZFIlDnfns+WvWfRrfBzdlQcT0UwxEWD/ocil8hTa4jH2Vl9HC9/cQ/pSbeTLCvONhyCYeCT+dV8tOoW0r313Dj6ftqnNgGOBM5HuWxchkGeu47HJt5CzDRYX5nFU0v/zNJFt9Gj4yoMW5Tu3T7D52kgIjE29TITzC9ZmiMRhVFQdYrEfirM4JRsxTab8tYqxlG1Kjdz55imxnuLJrOpuCuTTplDr8KtxE3wKy+oqlEj+9Evt0GlPCn8UgsvtcJ0JZgwWmT5pbXgWNqfC7W5bo1d17my9zIm9vgsUSU84eU0LV5aMpElK4eSQoRu/b+QRytPrlf2iwr1KN6SeiwLtmwejD+QgVOuYZoRp2fRIhrSd8vjFJOruteI7P8ohimyTwxsGHqEzmmVgEEI8DripHirMU07MYT3V5k/Tw58jHNeuZihQ1P47DPorCbjLyDxeJyrr76ahQsXUlBQQN++fRk3bhzdunU76DGH49nwHeK/feU3z8Zv8quWvPQy1hb3omLtWL5cP4JzRz7C99tO5ptNgzit1xzOPemDI8Ic9G67ko/XjWXXnl6Y5rFJ0rLpJm49jG78e5K+Pt96Es8s+QPQnAKuxDI1Vq4byrWjH6Zt1o4Djm2KOvn7Jzfx/d4u6NqBWAinrZrBBZcRc69tPqapFzEzmZzkD0h17EDTmq0a1cVOI4zT2Mvd4x/lijfuYOXaExmU9/0R3U8o5GHevCuorc1F12L4XH6mjHiI9plbD3/wQcSyYO7a37F00zhOar+AESe8SEVda15f+jdeXfY/XH3q38jw7iEcdbNo48XyuntpTkA+uBTvGQ3o3H7Gg6R5G/Epk1YpP6r4oQI32GwYQHdXBbeOfpDHFl7NZ2tPx7QMvtt+MlPGPYI3SdGVS2C33iT7ZqP4HlVAUQEmdjjayu8yHJ2oDCy8Uc3ppOJ3n1nJh4vOZ+2GvkzuP4ff91sEiBeKGgUqbKISVhW1QUgpC/J7S6VBhUeUkqIMPkUXqID3KlVUlQRQioQaQ4WmiaZpdNJjGDJ01iTJy8rsOnePnMFtlsaClaMwgRH951OBAm6Lq0UiZbINAtSZHg+w8IsL+HrjEOEpQwHNDbaVDuaKMx8ixVtPrVYjryeTHySA3h4PkSqNsFLDQNM07DJxIKBprN52IiVVXenc7nPqGv2s23oCr2w8ni5dtnJdq1o+vPgV+jw+lddfh//9X34xWbVqFR06dKCdBJ+fd955zJo165DKxs/Cs6FgQ/3zpNdAjhpHkngQfUvFVqHqlSanGqY0/ExdJ0lVTpUPTEXxlYNWIfVLJN1zNCpiZ4p1zuUSW4dDaKS6Ls6QJddY5dlIbqFdq7huWMbeKqhCDX+lvSa4+eWAblJWrzyHXbZZIda/i+yPD+kgb8YjZ13E2J/ZUHGM2OX/yvOTRHM2ikwnR84tasz9Y+oqXpok26J4ShSGI9ACy6E8OlnyOJVLoKwLS+XCq0VNFQtwOBKZQSqj3yvPpRYdldGvso5ypUejJwcTcdzKlcIKyckRacZCkwAAIABJREFUk9SladjlEtNkagmLSomqf6JZVmIhM+RvEXmfN532JAA7Q2k8NucWXp97K5alc1bvuZzb9wMK5CnVQqf6JSK3gXican8Gj86/HQuTAQOnUaWnYbPJyr9hYfFEo6K/d+0q2aeFyj8nfDDRmEm1P8pu6Zk4Tl4j2SW+B6tFY5QbuUzhkqLiWayP7s/I65KLmeHx0Gj68Dcm8/iKCzE1iMUcfLX1FFrnbGHoqJew2xWDojiX328wZ86VPDb3es4Z/Sj2rO2JPg9FndyzeCo7KzsyaNBbFBV9BwwQbQksASAlKLJMvktgb5NITZ1HONyF0rrfs9iookurp1HonOOLBPFYZ4lnatsqhMsewbDUCIfm14nibVFMkjU0NXlZOO8P+Btacf3p99MlbwN5yrMjp6dfeiqUF0ffx6OxdldP1pQdDzR7v6x4HH9TGpvL+tK73TxO7/k8oJObWszkQf/LW8v+m2mf3UXHnC8pre5Mlb81w3reTZJ3N83KxsGLhVlo2I0Qad76g+5zMGnTahf3TrieoMPBtoqOPL3gBp7/4Hr+cM4Dhww9/VSZs3gSazecxLn953B2v4UcScxwb10Wy9cNJBJv5rLJTy9lVJcfV7Dvp4quWUwZLvAQi1aOwm5E6drv4CRjlkVC0Rja7UPO7DWdQsnyutF/PHfNv5EnP7qJq854EHwNBz3P/ufUsCwBE1q97UReWTKF3MytDDrpNbZXGjQ1teLtt8/iggtmQPuNtGtVi82WcHb9YlJWVkZhYTOmrqCggJUrD03Q9otlozRGHHy2qRMue5S+xi5sunX4g36T3+QgkpG2Bw2T95b+jlvGPovD+HE6dIqnnqlj7uelxf9F1/wNnNtnzhF5NKr8mUybfxuRmJNzh95NU1Lt4Q86iDgc2/H7R7KpciWdMw8PmDpS2VTejd01xYDFNzv6Jt4PHVt/y1lDXqDe7qDZGS3E56tn7NhnmDv7cmbMvY7C0Y/SLms7oaiTBxdcz8697Zk84GkcRUeeHaFpFtnZ/yAaLaC4bhJdWj19TO6vqcnL3LmX4W9oxfhhj9Alb+NRHf/5llN5bfmlOOxhDD2G1QIaelKHmQzt8S80rRk0mp1azPmD/s4HK69jQ9kpGLYIZ554Pznpnx3xdQ2bDQ0Nj1TOFeZAhUlV6C/QQjmyq/CqruOMxeiWtZnJQ17mtYX/RemeDnQqWo9X7ttNep0sSfFdGhBenvKoMrqEqReLCRPA4VC05uL1oCjAnZownb75/mRO6raKs09ehIWWMKgCgLOFh2EvUFGTzTMzryUU9uCQtVKiMQe6ZjK681Kxv8JgSCXZ3YK+29MilVYpiwrUrGa88qw45b5JOihcv8J/q3P6MJk67E32NLRi9bqTGdhX4DcqIsKTYVcFPmNx5q26mK83D+G0rh8ypdd0NA1aS0hAZnoZD545jZs+uoZnZ9/E1eMfI8VbT400GKJSwbU7HCRLgyw3Yy+RdS6eW3khHfO28sqSSyjM2c5pI1/DtKeSEnEyaNBbLFp0C99+O4AV7Y9uPP875YfyQbTDLJQmNvwJCsIfL4dUNs6XlvgMd1v+8uylBJp87K1NJiY13My0Bgb22szUIQvoVlhO/nbpRquWbjSFo7DZMFRwUQ5E5aorVhYnwq1jmsKSUPU3lFfBbo/LrYjvZkmbX3lPsuQ2Xbku5T2ojkyUsLKgedir3ATJIqeJ79V6rWyDRPS3sIb3ynjfNsVRIfERycp7o/AXqnKovIq7xTZ5n5Z4pNvEJpPP1X2pOHTCJSn7T+EqLDkZymWbTLmNy/1Uvzvl1pcqrp4akvFYef6YqtirabjUtWJqoRP75kitvFL+ryrLqsoQBy8BIFw/ihvAssTTiJkmOVnbGD/kNWYuvpBH5k7hqjOeaqZLVjVlTDPBaqgq8iqvimIO9dps5Cc38sBZD+7XFmWfqmwoxaC6Jxajyp/JowtvIxpzMmjwk4SS/cSiYpHODItFWmFbDMuiIdAOPfg3IlEfydYSMlJFatsuaann5d1BScljvLbmb/QpuBTNsxpoxp6kSdeleqaKr0W521Vdm4hivvR62V7dnuc+uQG7MZPM1J1cdPofMeX/QZuNEBCPJycqjKoxrWk6Pp/JWWMf4P3ZN/PI3Ovp2note2ty2VOXz4j+08jIX0FNbCwAbrewdpxO4aGok7HqzPYCj5MS8chnV4bfH6Oh1sDbujVtpfclVRaA8MrtHoeLmKVLD6Oq2BkjEjH4fFkfAo0+4jHxnHfvzsffmM7lwx6mU+4G0mW2k1vNO/nM1MvQrWqe6Dori/vw2vJL6ZS3njOGPobdiNKkWHIlnsmpaWgOFzaasVERyyIrp4Lzz7hN9JfcNxTctxdBVI0BOJBcLm4eurDYZ+tPYmNJp+aaM8o7p8UZ0Xsh7XzNXrLUpBp5zv2X5IqaHJZ9O5x4BJI9tXTt+AaG7ceXxbLQSfbub70HQh6mfz6ScMiN0xFm3InzSfPVU1GTzbMzpwIWl0z6Jxmy6OAXX0zkiw2n/eg2HCvRNYs0Xz1V9ekJL0NL+WTNZNZsHsZpXT9kdK+3fvDF2j13B7ef+QT3fHg1j82cyi2T7gPt4EbPyV0+p6Iuh0++HcHSdYNpk7uFC8Y+yd6EKgQORwiXK5aoJxWL6/zAe/5nl4KCAkpKmsddaWkpeXl5hzgChP/9yEngDiZH5Nm4/akpbNudx3nDPyczrYEB/bfREHDz0ce9WLSqG3M/68HUsQu4oM3nZCcdmRvqN/lNlPTqspLKuhyWf306oYgLHD+clXIspcqfyRML/0w05mTM0LuxJx+6ompp+Ui+23ALoONxVrItPIx2sSzaZzTns9lsfgoLp7J924fsDYwAqWz8FKkJphONO/A6I4ny2UcjPl8dE8Y+wKeLL6OksghDi3LR4KdJyvn31RkxLY275kwg2OShMLfZcxKJGEyfPpGSknzSUmuxTPnytTUxSSoaRyt7/RlY6OSmlR026+hYyd//fh8bN3bg2x3j6Ja7LqEEqbCpAtPNXj2MOn8aXo+kuUaEXuoaMmiVVkWbEyoSx7b17MXjaGTRp+Pplr6T/FZ+yqpyeOGDqwnH7KS6A3zTkE5FbWv+MGwaFU1CKY5GhZISk2yvprk/UFSFrFLkdQqzSln29SA6t91Eh8LtbG5K5t13p1BVlYPPV0djYzLf7OrE8NOmM3vBJQCMG/cC9rQwjRKUGmd/TIYCdsakYp4kiwLqydLoispQtpzWahQrrIfyaCgytQbZV34TvKHmlPx9j1WKesfsUlZu7MP8pWdy5qnvY5ceCUsqj9/v6EdRzmrG9noLTYMUCaAPSQNRGWXH5+/kqqFv8tD8S9m9t5DkdIFVciijzencD5g96tRZaM4YFdW5nDH8XxiOOEZUhfxFm3Nz61m/PoeXvunBhs2dME044QR+Uenbty9btmxhx44d5Ofn89Zbb/HGG28c5igN9lGkfqwcWtnIg0DIzvbyHK4+9x1uu3o+0OwOHHXyCvbWJHPrQxdy7/tncC9nMKLv1zxy3jN4nBEUJX6w0YbRIC61V1bZq5eWeSyR8aBYJcX/yh2YqH3ilCyfurCSVBTYqWpjKO6KFuqjQkgnfBhaiBAqJ13tpSokCiutXhfXTtXEsmGTvBBRuQ2UCfCRliFcmBE5gBtkW0IKOS3PXqnaKn9XmIdcTUPXNOHdUF4QadUZsnJlTkymi0lPhMpVN2X/eeTkSpZbZQVmxFQtFbkQqLQzXdZxkSVIvTIkndjPjBILy9h4WC4mKmguV9F0xUPiE/3UVq4HZXIlUDa2kjvuEFlNo0ffJq8lJqVih3UCHpesVxOxUSGtij2qUq1lJbxk2fI+fKp+jbzG/pUkmqtQ2CVKPypjtFXBKHv8mTyy6M/EYk4GDnoRm89MVN1MDlVRXtWTb4v/iIku+BlMGyXVJ1DQ6lumDn4QQ4/x1pdXsmrnteSmpeO23QlAEx5sNj+aFiViOhO1TVQVmz3bJW5Cfv9927YAeIrk4hwQ21CDaEuVYTC86GtKG19j5jdJWHV52MMmhqySqsZ2ox5GBQiax7TokbDlwu4NccGY+8S15Tgpj6h5JUapwyHc8yqDQ7nnHQ7FW9DMCiO8yU5yM7JplSK8VU7plt5uOHhqzgQ+XnsiAwYso32v70nVI0Qidl6bfiElJflcO/YtBnT9hkrJW2PJeWVIT4Hqr1rlwpbfvcrLqeooaRoTj19AqT+DJetOJ2TFGdZneqLEp1oTHE4nhs0mUPUtwI9BOVpN214CjVn0bN0Lr7uJJLnH1Dsm0lKKiwt5++2zaNNqO1MGPMGhltHObdczbtSLgHgi8bjOP5969ID9fK5Grh/zEA/PvYmH3r+JtlmlbCtvi8MW46HzH6OtbzcLNvTn0cW/47UlV9Kl3zMHveah5L8mPs/jb/+R596fQofWW9ldk43fn8KZZ75DmzbfUV7emlkzL2LGrGtxu/2MH/8sKSn7pwHHYkea7PjvlzEnLKOyPp353wzF7QxyfLf3DtjHYQ8eUUg1xXNog2Nf0TQY0W8ucPBMjfHj19LY6ODtmRMAePBBmHjgcPpZxTAMpk2bxumnn048HucPf/gDxx133GGOsvGzeDZ0zcJpj7Kn+kB++5XfdWBTcT5DTvwOhxFj7ud9WPhlb+Ln/lZy5Tc5OinI2o6ux3l1/hX8edSjuB3/HpBcuT+Lv0lFY+Rpd+FM3n8VKqvswydr/obb3oDXWZOI8XfJ/5hBxz2BwxAW0QV9nqIpFuOzrReQ3aqW3IxpiXMku79iT/0ktnlW0j55Hj9VhnaZw/KtFVQFspmxYiqTBj2NTT8MfeO/UTIytrBz56nMXnEF3Ua8mQBYm5aWUDSGn/oJJw36DE2DcMTBi2/9nuKSNlx51gwGdPzmmLVF0+C8/q+jaRZL148B4KTurx4162mgMYtFS/+HD4KZpCU1cOslL5Pd6ofxOzVbCtGA60Y8hMcRwauK9qk2KYAqwhJX/pZ9gy4xNGw2WyKjwxGLkZNZwv1jHubpL86lKZBC54wy7hz+Hm3TqglYDn7XczVfVRby2fcD6TNUqKzhsDBllAJvmsIMs0uQQytZcl0VajR9jdw0+Wmen3cOtYEUXK4IQ4bMpLAwgGm2ITsbxp4xizVrTqJfv7kkJ/sTad+tLIsNO3rz5cZBdMnbmMBFxKRRsEem42ekyf5IE22SvGI4gxKUniDMkyBta39Cx0aEougHmlpQGijvUZI0NkLAlCEz2VCex3fbjqdLx+niHNKQycvewqbiU/mqbDsndf4cr0o/l0ZtovRbLCaI3YBQLJYozqlwGprNllBylYcjUXBOPV9Zpt4uqeIdjt1ccMEcPvqoN4WFu7nxxpH8J8iYMWMYM2bMURzxM3g24qXgJMboXkt59+ORRCMOrjrnPQxN5+n3z2TG4sGJfe22GB1zS7j+zHewW3WEgqBJ/IGRbCMuU5Myq1WKkqymJx/maruwrBwOweSmy8VUVdrLtolJlSlRDurW1URWYKz4PhMdmgeTcr/ZNY2QnICaphD8yGuq7wJl0WTK+gRycCXJ+HQ/GeNStTDUwI8mvDT7r3TqtanAWMF9JpCu67jZZxKpxqRKsJZMYUmplPfVKP/3imsnSysjVfanmjBqMikwmpoQ8bjMP5f9a7VS36VnozaG6ZfPaK+sH6K8KirmrNhLA0Kn3yb1UGWR5vPDcvLJIltgyxYRXlB1WmyWRXrmVs497WneXnwlt7/7V5I9daBBaWURQ3rMZ+JJH4r2tcCyaPt4R6AZH6MWcXW/FQ1RglEnN0tFY8DAN3AkeYnFhNUWDjdSX9+aFWv+RIpvFzcOvguvI4BPLSjxOGCjUI4BMxZjyqkv8caXdlbuuIbCbHDGhcLRNe9Gvi99ho/LH2B13YUJwKKuRSlq9STdPV+KZyPP7c4XnjG7TTzL5HLxu9EovgeBTI/o3fWlJzN/VROT+r+UwBDFrVAixVExSGqa4lsQM6VK8mi4FN+NnHcejwpzyPoeNvFiUQqEYSjPh3jWPi1KdvclJFnJLFkzkdtntMPtCIKmE4q4KK/OZ8DJ8+nRbzVmqI5IxMHb719G8e423D70RU7L/ory3eIadul2t8mx6tc0dlUXMeubSUTjDnzOBsb1eZm2yTIvTnnnWngrPZbJJSf9i1gszmfrx+AzahnQ5QPC0lVuGQYxTSNOsxUasRQ7gIdYzM6ipdcTjbr46/iZPD5/JE+8P5V16zik/BSFLxxx/uDvnTJ38dC4B/DJ56PSLZV4XEefFxCNGawvawdYdGmzhWRvgIvGvwBApSXWMlVNGiAnp5wxY2Zhmvtn2Wwo7s2MT66gbWYxVwx5an+K1l9QNA3czkb8wQNBjMP7P08o7GP60gvxuvz06bjpoOdpalEYcFdFB5aunUA8bpDkq2fC4BmJonRHKg5HjIkT58hv/xnKxtHLvhllPyRHFvY+MszGuGfJSKrhpSXn8MGnIkVO10z+a9QHXDhkAVrcJMXbiE3WLrCORZ7Mb/J/Trq1XcP5w59g5bphmJbO9nKR+13beHDo6dFIiT+HxmAGQ/o9TmrqgVZrXV0HTNPBwN5C0Tic6LrF7/o+y/d7OlNR3Ys0uV7b9CDdC65k194/0RQtSKzJwUgbvi59loyCK8nxrDrq9qd5ashP/ZItew6eE/9zycBes3E7g2zZeSIAmm7icwcYPvh9TjrhU0JkEIk4eOf9KZTuLuKy01/jtDaHztDZVd2OJz++DcMWITOljK17jue5T/7GLSPvJtVTd8hjNQ0m9nmZ7Xu7sKOiOwO6fHBU9yOUM424qWNaGjZbQrc5QL7ZcjlxM5tb3g6Sm16KT5L2KSVIwTcb/F8Saorw7vuSWEr+7nKsYMkaF5uL95DqFouloq5X2wR/iWxEozz3zvqPsbiP+fMFd4rCaGiaIhKUyrGkY3dZGqVV2QRDIu08O62SFG9DIsQbsxTZYfOroLl8g7gTtxWnMZRERd23eOyvkEQJry40E2n2OxuEQfjXz0V1Xo9ss5Emzymp8bWEbia/K+Z8+bvKUonK0LLFPuUs5JEtcR6K+2Nn1VLicYPpC0S/WJJAzrCBxXygPTOW1/PVuur9zqOMs0DEoKz6a3T9NWav2kE87mJ3zTZs+lwcRpSde1xs3hmhIKMMSxpm8RalDBTJmcQ943TKFH/Z2sWLhdKxZMkSfl2icWie0GOgbKgIlq/J4PqTZ3J2/7V8U9wegONb76Czq0QAEyIIk0Eiqa2gquYprXG3RTxdxt9b61TUpmKPauSl1ZKzQVp9coBuNooBCMl7U7H3Qjk8FBudSidrSFh3KjYvuTOUS65FepXdsvDIbAi/qXwOyspQ/BsS6CW9AooxVVeVaiWLaZ7cqt9rWoCYlLtQeQQSFWxV1VyF16B58ijWVStZckw4ZNpcnUQ1yxlqyEXF1UYM6PY1koFVej78CtMh25aimEhtMlulXmI6PPJ6Xtm2gEl8j+Q8kR4OxQehLEmVEaLC+ImXqdwerCj8HXf8HoDJkwX2p1F6koKaYpENkVvwLZe2XcfytcPZXt6Nnu1Wc/ngf5GiMjjkuRLrlkq7a4GH0VLleKgST35lJMLGgOirkJ5KPC5e9tFoiMrKnpQUX0RG2hYAWjmScbglLkUlxqs+ULVGDAPLsojFDTQM7LqeSA4zAU0PkpHzNwCaUOmJ6ZSUPMrCsuc48cR/8m1mMQAjS0S73DKkY0lvjF96tdw2G7rNhmZBHDeWpmO6XIksFj0eJx5XGT/KuybGcjwu2TqlZ6NGzlGPrK3hk6mVivNCkUIpz6MazSozKyDZd/1ROxkdVpDRYZu8nnogfkqrdRzx9Sxfch2lZUVc3O9Revk+p3ivzDKSe6qMKlPT2FndjicX34bH0cjFI/5Bqrea3dWdeWnRzdz50T9IdtcnUrcyUyo4f+DLJEsvTEy688Mxi5hpA11Ddziw5Ni3NK0Zy5VYL6Rn1TTR9TADBtzN8uW3c/cH42jTBpYsAd9BqBG97ibyMqrYXZVBRV0uvlZ7fnhHwLQE7mdfX2dOq3LKq/LYXZODM7MUtyN8sMN/suypySQY8pCbVkVDk4eK2kwMWwzDdeRF5oSikYvHHqIovRRbC1r5/3TRNAtakN7tK3FTp6xagNhy03YRiTupqMnHsMVok1GKYYvTGPJQUpNHaVU+uRm7E573w4llafiDXtBUFZdfoxzOs3FkPDNHxbPRKW83nfKa0eVm1SF2/gHZXZfODc9cxeptopx1+6xynhz0At0yyo7uRL/J/9eyfO1w5q48l57tVnPh0Bcki+BRBuFbyO66Al5dcQ0uVwPp6c2pX3v39mL16lsxTTu1de2w25p4//M/0W7k3aR5D825EY0bvLTsGgJNmZzU9TWih/HoGUYdhYXXUVExja+++jP9Ux+ic84R5uBbUOXPoKaxO4N7zD+yY35hSXLXYaFTFTj0Mruzuj1PLb4djzPAlcP+gcsrQkZtsrZy2cj7WLFhFHHThqZpWJbGul09eWreDUwd8QBumbkUN3XeWnk1lf58Tu569P3j8VQzYMA9dOz4MDfdBBK7+4PyN1nG4aF/DWNj6fE8MP7PQHMBMmUI3fvZWN79cjidcz/m7AGzqdWbjZF6fwp3P/ffDOz+HiN7LSdVKkFpMsyVrojdpMGzWYZV7v5iNEtXDGPy5L+K+44LRcuri+OUAqdIFP/xzG2c1KWEG856k0jM4OIH76JHx4Wc0F9giRrNNHkee+Jc8bhY2LOtEBt39OLdRZfTPmsnz498CJ+jO0mSdMy/R5YnWCo8Gvf36yeunSKu7T1eaGsemTatOaXhJDEa+l4JhJYZJ5WyzUGbDV0XadOqZEKW3Kowqgqb75L99c93LyXQlMzkMX8X53AK4G+aBNo//NQ99OqykqsGzQIERgagKhxmV1Uhd773V84b/BQZvnqenX89eal1/H3cI3RPFpPaqWnM2NWN+z66jFC8ggsmPIPuVengkqYhLAPJEvC8tbiSJavvpLJWhI9vPBNuuolfofwMmA1l9ztKJagmKC6oSYZMK6zYKCVATH6PyRi/JieMlWVRqfs467G/E4nbufbC90j1BXnundGcN+c6Pv3Tn+lZJXnxW/BiKOMiS26V60qt6+oVlEi/Up6BFlkY9n1wEsoCzZbYjai80zpNejxkZkxYE2CEKklhq0lLKStbcGsmSY9HUwt3WqyFR0NZhYp3Q7Wpap/aKKq9ijXRJ/EuuvRgaBGJwFdYhYjCrohnYkiLtkmSeKiMGMUCGskREyIUEBMh1iA184BsowxXWg0WgQbxm3rVqrosLf3KNQofwtHJmDHDAZg7V3gXVAZSrV3ju++GsWrVRHq2W80dI17CpkMSeiKDQ9kTynOlbCyF1TBckpshLDwaO5oihGIO7pn/QOL6Sz65IgHiC4bTyEreyfi+b/Lqp9dhMyIEw2nc+eG9uB3B5jqlcv+2mTs5f+Cz+Ax4ZukVbC47gUG9nqNr0edEI50AWLdZFLVqSjCqJJAkGAYMGzaTxYvPZ9rHNzFq1L+w8kQaasdaSYqkxpNionU4qA2lUNOYzqndPmfooDmENBfEdOYumUzxri5oWHRt8w0DT34LXbeoUqC7uHJNi1Fvt6uqyaJNoZBkw7U3Ulzclc0bRrJnbxFul58RQ57HmVQv7196Cax0uc2Q21x5HTEjYzGhPBnxIKd0fwZ/2M5H685nybaR6Mq6bEEe1RhKIslTy5SR95Dkq8fS5Tqj67TO2UVe7nMANChel+KeLFhyFX95534MewjdEvwUwXAKQ3u/SdfjlhPA3sxvYZrEYjE8gFO9xCXCKG4Jt/qoCYJv5MILOSKxLGiKHMragwtOnUtj2M28r4aRkVxDj17N6caGDDnXNyYd7PCjlnhc58t1JwMwuOdX2CQdcTDkxrIgGDo4G+oPyZ6qAmYsuoKizGJuHPUIPuPfx2x6LKQp7CUWNxKFFVtKw2H6Ohj28exnl5LqreXv4x4l3dvAvrDe3m03cusZL3DPR5cx48OLOfe8A0vIx+IGc5f8gdKKDjSFHESiPm6f8B5fbOrMzTcfR1HRL5+RcvTyM/JsHAv5ZnsHagPJPH/XfQzq+x06Ouu3tmH+shNxGFHM/bDav8n/RVGKRq/2X3HBsJeOGTutwxblhM4zqawtwusSQGNNpsImO0MM6PQOOelw5bB/8syiP+MwQhRlb8RhhBOcAnHTJG4afL9rAM8vugGvI8Tmsl6M6fsiRa2PzpJ2uYIMGfImy5ZNZt6839P+9Fo65x8cuAbgNKKARUllAaGwG4c9zPvzL2Hz9p50a78aK6azYv1QAlEXowe+fNSOoB07jmP+/AsxTYNunZezY9fxvD/7ZkaNepzU1L1HdzIpumZyep9pZCeXUhvITYSgNGnh65rEFxgRBh43m1TfkbG3FrX+mrHDH2Lrtr5YloZdKYK5mzi+3WfEjoEVdigJWDDzk6Gs23UCI46bT1jelzI64vsQ5F05YhbLt/ZkR1Vr8gxVZyYJywdt227lg1XDSMqsZmy3NQAJwjaVwq7CxmqhVsZXjl3875WhNp/p5ql557Nqkygruqe0I/81bjp9j/uGuZ8P5akFZ7GlpB12I0LHDuuaw5AJdT2aAOPnakIB3VSbj2nZuHTgy7gdIfySZ8O+RxgsVgc5PyXbdYKdMiD6IbRR7OeS2AVbtgzxSS2wXhbiq5JjNbhPyFtn/0wepeaoFUGFU/NkXw/v+jVPLujB4k+ncvmoF4jJyHhM9mfvLqtZsfZUXk0pY9SJ83HL0JsZi2HKvq4L5BCJuTh/4Du0TwkCBjn7FMjcqev07bCVnj3X8P33vRJgbMsS95kaN3h59mVs2HkcJxZ9RTxcz/G5y5jSU+eS7t/TbeNxrFnza1Q2fo5sFLndLcdjSlDS7MoHqGgXuH5qAAAgAElEQVRoDbuMg0pkTL2+P27CbY+ztUagnnt12YQZjxOsdDBv+YmM6boGVyiW4I9QXGaqEI4SBb5RtS3UsqTAWKqcs/sgHg5LDsoUmy1xjc4JbgmxVeWeNuqqjop0j7E/AKyTdGkqnoN9q7iKi8n4tooPy/OqxVZxi9h1HdM0RaEbdV/yWM8O6cGQIATpJU24aNXkcym2VtlGXd+/rco9G8mX/SHruGgJnmL5AqiT5zUhJEeFmvxBOeHiaisPVc9C1cY50oTnujpx8WhU1aaJsnv3caxaNZH2RV9y7bCXsekmbeXLKINmPEijqpchv6tFxybb4m8QHbU+JJ7dDsm5cE7XV8T+0sWpslXSZOVe03BRkFmOfeQ9PLHwdkqq23H5hFuplbH9RsmaW1C0gYVLL8eydPr1eYGM9ouolZVhw/Kp5LYRvKVVO/eP5Xfr1gsArzcdrxfGjp3O7Nnn8eT8azh75OPYJE23chlny22erpPmDGG2KqesOo/7X7wTTbOIxhycN3gGo49fii0e5/2vRvPul2eSnVZJ+14CEGiziVVX1QGy2ZTrN05ZWRGfLhtNJOomFnVSkFnM7aMfxeNsYkd1Fo/MvYVZM2/HbkQTi3xK8m6GD3oY3SMpuk3x+lMueMsSPki/0ZqQXfR1Ye8lFAKFErSYqMwMbC/vwufrR/H4h3fjsIeYcOpLFBWKNBA1xuvVM4+LcEwkouFr1UCPtLfF+W1hZn92BQu+vJgFX15M2/zvGDvwOTQ5f61YDN2ysNNMkZ2kFIRE1tKRZ5Z88W0P5nw6kMGdFzOp79s0cwIfKIGQm1jMoGXqhqbBhAnT+ejdybw++1ySLYuBx319xG3YV+KmzlMfCUXj90M+wkLj9cVjyU6rZtygBYTCThavPhWHPcJlZz9PQXYZNUcBu/gl06yPVE7tvJqmiIuXlkzmthfuRreZHN9+LWeNfB+bbnLWkPeIRB3MXnkm2akVnNL64ADtw93vwcj1Plh+Fht2HsdFp77GaV2XsadMwQP6Ydiso07H/s+RX5lnIxhyomsmPk8TsbjOn566gsYmN+ef8MsU8/lN/rOkoUEEfAaf+hq2H8GUeawkL62EQV0WMPfbszEtnX2gqAB0av8lLmcj8YidVtmf/6Rrud1Bxo59i3mzJ/LugmvJHfn4IeuCJLmC3DVhGgu3iZJ3HfN20KfDtwnjdMKJc/l44ylU1eXQ/jDXLisrYuHCc0lO2ku7tl+S5Qwz4LiFeCTJV25qOTeNuYdFmwZimjaB+rc01m4dxJxFf2Ho8FfxHAUJ0g/J9vIuvP7xDUTjTvp3XcD2PV1545NrmTxsGh0KjqxSbDxu8P7yK9lW1oveHT8F4OstA4nGnJwx6NGDutR/iuyszMRmi3H2Ka8T0UQ4FJpB7goAXtLk4d63ryAat9H+uK9BlmRQsHe73c8ZZ8/k3Xcn8dTcydToGkO6CYUjoGj4pRKtDBUVDlaYDN3Uefmj81i9qQeXDpnN5H6itsvS7/uwuyqbJg3OGP4RaekVFOSUkZu9a78R3ZyFYqeluaBCjaZlYZomfpmqbJfsnEat/F+Gx5SHQPnB0uX/W7xi/3Zxoei6vc1XhGblU0lc09ARoXIF7FVKYbrcV3IS4pL9UOZ00uPEryhMbuLbXR3Y2+Tli3X9icYcXHD6GzTEQowZ9CprNvSluDKDfnmSAt8wEiyhusKF2O0EpEEd2MfQUsSCdmKyaqwIHXotYQpV1eTQLmcHp3dZClZz8LQtv3b5GTwbigFxg8I7yAeeJR9AW7lNV9azdOmp4jWJOLpPwyatVEfEwZNvjmfuin78ZcJ0+rpKodLJHo9oSoIPQ25Vdc8qOdB3Sku1ukWqmOJ+ULgIU9HWyjZ6k0RrNKczkdmg0P/4xPcue6QbVF5b0ZgpjIeiZ8pziv1rVeVoeU1Vz8Ql26TYTeOqemkLzwCmSTgcxgM0KHpduc+WoPQK7ZbnlBNB4SfCLWqktFLfW6SKqRo0yZsl8l9mCpkhWbpZLhTScMe0NaegKS9KrTx3vQJwxWVKl+SoqJVVA8+XALHDyXXXXQfAnsXjASgzXdhkjeFQbTa6VwA41QKj6+CWA0PF7ZXnSlXoVWyTFXKc7JLPX8XoO8jvyhOillXlAVIucKfdjl2mMtpsNsKy3LzdLlbIkOYjq7CacDiKaXUW+2ku2U6Bb4hJWtbWrVvJ8wiLPCUlW+4nnk48Hsfh8DNx9AO8MfO/eWLBVP5x4S0UOMW95Mk2+Tzg0sFhwvl52xmbL9L7EimWmkYFUNuYTDDspgkLXRdYCsPwymspVs0w4bCThQsnkZxcyV0j7ibZ5WeAKiYmw0v+qAWeMk49YX+SpK8KVnD/kltZvOgizh12Fw0ulXqZIa+n+i6CYaj/0mU7K2V/aYTCbl7/5AbSk6q4cfT9JLv9NIS9PD7vJt5adA0XDJtGSr4IOwRiYgYq5kqVLWYYdpYvv4Kysu5MOuUVxnVeCsDs9C28tfIPzFl8LecOeJgmQ+CCdEQNHYCA8rqqSrLRI6c61zQL09Sp8bciI/mHUfINTR7ue/tyymsyOXfiK7QuLCZClwP2s9tjTJw4gw/fG89bH53H27MnJf7zupp44tIHSPEcHHk8b8VgVm/qwXmnLmJCv+WJ3xVhlmgvnNJbzNHoUejxir25oj6b7OQfF0r7uWVgx+8Z2PF7KoGs1GpmrRxOXsZu+vSc11zd+98omvbDHby1Oo14/ODp1P/ZcrhslCM/y88uq9Z1pmeb7Vw+fMEvcfnf5D9Q2hSuJNlXybsLr2fznvYEQh5i8R8/PP8y4x3+MuNAANd/omze0ZdAMJ2uhetw2X8cCK+2MZk7P7gey9Lp1u3QlUubmjzE4w569FhIsuvovBOdszZz65D7aGxK5e2P/0pT048DOAbDSURjToYeP4dkt2iD19nItaMeJDutjNc/vobtu3oTCnuJxw+0ieJxG0uWNCsa/aWiATCg42LO7/cCW8t78/byG4jFjy2Go0vPTbhcYR6ceytr6nLYEnWwJepga8TO1oidzfVe/jT9cnZXZ3HxuBfJzq8hEGlFJJImPymJTzSajqYlMXb86wwaNI8h/ZYw8MTldC/ajL/JR0UohZDNRkjXCel6IhujTn7yWm/DbkT4dFN3ihu91Gsa9RJ0HkcUMQyaJk2xGE2xGJb82ONx7PG43CuOZRnE4x7icQ8lUZ2SqE5y9tekJZfz9OIrWbGrNeFolHA0it3lwu5yoVW70ard2CI2bBEbKV4vKV4vjU4njU4nn2Pnc+x81BRmdijESvkpDcQoDcSotSxqZXhr34/TsnAiiimmyE+aZZFmWWQjQO9JqRpJqRqOJHAkCQ+HS9eJyM+exiRWbTkehz1MUe4m4pEI8YgK9QnQtc3hAJcLFPmbLOUQt9kIyo9f1/HresJoA2F0a0CW6SfL9OO1LLyWoO5T/o5GRIJAxLLYccEdDHtvKhkZcMEFx3Qo/kyiI8y0g32OTA7p2Vgvt9/Ijs5QmSLKClTVFxXwS2UnKHCTtCodbhO7w8C0dJyWj60l+ZzeeT1JoSSqPLJGSguVT3ksaoPCRbVDDpSmFi5LVcUxUahHWrYRiQtQeqZy1QXtdvYoT43EK6TUS6ZMqfkqLEqq3C9LcSwoDKsio5FfnfJ/FdVKsHjK7wm64hZWdE04TG11NduASkn1q8uB70sR1pxN1QJRfSktMAUcUy5AVZsiWXo6FJunquqa1STOa8paK1GXZGhtgY2JaRohVeNFbuvkgIrHJTojrn4XLwn1usnk6CR/uMhKqfn0U9yuGiaNuJt3FvyJu2bdAkCKp45rzniU0WnlzeNBbqsURkP2hyHHR6hF7D1Dfi+UnCiuFtTKcVXVVTKD2nU9MZ6dhoFP8lSEE+yyiovFjWEoymiZrWUX2r/LJXokGhVjMBIRzyYUktwnitvEaqS6OpclX1xApzZruHb4Cxi6luAK8UjL0jIET4Cua3g84JW0DKow1nd+H3+ZdS3+YCrDhs0gJSWKZbUV92WoKsrC6xKPb6GysjUARZqf/nL6RItEPwaDMtUvIo5rI2saVUkdKAMoytxMzeB7eG7p7axcOZbBgx/CMERKvE+i/yKWRcxUnhwRPgggPEGN7KBBZrWYmkWuChVYFhgN3Dz0Hh75+DZmfzJV9muQAQMeJj9f1eiw8emnl1JW1o3Rp7zM5I5LwIR85caPxzmvaBFRy2LGqims2TiB006YhUZzbSFVUdhvCVKyBy+/nCOVzMwaLrpoOq+8fA4vvvePH9zHsEW5eNyLdG67id3W4RkW7PYofft+Rsn67ry74OyEgqUfxFJW0qZgF5dMeplX3rmEe9+cwh2/E8yg9YFkMtNqDnns4cTtbGTS6ffw3rzb+NfSmzntzCtwHGWxu+rGbF5bdSdZqVs4YcBzGD8D/qMm4OP+t6+kxp/KZWc8RZucndQdQoffVSVQfEcavtV1k0jMzt6aTLLSK5t/10xqA2k0hj14nc08JuecA+EwfPwxdO784+7pl5Vj49n42TAbBZli4H+yphtV9cl0yTk4Ec5v8n9TUnxVnDfqf9lVfjJx08bKtaN47MMbyB/5DDluAQlWYEGVdtsYjZLurT7gXEWZx67+xr9TgkGhmJzScy6G7egX4orGZP4y81r8wRQmjXwEe8ah99+5szPLl59Fm8ytdMlbe+idDyFFmZvplPMdu/y5B/wXi9kxteiP9pt6nY3cMPwe5m3vS9w0WLV1BMuW3czQoc+TkbGTTz+9hNJSoWj06ryMg3FMndxhMQu+m0ggmPrDO/xI8dJEh9ydjBp9LyUlPXFIwLhPvqzsFrTP30xK1i4aIhCRPAwqa0GZApZVDewCoIutjpUb+vHOJ5Pokb+Noe02kuwMMiCtAs2EMhU+lWdoSJQ7jJLeupwpk17muXcu4Y43pgAQijg4uc+nBKWxFpPAaGWkeKRyXW8I5TIScRIOKzCxOHeD3QUp0LvHpyz8bDLB1AIMd2MirV6RyoVlOvX2fFGoYE1cI9jkoyLYhXlLJhIKO9lSNoh7v3AxceBTBKWCb0rF3y4NrIDNjWGL47EszFiMnkCWKqYnjSqHDHFqNqUli41aF74P+Hj47Supbkjj92c/T2bWdhrQcBoGpixy6bYb2OT9f7alLy8suoD05BoKssQ7yadppCtjdp97VSD0049bwYrv+/DM9Cu5edKTpMtsraG9PubZ2Vfy4Nwb+eOoB+l1skhDLn0cJk+GHj34lcrPgNkok1UugpJxs1HWX1DZF+XKulYDQnFAyMGjdOBWEehTJF4WF955FQC9M6twR9xEbRIz0II3oVFaKdvlZFGTTFn6KutEZY6r78q7kOwRmli1nGSV9cKyi7pcGPK/cnmuajnoVVxatUV5QxK/y3dBpQx81iveADUwVccpT4hit2zBU6FwBnsaGqhtbGQjXjRNZDC45WSKW2KB1CSYokYuVEmWGNgqyyQusR45ysMhvU27Ek2RGAd5bcWG6lCLTos2a+zDUSJvOBYXx6gy1vG4XCxMRdIjjj00ofSBcs011wDwZiuBbVj60Udozhq6dVwIQGb+WmbOuZWrpKfjYJKdvoWrBv4DtyOIW3o67jpJkB51cIo7zMiRlX2VRbtL7FejYvVyAcSyEiyTDk1gOABiMjU7HldeLjvNo1Xu7xCLtCYZUe128SyammSl43oxlhWaXVRcFdf36XoC46Pe0cGYzNaptjCjFpYGDf7mwO93gWSunXktlY0pDBz4OHFfMcH6NNk+CeIz0uRthYhEDJYtHU1mqx08NOx+vEYY0uQLY53Yv6FBbG1yYgVVSW7ZJkP2jT0WQzMtDEwyrCAuec9Rfx4vLbydFG81Jw16BIejCeXzUtgNTRPueoDVu7swOHcxmgbp+3gIvVo953VaDMDg9quZtuB2liyeQuvsTZSWdWP0qS8xsf0SiENX+Qx1mRcal1lzFbqOjvC8OmRhL0VCH5ZrWyz240N1KSl7SUlZiFeSO2VLZVG90BuOAiKwckM/3vrkAvq03sT/jn2eAomFCWlHZg92aLODKZNe4fl3LgbgD+e8RFFBMXVHThR6ULFJkO2WiiL6tD00cLemMYUXZk2lpk54c5zOJs4440XKy9uycuVo3vsUpvZ//ICMj/lrR/DOqnO5bdI9dM4q/dFtfevj8dRIRaNtwXbikeb/SiuKxP3Ia4ejDp6bI+IaNQ3pvDr3fIDDKv156ZX8ddJT3PnOH3ngnau47pwnyE6rpGvrjVw2+nmenzuFp+bdxAMF06luSMLvT0RqfqXys2SjqKJpQhP3qdipnNz1UiHYqcBWCq2r+PzVC7DaTt/c3bz1h9fw21x4nFGG5OxAszQiMiVMLQLKRlUvrrAqOZ8g4xFibxG6SFahEXntqHSbN8rj10v+flttLXb5AslqAbrcK6+h2uKRC2uD/K4Ai7uURi9/V+RldSoFVv6ugJZpClkuf7dJF35dQwOGw4EDH263eFHpMsdVpeIpK0MRcdcnUlxFDmuWff8wlOLGVODeOsnWtUsTrcpXKcYqHKUUCvks62Mx6lWhNQX8tZT1WgiAZYmrqLL0faUGf7TKhpLqakmsNEmA45SlOOeNN5g06m+Ul3dD4mWJWCp1UypEYYNvvzufp5b+hXNP+R9G6UIpy80T/eJOFs/flipfKg0SpCstm4BURtP3Qf875LnrKvJpkqyHNl8tblcj9ZK8ymbzEIlIQjXDJ7dKCYvJ+7DLfSWfRKJQnywRbzik0gKmzZZInVYpxfo+4yyETBW1LKKmSXVjCjfNvJb6YArjhz2A270GIlDXJN4uDQ0Cr+/1im04XCOwGqaDXu2WkC6r6oZrJHujVKCDisFSJhvbGmVfyHmklI4m0yQu49Rx0yQE1Dbk8uGiPxE3Dcprivhi6Q1MHnove+071FHy2aXg8Zh06rSBzZsH8YQR4KTer3OKIdqSpwquyW2Gs5H7R9/PbXNvZVuZMA+HdVhKuky1d2TKbAKPVPol4V3YsrAQVOVB06QBiEggazyeJPulmRH5SEWFDW0RYYTZ5YskIsHEVlhH0yx0yVcRUvnmUo1UxfGgktZU882WU/lg+QWckLeBN694Erc9ii1frp3bJHFgUK58CeyAbb9tgxYmu+0OrrjkKfGrp5TSEARlODkprFHfmEmGfI6myyAjuRJdhkINIx+nUygINlkQUK1F7boHydxQzcPzLmPc6Nfp02oPKZ4G0pySIFC2aUckg0dmXY2/MYVBg+ZgtyfTuvVuUlM1iop24nLNZenS0Uyz38iwfrMxJaFc8dZOzF51LgC7G5PoCsSiUbxAxC1GXCyuyDjEKuqRZpIpyQwV/V5VYxJ5uTvJaB0kQA6GQ3grgns78NqcK8hNrWRCz69Jt9vBbnHz+Fep8adglwpGhiPMaXkliZCwWtuDppmwNjXLonVqGX+a8Dh3v38tj824ilsmPE5yUjndW3/HRUOm8eria7j9lYuoaUgmIwOuvppfsfwMno1jKZoG445fj9ZKDpofr7z+Jv+HxOeppWu75YkaOIpe2ZL8Fw5qSU7azbLPb2bFlrMZ1fmln3xNp00sgg9++NfEbw5HExPHPo4n7dgOXMMQ19q8qxt9s3ceZm8h1Y0p3DbzOuqDKVw1+jFI3ULNEeA8y8uF4mHYIofZ8+iltiGXmYv+jGbp/GHkPwk2ZPHyp9cy/ZPbOHXIhzh+oP7HCSd8KejHN46hTcFXkLPloOdPczdw4+j7uOWtR464TcVV7WgMe7Ebx/5+DyZ1Dem88cEN2GwxLhx9P0neQ9eN+GbLKcxafil98jZw54hpuO0/DdOQnSkUm6p9Elj2VrVn5heXUVVfuN++fdqv5NQR/zoob4QSlyvCOefM5d0ZQ3jvo0t4D3A5Qtw6/lk65+1I7PfusrOob0xhwoRXycvbhaa13e88vXuvwLJg2bLRrN/W+wevZTeODhNyJFK6uw3vvH85yZ4G7pz0FGleP0rx69dJcLoo1e1oAm4FrfbwpwnTuPv9a7j//Wu5dtzDZKVW0rVwLRcNmcZrS64lyRNk8WJof7hc9P9o+Rk8G8cjtMKGsFjJnJJvXjke98gXQLncKnY75WVIlZZJxOEgu0xoor4KmfYn91WpjMqroJbbkCH2T/I1u20BPMrDIbcqDKBia03SeiyV3zfJ71URoasGAzVkuoSvwkgVQ0vlTyscgLJ1FFWP8rYE5f8bVL659I0p4KciHlM05YoNUHk4CuU9BGpFSMlhWaT6fBQQJegQi5LLUtaxtDQt5X8T7bfZRKt8hvg9V1nksi27Zb/stYT9pdzo9Zp6GzXudy+N0kvVJLeVppmwrEtMdW2xMGiO48TXFgRO6ln+2NqsKpzy0ktCUcjIENZnlUx5TIlVNJeSt0lAliqSF4nRKWslXzrqCYY9AmEOuN0SGGnsj+bV68WYVIXqIgpgKvuttcfDxcd9RkF6Naal02izEbdszFgxnlmzr+X8Aa/iczWgp+6mxhDP0TCayckA4rLomUqDczhEP7pcYobY7emJ4woKwnTu+BWLvjwDuy3GkBMWHlBsLqhphCwdf8TFrF1deHP5ZPzBFMYPvR8rZQtGKJwYL3GZllxfL+tX+MVo9njasWrVIE5ot41rhtZSul6MhwbpAXQni7ndRnoX6urF/5tl+K5C4RIUoZ/Nhk3TsGIuAhV9+eCry9EsnT8Ov5uclDIykkvIGjSNB5ZdwxdLxnHh8Acod6ox2E72j4POnbexZUsXwlYeLnsx0LysqbmtkA7Zrnqe/t1VVAZSSLeshKcoKL1VpnRBbrFMtlW1Y9rCm0ny1NGr+zwimkaENCxL3GckIgiXZs16nKMVpT5YiiBOhY0bM3hj7vWEIm5MU+e12Tcxsd8LROW4aJKeDkuCaBtrejB/1QV0z93Av4Y9hkuPEpUvpVihtKID4t7StkkQsry2pinlTY5jTYytWEx8r6srB6BmeybzV92CXYtzRvcXyHOL1m8NdOSTDWcS0DRGD3kZuycHm62NPKfo1wQjKBm4XHDOpNns3Nkan1nFoi9Gcu/7V3DNhGcS/RIKeclMriZNC5AUiRJw7tnvfJrmpE+fr8nNLcHvT8Etk7e/W3sym0s7MrD915xbsAN3OExTKMReIFAvvUNy7Ux1iO8F0qNhyDBfIOHxUf0jvlfsKWL6u5eR7gnw3+c/R+8kwQyqlIsEM6nyzqtwvCo2qUKqppn4b9+Qc/vUUm4/8xHu+eB6Hpt1PVPPfAjdXkzr3DX8+cpn8bqb6NTpV1kQZR/5lXk2fpPf5NcibnuEE1sL8GSdVEqKsou5f9b1vPjJlWIfp59hIx4hPf2neTp03WLU8FcBmLtC8I78vteB9OeVgXSqA+lMmz0Vhz3EpaMfxZ1ycE/AvmKaOh98MJg2bXZz53lv4bQfG6Irl9FEbWM2//r0Vryuen4//G5yUpuLKvYrXMPNg6Zx/7JreG3RzQwa8QYOx0+rr+FxNJGfeuiKd1sr23HfolvwOANcNPJuNG8tP7WQ3+GkPtCK1+fdSlPEwx9H3Ec0ZufZj2/m2UV/O+Rx3XPXcdOwR3EZx558DODz76/BaQ8wdeBfSHVXJfh4urpW43IEmfPtZDoWfU37boc/l9MZpVOnbWSxjaKCbbz4zh+Z9v6V5KQ+jtsRwmkPU1rdmWem30BqcjVnT3qD5OSGA86Tny8QZck0sWLNQDaXdqR3h2/584iXjzmh34fzz8bjbuS/z3+G9KQD23IspKBVObePe4S7P7iexz68kQuH/4NWyRXkZVUe/uBfhfwM2SiKommZxBg0Sg0+JAdsZcLyFe5ZXcbLkzXhystXmQPx+P9j77zjpCqvN/69d+rO9sYWlt57700pgnQUEcUeS9SIxlhjDMHEmJ/GGLtGE8VCREBApAgICghSBZZel6Us29vMTr/398f7vrMsgoACiXHP54PXnblz7533vvedc57znOeQf0rUr0h40ZLg6JNogZLENlwi+iu3ikikICyIkUmS+JYifwTUsqOQjQr5+RyJS4R1kYd0ucTD7PN5CFYIIR6vLBf1KM6GEq2Scl5K8Mpnlsit+PugvGaXQjZOKdtVuXb1qopUlQKfR5Zp6rGxmFFRpHBSczuJZKgSzqChSIWKK6DSB1KESd4LxZcokoTaQEg8WJpDfNcMSYpV4mBKSn27EkmTkYOXdBSKokoWzboS0ZBt28PfipLGYFCBjiJi7TJlCj/GbpXdNJWNGjUKgJemTkXFXN/sFgqbbnndFXJMNUDHJCC5GPYKMeoBj+xkKcet0BDfX93zRDkuafKeuEyxdci+B3Gq70ZcBf+89ll25GXgD9l5cdUkvlj6AJOGPkd0upjvVRE+ibhWTRP3MkpKJmoy+lQRpKY1BSBIMpcP2ouBnUXfjEU3NQZ3WRIp9/UhJKk1zWDSyL8RjiklHF1OyGdiGBrRviAFfvVjqngkYtujRwqBgM7SpVa6Nd9JrF3c51YdhArpWinI1kKifCldZbZ6p4yUi8T8UXNakZ0zbTYmd32PohZCRbVx4nESnJVUKMY/UM80aZO1iYQBr/C7r37FqiWTuHXIc+Q6lBCWDcEDGkESbmKVaCA1TRHRVWylnjf107Fbic8Bhwob8/dlDxLldHPV0L+gRZfilw0PNSAUEnPV6/3hPzyPyHl+x8iRAJilcXy47BH8QRe/HvwsjRMPAvDUiEc5Xl43Uqav1jbFu4izmgzL2I/dArZM2ehOrchqiE6pXlXEbqdUrfTrSnpQzNegbD3sr8wBIBR0UT8xm8aOAjBAl8+NJRike8rnLORaLJU6hrEdXVdjIuaCQoGq43/J6zINcJXyi3Ev89ac+8gtyiQr+RiPDpvBgdZfUxJw8e6X1/DJzOu5ffyr6FL4zB/BvsVzsWZzF5Z8NZZeTbfx6IgPaB8Wa1KJ3xxDvCMAACAASURBVI/b7eYEkK0Q74DGidLW2AyduKgCBkeL35rG8nlXpGm7BhY0YiVPJuh30rLhPtrEVQIazdTaLJUawyXi+BVy/VMIofWU36uQYUQ4bCcjGyAQyEYJR3lw+F/528KHmLb0t9w66E+RJpg/fbswaZSfpJ5ZrdXaf8Ki7T7aZ+6lW/3tPDL8OayWIB9+/giFxVln//BZTNdNBg+eTbNmW1mwbgzLNl0Rea/EHY/HH41FD9Og7j6iJQ+goLghr01/l6c/nUVFReMzHZpvvxWVF1HOC9u1M9rupVP6bjql7ybhe8TB+tb7lj8NeJm80vq8s/RhAoEz9xL5MXawoDEvfi4cjRuH/R+x0T9OZ+JcrLIqldeXPYEvGM39g5+lQXI1hyE5pph2dbdV/8vKpl1WNm3rbadtve20r7sL+0WQU1dWUNgGjy8Zu/X0JSkOqx8Ng5253QgrCeHzsPiYcu4YJypLCspTSXBV0qXhLnq12MyjY1/DXRXDivVDTvtZn8/B0pVjaNZoB4+OeB+r5cyIRiDkYOGGP7Fg/TPM3fg0769+g/WHupx2X6fdx7HCDAqKTnVZL77VTTrOg8OfJxBysnzb+Et+/otnKo1ypn/nZt+LbNSVHnyHqVMBWL1dlD0FnFJwSrapVvLLKnLzqUZmEoXw22wR3kJQeqqGjCSRKIFdRqgq8vbYZT211lbuJjzyI2Hx4ORZxUPtcMjP21TeXHjNuqE8/hh5HFFBEW8pJFGy2JWWf4XMR1fKNtwaGfJYKrIUxzBkPWAoviEAXinPrvKDqo4+WfIuok9BPI7J76jY2w6rFSwW/IBDXkOp9CANiRpFmao6ReQ/FQO+TDWaU+iKHFcl220qLoLij6jKG5njLJDnqZLRi0/Ju5tJVOfUW8uxlAuB6JyOYUhkyCvYLLHnoSL3QyyD6gqA21oKyefnN24U1xiqXqxNtEjTuKCqhJKNyHw+WTEkLzUg91PS9S71OVOMQ0JIRuhKul2Nn/y7UVwhj478K88veIg5n/2a20a9gDVeMI4CEb6MOJnfr+TMRcSoW4VzYsbIB7VScFQ0zcegQZuwEWDBujH4fTHUTTrOws1DCRlfk5xcQIWtLlE2HwUFmXz6xS2oeGHzxj8wsvvjlDnF82Gagk+ybp2dRYta0qvlLq7psCWSq1YZ/6ZSYv74GoFQRK2XzdJSBcKRKPkzQVkxpJCeLDleyY1kJUgD+QxIVWszZGAGpDjeYRhZbwuFA17m71/dx6olk/nFFc9i2N1YZdVLLNWLUZQaFnkPPCepZopx0ijzJJCd1wbTFCMQCDmYt3EcLmclV1z5Eu5oH6asxIrCTygUIoQDvCL19Omns/ix5vUksXDdnwmFo7lv8LN0ST/KyYuv+j/XKaXvZiQK14hXsgGyjJxjct2TPElroTiK114TFaleWcT7pikrnnwirWcca8aqTU+QHH2c4U3/HWlk6FONKUMhdPxM6PYeMzbcgmOxhdEjp2GxGLilhodhiPUwHCl9Fze3IijXzbAbqMBh9REI2UFW/EVZLLSJ3kVCdCkhr4WwXFsMi5LMdxAM2jBNnaaNdhInHQ01Nyt9Pip9PgqBHUYUKzb+noKSNrRuPYvo6BL27RvKqyvuZHXJXPpmuclKOUHHOsKxvHPgAqb8+07enXEXV1+2gGDQhpVq4qdFduEMd5LIcYm4JtthuW6WyvGRA+bwSjQ3bEZaJCj0Q/E81G+bzzBoGJ9LcvQJgkE7P0xb97/RLNQiG7VWa/9BS40r5Dcj/ordFuBf839N0QVCOEYOmkab5utYtnUQ01bciNsbQ93kY1KXA/LzM5k791acjioemPQ7nrvqN4DJtwcm1DjW4cPdWbRoAC1bHuDx8bOwWS9sPvx8rXO9LdzX7zWOFjcmO6f7Dz5Ofnkaf5n/O6avvI1/r7qND1fdxsy1k4iOqmDi8OeIjv6hRdjnZ9tyxuHxpXDf4GdpkJJzSc55LpZ7rBlzNk0lPiqf27s/RozjzBUxA1p8wdWdP2T7wXYczD1/ecvS8gy8gaizVrScajZbEF0PsX13F7yB0wcr/pCDFRv/QGFJazp0mE6DBmtJSMilU6dpJCcfYsuWq3nls5t5Zf5Nkc/UTS5i6nVvoWkm7y6ciMcXTYzzAoiNnIdF2d0cKW7OkfxLj65cHLsEyIYylWlzqxp8Cf0l2oQnW6kLZYqgJnLWqmIibBFRUbnVQ0MZMcbLY/gksqEpQR4l0hVpCKX0JAQ928gUxwwdOibfVwuKV+4nvG9VGRCWktrBoGDjR4X2AEJ6PFmiCLHyXCrKi5JZYG+1ELm4Rk2JNcloOaLQoqoyxHdSlSSqM6PKeKrcnqpOURztxECAsM1GgGoxLk1Wmei6uEaVY06TiIZboiP5cqyrrLI6RaJJqnBMMaetcrxV1UWV5LpoVsGJEaJLEJaIUTBYjmmWye8lEAwjV02oE/KaBHmyU6d4+aqqF7g4Vk51ZPL1pk3iNfl9bPJ7GoAfkzL5uoqGHVIOXzWsc5yCfCjZ80Q5J5KD8m45pI6LnE8BpTmiolSLhXRNIz2xhEdGPs/z83/D/EUPce3wZ9HixfPg8YgxrawU54qLE/l0TSJgmhR0MSPMIxGJV1ljuGzIHEb3WYBhWvBFVfHJp35MHBQX12fevGtwOHz8YexLpMSVUy/eICmmFKc1GouMHnV9KLt29aR3y108Nn4WzeT3yAHCYY0F29vh9kbhsgXo2y6btN69geoKrJUbNgAQkuNiynlkVQiYEsI7Id6350uxOMl1sbSwYh4QY1huqRbsa5Z5QPy/acel6zhlg0YL1TL5RfLxK9egzBvDrJxuhA0LHk3DNDXWZ1+BYVi4Y+RfiIsui1RWVUX5CFjCmLLtvWFIfaBQAK/XSzR7+Nsnn3ChLD2lHrmFflqmHgY06qj2DUp4ULVxkNvwKdwNQ9Mi8zTKIzlERVLYLUbyUCSiobhoamWqTnoIZFehqpWH6jNn2T0kO09wV5dHcNkrwISNhc3Ir2iEbgnQJHU9jVPEmMUmJNCl+WFmb4aosJ1kXSdaijiWItCxCkNW7akKjaC4lpL8WD5f+Qgaq0iPOYbNLUprFbctaBh4AkGKpciafASx2ULoeogRQz/ks8U3cu+c2+ncemPkN6C8spJKt5t9xwdTXNaWDh3eJSvLArQHGmC1Qs+eq/B4tnHoUEtKS+tEqC0JQLPkQt68/TkKKxLQNKibVBQZL1MiFaETUl9I6Rqlir9Nu1xP3BI59oittdjE6qnZ/FG1pVDtDVSbi6vbv8Ebq//I32bezVfVLXt+wvYTkyuvtVq7mOZylHD4RG+Olq0gKyH37B+4gFYnroiHRj3PlFlPsmXXQDr1/PRHH1PTICFWRKRFJ5X1bdnSGdPUuOqqf5ISU3rGz3/1VQcaNDjBY6cgGuGwxl/njuXL7Grt5NXZ7fjT9dNx2i8ef+BMFu2sQNMMlm8fRv/MPUTZqvU4SqrieGjRw+SWZ9b4TKyrjFuGP09GkggkFGnSbzq5VLZ3L2zc3YK46O+vjLmQVlQZxzc72xN7hnPm5jZg5rJJJMUUcVeHR4h1lBGW4PVn2Q9Q4hHOQKLrGJMH/ZH4qFIMU2PRloEAxLjcpz3umSznaB+8vkSSXSU4LN/VUTmbtWr+LQALP59EzrHvClFoWogOHd4lM3MTUBMJ03WT2NgyEhIKOXy4Bev2tKNHi+zI+1F2P/VT8iOO3sWuRjrZUmPy+GXfJ3ntm9f429/g7bcv2akvkmmcT8O1M9k5ORtK+2Jsx44AlBwQ0YlaAspklFgs68nzpRxsUBcPf6rpo2lILAjNpRhTroyMlBqnmuYRD9RUC58oH9KPK26veNCUSmM4rJpdCc/eFRLRZLqMxJIlJ8QrK2rKg0GiJPNe6e0rdoei2O2Q39g0VTythklyPQzh+as6cSVvrnJ4p1bIqMVQO6nZF4Dh8WDqOn6qtTpipOKdovJFnRJRKr0JU5fy26bQ0fBKHoWSfFat5p0qxytfV0hHgSbO45IiOjan2Lp1nVBIoUdKDEmEJOGwQH78fsGXaSn51rsvMmejBCjauhUgom5aikDN0jSRR27T8e+sWzeV51f8jl9c/ntaJgo2erRUxnTEiMg7MSAjaRmxFyn9FjVe8vUkGY0rRXqloaIqIaxWa2RMbaEQmbGFOO1VENTwlIpqhB271ZMj5lGHDoq7oWa54hPJaFZXUugSxZOzwCG7TEKYcDiMy+kmM+YwKSqHrGmENJ2AxYLdrqJQqFPneATR8CBUGKfOHcuG7PYMGvQlXbt+S+6eRnw0bzQPv38jbZocPGmmDwAgw1bGgI5bI8x61VJMYV35wJbD9Vl+SEhB5+QJfYdOOTvokS7mkWpjUA5Uym8S0DTKdR0trpyrBrzFJ1/dwZQlD3D70BfJt/kpr4rjb4sepsKTyLBh00hJOY4m0TybbT9+vVoPRm0Dco2pFxb8rAYSPe3Rrh0AHX9ktZSygwfh8svBNHT+MH42CRViTip9oSql0inXF8XZUFwtpRRbqWkRHorqN6J5xDa5SmxVYfU2Twz/9+HtlHtiuPXadyLrQ7REYytzs5g18waSXQU8eNmfyNu1lUpUnRhc1ekF3l79NwBKq+ry+qqn6N/maw5tacymvR0Y3nsJDesfJoweUWe2K/VmycUzTfWci3NmNPiSI/kdKC5OxdT9HJbjXanaHZgaXlMHmsvPqXVSrNV+nDRunsedDRcTDFojnD+vt4gTJ/KxWr0YhkY43Jxq7egcMV4+4Wi3b7+W48cb8/Kn11E4ymB8K9E+NFHura5Yrc1VxfIaJFcjKMkxhmwNYMj1wkiX62wDufWaVMqbpZA0dT/V/VVoclk4TGzUUerUqe6C8NO2WmSj1motYtHRefTo8XtWr3qJLYcHMD7x40t6/kXbhlBZlUR8TNHZd/4RFhdXxp49Hdi4rT/92wmMdtGunhSW1KVe5t7IfgkJ5WRnt2ZHp420ycwjFNb4g3Q0xgxaRqd+Ik3SreNWdN1g5vyR7D9S/7Tn7NFqJzhOr+z41a6WPDlzPGGjZjXD1v1+Ega/QIuMPZHXDENjrpSlToitHqd2TTagafDJl7fz9uf3c2P/d3ljyX1UeBK58YoXIUMEECqNecbOa5fI/vUvOHEC3vrlNBrWKaT84sg31LANO9tRUJrCnZP+QYOsI1SdMgRLN/bDYfPz4MA/ERdVQd4pn6+bsI+7+k3m/XV/pioQQ0FZHWZ9PQ5NMxjTezFX9FnO+dYqWa0Bund/keVLqyhxZ7H+6AC6Z4k5uenoQNzuNDIyvj3rcZzOIE5nMNJTyGKpIiqqEghHyNVnMrs9wLBhH/Llsol89Nkk6ur/pleL7+/fUmvna5dQ1OshGRHMl1UpPrfAIVKlR6f6bey11jxcSOb800wzwvswoqTX7JPsdVXJcVIeE8AwFA8gBwBNE39bLMXyfRFdNzSEh5suI9bm0uvMkJLMeZVioTos9SecVmukjbvKLcqSazrIbbKkIhdq4vE7LKNbJZGt+CRVWqx8XTHCxX4++dBUynbkyOoEdJFZtFgFWmN3u9FNkbFX0YBqlBalcrSnNIfL0wUrWNeVpymjYYnoKBRF5d6VimukuZdEBqwyL6vJ6EvlhAP2ILoulqpQSIx1MOiSW3H9qRWqvE/Eu1OmPM7FNC912CHHQYkSKVSKsFygdAuxsYXoehhTs5Ekx9Emb64eJe5ZrIxsVBQaVFyZU86pcuNqPtp12VNGabEYBjvlnPr4216s2HYNKbGLMLy/58Ru2WdBHsMnOS0Oh6iEUJopSnNVk/06dF3cE6fUdVH872TTxAF4TIOuXRdTVJTEkpXXUFBQD10Ps3lnL7Ky8ujU4zj5+QJ7mDBhLdOmDeHG926kV8etFBakkn2wCcMHL6Nv369Zt10gW1FRoEef4LZR0wEolaqY/bt3Z9ma3sxZOoSQqUW4QOrKy4F1+5ry5MzxNMw8zjU3zMHhCADReDxRTJs2iheWPkDTep9z4MgwQhFNHmFWVy55Uu1S05zENNhNv/7TWLnyZp6a9UcslhBDhnxEuE4QwkKPxDQFUhIOS7VbOecrJMGwfXuhXxInlTrayXNdKERDWSgk+AcdpGiTW6Knhqz0OhXZVMq6ISW5H2nUZlJqmKza2YsujbcT53JTotBWuT0ityWSgxaTFqKCOhjS4dKlIIcR1kmIriTaVkL4pGxYy2bNxOdSU8lIdVO37mv839x7sehhHrz6NbT4Uuy2IPuC9ghyoTgnmqb0NuLlVlVhqDU6E10H3bYf3WjCtG8f4POcFJyxceTkjqFOnaO0anUYTesMgN0u1hGrVN5Vuh6aliW3AmN2ueqRllYBBMnLE9jO/v3KaVHdn8SzkpraGQgw5upZzJ59Lc9/eh2TRv+bsc0Er6yh3Fu5LKqKT5PNlhyyYioUrqkYapHfNRwtuRyagVuOq9LoiaCc8j4rdDrJ+M86wxfcNA2sPx69rq1GqbX/CTNN2L79NkJhO6lx599c68fYtkPDSEvYS8uMhyJN1i6WWSxhhg59n+bNN7LrQAd27OtMkyY7GTp0OVZr9bkTEz3ccstSkhPKWLO5EwePZ3LjFZ9zed+vT3tcTav570RhCl+s6UVyXDkO2+lRjUWbOxHjquL+Gz7A6QxEPhsT4+Xmm2eRGHeIPYfHfMfR0LUQs5c8QUVFao3XGzXaTP/+7xIXV8iQIa+RlnaE/3Urqkhi2vLrmPz205RXnb5YMr8siXWb+hATXYn1DEqjKQnFHC1MZ82hy7/3fPVTjtGq7j4qquIoKEvBfoZ7e35m4HAcICF6NSdKbyYndxx1UtbTs+eCM17vhTaHI8DVV8+gXsYRPvz0OtbuaXtJzvuzsAtTjHJ+aZTNsi3zSAkBHJK6Gyp3HCWj5hTpjSvQM5ZqTsYJv9i3WJG6FMNZ9TxRXUkDIud+WPb0UF53jCai7WTZdyJNamY0kZ+Pl3nDCqdIlvXo2A2Ao5IWbLXbIyiK8rSi5bWky61CYVSXV6+mFkup8meK6FF5/ppEOBQMqGlKd0T504r7ISLWUl1ERPvNKsyqMA78mCGxj8MhvHu7XVUVyD4uVqfcqjy/iGicknNQaQrGSZlUWm1uinFyKMVBOc5aRClUmGJS+xVioAdxoZRTxV2rDMn+Gm5BWOwju7zupiWXxtLwhsV9zLeJnGwj3YNpwt7cUeSVNsPjS+JwQSeGt1rAuCYriXXJ6qQ41alYbLzy+8cpJEmOT5LqGqyqoRTicUp0apGYx1Gvjyqprhnw+6kyojlkPFXjqk9FS8x1Agmy2g36dlqGL1ZEbbqu0gQ+eU3yWuU1nkChcBYgHqs1liuuWAMsl0dOwO9vgmhMqc7agYQEuP2XHwFgl3n2lZvEvaxfX0T/Tz4p+tIUFoo5WVVVxYkTdm65pRUWO/ymw8OEthxjcBchoqT6l1YBmBqhkJVPFg+LVHQpd0cHMpLsFJXB+D5fc9vgZSTKS9udX4cHpt3EkoX30zh1MyF7kHbN5mLGBalTZzVDh4ootrJSZN4NQyFt5XIryK09eiiNY+Vcimc/FjFHel9gRONUizAYJB+sOFasA2E5hxSnLTayIMs1T/7+uk2TvHB1vPfU7Pto3XAPDrufid1XE+P0UuKOZer0OwkE7dxy3T+xWBTeJdaDgFzFevVbRE5xGh9uvIsKTaNrY/HsupLEzI12uTBMjX98MZGNBzpyWbdFpNXfytGAQBtCoeoWZDabqogTa00wosEjxre64kndbQ0wSct6QmKdQqfIbr9NHlCMhBklzhX2JcvjHZfHUZWHClGJJTY2GjAiVYVh2W350KGIYoj4/gGlfeHCZoNx10zn449v4G+fTeJu2zQmNhWpxQjKqPgzNoVGy8oZVWWm1gWfRDjy5XpQEsZjlZy8U7oS+yJovPjMwG5irWIX/xt2YQREazkbtfbTNNOENTuuZ9Oeq4h2lGDVwwxoOYOJneZXd+G+RJbiWscJ9yCKq3p9736Vx8Qi7vHFsienLaPGvkFc3MVXuTxfKy62UV5up2XLMpKizsxB6dDgMDuPZ5J9sHGERaFad2mARTO5+rIvuW3AVzXuSZO0Av5+83s8+uEQcoo6UBWI58iJzgy4/Dlcrv++8bhYFgjZ+OyrCWgYXN5nPhu39WPDzm74Aw4O5rTitxPeorAskeLKBBrWP0hKSiGhiHB/TbNZQ1w39l0+/Ggi8zfcid7WS+d6SyPvG6bGP5dfz9e7ezGq2yK6dl8o7ol52sP9ZM3h8DNhwge889avWJPdLeJs1NqPsAtD2Tg/Z2PKlNsBmDr1JQA6thVQ1ZEtWwCIldUWdRSyIVcYq2lGNDoKVTdTeUxvqCbMFitz7Qny9Yayu6FiSAckgqF6YgTkNthdlEapiF0Bkqvl1i17YMRYrZEoXyEvKpeqeF4H5XWrWoJqxQyFbKTVeF3TVIxTU1lOVdRomtRXkBC7LoX5Y2Iy8Pl8GATo0b2fPIZCQ8TdXbdOfAOnHNtUh4iG0+UYlyquhcSO9JDsCSDHTzHjw3LcFDtdaf6rSgGlb6JpWnVfABnRJEuOTgvZT2OvRDSmTLmWS2M2unYV8t3Z2TkA7N47gk17rqJ34yWM7/xP0iWfJgGHWEAjbR2lAmCR7Lsgv5NChBTfKCpV6kVYZSRTKXO7an7GySoKGZY6TJN6ck7d1v0D4AP2Hz4sr1aYuoT2rVoBkJEhIr69RfX446eTmT/nHhrUycHi8DGo53xiYyWP5qScPkAliYSxyiMnUT0fVVSsoQR5e/QYKl9TUae4Z6vWiWe2kewRk+GXOixyfkTL7q8Oh4O+feEvfznGY4/V5SVe5bHHVlN4UJQVKn5TY+CxXuu4t5foraJaTikm0ckySmocVOWFHaifVsCMBz8EYMuxTH733o2s//p3PPPLN9i08xsATljEvDMMgaqYZqb8juPkkVQ/ZnVWkae//SIjGuKawGNoWHSTrhJh2bJPcHKS1ZiqSD1Jbh1iJKKOaZgmvPTZXRw42pyhQ2fTrt1BOvfajUsrZu+BlsyadxNPz7ydv016jV8Nnc0rn1/N3DkTGXnNOnkFsqux5IVVavFgg4GDXiGwYjLztt/PzvLuJESJcxVVZJCT34h+3RbRoftCCogFs5p/ZhgFEQKuYYj5pSTMAwHZgVZTiIZAFWw2RSlVrqb4u3Hj+vJ99QzJ+yhJD4Zcq0zFG9NC8riKlxcrEcUwsbFyfQsIlOvQIXWv68lrVE+buDaXFsDlDBAdJdZchairtT2s1GglsqEUhz1yfVTrZLzcxkrRl0rDQqFdfJ+tBS3YsLc3Ohp1k48wqtUyNA284eo0pmkKbs//hNUiG7X2cza3T8C+ydEF6Jr5k4rQGqUe5cnRL/HmqmsoLE+lqCKV3LzG3HLVS8TFXILShnOwESPEdTz6aF2eeaYffcftJtp+IfL737V4lweX00eVz0kwdAFCqItsHTtCMAivHvw9774L+/4kiPNlkjDsOqXteZxbSroryXGLRqk3muzDrejdfRld23xDVVg4u/FmkMbxx4hzuikqS8JXBVe0Ws3eoiSWbLqcgVXzcTgC6Lr48TVNRbIU3mZUtM6oYW+ybPkkThS2oAiNKn80/pBwThLSj1GmRX1H+CwZN4ZM/JXLazEMKc4Y+Q2VQowytW2zCfcxxiX2H9JKOABliNJvzarSzaXyOMJR0KUAoZIvUK6pklw3zRjpbDgjrTDipH/dqpVIF1dUyOBKV0GScHhiTmqCaaFa5LDslLR9kfy7UDobJ1TZshSitBrCkW0kv7w9HMZtmuw50op/Lf4lVksIuy3Aur19KKxIZkyPGeRLonDS76fwyCOQmyvmyk/e/hPIhrIpUyYDsEFWp3SSI6pq8JW/GyedULOqmkOsbr4CS52nfEYxuTesXw9Uq+3FyZs+QEYRShsj/QxRzBZ5barw7oTMXTYJBCJ9WSpO6RyrtsflxCuMcC5Uxl5FE03l3yqv75Gvqx8K5U+rp1TpVARrbGNiErDZ/EAl9RFMe8UXUaVrt/cQk19Fh2kSVfjgGxH95dqEvsGoUQ0BmD1bdEXt1UvktevJz+2U+7eTfAsVE2fLcW4iozGPaUa0J66SY63GUN27S4donGwiv2vIEst2nT6kwJ/A/OwbcLo8jG+4AgCLUhR1Sw0GGWIfVvoc8t6nKQ2ERKl82VyiU3IimnkSlVLdeGV5T1hqKrgqTLIkGqDq7UsksqHulYrBWsj9GqpI1zTpmnqUQeOE7sGKgqZM+fRu3v9kMr8Z9yLIRmvVkl3xiLnmAOqdhKypu1iO3y+bkqBavKsnTCBdKRLRsEoksEGWqAD4SnKZklRuX15rVVUV3bsXMn16FpMmpTJ05m+ppybTBbYdOyCkw8qvoXPnh4CHzvGTp4ZbbS7wlZ3eJk4UWhtPPAGxsTD5R7T3jImu6VwWlyfx+qx7CYZs/PGq14iWvZ/iz8MJtVqDDOv3Oqap8e2mO/h6V18GtlvF/rxGLFx4M+PGvUGdOmdunPdDLb9UVL7YE/Zd8lTm6SwY+v6fN7c3io9WD6eyKga/jFbCkomjSTXoNGclY3t9it3mjjgaqQn5/GL0S8Q5PHz69XhWZQ/hWHF9LLp4YjcMhC+/hHvvhQcfvHjf75LZ2WQ2zjHQq0U2au0nabpuMKjnqxQXNWdvXnuQzsZP0VplHGLq6Nf5/ad38/yc+7l97IvEx5y5n8WltIkTwW6Hl14ikqq50NahAzzzDHTufHGOfzHst7+FLVtg9my48h7xWkeZZtyZkwNUtyDwVMlSSSmOkWealAdEABITCpHi8+EwvRRXJPHyvHsIBh28MeLvtIw7Qp7MC4cDst1DoBSn5sflEAGOSmtZ5I97QURe3mDW6htZt7cv47suYkKvxbh9Lm576xmO5TQhOVmQcBUB02uEk7OqngAAIABJREFUI8J1AYlgGFJWQAkmalJf32WVjSYlLVjTNDxVKcz86lkA+reaxWWtZ+DWdwBQZohQ0zQVTVOZErlTxNOqyPGEpUTa3KtS/+hoERwosSy7PUp+RrZjkGFaw8xcVm/rwezNPRnS+ZuIdIBqvpnncfDC3Ds5VpxOckIBochPodqKe3WwLIH9+fUZ3OlzPlp+M3US8vnF2FeIdnoJGDC0zyzClkr2He4MQTH2zmLhiP7xj/xXOF0/2s4mIHqOwmU/ytnodgZU4dTr0oBT5YK+K05b0y77YZcUMVVbP2/qCwDsLRUPTlw4jKm07SXcqfpdKEXI6jZO6lFWvHKlXqFIWoqbUSq3amaph7NUbmV/koB4WN1uEYUaRiU9evSgJaV0lZ9UWIrqn6LQBFUFoHj3qT0Fh+GVKb+u8b3vuOOOGn8XSIRn+ICeNU8gbdiCBZzNep51j0thZRgG5OQI/oOlyW503USzBCgLRJNrygdb3sPNSs1Qfro4HKagIpN5225gQJv59M8SkuZZQbHoOyWCEUySioJysbEo1rpkoqttqCpEkkc8Pj7JM2rWQjSy2rlHYEENGgvI1ybnWZwceyNT9l2R3EtbJdTLOIR3zBv8Zd7dvDVvMvdf/2cCmojcNa0O4qmKApqCTSJtcnKEwza8XqU1qRANcfC1axcD1dVM3fuImXbDefAarrpK/Ku1mpacLBywYEg/7yZ3vqCYMxWeON5bcitV3hjySjMwwlaeGfkiLVO+v+x38672fLO123cW8KDUi/B6nRwtbsD4rouY2H0BpmYhNuriNCTz+hLxVKXRucEarJYgK3eN52B+O3RHiOYN11O/1dmFvS60XTdkHpVVMUxbOhaAsR3XRN5z+6J4Ye7dHC9JZ8Lwf9C0/k6KTFWGLWAqTRNjVZTjZPbiO/lg6R1kJh/hrlEv4XBW94LSNOjTaR69O87j0Hbx2Vnrn7nkTsa8efN48skn0XUdq9XK3//+d/r27fud/YYNG0ZeXh6hUIh+/frx6quvYlGaRWeysyEbl8LZqLVau1RmGLBwYQ++/VakkUpL19K163s0rruJTbtHsTj7Woa1m3HGFggFFZm8vuL3VPoSOJTfivShL9A87cAl/AZnt+YZhxjfYyHvr76KKm/0hVAIrrWLaAMHwhtvwPvbn2TGDFj+jHDsC2UpbEgiG3mmguiFFXmjeGXBLwBYtnkYdqufpsm5NE08wm+7zqZVfC7R0pFUFNiQTAPqoRCb93Rm9vKJpCWUkBotuQty3qtAymkNMqHnTMZ0WUngJNI3COG/UEgEQqGQ+GBRyB4pbdWkvEC0RDiipWa/Eq+KkqRSt0JCAtHoepCbu7yIppkk24vZW9gad1UCy9beyoiAk/5tFhPUpLS6qdpbKFE7cbwUU4xbrKaj6zrHcROQcguGIdOAVsHVioqyya0SIhPX6pahbqw1wI1jpxOeO4lpS8dSZRj067SWQJWDF+fczfHidG4Z9ibJGdvwByFgqFR4udyKv+umHWP04Jc4sL83Y3vNwGlxY5HpGY8ca5/Pz5otE9m8axQAv/kNPP/8pUU1Bg0axOjRo9E0jW3btjFhwgR27979nf0+/vhj4uLiME2T8ePHM3PmTCZOnPj9B/9PcjZ+SjZFRv5vTxUT/eTCsWwJd6o8daLSpJDvF2qKxaFGWs0e1WmxZkcX01T4jYpyBEZiGFLpsELgFd26iSqedIqBUgYDyfKHJSCDj63yCOoKrjklEj3XQLPOJWDmX2ybMmUUgwevY+PGltzcdzVOW5A3V1wOYS/9uv+DSn8UX+wahxuTCW1nUOlL4L1191HmSUFR0Lz+eKxWPxOG/ZWla27gL0se5KFr/0CCXSwunfZLNnqa2CpvX4ILGDbV4VGiYEEds0gcPfqUas1UyYewy3llKnREpiEi5aHy10ehVz6gIiBmn0fTIvotwuvQAU2o1QbFj4HiCvl8bjp1Uo2qcuRW9hSSDP/4oJirxReCVl5rAFxzDbz8Mtx3H1x7LdzW9uwIh9vn4pUFD3C8RPyIOqw+Jg97icvSRIlmQ/P7E+D7jzRn9vJJtG24n4fHTaORXUwi1WH2uCQpFlWplEQ1zuzxR3GxTNMMLLLN/Li2/wag0hnL+6t+yYJN1wHQq+3nZ/x8aWkdvlx/Bf27LqJF+tEz7nc+ZrWEuWXsh7wzdxIzv7iKtdu743bH4PbGcMuwN2hZfweF56DB17DuDjrX3RGp3DvVtu4ZxuZdo7i260ZsepgXXuhBRgY8/PAF+RrnZDExMZH/93g8J6WialqcZNqGQiECgcAZ96thFmqrUWrt52PHj6eSnFzGPYO+QNPg67w8tu++HotuoXfX13FqsG7XVdhDTnaf6Ei5N5HWmRupklGZxWrQqfUC6qaWMKjXdGZ9/iBF5XXgv4QbAfDN3s58umEYDbP2EO2qpILTK0rW2n+P/epXInM3eTIc2z2e+8bPomEbQVTNkaWwLplmK/RH88/F95NfmsGYvv9kzqo7GdZhHg2Sd4IhfsjsSvraJsWnJIoQkj90ufmNMNF5asw7OCwh6shARwVIqvlbqdyqKozSYDRvzL0Hix6iWdZOXGHhsFaGZNrQsBIr260nKVK+lKhWIoinJmFUKwRT/kchOnUkb8Rp9XJbj5d427iXBZuuIxwO0aflQpwS8alvFak+X0kW0xfeSaUvjtzjTbl75Is0zjxOHFCki31Us0JVdeN0huRWkfRFYFdHojFKdqHCEubqsR/iXDGC0tIUUqPLuLLjatIy91CKNeLo6xGeijifkmZX1SsBw8CUY6oCmCNh2XAvLFAio1FXDBuwvrp65lLanDlzePzxxykoKGDB96THhw4dyvr167nyyisZP3782Q9ci2ycn6mMXJhqJ81XLB64NDn568mHRFXVlEjk4kiE4S/+1rQvTzoamDLfp2mKrq/wb/FjUVEhopahrUQNTZoER9VeJ9Mo1AM9/H8AkbiQ1qZNY8rKoChgx+UI8P7EffzjqxW8vuJyjhzriq6HSY7PYdW+4disXob0eZq0lN1UWQVUGyV5E16LhZC1WuulRMLTZSWyW65cSbR02asH1ZtGviEjIUu8Ttgh+ysUiCVLVcJESSQjRupwqIqqYhn0JhbK6DWoernC7oIs/rHkJppmHmDUyLcwNMBUyo3FCPzDA2yNKNQqxcLKyiDVPYulEqysZWkg+/w0790bgAoGn8No19r52H33ie3kya24/8X7I/LuoaBKS8iyykA0/qCTiQNfIjMlBwC75dxYt25vteOpYeCwnZuIw4yV17ArtxUevwtfwMnEK/5Bg4yDFJ5v17WzmGnqhMI2rJaa5dEWPcyknq8AsHjLjcRHF9Gy0ebI+wVlmUxb/DCaZjB5+N+ZvmoSr312P/eNeYXYCyRXb7WEGThQoCq2kGRxXcAq7mb1l+EPxjBzplBM/fOf4a67Ltzxz9XGjRvHuHHjWLlyJU8++STLli077X6ff/45Pp+PSZMmsXz5coYMGfL9B67V2ai1n5PdcgvMmQOPfjCJ/7vhQxIcAe4csJJ9ZdvIL2uKx5/KwePdqZuyk/7tpuFM+u/iY5zNcsvSME2d6y6bScB2kco+au2i2X33wc4Vn7B1X7NI5OsukS0DbCKICekmnZquJC1zDx6fhL0tFrDZIk29iuRWifVts8Dm3d1ZufUK6tffS9AaxuQk/oTcKn2JkBJUlAHU1hyBsjRqsJsOrdfTou4uTKwky8Aq8aTmmVZT/L8SPVTtGkpV80a5r0ImVFrB5aigLBDP+5t/x5Wd/kisU6YaFUSvh5nY8xW2H+3GkaJGNM1cK45bVId3v3wYHYMHBv+ZBsmF1B16lOcWP8ar837FvSNfJLOuqC4pRxC6w7IiJl52kMi0Cw5HiuRqqABcNdkMGEpoUZD9/bKRpWkXxwlLgTK77F6nZAkMwy4/LwLE42YIu0xq+01x7/x+cbbpn34KwLRpQsjrF7/gktirr77KW2+9BcDChQvJzBSFDP379+fAgQMUFRWRknJqBZAwp9PJ6NGjmTdv3tmdjVpk4/xsjEQKVk2dGlE77Cj7PRzZJpQH9VSJUKiHSe6naSoprxT0VM5csXiV26doueL1qirhRRcXC4jP2UREJ5mnfMoFeCSkoQhh1Z0Kag1gxAj46COYOLE+T3/1OItvfYbYqACvjSkDNjJ902aWRt3M1weuYlvOZTSOOYKmgS3SFUH2MTBNArLPjiUcxq4UbeXi5JLKoWaMRDQklGFIxU2qpO6GC8JO2cVTVr6UAaVVqby9YQrF7qwIw0fXDe658p8Mqy9UOC2y3CkuSyIjeWaEwBckjFten6puMk0vggcUlD1xxHndbklU86RAluQLHRUzJyCrUfrIUqIDsv5rypT/BZWh/07r0yGbPh2yIzyrgxs2AJASL37oKqUj4D2P/peb93Rn1vIbyco6yLBhH7H9226ATmFlPKmx55YCrJ+5nzHDRI8czoGjcL4W5ajANI+TW9SNVbvuplm3t76zj8cfi0m1PnoobOWdr54A4IEhfyY9Pg+wkhJTzCMjnuPZhQ/zwtyHcDq8xLgqGTVsGilJgvNmmrBm8zh27OtfzaE66VztGu9l0rBPsFoublPEU+3mmy/p6bj33nu59957Adi/fz+maaJpGps3byYQCJCcnFxjf7fbTWVlJRkZGYRCIRYuXEi/fv1Od+iadrZqlHO0n42zUWs/fRs/XjkcMKxwEosf+ZBqVUMY0noaHk1jy/5xeEwr7dq9c0mvr7QqlTfXPkNVKJruTecQEx1FMGxjZfYVnCir893671r7nzJVTvy2LDdvLRty7csWTiayUZvFasUiZbatFgsOm40yiRLskmjAQS2e3bs7svSLq6lX7zgjR2Zjs7WmUXM3G7cG+PVHd/Hgdf8gOUFE6MpZVZwPhUKYgGFWt06PlQ5PtOSRqM+FTDPStqFcSvoXSSdaSXk7FJoi04Tx8lgOXcfhKsfl3EqRpyEWSYxWDenKKmN4+8vfYrMEaNtkE1anE583nkpvEmO6vkti7DH8BmjyfHWjCvjjqOdZkD0Ir+lk08F2fPTJr3hw3Ms0dXj4dMMENuwYSof62WQmytS2LMdx+52s3N4Fr9/BvaOno8lUpOK+KLdENc10WdTnVUM22XzTEO8rhANcEaK/zS/E+7r2U6Ts/7zNnj2b9957D5vNRlRUFDNmzIik7zp27MiWLVvweDyMHj0av99POBxm4MCB/PKXvzz7wc+ms3GO9rNzNvpNmcILcjFQXIlG7YXa5rGdolukL0FEhwUKYtQUziAeUE3Lkn+Lh6NaZleoYfh8IrYpKhKeePfuIrw8IbkfyklUWfbNVCMZTWq5Gt9r48fDjBlw7bX1GfbO4ywY8AyxjgBXS0WohOBbTPfGsD5nCA3ivyUmaxMADoeAPnU9KtK7JmSaEd6DWoyrZDDkyJV9HFR1QKRKQPZ7MM1ImaHSRHnn24fxhKLpP+CvJCYeJjk5Eb/fycrsKygyzYhWiups7JdUII9mRhQMJb4iTykkqTUtAzFbNSCdKllpUFYmjtOz59Dq5iQRUqnQIzkQUY1RKri19t9gmkSnCspTa7yefbA9M5Zfhy/oIBy2Ua/eMUaOXILNJu5ramoJ48YtYN6cK3ljzo0MufX18z73iaJ03pt/O2WeeKyWEFf1nkefNqvP/sGTzDA0ZqyayPo9PQmGd+KweYl1udD1ai7JB1/dzfbczhimjtUSYNLAv5KRdBjQKKkUmhTVnWNrWmpsKbf0noXfbmdYxy/54yf38dS/H0fXwoQNG4PbruD6Ph9TJ1Y81ypt5ANa1M3lraWj+WT1EDr3+ey8x+enaI8++iiPPvroad/bInuXpaWlsUGibedltchGrf1c7eqrlcMBw49M4r2r5pAvIdMDpW3ZXtCTmKh80hOzI8Lxl8Lc3hQap39DYuLhs+9ca/+zpqQAd8qGeQdkI8NUWZ5o03WsLh/tmq3ni+yBuGLLaN9xFfty2jBr8a2kpBTQsl4ODkeAjh3zsNmSI6Rgi8VCVha0bpvNjh1tIw5smmpzrhAOVbqNqMxwSNSgyt2Qtz65F6se5sqOK9mfX4/pX04EAzo0FdL1/pAoZVUih1Hyh9wltzGmzsdf3sDGPT3p3XwdO4+UUuZNxF/ejJTYo1gkH+RYSX2SYgtpmbWJtvXXkVnnKGChoLQRH634NUkxRfRouosESaTWpfNu13WsqtJF02iYVMjjY/7K6j29CYcgNbaAcZ02oWk2EuV+ymUJAqO6rGXB5u7kl6QQlt/bH65ZS6OcIl0qj0bL8VPpGL+uEFPVJ8aCYcgycilfevfdd5/2/v/PWS1n44fbryV68IpEOBQxuVnr1gAslByOI1HC+7bZJCwouyBWVoqHw2KR4j0hoQgaCAgtD49HcDW6dFEwm6fGeZSTqPgZVUCXWkTjvKza4ahPsxfvr/FeQnQlTmsJOw9MoG+LV9E1A61c3AOrEYs7KKL83LxG5KVsByA2ItUsTD9lEVPqCeoehoCAhGb3AwWVdfEFY/HqYLE0BEDTEiOLVUCLiRxTdXMNKrEn0yQoVWaP5jUiPmGnPIvC3hIAK4ahUVWVQFmZuIrOnRX/ohz8CtpQi6qYg1Om/EwWxJ+gjR34HrphZf6aq5i/RijnpKcfY8yYj3A4lJLl6WsoNe38Ow8WlGTywWf3YtHDPHn1q2QkFuINary86Damr5zI9JXV4k42q49hfd+gSb3NNY5hGBofr5rExj09GddtPmO7LuLpTwpwOTwcLwNvoFrvQdMM7NYAl7efg80SBCwcL67PO0sewmHz8esRzxPvOjfeSZ34Iq7q/ilhmeLRtO8PtfUfMD61dgarrUaptZ+7XX01rF0relSsnz8fgOKSRBau706ZpxUnylvhD7oY1PY5ThbkTU/aT9N6G1m15RpSbF76tjx9idjZzB+yk+9J5WClg+nrf4PV6qNRo8+pbqd37ta1/g6aZOxn+orrGGz9mGbNsn/QNdXaf96UAN/UqR8A0LLXAwDs3Cn698TbhUtrtwa44op3Sd+1h3JfHWy2IK1b5+NwxKNpolRbKUlHInFdzWQbJ8vlxsnIPKSECfXqihCbrlNelMZ7Cx7Apod4aPjzNIgtk4IRJg9e8RaLs7vj9olzGhpsPdyZhSt/xS2D3qRlE+GQW3QrHy2fxMbdPRnbfSG3dF0MaNiARIeHWwb/DtMkgjZc0W4RH6y+nRlfTeaGAS9RWFqXd5c+QpTNx6+HP0urhHLAgkPur7QxDASCUwWUGAbegJNSt4bD5ifBITvoWpW+RnX5OFQ39DRMMRYByTcJBpUQo/rJE6/7FcdFdqJVAYFNOv9eGRoaho9AQLz23PTp/KysFtn48fYruSjMlAiHig0bSw6HTypurF8vvO+QFMApLRVIhq6L8spwWICZXbq0lkdQFRCyrEpyNRTOofgZqm9HrabGD7du3cS/O+4QUsEpcRUkx1Xw/C3TWPJtR95ZPghH6gHq1BHcDT3QB4CmbRZR4Y9hzoabMOJWYo0TFUeXSeKcyyWeLj1KEcrEouSReZmvK5J45PPHqPCInLvDUU7Pns8RE1OCy3pCfqYVFosVXQtTdiwDewcLFt2IlOUpl8SiadjtISZf+RpPTH+KL74YT9uslZFW3V6vSSjkJRy2UlJSiN+vejMonKWQakxGvDZlyjmwzGvtP266btCxzdd4tFT5d92Lcp6PVtyO1x/NI1c9RXpCAScz/qyWMJe1+pKwTGOENI3+rVbwypIHefeLu7hBf4u2jbaxfldP1ktHY1z3RdVwn7TGyfvl/wl+Sc9mawgbVv695ha+3DGSTQf6Ybf5+PXw50iJLeJcfsEKy5P5/YdPYhgWnPYq7hn2Ck3Tv7+svaginnJPHBkpJ753v1o7R7tAnI1zr8GqtVr7CVilN4ruLfaQHOtmRFfhYASD38UAdd2gXj1BnAoEzw+JOFaZzJOfP0YgGMWwHm/QrdvrXHbZU8TG5n1nX5stxKhen7L9UHte+vwm9uQ1ivw7WJQZ4Z2GDY2PVk/A7YuhQ8uvOFHUgPz8+uTn18fjqZUY/2larPzXEGhI69ZDad16KMFgEsFgEhXE4bUk4rUkYrG45D+BZlitAazWABZLEIsliKZ50TQvplku+3dIeX3TFGk4hJupaVqNfyYaYU2je9vVGKaFj9ePocgbpsjtpsjtJhAIEAgEcFkspDudpDudpERFUS8enhzzOg1Tj/LB0jvYfbAHxaWiaH9818+xI1wFG6LQ3wI0sFhoYLGQoWlkaBoxus7QVquJcZbj8SVQ6Y2nU8NvSHPmYQkGcQUCuAIBksJhksJhEkyTBNPEpeuRBOK3OU0xDAt92i8gOqqcVxbdz+6ilvgsFnwWCyWI1oNuTcOtaZyoiGfq9DsIGzqDuq7Eqes4dT0yrsLJshMOOwmHnQQCUQQCUeT5LOT5LFT4fFT4fBiBAEYgQDDoIxj04ffrlJcXUV5edGmmzn+T6ahhO/2/c7SfNbKhTE1sxaGobnUhXPfu3QXCsWOHiG4v6yyQikz5SUN2XPFJbsYJuQ1IZKODPJqqPqlfi2RcNItPtHHE34dE30qSLCF0zcAa6s7gXgexWg0sHALET8CugwE2bYJobRwB3/8BcECS27Jkg6qwR2wVPFtgmvx90zWUB2LoP+BtYhOPY6myAFERCNaUCpKxmujR26nLCao0jaVfj2Xt/pp91Pt0+IK7e8/lzRU3sHZvD9ITjrF5x2A276hW+rRYQiQnP01MDHTsqAGqGkrN1DJUNFmLaNTa6ayHdDY+WzWB97+6l3sGvHpWHQqXw8djo1/j6U/v4Z9LbgHAoofQuPR8iG6tl9Ot9RdMX/wob8y/h+Sr36ZlVs539vv3iivJL0vmztHv0CD9CHkXWCn1Z2m11Si1VmvftTffhAkT4Pb8G3jrhg+5/spFfLBwBO9/PIEbJ3yM5aRGWS0a5tC//VZmfTWA4sb5NErcTplbPFWHpZaAIR2IOnH5ZMWJdJk36CQp7jiJicdrnDsUslNc3BivN0Ra2kGquyhAn87LScvag9cbEym9PXawPV9vHcSh3DYcL00nLf44J8rq0qb+EppnrCajWTNAY+7ywRw/nkxSkoe9e9NISbGQlFS7iv6325QpYwCYOlXB+YJv4HYLgrLDkYrNJpKpFouYl5p0UFX1SShkobg4hWBQzBnDEPfdX6GjYRAKiTl2XM5X20m8B3EgQNeocDho0/UbQqEgi9dO4pUVd3FtrxdJkaBZYkxMpAeKUhAtC4exWd38ZtSLZB9uS9i0khxbjF8zONnfUC6LUjVVpjgYGhreQBwmOhZdxyaJKFZ57ZpS+ZQpzJCuE/D78QCmTF2XlTcgPfk491/zGi/OupdnZt/Ow9f8k871j0S+JsDwrmvZvL8l81ePIC3GSwAfGcl5eGXDxSpdBIjhcLQcX6v8W2wrwvJIYSVrIL6dz5fPsI4qXPyZWS1n48LZKIk0vHlKdUo6gpuRILcxspCyrXxf7af41Op+qPejEbl1VUlfi2hcfBs3Dj7+GCZMqMd9Kx7jmcv/Qibw7MIRzPh4Ak9MmInNGqYQ0HWTy8ZupFyLYsXWCaxgwhmPa9GD3DboFepFF7K/qDHJiYcjC71hBCgsbM62bZMISDZ+ncRj3DHuFWJc7gibIiG1ggQqIvoZ6fVW4rU42LatB4mJ+eSXZtKz8zSmjM4BLCRLzsaIukcZ/0KAkpIYpk/vg80a5J5J00lspJCNBKZMGX7Bx7LW/rNmGBqLF49g1662p30/LrrstK9/n3VvLUiqi9dOYsba+7nr8jfPinA4bX66Nd0EZ+h6ejazWf1syekKgN3mP8vep3xW9o55d9FkdD3MbcPf487R/+Lp9x7h3aVj6fyLl2vs3zIrlyeuncbTM27mj9PvASCrzlFGj3mFKOepreRq7Zysthql1mrt9FbtcMDkozfw0o0fkAe8v3AEz358DY9e+zHISFLXTcaOXcm4XssJhSwcPSw0MgpscfJ9J4ahs23dSP71xa9w2b1Y9DADu70XkcsqKmrO5s23ER1dSI8eb1HHHsO8L2/m7bn3cce4l7C5Tr/IaRr07r2MsrIEcnNb0KvLu7RpvgRoUWO/2Cg/zdJP4A7auW3Yv3j1s5G89uH1XD9pLo0aXZh23LV28WzKFJGGnTpVJGrbthUE9EOH8rBaxY+vU8sBIFPTyT1RDwI21uzowa7dbRnReSkd0gX5UnF8vBqkxRXilw7vMekIKH2NUARVABsahlX8WgQcfjp2WoMlFGLBhpv55yob/dssJ7ZKp2VaDrpmYpXlpbZAzUZyAYmeVFosHC5ogCcgkIiSgAu7NcABRXxWnVJlJch9V7xAfnkaulWnWcZeHDJVqXQ8bHKraM/lVVX4/X68wKDGG6nrcmPa45i/cTDvLLyJtMQiLJrB9f2Wkig/o6gDHqBXvRxe/sWL5BamUVAZyztfjGL+vF8xefybFNtFGYA7LJpmWiwiODAMZ41tOCyebr9fvN+jrc5dP9dgsRbZuPCmJtMMiXCo8VXpKvW30mI8hYwdsZo9X6Hdz3WS/gdt3DiYOROuuSaLx1c8xoOX/YXN29uyYW8LluS3JDNTMXWcaBqQ3g4r4K3cCECKYxUAumzUNOqKvzJ7yW/wViVw09BnSYo6iinFmtbsvYv4qAL+PPzPxDo9OFwu2rg8PDX/Abbv7E3LrqK01jTT5Dkd8thhiotTyc1tQVbaAa7NmIPuNlHKCqpaCYSuQpzdT/8GR9CGfc4T79/It2vb06vRTu6a8uuLM4i1dknNNGHWinGs2to38tr4np8xutsSYsOqw7T4Ya6MpCx+mI50jxbLME2NhRtvIvtwJwD6tFzHHYPOXta5K7cVbyy476RX5qJpBgeLGtM45eB39k+LP0Fa/Ik3IVFAAAAgAElEQVRIz6mTS3bPZlZLmLZ1d2CLjaVV3X08O/8eDp3I4jdjp9Ot2a4zHis9oZT0hFL8hkFKXCnPzL6VFZv70b7HwnM+d61Jq0U2Lp4p/UdvZNkX7kWpdDe2yVezarxbLaek3p9c62T8R23sWOVwwD37H6O4GPr120pGhhuoJ/dqJjZZomlRYKu4q1brWPn+bEIhG74j9enZZBUZcUdpEHOUEl8wEpkZOEhPOoaeEMaDk5Cu07i+iEQ9YRuN5H755h4AyuQPRZBkUlMP06n9HL7dNo73Dz1Ns4aH2SgVhYsj1GULRyrnAPDnby5j5VfdSIwrZ86iFjRuXDvHfjpWnaAFKCnJwWbT5CshPlt5Deuy+3Jlxy8Z1PBbYhxVdEg8CsHqAMYqkYsCiTKUyL8rpTOiAiKL6v6KcG3r6uLcHqeYU07DYFDXtXRunovbG8PuI61YvHEowbDBrd1fR9dMHPKYSkFUk/N495HmANw06q8ALFyVS2lFOs+veJwhnaeRFh2iQeohkh0CyTHkcSxyG5bXHpDHDSttC/m+5vcTbbFgAPFRQvsDu504u8nvr3uL8qoY6sVXABqx8llyqhYEClWRf1t0na5N9uGwBTBCUSSpc1tUl1chRKDaFhiGFPcLiPFKDO4G4KEpM/jZWi2yUWu1dnZTDsf118PvfgcWy2a0cw+sKCtLY+nSO/F6hQi1roW5vu9r1E9bCUBOXm+KKjJpmLbrO5+NcVWwaXc3BrZaQ1LsmfPrXTrORdNg09ZxbNpx+vy8UmdZvHgASQml3HfTezRufP8Z9q21n5oVlqazLrs/Q9uv5KZ+c0iSLc/PCJ+eo7mcPnYcbsxlZYkkJ5R+5/30pHwgnyZ1D7EjpyXr9/ViRMs5sgvrmc1u9dMgUzjUTruHOkm5eL2VfLZOKNZ2aLCROwe8/H2H+EFms4ZJiSvnfNCR1bva4w/YcTm8Z9+51r5rtdUoF88eiSgAqiZHggJqlZFJroQucyPunpLpEtHElCm3XorLrLVztLFjobwcbDaYOrWBfPWQ3Ap1RI6KpFeHDiLKys5eTWVlKl9/dR8WzWDK4D+Q4irihTX3Mn31PYzsXAmazorND9OkziFu6b2AOBlNuqQ38+DIt3lu7t3835zJ3HD13zGiBBapy0Z+oaCI2ooqTOo3+pYhw4oIh3Wqs9cOuY3jo48KsOLn1ol/5bGnH8Jur3U0fmo2ZYqQl586dQ0AXbp0ZOfOeQCYATFnutbdTlQoGKkI0ZUyqJxbQRmZq5RE7CnKofop6ZbJwz9hyr9v4/V/38kTk/5BcqwgFRsS4TBME9OED5eO50hRA65oP4+s6KNoYUhQyp6qpFtdk9wqvkjINEEL8P/tnXl4FFXW/z9VnaWzEJIQEsMSQEjYSdhCWMwbUSGgwCgOYthkiSyviC8j80P0mfzyG5dxdHjGBQY1As4LyI4BhCAomwxLgiyCbAaESEAWs6fT6e33x73V7CSQBFDu53nyVKfq3lu3k+quU+ee8z1/TJxCQVE4G3e9SKnDC5ecs49h3ctYECOw2iJjN6wyC8UoUBjk5YWXtzfegKc8VirnkFfmy77sFphcGvXqnKd2PZGNUiDHPC/jTH64UI9T5+tTbAlm2bbeNGvwE4902uL+ZHnJoH+rrPKqaUawt1ga9ZElKOJaGUKN9zFqGUWhqDyet+EGPH8+ihJrbeIi19G87lEAxj/0Ju9ueIuth4eTXxpOeOBR/qfPLHy8yrj649Qk7BRtIg6T+WN7cn9pxAONby4I5ONjROobC3LGY60XJpMTEw5q+ZfgVQ3lnhX3Fj7e4iaXcTCemIaHQSuvoEflaPpALqnPzubPn41n/Xdx9P+va2MWzuXXZcehHsS3/IrEmBVotusMVAk8PcoJCTqJl8etZZzcCht2d2X5t48BonLuK08s4bE2e69os+enVry7ejR2p/g8tmiQzcSBczB7lWNRJVNuHbWMUvNcXcRq48blcv8rd2M6imogJaUnAKmp78s94QD4IYqfGZUnHmkbzMOtDzPj/AZ2HOuNpv1Kt+af42O3o2ll5JU0pVHwEUZ3fx1/X1kozSgdL7czvhpK1o8i+O702SbknG9O69a78fcX7mdDbyEmRkhUB3CWwiI/ThxvxplzoQTXLiS+Uxbj9Dw2UgaNG7uLCCp+yxiFEXJo1aotAEeOrKFz53lkZg4lZe0Y/k+fNDxNdncmiNOo4npZlgmAv/zd0MA1JMct8knfpmlE1M3B7FWOy+GJr/QQlEnPSLnDgd0lrNcWYUfx1TV8jBgKeU6HbGtc3y5Nejqk98TY6pfVYzFpGt7SwnfL8svjNlk19WoPh49sH2Qy4eXpSQBQLM+dZ5QLcAj5/5Tk6SxY9yRvrf4j+84F4+sllikLrF58vbsvYcG5DHpkDv4+EFgrD4fJRInjUuZLqPQAeTmFQKPbMyQ9I2fzxXjPzp7NfY8J5dlQKGoSXXfxaPQHaJqL7UefBaCe33HOFjbFQy9jdPe/Yva8sbjWL3mhgNDoyNqXgMPhwZEjbXnyyTnUqnVttcuLeYHMnDuCvIJAPEx27A4PTuaGk9x/Vc28QcU9RbNmW2nsDUu+Hco/1yXzUu9P8PK4uQZGZVi7uxslZT4E+RdWeawzBaF8lx1LgO/1Y5BO/NyB3IsN6Ri5vcrnuppf8oPZdbA9gbUKCQ26yISBn/HxsiF8ueuxK9o1DD3BiL4f4msuxazcgNWCyVRxm4q4K8bGl19+yVtvvcWBAwcwm83069eP6dOnU6uWWDd/+eWXSU9P5+zZs9SvX59p06YxfPjwuzFVxT3GmTNnGDt2LFlZWZw5c4YTJ07QuHHjWx4nJeVFAFJT0wAooac8Ir7cC+VSRp3OQTzd8RArV7Zg+95nARdms42AACsBZlE2u7t86gqQH0i7dNUufkZE61vkU9OOXxrxevoEli8fwYAB75KfL55w/fCiqNiPj+aOodzqzb+e/4ioemfZsum/SN2UwMS49tD4m1t+j4p7k0vKousxlsyaNxeibMc9vyPOvoodO/rx2pcTeLCBLG4mrzGT9Cp4Si+Br6bRKPQ0XR8Unrm9OY05/HNTrNLDUWQJZOv+HnSMOkDPzt/iMqqkGh4OoNyIzfDwxNPLC6eMrciTngeHvGGftIQyfc3L2JwejOj9oVvTw2X3oazcn/37k9h2KJGIkByGdVuBWR43Mj0Mb4x+lefEXfVV/h5iMuFhMuEACuWxn4tq88bnyVjLPRn3TBpWqxWwMrbP+5RafSmXcy4DzN4WbB46Ftel7BQfuTXkCAwtECPjxir7FxWJhPM3li+/0b/vvsPEpajEqnBXjI2CggJee+014uPjsVqtJCUlMWXKFGbNmgWAn58fq1atIioqiszMTBITE2nWrBndunW7G9NV3EPouk5iYiKvvPLKHbsedB369/8eb287eXneBAUVs3NnFBuPPMHDzVdXepx6QecIq32Rny7Uw2IJAFlDB6CwyJ9fCwNoEn6GBnVEEF9Kwmayfw1i9uxounat7neluFeJisrCz6uQTdsGkXO6RaX6FD6ygkC/Qt5bPRSH88rH0E5R3zFuwHKpFHptFoe/bxEeJhtr9ibSot5hzJddl5eTdawz+SVBTHz6dR6ok0uJA37Kbc65/MOAzpaDT9A49AiTH/9IZn7cQtpXBew63I6LhUG8NOwDGoTluoscaxr4mUvxMAljQVUWrX50LtUPqwoVGhvvvPMOO3bsYNmyZe59EydOxGQy8c9//vO2TpqUlOR+7evrS3JyMimXrUWnSlEtgC5duvDQQw+xfft2ZWz8xsjOzqZz585s2LCBDh06kJubS7t27Vi6dCkJCQm3NWZYWBgTJkxwr/dWlZSUMQC8Ja+5crcmoaGiIjQFdN1Jnz6HgOM4HDpFRU7S9w/ngqZRK3QnAAFO8eXqIb9jjWLhJk2j2Grm/6aP49TFesTFLUXT7HTq9BQAJZQSGA5PDdzBsmVx/Hl+Eq8OWcA673JK/UrcqpGK3xcpKY+RmipFVeTX+fnzoo5KwwcvMLTJTMxmkT/hIZdTTPKmGmASBoGv08T8L4cw++sn0TUH9R84SVK/j9B1cdzTZELXXVgwgwO8ZQyERXoMCl0u8C9l8IC5LPxiJO+unczU3u/iby7FYhHntsnPWqm8lQfVPYdNN/Hr2SYsXjcRL9NS6gee5P89PgpNc+Hp4wvo7uKFxifViIswy3PXlh4TY04+0rNhNpkwmUycB4xkXYsMWq1bKwentdytcqrLuZmkp8KIC+GqLB3Du2J4VYzw2wvSs1FcKjxM3i1bXvN/ut8xAbWrYZwKDcGhQ4eSkZFBvgyYsdvtLFq0iGHDhjFhwgQCAwOv+9OuXbtKT2LLli20bt36uscsFguZmZk3PK64d2natClvv/02Q4YMobS0lJEjR/Lcc8+RkJBQbdfO3cBkcjJw4GqaNdzOtn3DWLen503bF1vNTEmfwKnzjRjZK4369Y9ct12bNjk8/fR2juQ05I35SWz7oQWrdsXSuXNNvAvFvY6mibihm/14etgZ+sQ8OrTYTWTEMYb0n4WPt+WKNpUhsskRxj6RxpmL4fx97WSKyyoWVth9pKswcAJPYtLt6LrrljRsKkvOhbp8szueoFp5eJpuM1VGcdsYno0b/VSWCj0b4eHhxMfHs2TJEpKTk8nIyCAkJISOHTvSsWNHZs6ceTvzd7N+/Xo+++wzdu7ced3j48aNIzo6mt69e1fpPNVBTEzM3Z7Cb47k5GRWrVpFly5d0DSNlStXAjBz5swqXzvVSTlG6Xcj7dQIzDP8E8bHqgsAJt86dOy2Gut/cln8n6fYdrITXiaRvmh8qIzE1QsF9SgqCiA+fh+20Ma0eVB4U9Clu9tpnOs4wqZex9KlvXn9VCOio2HlSvjrX9W193skJUVYkqmpuwHo0kXEc+zcKSTuw8JExpKPjwgo1jSxLXeJbZl8Yh/wyBxAxAeVOXDHZngZMRpGZVV5XqN2SpkmjAqXbici8keG/WEu//vFc7y97mVeeeINPEwOXNJ7YIRa6njgodvR0TF7WfGUyzO1ryrUZpHnWHeoOyfPNcblstM5chvtHhAazU7p2TA0QzyMOBJdRwNygR/zA5j86Z8AaFovmy++Hij6uFyEB53hoVYb0DQ4cKo9ZeVmoqN2XjFXzR3rIjPF5N+hzNAIkR6NV+fPR3F9KorZuDbU/fpUKmZjxIgR/Otf/yI5OZl58+YxbNiwSg4PW7dupU+fPgA0atSIgwcPuo/t2LGDpKQkli5dSlRU1DV9p0yZwoEDB9i4caP7ormb3O6y0f1OcnIy/fv35+OPP8bb27viDpKbXTv3Arruolu37zh06Axnz9bDaRdf3MaKuWFs+PqW0aPHDurUqdw13Lp1Nrq+FnicGTOgTh117SnuDC2aHOaZ+GXM3/QMp/Pq0yjklPtYvWCRJrp0/TAG9fqs0mN+mdmfMpsPOk6+y+7KpN7vExV+rFJ9C4pruV+fLwjhfL4oK+By6Ww79BBn8+vSMOQUC7cMw4VOniWQhOh1lZ6bomI0bu7BqKyxoblcFa8Il5WVER4eztatW4mLi+OHH34gIiKCcePGMW/evOv2qejmsGfPHnr37s2nn35Kv379rjmekpLCsmXL2Lx5M3Xq1Knk21HcaxQXFxMdHc3DDz/M2rVr+f777wkODq7StQNiOc/T0/O2s1GuJkPGbOx018MxTAZDPjz4qv1FHDsmMgACA8VHUdfF09Ilw1i0LS8XT2xnzog18PbtE+Rxw4siIuBTUlRM0v1OaqpxcxfX1I4d6wEIDZUxGr5C2dJXywWglvNKPXNDj0M34iCMrBVdx2Y3sX5nXy4UBF0b0+C6dGUXFwVwLLcJf3vmHR4MzXFrT5SZTKzZ25MF/xlI55Y70bFx6FQbwvxEleIZ8nvcQ9YzOS3HG//pG7RusoeHOqxm7urJFBUHM2XgdGLDxXt5QM45WM7VR9NwOp3kAvny/TlkbEWZ3BY4XSzePoC1e0Taa8sGB/HzLiErO5b+scvo2l783QyvifGZ9JAejV9l1snrN/gOUlyiTqdOJGZl3fD4kU6dyLrJcYNKeTbMZjNPP/00SUlJxMbGEhERAcCsWbPcGSS3woEDB0hMTOSDDz64rqHx1ltvsWDBArZs2aIMjd84kyZNomPHjqSlpfH8888zbtw4Fi9efNvXDgjj1/jysVqtlJWVYTZXR7y0QnFvERcXJ1+JaqpHj4pUWN1bhF8axoSHvKkaAZLaZQJbADa7iTmrR3DgeGseCD7nThQxTBWXy8XlJnLT8JM0CCnEy8vLvQRhB/p32sKxvIbsOxZDTLNMsS5jFD0zDB3j3Je9D03TqRNYxugBM3n7s79y6Oe2dG2w6Yr2bgEzpxO73S4CS696f0bKr5fLxZD4NXh52/glvy7DEz7HpDvgK42VuwZSDsTHfIXDSN+V3xd2aWREqkDQSqNxqXBCVah06uuIESNIS0tjdjUoqv3jH//g/PnzjB49mtGjRwNXPs1OmzYNLy8vIiMj3X2mTZvGtGnTqnxuxZ0jPT2djIwMvv/+ewCmT59OTEwM8+fPZ8iQIbc9ro9RCRJo0UKkBlbCQXdTEmU2VGIF7VJTjSehInTdeHYTK8QNXUI3I0J+bRfIOR0sEY7GR9s3BeCFlKZVmqvi90tKiniQS009LPeYr9qKvAALRpVXcW0Ziw1GrILxxW6oTC/4ajAHjrfmuUdX8Fj77QTJm7e3vEZLHA5K5GtPQzdGehWMsYwMjlo+xdgcnhzJaY3GJY/I1VsnYHfoOKRsuCfg5ylGuXxB0chaKb1snwNoxKWbnGEUnZPbn+UgSV2+EselMTGy51wAMnYNxGwuIbKlqENjjBMqtyOUEm+lueM6GxEREfj4+DBw4MAqn3TOnDnMmTPnhsereuNQ3BsMGDCAAQMGuH/39/fnxx9/rPK46vpQ/N5JSRFGdGrqDrmnLgBRUUJw5YcfxE1UryXEwO0e4ok90CQFtK4K1jx4ogXdWmXSP3obOMFffoaMm0iAy+WWODeUqYOlp8IuDRPDgxHb6Ag5Z5rgcLho8cBRTuSK/UaYs6EtWuzQ+SRjBBarL00bHsfD6ce/1zyPrjloU/8nt0fDEBgrvkxq3W63Ewz4eQtzycNbCn7ZRFuLbGvIj5dKA+m8w4a3l5BDL7R6cKZEmF/1CkVQ6sT09Gv+1oqbc8d0NkC4taZPn87gwYMJCAiouINC8TslJWXoNfsy3LowIQDslBkrBu99UJG/RKGoeXyqqcR620ZHadvoKLYSEUfy9opr29gdOmnrhvNddgz941fQvvkePv5iLMfPNOLFx+fRssEJLvlAqo81ux5n2w89iGu3mg6tvuasrRqKetzn3DHPRklJCWFhYTRq1IiMjIxqOKVCoVAoKkNKiojZMGT1xeICtGoVDcDhwyJI2cNDLC0We0jvAEKPwqkJj4cLuRRhBJQaAZfSe+EBhMt9/oHCw+EZJlNSLWKri5hUtwR4gQwcNTyNuXJ/rtXJ/A0j2J/dnl49ltOp/RZKAZOHHZdLo8jmjUXT8DAKu8n+RUZchc2Gw+GgmEsBryZNtCkwxMjktkT2MZaADp+OJCL0BI1breZ0mSfPNxcxfwkpRuFFxa1yxzwbfn5+FBcXV8OpFIrfJ4lXrf8qP4biXqTY4l9xoypid5qYv3Ek+7M70LvHMuJiNmF4MIb3nUda+ihmrxsEQN/oPdV6bodTx2L1pZZvYY2Ii92vVJeCqKr6qlAoFPc4hqx+auoiuUeEhLZoIUrUf/+9SD2sU0dovZjNIlYh3ySe+NtE7ifzQBwLQ3Lo03EjnjI+wyjC5q/rbhlxZy3D6yG2Zqk37umQQmFlIqTTKrfl8s6+u9zFms2jOXqyA926baVZdDEXXJ3QnSKTxqwX0KdfGvbVY5i9bhAWXaNLm93UNdJbL8sccTid2AC79FyUSg+HEQ9iNeK25PHzFhvLvxnBL3n1aNp0Ld2ahwOQoAJBq8wdjdlQKBQKxW+XAY8sxWrzYvG3ImB7WOfN1Tq+C401m8dy9GRnunX7lujofVzKkbmEp4eNIf1nMz99NJ+v/SMa8HirzGva3Yh1mfF8/V0PnK4rXRc2u4mSslp0il5Ay2YbgMoVsFNUzG+66qtCoVAobp2UlGcASE3dJPfsB6Bt204A7Ny5BYDQUBHI7+cnnkl/Mbl46NFVOJ0uFn87AKcLenf8hiDDq6Dr+Mqsk/B8kShq/1V4GvIKhfcgR3oRzkitijPSE2LTdC4U1sdyoTMdOmQQE1MLaI+mCee7yyXSea2ub8S5PDX6DljIqvTBzF/7RzSHndhWWWgOI58FXEZMhhEP4nCwedejbNj+BA0aZBNUSxSsc8k+5VYr4XV+4C/984EW9FQejWqjIgXRyqKMDYVCobjDWK1WJk2axIoVK7DZbHTv3p1Zs2ZRv379ijvfJrru5Kle/wvA0m3CwzG427YqjelwSkPDGkCHDhm0bLkd6FVhP09PO0//YTZLvxjFvK+GsGTjJUkFs2cZQx7+jI4ND7v3bc4Uhkbz5nvp1WsxZofQF3GUleFwmNi682EKS8IptZbi611+zfkUt48HyrOhUCgUv0nee+89tm/fzv79+6lduzbJyclMnDiR5cuXV6p/SkqCfCW2qami1kiXLmFyv9Cz2bfvBACBgcKIsZtNdO+5BhfC4LDpOj07bqK2h4bTUP60ingPpxTj+lkXmS0/ylTXX10unC6N2pEtmb/8KSzW/yYoKJ/IyGzs9lAcjiAATCYj7VRms7iVQsV4vrqVZ/unkbk7HkuZHy7pZTmW05KPM8bz9OMfE1T/OHv29GTHjieIjNxP9+7LsVhM/FIoPB7RUY2Zt3gQh44KyfS3t8LatZX6E/6u2LRpEy+99BI2m42QkBA2b752mczlcvHaa6+xZMkSTCYT48eP58UXX6xwbOXZUCgUirvEokWL3OrHADabja5du7Jp06ZK9T9x4gS9e/cmLEwYB4MHD2by5Mk1MdVr0HUXf3js37iA9K39SN/aD0+TjfGPpNMnetdN+zpdGquzRpH142PufRERIYSHO2/S68Z4ethI6CzqmDhlgGhXix/zVr7IwpUvuNtFRu6nZ88VOBxXCvp9szWeQ0ebM7zn1wT6l/D+yv786U/w0Ue3NZ3fJPn5+UyYMIGMjAwiIiI4d+7cddvNnTuXnJwcDh8+jK7rN2x3NdWVjVKpQmwKhUKhuD6FhYV06dKFl156iby8PP72t7/dsG1+vsinyMrKYtKkSSxZsoTAwEDGjBlDaGholav7XlIcNWpKnZdb4ZXYu3cfAAEBJTidGidPtsVi8eP82cac/DmKpx5eTI8Woo0mbw35FiEG9nN+Af/ZP5RDJ3oSG70X36BiwsLO0bKlyBTZtUvcvIKDRRzJn//8PABpaUcAMJmkUAcXAPB2FoqZSQ+KEbLhcvlQWurN4cNdsVq98PEpoV69zWiaizZtmssxLgKQkxPOv/89iGbNPAkIgN274Ysv4PHHq/BH/I0xc+ZMcnNzef3112/aLjY2lgULFtCsWbNbGr99p05svEmhtUersxCbQqFQKK7F6XSSlJREQkICY8eOBWDq1KkV9ouKiiIiIoL69etjMplo27YtH374YU1P9wp03UXr1sI4qa3ZSF87muUbB7F846Cb9kuM30zfhzfxq2bUKGp+0/a3g9lsISZmB1aruEUVF1//mbhhwzMMGbKMxYsHU14OS5bcX4YGwNGjR7HZbCQkJFBUVMSkSZMYPnz4Ne2ys7NZtGgRK1asoG7durz//vtX1B+7EWEhITzaqdMNj4eEhFRqnsrYUCgUitvk1VdfpaioiPffvzWFyvHjx1NWVsbFixfx8/Pj73//O3369GHnzp1Vmo+hOGqQmmqknwrPRkzMg/L3I3Ir4ij27t1C285zCQjtgMMhVuidTlmHRHo2GjeuQ+3aBbRrcZBiDaDhFeeKjfWXc/gAgKVLlwLwzDP1AJg3Tzz9apqI5bA4hSaIwyE8HFarSW49KC21AMV07Gi8n25yu0ee4+Urzj15MpSWQpcrKwXcF9jtdnbv3s3XX3+NxWKha9euxMXFERUVdUU7q9WK2WwmKyuL5cuXM2rUKLZu3Vrh+NWlHK6MDYVCobgNFi5cyOeff05mZiaenqJg2Jtvvsmbb755wz6GGvO+fft44403CA4OBmDixIn85S9/4cKFC5V+UqxuTCY7Dz64C5NJlpS3i9tDQUEeAHFxwlC5F8U527a92zO4s8yYMYNPPvkEgEGDBpGYmIifnx9+fn7Ex8ezb9++a4yNBg0auAupPvnkk4wcOfKOzlnFbCgUCsUtsmfPHnr16sX69euJiYm55f4jR46ksLCQ2bNn4+vryzvvvMOMGTM4ffp0Dcz2Eqmp2VftscltLlAkXxvhgEbch1EEPkduf71qDOEJuV6RwuvRt+8bADzVRQSEnkZogjSm8IrRC3kCI6vG0BdRXMuhQ4d44YUXWLduHeXl5cTGxrJw4ULatGlzRbupU6cSFRXFqFGj2LRpE1OmTCEzs/KCalVFr7iJQqFQKC4nPT2dvLw8evTogb+/P/7+/vTp06fS/d99913MZjORkZHUrVuXNWvWsGLFdcqnKhQV0LJlSxITE2nXrh2xsbGMGTPGbWj07duX3FwRmDt16lSWLVtG27ZteeWVV0hLS7vZsNWO8mwoFArFfUpqqrEe35BLHgxD6MtbboXuhh+n5FZQIrcvV1GtMzVVPF2npHSu0jiKexvl2VAoFAqFQlGjKM+GQqFQKBSKGkV5NhQKhUKhUNQoythQKBQKhUJRoyhjQ6FQKBQKRY2ijA2FQqFQKBQ1ijI2FAqFQqFQ1CjK2FAoFAqFQlGjKGNDoVAoFApFjaKMDYVCoVAoFDWKMjYUCoVCoebxCKMAAAAJSURBVFDUKP8fGvvVE1XXD+kAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" + "ename": "NameError", + "evalue": "name 'mask_imgs' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmask_mean\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmean_img\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmask_imgs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;31mNameError\u001b[0m: name 'mask_imgs' is not defined" + ] } ], "source": [ - "fig = nilearn.plotting.plot_stat_map('/home/oad4/scratch60/kpe_work/2nd_level/_cope_2/randomize/randomise_tstat1.nii.gz', alpha=0.5 )#, cut_coords=(0, 45, -7))\n", - "fig.add_contours('/home/oad4/scratch60/kpe_work/2nd_level/_cope_2/randomize/randomise_tfce_corrp_tstat1.nii.gz', levels=[0.95], colors='b')\n", - ",colorbar=True, threshold=3, display_mode='lyrz', black_bg=True)#, vmax=10); " + "mask_mean = mean_img(mask_imgs)" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "func_files = glob.glob('/media/Data/work/modelfit/_subject_id_*/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz')\n", + "len(func_files)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for img in func_files:\n", + " print(img)\n", + " plotting.plot_stat_map(img, threshold=2.3, display_mode='x')" + ] + }, + { + "cell_type": "code", + "execution_count": 140, + "metadata": {}, + "outputs": [], + "source": [ + "# visualize results\n", + "t_plot = nib.load('/media/Data/work/fslRandomise/randomize/randomise_tstat1.nii.gz')\n", + "p = nib.load('/media/Data/work/fslRandomise/randomize/randomise_tfce_corrp_tstat1.nii.gz')\n", + "# suggested threshold should be a=0.005 / .001\n", + "\n", + "thr = 0.95\n", + "t_plot_data = t_plot.get_data()\n", + "p_data = p.get_data()\n", + "\n", + "# threshold raw t map by p values\n", + "p_mask = p_data < thr\n", + "t_plot_data[p_mask] = 0" + ] + }, + { + "cell_type": "code", + "execution_count": 141, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 8, + "execution_count": 141, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" + "
" ] }, "metadata": {}, @@ -94,54 +125,105 @@ } ], "source": [ - "cope1_z = '/home/oad4/scratch60/kpe_work/2nd_level/_cope_1/flameo_ols/stats/zstat1.nii.gz'\n", - "\n", - "nilearn.plotting.plot_stat_map(cope1_z, display_mode='ortho',\n", - " threshold=1.5, title = \"Z regular\")\n" + "plotting.plot_stat_map(p, threshold = 0.95)" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 142, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "21" + "" ] }, - "execution_count": 2, + "execution_count": 142, "metadata": {}, "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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0mBlLOd+tp22e17rf8Tom93DicerhIbM0WE628Hg8Ds3ktc/XZDKxJEnCNvC+l9y6teLvz2eaPlTgMee7bIrNe5bs82CO/02M9Dy0OoCP2NGcjaX0P3KtVqvZZDKxZrNprVYr0/fKktmxezC7mWjhj70Pefgc+W5XKDGzB5EW2zj3vifHXc6RRVkLbN3xMSLSVKlUzMxSUc/5fG69Xi8VUUAB8Jr3qixqtVrorK9GOQt5WzDsoWjTczG7n+f7EPTUfKfkEfvYa97raxzuQqFgs9nMqtWqJUlivV7PzCzFTxgS/g/BjEOm0YBCoWD1et3G43EADjjXQxoQmyjnu4cDYrMiWKqwtS8DfFipVGw4HIYa+yRJAq+YrTKPvPLXkhEF4gE5tc/XeDyORlKzDKT75s/74Lun4Dmz3ec7s82OGICPd4TgFYj3lIH4CCe8QT8SAKVSqWTdbjdEWKfT6Y1zx4z3h5aD2/LMuufzJfGd2kW3cSqywCQN6lWr1XAsJbqj0SjYZNhuCjIRHByPx5YkSdDF7XbbzMyGw2Eqcw6+83x1Fz77HP7M+e7z/Ir7IM5TKpWCLON5ViqVABz1+/2QwcluhOjTQqFgo9EoBLgJ4JBlQqNlvzvwbeg+ZWDOd3fju1gwRvWfypSsjPR15y2VStZsNm25XFq9XrdCoWDn5+dBZtVqtXAsduDh4aE1Gg27uLgI41ksFnZ1dZW6/rr1gs5WmQqQdZv72ET7zHf7SDuRqfQUtE20CMfKGxMqpLdBgdd9r6VMmp7/GNGpnO6f9Jl5wRhD2n3UU1NPSUUtl8shgo+Tvm0EMxYp4zwoEAQ7fZruGpXLafdIn3mMHzkGB0mjRMqLPoLpKeaU6+5vfFar1axcLgegE7nnyzmzDImnAjxzuj2tC454EFxT6uFH3fnI/y52HYgADQCT2bXBCMCujlzWeXM+2y36nEBbDIBBB+qulByjzgVOPK+986aAOp+RKddoNALPcR3vuKy7n3X6N7cPH4fuOscxORU7Bp0L/1QqFavX62ttRLXhtGSzXq9btVoNwDvlV5/LJzmfPS75zBz9PBZQidG2gJJuZLFcLkP5pN9lWn9HttJyuQzVFJRhYi/qNbIIXtYeTvjavv9h1pzktHv0YA0GptPpk/bN8FkhPlMEihmo9HXQviDFYjF0vkdQq5Pvr5m1sFiAGMwsxnK5HJQB9flkozxl9khO21HMcefz2LH8V7S+XC6nBK2ZhbT50Wh0Q5HEmoPqe72Gb+o9HA7DDl+z2SyVgbdcLkNUNXe09os2RYb0NXyh2UkYDIeHh2ZmofRN+9p4nlDeV97WqCqNHZMkCZHVXq8Xet9gyGjvphjtKg8eHBx8UdEs76jHeIPPY+8xQDGQfQNkoqSQAum+LAg9zPkpFTk4OLD5fG6dTscajUYoG4YnydBUIzkGQHjbYZd48Evhu5jtFqMsfaW6Vhseq7xC7lCu63kyC1hXYHQ6nYZtuLXXkpYpVSqVwHfbZpHEZC6f7xI/Pje6DXi3LW9i72mg2sxCOXin00mVv+mxPjBUKpWCfqYdAhnqXAd+Q8ZljWvdd7kd+Hjkn7GvfNGgCZQVPOS7mPyk9UWSXGe1FQoF63Q6NplMgm5UPYtvTKb62dlZOCdB72azGeQnv1XfI8Y7VOzE/pCdug5z/ttt2u2ulfdA2zKgIqWAYThAGAuesWPGxaZxxAwTzksEH4WAoxcDlvKFFafHBjOznnkWwOO/153YtCQIgEl3n4k5VJvG5flUFQRCm2sNBoOUgYyhjeG7rQGbG7qPT7dxthTIxLHXZ10qlWw2m4XyD33+Zhb40Wy9HMIgoFSY8koAVEowFXDSvhLb7q6Z0+NRDEA02+75aFQSmcc5dLctytI0+LLuGjEH24PqlCiZWcpgZkwanfVgetYc5PS4tK1z73Udv1W5R9BQwR7kHyAdzjmOkQYLOadmjujnXncCEmgDbzZA2IaXsjJXcnpY2maulS/8/5gs0R6q/liO1x6am2QRfFapVEK5G6VyqluxL73czgrAx9ZRLvcelmLBGX2vwT2ehd/oSY9XnwI+IZBYLpdv8OtgMEglNkA+2M1Y5vO5NZvNFPCj1Tbef/E96mL3r/etc5Lz3n7Qk4JK9+n8Zwm9mCOvBoaWfKjw1QgqwI4uqMlkEhBWLUliDHotlAW/154PHD+ZTEI5EotysVikjGEUiPaCgO4zkrrrOzN9Lt3n/XnnJUYKIPEeIEe3wSaCTvYQjk6/3w9OkE9FjUVTNfKvAl0N4NlsFtL0m82mFQqFUFc9m81CtEJ3tYGP183B5wj/fea7bcDMh7q/bQElFD5AEgTvlctlq1arNh6PbTgcBucK2aUR93VlmN65175dGBmj0Sj0qUOu8dqn9XuACbovI2Of+W4bum95t8kYjH2GLFEgifNxTkrUcLY1e873jfAyz18XHlT5Ck+RhaIllxzLWNUY1mtsAvNvQznfbUfrbJrYs4fHYvynelGddt8cWTNDeB8r0T04OLDhcJjSr/P5PADp2i9H+xxC8KTagrGApbctvY15G1l4H89llzPk7qMX66Y1riXisfJtfxx+hcqRWM84Ai+UTioA6X0MlVnz+dyGw+ENP4W1kLWbHOdScEplsn6m83MXyvluM8X8V++36sZRGiTGb/VgEJ8pwKm+A9cdDoe2WCys1WrZcDgMvzdbgVPw+3Q6tcPDQxuNRnZ1dRU2d+FY+M1sFYRU/0PHmMVfvNZMJuXNbfnwuevZXaNnk6m0baTULC1o1bnSTCVNJcVQ4Bhv0OrCjznVPtJvZjecc+80eSXEuSkb8CiwX3DbzklOn0fbOPSK4Gv9MHzFs2fXDhrLJkkSFCgKPsZ7kDpOyg8+mqr/cfCXy2WIXMD/XmmpUa7GUM5vu00q61CwPuLFcx+NRoHXMAxihg2vY6CS2fp+YgoYmVmKxzWCq/yMUe1ToWP3mvPhbhCGq250odkbatSOx+PghFNCRNYaRPTebDtZo327dGcuBUg1ArsOqNJ74n9sDDn/3S95+0fnXz+LBQL1TwFKfdacRxtpK8XsvCxwk+N4Dy/rtfV7H/335zVbrZeY3PNjy/nu82lbP0L7n3qe8+fLejYqi+A/3VXVZzkp78MPHI++NrNUwJAxxPwCL+s0GAnPwZ/e8b/NfO07PXblQwxYglcICKosUf5TneptLs+b6NbJZBIASdqwZPGMyjJk6Xw+t8FgEIAlzbbz147xS0zu6VrSjNKsOXpo2mUwc9fo2YBKUMwYhMFh7ljaPemAPmKkCwjyu8bEDB0Wk48OQN5ZM1tlMOm51bDWOny9j1j2SE4PT1kGhH6nCkH7dOlvdIdBgMJarWZmq6i6lmzEro+gVaMki/e8cap8p0YQfEdfJy3L5PxPLey/ZNoG0CwUVluqe4eG1xgR4/HYzNIAd8ywjYFKChaZ3QSV/Pm4PudTGeeB+izgfh2Q9aXQU/UuzAL2vAG8KTrpeYlySC/nPG/F5Ogmw5XslJj+97/jPmIGrx5z26hpTrenLGcWvmAzi03ykCxv3wBeM0SgGPDIOTQwpNtu++vDo0TafRNbbLflcpnKTtd7Zaya4eR5Pee9z6dt1rDqoXK5fCMrRHVr7Ly+DIjPptNp6GvJd8hHBav8OtA14EvSR6OR1Wo1azQaN3ZXTZLVToWMw98/32GP+mvcZt5y+jzS5tU8h6ykBC2tVL7x/ij/fXauyjAF4OEBX12jwI9maHo55ylJVoGeWAYd/Of9DT2GceS0W/RsQCXPuDAmilwFvS4QdtbSdGcAG7Nrp16bFmvTWa6jC1Ydcl3EMeWgxjEG9WQysWazGc7vI/eMhbIkNZK5rs9eyun+KabkNatCs5K8AwUvTKdTm06nAcxUHqU2nt8oz5mlDRifFh07Rh13Xitvaaq1vz+MWW9ck/nC9fPspcejLEWNvFMnxTtLOFcKQqoBqdlzODwxo1Mdai8HFTDyY4XX1NiJyUbG64105S01sLxMzun+KQaa42QBfkPKezHwRg1KdbCVb9YB2H5c6jh5Ocia8Aa58q3KZ/heo62cP9ZkOQacPWd6LDAzBl5qD0LvBPEbjuNzmhUzdo5Bz8YATpVrype8Xyyut3D34KNmVapNSICoUqncAA9w0GJOFJ+T7YczxnexOXuO9JDl4zHgkvcK8NFjVY/1v/FBD+QFPKt6FrvJZwLphgIKzBeLRavX69bv92+ABVChULB2ux36KpXL5VTzZO7F860n7wspwPBceeypSHlIfT/vG1CWFgNh4I/ZbGaNRuOGPlR9S9YuMrRWq6VKhNk11YPdjKVYLKbkGbxUqVSCXxMLMqr/4IF8f1+sGWSi1685D+4mPQtQKWZ0aDTJLG2c0BDbbIXsAjSpwzIajWw0GkWNjpgRqY67fhZT/FyD82oNKjuH8Jmm8Gufk1KpZJVKJSglFACo8boFm9PdKcsIQdiqsatOuzpck8nkRm8FhDHRK1XiWgqUNZ51QE7sM2+0Yqyq4lDiOwWTVNlQ5+1BhZzvHpb0eWlDWLObZRvwnDrxRMFjgA7vY8/Qg5zr5JyO1QOceg3Oo45VrLkjxwGi5VlzD0/++cJzBGc8+KJ8w3PUTScwXLVRvOpDrun/vNPmeS9mwCLfdExaHqL63xvjAAjwJAEd9G6Ml587PWZ2nOoSHHvNtDS72ZBWHfokWWVmaOYFz90sDSSps+3lCDzO66xsYL7X/1yf38/nc6vX66GHISVLWXKM/+VyOfTj8fZmTrenbdZroVAIjrcHLz15f0GfEYAmn5GdzjXoKac8Aw/omsNe9Bly6twnSWKdTie0y2DnLsbHGH1D8FgVhYKggF453Q/F7CZNeOA5ZfmWWfpK+1hqoERlpPIZoDVAu0+00GPVZsSfVlCcNh4qI1W2rpNbqkf1vCrjc9pd2ntQySO8gETe0a5UKqmFgHGBoDVbCX8Qfd5rA1GfduiNjqxoF+QXhKZTs3g0gmG2qr3mGB3DwcFBqIPVbZG94Rsba053I++08GxU6SOUq9WqmaWj8ppNVqlUQvRrOBym0HuNdqqj75+hB2+yImj+Hjzw4M/nM0Q0XVWVhiouxufrsnO+ux+KRbTUycLp8fKH+Vewks98hojZytH2wKKXbx4MWEdcT+VU7HuureNRnvTX1air9qX4EvjuKUrfmFsilB5Y10we5EK1Wk3t6qbPV+WhJ+XLLBBzE5ie5fxrmr6uHe5Jdao2RmV9qfzL2q47p7uTd5bJ9MC5nc1mIeuH45UvsH0IgqjTPhgMUgC7B0CzMoBVrngZ4527rIxxSvDgJXhLy6NiNqMCGtiE6OSc9x6GNCtOM8u8bjKLZ4+YrezDUqlk4/HYDg4OrFarhXJz3WkLviCbFx+F77RUU3Uh1+QzfAIImYVs02w9D5p68rxvZuH8vmQq58PbU8wWIkuJzCOzm3149bfqH3AsrxWU0V2mlV/ICppOpzYajcL5FZDyvgfyTnUnfEU7D97H/mLk5wH5HZujLymIs0+016ASTKUNaFkoOPkwpJYTsVsHNBwObwA4WvKmAl4FMdeKAUsxkEjH7I0PXzqkfypMNKqrjU3NrvtCYdSr8891tCGujuE50WOmSMNj+l6zRebzufV6vSDgKWtURUyEUlPl+a2/tpaoxXhOn2vMEeM3GKZqIGUZSvpae1HATwpiqpOlY6GnxHPkN+ghnfsYWKMlu2arrAscYYxYMsrIckQW6W/VwIwpbniGqJlmEXkDIesZx5x7deLWGeb6G8+Deu8AHWarXhXPne8eg5Qn0DHoOO3zolmMtVotlWF7cXGRyuqJOTQQ56HESrMmvbPvgQTPP+jBGMjor834kLPVajUVbcXAZY0RvGKM6OR195bT7ShJrksr6evHsy6XywFQIsNXQRqe92g0umG/eXmnckSz19ShgwdiIJKC3MqP2J5el2ufxF6vl9LJ3IPaj3zOeRSUZ15ifaGeGz10yaU+OwBzfYZaNeDtJX2GfB8Dn/EtkKMEtfkefV2pVKxUKtloNLLhcGiVSiUFJikfqh6G9ylbqtVqYc5Go1EIKmm1hurYmBxV/uZ4lc1s9JLT7cjrLnQqFSjYMBrQ0N9C+jk8tlgsgpxrNNnbVeYAACAASURBVBrhM/QzFS6j0Shch95eZhaabk8mkxu84oEhQHK+b7fbKZ4CYJpMJiE7We8hK2vJ62sF4DfZjjk9He0tqAQjaTNQfQ8iS/YHjO2dcnY74vNisRgWmjrfapT6Mjn978eIA6bGiY4f0kWqgkbL+DB4teEzjh69nxSNVsFitop0fUmR/PsiHxHQhnhmFqLxZhbS2dlNgeeH8cBz8SU7Zjd7j6jC8Wi9fhbjQ33G6qDr+f1/FdIxHoXvuC+OIWKq4BJ/ZPrlvPb5hEyhBAKwR7MqzVaRSRofa3bIpswQvY7nWx1HjP/0HHosn3lQwH/v38f4EeMe2eebfyvAkW9icDuK6QR1dNXp1gwLnBdtmKwZwB5Q5BxexqC7KUn3Y9D3McfOj5vfxfhUx+AdquVyGWT4wcFBqgxBdTMAroKdeWnI55Pac+qwqHwzu84qV2dfM9U1y3cwGJiZ3ZB9Xt6prInJN332MdmC4xaL6it5eeptP7+dvGbZ81tkqdqumu2U0+1IdZTyEPqzWq3eKPtXu115B31br9fDcfDYZDJJgT9aCcFvseErlUoIgqvsiV1fP+ce9JwaYOaYTXqb/5oBA49DjN+Drs+F7hvMVGDG6z/Aco5RYBuK/Q5SMJrjxuNxOC/yVO2wXq8XMpW0FYwPkmjJsM9QU3/Ul2n2+/0Q4PM8tYlnNNsKeyNmD+a0O/RgoNJDZozwHwCpUFg1CzOzgPD3+30rlUrWbDajdfLL5dKq1WowOkhH5Rhd2F74qoHrx+Y/07RZXSQ+usG5+Y8yYCHpNXWxE8nDmCV9kXnh2oBr2iQwp+1IjUmEr0a0kiQJTfQODg6sXq+HZwtC7w1JSBVMLBrBd77UhGO8klE+jzlcMePEX1OvC6kxpcZsuVy2arVqk8kklI7WarUUgKap+n48OcUp5nATnVdnFpBpuVwGA1SbYWdFdtYRstUbrL4k0oPTXuGrrF0HAsTGlAXYM67xeGxJstqJBweA1xjs2ow3p/WU9UyInGPcIYtwZuG/mLPjo5yx80MKTAHaq/OuWXJKyov6mZbjqiGr18/iCy0L1Qw4AE0Nzmj2FufEkF53jZxW5J+dloC0Wq1UlFo3LPEAj0bD6/V60L2UY2gZNxR7fjjPOFf6nQKtkOdtslJiPKA63ezaZtXWDHwPj5G9oGuuUChYt9sNepmMArVjc77bnljXZJ9j+yOPeA6+t6nZys7HZvcZ6+juJLnO5CA4PJvNrN/vB70FH8I32JtcA15CnnEcdj3H9nq90FZhPB7faGyvpaFJcp3R530Ts7Qcp/9XDFTzvRy/dFoHlHi7WmUPDbaRWQoqq5yL+QH4xPyGa9VqtVCuqP1QDw4OrNvtBiAe+YpMxZ8xW5WBDodDm8/nVqlUAqCPrUgQ3WyVRDGdTq1WqwU/QMvedc14W0+/198owGVmqdYvOe0G7VWmkjoqisJrf5dCYVUvr7X0KGfNqIBhPcquaL8XrrrAfZQAUoBAHSk1FDzAsC56741hlIGWeHiEWBFljVZoqmIOLN2OvEOlc44hq3XQPB94S/mK5xkrB+JaCkJi3PpGkTFHSqNijEWdQK5zW0NAI7kq6Im86U5wpGxjFHm+W6d0v0SKzYcaH5p9qE4sDq+WPygQrYCOnncd+fILHwFXOcyfNmDW45Q3dfzr5Kafl9iYdf2MRqOU04VRz5iV53OeW08x4EezwviMiKZmZfgsWA2mZPWX8ddFr2tJh9efUBYPrQMvs15ngZoACtyrNrtFHnu9rnye02bytpLZKnhTLBZTpZSx4KBmY/vNJtTB11Ij/b1ZOpOEzzzP6vP2cpBzQN5u3MZOZLxZ4Kv21mGcOPoA7Bz/JfPfXWwLeEvlz8HBgTWbTVssFsG+U91oltYtPguXZ6SgO0ApgY5utxtseEqdIMZglp2FuVgsrF6vW7FYtKurq2BnESRXvVyr1cLvGbeOUXlV/Rt8CM3G5xyLxcIuLi7C98+9BPNzKIsvNUgNsMPnmqGoGUacT4FwzZhFP2kQRvsCL5er3cYPDg6CDJ3NZlar1VJyUjPTVNZptpr2MYZnfMmy+qExG9LPFfc0m81uBHGYM77Dxsh57+lpL0AlvxjVsadDPkyIEw/QpOeghhQjZT6fB4Red1HzAlUZP0tRe2NXAQEzSwkHjlHKcih1EasRpU4fAoFoqgJsvi+FGkdmObC0DTHvGgXQrWXpi4RgxcH3vbJ8XxCN+Ky7Ns/OLO40xQihD98rSIXyj2U+xc7DMWpcKF9qJFevSdot11WjPI9orWido222knfqdMAXZCgSnVYDhN/fpvRQlbkCBbxWmRq7h20Neo26bePoex7UdaElCrVaLdUfz8u6PGNpPanDbbbahUadKHVINCKvZa/67DTzYt3c49iprvXH++88v6w7fh1gqfftwQbkOVmp3CeOpnfidRfMvOx3PcXWOCAmc41z4h0adYJ11yzVN/yW976xtecjL2P1OAVN/W8VQFVnLgtQ8kAU8kyBSe4HgA25p/oTGxidqzJ6U/DmtjJ7X+g296L8p02Ma7VaAGs0SAMwqfaO8pzyBoE2bCB6acEf0+nUBoNBVJ6pM+35jGemYKp32LVvLPdAHyeVz9ioOm54V3t3KSigx7K+6BNFRsptn8Nzp5ic4zVlaWYW+q56QJAsIA3c8nu19bxs4DsFBOGrfr9/wx9Vf1ftdbOV/8K5kZUE12ezmfV6vcD38CvAvsrJdXOkGXNclyxMAofoiH6/H3wZvfec956O9gJUUsWnvWw0VZWGjGYWGpOZrWroSVldLq9L3bQfCUCNLqaYcaoKIQsE4lhv7GhfEkWW9d5i5/RGM8fqziV8xoLTz4iyAJzRfE3LRLhWTjeJZwqvYUhQ3kX6KEbgcDgMABPPHmMUvlXjdh1lNb/2SkkNC86vBgBZBWp0eMHtKYsf1HDGkOX8Gs1vNBohU8ss3QCfXSbWXedLoiwgxWy1Cwi8glFByetwOLR+v59yaM3SWWgAT7FsI08YIto8NFbSpPyjspFr6vEKZmKMw4uxe9bxeZCD16zH8XhslUolBAUuLy9T4G+1WrXhcBjWbV4acpPUudTPaOjJui0Wi1av1206ndpwOLTDw8O18gMwxvcTzDreG8ZaAqA7JKmc89mbei49XwxUWve5kjZMhY/NLDiY3KOCFaxbACYAqC+V57KAi9gzqNfrQY5pSYbZzb6QtVrNqtWqnZ2dBV7hOORCr9ez4XCYctT82MxWDWfVdvKyS8EDtRW1iTJyTUGg2H1zPvgbx1L7SGnWlQegVJ/XajX79OlT4FHOEevv5e3NL4Un1+kUMwvgT7lctnq9HgATng8yplKphD4xnEfLxdEz2GEErnk2k8nEer1eavMg1oHPLuEaepyWSeJMa79Eta0AKAAvCHwynslkYoPBIMUzxeJ1X1nGUq1Ww1z4eZvP59Zut0PvRu5RM+e+FP6C/Jr34DT/sZUp4SqXy2HeeRaa6TuZTKxaraZsJ7NVYgA8gc1XrVatUqlYo9EIz0bLca+urlL9ovAVkLfY9SordDdx9F+z2bR+v2/z+TxkP7148cImk0k4J+ui2WyGc6I3NSsZOa983mq1UiXx3Cd9XcmUK5fL1uv1Nj6DnB6W9gJUghRQUiUMA1J6pEJP+wzp1owIUY0Gaa8hFfSczyPEm7ItvEHCZxDXwOHZVBe6ySgfjUapUkAUCaAaTj9ziBGlANWm63xJpMi5lo8hbEHI4QMylogyKRCk5Thm8e1BldQg9emvfnz6nuceUyIxx1F/B60DHWJAp5mlnDtSajFcNBvQzIKDmmfJ3SSVLwoqEq2hZ9VwOAy7udC/C2NgNpuF2vzBYBCA9Sxj2pNmKcUcbAUlAZNUlmm0XX+nEVHGkQXOex5UWaxrAwMWA61arQbgSAFh9ADz8yVnym0ysJhnfX44F/CfRrGV1KFGXm3iN72ugtU+gBPjC7P0mvGZxZppF5OX/D5m+Pv54FiV3Zxbt06mzMRHdv11viTyc5s1B8g91Zsqa/ge/YoNQ29MnA0tYzKzG86RjiMGaGqEn//6WwUACBLxvJV3N/G+gku+dw7j8GPQ9Ynjhg2HHazryD8DrvHc+TBLv8RIM4FjGeWcz8yCniEbHTo8PAyfoaObzeaNjUum02k4TrPQvQzSQHRMHyvA7QM6rAfVuQDbPttY7UzP2wSvvC7mulraBy8yri9Zx0JZOkuBSL4D0JnNZlav11O2FME9/AutGFAZp0A7gJKCmtPp1CqVin348CH03oU/Gc9wOLRGo5Hifa9DNbiJbQX/aEDdLF0KDNgPIcOQVz4gqY3L+Rw/vVwuh77JfM61de5zelzaWVDJC1iUKE49jMYiVEY1Sy8CmIxFqosZ5tWdNWIoJ+eMnV8VvY/+xJx4P06tD91EMSWJQtTIrl4ToEmjaSgW7+Bv6wB8KaTgI/NI9McsDbJgWKqxx3wnSZJyPLYhdYrUUeK6elyML/itPlv+MGhiv485WzG+0O/1L0mS0FMJh14bQ3oA60sV/FnzbrYqM4J3MOzgJ3YzarfbwXAA0GPNo6w1TX6bMW2SAZ4nPA94vlLZ6kuS18nL2HuNai2Xy8Bj/L5erwfDnUymVqtlZhYMMuXBL5H3Njla6Ad07ny+2sUIviMqSSm5B+pismVbI887/+vOpXJNyZcEQLExeD7OIq/zWVuTySQ1D8wXveYonfOZCVn0XI3hrOehr9WBXS6vN1Lx2TbwhJYYUvY6GAxSWRVqAyo4ENNp6sTpZ2YrgFC/U322WCxSjrzq7U3ENQFscaYYtzpVjF9tUvgQR05L8bOClV8CwLlu3et8EvDSTFr9ziwdUC4Wi9ZoNEITbDZiifkUlJ2hm9nMxMtLD9po/5yYzGMcMaABPQufaK9F1XvqU6nuJiNVs6uU+B3/Ly4uUqXAZhYAjOfMXzFSXeI/U9ISMeQITfcPDg6s3W6nKmMA+D58+BCei+oS+KRSqViz2Uz5x5A2f+90Ojeeje7SrLII4nr4QdoknutrplGz2QxtMMzSIG2hUEhlUGkvPFrY1Ov1kJnFOfU6g8HArq6uQsAL/QGvK31pfPiUtLOgkip9FgsLAgbCeVAHDAGIsEfgqhClW3yM0bIULWOJCVgdsx+79vFQ4a3HjcfjkO64LoPFGwJcQ7cjXS6X1u/3A1jVbDbD71n8qhS0BOW+lYBmCOwbMbfwHWmqZhbSNtlZDyPu8PAwVZJBZsl0Og2C8rbXh/gt/Mf5NCsNQujqbgsIcu334fsCeCM4y/j2axPexqHHuRqPx9bv963dbtt8Prd+vx9KElgTNK3kXF8SZRm9mtXFvE4mExuNRtZoNKzX69nJyUnYCU4bLSZJYtVq9UajxduQjxb5cWY5SshnZJ5GK7VsxctQfuvfe2OaY+Br5olSVOr7W62WLRYL63Q61mq1rNfrWa1Ws3a7bb1ez5IkCRl0z92xyiLv4PO+VqsFeQBYmSRJaAJLWnu327WrqytbLBZWq9XCs0en4DSNRqMQEd00zzGwS/Wm8pOCSTHdrDzjs5D99dbxGkQfCo2+6pqrVCrBeez1enZ5eWmtVivsfjMYDML3m/juOfFjTFbE7p1SS3VSisWi/frXvw7ft9vtsJMR/W80uKOBRcC88XhsnU7nRgY6v4E0I0r71qhjZ2ZB1+s5yFjW0pFY1nuMlNcICCDbaJirUXzld0qXWBPHx8dBvjFmyoQBnfSaz4nPsihLzkFkQmif1svLyzDvf/RHf2Rmqyyf2Wxmk8kklMhppiJADiBOs9kMfYyGw6FdXFykbEHN5tTsYJ4/wJRmm+t/3QQGvoFnyUhR+wowCxuBbBaAWTJPtPRSHXTle6jf79t4PLZms2mXl5dWq9XCzmDaagPaR5677U7mMf2hpD4sz4pev+Vy2S4vL+3FixfBruHZVKtV++lPf2qLxcIuLy9TPq0+U3pskmhA5hPnOj8/D7xCCZuZWbfbtSRJ7PXr1wF00v688AJgN8BTr9dLZUoul0u7uLiww8PD8BtkFLYb2X6aDaflx5BWaagPUy6X7Re/+IW1Wi2rVCp2eXkZ5B0BsKurq63k3JciCx+Lblr3O0AxRYAApo7SzIJRpwZBkiQ2GAyCsFMkFwHto1Ex41LH4g2R2Gs/dj2fnt87j3eZl5hjxz2BABM1o/ZbAQRNvdV5W+cwZt3jcyO9NwSc3+VtNBqFpq04DbVaLQi7Wq1mzWYzIP+3AZTWgUkYqmYr1N4/MwUSNJKhBrIq+U0RFU+e95W/ybhj3qjrpucPgC6Gt/LclybUvZGoTrJGmbUpMAbrfD4PDpQC5uVyOax9FL7PDNtEXi6qgeTlsr72hpRG0vzvYmDVtvOl16UEFSPey0eiWZQqTKfTVCbEl8h3UGz+Cc4QLWVekWP1ej1k5JhZCjxCvujmBYPBIGxBvC2hlzTbJJbxEZN5HMt54APALs3g9eeIzU/sWDIOFDil3I3PKpWK1ev1UErDhgUc/yXxXew+VdZB6Ffmib4ujUbDjo+PQx8vHGQtyxiNRjccX86Dk75uPGYWgh3wnepPlbHYWF6mKWiu9t02z9rblLquFMjU6ynYZHbd4LdcLlu73Q6BVsbFGvbXjNFzsu3WyQzeV6vVVJ8hdo5++fKllcvlkAmBXOP1eDy2s7MzM1vJGhopY/8gcwaDgXU6nVCu7nnJbFVSpmVOXE/bdPBbLRHV7BCuCbDgewgSUB8Oh0E+q2OvPgH/sev8muU8rVbLWq2W1Wq10FOUY33W4HOnGKDkfUA/18i5o6Mjq9fr1mg0rN/v30iUQJYtFgs7OjoKf41Gw5rNpjUajaCzydocDAZ2dHQU/JHpdGoXFxepIA3BOQJJvPclbwCXyDrAfcB7nwnHZ/RSarVaNh6PbTgc2nA4TIH1+DO+pFSBV/gcoLRer9vR0ZEdHBzY0dFRSu7htynPZcm2L4EvH5OKZvYPD3JiZ8BtSz5qCHOg9LWOVBcDAhQlABOTVrcpC0edb/+5KgBt5KjfeSNXBTBGUsyBJ3Kg0YosR20TYZBQW0pkVJvoMQ517h+yHOS2WRKfS3flO0gdUkARojcIejJHiNCQIqzGxHA4tE6ncyMjbttn6qNFGqXnc+0p5o1czUgys5RQVqNXs+di44wBCX6uzFZGOI3zSUOFaOxrZqHnEkL/vg1Z7XP1WPQ5fKfziGMDMFkqlazT6aSMjVarlTIEAY8w/ObzuV1cXAQDed11PcVSq/VY/vuSJB810+xJs5VhpcbpJmApBjjGQFddIzquarUagBKANta08sd9ybzH5jmzzXyXtbY8AIecQ3dqT5ler2cvXrywRqNh5+fnZmapnYQwCLUciWym2xC6nmtrlquWgzBm9BxAAtkY3BuyDcOWcWbNg37m9TqGOuCkZlpqA1x+T9NQNi0AlGMsjP8+ZN9j891tIvexefTgM0GZWq0WHNJOp2MHBwf28uVLazabVigUQva58gI7GqldSHbcZDIJEX3GEptv5BbPVG0ozb4zS5e8aamGgvyama46zoP06+YMWaZjUIDLzFLN4SmnoWdJr9cLGzxQyqT3eB+063xnlp2hxLrUwOHZ2ZnVajV78+aNVSoVOzo6st/85jd2dXUV5B3HY1/71hEqE+v1unW7XTs7O7PRaHTDtjdb6Vt4BR7mGEAlD9yzTuhpA7+QNcp51D7zPspsNgtZpPTfSZLroDxBU7WlOC/27fn5uSVJYq1WK/S4KZfL1u12U1nr2lPKy1s957a0q7ad3lMsyJUkiR0eHlqj0TCzax4cDAZ2cnISSvTb7ba1Wi17//699ft9e/HihY1Go1QGGfyAX0ewdj6f29HRkSVJYh8/fgwATavVsuFwaGdnZ/b+/ftQqsn1sNur1WoowQN8BBREzg6Hw3B9bQdilpaNpVIplZ3HMxsOh2FO2KEQm1erK1hfuukKWdFXV1f2ww8/2OnpaarNRrPZtPPz85DxypzFMv38623oKey7faQHy1T6nLInFTKqXLX+12yVgg46jiODsNfspE3X0/+e1OlW9DaGSPvz6Gdeqfi+D7HfrSMPAvCfCD5AEgqCSJ86oKqo1ClbNx/PlfR+mQsEJ8g8vMVODP6Z84zZ/cM/x9vOqQc1vWPkeSbGgzxjz7MaJdg0Tv/b2H1oVFidJzIMyRQhLRflw1geAmDaJ1KZwDyNRqOgXHHa+/2+mVnKgGXeiB5uM5exZ+4BIp/pxGf+PGo4IYP8ufn9NoCSB9bX3Ys6/F7GVqvVsCMITiuALM7BfTlZt02Tf4zrxZ5xTN/xXEgdpycVOgTwEn2KE8FnnItIJM/itk6sgvAqnxRc9Dyv59c1wfXVUdtE65x/+DrG3/4zAl40kYc/yWpC/953EGeXKTanlIGgU8lQKpVKoYyVjQdevXpllUoltesWThW7u2nTWPrMce11c01Zkn/GXi+RTcK5CG5SvqHHAhoCfDJmnY8s0lJhzbTT7CeCWtqkHHCpVquFaD7lWjhwfhy3der3ibLuDZDIbAVIVqtVOzk5CfbeaDSyr776ymazmX3//ffhc86rmePwyWAwCA5xqVSyXq+XasGRNUZfMQB5Wch3AAPa68tn5Xl70V8f2Qz4QEmTzotmiuj5er2eFQqFsFMj/EmWJmA760F1VUyuPgc5GAPNlAikolMJTNOfi3LK2Wxm7969s+l0at99910ISpitAsG0Nmk2m2F+2T2u0+kEv4/ytl6vZ91uN6VL4XESDJB/lOOh99UW1HvVYJ6vFiIIMJ/PbTQaWbfbteFwmCpdxlbVrF+zVWDV63HWU7fbDbv9FgqFIHeRmVoSHesJltPD0s7MtnfKIc+wy+UyoOsYExi11FMi8FkgnyOwYsIhZtB6wzdG/t581MJfd9P5spx8FrxmKWDU+J2RNMVVwQd/n18aqfCGcERpUOuBOQw9AM7PVZRqYKjw9g5TzEn3YJRSjO82Oe2xMXlSx17XJAqBlFdKExib57t9o/sCE9R4m81m1u/3QxPaJElCk2RAJ7NVCRLAupaDeYBlE+lveCb+uagB7H/nQa4sXtlWrmwLyHJNLRvBIcTQwGFVZ1F5b5vr7AvFAGEoxg8K/mJQmllwQHW9YgBqlisBjNlsZt1u1waDQWpL6duMmQbgWiLLeNWRj4Hn/jOfvh+ThevmLYs0AxR5r2uAOSLyT6NuLVlS2bfOEdmGHhvMvCv5+9MsEfiHKD69MtC/NDymnHowGARnHdCQOWW9833s2koqs5bLFbCv/ANv+WwfPR6d7IM1WdfeNCYFlTQDajqdhr6ZgBdkCeCUAg43Go1QyropgLPvcs9sO7uZYCGZDABw2rLA7Bp4Ojo6sjdv3piZWa/XizqpPAPmfzgcWr1eT/VDygJOVJaQbcJ9mN1sAeJBb5+9juzcFrzEV+LaPmNKz89rAK16vW7T6TRkpNJwudls2tXVVSiV1v5B3l/SZ7bPtInvCEjrWgXsRbY1m83Qm6vZbNrr16/t6uoqVEcgD2JAI4Hbq6urkOXJsb1ez66urmw0Gt2otEEnqc4FSFI5oTzl+89l9StUGwy7AnmPDavAFJlRVCSpHclavbi4CMBlr9cLIC62HSC6+rdcb9tnldPn0YOVv90lRZrX/CcCBJNhLBDFByABkTWz8BtS6QaDQaZjo9fLIjX8dDHDxN5x1wWo6fr+e02BhxQw8PMTG/O6e+CaunOIGidqgGjtKcbMNiDZNrSrqaqedA5LpZI1Go3QKBOnAaScCKACnuoUERG4y9zps1K+gcc0ws2Y9Nnp7iW6Raw3dFFQagwrKW9tw298jiGCEuD8jIX0WY5F6MfG8Dn0mHx3HyWXRPkajYY1Go3wHJvNpi0Wq8aMJycnqaa2y+UyNBZlfv3OMlxjW9I0ZpVRGAR6TniOe0iSJACq3ojkP69jvXZigNSmsasTSPSKdYnRgh5gFy7WsB/b58q8XeM7NSBjc0pUvd1uh4yHZrNp7Xbbzs7OQnmSyh8tOUOfoG8BpHzJxLrx+bEy3lqtltLr6kSpgcs1tN+cyiz42WeZ+GN1HPp7P2+sPwxydAR/atBXKhXrdrt2cnKSciC0rOQ+eGaX+C5mwHsCIGq1WiET8+XLl0F2nJychLnEUacvzfHxcXivDg3NiennldUg2K8FPsNe8veqDr2ZhdIPdYR4rbaiAhB3CW4irxRMHY1G1uv1wpqjx9TBwYGdn5+n5Fqj0bBPnz6FtW22AohZC9uCDzF67DLzu5QhKSHL6D8zHo/t5OTExuOxXV5e2tdff23L5aofF32TyDDEYacVhzqzyAN8j/l8Hvh1nT2tehMgVLNCvA2H3NVnCK8pCIT8WRfc1HmiNyi2me9JVygUrNvtWr/ft+FwaKenp6kSfYBeNnoYjUZ2fn5ux8fHAbDjXm4DesVo1/jO61hP7XY78BzASqVSsaurq1DxcH5+bt99913YAIO+Q+Vy2b799lvr9XrBJzFbNV2H9+CH8/Nzm81m1uv1gl7q9Xqp7PXlcpnqE4sNbmY3WsUAFCLjsKPgOTMLFQhkH2ELeB9CM5K4JnqAAD7yl+OKxaL1ej379OmTnZ+fh55P2HlmZufn52GtNZvNUGLH+AA1WYce0NyW8vK37WgnMpWyQBSN0qjS14izMiTHYVz6PkbbXNuTGiA+ouXHq6+3Aa2yyphiY4ydL+bwK6kBrb/DEEMpaQpvVvT0Notvn0kFXqFQCA6opqviZOmcaEnhbUs+lDx/qbLCgVHDIUs5x6L0myJWHJMVXfVK0wMGCHnNXDCzMJeMl55KOKQenLur0H8q2rbUV+/Jv9aoPbIOR4AUei2dYd2SFTefz1OpxHclnW9Nf1c5qHwXkz8xea6OUeyY2PVj7z0fsy4UJB0MBtbr9Ww0GoUgQ71eD6n92oxX5/s5p0nHwD34Dnk3Ho+DswQwye6h02pWLQAAIABJREFU8BvzDYCijrsGJ7Z1Grys0ddqBOp5tj03zktW5J1zbSsXIdYdwFe73Q69MjCCydQCGKYfH+VbjMkHJZ4DZekPSB0adkjF6aSvDYGJQuF6++t+vx/4dDAYBNsGUIXgo1nayWM80KZ5jvXf8tnbqpOxobQkzywt5zZlLWfpZv9bbeVQq9Xs5OTETk9P7cWLF3Z0dGQvXrxIOW7MUbfbtUKhkOot4rOwnwt524nPzFZApgYWKpWKDQaDMF/ojm+//da63a4dHR3Z6elpyPiazWb28ePHG7td8R6ZQE+v2HP1upTsEO2vityC1zQoyH+18bz+QtZt4jtP8K2WtGEH0xC/3W5bo9Gw5XIZQCbu+ezszAaDQcjSZN2yw7WWgm7jI+0LZekR7c1qdi1ffA++Dx8+hF5GBBZfv35tv/d7v2fHx8dWr9dtNBrZb3/72wDw6C6YZun+gcgTbHD6eekYCYzgNwPKq2zjfATrzFZ8R4IHPEG2G9972cuYGN9isbB6vZ6aCx9AXyyud/C9uroKsosgg8phMsCm06ldXV2F76rVatilW+fqcwDNnDbTTmgVbwSYWQq5xMhdLlepxggrVez8hsi92cog8I7ftoJM05k9Yu2ZUxetOsgaZVWgTBeGvo9dY5OhFnNYF4tF2CaSRYVxwZafZOP46D7gnL+vTUb4vlBsXjFaUX48DxojX1xcWL1eDwYxTZSpHVZAiojTXXqLaSSKP4ADBWY8zyjveUCRtYNA5lmrkog59N44jzmAjAkFihGBwkEJkhVH5A+gDv5Uo/e+mtjuEmXNJfxGxKnf71u73Q5O03K5tKOjo6AUF4uFnZ2dBd549epVUOqfPn268/j0eeP4UpOvGSK+/MPLHo7hvz/O7GaWUky+xT7T98wHfTAg+FHr75MkCQ4Ea7jf74cde7gefLcO9NoV+cczWkce7NNnValUQrYIuwXS0Pz8/NxOTk6C/qJ09eDgwFqtVmoXVjOz3/zmN6k0cy+TbjNGIvXIMdWffv69TuYYlXnInFhmHHOxbmxe5iE3X79+nco61u2MiRBj/F9cXNh4PA6bFVAiQ/q+7lS7Szx2F1Ie8/NXKKz6sLRaLev1eqFx/g8//GD9ft9evnwZdi6azWZ2cnJi7969C/ymZTi/+MUvbLlc2osXL0KGCbuNmqUd1yye9KC3fq/ApAbjvJ2lvW3gEUqXY+eNzZe+V6cOvc19vXnzJtyrbuddKBTs9evXdnZ2FnblajQawUZ59eqVdbtdOzw8tF6vlwJD9pWy1oxfs7VaLWQBU6b/5s2boDfhJXiLTHQtJfr93/99MzP77rvv7Je//KW12217+/atTSaTFAiKraaAYNaz53oekFdwSfnJBz5UXsInBNvhuSy5p+cAQFLnG1ACG/b169dBP3z//fep3w6HQ2s0GlYul20wGAQgYzQa2Y9+9CM7OzsLwHG/38/subivci8m52q1mlUqFXv58mXI8nr79m2Y37dv34aNpeBfbPEffvghyJp3797ZaDSyT58+2X//939buVy2r7/+2trttpmtsiCXy6V9/fXXNpvN7He/+13IVvKyL0mSYItjq+sa8joXvc4xi8V12e1wOEwFoABd4VnNTIPgs2azGexWrjmbzaxardp8PrfLy8sw/kqlElpAkAnNvTDXJJecnJxYr9ezer0eMmC73W4AhTudTghE3BZcwq/LaT3tBKgUU/IKciBQAUWo/1QjFgO03++HCDXACNGAuyjQmFLQz2JC3v9X5tXSM0WFs657G8fal+Spk6QpjqDACBYUke68o4BDbFzPhWJAJnxGqSXgB3X48/n17gSj0ciGw6EVi9e7S9Xr9TB/P/zwQwpxvwtpGZInno0+c70fz69ZYGXMgdkEYPpzQIeHh6mUU1LIr66ubD6fh11CkiQJWREAb8w5YJpXRM+B7zw4CymYqQYCTQ4pgQMImc1mwYkys1AKUS6Xww5xd+E7lR0+6ul52T+T2GsF/Hmd5VzF+G0TiI5+8JFPrtdoNKxSqVin0wnp2ezIBe+pAUX6dswpvg1IsoukOgGdQ1CBLCUMN1Lr+R1bYTebTTs6OkpFNuGHZrMZmrfetqzGjy3m2GvZhwcrNEvNPysdy11Aav2tGv+a4RYzyHES2Unp4OAg7EpWLpet3++HNb+uHOS5yD4I/dput0MwAeAFR/Pi4iJk1/zkJz+xarVqg8EgPGfVMdVqNfAnPKIOttdlWboUJ8jr3BhIGtOdasepzapA+7akY9TMA5x+eIsyPwXEZrOZvXz50j5+/Gjdbjc0Nx8MBkHukfGvPU+gfeO3GJDkASUyFchkQ6dSFkMpHNk38A19+Fif3377rb169cpevXpll5eXYT0DBOAUKwDkdYjnA7I+aTjPedBNZjez59DNmpXm+dVnNq17rgpaATRo2Z7ZdWYca63T6YSx83tK3orForXb7QBUALTRtwrQQHXMXXydXaJY4AF+434JALHu8BkqlYp9+vQpxR+aLLFcLu3jx4+hjxB88P3331u327Xj42M7PDwMm2fA01RXdLvdUHKnskwBcrN0lYo+V+UjzoEtambB11Y9qPOg/5XwtbB5kZWz2cx++OEHGw6HASiq1WopfmE8/hoEKny2PwEdElS0Oien+6edAJU8KYP7LCScfV/yRq+b6XQadh/QtE0MvW3LQ3SBZAFK/M8S1jHwyYM+sePN4llQ60i/V+VIhFZ33loul6m6VxYzddkYGl5A7JOxsQ35ecUYZR5wHlD81Isvl9dpv9Tko4iVXr58GSKEXOs28+cBPcapTrCeU50y/U0W37DGYsI1phj8a67JZ8wNAKUqDZx50s2TJAlZIkS2AJE/p3Rw1ykLTGGuaLRIxhKgEpsPYKgeHh7eaJ7Mszw+Pg6R0rsqz6y1HpOJ3pGKlRc9hDxBjukOM2r4sH40O5P1zc4mgMW+ibLer/7fZ/KyAYMLo47eSpPJxLrdbjAae72e9ft9++qrr0IWDnyInJxOp3Z4eBjWMbJo3bytA+o8eGSWzkDy9+T/VBbqc/2c56h8zFwpiEmfmyS53mJ7ubzuTXV5eZkCxQaDgZ2enobgBOVwukbW2Qi7QNtkyEH6vBT4NrOQNUOWD/fc7XatVqsFWfbx48cQoWZnM2yZ09PTkJmj+jnLfovxT9bxKls5xjvw/AEC8F7tgbuCmfpH8234aDwepzZu4D8ZbycnJ6FMq1KphNJoGp1TbqX99/bVqTdLP0vPc4C3hcKqJwzgT6FQCBldo9EolEjrc+bZD4dD++6770KWhe6cVSwWU71cPA9kkdp1vOZ5cF6t1sD288cp2BSTd5vkCMF6PT8ZqmarXWUp0+J7HUupVArz+/LlS+v3+8GWoe+SVp9kZcjvE/mxA7oAeDcaDbu6urLFYpGST5BuZKP2uD5TshSxl/Hpzs/PQ1YO9iBBcHpZ4f9yTl+dQFNus7SfyncKIEEKoJL1s1yuSnVVD3t5y3V5jc0P2PPhwwcbjUZWq9Xs8PDQFotFmD/mV8+L34D/ytwyz+hqvtddlJ9z8OYp6cEadd+2ea0yHxkhoK5sywujjEajgEZOp1PrdDoh4nB8fGztdjssUowQ0jg1TXmb8Sjzwnixe/MOvqK6igZn9XnKygxiDFlKE+WFcjw+PrZCoRDmr91uh4wGInpa24xjViyutvS9bRPRdUrhrlk6d6W78h2GhkZkiAxSa0+kq9frWavVspOTk5RihRDOrVYrtTPGbedCjUr/Xg1hz2u8hjfUMYv12VLgYRsAE2KuX7x4Ye12+0bJKdeCD3u9nvV6vRs90TSqxdiZK73H29Au8p2XKTgjGLVkwDWbzdDok2dFOvnx8XHqmgrG8awPDw/t4uLCkmTVlyE2lqw59eNTXlN5BqnC5rmi0FU+xQCb21KSrLboPjo6skajkSo/oZRB+3ZRytDtdkMjR4w81ipOoRq6fv1tQ7vKd3oPxeL1bjJHR0cB4D06OrJKpWK//vWvzey6ueiHDx+sUqnY27dvLUmuSxzOzs5CM1H6VuEktFqtsFsN180ag/8+dhzGphq96jBpCS+Ot3ek+Nuk99fJPXgOsLzdbgfdMBwOg3PJ+OiBRrnNcDgMkWZeV6tV6/V6IfNEMxQ3zVuMdoXvPDDDe7LiWq2WJcl137NyuWyHh4epZ3d0dGRv3761RqMRSkaYV/4Ph0Pr9Xp2cXER+mm0Wq3QjHY8HgdwJSZz/fg8OKSf+0xI5B9ABb1iAAc5v4INgPvbyjyuy3+eLY2hzSyUECGLObZYLFq/37dqtWrHx8f28ePHAD5RAgJ/stuU2fb9PT09Jt+pnM8iP/bDw0NrtVoB4GVHN81sNLNQmqXlQqq7dAzD4TC1HfzFxYXNZjN78+aNTSYT63Q6wSnHtmFsMUcb2wegGn0K77CLGp9jW8Gv2F3oXuVjdZ5j8ledaWxUmsFz/+hJskU4t84hWa5c8/j4OLVZC+uGck3OGXPud03ebZJ1SoXCdQ+909NTq1ar1u12rVqtBj7EL8Vmazab1u12Q8Y+6113l0be8NwPDg5CCWuhULAPHz4E4KXdbofECub98vIy6jtwXt0xt9VqpcCp8XgcgkkE4XQd0v9ObXb4QrOd4XvsRHhmNpvZ5eWlXVxc2IcPH6zdbocsfOw0sq50vvFxSRShF5V+z5jhweFwGDJkwQ6gbf2ex9az+0g70ZnUG1HaU0GVs9kK0ceBoc4cx4wmfJqFQ9SQ/kGcextC4OnxWREANVhiUcYYSODTDrMMD/1NTAjP5/Ow7aQKDpx6UicRDBjaimQzv3q/2yy0fUR4vfKCpzAgNXJEeuZyubROp2Oz2SwIJ7NV7bnZCrjhHChbnOwsUDFGns+Uv3T8ntf0+StpKr1+7+dhG1JFS9TTn0OzRNhqlmih2fW8ojC0REoBiKx7eQ6ErCMSBBACMEJTTEosDw8Pg4NC6SUZYNSkAxQ3m81goOIA6TPLev5KyCOfSp/1LHwESJ1kDCmud1uQEEI3mF3znZ7fzELj0PF4HAwgwEtKMunfZbYC8wGqYmPbV97LAnKYQ0qy0AXMFWWWjUYj9ADCifcOErtw8Uwo1VS96R15/b0fG8RYkMtqmKrz5IM2/lz6fx3PrfuO89LbAYOd3/lsQBwEeIzSQM5BrzkM4hjoCu2z7NP7AXghawbA0GxlqOOMsU05mRletyBLCoWCXV5emtmqhwnX9PbLNnOYJKtSKXWQvK3ogSh/TJY+js3LunmjRIa5w4ZVe81spWexXxaLRciQfvnypbXb7fAd98hOjfzWy/i7yuddIjLjsPvJWtBgjH9u+BUaUNTeomYrncE5cYDZ5WwdgJ0F7PBs0NXorixZitzToCFj9eCBtxv1ugouaEnUV199Ze1222q1Wih3A/Tw96XyEXBMAzR8T0kYsk9B0iyfahcoq49ObJxkE5XL5RDE576xzVTuaRBfs5gURPf2+XK5DJmcR0dHoTz48vLShsOh9fv9ID+VH3TMyh/4JPACyRyafc5Y1IZjXijjiwGZfr44H2DX2dmZffz40S4uLsJaSpIkZA5iE2umEvxUrVYDcOkz5ZW/mWOSK8h0jdl5z0HuPTXtXPkbRq/2WNGIJHW5MDXHoixUACs6SvkS52AhxcpDYtEE/12WwvAOP4Yvi8Ebu3edI48861a43jgvFAqpFFozCxFmVY4+tVuzs/T+ngP5Z6xOL8CjbmeM4TCdTu3ly5c3kHn+e3QeI0Mb3VKOuI6Ul0iLjRl+2zhKuo7UIYtd766kPK6k12QL0V6vF3iRaJ/2B4g5WPvMezEDj881AxO+S5LrSD5ybz6fB4XIsyQqj9IluxM6PDwMoLuZpeSpyrB180qa8zoj2YPu647hfjn3bQlZjmHmwQQFiswsNJLkfbvdtrOzs5BCzrGk/SuotAlA2xfyTiKOS6VSCc30KUll/dHz4u3bt2Z2DZrT40ZBcWQKmz5QokMzVvSu6kCd1xjvxZxvBV/UyAaY4NpZzpSZpQzObUl/r84C12QN6rHwJpnR6sRju/A7bfzpDXjOuY/8FwMLyQKGv8gw0t+oY8s8qlOgGRkaFMMpY9dRdI2ZhYwlPz5v3ynfIAd8VqaCPWYrEN03w826ThbFfktmF8ErrtHv90MvMz03OoI1x/jIlru8vAzXIDuYeSJw68+5LxQDDnEiARq1R4tZPHMcG4Rj6EXlsyW5JrLu9PTUhsOhXVxchLUOETDbNH7Vy9iR2phbgzuxgG8suztGMdCQgFOlUrEXL16E7BP6RhUKhQBkevuF9UxPHwUXGJcCFJVKJchqXrNZi553l2RgVqlvbI61Tx5ZPgp6aLIEPIguYU7QEexySc85zk9SAHbzN998Y7/73e9CM2/GpjwED8bmme8oI6vVagGUgjcVADNbBajn83lofo8N5cFNXWfMA0kfXOPw8NCOjo4CH5pZ6r45P7wAKM480jPJ35/yHkE0qlE0Q1jlf06fRztR/uYNXpBPZUgQWBiXRVgsFkM6K9F67+AikGHY4XAYnKWYYIg5tGpIrHPmfXQeJs0qCQAB5tz+XFnj0yhFuVy24+PjFKCloBrKkmg9C4lduBA+se21UXYeLNuWdiUtX8nfBwKH7A4AyMViYefn5yFN9fLy0prNZkiVxiGl3AbgSAEqSk1KpVLYzQAeNtvstKrT7g1cb+jwrDCyFRiEH7xBsi47Lou4N1LJ+UwVEM3xcOwrlYpdXV2FXevMLBi0zA9ZS4VCIVWr7Y2MbWjX+M6DyRhY9Xrd6vV66GNDBI8d4DqdTthW1syC8aoON5kRlGgCXlJrz1x60MQbbDGFDGjvjUPklso6ff7cI+Tl3F0cfO3RxU4zyCYylBi3Olftdtuurq7CblI4sIDxfK4ZdzFgYhvaBb7zwJjeAyVI9Xrder2eVSqVsJsb5anT6dRevXoVeIcyLd/cV1P5SeFPksSOj4+DcwXfMt8xkEtlmedrHA4v43y025cYqdz0YPc28o7fMD+Hh4fWaDSCwc8x3tnSJrtkebGGANMBl9AfAALaT4Nx7qK828bJ8jYdzmq/37darRayVpErKmdYl+gKHDEtL1P5hGPx+vXr0Nfl5OQkZIjF5FxsrOhH7bGmuxziPPM9/MZawA7AoUuSJMiUrOfj76dQuC6fYW212+2wWyXBBwXK4DWuf3FxkdoJD3lGMIf1WCwWbTAY2OHhYXgOd9nIZpf4Tp9pvV4PrR+w4U5OTlIOvtrHOMw8K2Tf27dvbTqdBjvGy5J6vR7kAhlh+C/wkAe7GKsft/YqIyuIcwHuKBitGfH+/rVnkZ8jvf9CoRDkP2Om7NSDlhpkXi6v+8OxadJ0Ok35bZqRgi3NdQGpKEsnW/Y29Jh8t235W6lUssPDQzs8PAzN4I+Pj1O9fADOCahyHvywcrlsl5eXQZeSUaNzD1BFJvvBwYGdnJxYpVKx7777zvr9vnU6nZARq7rT+8X6XL0MwH5CxyKL8ReRbfCkZkgim3nuSZKEQAJ8Tj/Lly9fWqPRCGXMlETT1mY4HKY2kQL4x+7tdrvWarWCfPQ2BeNgzilNV2As9jxj9Nj23T7Sk5e/eWGHQ6BOC38ofIwNkF1t0AVAoNF173yz1aMKunUUA1WysiliwMs2zBqLjK8DrlhcNL7kumqQquL0hjn3oEADAiIGhD0nJNffg4I83CcCdLlchh5LsUZwnU7Hut2uDQaDEF2IKUl18tWQziLl2U28EYuQ6mtdY96xu63TzG+IgGJ067343RdZyxjDsQxE37hR11eMh/eNYjynJUgYsjgHZJJQNsg5MEwU9MUAxTHDSOY6HEtGzm1LMD1YHTPiGUvsOd0FnFHS61ISolEpDAbkn65njHSMIY43s5TTigOAM5fleO4DrdMhOA/Mh/ZqoH8NYCdrtFqtht8TvFGZRMSRfkEa7Vf94p3CdWsZGTGfz1MAs5dfyAyv5+EZvUYMQM/S2YDzfAeAiRxTZ0h1b6lUChFU+HCxWARggJ144D0cRGRBLDMm9hx3mfy4tSyLfpi+FJw1jI3XbDZDJjVzDBCn18DRn81mNhgMrF6vB57R7B3/O2/PefsJGaafKyiOLFH95mVjlr2UJVs0u6Zer4e+Kr1ez66uruzi4iLwnAIi0+k01WCaY5CJhUIh9PfB0aTUhCb968DpXafYHFOKRVYHYBo6BJuDuWBNku1WLF73prq6urJOp5Pa6ZLzcA76K+k26PDbycnJjYy8mD3H8wKUxNZEZmp2uco2eNOfy8tnT9qT8OjoyOr1etikgeBUo9EI2YVqN6hMZG0BRiGrCeArsKDXBkzPKkXaN+KZwXeFQiH0+CFYqPIFUMbMQqJDt9u1crlsL168SG0sYpauhgCYYQ2bWcj+fPnyZaqqQnWhrnHlCbV3+BwZotmi8COyHHAMWatglfIfOkDlDfJce/7CZ6zFVqsV5sfMbvBfsVi0Fy9eBLAIPuS/ZiMi4wDvsKO93NtXnbtL9GSZSqqwMDxZJDARTe5IaUbAabokUSoEFYINpe8XEr/3QnodA6lDpZ95w4RrxO5PHSMfrY0pmXUEKswiI0qggJeZBWOEEpjRaBRe63ExQ0h7CzG2uzj0uxC5N7sZEYS0Kbw2oqMBsDqgpdJ1E2UMNJB8FIaWVHIdIhNmFozdGB/FxqvGpn9WvNb59Q6UWVoZwYNa043ztg1p1BiHVMsul8tlSM9nLthKlnIuVQrUm2PoogwwRBQgvS3tQgQVijkvZCgRvSeLcLlc2tnZmdVqtdDU/OjoyObz62bxGK0QBgYyhh1XyIbAoCGbk62ltcRDDQrlL5+VBGilFDNaON7MUkaRAobbyhPOi8P18uXL0NMmSa4zRWiGr+sKo4qmvegIBSE0Ko2BRD8IvYfbgJm7wncx4A8+oGE0Mm+5XIZdV8rlsr158ybsmKK7/ozHY2u1WqFHieoxDE9KzOFbAE8zS2WBqRyI6V4vo8xWukgNRSgr2zd2jSy9rfIWYA2Dt16vByeJpqg+qgs/cS4CDRivWhJBGj73RW8I+JAxbUtPHbn3tg6kmXFnZ2eWJEnIUuJc3DegW6fTsQ8fPoSMTOTWYDAIzfa1HII5Z0fWn/zkJ1apVKxQKIRMJWgTwI2MwzkGJMWJ0mwDMm3JoMIG0FI9eFTLM3XOABMpyQAwZ5zn5+ch6MCaBLwkqMgawR6hpyilX5ol2Ov1QkY2wIk25VXAivlaR7vAd/55FotFe/XqVciAPjw8DDoDH4O5IwOJ8tSLiwsbDAbWaDTsZz/7mX369MmOj49DiQ+yrtlsBrsPf4MsOZqoHx8f27t378LzBFA2W80r/IZ+g5d5ppSIqU0FGEbwCX8gBlip7oK3ms2m/exnP7N3797Z6empnZ+fhyoQzVjCTwLs1vEVCoVQnknmCYEJQDm1CbDtWDNmFjZg8ply64Ii0FPznVlaxxLcpzWGgkjoS87F5+jG9+/f2/n5uVUqFTs8PLTj4+NUk2rWp5Zlol/JktPKHgXW0dk06SdrTO+L+eeZYgcgb7A9KfXE7sLPUVBb/W4yj/ARkiQJGzVUKpUAuMJTlOXiW5AVyqZJGtRPkiTsro3sIvsNQIl1h53ENeBBxkXm8TbBzzxTaTM9eqaSOjBeeKjji6ME42KUocARvES/UN7UWlIu5yPtZhaEIQbwJmbiGF++kWVI8d4DWv4aGnndlC3lf2e2auSIkabAl4IeOJCKJvvrMwbO7VMl94E2OfcxQklz7wjR4XBol5eXAYRUZdDpdOyHH36w8/PzoPBVqaNAEZA8m2azaS9evAgNg7l+lmPl0f6YM+SP9d8pMKNrjMiDzkPW/ECacYDj5desGl7z+Txs06vOvHfg9B4UPPNgzL5STMYA7nGPPluQSBEA0GQyCcYq/MYzjGWKJUkSIl8Ae/CC9nHxipr/HgAHlPEyL/ZcVMab3eTBrN95AtQifZz5UeOT9QppXynN0sJJ9AAaY8NwY23sM79BMQeWlHV0JsYaPNVut4N8ArAbDofhOfR6vRCR96DvfD63s7OzAGiy/nFscZLUkIzpGJ6Rnl+dLbOVflKHH1J56T/z8xLjffgNBwvDfbFYhC21tRQLWQfowFxzn7qDWcwuwPj1WYT7JPti+ofnrhkjAOfeXlHwBccenYyjVq/X7eXLl2a20kXMc5IkQRerrEQXZ43TB3hUPmjk3WzVa1EzGiEcRI2Oqz2gWd98B8CBI0nfKcBI3w8vSVbZWiq/KCdEJ+AssSEGa4dgg/YvVD2cFbjaJ1I5pyCf12mq93CILy4uAlDDdukEELXHIbxmtmpAD19Q/mZmoZT4+PjY3rx5E2xwPx4dK3aU2gWAVsq7PBcFcPjOLK1rmYNKpWLHx8f2k5/8xBqNRgjCA+7ohj66uQfBfLOb/UPJVAGk1E0wNDNY1xLXYm0CjOm4obsEFB+bNCHCLD1mDY5oUBW5MBqNAm8BoHz//fdhYwef4QSvcT10k/as4zm3Wi07ODgIgFC9Xg+yRn1a+IvG1wCuyBnkBXoPnoc/ORc+O0TWVqlUCv62tp3h2o1GI+yMByBPVUOtVrOjoyM7PT0NYDi8BN8wHuQ8a8YsDZxxXcbE89mUAJPT7ehBEIN1zr0Hk8zSdb4xg5OH7qN4fI/QBwnX4zEsVMgWCoUgQM3SWRxZTo8atIyZz/193UYpe8fLk/+9GkNqACtpGi3bLiLYs0AlzumNJa8A98nQjZHnP70vFHeSJGEHKQUEEFb9fj9EVthSWo08nJzlcmmXl5ep7DC2F1XlGQPuvEOkGWOx5xDjP8324XP/220AVcbIWiTyqefkWDUeKElQh8vPP3NOJE4NcTV614EYu0zeUeEzH3nhWdEQGScFo4J0cXWQNPNN52uxWITMpG63G+SAWbrpsRrJnnSsHlDKOlafkX7G/Zmtnvc2pZ9qEHMeMjo+R0E7AAAgAElEQVQ4t94zAQV2XcGIZ60qUL5YLEKJofZqMks7WPtMXs4B7OAM6LNBxtDPBWAdA7NUKlm9Xg+6FgNS5QNGIo4uOhbjFp6kFIwxenAK/uF56Wu1DbxOVn2mx8RsiZgeg9cxVnlvZtbpdOzi4sKurq5u2BIY8kRB9brIylKpFDLDACXMVrym0eN9k3FmcXsAUOng4CA0UtWMap43QIeWOeI0sf7p+8IOmD74gH1TLpft06dPdn5+bmdnZ8HhwNnX5+/1H89bZVTMRuK56n1ruaPXVQp86bwcHx+HzABAMHWG+IPnkWvqnCrYCmDBnHM+vteMJF03mkXh5fI+OPVKClz77DAPoqEXANnJ0IC33r9/b58+fbJut5tqvl0sFkPA0GzVL07LCuld+sMPP1ipVLK3b9/aV199FbITGRegq4J82ALIBe17g7yBxzSIp3pX9Rcy7Uc/+pH9+Mc/tlevXlm32w1BA2QTc4OsJliNHkDmK/9pWwg2MoD3NKsdUEXnHoBEQcB9lH3oFQI28AGfq15TMBz7I0mSALaz/iH0BbKNeea5F4urHkdkBrVaLTs5OQkZoo1GI2TQmVl41upT0FMWwp7itZkFex5QkHvn+SuoAy8kSZIqty+Xy6HBPW0ykFdmFgIsrLHxeGwvXrwIu9xxLWxSgCvmEyDYb2zD/Ou8maWDifvIe7tIj777W0wAmq0UL1FTdfZ1oXmHBUb5/vvvg8AlasO2vuoQY5xqjbTPGvEOuo43dgyE8lbwRg0oLYvS36jRi5Gg3/s5Au01sxRoxPUuLi7CawSOKjE1wnR8nFMNDu/U+bnfF6NDx6nGnfYYYSetUqlknU7Hms1mMMpQFDiypGdCzDHH4NS2Wq0APrVardD0sV6vp8qW4EnGxXhRzLoevMOlQIxPNzZbRViVEKzwZNZz5J7UyJ3P50HIQ71e70ZfB5wnADaN2sB/GEwYHXznwWV9hvvEd0o8v1KpZI1Gw4rF61IaDFmaFx4eHgaHCD6jMSfzBnBM+aD2KJnNrnfrOj09tdlsZpeXl0EOHh4e2unpqf3P//yPma2MFgVU/Zg1BV551GdsqiFsZmEdIHM4BgdHI1v+2hgMZqtyXxpxq6NPNpZGAjHWFBRmDauzz3MYDoeBr5XX95HPPEgCqZzrdrup/jSqL2hE3el0UvNRKpVC1lG5XLajoyMbDAZRcGY6ndqnT5/s48ePIVJKNgWZi5QXU6qjsoxn7/kD3lIeUOcpi4eVN1SumKWbkB4dHdmbN29ClsjV1VW4ZwUTuIY2+PRZBjgXyF1KIGiI3mg07OzsLAQYFERWIGFfyM87c0bZoJmFsj+eAfdJZhuOLjumcr7379/beDy2Wq0WQD112NTJxgHmmWigo1Qq2Y9//OOwU5IG3wAjarWaDYfDkEGBrvU7S/JenxEyWkvzFLjHgTk6OrJvvvnGrq6u7Le//W0Aa7W3jO7kBigHT+C0kRmMXGu1WildWiwWQ5+zJLnug3h4eGgfP360w8PDVOkU19TALc9xl/nQO+wHBwehVI3yGc+bvKeHEtmHR0dHYf11Op0g53Q+NANRe5Di8NN/s1gs2tdff22DwcA6nY69fv3a/viP/9gajYZdXV3Zf/3Xf4W1oH2ttHRdt6VHXqvcw2YtFovBntQm3vgG7969CxuqwIvffvttKtvl6Ogo2Gr1et36/X5oftzpdAKPYN8pCE6JqJbHoRt08xuOU1uQOVTggefpn/EuEutaN/DxwJsC1JrtSqXDixcvwhyxuQAyEJCYjDEacBOYgX/ovdloNIIcI0Pp5OQk+NDIGw1uvHr1KmQW08yf8mwNcJqtdg3nfqbTqX3zzTdWKBSs0+mEeSkUCvby5Ut78eKFlUql0BbjzZs39unTp1Q2qmaIw19UEX348CHw52AwCLYyawSQHV+EIP/p6al1u91UGxN8Z+xZLZPTDPhdl3m7To8OKimpQarMlRWx9L/V43TRajMwFpNuT6jnKhaL4XgcbO+w8xqGV2OSMWhWiDeuPJPquGPHZzE0glijvN64VmOLshm9BwUr9Hr6PzaO2Of7svA8r0AKqsGDCrTonCpfoOzN0qnxCsyhEHq9XuBtImFcQ8en11vHRzp2nmcMFOW1AjL+vZ5HgQB/HeUpPZbvza4dhqurq3A+/Y06gn6d4IAxxwp+eSBN52QfBH/MMNKsIgUDK5WK9fv9AIj7udASTY1eUvfu5dTV1VXYkAAHBECT8t9utxvkhM8i00wmD/zwDFVZe/6EVF76z9WI1DnDSACoJZNhubzO/MPI0n4pytcYDoxdo30+Ql8ul1OlDSrn94HHPMVkttkqosh8665UREt9RrA650Riz87OzMxS8k+fAfqU7bXhEY6HF8fjcXCcAKHVCfc6xoOV+jkAj894YkyMT2UZ/KG9KIjEsluUOgdmlvqdGtpmK5lNhHQwGARDXeUd4CZgGsax9i9hXfh1t8u8GFv7arCrnaLPWTe14BlrFJxARbvdTtkuXj5yDYBLen6cnJyEXnQAzn/wB39gnz59sk6nkyqTQxepztHgB3zC81GbQPWa2qv63E5OTqxardrp6am12+1U2wbOATDAbkiDwSB8zjG6i5KeXzONdP1iW6gOphmz6uh9y9D0tgz3R6kq8o5gtdoZgJlHR0dBPpHBQUmOWXoHLLOVHFUfAF6jb02SJGFXqq+++irwtV7zpz/9qb1//z7V31XtTu5DGxDjxOvz5FrcM3PCRiqUky6Xy7D7HaAGACf2AO0e4A8yV9GT//d//xcaa1NaqQEb5gigazKZBIDNBy+5joKg8F7MH9k18j4kWZAE/AHMzSwlP8imPj8/tyRJUn31KD0nmALgR1++er1unz59stlsZu/evbNSqRR2MqevEjrFzEK/TrLZW62WNZtN63Q6qYxPbCYFNeFlnjP3TPsF5BRA4mKx6jWXJIm9evXK3r17F7L2CHBSbtnv9+309DTVj1btQQ20EkyEx8h4Wi6XwY5lDpCLnz59Sj0DCH7TiifVuXqvu6xvd5keHVTyhpJZuus7hOD0DqgyCczonRbtd4BC1lI3/oOQI9zM0rssKMUcdBwQBH7sWI04qiMZA8n8/fG5nz81blXBcTy7CajzyXeaFqzGOaRRP+4vy2HcF/L3yP3pvalDoqCi2c0SM5SnggKabmlmYe5RyhgUODUaddSsMQ8osTZ4rbymitcbsv5e/Wvew0s4gzHwygNUABXa94eomDfIGa86VB4o8uvCA2XrnuUuk3e4zW42OzdbOavdbteOj49T22BzDCALEUB+Mx6PU8ocnprNZnZ2dmaVSsUGg0EK/Ly4uLBarZZSpB4s98CKyki9Pz0eislks5slvgqu8XttWktqPmnSxWLRRqNRMJrUKPLjIeuLdUHEmuPgRb0+/KrlfvtoXHhny/Oc7uBCeSS60GzlQGn5OMZjq9VKZaj5+cGphfc1uDOdTu3Vq1f29u1bu7i4sMvLy9Q4AQsYL98p78ZkGc9Pj43JDS1NwkhXIKFQKITdO8kSVKdHs1FxVtUQ1fWiuxNqBojaNVxbx8jY9Zh9oNi88zxxQDzop5njZDrgnCVJEhopcw4NhKneRH/BH69fvw6ZSGQRICu/++47+7M/+zMzs9TvNMNJ5Z/qLDMLzhPAtQc6VVeqPqevCI49GwngsL969SpsrEKwAKCAzClsWOS9yi0zCxtf4NBPJpPQbN7LSSLz6niRhbMvMs/zHOsawFwBOx8g5NnV6/XQ+0j7I8F/NFDWZ6t6gk1IzK6BnF6vZ7PZLGQiAw6YrQLP8/nc3r59a/V63X75y18GPiTIo5mybNGu1/RADD2Rlstl2FDmq6++soODA7u4uLB+v2/ffvutffPNN9btdu39+/eB/05PT4PN4YM39GM0Wzn5WuKkGaDL5TJkExI4AHA7PDwMzZDhN12/PCMAgdgz3mVSuaU9A81ujh9Ag2PpbcWa//jxY+hrdXR0FPw4+hHN5/MbDa2xl5hPMh4pxx6NRvb27VtrNBr21VdfWbvdDnxdKBTCNcrlsrVarSA7AZAUFEOHaobc/7P3Zs+NHsnV9wHAFTtAECR7U0sjjUIje8Z22Be2I/z/38449FozY229sLlgB0hwwfJeMH6J81SDkt7vCzWpCFVER3eTwLNUZeVy8mQWoA6HMsAAp2SeU9zG43HmswcHB5Ho9Ook3qFarYZ9hIEEUIqsYNc9wXp7exuMK7cbHs96FQesUAgYv43/f+MXOf3NM0jpWAem5PP5zNGSGO5CoRC9RPhcuujuuDBo2oUhAHVl03m2zIOyNBBKgyt3Evzv1JlIgxcPmtwBxsnnHlBg0ywsxoN3pRFbuVx+LzhHWXMKA4ECCsgDvtQJd+PrQIUDAuvW8MdGGkj+kuM+uUsDe96TjCBz4nKWnhDoa+gBP4ZByvYS4xoAMGSZCK48iC4Wi+8FYdzHM+mspa+bO7OsvwdlvoYeePEdjJT3+EDmCoVC7J3ZbKZaraZqtRrBvaTIklFuhPw6lRUjirHl/dL18kaHMCOYtxS0/anxmOTOB709vKFlLpeLsg6cAIAcas+lu/kZDofBAPAGoek9Mf6sCTLAs0KZRvfikCMX/p1UpzlYyHPxOfaRX4fvMby3SrVajfcplUoZEAsqP1k471PgAITrP58LmCLsQWd/uFOLM5HaCG9u/nN13mOSO+aHeS4Wi+E85nJ3JwVCZ+cUKHoq7e7uRvkgvRqQR5/3VK4cDPFgCn1LcN1qtfTy5UuVSqU4VrharUZQxPWdQee2Cn3idpW/160VPStyuZw++ugjHRwcaH9/P1hq6CYAJZ6bv+k5ge4DOEJmXG6x4/P5PPpaDAaDAAd4DhpY+1ylbDHe96ec3YeUO9cT/J/sPYAOOoYA2u0AJeLoulwuFwDKbDbTixcvMmvhumm5vDuJi8CMddnf39fz58+1tbWli4uLCNCvr6/jdMO9vT398MMP2tnZUbPZzFwTMCCfz2eCFy9R4/kY+AjO/CwWi3r58qX29vb0+vVrXV5e6uDgQP/n//wfnZyc6NmzZ3r27Jn29/f16aef6vPPP9fh4aHy+XyUoOZyOe3v7+vg4EC1Wk3Hx8expxxoI1BFjre2tvT06dM48Yn3wtbc3t7GvpZWCTFnj/3UeGh952tBv0oCcBInAOIMgBjihul0GgAKpa/ValXff/+9Xrx4EYwN2CTMDUycRqMRJYyDwUCj0SgaLcNK29vb08XFRaYfnSR1u92MT8Vz4fvApMMX9PYg+OQE/+yL3/3ud5pOpzo+Ppa0YjlXq9UocQIQyOfzGgwGAXSORiNdX19HWeB0Oo1SpS+//FKNRiNOkJUUQNfu7q5qtVokc0ajUeh7yq94jhQwdxYe7Nl0bdPx0PqOvzc2NoJxc3FxEYei4OO4risWi8ESmkwmcZIqjbI9Btnc3NTbt2/jBFVOcuPEt7Ozs7BLh4eHGo/H6vV6evbsWawBz7m3t6cnT56oWq1Kupvver0ejKHZbKbr6+tgRAFkp36QgzK8v/vq/O78/FxnZ2daLpeq1Wr66quv9Oc//1l/+9vf1Ol0ghnHSW0wg+kzV6vVVCgUwkaXy+VoYo6NwP8djUYBYKGLU5Ym90n9FgBb3pk1+LHxIeXu1zoetPxNygI3nj1G8TjTJzV0/n83sigvglmn2Pl9JcXpDp4V8numqHMa0N+XmeJ5+Ix/16nUfp3031I2m099crVafU/h+rVwbBw4SJ81XQO/H5vSHTg+92tGcn1u+duDEtbEwSNfF4b/nLnGQXHHdGNjIwy23yNVztD9vf8XStZL7fy5PYhPWST+bP7zdZlyD649+4STBfiBMwN1mu8SDKTKmOtA4Xf5W7cn/Ln5bpqp9+/8Gka6l5kz10O8J8F+WsomKeNUos9gTqxj1Dho7ZRsnzfkAke52+1qPp+rVquFU0TT8HWguesUf1/ug/7gj8+BB4W1Wk23t7caDAYRhPE5ekY5uOAgUipL/MznnmydpPfkKU1SpPs6nddf43A54P/oJu8Xh1Pl81YulzMnUC2Xy+gJAggtKaMLUvYY5ZySwkG+urrSmzdv9Pz5c11dXanf76vdbsdx8uwDgOl14D5rw7+9Px2fS+eA70ynU43H4+g7Ua1WVS6X1e12o6cU80Km1eUAJgKgFA54el/v/+AJGewMz+99x5yB8GNB1WMa9+k5l5HUh2I+0GVuC2ie7z34/Nhn9MxisYjemMgzvUUo0yyXy2q32zo7O4tr0Ltkd3dXL1680GQyiUC70WhkbLaXx6Xv6ronBdX4u1arqVKp6OzsLNjA/X4/fE704XK5jN5jsEkACgj4Dw4OgsEAUAkAlNoVadWc36/Pc7OveDfkEdn7NQZPJGyQj5Qd574Q+xTmK8k7GIo7Ozs6PDzUcDjU0dFRBLPe4wj5RPYATH2dYWOORiO9fftWtVotdNtoNFK5XA6GxcHBgW5ubtTv90OfehwBOOvl7O67cY3d3V19/fXX4X+5LWa9AXym06kuLy81GAx0cHCgYrEYJbmSgs01nU51enoa/XhKpVL0naNv12QyyZxABjALSIY9T3U6f7ve+7XYXAC1lHHlCToSVsig90iCVcj+3dvb03A4zJQQkqTY3NwM1g+VAVdXV5pMJnr37p2urq7ipEzAy6OjI/X7/WBFMr+TySRTWssz+mEAnoTm3fD7KK2bTqex57a2tqIPIb08/+d//kcnJyfRU+vo6CjDiPb+UeVyOXQbyZ7FYhGMdZIPlGy+evUqyvUkhU5EzmAao9ewOe47O7vzx8gwv42fP34RphKO0X3DlQnC65lEnFwcXen9k6XSa/E5avjZuNBTcTyh4NENH1SUIxlLpVKm3MKDmXVGyf+fBm2pI3/fd5zVsVgs4plAa+v1emT0pTtDSDPVy8tLXV5eBqNLujNgbBafQ0dq0/nzdbvPmXWw7eeOh85kMVJAg6wjCg6jDGttHd2e4ZlomgJ7vX76TNzbAQDYKmSLaEznip+Aw2uscQyk9083xHl0ANXXjO+yJmS+CBZzubuM6O7ubhxxTBDmtF2XI3+nNLh3cIH3Tx1xBsbWnQrf2/fJ7H3jMcjdOvAWPeMGGicrn1+VGTkA4gEa4BIObDovnq0nSIUyvFwuI2AmS0MmkT43nPjC2nr2zIE+5B1nxwEt/ngzWwdTcbrq9XrIBSeEHR4exrN7SQKABc8BO873cgq4OnMQ1hMyybO7k+T73cGWNHP6Y/L30HK3TuY2NjZUq9VCztBXZPwILth7yAgBBn0xaN5ZqVSiySZzBdujWCyqXC7r6OhIP/zwgyaTSdhZmsF+99136vV64QD3+32dnp7GetIPhIA5BaxZb9fJrOO6+c/l7npX8OwE4zSzb7fbqlQqwRo5Pz8PvXtwcKBGoxGB0nw+1yeffBJ7bTKZhI71AJBnrNfrMec+0n5LqR7F2f+54zHIndsemF3oCjLNsOKwJyTIvOnsYrHQwcGBms2mut2u+v1+6EXYbNhqAhIy7vP5PJIxW1tbajabWi6X0UPk4uJC33//vd6+fau3b9+q3W5rf39fP/zwgw4ODnR4eBi6hPn3YDy1edhD9yskxaEflJ1wdHilUglAaX9/Xx999JFubm6CydbpdKKp7e3trfb390NfAZ5xJHilUtHe3p52d3c1mUz05MmT6DnnewYm9PX1dfiO6GF8GeTHmXgpUL9uPAbGiHRnd5rNZqwzDbPxKVgfSl1ms7sj1mHhkHygWfxoNAoWzg8//BD+GXYNmaB0knngQIKLi4uQ9eFwqNevX0u6AymPj4/16tUrdTod3dzcqNPpSLrzx5rNpg4ODnR8fBzsKE8awnaEZSqt7Ovh4aEODg7U7/c1Ho+jOTfggTNNYf9Kd7qoVCrp9PQ03gtZRk7wc/FRvvjiCy0WC00mk0gOONMF++BVItKKlZQmN1hPT278WKzx0HLH/Ozs7KherwcziFjO/X5sBzEaB4MgU7AnNzc3NZlM1Gw2NZvNguV6fn6uxeKu9LzRaISc4wP9+c9/jmbqJH263a6Oj49VKBT09ddf67//+7/V7Xa1u7urTqejb7/9NmTJT0uDlYR99H7DJD5hk7JexWJRxWIxyvfQPbe3t6GX8dlqtVrYbhKYudxdQ/dqtZohk1C6e3x8rI2NjZgHTswslUrB4nIMAb8YNhT9lrxFBH+wI9zXE/jrxq8RbP/Q40FPf/Of4Xx4JisFQNYxe1wpEaxcX18H64PAAWAJRcZ1JpNJ1JZSElKv16P5Hn9gLKVZd38PD1jSn/F5/na0nj/c6/LyMjYKtfHMBdkmngNnGuXkWVB3WH+K1sc1eVe/7rp3/TVlE3ykgSHvgFyQZfJ14fP+c4wrdPP7SgNZCwdd8vm8Go1G9Isgo0QtNcab3/t33cF1wMjX3eXP94zPgf//9vY2gMnt7e04pY596GAme4BnXndNfzbAUQdFfM7Tkb6XZ4B+jfKWZrEJxFkX3g9QE5YGe56BfpQUYHkK4LH2/HHHbXd3V4PBIBxJTivBcDvgtVgsIrDhHZw1mq7Puue4L/B0XUcZxu7urp48eRJ7aTqdhg5fLBaZUj/2HSczIrMAIw5CAGJ6SaknCNDBzNN98/hrHuvWImXssp7z+TycPAJOlyEHCLxPEJl97CjywylC+Xxe/X5f8/lcrVZLz58/DzAGyjtONg6ol8LfF9y6n+BJGX6X+hoAO8gODCWeHftbrVZ1eXmpUqmUOV2QUgdJqlarOj09jRNpSOLQA0xSBBA8j4/0ZMI0QHYf4bGPdF0IRL23ioPQAGasszOBKNGcTCbBBlksFtFzCECgULgrzXaAyU9Kw5f0oHw8HscJRczxyclJlDQhLwRmqQ/EZ5AFScHC5TNpP09O3mS9e71enIg0m8305s2byOxTjvb8+XMNh0N1u11NJpPwA+i/Ui6Xo98UyaBKpRKyxqC3SLVaDRaCz4eXfbCv2Uc/BiQ9xoHMuY+OP+cjLRdEZwyHQ7148UJ7e3t6+/ZtxrYsl3clgzCJ0FPej5BkD3JweHiYAT5TBgi2DVbe5eWlGo2GhsOh9vf3NZ1Og63Ce/g9uR+leTAvnHUHy87L7crlsm5vb+MkRdhQs9ndKWTIqieQ2L+UGZVKpQy7I2UlMtiDGxsb8Z7EKMw7fo8n1j02esw+H8QFKduzL/UZvA/Rzs6OOp1OAOk7Ozs6PT3V+fl59Bq8urqKclx8sNPTU+VyOT19+lQ3NzeqVCo6Pj7WV199FfeczWZxqq+k8OVg3J2dncX6euIS207ZnDf7dvuE3+/+Ket4fX2tyWSSsWkA64DcgNmcdDkYDJTL5SKxnvoYgD71ej36ntG3DOA4l8vFszihZG9vL3zHi4uLSFrwXuxZEo/4Ow46/Tb+v41HU/6GkvfgRdJ7f6eDzyNUCL4HPx64+fVQXihelLZvBLJK9XpdFxcXcV0PUjyg/zmK0K/hQYw3UYWuSCNVgimCTt6F92cOUpYYxod3/ClgKN1QHgyn33lsSh+n8ucMDxg9cOL/kgKZd6YMn3W6ZOq4+Gc52ceznFCfWW/PfOB4O3MA+XIHwY2CrwH/JuBz+Wc/+Pvl83enQuCgw35zxzI92j0NdNaBj8g1yprgIZUtAAY3Xh4c+uf4969hrHvOFPDjZ65DWBPXWc5gcsc0LREkICoWi9GkGxmANUFgTXnTbHZ3OkwulwsnBDng+Vgjv5frG3QOOozf80z+N9ektCifz0dz2r29vaDdU+Yh3Rl8erMQWG5s3J1cMx6PVavVAoj1fmXOrEsbTqZr5PLme3wdqPSYdN6PDQfxUpajl0U4AAkDDueTLB66kUAVW+mgFfM8n881GAwi+KKXzWg0ih4jtVotHGX6KZFRJ7HiYOC64Xrtvn3FcH1E9pzTFqHm8zmOZC4UCvGsyA46erFYRLDIv5Hnd+/eKZe761l1fX0dvSzSZ/N5T5McrvPWvc9jGulz4azjxHvpC7JFkOrla9vb26rX6+r1enEt7C+fu7q6UqVSiblF3qQV25WSkcFgEL11ON3r6dOnGo/H8Ry9Xi9Kf8/Pz3V9fR3MIm9czN4gyw6oQxNi9Kr7ZsvlMuw4bPPFYqHz8/OQRdaeZrVXV1ehl0ulUvQbyefvet+Uy2U1m01tbW3p/Pw8Pt9ut/XmzZsMS4LsvettkhGpzKXlmT/Xl33I4e/AmrgNQid4PxX3s/HP8JUWi0WwKUejkU5PT9VqtYJ11Gg0MiVtkjJ9S/1e1Wo1mGGwijY2NqJKAnlmTKfTAJe++eabsGckGgn0CbphulcqlZAzWCH5fD5aZXhDZ/YkABZgFAE8bE72jZTt0Uj5FWww+vgAFjWbzUiG+smfrBX35/mdHcd9fi0lcKk8YRsKhULEW8gfQAy2gNJBmDX4PZQ3YoNhD+G30eQaWb26ugrAZWdnJ/p60XupUqnEyWtv3rzRaDTSYDDIyB32llgnbUrPu7ofSGyMT8D3vXUMOgc/DzARoBTgkvYGrj8BcwHb9/f3dX5+rslkokajEb7yq1evVCwW1Wg0ou8rTMu9vb1I0uI3ExvyLtyfUjtP5Dx2+XvM4xcpf5N+miLN/wk4+bxn6bwJYupg8bcrIy9X43eeeUHYEWR3Fsh4sclQFNQQAz55YJ6+iz+jI6frhgus0w9xZp3hgSPrTex8Hpxq6f+WVhve5+XHBk5+Os/MnaS1z3Df+NB0wfuoqv5/HBBHpwmMUUCeuUyBRDLsOJ0eyEoKJxI2CMFWGlhzLzKIy+UystwEKwcHB1E3jDOeAjdpJpVsgBt0D1bWzZf39eAdMJLskTTY5ndcG7aBn0bmQfy6Z/B/owfcIKeg07rvrRsfUu5SIFd6nxFHoMX8pNlU3tObIvI9Al0vzaUvSD6fD2fz8PAww7SjeSb9itC1UO453hjK/2QyCcfl2bNn2hEAMMgAACAASURBVNnZiUy8M9dSIIs/nDqJrKZz4fNAz65CoRC18oPBQPv7+5KkwWDwHvuIE0BwQnK5O3YVjjVz5/0MYAh4+RzPzdqhB2A7pE7Uj7Fl1snChxpp8sD/llZBNiAJ9oN5WiwWGQq+B6R8lqCdwIHPjMdjtdvtAMhx9ijPabfb4SyjVyld6vV6evfunbrdbgRe/X5fm5ubarVaEUh1u9339Ka0SiQRLHHsstvaVFfU6/UoY8vlcmq1Wmo2m3rz5o3evXsXJeOlUkmNRkP1ej1s+Gg0CqYzRxjncneUfcrjYDZ4pn93d1f1ej0ArNRX8f973y8HQtN3uW88lNxJ78seuorTd2BvwUKi3xHNbAk4Wc9+vx9NhYfDYSQ8Li8vNRqN9PLlS43H40yvKgACSZExLxaLajabUVYiKdhP2Ed0AwAM+2E4HGo8HmfKKmEWUHJWKpVC96VyyolQ+/v7cRgILQwA9CkXklYlnZubm+p0Our1ehlglX5kNHZG/k5PT6P5L4kqnoeE1mAwiCQBzHf8BGcRe5LAk1M/Nh5a7vB5t7e3VavVQpf5CXDofZcP5pUGxjc3NwF0Ux7bbrclSS9evFCj0dC7d+8icAUQpGwOmeL+6AzAlWKxqBcvXujs7EydTue9wB72ENehHIh2BLlcLnQQ704y0Fml+I3VajWASmz/v//7v8ccOCDgoAfgE6Aqz8580YsMH2RjY0O///3vNZ/PY1/zHJVKJWwELDL8FWkF+mFrAJrwg34sXnloucOHgdmPDsOHJWmArzSZTLS5ualqtarBYKBvvvlGW1tb2tvb02AwUKVSCQZ6q9UKWQCY7/f7wZI7PDyM/lWlUkm1Wi3D3AaMJJl4enoagKO3AMC3xN7gG9BnmM958saTnoDfnsB2ABfQBtuMjgMExddyxhsnd04mkwAvv//+e71+/VovX74MhjGMVBII9DsrlUrR5xAG9HA4DNvuDczxa9inuVwuYjHWOR0fOp79NY4HKX/z4RQ6NxIEz+nwDJ//n2un32Gzo7CoVcdZIMBDEbAhCDZwsDH+PK9nd+57T39OD2YcrPB/u4OVoqYeaKcgAp+VVkLPvVMgb91zcj1/XmeN+dw6oPFrHc6MQ5lKK3ZPavDXfd9ZTcwH80eN+nw+jyC4VCqFIfYMqLONYAiRDcjn84HWcy/+9n9L2X3ljCCXkXTNkBsy7syFyzry77KYsjr4HYHUxsZGBFFutLinP0f6TClQ5gYqBWh/TXLIe6RrkTIOAXUJdtBDyIID5PTkotkwlGJJsQ4OikLFR1dsb2+r0+lESS1ZS469xhkki5SuDT/DofBMqf/eB++C4+mlnGQ5oYnTeyWXy8WewXHL5/OR+ee6MAmcUXef3pWyp3uleu7H1uwxjnXP5g4bwwFagkecK393TyK4fsP5r1ar0bPEgzV+DpBFUE/GsNvthrygE29ublQul7W3t6fJZBL3WaevfO3QTTjLbiN94MwiU+PxOPo7tNttvXr1SuPxOEqNnj9/HqwpAIpKpRIMGfYJAC6NRPv9/nvPfZ8NdhYFezz1J9w3SkHmxzoIuNjnvDPgOck59AbOPuwI+mzx3swxfWpyuVyUX45Go9CV2Et8NXp7EcB4HzHkfXNzM8Brfj+dTtVutzOZdmlVnkygTY8QysZ9r7AnvFeHyymy4EdZO/hBgIgu3drayrC6RqNR9FNpNBrqdDoaj8fa3t4OMAkQbzKZhMz4NbHjboeQQ/cZXHYfm9zxXOg4wDRppR/cZ3aWHAPAlyoEAA3WliQ0ASdyjG1E90kKfw8mDrIPENntdtXpdN5jzPJ8FxcXajab4Y95eZ608hVcfnk/1hzwjNIs9DrAZrlc1mQyCeYecuHPwDsCkKSMeth8gBr009nZ2Ymj3Pk+33WQj+GJXI87XG881sFcwLxCpgClAdHQd5LipMVcLqdmsxlJjsViodPT0/DFAT6Q7WKxqHa7He0CptOp9vb2wi/Dpl5eXobcwD7ntGCIAtL78SPPKuk9uUt9JvwCYhnk2FszuC/L+2MT2EP4c5SnSQrgjdI2SjsHg4Hq9brq9XrspU6nEzJPQoDyX/xAmPfb29vq9/vBfPd347nZA7x7WlXx2/j540EbRqxz1t1Q/JRi8Y13H4IItZ4MlRuEFIxaB8T8GHjlDrg/O//37JUHKunfDiDxDNDBvbTA77HuZ2kQhNHx4x7XgW7r/p2+ZxpspZ97DOPnlr65syFlyxH5vf9unSxI2X44HnjBvPC1p+ltehIQjqIDR3yPMsh15XXOQvKBIfN3vQ+E8iwlLA1OF0Fu2Ie8G4CaB6XugHg/M9/f/gzpHKfycx8o8ViD+5+SO+TNWZP8nEHGB5aN73McZoB2DB69hTyox8BiMOfzudrtdjRIJOPlJU6uO3A+oe2neiodPCdZLn6WfobhIAeBGgE/jlGlUlG9Xo/3RaaROTJUaVPFp0+fRkNcvuPMUl8P/3cKJvt+d+bnffrvMQ4PtlIQk3d2XYFs+nDmopfNwYCj0SeONQE7uozgBRbKeDwOPUL/FgJ1jv2lDwg6yJvAr5MrArl1DrCkCP55B+5NiSjHfQPanpyc6OzsTGdnZ1F6RFnIbDaLZqG3t3dHkRO0k7V3mwy7xrPDrA1AOeuRgjCuL9zveIzDdZWz3dBZUrZ3lydx6Bc0Ho8lKf5PYIIcVCqVYAVzAunOzk5m/ph/SmM5oYi+XjxHsVgM/QjbaLFYRO8N9CjljL73YRbDPIKV6WsL8xxdTIAP+MWhBDwH/ivBH7IAY+Dm5iay/VtbW5leS5eXl/G8BPowofAjmRMCPJc99Cp+J3bl1yB3DNYotcPOvEKmWDtnm2MPsQGLxSIA7slkom63G6An/VxYJ/qyOcCCrBYKd32/ONHKgWMHu9g/o9EoGFN8lnXyJDt6nRI4r0agVQfAK6xBjmUHCMPnJPBG13IP9hPPgXxeXl6q1+tFfzJOEaOptPvSzD/989zPdRCWv5n/1D9/jPLHukgrf9z9Ff6WVuAZLLDDw0O1221Np1MNBoMM8Aww+ubNm+ivBOOxUqloNBrFnN7c3Oji4kKXl5dRHgbzdzweh87wJuJpbCOtEn2skR8+wXDfm/dzgDyNnxn0GsSOk5SRFKV6MNCn02mwlwHae72e+v1+xMKwL5kndBfvhk1g3gBSOcEwZXejI1nLNAH+2/h/H79I+dt9Qda64JGNlgZeOCQpWOQBrl8HYXZQhtNe2Ag4Jd7E21krADnQZ/keguhZ3tR55dn8Hf3Z14E5fB5U1VlJDj7453lmns0ZM9wPVFhSOO9uGHzOUuWN47MOWOF93YG/7/3WzcEvPdaVg6T/JsPjzWYZ7kSlNeX+twMsKM1qtapCoZA5uU9SZDGGw2HIM3Tt+Tx7KpAHwGR2dnd3M431UmOc/tsHz7oOkOQZvDQDQ4HThMNMQOWBAY6yO6P8m34COCQo+lSe/d/sXWTPQT7WJs3u/di7P5TcMVxeHKAjY+R18wSgDpzg+CKL7Gnq1qHV9/v9MJqsHQEL18I5psQnzcK4U5HP56NUxHsSudOzbg08qFqnF5AZ9okz2wgki8WiRqORpJXDsVzeMVpwmJ1dA/DlcgioAUjqfTYcoL/vOZl7d2xdFtftPx+PQe54NwJaZwotl8soy4Z14Q4V15CkRqORAXim02kEUchtPn9Xaktjd0rGF4uFvvvuO52enqrb7cZnCbpyuZw++uijCKy3trZ0cnKSWRMYQVDdU2DPZWGdXCJv5XI59CyOKWBDLpfT559/rtevXwfDBLmjFI/vdjqd0NmUIlSr1QAvtre3tb+/r16vF+VbBLK+Nm47kDdANUkZ/4fx2MuQGMw5Op/j2tFL6CPmsdVq6fb2NsBuL7sBRAFkBsiDyYGssP9hoVA24adekVDEpj1//ly1Wi3WAPAQ/wsb7ICzg7H4k5yYlc4P9pEm4LPZLIL9crkcZU2j0Sjui2y4vkdWAENgAXPK23g81kcffRSNexeLhRqNRqYBNHsDRirXcXDFdV4aFK5bZ8ZjkDt0BImJVIej83yd3R4AZMOMqFQqGg6H0VybUkgSbtgk/D3KONEbAOl7e3t6+vRp5gAD/K00fpjP7w4xuLm50enpqZ48eaKdnZ3oN+gss+VyGUxkko4822effRbyVCqVVK1WdXR0pCdPnmROwm61Wrq6utLr169Dz0uro+ql7KmH29vbUb55dXWlt2/fxoFCxWJR3377rZ4+fRoA2ng81v7+vjY3N3V6ehpxx8XFRYAW2BUSE9LKz3MAat146LgCmcN+IWPMPf6ynwS4WCxCH3zzzTcRo8JwlVa6v9PpaDgcajgcBiBZrVZ1cnISPnm321U+n9fx8XHoKUrgkC+AZPQtJWcO3uFXeiySxgquLxzwT/0HYlnuXS6Xg9yAjNHDyE8I5F4kF9rttt69e6evv/5aT58+1SeffKLFYhHMesrn8K0ps0N3TyYT/e53v4teVNhXkvs+1+g4Z8ff51N8SLn7tY4PVv62DlBypNeNmQMoP6ZY0uuyQQANnNZHFjylyHtA7Bub+6JQodkxUjbIunf0jHf683QucIx886Vgmd+P+eIzfJ6xs7Oj29vboECn13HAIQ3w/V3uCyL9Go9xrHuu1GkCpHBwLXXm73s/D8K9J4uDSWTenYXkDrB/34E6N7TOtvDygRQw8nf0db1vjVzeeB8vlyoUCmFoSqVSfIb3WBfkeA8Dz946GJaCDz8mZ+l78f7rAIHHJIcpIOt7Ff3DngcAR27S/eeAjqSM80fGBqcWhw9nFH3nJRussZRtdOwlKTixOCCAAeneWDfWATUETARK0JY5ol5SlJ9sbGxEzwnmCTALYMqdpVwup06no2KxGM0pe71eBLA/l+3BNZ2Z4M5XmjB4TPLGSIHm1M45IJaW7zp4SPDsJUueuUR/dTqdyHQTuMMKwjmDNecJD0CGy8vL6HfAz9FDOLiehfThSRn/WTofrt+QXQLQyWSiXq+nVqulxWIRh3IQAJBFheHnZfBcnxISaVU6IGV7leB8I48OIHjSKi3b9DW67x0feqxLuvCO/r4eoHpWfzAYZMqXPLkhrZr039zcqFQqxclpnALkbADYYl5ix3p51v7TTz9Vu93WcrlqEEvpRblcjqCHgCMFMwnaAPh5T9aGMrdcLhflUK6bsaeVSkVbW1saj8eZUibAJEBV3od7ISdci/45XrrJ/MFSwB57gJiuG7bKdXzK9nlsI93/6Kt1dgg7iO2kF5v3LgOIZw9STujf49ocHuG6lcCaBv/8HBCak6XfvHkTtozkR6vV0mw20+npaSRb+K600g/IgCcg8/l8NHDnniQPaFpMUmA2m2k0GgWzant7OwJ8aQXmp4AsYAnMUOwy9tZbPGxs3DU7L5fLkhT9ydyWu+6D7cp6uX58jMNtKz6T2yl0j8cH+NwwD/f29uKz2D5JwayESX5ychLfBwgEoEY+09N6fS2djUiyDdvizCR0mINo6c95P9Yml1sd8CKtDlgBDK1UKuHP4VN4skHKkjHwNWGkAnLS58z9YO6JXanX67E32Ts04q5Wq9GE3HsdewKSd03LTn8b/2/jF2Eq/Vjmnn8TgJPB900qKbJO94EDDgzgjOAskiXDobm+vo5GhdKKLitlnTRqPFMjg4HZ3d0NgAnjxeccAErf1x2r1EEB2c3lchG44ZD64PrpfdJ/8wcgaTgcZjIB/jy8uwcLzghxB9iHf/6nNt5DZ7L82cnag267YcOJdMO3Tka4phtDKJlkr3A4yYBJyhhnzx744Pcovs3NzWBxODPAA7x1oFIazK/7HNdyOrSXkWJ4oPjjaKUA8LprX19fB0twd3c3MqQeZPh1eBcaQHpAImXljM+vA6l8PBbGiKSg7nqjQj8NLy1vg4nkQAeOC84GjkQ+nw/nlhKj4XCYOeUH2XMdi86lZBEGh6+J698UKLxvOACTAoWABf1+P+roUzCf73gPBhikHFG+LkCfz+9OHCPrtbu7mwHCUv2bgpt83ns+ObDEYE7vC7AeWt9J2T6CrKm0sm/scz+BiHkgcEH23JGTFP0QOA4YGwk7I5/PZ45B5zvo2HK5HOydy8vLKH3keHTAJtdzBOkO5DNYj3QeuHd6oo37CmSZv//+e/3ud7+LdyEQB1h1logk1Wq1yPqfnZ1F/xUYqX/605+Uy+WCnUqCi+chgGJvc5hDCmSmeu7H9t5jkDsv8WAPIXPYkOVyqcFgELIHGEKj1MVioVqtpkajEWVAnJTkmWb8G4IL7JUzPNE3t7e3arVaEUR//PHH6vf7wYYkICfYQe5ZPwebeU8HWt2W+R6k/MlZqDAxl8tlnAo7nU7V7/eDkSmtQEl/F090Egh9+umnms/nGo1G0a8EMBT/w0vcYbVQksozO/Dp/vi6hJCPh2aMeAKZxsHoCQ6C4Lv4JezXXq+nWq2mXq8XzCVOgkQ+0KPYFe6VglJXV1dRvoYsObMW9natVtOLFy/i9MJPPvlEX375pT755JOQz6OjI11cXET/JcBPB7A9WQLbBV8NltrFxYUqlYrevn0bTYz5GzDLT3r1hI1XK3gilHJBmkPn83n98MMPoe9ns1mcPEv55unpqSaTSdh9ADbYVjSs933mvbHWjYeWO3wFeloCDALGeWnicnl3aAA2J5/Pq9frqVKpBJOpVCppNpvp3bt3khS2hzlnP3vvt8vLS719+zbDOpZW+5R7k0j0Emu3zd5XOAVp8Qk8AcrveL5Wq6XPPvtMpVJJZ2dnajab+ud//md98cUXGUCJRFOlUpGk0Hfuo3mcSlP7fr8ff1PWzP3pHeXJKHTl8+fPI56lDBSwy/0I93Pxm13v+fgNaPrp8cEbdUvKCPa64NQz0YwUsEkdewytG8R8/o42jKCtu4+0Cvg9W8TnMCA4EgRiLlzp86T/T5/VwRyCNQ8Wcbrvy9CmDqYHQLwPJQMYw83NzQywti4wSgMvv57PmzvF6Ts9tuHv6YyRdM74bNoLKf0330NZkQl1IGSxWITz6NcguMGh9mvxWZ6TsjmcR6cE/xSglIKF6Tzwf+Qag+dgmjP8UplI584DNj6LA8e10v3gmV03gr5O697DwWIPvh7j8PX1v33MZqvjgVlr1t+/g5Ejy+JZRLLz0PUpWeL6XuYrva9n3eEgG0bJJUwnPr/u/bimr1cqH+4E47wjL5VK5b3TRnDYvb9IPp/PgFF+P3Ret9tVo9EIYNcdJu9LkdodP3kwZaH6HvUMWfrej2XkctlTQF2/sGeQCd6H/S+tmp5jN92OLJfZAwXQZwB7yB8DGQO8dnYHMk8gSF8FvpcmblL9lr5zKn/oc2ezSMoEL8ViMe5LadLJyUnsS2mViWZu/ETB2WymTqcTn/PT4ZBL5J65Z97Yd+6b8C6sEQFBmkx4LMP3kfdhccfdnX5nvTiI5k3fNzY2IkiG0Qggjz7y+URWkEmCQG/evrGxEUCUZ8k7nU6wRwDl6YnoPTvwoVg3QHzp/SbXUrZ0CLCLEqLvvvtOjUYjnrFerwcAxLp741iuyfWRn93dXZ2enkbZB71JaCzN3NCfhJ87g98z8x7YM7fr/N3HNNzfd3uZJmyklV9MmRvsMdf5BwcHKhaLms1m0UdJytoYZAm2DzrGYwjsyf7+fjCGi8WiBoOBxuOxvvjiC02nU9XrdeVyuQzIju8PEMY7YQOdjecsDRgjlEcNBgO9e/cuytEuLy91eHioarWqyWSiTqcTZUiw56SVnKXNnZkLTlwlGeW9lihNRZ9LK+Ye8p36DOuSAsjdY7Wvrp8drEFHOwkAO+o+xnK5DB3k7C9vzcK7U+LIn9lslgGX0kQLsuLgCMkLWruQkIQJSWyCbqRMEv9JUtzb4w8+s7e3p2KxqP/5n/9Rv98PBjKgGSX4sK+QcwAigLGDgwM9e/YsToQlRuGex8fHarVaqtVqurq6CiAZmb29vVWlUonTaInRXP5ct0krv8D9htRP/238/PGLN+pOA3fpfVApRYLdmDPuA0H4nQcELixpgJA6Z2xgNzx+P06yQRHQ28EdQwcb7gOU0gCMPzgD19fXury8zJya5U6yA0zrAlQ3+mwakHOOYGQwJzgL/uxpIJsCGOnape/0WMa6OXcHlz/8Lv3uz7m+pGBIOAjDKQ1p4Io8umz7WqfKmnXK5XJhSFJmgQ+MSLpm69aG5yHDLmUbyzv935+D/XqfbOD0cnQ4NdLrMp/p85GdSp/Xg2D+n8r/Y3M8GN7bId0zzJWUde75HvuYQaBbKpWirwvXgR3iJTruDCAvHiRwf7LXMAoIUnAAXNf5uG+frJM1QAWCK3pA8Ht638zndz242u22crlc9L/weXE5cACF5+T5nUlw33PipHNNB8B8ztbpjcc6UgCPfYnz5npeWjEId3d3A/De2Fg1+KW0ARtLFtXZbcgxTmc6h2R2HQhF99Bbwin5qS5IbSy/83Xz/cXnyaZybcCybrcbOrBcLms4HAYbgIDfHXKXIeZGUjR2JuBzneqnHnFv9hR723vnpH6Qr5MHGo/JzvrwZ3PQ2wMTBiAGnwfYg3XDqT8XFxfBAoEd56CVBwkOYgH4LZd37LNerxeBEgEcTYYJgJFpTqB0O+VM5lQfInuub7D13sweoBy25mAwiF6ayIkDCL7+Pn/IH0Eep4rxGVj+yJf/qVarGX3gQXGqW/3d03K5hx6pTicp66xUBzFI1CwWiyirIYFCgA8bDlkYjUYhSyR0uFcul4ueXT6PMKGKxaKk1SmsnC75+vVr/e1vf1O329X+/n70p5tOp8rn86FPqTDwMh6YbzCNpBVTvt1ux7qiU7j+06dP9fnnn+vi4iLeaWdnR7u7uxoOh9rb2wsAHaCEOWSuAZkAR9BvhUJBzWZT1WpV3W5XZ2dnms1m6vV68cf9RLe1ALNuZ3kG13uPcfDM6Dh8GQd9eSdOiJQUzagBqM/Pz3V4eBgMXvZZmnT2/Yo+IPkHIORJIZhi6B1Ax6dPn8ZBARwaQMknex0gx0seYVu6TLD+rPvGxkacsDaZTHR2dhblzcgx9nI6nWaemXem3xg9xLCh7F+YzIvFHaO1Xq9rOBxG3yr29M7Ojk5OTjI+J2vgwJgDci6fj0XP/RrHL1L+5puD4YvkGRN30FhMz1p78O6Kxo3ecrmM7DRBCYKJkDLc+XTl5fdzhQD678EyjJF175cGuil44L/zz+P8EOS508TvnSKezkHqhPJ+INKTySScFhSKB7XMPwAW//fBczmL4seCNmThQ40fK7v0rAKfS2m+vnbpc6cgEddzyj/oulPxPShFQadBHdRMHCP2hrNWnJbJs/q8p8FWCnL6OzAPaaBJkIhMeB23lG3A7wGjz9E6GeffgBkYYp9n9jUZFt+bfJ/94JnW+7IKDyl3rs8w7DhtHqQScPGu29vbwc65vb0NejB7lswSxpdGwZyyxbx5AO3zxH2duYERRfZcfxYKhQCm6Y3j5cbrxjrgiWfCKd/c3IwSDL6Dw9BoNKKHCv0YCoWCGo1GsER4BkaaVffMcb/fV7FYDMfEwQrmgnf0a3Bdn690fdfpvoeSO9/7NK7EyeIdKO1O95frc7edzBdyh3zW6/WMDSIYZy4chOEZ9/b2Qi8uFosoC5pMJnHcNmWy7jin1H5pfY+hVBf573kvmAY8cy6Xi/KrarWqSqWiTz75JMqtxuNx6KyUOeiBK4yHarWqXC4XWX/KDykDYR8jg5zeKK1kON2v0qoUivdMy6b5/oca6/Qd+3tjYyMOR4HhBtC7WCyiqbuXRLovAujiv4cZwml7vsdZF3xK1gT5PDg4CBB+uVxGgFcoFDQcDvXixYso46F0iVOXHCCSsjbI5Q7whnVwoKtYLGp3dzcCHZpqUw4Fc0VaJXWq1aqk1bo7Y83908Viod/97nfv+bmegPQ+dviysNjJ9LsPhI/oQRfv+JjkjudFxwG6oM953nK5HEA5QW6/3w+mETa62WwGiDkej/X69WuVSqVMwE0g7evrjEZkE93baDTCpvJsAED1el3z+VydTkfffPONTk5OVK/XM4zao6MjdTqd8C+9HPzy8jL8xoODg/CrnN05GAx0fX0dfVW///575XJ3Jy2enZ2pUqno9vZW+/v7KhQK8fzOnsRPcRAhn8+r3+/HZwEnxuNxlDg5oA9b2n0djzH4ndt1t9P+b8ZDyJ3bWPwXmsNjFxyU8Fh1d3c3ypw7nU6U5U4mkzjYghgNdk96iI8nbhjoTp6LefHkD/rp4OBA+/v7wa7D7rVaLbXbbRWLRQ2Hw4x/48kP9C3vxF7ATy0U7g4maLfbms/nOj4+jmbjgFqUQeOj8Pw862Aw0NnZWZQBFotF9fv9AKF4z6urqzjAYTQa6e3btxkWK8mIb7/9VldXVxkgC1mjCsmJJZ6M8EMKfB1+Gz8+fhFQSbo/0GLjORIqrT95y4MX/7c3rPOsO44NaCuovH/Xg2/uiwPrmVvuuY49kTq5KfiSBvv+M7+3A0GSosQgn89HSRIOO86AAwTp/KbgCBlfB8FwbH8sYPLrOHjg13XH+rGASimY6e+RGjXWDOPp74hhX3edNKBcLBYZRcY178v4uUMKqEXZBadubW5uRl8Pvwf3ve+Z0udd929YKTgqOCEu+2QIWGecolQO0nukQDDXA6jwzL87P1K2CXj6Th7A+t5cNx/+nQ811skcP0+BI8++rctEof+8jG02m2WOKubUFZxZZEVSZGbQUX4PadWQ3U8BYf3T8gcHTrnX1dVV5h1THZ3OC3qZ6/hapkAXxhzQgjnh9zy3/zx1qJzNwbtyHxyGdfMP4CWtmJx8j2dOS0MeY5CFnuOd2GcelErZvoLIm+9NSaHXCJhdV3rfQdYHfeagKfqG3moOHI/H49BrDgR4mRTZbJetNFHj683PU71LQ3icdmdkFQoFffTRR9F8/N27d5rPIkhXSgAAIABJREFU51EGhSwSoLNHXfYARb3MiMCd3wM24dzCamD+HKQiibYOQEtBVenh5c7LO7yXSNoHZrFYxIlknh13neC2Kd3jADXOREz9SA+kCOQ41WtnZ0dnZ2dxrcPDQ0mKcg2C7pThvg4wZS5S3wK9gawzP6PRKNgsyAQlecjo3t5eyAI6xpMAqa/abDYDtINFz5z5nAIKk7GnRNNP43R9zBq7H8S/Hzq492fwfm7oDRi3kqLh9cbGhk5PT4MBgX3EF7q5uVG/3w9wc7FYxCmG7uOSoPC2APweMGlzc1PNZlOVSkXffPONfvjhB7179043NzdxKMBf/vKXKAF68+aNlsulDg8Pg7FXr9eDuetlxYC1yNHu7q7a7XboFhglhUJBJycn6vV6+vLLLyVJb9++1WKxCOBgOp1Gjx8SNq7H/d1yuVycMksCJmVNEbhLCjuAL+12yWNA7uPJDd6DdXZbw3hIucvlclGmS4zmCTNPJgIk0k9puVyq2+2GT8VeWy6X6vf7mUbrbgulu/1HuZj7JK4HkZNKpRI9urC14/FY0+lUnU5HL1++1PX1tSaTSVTioENI/rAXPEZ2X49nA5BnT+3t7alUKun09FTj8TiSkuwdEizYZMolXc+iL6nQQBey96bTqdrttra3tzUYDILhSoKHPQ2TinJB5ob5Rdfyf2/LQCL/ofTdr3V8cFAJJ9Xrj/k8QYc7TWmwKClzFCUOLw4qG2s4HK4N7N3oOkjCs6EEcZD4rAcdZN3S91vHHkqDYSnb6NqzT55VBvFn+Abm+ilY5oG2v6NnSnwOvKzJn9mDBxy+9J6800+xlT70JkzlzjMhGALmhPeT7t4NtJyMkJQFLfiOl2swHxg+z064EiZgdyWWBiW5XC6orAQ8OC+eCb0PUEzlIZUvMpZeduQBF+/s9GbkxNd8ndy5I+3PxLNz6ogfEZ4CSDyPg3L83NfTr8+cpOOhwExfb/QULB/0iINL7vy7zHn/rXa7HU4fmW2CDxxM1tcd0DToYn494wlYhEPh7AgHV/gupSPrdCt/uzxKijlg79FAFdDCAzF6NUh3R88SFLRarWiw6oC438+zvNIK/KcvS61WixIUnsuDYRxbnzNnyLIfnJXD/LgsfKhxX+be+7z5GkjKACP+/gAdy+Uyc6ogn6lUKsrn89GUFJ2FfkoDhOVyGaUdsD5wBm9vb1Wr1TLP4mAhc0jTWWd3MlJnz3/vzALen/W9ubmJU2IAt9g3nnx5/vy5ms2mOp1O5rqu41zP887sPdh2zMtwONTl5WXMhaQI6Hl+5Mr9EP4P2ORO/WOSOw9OeXYHsPnDc6ODAD5ZHw54kBSlgjCL6P3hJWjOPMZWsbbYOeZ/OBxqOp3qyy+/jDU8OzsLoIvSX0AlAArKP2GeARTy7q4/CKD8OZmzJ0+exKl1Z2dnms/nevbsWZwwuLm5GewB/DWfG9eTXHM2m8WzM+fIHPItKRie3uSc49+5vvuMDuq7b+H+i/SwcrdcrspqPeFKyTTJGIDO8/Pz0D/4edPpNMq0YJ0AAGOj0E/sP8DKQqGQ6ddaKpVCnv/617/q+++/j15JNE+nd9fz58+j/LJcLmtnZ0dHR0dqNpvBWKLPVrPZVKlUipiG8nFA0m+++UZv3rxRpVJRrVbT/v6+3r17p+l0qp2dHb169Urn5+fRXLxWqymfz8d9AR2m06kKhULIbi6Xi4MUmGP2YLPZjPWAKZ0ykJ1lB1CMLoPVSI9I1g55giErre8j+5BMJWwmgBr7Yj6fR7P0wWCgZrOpyWQSNmNjY0PfffedJpOJjo6OIo68urrSu3fv4p3cPiN/xLr4ze7j4QfNZjM1m81gwsGIZG3pt7azs6NarRa9wwAfAfJ83llz7024sXHXFB/9y2FTNA+HWVQsFuMERJqzl8tlPXv2TI1GI/qZsXdpeJ/P56MnK+xqBz63trZUr9djL8xms3ifXq8Xc8rzLBaLDGDWaDSCdc21Aa68BQhy+VBy92sdHwRU8oADBeMOEhtIUsaxSwNlBkEa1FOnh1OG5E7YusAn/duDBe7pTh2sH0nhVLuDlzq46/723zvIBpiAUWs0GmEQPKDnXs7OciDJAyzeCcdkd3c3SuHWZab8eymF098vBcT8/g8d3Evvyx3KyMEe/9szjw7yeBaKn+F8IX8E2amMeUCTrsc6QMgz4Q5M8gw4iV5+dt+1GP5ebgwdnEqdUDfkOB2wGDwbzLV4jpT5kT6PZz/JYrsjkYIqrg/uC94d8Hhoxoj0vuPhVHHkxT+Hc4Vhdplz4IQABdYDOshBbrJb6Cnp/ebmDvLxN5ks+ri5vgRYSPUDpZAOmPp7r9N563QJDgIBINk9TtzhfQCaNjc3dX5+Hs+WsjXu22s40vyfuWT+0nI/l2e/DuvhsuaOFuOhg3s/mthPjPSkTQrMkqHDqeRdAYVYBwJXBk4tgRYDmcbho/kn+oUeD2dnZzHn6ATXMzjTyIgzmPy9U91LRp31cxDVmSX4CcgDAdDl5aU2NzdVr9cD1EBOuIczidyxZ//e3NzEEeSTySTTNNqTOZS1OCDi+p/5cMY0n38swb2kjE0EqOb9HOBmTjgtKf1DIiUNYhaLRciigyAOtAAWYEdvb2+DiQRQjb4bDAaaTqfa39/X1tZWHKxxdXUVYPTGxkYwxj0R42ARMuXgtCfivOE26/bpp58GoJDL5aIhOQFftVrNJLcAPaX3e4BIygR9+Dvsa2QTXYjvSuklviDvha7GNwD4B3Dnc4yHZowAGrldZU+hd9hHlB25reDfHtiSbHE5Q79h1/H9YKe73h2NRiFPDrATJANiwhjimtPpNBJ8r1690g8//BAAASCTdAdeVavV2EsA751OR91uV91uN9Z0Z2cnWJmcIHZ0dBSxhjNU2XfIB7IEAIScO+touVxG6SV701kp+Xw+dDFyBeOEuMd7AaU+5H1+3kPKHT4dPgT6hISFA+DoE+aVgwEob1sulzo+Pg5/G/8HnQMDaN17s7+RTU6T4/v0L4IZVS6X9eTJE+VyuZBR982cncRzpH4tsSQ9oIhTXV54f+QFdhX7Eplg+El36KDb21tVq9VIdhEfYwfwy/gs8n5zcxOJT2cbeZKgUqnEfkvLBLHjnrjw8Ruo9NPjg5z+hqJA6TgTwYNHD6gdxPDg2A0BgQlHdbpAuXOaKipHvt05ccPP/Qg21tHRGf7zdUHVuu9wbzYj2XuUAY6CgyD+zCkYsu5+Tj3lHZh7gAKfV39uz8avA/b8+h7M3fe+DzF8XdP5clAz/c460E1aZWMxwGQRUMDpfRnr5MODXBQfpyNw+gfMHhSi9yJLe4X5tbl++jPmwvejtMooSasa7ZRZ5z/DyXenPv23D+QZFiF7NN1n/pwepDmTcB3Y95iGzy1r5frGnXcCTJwshpe/oI9wdLvdbvQIkVY9JVKd5sOZVP45nBoCKH8HvwbPge5gDVL96e+f3t+vhW7DSeD6ZOLy+bza7bbevHkTzhD70ctB/Hld/vznMCU4TrZer2cOXnBmrLNBXeb4m2clwH9MDobbBdbT2Q7S6h2QKZI70qqBprRq9EkmUFrpDml1ehq6MrVPfJ8srfcD4Rm73W5m7hkuy9hwzwqzX3iX1I7zLACTGxsbkaWFYUC5Ajp1Y+Ou99bOzo6azaYWi4W63a6Wy6VarZYkBbvDdZOXlOPE8vzj8TgTrLHXdnd34/NkY6UsyC9lT93EWQfsSIG1hx6pr8Uaofv8c6wJPgi90mC0TSaTeD8Hz7whPDYKAMoZvehJgrKLi4sMmLm5uRlMpFwup0qlEmUWUtb2cE/WwO0ltomGuOt6juzs7ERJEWDF+fm5/umf/klHR0fqdrsaDAZqtVra29vT6elp9DupVqtR5kew73LP3JKAQDYckGQdHNSTso18HRD15Cx+ndv6NLB/6OF6J02oIDf4vwzmh+868O6NqL3PjTN3pFXfKRgg2Ovt7W31ej0NBoOQHRgaR0dHOjk50eXlZQTznryVVj2QONUPdj176enTp+r3+yqVSqEP6Iu1vb2t0Wik+XyuyWQSgTPg13w+18HBgSaTiSaTif7xH/9Rp6enIfu5XE5PnjzJnISJ3mJQYoc8o0PZfwwP5p3Bivz4wQnsI3QDPi+/I9n5mPw8Tyx4DMR7O+NNugMZd3Z2NJlMApD53//937BFhcLdCcwA89huZIFEXhqDYjv5P3oIn2c8HqvT6WSYxuPxOPws5LZcLodP2ev1Agjyag6ea3NzU7VaLRhZ6CgON7i9vc30EpQUQCMns0mKk994Jp9DDqFJWeJbW1vvNcfncA33c3h/2IEMj92YP+bQS/zRGehYb0Xy2/jp8cHK3xzF9AAnzQ5j5BAAz7KjZDjliOCfLA8nCrnSckObGhQE5fb2NmpP+RlKletCy3NjIK0cbEaq/O5ThiC+ZC8wgigryltqtVo4KGw4z4SlgI7fE8cChY1xgR5MFixdM3emHHxw5z0NJnjudONx7w81UgcCIMazKw7KuYHAMUTR+xy7YoXemsvlwjB4YOuBqMsMsu7Zxnw+r2azmen9wGfdwPha8o4OvPCcPlKQD6OAA4XDgsIvlUpqtVqaz+/qk5ETdzx5/hSoWwec8Yys/2AwyJQJorh5NknRbyIFnQkoXA94qVPKnPnQQZcDtA4W+/pJ2Wwc8+cA3Tpdcn19HSdcPHv2LBzonZ2d6MWV9rtIAUbWBhlHd5LZx9GA/n5xcZGRNdY3ZZOsGzgBMF2QFbJqGHACPRo0j0YjPX36VMPhMJ5huVydbNdoNKIkIE0cuB5yOfSAbnd3N9MvxYFO5NEDB9bKs/08uwfNrvM+pNy5I4WuIyiCLYKOxvnls9JKN7sjB5hEJg/76Bk9dBGHC/g7ez8hD6y4PgwhvuMMC0As9AINnXFcfe+7Xkl1ubOiHKxHT5M5rVQqGTl68uSJ6vV6sIVpFurgo4Nrfm8+h41Ersbjsa6vr6PkzjPvrEEaYPmaASq4j+Dgnuu/DzX8/bGr2DbWD5BYUgAraXLGWY/eSNX3IrLsDDPf58w//26326GnPIFBuQa+4nK5DLt3cnLyXsDbbDYDeEHnwYohoSTdlTB6OS/21Eul2HfM0zfffBMywXfG47EODw+jFwnzQcN4T6K47wmYhI51UNaBB+4NOOXgkScwUx+DAA3GUgpoPrRvhz/jCQFnkY1GIw2Hw5A1Srz4TrlcVr1ej1Px3O8jGIaps7GxoVqtFj475ej5/B3zolwuq9PphP9IwF4oFOLACHQgsQo+GInJ5XKp0WikP/7xj9rYuGtQ3+l0dHFxoUajEQyPwWCgyWSijY0NVavVaPxNLIPvyJ/ZbKbhcBglcp1OJ8CpWq2mSqWiy8tLnZ+f6/LyUv/6r/+qXC6nwWAQ90BX42+Mx2MNh0MNBoOQI5L8JycnAVBNJhNdX18Hu2W5XMa/HSidTqcBIsFaBmgCpGI8lNxJCrDP47Lt7e0oJ+t2u+r3+7q8vIyyS/bzxsaGjo+Pg83a6XT07NmzjL558uSJzs/PM34h9gtb4ToRXYNtZi7Zyw5ES4oysMXijjFHGR4288mTJ9rY2NDz588DKJPu+rf9x3/8RxymcnR0FIdZkKTkOqw7oA4HBZycnMRBCLlcLkrEnVUo3dkIkusw1Vl/ehFWKpXwEzk5Hf2LnHMPgE36Fr979y5AL+J85hrfbzgcZsBS6XElEh/r+KCgEpsAQV8HXHgAK62ADM+QOA0eg8jwTZACLn5Pfu/0Xn62sXF3DCNoKgbJM1YEi2mH+PS5eaY0+E+dfx+c7LC7u6tarRYNFqFL4yin2RmGO7l+fDGIP1kMGCROx8cR8mul75QG8Clyno6HMgAEtzjongHxz0jZpux8xkGU+XyeOZWFprOAjy7X64AeQAB3XJnbarWqUqkUAQhGggCoWCxGppsBPZ5n9/vdBy6lIAfXg+XHXprP57q4uMjUSvPMOG7u3K+7lw/kEOAK4+tMivl8nqHErpMvf1fm2VkTLmcPBWayt32uWRPWPNVBrnvIcDlbw2VLUpSr8XnP5KX6jr8Bc5wxAkuCn/u+Ri85aIJuQPc4gMNAz5Ot8rIQD/74g+4BZAeAcF1zcHCgra2tyGh5KUr6fKmseOBN/wpJmZJOZChlLyJXDvRJKwAU2XW98VBgJvPswQRz5YkAb0TpASSlFQ5osNbb29sZ5g2OGwG360rKWwH0ACp9n+fzd6dynZ+fZ/pvSCsAhyw578WzeYmOry1y530ueAecdQ+2eWbuBaj6/PlzjUajAKK4x2QyiWumAHc+n8/IgDvz+Bgkwth3ZEz9+ynQ5jqFNfbkU+r3fKjhQFwKxnq23X001oQSH8AK7DOBJ+9H0EEPOvcZPRhlDQiymAf+3tnZUaPRiH8jAwSuANrY9Jubm/CP3DdqNpuxj5DNxWIRTCv2CnvE9wTMKUaqd3O5nOr1uq6uruLQjoODA+3u7kbySlqxh5APbLW00vteMuMlYARTvJcDzfT54TrufzCP7n+7vXlI3473lVYMa+TRS8aZBwBuB5thhuGf8K7IGfOyWCyijxGtJGBD0Kvv1atXGg6HKhQKASaNRqMAjCijrVQqcQS6l+N5cL21tZU5uCWXy6lWq0lasX1hjbAPx+NxJkHCOwCyc9IloLykYD9vbt6dDuYlRxsbG7EnmBf2D2AETd+dRUN/GsA49qu06pVEPMP3HFAmecMeQ98+BlCJufbki5fq5vOrMrZKpZLR/YVCIXpsIb/1el1/+MMfQr9QBjybzcKW+WnozIe3Cmi1WiHXnLKGboF1xvOiF9BjzGmpVIpE0dHRkebzeYCNnI7IKYOTySR0TLPZ1Pfff69GoxG+q/u9gNqQMprNZshMu90O5hZ/038M2S0UCqrVanHNYrEY4CpJAmTx8vIy7AhyD3DGHsP2wJRHD6SYQC6XW1sN8huo9NPjg/VUcpYSzhGBhgdVnjXxIMGZICgdbzDqNb5S9qQa/vaAgWw3qDPH3xLcgJgTvHNfd9AxAjh5KcsgBRb83zgiPKc7yDg9i8VdJ/1CoaDBYKCrq6tMaYxTQ9MgnICKjLqj2VAtoRLy3HwuDRj9/zjinhlmrdNsAuOhgnuCad4LeeO53TFCHpgPD1YduGO9MAwECmQ9XW5TGcZQQpH1+2Jk074FvEMa4K4DE1Pwz50V33/p+2MUl8u7U2RYbxx6Ak7m1HtmuCwwZ/7uzCegFb0cMILOGgF84L39vTzTwvU9uOcaPh5C7jxzn+okAm4+x37hD04AgT+yAXWadcDR9caKHuD68+B8EnBhUHFYAFpSPQA7RFrJE/uHzwAaOUUecMZPtZKUYSh5ILRYLDJMFNhx4/FYBwcHGg6H2t/fj32Go4se5DrpPmAuYEQg2xx/S1DpQboHXeh46f0+JlwX5/mhgntptc6wlChtYX484HfZYL4IPijv4thx3gWZTUsWAMhdJ/nf3NOD7VKppNvbW718+VKVSkUnJyeZEhzkHUcU+eKeOOXYKAcXSqVS9JNgPrzPCYGZ34tnxR+ZTqcaDAb6l3/5F3333Xf64x//mAl4SCq4c++D+WYvw2DhGgS7MKS8kbfT+l0/u9yhx3HQvanoQ8gdOtjZr9gM/A0Hvekv4o2sJQUThiQXa+L+CHrUS80dnCZhhC8IeEwgVK1WNRgMoo8NCRN63wBY02zZE3Hlcjl0kLQ6AAD2I/JOeRAZdgJq6S54J/MNaOVAK0wOyooA0kejUTBPCI4kZcAO968BEJB1bwLuwTrgJux1B+7chqMD8ElTAPWhfDv8X0BnZ6Sjk5Al5gVmFz5Mq9VSv9+PMhn2kydrkUn8IewY8ixJrVYrGG/IHnueRJqXEwM8EOCn7wWLCX2Ajtjb24uAN5e76ydFgi6fvyspxq65X+4JHUDEUqkUTFAHL2CffvXVV3Hf8XgcMsB8AGAxnwAhgHg+V8gOMk8y3fvEMffoFWc58r2HljuetVAoZHoN0sICfV4ul9VqtbS7uxt7HgAHPzifz6tarardbms+n2s4HGo0GoWvQvWCJPX7/fDJADqYE0BRQJnNzc14FlhC+ASsMXYWv79Wq2lnZ0e9Xk9/+tOfwmeiFyD6mMQS9nAymajRaOjNmzdaLBaq1+sBoBErEXNQIvfxxx8HW7nX62k2WzXTXy6XAcJ6OVytVtNyuQxGIe/O6XW9Xi9zX+wziSHv+YXswVwlscHzUioPuJTGWb+BSj89PgioxMYjuHHgwoN4rxv3wNyDckCfQqGgy8vLoNjv7++H4LiT78EuziQGwjNVLnDj8TiMLQbaA3KGo9MOUKSgTAoysEnZbFzHPwcgdHt7q8lkokLhrhwBYcfJd4ZLalSZM8pQCMZGo1EEEBghSQFkOeCXAns4Uw66cC9nzvh4qODea4yl9Swa3o9sdfq+yKh0l628uLjQeDwOUIgg2A1iykwDGBqNRuHQ4iDiGHBygQc7GNuLi4vMUe7cC3mFDppmG/k5Te7YPx5cuQxLq34+t7e3evr0qY6OjkJecMTJYjBvvC/zxUBGKDfBsOBMu3HEQKc6IZUlnhNZBJxZx5J7CLlDHzk9GcDMB0E8jgbgtWfm+D9gkpf2AgShT1LZZr5zuZyazWaG0cl3qa/HwfCAhQwlxjYFDjwxgCMqSY1G472TEXk+DwKl7BHZPPPNzY0ODg50cHCger0emaZmsxlzKil0IfqK4TINSAf47j1OnD3B95315qwQ1+M4GrxTCqQ/BEPOAWBOQ0oBf2wrtgXgDvtHUE+ZFjaEo4hJvhBoeGbawXNkieBHuguy6VX0/PlzFQp3x11jbwigJGUcYYJc1kJa2RbsGk25KeVAf3pzfA8Q02OM0aPoN/bNy5cvNR6Ptb+/HzYWZ5pG3uhZ1/fIjpfp0wgc55UADHkDHPbsdwpuElC5j+M676HkDn1HY15kAGCTUhl/foL8nZ2d6ANDNppeNlwDwJmyaPSV6xDmCt3z5s0b7e3t6dmzZ5rNZnrx4oW++uorTSaTaLydy+U0Ho81GAx0cXGher0ewRVrcHt7q2azqcPDQy0Wi+iFc319rf39/Xi2drsd8k1yCLkliHM76KV5R0dHqlQqWi7vGvYeHx/r448/jnf461//GjbeQSJJAYIRvF9eXgab3efG9S7BGKzgfr8fPig22Zmo/jsCf7f5aSLnlxw8B/vOYwpA2slkEsEviQ1Ys9i4XG7VtmCxuCuNpKwNIJTPud8lrfzFbrerTqejp0+fqlwuR4nT1tZW9OkCbEU+CfwlqdfrxX5Hd9zc3MQp1o1GQ+PxWLlcTo1GIwL2q6srjUajOBHW9Q6lQBcXF5kKCNaVBA4yent7Gz2VptOpvv/+++jz1ev1VKvV1G63dXJyEoe25HK5KDdyeULOpBWgz3NNJpPww8vlcsg7AT1zxfHzrlMBMT2J86HlLo1lYb/6ujq5wA9AGQ6HwfyHpID+okH/69evo5yRPkiwuGq1WvRi2t/ffy+Rms/fHWRCaeX5+XmsH/YH+wW4wnrVarXwDefzub744ov3+hAB5mxsbKjRaOjly5dqtVqqVCrRqP4Pf/iDPvnkk7BnjUYj/HKuAfhL7NRoNPTq1St1Oh0dHx/r7OxMZ2dnqtfrodOoFPrss890cHCgVqsVJW7z+Vx///vf4zPgCvgBgMjeTxE7xT7s9XoB/rq/jj8uZROgPu+/jfvHLw4qoRi8XMs3KZ+RlDFgKajkzr8HYWQ/q9VqCJt3y8dJdCozVGDux/URztns7mhGsoL+PI6gSgol6H0FPBhGCZJ1A+jwYNo/K62adu7t7Um6Y8VwqoAbd+aW73v3fGkFTEBJhFEAWyFdB5/nFEDj3/7uKcDG/KYb7yGCe+aY9UllL80O4Sg5qIYzSObl5uYmjjkna14qlSKI9uACZ8KDLXcAcN7I5M/nc52enkpaHSnKM0jZE7SQXdaL+xDw8e7uHKZglzua/v91gSF19Tc3N7q4uIjre0aBOffBu5IRxWGfTqdxrK2zDXhGZ9lIytzDQVd3xnzfPYQB8AybMwOlFRvCdQ3ZRebc9RuDNabUiEzKcrmMABXGCIN7kRnc2LjrD8L/yabTsLpYLKrf72fKB7g3+iZ18AAVvIwFijXvxfs408LXxsFBnweyt9VqNeNAlkolTadTdTqdaNztQDrP6DqVII6SgnK5HMkCsnzp/kzB9DQx4I58Wqr4kHIHy8/nF3ljLf25cNJ9DaRVSQ6OM+AOzubu7m4Acy4zDlIzH+jNarWqw8PDCDDoEUYQjm3GJnn5jTOMmHP0IvrGwR3W25kgrAnBDt9h/lhXwOl2u63RaBRHdtM7hfIRbAGyn+p2AiUc+OVyGZlR1sJPqHG9IGXLb1JZcj/Ey1F4xw81XO5IGgJuOtjF+zrIiKzu7u4GuO7gNoHb7e1tBFeUSNArRHr/sBPfvwcHB5mgAkCIoAKmhaQAU92X4r6clLWxsRGnK9HzzQOYnZ2dCOLQTc7O4L1JzFCONJ/P1Wq19OzZswCM8GkBMAkCvU8Yc4AvAnvES/NSYAEAE38VPeiMC5KGqS/Hmi4Wi/f8z4fw77yfkvR+/0qCfN4TXZQmCXxO02QgfiAyyV4DwAMkQJZPT0+jvIf4gWuNRqNgM93c3KjVamXKJZlXLwlF39HDxpnM6GnXnewn2JzuR6KLeG/8lMViEc2+aSKOHnS5wl91/x/gnBPqxuNx/BxWImwu5M/3iveeYp9QJSKtktQpM5u1+lDD4yRiCvftiROllS0C5KHHlMek7m/DLCRpg2xyPcgPzWZTpVJJvV4vk2DZ3NyM5tdnZ2ehU7Db3M9bJgBokYDCXrZarWBy4iuSyDw9PQ2win6J7AeAnc3NTZ2dncUzoUM8CUVcBJMKu+Ay5ck89DXPg4wtl0v1er1MnMV8evk/oD4xINVIgNCsoSe2/MS4NFktyrzRAAAgAElEQVT9G6j00+MXB5VwELzfg2dF3DhJ2bIeV+4sMv+GqomBI7h3QfKeCNKqRAAmABuCOk0cWmiEOCVuZHknlKQjxpR9uHCTwUOYvQyL66SlWaDRs9lMh4eHwSyQ7pydQqEQjcw8KMLRrlQq4exsb29rb28vk/lwtNszOMwL9arMI7RW2AFkjj0QwCFkvXw8pNPhYFjKkuBvFJg7UMgNhq5cLms8HkdGFaYS7+r9IHBGkBtqfb2fCYZgb28vyi4ODg4yAZszIng3B/3caGxubkbmlFp72Ek4GQ5KMTygd6eagHw6nWpvby+TQZ9OpxqPx5GFpq6frJc3DFwsFhoOh7q+vla1Ws2URXjgS+DK+zCnGGOfEynbay0Nrh4yyMIJYK54R3dK0/8DnDjI7XODgZzNZuGMkpnHYLquRM7Y5xydzR4tFAo6Pz+PYMzL6Piu9+LhugSR8/k8Gnvmcjnt7e1FbTv17pwM4uvgAJq0YqM4OETADegwHA7Vbre1WCw0GAyifj5leXAfaN5cBxYCei4FVwFPeS7o+6mjIa30AvciKHUgxd/3QwxkjIDVAR3f5zBusYvea8/nw/tn4PAvFncUdABISRmZc/vN70qlUvToODw8VLfb1dbWlr799ltdXFyEPuHenrxxEJwg2N/BmcgAoziorOPl5aVKpVImEGFvUH4krWQS1sB8PtfZ2Zn6/b7a7bYuLi7U6/WivwnNQWEjsJe5h6Royispc4y4dNeAFMfd7QVrA2jlwT7v7o4we/mhQSUCLD+llGdDBlMmKYEqwQUAJzJRqVTCpjUajQDpOLYbHYQcwG5aLu/KJ/7t3/5N1WpV3W5X5+fnUeazv7+v58+f6/Xr15GAKZVKajQa4T/BFlkul3r+/HkA0bwzGXuCn729vehjlM/no0ksttN9AZ6XPVur1cKO8h7FYlHj8Vij0UjHx8dRdoI9+Pzzz9XpdDLPJN0xXw4PD6MczxNNyBn3d79EWskNQCd2gP3G9/ncQ8udpAw7VrrbezT09RgAsAQWDD6EVyAArKArCPBrtZrK5bKq1WqUXeJ/YwvPzs6iMbN053ceHh6q0+mE/pzP5wGmVKvV0B0Aj+gugPunT59G8N5ut+NUOXRhtVoNUHM+n2eabh8eHgY7lz1Xq9V0dHSk169fBzvl1atX4ZNyX2Kjvb09VatVnZ+f6/j4OFpw0OMOIAK7jZ5nHrmeg3yLxSJYgiRw0aWwnrwPI+wSYjRiOZeDDyV3xKvYOQczt7a24p3xufL5vIbDYex/9F/qu8IIqtVqARrDsEVuACy3t7c1HA719u3bKJHjuqPRSP1+P1Na53Evc7e5uRlVD6PRKJqyv3z5UsPhMHykdrutd+/e6e9//7vevXsX9+M6g8FAb968Ub/f18HBQQBjME+lO5/gH/7hH7S1tRWstydPngSgSEN7bK/H9bCqsHWwkfP5fOzTm5ubYB3DvgPYyufzEbMyh7lcLkou3W4764x5x5Z4AuMh5O7XOn5xUAmD6qcASe8HGAQULKwHM+58sWm81hOFRVYBihwAiBtXSe9da2trSwcHB6HwMOCgqQ4C8UzrBIvnBkjCGfZA2rMkntH3oJ458XpTSZG5o+aabAwOnAcYXN+DAwytg2o4Ox7Epu/JXHnGzYGjdDO6w8F8f6jBXDli7eV6zpxIn30doIlhLBQKGo/HYTQIOv34VZ8fDKj3TwJwlO5KkGCguOKCVeay4BlBfsb8OrMEYHS5XAaz7eLiIgPcOIPEr++gE/uI7EWlUgkngznz+YM2juHy3khk9VHcaVPpdbLB7wkSvUY7zd4TDPi1HjLIgkbrJTvSinUF0MneJ/BKHXfvP+QANIYQqj09Mjyjn8vlIkjb3NyM4NjLP8jOU/PvQJaUbe7uwJUnAdDrOPNkwJAnD4DRrQ6EOjjq+tEzojSexOG/vLzU/v6+Go1GOLX+nNgFHCgH0NkH3ijf59f/zd++11Ld5sApv+fnH2p4cO8Aps8xw4NF5GNdph/n0W0H7weDBFlE1mE/wLAlaGdecdCc6ejz7yAsz05gAUiEw+0ADfKBg+5zgK7h4AvsFmC7lxIVi0U1m01tbW3F0d4AQ+PxONNcmaaqOPHIWi6XC9lKS/b4P4GGy6PrcPYKgAugW1ruxv9TXfihhjMP2G/IidsWdIDLGvYQ5psncZypweBobcA27xvkviX+0ieffKLBYKDj42MNh8NY41qtFsdmk4H37xIoS9Lz5891eHgYIJbrDO7L88CS5+jw5XIZPXMos3T7Cwg2m81iLvxUS0BHSoIA4QDHYcngcwCiUB4zHA5jHZzN4izLtF8If9CX/NxZPPiZ3stLejj/jvlMnxfAJ5/PB2PCS9HQO+gSfGb3k2gtwHXZh1yXUkNsqbQC5YrForrdbsQCi8Ui4xOieyVlbF6321W5XNbHH3+s4XAYjDZ6HnW73QAbT09PI/B2ZkWhUAhWFLLYbDb1+9//XuPxWB9//LHK5bJOTk6iHIoqBlotTKdTVSqVYPmRoGGeAHSRGQ51GQ6HIXvELbwnTBOXG0pAeXbmVlr1LQNoAFT38RByJ2XjIgB1QM5isRj2FQDT7UDKsmTtsRnOeCqVSgGywSJjTrEjXM99F08GYn+lbHsSSswuLy9Vq9XCRjYaDU0mE3399ddRduk2h/XZ3t5Wv9/XxcWFXr58GetEyfPV1ZVevHghSfrkk0/09u1bHR8fq1C4a1tDghD5g0WcnhRKCbLbCeTPbSU2BoBvMpkEGLhYLOIeJDB8f2Nz8vm8Li4uwif3HnYPpe9+jeMXB5Xc4fSNJGUbqkrZppmpwUvBF5wyQBE3wCD1GH6cBowI2TA38ggtzq0bep6DZ3YHyQfv02q1IsgmyPSAB8MnrZoke5DlIIefZoPxYm6p13WmBs/nmQ+CBBy5xWIRCoBnYW58jVBafn0HrVgzz4KtA9weQvmTuecZ3RA4q8MDZGd4pJ+HoYOsYTRwOvP5fJzUlsvlolSCTINnrQhM5vO7mmmoy4PBIGTan83Xwx2jFCja398Pp6JUKmVAREYK6krZEkB+x3vBdgOo4FkByXC4AX+QD06OoFkh2QicIMpQkC1nSxC4SquTHn3fI7PsERzElLH0UKAS/097T+BcOkjrwWUK1OKw4tgtl8vMvBEQdTod5XK5yDA6NR7npNfraXNzM/qD4PTiEPJZAiZ3utETBEHIUKPRiJMDcajov3NwcKCzs7OMA+9y7e/pupw5gKVAX5TNzc0I3mjW2O12w3Gmf9hiscicIOLBAnoPRw6mJ++blgQ7YMRzerkT+8WDfb73oYZnzQkaWS8HaAj6HWx0sJ33cKo6oJ2DTVyTe6BnYcG2Wq1oHkrZ5dnZWabcAzlDP3vpMMEKoAp6BSCIuc3n83HqEnoFPQ3I5vT2nZ2dcKQdRCf7n8/ndXR0pBcvXkT2cn9/P+SeEnvsOQDRYDAItiny4+AS70NTW9YjtS3MMaA8usP1oyel+B3z9lByhz7wLLmDZNgLvsN6M7ALLmfOwvEGy7yrB2u7u7tqtVpqNpuqVCp69uyZ3r59G6cvwYKo1WqhS2FYum7rdruS7uTq4OBA7XZb/X4/kiYO9tdqtUjw+clMJPzQ19hgfAO35eVyOZNo4XOsO7J6cnISAd9//dd/aWNjI3raIIPMCfPB/EmKIA2ZkrI+p7Tybd0XZN/AouF72BUfD+Hf8ax+QhgBpgOyfMcPg3BQJNVH7ocTt3DKGf0p0ZsEvM44gqXr9wYY8DiAv6VVuRhsKko3c7mcDg8PVSgU9ObNG52engaDaTQaaTgc6uLiQp999lnoYJJF3333XZSnFwqF8AsqlYpms1kcwQ6wyp5FTk5OTmKO2JschkBsxM8vLi40Go2CgUpZVTq3yDq6i3VAj3ks4b3Y8GPdb5AeDlRyXYCMwJbBfmIDPXnvMQXXYS+5bsNeea8/gM5ut5u5Ln6mx8jMpcv3ffErtg5AdD6f669//auOjo7CflGBwH1hCzWbzWD9EHfAMiURM5/P9Z//+Z86OjpSPn/XAB4gkaRopVLJHF7gFUb4/c1mM06hJTHG++A3wGIHGE2rM0h04efA9CPWyeVywaDCnksPW3nzaxy/OKiE0ErZI4HTIBllggH0wNmdTUnRCM2biuGMQHunRIlO7zA3ms1msC9weFBmOIOesU8DvdSB84yttOqHAKhDNo+A2+/F9xB65gWlTP+K0WgUjQEJyHGSycQVi0U9f/5c9Xo9KLsAShiBer0e2QGe19/PqYLuaKA4YUilmSq+uw4I9Ln6EIP38tpsabV2BIrUOksrYMzBnxRUm81mcWoPxv/m5kblclmNRkOlUilzDDLriBODI0sZGArX94Az4lz+MTzsE3d6kCXq6YfDYQSANB+FjeIOE3PB+5O9YH1///vfa3NzU2/fvtWbN2/05s2bcE6g5GP06vW66vW6ZrPVEeY0u0d+aCaP07G1tZXJQC2XywBRAPDIxjrQyx8cNw+uUll7CLkjaPWAj3Vm/jFknPjkgSqyynfYdwB6vBNGNJfLaX9/PwI875mxt7enw8PDjH7BuBaLRdVqNe3v76vf70fWx+v6U9ASh3O5XOrTTz8NUNVlEqry5uamnj59Guu/s7Oji4uLyBw7kEEjSHTe0dGRWq2W/vrXv+pvf/ub3r59G+AXzoV0VzrqpTKwS9rttiTFkdKe2aLhN+9L0ODZ7BTgk1ay5CXBrLGzNP2zH2J45p53BLjFgfJDJ5AN9r8ndpgPHGD6dQHqSauSRfookKWF7Usw3Gg0ws4gY/n83alH3sAa5451RI4IQGAYueyyVpQlAz64Ld/Y2FCtVouyveVyGY4zFP1Wq6V2u63ZbKZ+v69er6fvvvtOrVZL0+lUf/nLX3RychLJAdf36FUo/41GI3wQZIP+YOhFdJi06r0hKVgyLlMuQ9hR9o3LtPRwDDnu7QA2OovncwDNs+oAkjw3wfrOzk4wxNxGe+84DrwoFApqNBpR3j+fz/Xdd9/p22+/jSOmCVxgUVBSTUZ7sVgEg5NWAVtbWxmGr3THVjs9PVWr1VKv19Px8bFGo5E+++yz8BvRG6wnx8v7SVckrzjtCVkFgN3Z2dH5+bl6vV7IK75krVYLABPwFtsBAOs9cdzn9CQBMsb8uv7CB0Rv43vzHN5wnfEQcsccA8zBlvakKskp79PiAAXAED4eOjCtemAe/XNbW1v/l70z623syq7/4qCB8yBqqlK57LLdAxCgn/KavAT53vkAQZIOuvtvd7ddc2miSIoUNXH4PxC/zXVPUXJ1Iy6pAR+gIBVFXt57zj57WHvtffSb3/xGf/zjH9XtdgO85PsAh7FVDGyNg4iDwUDj8Th6qL5//14HBweq1+v6/e9/r5cvX0asQpIPgKdYLOqHH36QpNg3tAV5/fp1+Gz/9E//FEBQrVbTzs5OJhlAuR+9L0ngICMOVNCfrFQqRTNv9l+tVov5R44oucKno6cevgQ2Cr/HwT+Xv4cM7p1hzRzjf+MzOyjb7/fjHmHYegmsPwu+HL2tvNIEQA7w5fT0NAA391PQnexfnxtiCk8y7e3tqdlsKpfL6Ve/+pU6nY5ms5lOTk7U6XR0dHQU/rnvK/cJLy4u1G63o8k2tolYYmNjQ6enp8Fa//LLL/Uv//Iv2t7ejn27vr6eOZmzUChob29PkiIpdHV1FeA6/gU9Np0NmsvlopSY+A9fhjlxkgjJKN7HCZzMoZ9q7OMXUOn+8bODSjiEOKOeHZKWm8sF3x1LsuApau5ZHnfOcDZdYOnxAHLPJsHoIIxQhNnkOLUoPgdKuA9+5z3cP/dLthf2AO/3gN5BKV7je29vb4PKxz+n56LsvWE43wmy68wo1oB79qyUsxUYXN9BDs/8uzPizu1DOx2edVoV3ANmuDy4LHomLwVjPJsK0DQYDHRzcxN14vT6qFQqwdrhNCvGZDKJBrDlcjlTW45h9ntgkKnFsSYggxknLYEyD5ZdPj2bjHzQbwTa9e3trc7OzuK5MfDSkoFII16yNJ1OJ5pKpvOJ80fpZpo9AVAiQ+Vy6qAM+8vl0IMXxkOBSsw988/cubGnhIjAimdiXTwbhnPmwebt7W2cWvPu3TtNJhNtb28HMESgTnYGx+fi4kKnp6fhTBKkY1w3Nzc1Go0yDpLr6lqtFn1Izs7O4nWYGK5LisVi9FbAmYRxQsCJTOzu7kYvEnTfq1evMn2N+A4/WYrSuHq9rnw+Hxmq29vbDMOA/QMQhtwzp9ioVTLkYLT/c+fXx0PIHT+5N+bW9yF/B+iQlhl/T24gE/wdO8wADMIZI8FDuRB2iXKNm5sb9Xq9cBq5lvf7G4/HKpfLEbA4u01SfB/AYbVa1ddffx0AtTf8pmSE3kb8I8EFQHZ+fh42ExnI5/MajUb64YcfQge7bMBMAWAqlUqZpvIkF/x6bt9dnliHVJ955l76OEnjBxOktvpzDX+e6XQa/liqv6Usw8V/d93ooBv6x/WEA/UEva7jKG+YThelYjRZp5QMmeU7ALLpN0iQ7AlAT3yur6+rWq3q+vpaL1++VL/f12QyiZJw+tr4Eegc987zwRLn+2azWZQrs86SdHJyokKhEM+Br9Hv91Uul7W1taXRaBRglbMLPRj35Av6GNnFvrtNSe01ATP3lwayjIcK7j3gZk87mIu94DU/ic+ZSM5uZI54nbhlPp9HDyps7fn5uQ4PD2NO9vb29OzZsziJulQqxclmyBpzy3UBH0ikSUvfrdvt6vr6Onp+AYr6unHds7MzffXVV1FC1G634+RO4g96eF1eXurs7CxK3EjE9Ho9TSaT2MuUQqGX1tfXgxU4nS56r+Jvrq0t+p4B5uLfoDOdocS6oPecOYcNcll1W+vjIeROUsgdesFPDuMenfnjzEpnyEnL+I/fkWf0GSw3GL+DwSCuw/fRq0hSsLj9EA7kF0AR8A8dTL9YDmyh/6HrXE92u08F2I1dzOVysf92d3f19OlTDQaDiBcAS0ulUrAtR6NRsIXw6XK5XDTlJv6HCUcsgU0mkQNLCZ+XBCn9mABJvUE8iXH8U9aZ//uaM34Ble4fn4Wp5JsGY8drOLNuqFyZ++bgp4NCbEqcZI46J4vZ6/XU7XYDyc3n8xnjArJJ6Zy0dNq4Llkoz+5K2dPaPBOFIwzghRDicPG8DmT4M7rDD/rL97mjSsNQMlY0V6Z5oLM7uK431GQ93EH14NwDSz7vBs0VDj/Tf8zP5xrIHWCRo9PMKc/swIsDS+5MIifOwkFmYYzNZouSm93d3QAlAXhgK3k5JvIEawwj6ooQh5Dvc2CLgERaNvnDsfeGdWT5aXTIdTjRCMOFbLFONJMlwOF56J8xmSyOaQY0gyEDyEtgimL2/YrD4hRx3o+84AQ6mOKAsgNJDoY6sCk9HKjkTrm0LBWSlNEnHrCzr9xws57MBSAUgZU7w8ihsxz5jpOTkziqGKPqZRlPnjyJ47UpN6vX62H8WdPNzc1gn3j5MEBRsbhoYosMF4tFnZycqN1uq9/vf8RwdKYe4CSODs1VpaXOJ+OFTcAx4TN+HPjV1VWm9xvOGoBGCpKj49JMqQfuqc5wvefjoYJ711vIizvjqc7GjrjeI5jHMfTvYI4rlUocPIENQnar1ary+byOj49jbdCPAIL1ej3kA9k/Pz+PjKO01NMESTSaJ9HDd7HOMHo9oPRjg7e3t+OeCbAlBROBMs5yuRwJJsZ8vmBtsUfOz8+DZQgogU6dzRYNaL280mXE/49u9GDD7ab/39kVzoJ8aH2HbgesI+HiPgNy50wsnot9iF7nSHQCZlhw6P5ms6kvvvgiglVaDZRKJR0eHur777+P4+HJ/hM4wU6CicK9eCnnbDYLJp+kYINubm6q2+3q9evXmeCm1+tFeciLFy/i+a+vr0N/Mw+7u7sfAb3ValWj0Uinp6fa2dn5qKSO+YFRc3x8rO3tbQ2HQ9Xr9bi29/BEnrAb2F5eJ7B3uUz9UPcZeW0VS0l6HKASALAz/vgdNgP36oGx//TTqOiR40AoMri+vq6nT5/q7du36vf7IUcvXrwIIBFdgu5wlhdrApMWe/bNN99EUqTX6wWo6KxmAmYHJ1qtli4vL6MJOEy2XC6XAfW/+uqrOPG02+3GMe3v3r3T7u6uRqNRBoxst9sR8APwEKRzKBJzTM8fSvJg6gEWeODusocvm8ZDADH4DG6jGQ8FKrl9xR5SQk/bi/F4nAHLPLHoZec8M/4ir0OMmM/nceAAoKK07NNXr9f1m9/8JvpqNpvNjP/usSrJRfY//jjljs7Q9ORzGqt7jAVALymSAbB+AM2RB8rj6Dd3fHwcCUcvN8N+wm72WJ99zb9+v6/hcBilb67jsOHoXGdmEsuxp/i7yzT7NR2/gEr3j5yk+U++6+8YZA5wNtzgsYhsMAIGNpYbVWnZ5NadKjYdBgKKurQIILa2tjSfz3V4eBgZTgzC119/HWCTBwkEI9Qx46hw3/xD6JzBwzOklG9H4Knh9GPBHVDzbAvlKV7jicNP6d7NzY2++OIL5fN59ft9nZ6eZjJMGIa01IsGg6yDZwj8WXk2d4LcufWgypVnmh2/a3P+HIM59OwVw8EjN1IeECGn3jCOZ8FhmM1mwYKYz+fRc0hazF2v1wsZPjg40M7OjiqVit68eRNKG0cFRSktynko2eQeyNw7uAIARTkSjrPT7AEl6Gcxn8/jNCSUN6d/EATwHZRTwiyguS7OVrlcVr/fDwO2sbGh8/NzvX37NoL2RqOher2eKQMAkHKDyr2m+91BXAefUhApDf58PITceZbNjSEjBY7YZ3yWdSCY9hIgHFTmxxsr0pS63W6rXq/HmtL3hcwZekRaGNt6va7d3V29fPky1nYymUSDUUD4XC4Xa51mFT14ISvkwOdsNgu5Pz09DSeD5+Je2FNnZ2chy7Cb2AOVSiUc3a2tLVWrVT1//lxra2v68OGD/vrXv0payN/JyUkGlHVAD7lCBzI8KGHwnL4PPZHwWOSO/xMkp4BDul+Qg/X19bCn2DCo+OgWAGiCnJubm6Cpk81uNps6Pj4OQIeSRa7HtWEzots82whoWSqVolyb3jL0b/KTXkejkb788kutra3pzZs3Ya8AzTnqmiwk4HgutyhR2Nzc1LNnz/T+/fvQuzSoBVBoNBqx5rAJCAg9ObOxsaF2u50pCSVAw8EmUca1WBOu73bE2WMeHAAwPBa5A9RBj3mw6Ak5hv8f9jjJhqurqwhOJEUvrnw+H+tzdXWlTqejUqkU7Ioff/wxZOnp06eSFkw0AMfd3d1gMhLUOvORU11zuZxarZbm83kE9ePxWN99953y+Xy8zxM9Hqx88cUXIecAHdIy2Yg88Pl+vx/XI+F3eHgYer9Wq+n9+/chv/hkyEqlUlG9Xle73Q5b3e12NRwOg7k/n8/DfrA3vAwkHZ70dPlzUNrHQ+o72Bz4UQ4msT4uewT2zAu6ElllXsrlsmq1mra2tjSdToONyPy9efMmA1aVSiX99re/DTBxMpnEKWuejIV5QgkT37O9va2//OUvUZKGr0bPLE9ooBvwIabTRW/O4+Pj8DdhRX399dd68+ZNNF6u1Wr653/+Z7VaLR0fH+v169d6//69Li4utLe3p7OzM11cXOg3v/mNZrOZ/vjHP8bJdsyf+yj4N5Tx+XvwU6UlyxjfzZmA6Rqx17HNMPzS8RByx2D+qYzh+bzlAz4qsQi+E3sIWWUvA0who8yj9zL0fVur1fT06dNIwOXzi4NSOA2O7/HTzCk1I+lIMoSydI+107XCn2WtPCnSbDbDL3N/tt1uB+jEa9JijY+OjmIfIMsktLgWn3EADjAPfca+YK7Qj8RyDtg5RuD9lRxIp0R6VcJQ+rxy9484Psvpb2mGTfq4VxEOuwf+kjIBFILnhs5LergmmXuEzKmsBBJsfkfNCXhxMigfk5YUbs+2O2vF7z3NGksKIcep8LnwjD2BGZkMDBlO/WQyifIiMqzFYlGnp6dxTzgwMBa4J3rU4GSkwRLDN5MrMX+WFGn3YCXNKjxkJssBMF73Z/Xhxs0z/KyxK1xAm9FoFCAhpQ8oVgwHzgvNklFyKE16KWxubqrVamVKiQi8WUuyRATjsEgw8si8U3J9z2EIAcb4jN8rewxnwU9ayefzGZAJmez1eur3+7F/RqNRGFIyANISVEGGPDvFT97DSEFK1sfXddV4qEyWg7LopjRD73tslTziiCArBAiUdXBqB9cmU3N0dBQ6xHvXIBfS0sjCMOI0DAfqJpNJsB93dnYCLPIjac/OzuL4bQAgqPhQ76+vrwMgoASJeYEmT408fZcceEOPM5+wCSgVLRQKUddPg14GgRQAL0fmujPrI80YpvKTrt1d8vdQcpcG7r6fAMr8ftMA1XUf8kHyAh0AE6NWq0lSNHsdDAbBhqMvgdtA/k+5j/cGpJfHbDYLFhT9QQAraGxM9r9YLEYz2XK5HKchUYqbzy9P4iGZxLX9NUmhhzm1hr1XKpVUq9UyCS9kkcARNirvQTd6Pwf2rvckY4+lcrRKJpnDVPbS8VB2VloCr5ICDCew533o+5RxwPXQgzB0CTIKhUKAJ+VyORKC79+/1/HxsU5PT8OfgZXE92CLYVkCLBHwku33Pjh8bj5f9I958+ZNfD860nvNEASOx2MdHh7qxYsXmk6nEdiz97Cp+JC+Hz3RRVKH3l7eM2Q+n4ddYG8OBgOdnp7GiWQki9y+esmd+wN3rYffl+uRxyJ3DN8TyJ37aasGvg7+PDEAPg5ghh9lP5vN9O7dO52dnanf78fJaR5zfPnll+p0OuGD07oCkIs+M+gJdBT3TlzCQUMASoyUWeq+Bc88mUy0t7cX9m4+n+vZs2e6vb2NZvTj8Vj/9m//pqurK/3Hf/xHho2EX5jL5fTu3bvot4gvCEsZ5hXMYfd3FvsAACAASURBVJdRZBj9h/+Xgkc80ypZcx2ZxhO+jp9rpHInZRmB3quLefA4zCtY0A1pOamzgCA5SMrYDAd70D/Pnj0LNhzsHWl5ghw2zHWb22FsubPl/RmdEILO5LP+HgfTkZfpdBqsP3zR4XColy9fqtvtRp+ver2u2WwWjOVUfzEcyHf266rkjP/fQbF8flnqnMqeM+nuGp9T7v4Rx8/GVJKWpW/uwKUbaBUKSa8jnAtHx1lQzxahUB3xBcn98OFDOIFshna7HQKcOtoEZJIyKLKDEQgfCtgdFleiZEVRHBxhjLPOdzmAAZWU7DDsJu9jQZDE/boRm8+XNfPr6+va3t4OoIPrYMiYM4YrdMAIQAtXNj5nKH2fw9TxeKiMgqPssLxW3SO/Ywi915b/nedPZZG/NZvNyKo7Ul6tVqOhqxtXd2Dm83kcCcxaXlxc6OTkJIw0vZMot6APDnROaSGzfB4DMBqNotSEBp9/+MMfAtjifbBgYPUR0JOx5z559tQIIifsm1qtpkajoW63+xGYzP/dWcCJ4nnTUsv086sAah8PmclCRpxtwPBAHn3n4KfrHIKq29vb0BWSooyo3W7r+++/jxII+sg8ffo0WBUbGxtBn3dQj4EjQM8QaXGyG59F11Gagl7zgY4hwJ7P53ENAHD67zhbzvUlDjHsTGcY8V7k318HZOP7T09P1Wg0onE04NbV1VUwb6Rl7woP7NHbXvLg4z49x3houeOny5TrMvSYs0s8Q4pOevLkiY6Pj3VxcaHNzU1tbW3FvHiiY29vT//zP/8TvbY824/+4T7pr+DJj1qtFmAipwsVi0U9e/ZMo9FIZ2dnKpVK0SwZPQTLhecbjUbRzLNer2tnZydK0Om9dXJyEsCDr7WkYB34/lgVCDGnMAI5or7f72fKU8i6zmaLBvEeCDjILC3t6H2ykyZ10vFY5O6ufcFAJ2JvAPloUgvDkDUoFBb9XSaTRV8NSWEPnY2IbDebzfDLnHlHUCQtdR7gOzoN+V1bW9P79+91eXkZtpu1dJ/UbTl93d68eaPf/e532tvb08uXLzPlFbu7uzo6OpKkjI12u4n80zsql8uF7sIvANz/8ssvQ+6RLbcfPDPl0dgEXycSDs7YXDUeq777FJlzQAZ7Optle0bBfnQGouvF1N/xxEOhUNCTJ0/UbDaDoY0d4z498KYhPAcJTKdTvX37Vq9evVKxWIyT3NxPcLDMwRjsVqVSiR5OX375ZSRx8GePjo7U7XbjOru7u2q1WvrTn/4U84i9lxQJLPzHt2/fBpCOrOfzeQ0Gg5Af7hd5A7hzfzddS/yB+4L1x6rv+N3tBPNSLBYDvPH4CSCY/3Ntnt99W0kZhlOaFOIn/jI6BUbw5eWl9vf3wz+6vr6Ocj2qFFqtVvSe8/iatfRWFJAa+A4S6jAtYQhLiu88ODjQ9va2Go2GptOp+v2+jo+P9fbt2wBzHThEFvDzJEVsS/IgTVI7iOTr4iAcSQNsNKfeAeBRoud+06rxC1Pp/vGzMZWkbN8K34TOhPC/I9Q4rTgJ/M03pzsxfBf/9+uyub0MxU/N8AaO/B0BQ/i8xE3KHrlO4C0tlSMMARwJScEKKJVKkS11hoDXW0PndSeTDcX3u9AzL15DWigsTniiT4kDbuk8pfPpzCucbp+bNHNwX6aV9f5cY1VGgedxUMhBDX825Iy/pZkil1Wnq0qKhrFeU81pGACF3q+LawLA0OuBpnw0kqXRbKvVigCJ74LG6k39+J3MPiAjhoK6egIy77FDlhQlTvNR34PMgQdk0jIwJWiD6YKTlu5ZdwbJ4LJO7Dmu659zEOC+8dCMEQ/Sec0DQndWpWwvC2QUxxddANsBZtva2lqGLUeGkgxrLpeLI5Exnny/U/9xYGmc7DrYe99wDa6NA0DGDmfFDbqUPXzAwerpdBogfi6XizI+yj9S+4HMOJiN3KJHZ7NZMPoIwrxmnzl2PerfkQKYPyVn6XhIfZcCIIw0I4wT6DbNs3rz+TycQMqlccjG43HQ5be2trS7u6vBYJAptXVdkPbFcPnxgHYymUSTW5ias9miHB6WgB+CgB70PmI0+x4MBtrb24tnhAmAPqOhJ8/r8oQedbvhIBPPJy1Pe/SSNC+HwF/huVJQMwUm7gKM/LvvGg/JVHLdnL6WDnr+oRuZN9bD7Q3X854ZzWZTv/rVr/T8+XO9e/dOt7e3YT/JQjtzifv1tcIn9OQI/hIsOG9m7EGv92pzHQKTg15y9E/sdDrhLxL4Mz+uI9lj+KyFQiGju/keZ5978M73c18us76/WRcALbcD94271vMh5Y6xCvzlffzz0mBPcrsvjM/rPiE22qsFXJ+tra0FswymxWg00ny+TGbz3VQUtNvtYIEDNB0dHQWDBZl0gJD7xO7yO4E5/tp8Ptf+/n4kpmezRXkxYDt6qV6v6/b2Vq1WK0ACP0UTYLNcLqvdbms+nwe7eHd3V41GI9hxq2TH5Y15Zi55bt7nvk867tJ5j8XOpr4x/jhJamf6uK/k8QWy5ywhT0o60OT6FfCF7+U+ISTkcovm3NhgDpdw5rLbHNeTrJ3fE74sJWPSEqCfTqfh83vsPxwOo0XD9vZ2nNg5GAwC5GYOXK65dweBUz87TZKmoJv7uvxDR/t6AZ59CmD0C1Pp/vGzg0rSx44Hi+qZNy8VQdCdzcTnUycMAXSn2RHOZ8+eqVQqRR+P2WwWAf58Po9gmmM6eR2nxzOKCBPBb71eD8o/QBT0ee8XgrCivKnZx/A4LZJgn887Qu0Kxje9B0bMzcbGRvRwIFPmpYIeTEjZDDZrhAJk+PynG8s3c2rcH1L5e4bKnXju050sZNJfXwUyOcPBAcd8Ph+NRUHsCWhQ6g5y8j0ESgRsKNtisahOpxOOLoaCRqSNRkOXl5eqVCpqNpuZE3hwPinTuLm5iVNE/Ch7z5KguCeTiQ4ODsLZdaaBGz93fFz+yuWyvv7665gfr9Vm7pBl/z/XTQFLLw91eWVN7hoP7XSsul//m7OYfP5c50mKwJiggWsBUtP/hWy7Z74dXJKWAZFnPllbgnKy4qwrYA+sNtYrl8sFWwSKM6Uk/pyuT5F5z7qxJ3Aq+B4HvZ0J53tSUsahgA3abDZD7/X7/bhn5tLvDRo398w13YlbFTzfNR5a7vxn+ru0PGUm1W+p7YUR69RybCanC5EFp2eSpLA1KWvC9zqBCzYZkIg+SmTe19fXo8xpc3Mz2Jrcr7PcYJ4Q+HW7Xa2tremLL76IcsxCoRAnIFHu5vuN/eOObKqXeBYCg3w+r+FwGHNKoO96q9lsBkDg6+C+jPRxlvpvGQ8V3Kfy5X5COnK5XDAo3NZKy2bQaem5+yrFYlE7Ozth12D/NpvNjH1leJmh+zSsM3uhXq8HoDMcDgMkBZB2G89z+Fy4j9XpdKIc9MmTJ5IWPuDOzk6UGuEPlEolDQaD8AO4Jwep3KY7gOBlT4CYDnYw/2miwp+B+cV/TdfMfcXHFNynem6VDErZskw/aMUBG59f5lPKxiW5XE7NZjMa+qMb9vb2tLW1pZ2dHfX7/WDEOjhTKCxKxnq9nsbjsVqtVhwaAFhTqVT08uXL0GceKPszpTETr7O2AI6dTkeNRkO5XC78r0JhcVz78+fPo/zOy0WbzWYmoY0e9O+gtLJUKqnVakWjcffTfN5zuVxGD3qC3/9+n967a40f2s6uikN5L6ASa0+FCevkvhV+Iuxv5iqVU173+UgZdLu7u7q+vg6QHQAfhme1Wo2Enjf9ns1mARR56V36jO6n0vTbwbBms6l2ux0gJQl1mMh+0Aynvl5fX6ter0e5JvOxubkZJ9N5/CAp851uR9ITf4mvAfhSP9j9mpSteVds8QuodP/42UEl/4ewoFTYXO4IYORSIMA3nwNI0hLRRQl6bStOBz04EBSUd6vVUqPRCAog10PYPNNFLWwul9MXX3wRAR0blNIyBBjBxdlkk9EEFSo0R5XyPkePaUpKNoQsqI/UOeW7KHljPtzJwIj6xnRl50ABwzeptFR+qfOSjs+5CVM0G0UC0IZcpOwXZMMZbakzm8vlMnLKezGUKLpOpxPUV5occk/shbW1NW1tbalSqcTavn79Ok4e4uhWroujwpwj0zjDGOejo6M4cYsmfPV6PUqL/DQ4mpbCnpvPl5n0fD6vX//618EY8T5gPj/8HwOHokZWAJUoJWKfehmgK37WkOFBhztV/tn7ZOFzjdTpcGdU+ljOnKG0ikGDcwdTTVL0hCHryf9hiLiM+/ywLhj0XC4XATtyvbW1JUmhiwAki8ViHIIA0EBDWb5zMpmE4ad5p4NHrlOcAZI6KjQp5bO7u7sBHEjLvZzqfgKwyWSib7/9Nk5E9D42yLzbEfYMSQJfIweNeU539FcF04yHkru7AqsUFGONUlvrz4iD5aUg8/k8k4mcTqfRENiZxW5XuC4lHhx5vL6+HkyQSqWik5OT6K/w7Nkz7e7u6j//8z/1/fffq1gsRiPiXq8XICoMPRxTnNfb29so1Xv79q3+3//7f9ra2opm3twz5UI3NzdxxDyyiL4CzHdnG32Vyy0ZxpSEHBwcRLmvl+V76TPzjiynAPl9jJHHqu/uCvz87+iz1MF3PeFBvQeirvsJ0E5OTuL/6Cr6afGd9XpdW1tbwaIE9IPNNJksGiqvr68H6IMMAaSnz8jvrr/8GUejkfb29uL39fV1vXjxQv/7v/8behJmFKA8nwWoxE/woNyDSk6Zcob7KoYXPymR94MefM0c4E2fk7V4bPrOx0/JHbaAvUzMgF3CX04/S0yRz+f17NmzYHpw0pazMwHLscntdjsSPNfX13EwAAlAytz29/f15s0b9fv9zElpDr6sAhRc3yKD3j+x2Wzq5OREz58/V6VSiUMUTk5OomSX50O/wYbG/8jlFokj2iIAsgK0Um4OAJruafdJ0PuekPQyqzTe+Ckf76H1Hc/qzFbAxGazGc2gKcVNwWkHgJFBTyz6fNEnFT1JJcLu7m7EohwGNJ/P9a//+q+h+46OjkK2AAVJCKFLOVjn9PQ0qm8gWqA/APQrlYpms2VfMGlZylupVLS9va2tra2wy+heSnlvb2+jTJMeS81mUy9evFAul4vY5/nz55pOp9F0nDUHjPWkLSD9KlCKmC2fz2eIFsg0cZKD9NLjANH/EcfPDip5UC8tmSMefEpZ5Ned+tQhdgDFA0xGGhxgtAF/nCWFkNXr9ThFhIwT1/VMOc7zwcFBOKH0gXEgy7MJBFhsSiio1PhzbbLz/r0oGwfLtre3P+o35ffp85HL5SILgZPMHKSGyhFo/+dK3R2p9Hvu22ifexO6cXOHzcEwlz0pe8KTZwe4f58LD8L4Pj/FChDFT8ri2ji9u7u70cMGNL/X64Uyb7VaMa8Ew9w/zvPt7a0ajUYwBabTqQaDgSqViiRpb29PpVIpsvIYJYArnBcPnpmfyWQSR3/3ej2tra1F37DUkeYnr7mzViqVok45DcR9nzpg4PLC3HNffp37Aiw++7lGGty7HuK1VN58pM4jWRuA3ul0Gg5KLpfLAJrVajX0CqwPjgeWlgw8MlE4rgCF3pAZGfMm4dIi0z4cDqPEhHumtw4lSayXO46UBPjxzz4f7Akv03Wn008ZSQHHVOYajUb0fQJIwDEiWCQjz/4CgEIvSFkdsSpbx3tWjYd2dlOQyPdLPp+PDKo/r9ssBzWwAzigMEJyuZyePn0aZeToMPo1SMrYWfq6DIfDYGWMx+MAucn+cww8Ryhvb2+H7uHIb57T/QueDZmFGQzV//z8PBijMIk8YJ9OpwE0pKe6IZtpoot1nkwm2tnZCUYpjBWu77bE9WaasGH8vT0bHgNj5K7hQSX7nb3n/fPu8gNZAwdCAbGxVVI2yy8pggo+OxqNQvZpWOts3fF4HA2NCTS4T67pwISvp7cWIFlzdXWlJ0+eROkTe4VSOF9r9p0H2i476E5klmb3+I9cg8+lyZjUf3Y7wmdTGbpLXn08NKiUyp7bFhJ+MEeQDX5i95xV6fPjYBG9cAaDQfSBw7/GR09jFS+zu7i4ULvd1pMnT3R+fq7RaKRnz57p6OhI3333XehSehixjhxo4CXnzAM2O/XLbm5u4pANdPbx8bGKxWIw1WF1uI4iQelzgVxfX18HKJHLLRPp+CQOfvoeZd3Sw4HSxJvvhVTWVumXh7az/jfWBD/IZQHfAoasJxGxPZ64yeVykWzx0rVcbtnfiGTHs2fPtL+/H5UpsHNbrZYuLi6COYe+kBbkhfF4HGChPw+2ent7O6ok6A24ubmpg4ODOEjj5OQkk2DhOfADuVdia0Ae9NXl5aWOj4/19ddf6/nz5wEUkfRCb7579y4DhOMfI79peTD3AVPQP4vtQca5R3p/Oah01/gFVLp/fBamEsMViAeLUrZvCs6Eb1ynNLtiYrjB9Npp0FAHk6Slswx1kww9RsQpqChQskgHBwfxXm+ajZJddWLR1dVVNHKWFKAAnfnZGJ5FR+m6gSkUCkFxRNnw/I7085ywnHxzpWvhmzEFCXDA3KlIa4RXsZp8PASoJC0dPQwYYJHfr881hiBlzd33HL5OrK2f5OHX4EhkAILz8/PoZ0SJDsYBhYlBgGXiICH3BKOAZyEDy1HyGLXZbNG7iYwE60WDP8rnPIN7c3MTjcddxlwG3AHjWSlTqVQqkaHhnj3AwEF3NkAq0ymw5PJ4H7D0EAy5NJiXPgbeUoAJncW8s+fJnPi+q9VqAc7AiiRAJ1skKUNN9qwjPdYInLmuA+B+X9PpVOfn59GEGKcTJ537wMg7iMDzXl9f6/LyUvl8PvqC4czzfp4XnQZgj9Fnj/m+RT+hp8nWbWxsaHt7O/Y6TAaOqkWXenAGG8xBJe8Nxfql8/NYnF13CvmZBpIkKACVAF/cMXTAzR0sDz5JgLTb7WBb+umjzrj1+aCciKbWbvv839nZWRwbTzNNgELX177+vvd8fZEJsp04rJIyTTphLgNw8B1caxWY6H9Hd/Z6vWgQLikTsLGfvMSJOfNr3wcq3QfePEZQydcE8NmTWtwzNkLK6nif/1KppO3t7QhQYPHOZrNM/xL2PPOM7HBN9BQ64+LiQru7uzo/P4/msWTz03v1pCG/O4jF/QPuXF5eBnuBpFGhUAhwk7IQ9qn7nB54O6OE+/M5KxQKOjg4yJTWpXYSO0pwLy2b9XvJ6l0Bfar/GA8ld3fdj7TUzbBInMWGjGAHV/kRHkvUajVtbW3p/fv3wZrd2trKMEYc8GTdvX1FPr8oq9zY2NBvf/vbYMENh0P9+c9/lqRgj+LT5fN5tdtttVqt0JXsI9h1kjJ62td7NBppf39fe3t7Ojk5iQOFzs/PA1Dge+bzebzmsYAnWPv9fpzwyxxfXl7q2bNn8Xyp3kfuSCq4vPqeSZk66do+FrljpPcGQIsfh4+ezy9YRoPBIFhegBkpW19axp985+3tbQB5ngDK5XLR64pkMtULEB663a5Go1HIPexj7tV9cmQAIGtvby9AznK5rI2NDdVqtdDfa2trmfiC4ffJyelnZ2eSlux3b4exvr6uX/3qVyoUCpkWNR4jvHnzJpPoIi6SlDkpLh3ENT7PAH7Sct8gew6qP5a44h9x5PQznv6G8+pOBcY+XezUKfbALH1PmkV0BeXZiGKxmDmi2oMAhGhnZyc2I5vFmRwoXowE/wgioXYWi8UIvuhNgqKl9O758+fx3dwnDRwl6fXr16FUuDZ/Ixg4Pz8PauXZ2VlsBIIy5gcGAcc1Swq2AJ9xRY7ih32AM8dgHkB7MZbeh4dx1wb/XMPZEDgUXtrgwZQHwQAlOP5SNkPnQKYHaCjVyWSiRqOharUaCpf5SQfzkc/nA3iRFLXQBN2j0UiSoolop9MJgPPq6ioCegalFx6Qce3xeKyNjQ3t7++r2+3GkZ6eYUC2y+Wy9vf31ev19OOPPyqfz6tWq6nT6SiXy0WWgn3n2Vz2Dg6ctJDf0WikyWSSyaAwj/l8Pk4UAUzwQMydXdbB5e+hZU5aNu31YEPSR/edgmboAnpx8TffYxjZVqularUaRn9tbU0fPnwI3UDmHnAb2WCukRvWhbUuFosBPhUKhaAuHx4eqlAoRNkdesCDZn46+CktaeGVSiVATo5LZo+22+3MiXCUBtNvjj1Elg1Hx/eVA7cEnMViUU+fPg19NhwOdXh4qMFgEPfKHNDTLJ/PR0mUy1XK5knB9HQ8xKk0Dma6XvPBc8AmSh0oADbfbw58NBqNkIPNzU11Oh1dXV3p8PAw+kFwP96cGx1DCe/a2pqq1aqazWbYwJcvX6pcLsdx2BsbGxoMBkGPp0eD236G20zmHoCM19vtdjAu3WmFneK+BA3KsaHS8mTZFORGXubzxWmHsJ5rtZp+/PHHSBZ5vxr8DIJIZ0fhMKc2wxNA/tPHQ8ndpwyCbxx7ZJNAwrPNacCGbuK49slkEifY9vt97e7uam1tTb1eL4ISaVl2SDJFWpaJEUA1Gg3l83mdnp5mmmnncrkIkikPQfYpYeO+AKBcFwLKwgrd3t6OI79hMSOLDAfYnYHCtcrlcgSmvEbAynUI6vB3vIcX30EJSC6Xi1MQb25uwlf2z7icuS/k4yHkzkd6X+zl9fX1SKoyl7PZ4gQ8Wl0wb2lSjGsQRBOAE5R6z9Lz8/NgYWBD5vN5sItgGH/48EGbm5tqt9saj8dxmtr6+nroKg5AeP78eZTIuT5HJ2GLJenPf/5znCbGM8Au6Xa7+vd//3dtbGzoxx9/DAARf43S71VsJ+aCJDntGdhXrguZr/sSzNgNqkfw4dB56EkvQ7wvuH8McsdPABOATJhLtVpNr169ypwOnupy/7/Hwcwj8pe+Z3NzM3oG46dUKhXt7u5qMpno5ORE/X4/7gWbJiniPn+Wvb09dTqdkDd8UI+/WWOu8+HDhyjxlZYnptM/kGcolUqq1+tqtVqxxtvb2zFnrH/6/KVSSf/93/+twWDwkZylLKsUSF+VAHSfEP1IYt/Bqccid/+Io/jTb/n7h28aFhiDl2Z/pGzDLf8MBhRl6KVm/L61tRXKD6fN0UecaAIrFOjFxUUYDndsULZ8xplS/B+nFNCCzY9TwByQ8SCYw5H1zenMDz9lyY1hPp+P0pZ8Ph/sBObPgyUMqSPs/M66+Ak1/B9ng82eosBpQJxmFD/Vyfy5Ryo//jr37f98oHTy+XymYXHq6JMddBQcFN5prswpGX4cDQZZNBwLZFRarglyKC2CQgDF29tb9Xq9CM4wIIeHhxlAh2B7MploNBpFg3lfzxQMwCEn08bg79wT2VR3qi8vL8ORPz09DXYfrAOAVmRmNpup3++HQ+/r4sFy+vpjHquc1DSTx7M768GDe64jLRyBo6MjDQaDyH67XsIJ5TvoucE6AIh7eS/Od7lcjgwrjiwgEPRqQB8HormGtKSBc78EP5PJ4hjaVquls7MzXVxcaG1tTfV6PUoALi4uwtF32U8BIGQU5oKkaBI+n8/V7XaDBXB6eqovv/xSb968yRy7zXCwiCCftWLPuH1KHY40y/hYxir2hANwq15DlziY5vtrOl30H2AfD4dDzefzyKKmJ6YB5qBHmftGoxFJEUDk29tb/eUvf4k1vbm5iTI4Pse9oHdSx9eBItYNGUUmAb54D8Cryy+2HH3t4Bj6imcjkKAshn5P2E1kyNnMzLuXnmKr3KF2EIvX8IP+0TKlrAvDgRNOjroLoGXup9Oput2uCoWCdnZ2JC30S6PRiPI3yhopdWTNT09PNZst2GTD4TDs7cHBgarVqk5PTzMJNw7ZcJu8u7sbslKpVIJxB6hUKpX07t27zLP6M5FcvLm50VdffRVleIAKKduEa8AeyeVyOj091Wg0ikMwhsOh3r59G8GRg3J3Ze/xPbEfHpy5n5mCLazFYx2pL0BClj0tKUALdJcP92PxMQiO8W24JqA8rA561cDmhd1BE3bWGZZPr9fT0dFR9GHzQ10AIqvVqqRl8O/6j/vhPgHi8dfwx7jOf/3Xf6nT6QTYzfyQJGa4/+7gFPcBK4Uei+6LMV/3xQAkFGezWbR3YGA38DX/EXUc68e8wDJyf8t/rrqGD2ycy2a6x0ejkXZ2diKOQ2c1Gg1JCkajVzZwnRTUdj3kQJakiEcd4CwWFz2WiGuJP9grEEdI2nkSBfl2nwP2FP4XCVAAJebEW7msms9V8SqDpCZgHXvzl/F/N3728jecIc8EgqquQhsRKGkpQDCFHCTya0gKJ5QmYtfX11pfX4/mn97UkIyTK6/xeBzNNLkPdzYZMCpqtVpQp1MHAOXrQNLW1lamxAenBZaC0xDZ+GxcL4mhpIrgqNPp6IsvvgiWg9P7ed75fB5IMs9NU1Pm0x0ZZx2g5AE2fG5Yv/s2MeNzGgnkjjlz0CsNiF1hE7AwJ+7wOqjjBvTq6ip6caDYC4VCBMbffvttZMt2d3czRxTf3t7qm2++Cboq9GgMt7TM8BYKhahBphxNWjbelRb9I6Co4hxBdyajSbNFqPiSPsrIo+glhZEiAwMzizI86rPJNpNx4O83NzdRCse94NR54IfjDCjHXvGg3p10d2juki2X2c8xnDHjDqr3W3C549lKpVLISK/Xy2R4VmVcCEQ4bhUwjqbFMC+RdfYoDjbN/tn3MDMA2wF4BoOBGo1GMCnI5jA8s5QCCr7nWPfJZBLNTgne8vm8vv3222imy74CTHXHin0ACFSr1aKHEtebzRYlos+fP1e9XtdgMNDh4WEc17xqAIJeX1+H7nTmJ+vp6yo9joMJ0NnOjsNZcvvrOt2TC9gFbySdgqH8JKM3nS4abr9//z7AIWl5bC/rhKwRYO3s7Ojg4CDAz/F4HD0jAFhgaR4dHWUa0JNpLRaL2t/f17NnzwKgr1ar2t7ejnV0kIb9d35+rmKxmCkfhnFACZ6DUhcXF+p2u+EkaSX3zwAAIABJREFU+1HIMPvoFbexsRH7hJPD+v2+xuNxlDukg/1PYoc+FKuy0g423TceQu4+Bdh3JgT2OJ/P6+joKFOqlQ4PGmDTsEfxP+j54cyUra0t1et1NRqNOGkOWQJYb7fbqlQq+v3vf69+v59hfvC9t7e36nQ6H/UOoxQEQLBcLqtarUaSz5Mz7k+w3969exelymtra6HrmCsC0tlspu+++05nZ2caj8fa3t7WixcvokE9e4YA7L6eND64/uXlZcgd/9xfT9flrrV+CLmTsrrYdRaBK7Z1NluUOXIC5H1BZJqw8r33/PnziCkoLT85OdFoNFK1WtXOzo5OTk50cnKi/f39WGPsHKDzzc2NDg4OtL6+HuWRjKurq7BrfN51srPgmHeC+263G43AYVVRRn56ehpMPi+H98DaTywj4bi2tqYffvhB/X4/Kj+YP7+HVUllXx+fX0AByuGwy/gN+Cx+jVWy95By5z+xdeg15hYgLm0A7+Ou51tlgx3Q4fXpdKonT56ED4fv/+7dO71//z5TNu7xT5qkgRzhvVwdUPa43AkX6+vrIXfoMmwbQL/HucQO3jMUnY4tZf0PDw/16tUrSUvf3/+l65HO6yodyF5EZ/LsLnP3XZd7+WXcPX5WppL0MSUNo0kg6ZnnlNYOhRMF55shBTLm83lkvg4ODiKjzsZDeTYaDc3n8wiwK5VKNJLFua1Wq3FNNrBvGGr7C4WCjo6OghmVz+fDSaZECcPmYBGbrNlshqNETweMVdowjwAZeiyKeDQaRfO/Dx8+hGOAc8r8ck2CPG8U7kCXB/ge0EvZEoBVmZ3HOFCWzqRhrFJMPJeXNUgfAxS8H5CG7JWXdWJooPt7c1o/KbBWq2XKH7hnFHFqrDHqHBMqKUAt9hGgI84pTjfrD2gDqAB4KS2ZWtxLpVKJzxC8k2G7vr7WixcvdHFxESwUz/hPJpMI1JF15i/N3DBfgFyeSXMnA7l24PcuI/LQg3t0+XImCK+zn1Njzmf8erPZTIeHh5GlbLfbIbOAR17mhvEn6JIWde58D2uCczmZLBobU3LpzAqnzENn39zcjICKwbVwRpCb6XQa90CWHefr4uIiwJzNzU2dn5+HLNEzBTBAWjYp9dfTTPtoNIpyZp/DdE6ReZwOl63UiUhBi3RgKz7H8D5aPnyfSEsZcsYfARcAtn82HcgrDMebmxtVKhU9efJEl5eX0Yxz1XdLin4eXhoyGAzU7Xb19u1bVatVzWYzDYfDALi8JBNge2dnJ07F5L44nhiHGtDak0LcDwmam5sbPXnyJOTUG4GzJ9DPfAe+BAcj4Ej7XuDABb7rU0CXtEEoGeR0Du/yfx5ypKC3Dw+6pGxrg36/H2t632f53YMbWD7oFnwWfD56Gs7nC+Yidgd2BgkaEjntdvujYIv5p7zcQRffU4CdkoJ5STBeqVSiLImm2peXl1EC0u12g+nMwCfGByAh0Ww29etf/1qS4kRZL2txNvFPBT3+fePxOMMQ8PW6K7HxmMYqEIi197WRlGFs8N50H91ne8/OzlQulwOQc1Cm2+3qxYsXUfJKUgeZ84Shn6pKTytpGfDyE3sGmMnvvr7uG9Lbib8TrwDWk+Tu9/va29vLzBvPigxVq1WdnJzo1atXur291d7eXgBVtAJJAbpVwMhdg2d3Jg4jZQY/tpHeLz6Z+0feBsDjX/+MX89fT/W8r7/LO5UUxB9OJkAXeoKX/08mk/Dp/R7xQfnOFNhCx3hJZi63ZExxQJADjcgHcUihUMicLkfMgn4m7srlcmq325l4lwQNQF1KaEjn8K61w29M49hV6/HL+NvHzw4quVA6XV3Kdr/nb27gPMtznyPPez1gk7KnaZRKJTUaDa2trenly5eZPkNk9nEiUA4OhHlZCYDB5eWlKpVKAEjSgq20u7v70TzATCHLi0Lg2ai/pq7fDTvsgSdPnsR8kl0bDoc6PT3NULF9zphXqP4eILIGDHciKHegHOGuTefsJtbiMWxKV77OIHFQM30fTqP3FPG/8X6Xaf99f38/6phZyz/+8Y/66quvVC6XNRgMMg3hNzc3NRqN4vQMghvP9ksK5wSZ3djY0NnZWdynZ9fdSPN39hWMAiigzoBLHWbK0yilRKakZaM8AADkF+ccoK3dbsezXlxcBIvJ5z115J2q7llbB3nTTMpjdnrTeyRgcN0CwJvOzX3XzOcXx1W/efNG33zzTbAinjx5EgAJwIaDlDgo3pgahgcgPqDnzs5OxnGRlOlN0mw2tbW1pXw+r36/H+9xQD9NJhDwASyNx2OdnJwE2w1GAL2VACPQ5eVyOVM6TGNMMl4ATMPhUNVqNYCMlOWWDhwp9prbAF+XNIh5bMPBMH9efndbii1YdeCDDw82pCX4604dziH99ngfvSTcuWSP49gCgFYqlUwfOT7r3wurEzCtVquFM012nwahzgRE9wAGFQqFOK3t4uJCW1tbAYxRKtzpdIJNxOmZ6GrYBS4HlUolk7H9FKYk80eghhySufVyUl+HVev0OcHM+0a6N1IWHck/dMKqz3sg5npkNpsFEFIulyMZSIktrGHWjEa1fmqSM5A5rSlllPke8T3FQD/4Zzily5tvAyrwvqurq2CxXFxc6PT0NErR6J3nCaVmsxmnVvK8vBfGOsC8+2+r1iGdX+6H53B/xpONj1XXrbL7ztKECYR9SBkjq+II/5kO1yvoJpLUMF1zuZxarVamrBGb1G63I+Hc7/fjfvHT3Dd1vzXVzf7TkwT4j1yXYJzYoNls6vLyMnqF+RyksVmz2VS329VgMIj+rfiJ6H4/ifNv9fkB5rzdgcve33vdhxgem0ofxxR3jVWAKPOAn8bauh5ynQizF7sK8xX75vGeg9X89BJ/dI7HDalucMCJ+0cWXI6l5UEY3DesveFwGGAqvoQnK6WFLdvZ2dHa2poGg0HsGxKTk8lEHz58CF8wlaH7ZIc43O0P9/CpiaBfxt3jZy9/Y4Gcik+g6FkEBAJKcC6Xy4AZKfiRDpxHyszY0DRgbbVaUYZBJsAVMzXSNJV1gffNjAPLUbSDwSDu1YElvwenbpdKpQxbo1qtRhPI77//PhgFBPNscozG2dmZKpVKPA/GrVwuR7+K169fRy04jij3USgUMsCGO0wEXr5OPudeIsBrbGgP2laNz0kZTMsu06aiyB+vOWgIQHjX/abKa319PZonw9JBET99+lTPnz9XuVxWrVbTfL7og0Am6/b2VvV6PYKrDx8+hPKs1WrhkBSLRZXLZR0fH0vKlqrwfWtri2NE+W4QeVf8OPIAoQSABEhk+jEQnNq1u7sbMoQz78fA40Q/f/5cnU4nmoX7KYiwXyhH9flkYJQwel7m4BTeVNbuk62HkjsP7N3h8GwP75eWx1d/CkgGiAeLY21tTScnJ9EMcTqdZjKjgOBkKwH++E5kjQwW+onM0/n5uabTaTgwGxsb+uabb9TpdKJJJDppf39frVYr+kwAXErLRub8Tr8J5gEn3On1AO/YBfYEQepwOIzj53O5RcNMjss9PDwMJ/q+QMsBF+6V66PjXCfy+30B1+eWO2TMS8dT+yplS5cJhDzbvEr2XG+yN8fjsabTqY6OjuLwCGyQpCg5gtnjTikZU+8XQ78RwMVcLpcBBCkfphcDz0zwiDPISW/uMDpwTv+n8Xic2YP5fD5Yf5QB0B+p3W5n5IDvJPi/vLzUhw8f9PLlS52dnanZbIYtSedw1QA8AiRlLzjL03X9fbb2c8ndqvI3ZMt9JtheXmZB75dPAc/ToJr5p2Ey1wLsy+VyUR6GfPjhKwCDg8FA5+fnUXbrSRbf4zs7Ox8FP9yT7xUAHhp2z+fLzD+yPp/Po4cTfUVarVaADF7OxnxVq9UAk16/fq23b99mythHo5G63a6k1X6x255Vg6CTMlj3dQEA07VN1/1TwNP/q7GqDMn/hs3DN5EWLEl8rk8B2vw9pVJJzWZT1Wo1QGMvfWy1Wup0OtEXkFLI1O+u1WoRBwC+N5vNKFv3xB5tDNA57iekAC3fMx6PdXh4GAA+vlTqQ1UqFW1tbenw8FCdTifWPX1uTiOu1+sB1uL30fbDAW/Gpyb40I/EVKwXn3X//K7xEHKX7qf5fB7MsxSYQwesKqvyecvlclG5srW1pVarFaf+dTod7ezsqFarqdlsRkN4Xt/d3Y2DTrCdsIFKpZJarZY2Nze1tbUVSRf0mMdBgDjoH9YCP8fXxsHm29vbAEglRYk5c9FsNlWv17W3txelytgD9CR9yZhjdDntHJxB7H4Ohxp50vFTQEj2JOxoLzn/lBK4z+nb/SOOn52pxCCzg0CuUkY4HU5XdwrrTykYMlTUT5O5I8hCOFOACOWLw4ATijJGkN0RAphBgXstqdec5vP5lSfSzGazCNIkxf260fDv5bOTyUTdbleNRiOc45ubm2haWa/Xtb+/H40keWZQYgf0UlbOKrQ9nftVDB6e2z/30CO9D0em/V6Za/7/U0YxvS4KEsMAaFir1VSr1VSpVCJTRuAD86Nerweww99Y416vF2wQDH+5XP4oUAHUos8X5SnFYlFnZ2fR/Jh155hk9haKnCbeZC4ASTEc7A/mC5l2gNFpqdz7cDjUhw8f4tm471VzKWXli+vjEDkN2N//mEbqLLg8+R5zJ9Eb+X4KoCQp+lsRkBD4dLvdzPWljx1x5hL9Q7YagArgiP0Ncw6AikDHdbmDFRsbG9re3o4GuQz0s5esIV/oY+QQwN2z/NDK+V6n+3szZxIMlKL4vH5KICst+0WlDMX7ZPehh9sLaTVN38EWnMX0GulInx0qO83dCdwJQrmu61r2PqAQYDSgISVNBIbOigQI9+au6b7y15xZCbjuwRPfT4Z3c3MzSmP8+3kmWMkwFNbX14P9wnygc5FfZyT+1PD1IPHkTj37PAVZHsvgvtLA3MEY1xF/K/vFM/YO6JBZB2Caz+exTugYADtsCMBCoVCInnSA6S4zgNecnumAMn9DlzIoQfFSZgfIYa9gCwEX0HPsAXoQcg10oaQ4uQyZhh3q8+Pr8FOywh511ojr7DT5+qls2p97rJIf95t5D/MOG/iusepvhUJBW1tbweB1Ngc6ADAIkBJQn7lCp/F6qVSKVgnYQ8pd379/L0mZPSNlGdypT5E+O9dFh/A6ICs2vlQq6fT0VFtbW5k4y5N3DgYzR/S/cfanz5/P/afICOxk9KUn5ZztfNcafc6xCnh0oBmfy33WVffs18DvITHNZ/z0R+wUusRJCxx6wr5lDr0UjmQQsuFN4Hu9XrQd4N5cvlh7973drsHOhP3G/iAh2W63o4IC5jgyz/ry0/uHcT/4FMTZ9FySFIkX/NjUl7lvHbFB6H/sh/uRDy1v/6jjZweVEEoXGILXVe/1zUSfmFUGJHWWaco4n8+j9plMJ86rpKAI+sYGXUWBwgDCaeYzOCy1Wi3YIhyt6c9IwOQKlya3uVwujm08OztTp9PRq1evoqGx98dYFRhiIE5PT0Mpkf374osvdH19ra+++iqUwB/+8IfIeNI7w6nbfD7dSCmIRA0q2TTe6+DZp27qzzkA+RzUSEv1WGNecxT9voGzVygUNBwOdXBwoG63q2KxqBcvXgSrh2zqmzdvNBwO48TBfH5xpDpAEU7K7e1t9LyZTqfqdDrxnRh01vLXv/61SqVS7KdGoxHrgcPwpz/9KdNQfjweq91uK5/Pa3d3V69evdJsNtPZ2VmsMWVKkgJE8hOycKDH47HevXsXMlQsFvXFF1+o2+1GSRVBP5n/VU5RakycNedBgbPK+AyffwzDQSN3kLwUjXliLv2EmZ/SdfP5PNMXibWSFr020qbJsOEKhUL0X8vnlz1qNjc3I8vFvYxGozDUBG0XFxe6vr6OpsjIiaRM4IXcFItFHRwc6PXr17GX6GHHPBSLxWBL8RyUGeH45PN5DQaDyHARHPAdyDvywe9v3rwJcOCn2B3MqzM2uT4ACvqPaz02MJPh+8ETFG5vf8rpZaSBgTuAyDB94gi0z8/PMwASGUEcTi8JOT8/j1OTHIjxEwopH6KPEroNu4NDz3Wn00VT7bdv34b+JFnDvNA8lOPkh8Ohms1myDRNlzn0g5I5DgO5uVkcv05gxV6iZJmTOZkzX5f7RgoGYKex3/zNT9Z5qJEmGrhnafEcXt7AM7jTvmo+0qAt1fHM5draWug3P72Pv3sZByVw2HRAwefPn0fZb61WU6fTCYYZp6w5SOMgpw8PhJEBWHDFYlHb29uZXjYOYkrLcq1qtap+vx8JAgJ65JuArFarRRBYLBaD4ed7YhXwms6vDxJOzvhCrtGBvuf5/0PZ3LsASeTRE2bYjPF4fKcdcMBQUgCWMLi9LAebiM1D15FM4d6wF+geyrmRXfY0uoUTTA8PDzMJcdfVfD/3jFyyBzc3N9VoNOLQDwJ1kpx8383NjTqdTrRMaDabwQj1pJ2zjPHhSB42Gg1Vq1UNh0MdHR3F/Pl+vW/wHvQBoD/PSiy2KnnwkCOVPScCAEwgd91u986YiOsUCouTJfGdADoAT2Aj8t7f/e53sQcBlfEjAXfwjwFDuVa/3w+2Ez5Bo9GIPmD0e3M5ID700kdf61wuF4B0u90OVq+0JF6gswCFnGUMIUNSHBxA7Nzv9zM+DO/xvSgpWIQ04v8pX09a6jx8DfYRYNd9cvdYyswf67j/OJH/g4GSQTg987xKASHA7ih4pp3XWHAMOsrXr+8bwZ2BVegyFFcCZ//+XC4XTgY0Z8AxR4ZrtZp2dna0vb2tZrOpVqulJ0+eaGdnJ7KsABB+2giOqx8R7lkuBpvSlZgDT4B1JycnOj091e3trVqtllqtVqaUz58b54SAPg2I3bnzLB7vw3j7mjymwdr7XKeykDoV0t30fv8dZgWAFY2FO52OCoVCOP44m6PRKIJisqsoW04A42QZ1oP7gHHmwSAKGofA792VNQEZShOZhTE1ny+PYkehQoPlcw4sugJ2kIfvhqXE3DoLhuEOO/PpWUaMWtpThM+lvz8W2fO96aUSDNeHHgT4s/tIP49+Qh5ghvgJQj5ffuojjivfRT06PRfYK8gsmS0yRbA30F3ueEsKZ1BSppSHvQItm/5x3Bu9H3CwoW77SYLoWwbOPEA/cjiZTAKsQk9/agCUAijSUl+kjpS/57EMt6epM4aMAVzz2k89Q2oD/HVpEcB7XwdAfE/iSIvsqpf2AI6iD9FlBPrpuiHbvq9S+8frgPnuZzh9XlqygrBlyCcBQa1Wy7D0kDHYcR708B2wIgA32U+fCnx7oOh6jed0HftYZG+V/QfUSWUvZZmuGu7I3zVfq8A09BVAlgdkyCX60vte0VMJPbixsaGtra3QlZIycuR6gSQHf2Ot6/W62u22dnZ2wq6XSqUAVwnyKHVHzghoLi8vQ7/zPM6iSpksKYiUvs7vPyV/fAd+AzYbneHM5scQ4Ptw/wKABbDCbe5dIwUwvUQc+4ddJCDndWdtuz4CCEZ+2CP4b3yuWCzGCZDVajXT1Jh9z7q47+1/m88XJeicSp3L5eI63CO6moQ9pXyeqMIHdMY6NtCZ6sRC7KU0Rvup4TIKaOdxiVeOuK/3WPSetDz1jfmENcNrd+1Df460Eofnpycc7SLwxbA92C58KOwsvhnXSStSUln0PoHYYv6RpKHPoce7XvnBvXkcySEgrF9aCeT7FRmi1x37AlATINSZUjwbz45u8ue7a7AubvvZJ+g7910fm9w99vHZyt9cwHzhVwWK/hmnFN6XYWBzuiPId6HceV/qlHBt0P1CoRCCDLp/dXUV1yFwIUM5nU6j/MgDLp4BZ3owGIQx4RQw6MuwANiUaUCNYmk2mxqNRhlwiHsiSwzbYDweRyNdTueSlsd/ewmKK3U3HD7P/CSA5T7Z0A+ZOV01/DlcvlIZSz+TMpkYPh84LATd19fXOjw81N7enhqNRvRrOD8/D+XpQQxZfDI/lUolU07CSQiAMxcXF0F55/sxJH5v7hAiF9VqNU6ekZYnMXGiAveBondmA3XQzCGOjd8rPaFQxgAWqzITq7KpDAc++VsKSntg4rrjsQx3uj1A9CweBtuz3OigT8mSpEGq9wIBYHI2IY4k5Q1unDnS2MEiMq4OUHj5Ms+ZgoL+Xjf+PA9yx3GyOB+UA7BfKYm6vLyMTB7XaDQaUcNP6a83cncaP/uYOV4VVKSvp8ARz+G2iM95Nu8xjNT5cZlwOjl/Q2ffNTd36X8G84tD7cFnLpcL2SJQBjynHAXd4GwTB2sIvgBqYB2x1s4odUdRWup1So89AGOP4cQiN8wdJ9t5RhSAFtvPfoAJwB6+j617n55yG+xzjA/CPa7ynx5yuI1FRhxMYu5gV90X3K8KwhhpYOa6heAXP4T+aj4IVpA3AggvQ2J+y+Wyms2mTk9Po/k/AR3fzfozB7lcLgLwRqORKZEkGMMP5L7R2yQVAS/pEYKP6QkWBnvEM+s+P+kcfwqg6XPFvbltYn1hSjz0cL3kiS2AJIJ97+W3So/dJXfoCHxlmnKjM9nvqQ2Usgx59gi6ER/Kk3XIZ+obeLUDQL2f4sqznJ+fR3AuLfU79+LxCj4kwbT34UmBRWkJNvr88dwkCdJY5W+VN67tcudlXeiST73+zz18PfGb3I/2+Vsla9LSXjO/2KpCoRC+DYxa5vno6CgOgmKuaCngzC6XSeTN/U9PxgH4eEkY+nA6XfRNnEwmQZTgmUlo0+aDtSLhl8/nA8T3+8InkJakBsrokMn5fHlqIbE4OtF9Mp/3T5GJVb41a+b3iAy6jn4McvePMH72Rt0MDwx9MVOFjJJlcV158tMdQHcMZrOZtra2ApEn64kS5X48g+2ZVJQ8CgNE2Bs3833z+ZLKPZvNgp2CwuX97nhICvo1QZbXfA8Gg3CgMUiUgkyn02hC7plckNVCoaBer6fRaBSldnxXuVyOxrUe7Pp8c++eBZvNZqEs0vppf0aywPdtuJ/KUP5fDmcZOZjhTBwp26icRnHlcjmOjV2Fertc0suo1+tpMBhoNls2sEXufvzxx3AgXr58maFsPn36VNKyETJsEk7qwLl9+/ZtlNCRYYLO3el0Quk5y439gLPLKXOsM8qfQH0+XzTM29jYiIb1z5490/PnzyP4dOOOUYFC22w2g7mVz+f17t27MBSABOx9roO8AVACLLjRomTBP+cnLznQsUr+PrfcEXw4uEQGxU+f4VnTDM6qEjj+D6g8m82iTp35Yh69UXIqSzAhK5WKLi4u4nQ1GjjSGHE8HqvVaimfX5Ta+qmCkiK7jxzxbB4U5/OLsjWOHZ7P5wF4Q2HmXgiYYO25fi6Xy9rZ2QnZBpiA8Yl8zGbLQxkmk0k05qU08D4AEj3KnmGPeYNInt0dP8YqGfuccsfao8eYWxxbso0E9+50OvgnfQxMrfq/fy+OnaSgzpPFLxQKcbJbPp+PRApNsAHZSeKgAyRFg2ecYeygO3wAir6PisWiPnz4oF6vp52dHbXb7ehb4+WQlPoix868A9DEWSeIdGAMoAfKPU447FPpb2ta6wxkHGu+z0F41pO1S8fnlDv2jLMmSKbhfzgLxwOB+/YiIw32HXh0RgY9p9CLtDvAD3ImB74S6wo73QMqaXmwBTqI+3D2hOvuXC6nd+/e6erqStvb2/E6IPrGxkac4lYoFCKZA1uYPQKoxD24P0wZjAeIyMffG+ygK9AdksKH9Gd2H5F1TEGUzzHQc54Y9cNtcrllCTZ9spzRe1diYZXNnU6XrR4kRb/M8Xis/f19lcvl6IuJ7abXobSwFZ4wcX3GfDp47Ywnn3Pux3Wcyx0JbwdksJFclz2IzmbPMm8kGEkqekIJew7YiC/GfSLLf48M5PP5SGrBWHZWFDqGf1K2mfLnlDuXNaoK8FGZLxIVrMtd98faeTzGmtL3tFwuq9PpqNFoqFBY9FrjJLStra2wgfidxI6TySSAVXxP9ivxIvoStubOzo6m02nYRZ6n3+8HuH5xcRHtC2igfXZ2pr29vYw/67oUn4N5qlQqGSwAf2syWR6O5SWFzoYnKe6+i7RkrReLxTjF/S596KARrUvwO9HBxCXEMzxbCur/MlaPz8ZUShf6rkyKA0/8TuDE/1FsGBEcFaf1cw1nOjmQgjPLqRx8bjKZZBB76lLveobUyeZnmtnBsPnz4PiDwvJ3GjV6FgADATgAHXFVgODzNRwOgwXj8+wKzQ0X9+qgmDcS9nlgHvnux4bico+ONq8CIADxXCESPKaNsZlrKO2APazl9fV1BECcOkXwQgBdKBTiVAaCKXomINcEOfQiAsiRFk3dCfihTXNvDgxiPM7OzsKIAHbhLN3e3mp7ezsMIEp0Pp+r0Wio0Wjow4cPWl9f18nJSYbxgAMHw86zLjD8NjY2tL6+HsdAp5kFv2+UPWvi+80zZJxc51Twx6DkPfhB3wC8pQ4tf4NBxrp5dpJrosdwaNL+TB5kw9CsVquxjznt0oFH5I3vbbfbKpVKGeCT63rzQj+RCxng/Q7C5nI5nZ+fx3XQ267HoYrDmltfX9fOzk4E9pym02w2I3uGLnaKPntvNBpl+vDxD13v+t8Hzra0ZK16uYnLIc7OXQHKQw0P7HlmZ435/XtQfBfjgPf4//0nn+caxWIxnDNn+EjLHkC5XC7ASuQOnelBYrFYDHvFmvf7/TiJieH2lv4vkqJkEiDJGXB8L8H79fV1AFicyMnfyJA6E8sZIzjoBEPMO/OTzmf6uusLt8fuwGJjnW2BzX4MvW24J2cue+9G3z8Onrv+v8unSgN991copxyNRhnmJXKE7uO9sMnxEz1A9iQAvmMutzhJ8ObmRoPBQO12O/6OPsbX4jVsJ7JCckRaAgbIPME47wOEYy7Q2ewPaXU5lfvLPkcub6tkj+HgeGp/AGy9PMl9voca6B38DHwmB5CYd8C8u4bvOx/z+TzdfpppAAAgAElEQVSaGjP/zkgkkPf7YZ9i/z1R66xyTxyldpGKB9oSkFTH7uMX8jlkwWMFZAw/MGVqpfEUz3B0dBS+PuwS/x6eAd2U6vfUZ7trrv3/fDff5f27HDhDtzoY8zkH/jRy5X6CtCyH5XeS8fcN9AcxJz2RIBAAdAA8OtOXdWSNfW4Asrln9APvYb+4/1goFFSv1wOUGY/Huri4iHgBH5VYSlrYLSph0n617m/w03WNpJB798s84ezMNJh03k/O7QF6Ko1vVw1ed9YTsus9QZ09z/c8tmqcxzg+G6jESBX4KscCwYVanp5CkC6yl1P4cey+4Z3ehvJCiHyzuOIoFos6PT3N0PlQrm7Ei8ViNJN1RcjwQMh7KXmmqVgsZjJvZJQBHdITanK55alcOMTupGJYmAd3BBxsSwPT+XyeCcqYK79nD1p4D9d5TIEW94LSSDPyKThGk00MM1lYjKrLH4ZdWmaWQOWROxoPA+588803+v777zWbzbS7uxtziuPL6SHIdKFQ0NHRUYbhgsyjgDk63p1d1oV7HY1GsY7Mh9cMb25u6tmzZ3r//n086/7+frBBeHZ3gJAfwB2uC3ugVqsFmMX+JOB3qi33jAxyLZzttBcKhhwH56dKKh5iOHsKUPYuR5y1cFlK2Urp7+4IuyEm0JcUx/+ORqNMCQ3MRYL1y8tL7e/vq9lsqt/v6/DwMBPgp6DzfD5Xr9fT06dPM6C5s6a4/+FwKClbUurMTfYQoKqkaEQ5GAz09u1bdTqdOPXQQVzYU1KWcYgjtsoB8vtwXcWcEfhiK5zV6DrkbwnaPsfg2fjnes31FraKdcKBclDW5cqD+/TZAMqxuc4i8Xl34HEymURTV04cJAs5Go3iRFMyrdhL2G0fPnwIJp47lO7AAjKUy+UIprDXZCdhrHKP9HPAhnsJqjMV3DnnOz0r605zGuTft3Ywl90hTssnPKP7GGRu1XdTosh6+1yhs1Pf6L7rpuAS60UwD9PHgzt8JWwHwB9MZO/r58OBCGwKiaHT09Ng3TpwS8KR76Y1Affsz43uwG/CbnKIAjYCAMf9EkAqfDMHqFJw+2+RC18H9wddF/g+cZ/wocbt7W0wbP0ZAYI9YYVPh867a6TyyH4GMMdGS4rgfzKZhF1ibyJjyL8nl0nYOZAgfVzJgE4EBOekP/Qkz7i5uRkAELLhbQqQPwee3TbjRzpY1G63wycolUq6vb3N9LdxhhP63MsLf0rmVv2dfcQa8j78RGyVg+wPMYhH2XPEQACZ+Xw+Kk8YTkjw4X4v64b/Q8IUlh22FRtdqVTiwAhiPz/MykE59Im0nDcH8JAD5p2G16w7/gFrxEnWxLkeT7gPxrV5Vp7TWaPuKwJ8uS8JWxPAKpfLRXIA+w0mgKzyvp+KB1yPod8coPUEBb97zPzLuH98tvI3H3c5FY5Qe4NDFx4Ud61Wi7IdvsuVEgKAk4lSBaghyC6Xy9re3o5mo71eT9PpomfMcDhUr9cLZ4ifOC0IMgZsOBzGCUc4mdPpVL1eLxpn+4Yol8txUgxlAY1GQ/v7+6rVapkTJgqFRZ0tXfrZBF6WxD/P4KJcuDfm2dldzCn3h/JwFkHquDgg5g70XeNzOiLInRt0v7f0Wfh7vV7PGFwcC5cfaWlgcP4BAilTRF45ca1cLms8Huvrr7+OJrDINdnyDx8+hFzRsLHb7erHH3+M9eW0Ij9e+uLiQr1eT9KCPYWyHg6HOjk50fv371cGj9VqNQOQlstlffPNN9rf3w9m23y+YLq12+2gllar1WAMwHgajUbqdrs6Pz+PJvEcxYvzBZMEo+FrgrFmnsnOTSaTaCbtMpYCKvdlTj+n3DkQQ/DBnkr3Bg6ay5gzajzzRMYJ6jAluQ6qSIv139raiow5p3IQyAN4wr5w+v6rV6/017/+NUO5X1tbnDRILzZ3QrrdbjyvA5ScTPnDDz9kwHc+m8st2Crb29s6PDxUr9eL7BtZZcpbdnZ2AjDv9/u6vLyMTJ6zCwqFQsgsToLLhIMHDtgR3AHo4/Szj9IMdwrAu35dtb6fa3ifNQdp6ZsgLXU25T7pfrorkJf0kTNFkFWtVtXr9cLx4/Qqynxg0wIg5XI5nZyc6ObmRsPhMJzEXC4XJ2Z5I1l0Ar21ptOput1unHhFNnY+n4eu63a7mkwmqtVqIeOSIjGSz+f15s2b0Kfj8TjD5Ox2uwEUkLGcTCZxD9xnLpfT9vZ29EekLAadugq8TAfZV+TVyy5xqv29zD3rtiqR87nlDpaGO/P4RJLCX9rY2FCpVIr+gx6I+HCd5695UhDW0OXlZegY37vr6+txOlWxWIzDL9irnAiWy+WCBTmbLU/vYg3X1tbUaDSixP3w8FCvX79Wt9vV8fGxDg8PMwxiwAZfE5dTZ3bAwGw2m9FgGb1Xq9WiDB+23Xw+j+QQ+i/1/1LAm7njPlYNntl7pHggit/D/vVk7UPJnZebXV9fR/DtQCxgnaQA4pz5wFglb9IygezJU1oNNBqNKOvlsAG+BxmkpQGMFdhpgDH4jMwhckSi2Fl26J2jo6PQjYDmGxsbmaQicuBJBvx3D8rxPdy3qlaroTf5XhLcMEFI2vBdt7e3Gg6HmbKjnwKNmV+//mw2C/n2/QNjBNZ+6kt9LrlzYFpSsHi4n2KxqHq9nrG3klb6BtLSprpcDQaD8OHQq9hWdK2z8/DpiA+RY1q/AOSQeIHpBKvX2cwO8iA3gLeXl5d6+vSp9vb2Qk8gY55E9+QcQKv3ZuI9rsP8er7mTrbAhwa4k5YxMT7d+fl5JByZ11W+DP939t5stjzZkIFPxfyk1QYPCaw/9vGzMpVQkOm4C7FOf3cjQE00jqZvZrI8GAKy2o6uS9nO+AgFWdDr6+tMuQYBBYgxDoy0UChkVZ0pMZlM4khHhJIGyx78+makqa477qenpxE0YSRSJgObEOq/ly0xdygfaJUeQLDp0kyAzxdr+Cmg0UNmTFeNuxBrd3ZT44Ti8sDAsyUYegJvFDXXxXHBWN7c3EQGYjQaqVqt6ttvv9Xh4WE4asjFxcVFnBBI2Zg7QgBZ7vDxDDc3NxGswa46Pj4OJejAGUE34FWpVIrjZdvtdtTWk/Xn+SaTSTgdBAgAasgIR9MDqJVKpej/hdIm6PU96Nkvsi+U9qWAkQOaKTj1GAZz7JkQ3z/u5Dtw5IBFCn5IioDTM3gEvNJSp/Bd4/E4dAJ9HTjiFeei1+up3W5HXX2j0VC32w0dKin6xzjQVSgseuC8fv1alUpFT58+jYDj/fv30e9LWuornokAT1o2rkevz+fzkD8yz+ius7MzXV1dhWOL04I9SEuUHDR3GULXeVaMfegOWxo4eSaQ+U7X96GGJ0wIgO66LxzRQqEQBz4wRykb1YGqVUmF8/PzTJlFLpcLuXGmLM4fOrbf70czbO6DOUemuRfPZAKIchAFCSNKlHC8YRO440dml2sin/TAQ594Lz1Ywv69+Xxew+FQrVYrA56g/5En7ENqb3xP+5rRi6VYLIYf4mvhgAG60vf/QwwHGqRs7y5GmgRI99squUp9Qfdb6EsjKcrTSIogI8wla+J2B7tKIoP3+9yyt9EVfI6kCDqAvoroRA/OkHmXZfSLJ3g8McBz0zuFY+gJarhfniuXywUA7iyA9Hp3DZ6V+5eyJ+t50MW9+rw81CDJwnqnQJcnMJx5etdY5RP63DDP2CiASQBmwETigclkElUHLj8O9vAd3lqDZCSvAXSSlCuXy2q1WgFAMpx16jLgMuYMd/xT/obeYrhvJi1lguekxBBfMz192NfJ59fn2NfHY49VMostTxMgn3NgI2hZ4XZCWvbgSksBV4275Mz/xn5nftzvkJagBqXj6fXc50nnFD3F8GQoesABWuwpsoKug51HkptY1BMgPkcAYNwT9jhNYDnjlftlHzuYhL/X7/ejr+GqJE76f+Sf+1xVxZKCtOmz/DLuHj8rU0m6m61010CQcELJAroTjzLDQXZlPJ1O1Ww2NZ/PM5lmFBmURBcUTk3DEQTdh8pMoMdmZ5Oj7PkMwnh1daXhcBgZWzYISqJarSqfzwcLyrMKMJEkBUqMM04QxsYk81CtVjMlgigUDBxBHc/uCoWeUu6UeAaFEhZfm79nPARTKXVSU+OW/oTtUK1WI+BC4ebz+WDOAXpIS4VERt7ZbB7o8752u616va7BYKBGo6HvvvtO8/lcT548if5Ea2trOjs708nJiebzuZrNpr788kttb29rMBioXC5nsvcud6PRSIPBIJ6XNcVgFwqFaDDOP2emXVxcaDKZqNvtSlI4UwBk9IbyzNrJyUkwFHA6AKRqtZpOT0/V6/XC8Hr2k1IGAlI3XvQVWBVorApKVo2HkDtpuffuy8gTZBCYsDe9x89sNlOz2Yx96jX1rD2ZS2THAz329sXFRQDet7e3ceQrYE273Q5a9fr6ejBQCNBwHFgP1g9Z6Xa76vV6H803eho9tLu7G/r1+Pj4o1MP6/V6sOyGw6EuLy91cnISWUF0Og2YYdThBKFncZhJOuDEeC8ud45chwOK+t7yYM1Leu6Sr8/NGCGj67ZiFahBgEGz/9lsFj3ReC53crGJDP5OabrPMyVE2BJnGfsBEuxdmiqTWAHcxBZiO9E9yJIDZ7D2YH9K0u7urmq1WgRLsEE3NzfV7XY1Ho8z7Dh6mLgNhw3MKaowrwjeYNgR0DF/vuc9EcQ8+P0DZhCM4PM4qMTwYJPP38WA/FwD3c0zeRKEMZ8vyjvInjs4nbIxpdV9lPD9ABNoXAsjV1qW+2LH0QPoSlhL+GAwPACYSMyl94CvhO2bTheHcFSr1WCFspY0ogcgcJ2OLWONAbad8Yw/y+fH47FqtVoGNAAMSNmaq3TRqgDLnwu9AVvE++W5z+RAmbMUXL98Trljb7MWHgBLi+fm1Fx0Ar6Jy5kDiamN9t5IzJGfrgZr3FkkrA3XIqnG93nyTMqeTIlOZW+TtCNm4TtI8qCXYWE5M9IT+dgzB7r5Lu6NJAN/Zz4J5LkPB4JgFeH3Sn9bYpk9uL29nTlUw2U2rRBJ5VL6fHIHUAjo4b1WpSUjs1wuR9JNygIWKVjBWpOouLi4CEYUz41+QQd6o2x0aK1WC7nyuWOtJWUayK8CnFzWvfqG192vJJ4kcQMA5tdELwH4o/c8jsd39WQEOhqAiOdirtx2nJ2d6ebmJpJbq2K6dI086cQcn5+fZ2QXOUcXE/P7+AVgunt89iLBu4AJdyxwjN0pQ8EhaM4YoXyhUqmo2WxmSlBSYUdBY6y5Fk7jcDjU8fFx0OC5B89ySgoKPw4MG4nr4yT6yRQ4AyD+nGbDJuG7KKuDIUUJmiPQGIJKpRJlgA4WcV0CqVKppO3t7ThxzJ1bB5TY1JI+2kj3rd9jGmkd8arsRgowIS+SolyDwAAZq1arqtfrEeBAy8QhxClAEbriASAl2zmfz3V2dhbvr9frur6+1tHRUfQxIvir1+tBl6fZN6VQHui7Q+jPDAggLZ3jUqmkWq0Wp4l51vTs7EyFwuIod5wzGgailCUFw4oADCOBnB4dHUV2HxljT5Ip4P8AKdx7WkKRBrbpWj5E9mrV8KyaD9bK9RzvcYaWtHT4KU9zQ+w18axXqVSKMjYMMgHVcDiMAIh1JJCnj8zFxYVOTk40Go0i4w9TiJ52MIGkJdvHg+hVMicpyhPQjzhmMKk2Nzczpb446jD+cFwoNygUFiceMi84tXwP10iZA8jW9fV16ETf92nm9K5MPGv3kJn6dLBero/ucnr8b2TPJWUyd8gfjmQK6DLYu9gzdCb2D4AZ28K+AEz1gGo+n0cWGNlxm+g0eQfyPSvM9zjwie6RFoFlv9/PMJ4JojjNx/u+cU3kEb2EfiYZhW13ZrSXzRBw4BMQ1BEoMf9c4y595kCmg1cPObwE4a7sPEEITry0DBhT+UqHB2EuV/gv6AAPvD3p4MwgfhKc85qkzEEqyK0PZIH7JknHd6A7AIaQVWed8jvv84COzyEjDoC5D5ICIbPZ4sCDdru9cj7vmmOCen7350zfiz70/XUfoP5zD3QAe3jVQF5INOOXpMMTbqmPwfoBFDLv6E3vmeNyjewBOEnKJHO9TMi/F5uKnMEgTYNkL/F2oMhjAPdnHYDBx3fmC7rKbbfL2qrYi/enTHK/z1Wv+z8SE+yj9Dm9IsNZWA8Vg+Cb3CVzkjL9cF2/pM8uLdefahb3dz0Zh2z5OnuLldT/cpaTz+UqBpOzlrw6xsvD+G5neKMnPVHgzB8+wz2jU1N/jL3iz+wVPZ7Ud3wAWUgrAfzZ7vLB8Vm411SP8f/Un7xv3X8Zy/HZZ+mnnCB35KSFwQPpZHMhdGRuKpVK9HqBdoqAk6lASZMJbTQa2tnZ+ajsy6mEKDNqQ8l84jRQEtdutzMsI6+bdgOTzy+65R8dHUmSOp1ObBiCAkmBeCPc3gyQvhPtdlu1Wi2ukdIjuU/qYkFd3TFn43mWw/+fZoAeU/D+fzk8EAH5docfI7+5ualKpaJWqxVlbawLrAmCs9lslqHCkt2mz8j29nb0S0A2W61WlH2tr6+rXq9rZ2dHjUYj7of15ph4Z1eg6D3QJ0DM5XKqVqtqNBrB3oB1hfydnp7q7Owsspb0GxkMBlEyNZks+hydnp5GfxNOdmN4yQjHkDYajXD+2aPs53K5HFlA7ttl7y6ZcyP8mMZdAFi6f1g3wGFYN54JQj5W6UV0FvMHKwPgwB3/XC6nWq2m+Xwe/RkAqgGtnQLtbBD0pd+f7w8cWw9O3MnBOa7X6+Fkj0YjbW9vq9lsZoDG0WgUgSC9T9gzlUpFBwcHAfzAUkHmvSE6DiAsGAdMcLh4DVDTnZoUoEiBwPT3hxysNcDaqjI2SR/pCZxfQBR0AaAb84Kj6dcBRK/VasEC8WOsHdBzZ9odNGwxex6WE/rSM5oeXOFsci/IKe+hVA0Q8erqSuVyWefn53GaDdlRP5GVn8gLdt71EboNVp+kmLeU1YXznM8vWK6NRiOAD2cuMS8pmJnKGvMOI+gxyJ/bzVWgUhpA+d5zX4v3pv/QQ9hI1ldaggtp2bm0LLvF9iEb7H/0GnKUlhK7bkbP8X7Wgb87wOPPg/yen59nmAsw0/BrSQghRwR/nk0HXHf9Np1OM+XCviapTVwV0DtwxRytWj+Ct1QvPtRg/tiz6fj/7L1Zcxtnkv19CjuJHSDBRdRmh9t2T8x0TMRczPT3v5uYmIu+8DK2W5bEDftGgiSWei/w/hJZpaJkWxJF+q8nQkGKAAq15JPLyZOZPAsYJZ7xw7Vyjxg2kPQd3rfzIDiy5YNjvtczKrzt9fLlg1YP/MT7qPFa/H08e4A1H+94EMMH33wvMhsHAXiN1z0gwXs8K843JfegBz+TwE1/Xb7NAbrPLy930mYSoQe/7nrF/Qa/vJ+AL+HBi/i9wA8mtuSzSbFY/Jl6HeH9MOwUyT7PZsM38OCdj/W8LOCvccy43cVXYy+gA5FJH1N4Geb4nBvH9/uY++jBL6+nkVGW/7/3OX1skCR7PMskXeZ9XL6Dz963WOM+rjuf/uaXRxPjASLBQr1et2CWDLdnPdzc3KjRaKjX61l2AkozTTrZBAgLAvXkyROrzaTPQyqVMoohQZ3PlmOICNZHo5FN4KrX65EshM8crFZrpsrx8bGePn0amSoDKwH657fffms0yu+//95e7/f7KhaL+uabb4wlcnp6qvF4HHGycTwBn3BuBoNBpFdKLpeLfNaPTMVZY90HB/ZjLO+ATadTYwABADI9y/dogHKKAqXZ+/X1dWRaIMfNZNYNOF+9eqXvv/9eL1++1JdffqlqtaqLiwv9y7/8i46Ojky2CKxhLwEGUdaGLMCaYvS1z25Jmxp1SqMoS2s0Gnr69KlqtZrq9brS6bRevHihH3/80XqTPH361HrwZLNZ7e/vG/jw3XffqdvtKpPJGBjhx4YjP4AIuVxO+/v7qtVq1lCPfQpQinFkbyZR2pNk8L7J5btAB2+UcHwvLi7U6/WMycMgAQAZAOdsNmtUcR9oeUMNIIWe9M4szwKjTxP3J0+eqNPp2PNE31HW8/jxYwvSh8PhG6xJdB3fh6FHLnxj916vp263q3Q6rf39fZVKJf3000+WXaOsE0Dg/Pxce3t7qtfr1v+Jsjje4x06dPxisdCzZ88kyRoze6YUSQIcQO/Q+4EG/vre9qw/5fLOd9Jr8YyjJGNe0mgfewHoQUCGLsROApKgA9ErlUpFV1dXKpfL1keNexp3HAkMcKJhS9IzjHLaRqNh9olyC64BOy5FR3Rjy6fTqba2tqzs7fXr15pMJgbgkhCiOTwlNZwfwKVnvRJ0+7IVAP7hcBgpS6Z8hcXffYmMtOmbwr71TXD98/K/38YIuuvlGVw+WJGiIBi/w8QJw1Cz2UzZbNYaGvt+NHEdyUK/MaGVcjOeF4AhfUYAmChnxw5zLGnDwkmlUiYTPnDz1wKzk/PC/nMc3iutdQjJQM6bPoM0QvbMQpjzQbBhLngGOraApIFnUpHI9D0Xk+wlf6Ndgme8IHv+GvxarVbW3PxTMZT8ufj+gEkLoBmwfT6fq1KpSJK1NsjlcpbI6/V6b+wrD8D56Ws+0YzceKYnMgEohf3mfjNlmJJLD9Z7XYsOQv5g7qbTaSuV8kBEHPBDB/MZwCAAf2QGne4rIjgeNlbaMFuXy3UDcvq03gayJP0Nf48pnNzzt8Ua3o58SoZcXEf7hQ5kYANgJX+n/NKTHZ4+fapMJqN//OMfERDPT0gGtEGOOLa0SZxhp7HbxHvShgErycpp46yodHozZdkz+tCrnk0EuEp/JA84SXpjWmqlUon0KvblawwL4vUgCKzliwf7+Qx/x79DF8XZV0mLvVwul5XNZm3/+Knp3u5i+7EH/h59Xm9fnxRU8o5H/G/SxngA9HiHAyFfLpfmsNFsu1KpGEBElgIjgGPMaE467W9vb6vdblswFASBDg8PjWHx6tUrO4fVamXZ2VxuPWnk119/1cXFRaS0AscEgxyGoZrNpkqlUmRSTKFQ0O7urk21wUDhNK9WKzWbTbXb7UgPJILM1Wplf2dhvCRZFtE7yJ6uyzlyn3z2j/dLb6/R/zMsP1YY5w9DStkDDlk6vemNtbu7q52dHZ2enkb6VmHEfXYFR/y7777T8+fPdXV1pdPTU7VaLQMqM5mMNaHd2dmxgBwDHIahhsOher2earWasabie0faoPzj8Vj5fF57e3sWnKdSKeu10+12zfG/vr5Wq9VSJpPR2dmZWq2WarWaXrx4of/7v//TTz/9pFarFQnEOTcMvy/dAiQiEMBASBuWC8YNmY2vhyZ3t51vPMjHAQAo51myv9mT7HmfHfR0YmlT94/R9eATy8vv0dGRTk9P1el0zBEmQKF0AIc8n89rNpvZ2Gx60CQ5tJ5hEASbCUvFYtFKPguFgvX2+v777835RT8HQaB+v6/VaqWjoyNzpMbjsQWVgCk4O9xDGoUDqJ+fn0fOyTul3EdJxozy4MXvebafcr3tnOIyx+/dbtcSJyQU/Ahunj/OrQ+0YcfF2RqSrETJO7Tsb+yn12UwiWDd0fC/VqupWq1qMpkklnvxu8+yomfQ2/TawTYDOhBQpVIplctlkxmfDYfFxH1hrwHg0wAfFqfPcCJncQYI5wpYgA7lPv0ehuanXgRM0psJwrhzz/MD2IEpViqVdH19rUajoel0ar33WByXIMv7JHHABtnxpbpedgmYYaDBeGESoSSbPgk7Bf3mATSuh2vyrFD0ie+5SLA0HA4tyUNAdnl5aWAbwT7H8foVmfSZfOSLe4Qs+mcibVit3Ef/Pv52G3Aef973Yfl9mbS4lnjpIfJSLBZNr1HqjzzweW83vawCHPjyac/28OwMnpMPpD0Y7UFs32oD3RBn5wCQIRt8T5zJgq2Ls5p9DMT78Bm4r15Pcy5eFvk78o/v4mM5/9MDy77En3vGII7bbC7X7cHVT7UAir2cSNFyPdhX7GFJNnny4uLC9txyudR0OlWtVjO2In5enCHJ9+HjxIFG7KnvtcXinJBD5AAA3V8Ln+V92C1sJQu5gwXO3zzDmNc8Y4rEFfFUGIaRBB7yyz3gvvBdfI9n0rO3vO3xz4TlAVvATM7TL2+78H+wJ/dF/9339UlBJSkZWPILFLZcLpvAeQUHmISg+0xhpVLR6empBasIIWjoaDRSs9m0oAfggIlYOzs7kUAnn8+r0+no+PjYNlsqlVKj0VCxWLRmxX7SGgHU1taW9vb2FASBMUtwaL/99ltls1nVajWNRiNrnApSCloaBIFlqXBGQa5hJ+DkeAXOfaQcxAf60MN9MOc3txR1GP8osOSzaPdtecVFE1fuibRRUGQeAUw8so+S9OwkPsszIRu7Wq308uVLzedz/fu//7v1JYKtRt+bVCqls7MzbW9v6+LiQoeHh+r1ejo9PbVGyzBcfMZJUoSNAUDx7bffamdnx2QpDEOdn5/rxx9/VLVaVaPRsIyvZ7bt7e1pMpnoH//4hwXoOEd8L3sBwNY3j18sFjaxCcfZU9iRDeTcA1QPaXGf37W8zgOwQS7ijVu9M0ZpJp+v1+va2dmJBP7e+AJ6+0kty+VSzWbTwPdMJqMXL17Y/segFwoF+/3s7Ey7u7vWAwHHgIlayIJ3iHDKC4WCOQ7FYtGef7lcVqPRiJSy0HAZRl0Yhjo4OLCAC4cKR8I3SJY2U0JxXrgntVrNwCLvtOCccN3seQ8C/NmAdK5/Pp9b9pQ+ayQ+AIT8VCzkE6YHThogMI2EpU2/HHQCYKi06elE8Oz3DN9JGWSv11Oz2VQul7NGx56RyzlwHOw7AWKxWNTW1pax8HxghRPtA0+eMzrIB/kEcciM76NDTyauj95QPvvswTrADd+MFHmOM3Ue2ko6d4IjyqHr9bparZZNufVZbw+68bx9cMozkWSJG4Jg/+EDHwgAACAASURBVF4YJLDfSPbc3NzYWG3smJd92EQADcgC+o5rWa1WFjzCLAC8IEj2Abln4MJsAYwiWYnswmBBLtGRPtDnPqDTkTuuk/vny3VIUPAZv598oPq2dR90YRyASDpvgmnP4ETP+3sGyIZ+8MfzxwSoRn/55tUAK753Kn4P9hg7iV7xATOveXDAl/2ic6bTaeR8PWiIrEmbfYGMxPUa8gPYgBz6hKhPYHmZ5ztIDnKe3FPkSYo2TMZX5lzxNwqFggaDwa1yFT/Gp1ww9TwA62UEGUD/S5uec7VaTfl8Xu122+4bAGexWIxUjHhd5u2mB9aRCZ6J94OkDelisViYL4f+8aWjyAe2CLnxPhD9L2l/EJcnL7ceeEylNr0zPYjkkzvIDPvN+w0+IeOT5J6J5X0/KaoLfCIHDMC3REgiTvjf0eH4r59a/h7KunfT36ToRmWzUA7kBVTaPHg2DgqOTCqZbS+UILU3Nzf629/+pvl8bpO2Li4u9Pe//936JDHRCGFvNpvmYBA4sdFgLdFIttFo6ODgwDLyPkgk2/n8+XONx2PrZcPoWpR2Op3W5eWl2u229WxqtVoKgkCdTsco4DSrZTNWKhU1m029fPnSJt5gACqViimCer1un4GZAwAQV57vu6k8Q+Bjr3fJnVdifpGV4t6Xy2UVi0UVCgWbCOXpr7lcTufn5zo+Plar1bKJRlCtfR8IWCR8x2QyMVlstVqqVCpKp9ORaVj5fF69Xk/5fF7Pnz83JQfYOZ/PVa1WjZY7m810cXGh8XisdDptcri3t6e//vWvKpfLFqT3+32FYajj42Pt7u6qWCwqlUppf39fs9lMT5480RdffKH//u//1g8//KBXr15Zxg7HhmAJZxzA8+DgwBzp4+Nj9ft9K1midIX9zD0l0B+Px4nK/o/KwX2QuyR581lODC2AOJlxZDGbzVpfo6OjI/3tb3/TV199pcPDQ71+/TqS3cRZyOfzKhaLVgrnAzhKl4rFogE5w+HQHHEyaPP53ILd3d1ddbtdVatVzWYzOx/f047/w1ILgvU0Ji+b+/v7+vbbb/X999/b1DgcCRik6MZKpWLTTVKplJUwAVTiHEiyUq79/X01m01znvr9voEA9Arzk2ZqtZqktayNRqO3ZsF/67oPMhdfBAgwCZFHSkmwD7yPhIMv6+AfjhrlhDitHtxMYkKQ3eb7pCiTlsCXARUw27755hsrj/QZf84ZvYj9Z5rh+fl5ZIrLzc1NhHXE/SCY4jxxPtlXsFu4jwQLPhhkn+3u7uqrr74yGwA4x3s9Y65er0tag3Iwst7H1n5Kubst+bRaraeeYvfw0yj1xfeglBy7ks/nzZeiMa0PYmCIAXpiO33gwvNGnqVN1ptAClAIXTeZTAyA4j2DwUCj0ciScsirv6bBYGAJImSa60dXMTGYPnG0OeCeATrhV2IHOMZisR6+4Blx7DnY1fiifgItwzk8K51SEK4vzgT8Pesu5Y79I73pH/h74m2D71eVSqWs9Je+cdhKhkfw/H1QSQLNfyffdXl5aa+hG2GteUYE8sZ5YJPm87n18vQJGnTNdDrVycmJAYwkFT07l6Ce72IP8X34X+h1ae2fwkZm8iuAGNfuAXbYUjDpARH8vY0/F2I33/yZsvgwXA+s+aP29q71nddv8Tg1DEMbqEP1i2ek0f+XJv/0uIQoQEmwJEuIIEvcW/xl3yQe3Ucy0IPtyBfyiM7i/2EYajqdRvQwtlJaA0qnp6eWpPFtZBaLhZWZo7t80scDlnyntKmO8eX13MvLy8uITwwwxX4g8T+bzSLDWTyITtxBwgA/lbinVCqpVCqp2+2+McXvt667lLuHtu4FqBRXKDgkHqUm2+MbqkobRBZAxCOxOBUoXv9+aoKfPHmiq6srvXr1yqjPKHkCJIwwAXS1WrUeEoPBwBgBfC8OMU4DTpC03lCj0UjZbFaPHj2ybHEqtW6Gu1wuTdkMBgP98ssvGg6HEYQfo4hzIsn6WNBMulwu6/r62sAy7iPKDlofpQp+c+FUfegswX0MtFhxA5HJZCxIRklxr6VNZg8lhoLzmX6fCcTgYESQr1qtZvL5xRdfWFBFfxOyrGRAh8OhZXh2dnYs2yttADH6B+CQMPq42WyaMbi+vrbsP0avVqtZacK//uu/arFYGDPv6urKJifRRBq6LUEZrMEgWJc8LZdLK0n1skR2lmaFBI449h4Eftez+i3rPsqdvx84bOi21WpluoZAlGC8Xq/r+vpa/X5fZ2dnGo1GCoLAMl1xXQmDkd/jWSr+lk6n1e/3LYuDDBIM4oBQi07wSzADeOpBgXR6M70NMN0zY37++eeI40oiAPne29uLjJLH8eX/OEueeSfJpmqm02mbbofc+yw+Tq4/Ry+rSc/rt677KHNS1NmrVqvmiOJ0cX9JPqADJaler5szDUPJU+59tpN/PBfur6fbe3AF3UGCBDAgCALrh0Myhc/dxlza29tTNptVp9NRuVxWtVrV+fm56WZ0ls944m9wHd7WYvv992IfsO0EBjjYo9FIrVbL7h/+APf/5ubG+vdxvXG26x9Z90nufOAFKI6fw4J9EWcHeX+KhGE8g84eDsPQ+m56cJ3z8+UbBPXYYAIwWLR8D6PqATKx756JgR4h443viU/H80TfwmbjeknieLmkRyEAGrKIfPGTPcO9oKyQfqCcGz5fnJWJr5lKrUvgAZYfSnAfX96eSpuyR5LDyBz+CX69jykI1LFHyA1JDv8Pf9mXhnmmiWcSxQNnDzR55tFsNjMmMufHs+/1ehaX8Py45/hLyBKALdcLqM5rPhaCGYefgd/KeQNq+uQoiVOfOED3xoGXdDqter1uAb0k8x8zmYwuLy9N9v7IumswM2nFAU6miALc0sMLu8FeBEAGzOY7PHPXJyORV2/zsD/+fbzuQe247fXsn5ubG7Xbbeu3ip5bLpfWv5K9gM0CDERmfBzuhzZ4mYozNn3/QGIpnxgilvbyiS7md/Y21UYMr+KYPn7jbyQc2u32b3rucQCRe/p5Ja9A0kfldL2rHCQp4+D/xu8AKdVqNTKW2itUlJq0UZiHh4fq9/uW4WYDMhntiy++UC6X0z/+8Q8DDUDsS6WS/vM//9NK75j4Qh0pwfhwONSrV68scwmyGgRBBB2GnfH1119HKIKg1uPxWJlMRj/88IOxkAh8MHzU5f7bv/2bcrmc/vd//9dQ5t3dXQOVJpOJZc64p9wbzqXRaJgDJG0moJycnNiz+JBMpbssf/stZUjxFVccuVxOz549i2RgJpNJpA9GpVKx0qBffvklIq+53HqCG4236cExGo2sefDXX3+ter2u5XKp3d1dLRYLmxJE1qzX6+n4+FivX7+2oHwymUTKxnCOYITwu886LZfrpriZTMYadGMItra2VCqVTBay2ayViMJ282yiZrOpYrFoDmkQrGvGfQaQ7yejQv+v6+trNZtN6x1Vq9U0m800m83U7/ffKEd533Wf5O5tTnsul7PpZuVy2e7hq1evzBHJ5/Pa3d3V69evLTvK+2FE4DzAwCErnslkDFgE8KHUFwDwxx9/1HQ61VdffaWrqyu1Wi3rO1GtVvXzzz9rNpupUqnYcxsOh5Ki02UkWZkHQDzsIgLF169f2zUWCgXt7+9blj2bzdrgAxywq6sr/fDDD8byxMHGQcdxARTHeXj06JFOTk4i2WKAX5o2c588cPy+61PLXZw5En+tVqtpb2/PyiMZEjAcDq0sjefS7XZN7+3s7KhYLGowGNixCKoIfAnUWTwf73TGWb7oKECfR48eWZDe6/UkSY8ePTIZ9kEW+jIMQwOQ/vKXv+jm5kbn5+eaTCaWhKHsw4O4+AYe5MSBT6fT2tvbs/Nl30nRCTo7OztKp9P66aefTJ82m00tFgu9fPnSnHtKnX1jVRoFPyQ7+3t0Hf5Ho9Ew3Z/JrCfZDgYDSywAcHtWlwdYLi4uIoMCYOfgr+FrUX6N7fZZcV9aAdiHbcPfQl5arZYFOwBRPshAfiTp6OhI3W5XnU7HAkCmvAJCYg+xyzDe2FvoxyAILJgDcJxMJpI2k7Bg13DN6M8wDK3/T6fTMfAd4ItEwWKxnkw3Go0iMvdH5O9T6DqffL4NjD04ONDjx48tkYXfhF8sbUC+k5MTY7ONx2MLiHkOzWbTEh+SjLWNvfNTSgHd8bE88BRncwAqzmYzXV5e2ndjJ/3kQPYDSSJkCDYag4VY6Ef653hAA9YLfWulTe8uAAX8TfQ5zepJGmFjYciQDGCvcX6Xl5dqNBrGltra2tJkMlG73Y6AHb93fUobe1vyKZvN6r/+678kyYY4HR8fS5LJBfsPPwb/Fzkh6Uq8C+jigVB0FUw07BjHAKSXNj2TsGsANT5OnU6nOjs7i/jvvI9ni17N5XI2gRr9hyxzDsi9B2BhTvF+D0aS6PFJw9VqZcBmKpXS6empgiCwdi6r1Ur7+/vm08Ey9Kxrrh/9C0Hg1atX9trvXXcpdw9tfXKmUtzxeBvIhMBBGfbG2L8Oi4LjsXEx5LBwtre3Va/XTXED2ngaK5lyFDYOBxsHBLdSqZhi7/V62t7eVqvVUi6XswySL/mh5MM7PzgAlLpx/6APEkAtFgvt7OwolUoZi4mMKNc9Ho+ttt9nd4NgTVPE8I1GI8susNlQ/EnP533Wp85mvWslodFQPmE0+N5cPH8ASqZa0YgTx5mMpW+K2+/3IxNDcATOzs704sULy2DgMND/hqCGEkVo7UxQkqRWq6WDgwM1m01zALwBC8NQu7u79rzp33RwcCBpM/0KxX18fGwAAT1VmPpEmR1OMJkM3+OEDMXV1ZVl6clWkMEKw9DKC5ICq4eevff7KUm3STKWIsYPA+jZEwQ41OKnUutG8RzLT54hyPalbwSxnvHJhM2trS1jPOFoYqDRs4VCwcrRPEXeBy2w8DygQWDjnfDlcqmdnR2Vy2XTnwD+29vbKpfL5rCSmYKZh/wAiPiyP+TK31uYnD6TCpsOZoIva31fXcczuKt1W/aef0nXBfBWq9Ui7BvuLWyji4sLGwhAoF0ul3VycmJBLMcncwp4LG2aKnsH1ssPTiW6jmlFyCVlZDCAYFju7+9ra2vL7P319bXOzs4kSY1GQ48ePbLnSjYY+4deiu9FzscncwqFgpWv80w9GwbmAsATNvXi4sJ+sp8ICsjucq/8FJqHYmffZmOTAn0ChKdPnxrzB7CaISnL5brXS71eV71e13g8Nl/Fl27Enx26MpvN2sRWzpFASto0X/X+lM/0S5uADyBKWrP0aCZP7xQPgNZqNUvkecaZn+pGYI/sc4882EhCE93GedC8nkw7SQR6k6RSKWP9IlPcbwA9/BnOJ51OR5jO77M+ta7zy8scOmhnZ0fT6dT2ca1WsyQY/SRhYkubhsC+NB/dKMmAE68PvF7zYCMgDc/E62OYvfzzzZg5f687uTbPXOMYyDHBOa8DZOA/klCRNn2CpM0z9IE8eplen/zzgCj6Gr+CvQWAxnn5uIx4533ZmZ9a7pLOGzCy2WxKkvlz0+nUYgViUfpSIkvoRZ6nZ2Z7MNKDSHyntGlsHgc9PIstDEMD7z0bip5P+EMeeOL7sVMAT16HJjGIPUs9lUpF+tJx7zgOMTq/o+/xTTxzCSBNik7wRNakTdn5zc2NVRdhfzudjun3PyJ7n5lKt69PDiolraSsqrQBmuimT2mHd2wRwGKxqFarZdmDeGNNUE3YIfwj8AVVpT4Wp0WSNVJMp9OW0eJ9KHWAJMo6oKvmcjkL9EFZcVR+/fVXc5x9yRwKfnt7284RZ3o+nxs7BFCJRs/eccKYcQ5MXfHvCcPQsiTc7w8RXLE+tQGQosH9bXLmF/0dUPyUJDG1hQxTJpPRZDKxxu9k1nESpCh9FoaYLwM7OTkxdhkODqWKQRBYf656va5yuazDw0MroaMhciqVUr1eV7VaNcez3W7r4uJCQbCmfT969MgmJEprJ5pssS8Tgpn3+vVry4w2Gg0DEfr9vpWs+AzpeDw24Ih7hDHBGUG506Q0l8up2+2+/4NPWPdJ7t71WjqdthIG5IX/+4DDMzYor4EB4Y11/J6jC5FhgmJ6hrEv6I01Go1MLrLZ9Qhw9C6DCXCGrq6urIzEX8/FxYX1q+h0OpLWMtdoNLS7uxthrPjMa71et0xxp9NRt9u1DCmOMw4LwQOlbzhtvIb+w+ECGGNvMcb7tz6z37Lug9xJb5aGsMIwtMwyACSBaqFQiIztLpfLxkyDcUjywTuT6A/sly8pIkDx2VTOg+/1fU3oB0J/QP5/dXWlXq9nMnd5ealOp2Plm41GQ/v7+9Y7i0w5AQzANUEQLFJ+x2EvFArGNmLvxMEAFsEbDivPhCy0tCl78ROQfEb4Q637Air5n6zVamXMXgIBWA4kUih9y2azxuCi3YDv54VcIYM8EwImgEQCFMrASGzADvDBNIEcvhGAOOwKEkaA2EEQqNFoqFQq6fj42HrSYS85X0AtsuycjyQDswH0PQvPnz/yy3l4cK1WqxmAVCqVzL4je7PZTDs7OwZs4c90Op3ERO4fkYX7IHfSm60M0AEwbgCHstmsAeP49yRikZVer2fXhX/PHkbGsEO+WgIQyVck+HPip9eXNzc3ltTlOkmEeD0rbWx7GG6GGMWBK4AuD2h6ph1xhe+Fg772DCd+H41GJpuSDARDZ8IapOQIEOny8lLNZtP0KuBEv99/43n93nUfbGzS+ZNsrtfrmk6n2tnZURiG6na7CsPQeo4S+3kdxv0kAYJ8eIAQOfTv9xUJ/j0eHPfAI8kTjh8E61Jz/35/ff4cvT2nhQLXg64jHiE+QDZ9govj+Slwfk94uV8sFlaOx/OgygJGPMlLH58DHOPreJ82KYH9W9ZnUOn2dW9BpXhmn/8TgOIEExz4jAFOGpOKwjA0IAXHtVqtqtlsGovj9PTUminiaCyXS41GIzM0l5eXBiJhRFGwQRBY0BPv4QRIRA0xbBZJxk4igO90OpFGkWTYS6WSnjx5ou3tbWt6zL24uLiwhmkESgBMUKb95olvbozk2dlZpMdE/Jn4n39k3QcDwEoCl5KujSwh2eXlcmkADs+eUjFGmA8GA2u83e12zWgwknQ4HOrp06cRMHM8HhtAAHtuuVwa4wzHFEWOo0vtPcGOp6wi98ViUY8fP9b+/r41kB2Px2q32zo/P1e/37fPdDod9Xo9BcG6gS8sJcpPd3Z2tLu7q+PjYyvlBAhrNptWQoS8LRYLaxIvbSaINBoNA0iy2aza7fYHDaz8ui9y55kj8b+z3wCH6vW6yRespTAMNZlMlEqlIs4ngRgA583NjWq1mjUOpr9CNpvVaDSStJlGVavVVKvVbNpWOp02NqXvcQQgn81mLXj3fWbIVKGXpQ1ogWMKuESj+S+++MLKm+glAasD5+b4+Fj/8z//o9PTUw0GAytdQFcDotdqNSutwhnzzCwc/SAI1Gw2rWk+sudZNf75/Nn0XdxZXC6XlsHnbwx/8CAkjEYASZqfEzzgiBIE4SzDfiIjihPJa5wXwZhnYlxfX6tSqRjFHhB6e3tb29vbViI+Ho+tx0ehUNDR0ZFlhWn8Ge8Bwvdxzb6nDzqTXnQEWuxdwDKGWkhStVq1xEKtVlOz2dRwOLTvY49SrgQ7eTKZRMoE44yEP7LuS3AvJTOWxuOxSqWSdnd3LZiuVqt69uyZCoWCut2u6YBvv/1Wz58/V7FYNPsAYOODbJ6zZ3UDQkqyRBu+FUAzwZpPoiAbhULBnutoNFKn01G73Y6woq6vrzUajdRut9VsNk3G8O94FpwbdpCAD8AIeY0z6nw/EYJF2J5BsGbNUyp9cnJiLILz83OTK8bQVyoVCwalNSvaM/3/LHIXvwaC0SdPniifz5s/n0qt+6+dn5/r9PRU8/m6yT62gQmpJGB983b0mWf/cG+9rcQuch7YI2nTKJ6gmvgCJjIBugeVuH6YJfTOhM0Lmxz5wwbTisB/H7JF4s8nBwAokH1sNCxk/Ld8Pq+joyPt7OzYoI96vW4tR/r9vr755hsDCVarlUqlkvVTfN/EzacCM+M+QpwJfHNzY3Hfzs6O7dPlcqnhcGgtA5gczmfxaageyGQyxuQGACLp65niJChIWPATWWQBIpIUGo1Gphv5CQDkP+cZ3lzj7u7uG4CmZwsh/4CZ7J84WDoej+07eC+J+HgvL0oy8TUZECOt/dujoyNLQJydnSmbzarZbBpwT3myB63+yPoMKt2+7iWoxEpySKRNvxoQWqiofowvWR2yUWRCCcSZWITDR1AjbUY6Uv5BoMImZlPgEHGuvjaWABDnAcNPdgrHhfIoHGNfy8wUk3K5rMePHxsbiv4gZF2YWIJT7BvzemefheGBRQOFOt5PJK44/0yZ+yQk3r/mgzCMK0aBbOHW1lYk04lMwISQpMFgYCDiZDIxg/38+XNlMhnLXOAk891+PDAlKr6shPr2YrFoYBLZKwI+DMfFxYU5qkx6QOags8YzwKvVSsPh0N5PY0+cpMFgoGq1qmKxqH6/r+3tbQsEJEXKaDxLhPtIZiWXy2k4HNq9+RjrPsjd27LBcWBztVqp1WpFStQ8hZrM4dXVlfL5vDGWAC2z2axl1AEf0WE4fk+ePFG9XtejR48iWXLkll4JTIjb3d3V3t6ejo6OTAcCIAE8ADIgr5T34vwiL5lMRnt7ezaVgx5gZN8phaOBJNkmenihn9PptDkplHD53hCwTpFDSVZKgyze3NyYg5f0PN5nfWq5uw0ci4Poy+Wm19r29rY5vjs7O1bqgB6EfYte8qVisMO8s+ZLO0h4cDwCJ//MisWi9vb2Io5goVCwZ+RLMgCmuHZKMwnumS7GPyjzfi/iuHv9S9KKfiMwgwHuAYr8fUTfwYro9XqREgRKpLC5JCKYsvq2Z/d7113JXTzw8CspacPCjvleIfS6KhaLBo5w/Hw+b01heX6AQhzPZ7qx4V62CE7iepYgxjPR8C3z+bz5bbQ/INFHItAzhzimL3Xk/hBo4T/4fmAe4ALkQb7QUzBNvG8AcOvBDpjNyCEslFarZb4JvshwODSQi+98X3m4i3VbcJ/0f9ZqtbJkMnolDEObftztdi1Zw/NH13m9hX7jPDwDifMCyMG35jViE2nTSBygEF3ANQDqA5rEBwUgA1438zsJJlhu6Ej0MjEP5wXzBPYawAM/8QEBJwH10+m0DStgmAJ9+eg9urW1ZWVgMEUWi4Xa7fYH8/fuK5gJkPzkyRNJm4EBsGqwLfScJN70JYZBENjQHp8E4fkQm/BMSYqw0EM8dy+DkiIMSpLbLJ6PLzUm6UM/Nz9F1u8FfATPxvPMIM4FYBMZ9WX3xOv0YIQ5zz0plUo2uTibzVqT8dFoZBU3tVrN9HI+n7fekP6e/BFbe5dg5kNb9wJUuu2hvi1jDFKJk8mmAFDxRp3aSt/TBkFlfLcHByixwCkhAEb4t7a2rGdH3MHEYfA0RBhVnAPOBQoGpwoWFAyDVCqlWq2mR48eqdVqGYV/MBhYnwdpM0FlPp8b2lytVjWfzw2g4jy8IfWlMPR4etv9fyhOh/T7JyIl/WTxfGkwiiKHxuvRdwKMg4MD6+1AeZtX9tBhaTYP2IlcUeKDsaa+GOVNmRHPeTAYqFQqablcqtfrGdgJ2AOLTpLJvKSIk8T5AygxuliSlSJBP6X8ktGwpVLJqPTVajWSdfA14ThsXEc6nVa73f6gzm183Ve5k27XcYAwGFWykD4wkdYZ+IODA8tuASJhsAGTCGbRO/v7+wbGnJ2dqd/vW8kuegnHGBkEjK5Wq5pMJhZoEwyyR5D33d1dm6C5u7trjWS3trashBNqNL0GRqORMdhgbRYKBR0eHhqYCWOQYNIDqIBLsBG4X0GwLgshe8a99pOPeAYfIoMqfXq58/osDqLH5S6Xy6nRaCgMQwtMt7a2jDbup0P5Hi4EIQQ9BMUEQNhR9CNO6dbWVoR679nElOMR1OBoAjDQ2J2R2SSWSNg8efJEqVTKgCkcTYBLADAcTXQZ/wjouG7K2T0LzgMeksyO+/J2z1DY3d01Jgr7kf47H3rdF7m77f8+ANrd3TVAyAMe9KNij3e7XQP/SL75sgg/dlralLIBvBCgcT6epc13oFfpoynJAG78SHxFjler1SIyACsGWfcJPfaKL60DzAJc8mwArsX31mN/Ir8EbxcXF8Ye4V5gA2BmsodzuZzOz8+NlfCh1n0I7t8WS3DvfPKM5w2rUZKV3KZSKWOMAPjFS8V8M3jf5oDP+IoAFvqQwBRZAGTke5Fn9AU6D/AeVriXE1+ix998sI9dJBngA3yCf5KUJCQ9uwXAnb1YLBZ1fn6u+XxuSR/fQuPw8ND2LHLc7/cNvPgQ8ncf5I7l5Y97S4N32l3QHoMkL/s5CAKrWAAQjIORPDOeMT69jxm8PeZznDuJv3h5Lr1j+/1+BExKKtskiYkv79lIXDN62ctUnI0cT06tVitjFPs9BTML8gd2vNFoWDwPsWQwGFjMC9MePwGf8rZqnN+7PoNKyeuTT3/7LcsDNjjEZBKOjo4itFOCdN+gMJfL6fHjx2bUh8OhZeZLpZJKpZKurq4i6Lq0oQp6mn46vZ60RFBE1o2AD9YQm4babL4LyjuZCd9UEqbTYrGwTMTjx4/NqcERnU6nKhQKkWl10KYJCjkO94yNTHBFg9vxePxGxorlP/shVrx53Mdcf1Tu4kbBO6JPnz41NJysaTqdNkPqqc709Xj9+rU9y0xmM554f39fs9nMaNaUnPB5DDcNtaUNgEDt8GKxaaCMQpdkRh7lC0X66urKKMw05b64uFCn04nIOXJ/eHioJ0+e6Pvvv9f+/r6q1aq63a4mk0kki1epVCzzCXOJMitfBgN7BkaCtC7/hIXwsZhK90Xufste8gyP/f197ezsRIKOSqWixWJhfa6gG9MfVCr4UwAAIABJREFUDkAchxanFt0Hs1GSTTZaLpdqNptKp9Mmi5T+jMdj/fjjj3bejUbDemnx/X//+98tY47s+bITyuu4LmT3b3/7m5XAjMdj9ft9nZ2d2aRB2EwAUZIMVOr3+1byCyhQq9X0+vXryJRCaOG1Ws0mzrB3CazioOqfSd8lXU/cnkoyEIapfzhhAC9nZ2caj8dmiwBm6L0EeCdtRmpjcySZPvKsJMBKbJu0DnoeP35swFC73Va73TYgCjYQ+o6sL0AF9jgIArVarUgPKHQP7Eh6I3r9nEqlrHQD2SWrTBkeCSmuablc2kTX4+NjK1HFTnAMssKwif/5z39Gns2fSe7iKynYz2Qy+o//+A/lcjlLjGUyGZuG+vPPP9uUrnq9rsViPYGLqYME+ovFQoPBwJ49dswHzlI0aULAhRzFm2sDNgKc06QeFpq0ARV8mfBsNtMPP/xggRQyj4wCfvq9xTkFQRCZDsUeA4gEaJUUKTOBmVyr1SI9mBaLhb766qtInzvACHpVsT6E7N2V3L3LxrI8QCet71m9XtfTp0+NYeMbbl9fX+vXX381wJxSVdgjsCV82wOYNzAlvG5EzgiY+R0QBx3I4nt8aRr2m72BngUAJVYgeKa/KvvA//T6F7nnPNCffGe73ba95Xt5MTAmnU5rZ2dHkvTTTz+pXC5HSimbzaYqlYpdCz4l8QY+SPxZ/ZF13+QuvogFjo6ONJlMrKT74uJCFxcX+vnnn8228Cx82TZAok/eebDQTxunCbi0aZvgWTU8d5/wAQy/uLjQ69evI3Ezx8LuPX36VLPZTO12W6lUSjs7O2q1WmYP8b2IjaRNWRsAGWAT9y3OjvO95ohxaHkAI56kJXE850fftJubG7unvhyu2+1G/L33WXdpZx/SuhdMpXetpAwTPwk6fFAtKcLsoFyCTeIVpVeYfvqDp+z5xmlBsG7MSM8iNorP+tDEmc2B8pbWm5O+NX50KMaerCjjvmlkDODU7XatdAmqNWAR6C21vPHF5A+USiaTUbvdfmNzxLPaH2p96gzqu1ZSRj++YBx5+jBgkJ+k4ZlwMND8dDOCMZrAIj8+2+oDN6jG0qbBI0AiKD6OK2AV8oHcF4tF7e/vq1wuW32yn8LjMw6w42AncT9R4ATrBGEo/F6vZ0bOXwMNlLln2WzWxhn7673tubyPHN5XufN6LX6NnDNBizeclCj5kh6e987OjvVWowEugQkZ2CAI1Ol0jB1ZrVa1WCzU7Xatx1apVNJsNlOv1zOAkO8nUMPhODw8VLvdVrfbNYfRg52U9tInCcBnPp+rUqmYLmSkLeD4wcGB1e2TUSODDJWekd1M8/HNP9HhlUpF5XLZ7gFOVjyw+pC6zj/Du1i/N3ufxMpcLBY6PDyUtBlbjl0l24wcklGXNswTX8bDOWHf+AyOLgE/7E0SNNix5XJpjcBhEsCeg5E3Ho8NuPEsUNjAvvSboN0Hhkxo5fg4sMPh0NhQTFZkGAM+AUEfDNPt7W0D3rgvq9XKyjZxsklaxfvZ8Cz+LAy5d7GVJBlzpFwuG0uEMi+y4J1Ox+wtTAwYmMiWpIhekRSRTV8iBDNI2kwNwp5xnpRrAlb7AKtUKklaT46s1+vKZDLGRCiXy5Zc4Vie6e4TjJSicY5cN3KITWaveHACOw/AKsn6AAEMLJdLa3GwWm1KDUulks7Ozh40Q84/5/iKM02TmKdhGGpvb88CXeQDVhqJB1heJGk9S92zfr1txu/z7DLkDXspyYA/mCaUYmM7efbIH7LkWxAQI2DTuDZ8SXSVBxckGYMXWSS+AEinfx7XAugJ+0WSyTJgsCS7zuVyqYODAwO+5vO53Vd094cE0+8bUymJ6YxeyWQyNk3VM64nk0mkRBfbEme6EQN49j8+HsxEz8T2vrXXJ/Hz9K1bOD7+FglhAHffvw697IGieFkosTffE9c96EIGMXj2qd8Ty+V6YAOxULwvXhiGFuPyvcQfk8kk0uT7Q6zPTKXk9SBAJZZ3VgiswzC0cexsPhwPAi1JFtQg/PQ7ou/Qcrm0UexsFO9sSIqgsQgxBodAB0fYMz7YvAALNAVHcfC5XC5no5tpzobRGwwGVqLGRsHZJ+viNyL3g+8mwyzJeqHQEPNt9/oh0qOl3x/cvy2jz4obfNg/3uGAwbFarQyMQSGiiDH8ZDgpeSRoQ85gNQFCoUi9A4yCpUyDCV7NZtMyJBizer1ugA4UZHr0wOwjiNvb27N9BNBwfn6udrttTD/k7PXr1xqPx5Em4X7xvTjCBFWeaislN4f/EDJ4H+UuCcCMOyPohb29vYiBJGCo1+vKZtfTVciSSzKGGhnxfr9vDkqtVrNsEj+n02kkewiIMxgMrD8I8uidaow6bCOaDuNg46TioJTLZX3zzTc6PDxUo9HQxcWFer2eOp2ONZbF+dre3tbXX3+tarWqly9fajQamdN+cXGhra0tu7ZqtarBYKBOpxNhIzCtkEyctEk2DIfDRN3nwdD3DfDvi9y9Daz1C71Do3bYrAQljx490tnZmTGTcOjQYzxnnEjOCSeXBA7vofyNwNc7yQTJlFu8fPnSAnZsO8kbWLu+hwOOJHq33+8btd4zgdHns9nMmn6HYahqtar9/f1IMIV+5zs5djqdNtnHJiwWC+3t7Vlwx/4ul8v65ZdfIj0ck4KQ91n3Qe6SQMuk10mAtFotC4Yp/6ERMOVk2ENehwFBUAUQhbwCRnlwlIVv5AcRcD3FYlHlclmtVktffPGFqtWqqtWqMSdhbHz99dc6ODiwZrv4fjxn/tVqNaXTaStzoblsoVCwknfssi9tprTYTxpLpVKRqYse5Pf7rFKpqFKpmL7Gv+z3+9bHkfvwodZ9kDuW199x4Jx7AQNE2iRM8MFPT08lbRiWlMcBNqL78HeQJQJcfDr8KmkzhIOqCC/D19fXFtTDoKR3UaVSMd+PsjMAVlh+2FkqFHyvLc4JsBIgifJeevv43kkAB+jrdDqtRqMhadMvh/f7MmZpzYAejUbms6LjYXF+aL33KUGleGLQ/43lywcfP35sPQLx5+ir52NbiAIQFnx5LiAj9gddwPuJPflHHEzcQGzLc53NZur3+xGWkWf/oj8Gg4H5+JlMxvq2IY/o1DhDENn2sSvnjBwSUxEfEfPSpxVmXLlcVqPRMP9TUqTKAiIGQ1rK5bK63a663a7d54cmdw9t3UtQ6V2OSHwDYrBxdPk7Ct2jvggaCtU7h5JsmhobTNrQ+aVNDT5URDa/dxx9yQnnmkqlrDRuNBrZea9WK3OsYBlg8DAYBHz+2sJw3buJLCgb3NNYcdBgqXDPMpmMTRVLcipuQ9vfd90np8OvtwEX8XvA+2ic7YEPsoG+9NKXR3rDS1YBB/jmZj0tIl7HLMkyUz4r5pWvZyfhAHlFz/mR2RwMBjbVTdpkzXwZyM7OjpbLpdUoEzxh8DBKGDPOw98nMrxkKXxm+fz8/A15eNu+fx9ZvK9yF19J+265XKrRaERKE72M5fN5mzLlM5mU9MK6QC8ReEkbXYacUEZHA21JZvjRr2TXMPQ0CqesF7DRA58Y+a2tLRtrHQSB9Wxg9DuyXygUtLOzo0qlotevX6vdbpvzy4QcSgeYtknZh7RJOFSr1YhzBqBEgoFz/Bi6jvt7V+u3BFn+Z/x3FiAKDFlsJzoCMI9eVux5MvpeJ3gGEUERTi//eN5hGBowDkAFSLRYLHR2dmayit6t1+sqFouW5AG0Rxf63ok4tewPGAA0XAYEvb6+1t7enmq1mjGmOHefpad3TRAEb9jm1WpleygMN41zua7j4+OIbMRZFO+77pPcsW6TO3wZBgbAavDAcKlU0vn5uYEuxWLRwG6CKx9UAcIAJnmZ86yjVCplADrfSX9AdAMlPBxjPB4bO56y4cFgoPF4bCwCSpDRtfzEtnrf0E9pIvj3TBd6znl5xrZ6Norfp/V63cr0+T5Wv99/o4fch1r3Qe6SfIUkphLlYvEktd/bvscSuioeNBPoe/+I9+GnUdaGDgW8BwDkOJeXlwZWoRPp8QagWK1Wbcowzxfb530wzsXvDWREkvVtRZ58HIIcAjoQi6C/iHU4Hn6JtI4tOD/fSPz6+tr62bwreft7131gyPl1m12VZH1ZfWkhCRzuK3KIP+jBIc9UI76QNjLuK1GkzVAET8KA7ShtpmLyTPAhJRkwig9JjOJj2lQqZUxfdI1nQgG8BsGmFJjXSBJg05EhQE0PyjLR0PfVQwYBzn0cx71hmiiEEp5PHPj6I+szqJS87iWoJL19ck2SINC02md5fO8bjMFisbAx7PFmmgRNQRCYgo9fRyazbtTdaDQijoqfkhOnv6KgpQ1qC5hA08lSqaTDw8OIEl+tNrXNPoj3NfONRsMYJRgDrhlUmF4UnBcZ2Xj27vc8kz+y7oPT8baVJHNJDgrOpA+gKLnw1Gjen0qlrJ9QEo0fB5cGc8hOEAQWzPteJgQyGBcyXZLMCfUUe694wzDUdDpVt9s12Z1Op+awkEHd3t5Wu91Wv9+37BbGhJI4nAyu0wNYyDdZPQwlWX2YgvF7+67n8kfWQ5K7pP8DmmPwKf3yWW0cYIw4484BBL1TTLkm7yVIkTaNHHFqisViJDsGC8UbZUqEAIgo36WHE6wp37Ae+aXkiOMDKNXrdZviQSmIL13D+ULeuBfoYL4HxxgnnCwx1+3v94fM2vMs7mr9keCe//t9yznjwHFffVkSJRe+NAIQBefXT1iCMUeQhDyjI9F9ZG/JmvNcfc8179DS15CegNhagmtKe9kzUOnpQcI1SjKns1Ao6OnTp9ZPjPMAgMcJ9hnmeKkVzVjJ4sNGLZVKGo/H6vV6b8jahwQ275Pcxe1o3KHnGftG5j4wmc/nZm8IrD37A1kk6YJN9iUQPjPuf2YyGVUqFUt80KcTew2YCAMcv2k0GhnIGQSBNVznPEjWxcEsrpsAksCbZ48+TKVSNqHYs5uR71KpZP6hZ9LjI+7v70eYDdjswWCg0WhkwZX0YVsd3Be5SwJp49dGaZkHjJEv5IjEhySTUQJeXkdn4ov56giAJm+3ec33L1qtVhHAEJmVZAH7crlUvV7X7u6uJSFpsUFfJp+0jCe1PbgAIwpdic71yUpv70nOSDKAi/NEtyGzBwcHVr4O2JVKrQfa9Hq9yPnxXN7X7t4XuZPe9CV8vApoDVMI3cYQnE6nEwHMfbUMx+MZ8qxY/n0++eFjCc4LMBE/Cv+f5IcHfIhPsPPepvI9xJb8Q7/xPgAnD0hKsgoOZCAMQ+vpCdi1XC6tH6Yk04kM3vC6v1KpqN/vW/ILULPdbkcGcfnn9D7rM6iUvO4tqBRft4FJOHLQh73xximJCxOZp1wuF6khpa4YxU1fBRp+oaB3d3ftO6bTqcbjsX0/4959dmk+X09Qwhmgtw5GpFqtWiNKHJLpdKrBYGDnKm36PAEa0ewYpyYOEvmgkMBgPp/r7OwsMWMQd2zfFez+3nWflH/SSrq+pHuA4sRAIGeAh4VCwUqFUP4oOhSzz3Atl0ub0oaziyM4Ho8tg1StViOOos/MTyaTCFjgM5iSInRRSVb2RkBPuSV06//7v/+zchHvvALG0hh5uVxak3IWbCnABGmTwW+32xoMBomycNsef9913+XOr6Trh/7sJ+d56nOhUFCpVDImmjf+caAZ1gZOKgAPzsjR0ZH29vasLxOOCdPoPIsI3dZoNIwuv1qtS+x2d3dVq9XUbDZVr9fNsYDOjS7qdDoGyOfzeT1+/FiXl5caDAY2lh2nF4Yc76Us0ANq2WzWmpVKste5xtPT07f2E/mzZe5vW0nBvs8gXl5e2v3lfvlMH6AJ2UQ/bMBPcEEWAd0Bn+jVsLe3Z/JM/y1KQ2azmcbjsYE7OJmwO2CuAJBjb9kbNOn2perb29uq1WpqNBo2mcizRH0weXp6aj4BOhx5p+STYwMqMJUVYBb5I2N6cnLy1h6GH2I9BLnzv2NPKQ0jqJI2QVCr1TI/DJZkEKzLvHmG6ELPLPHTsEjYAPLwd2yun2aK34SuogxjMploMBjYVKyTkxNr9j8cDm3yn2etoBcpGUL/FgoF08HIECVxlUpFpVJJvV7PAkz03MHBgSV/hsOh+a5M7/T9HqVNn6oXL1680SA5/kzeZz0EufPA3tXVlYGZV1dX1m+w1+tpsVhY02P2/9bWlulJn7jF3wEIQocGwaYMCfBIUiSoJ9EBwJDL5VStVg1MgklXqVQ0Go3UbDb15MkTlUolPXr0SM+ePbPegHEwFn0NmE584Qf7+N5k2GfKP9kHfogCVRG1Ws10IvuqXq+r3+9ra2tLL1++VDqdVrVaVb/ft8DeP48PAShJ90/u4kASP5GDq6srNZtNSZvSrTBc9/kiBkC/cCx0k08EemDJA0/4/iSbfeIIvYSNpY/warWyxuG0U+Af05xTqZT29vYsvgGIhIlGAtPLUpwEwff41ggASAz4IZbN5/MGaLKPyuWyJCmfz9skuEKhYOfVbDZNB+bzeQ0GA4t3P5S8sT6DSsnr3oNK8QyX/8kCMPH0Yu9gJgkSfyNLwfFwFOkTQW0w9E9GkgLUTCYT9ft9o3zGaYYeJZbWmx8jlU6nbcIIJUtbW1sRhoFnvHA8HHYmCPCapzBy75luAZqMU5N0T96Vsf+zg0pJKynrxe8Ae77Uxwc3vA8nhMDKl5V4ppEHYMrlsjF9cDTpM0Kw5jNlfLdvFOmBHknm2GB0QO9hc5CpoPG2N444HmRSPaMPI0fgBiDm67szmYxNLoyfVxwI/dDA0kOTu/j1A5wTzPtnxnORZP2V+Ixngvh74OnT0Jr5joODAwPHcTAAoGF4IHej0ciCfHRMLpczphKB0eXlpQHp3rGmJwO6e29vz3o6+Gv28oJjur29raurKw0Gg4hcwsrE2edecq3vGmX8/wqo5FfSNa9WK3uO6BgCZJ4/ZUQkalarlT1znFVfCrJarWyYRCqVsjJzso6ABvxDvuN97NC56Bzf0BMmASAsgIFnWj569MiCpvF4rNPTU8u6k2jCuUdXptNpCwD/+te/6urqSi9fvjRWKmxjwF10Mn1xaHofb1J72/1/n/UQ5C5Jx5HJlzYtB2C9STKWG7JF0MI0WwJkzyKhZxJMWXQCDCHfYysMNz0q6Svmy5WwrfTYQq5gUJKc8cGbTwD4viL4YwRJBGiw6P0gGWkzLTGfz+vJkyfG/OCaV6uVMZQ4L8pcAOKYWufv+Ydc91nu4kE+v9NzLx4n+NJIkjWSDAxED3IuBNHYQF73yTgfWHt2BrqJMvFCoWD6iWbrDHy5ubmxZHI2m9VoNNLr168t8YcOQ+/h0+FXcU58tyRrjeFLQ9lbkizxVKvVlM1mVS6XrdKBzx8dHVnlB8kfab2Pe72eJQRYDzW4/61Mpdv+xr2t1WoGuPj+RegS2GdhGG2r4UvFfJyJrvEsTa+H+AwsIoB3/Cz0J0N2YGz66/a9BDkfz5DycoXOi7PnPAOK10gk+RL2TCZjvei4liAIrGTV9/Q8OjoyfQr7iQmvtO9I2v/vuz6DSskrkPRx5nj//+uPjnZ/20oSDACaRqNhQApBy/b2tlH8PJovyRw+/sZGBATg9dlsZo0XyYL7cgp60GQyGQ2HQ3NmPMgFZVmSOQsYfTJhLAwPPz1biaCe4wAyoSTK5bJtMh98np+f26a7bX1oR8OveIb2Y64PKXdJQCZGm8Z7njYMu+zy8tJkyz83HERPy0f5Ay52Oh2tVis1m01jXiBTnjqPcpY2DQFxpql5JiDE+BAg8Tp7w49lljYyyPXyvWTlfIkLfbskRRxq9huTvbwzE1/vkr0/mml4yHIX//+XX36pWq1m2Xzu7c3NjZVYAhay/w8ODmyUry/LJfiqVquS1oHN4eGhBVOecSnJRibf3Nzo9PTUAviDgwObzLW3t2fNTWGS0EOGKWwwQ8g+wTxgj3iZZV8hf8Vi0WQPJwRwl2OwH3CQl8ulDTpI0n1eVj/kus9yF7/eJJtaKpVs+p7PdAKCYx8Xi4VNJeV+o4d8EE7GtV6v2+hfP0CjVqvp119/tWfJNM18Pq8vv/xS8/lc5+fn6vV6FsDX63VdXl7q5OTEbB334+DgwM4Bmw14ORqNVKvVlM/nNRqN9Msvv9jz8sAWCzCzVqspCAJjQCGnsJu9recehWGo7777LlJyKb3ZG/JDrfssd/Hl7QuMjC+//DIClpCAK5VKCsPQJt/yU1o/M4Lpra0t0w8kGmmiLMkC80KhoPPzcwMgAbd5LjDLYd7hv43HY2PqolMAtNE/+KMMQ/H7DaYejb9JzhwfH5vu8mwmgr1araZarWbHBDSq1Wr2PkmRYFCSNar1DM0knfe+OvC+y12SjtvZ2TFWLXotlUrZPqdxNi0DAI4lGVMTgBGfKq47YOLhJxEnwPphCiWgoQcVfB8jgu3t7W3V63VjfYxGI7OP0oZRJG1K4rDP6CfsLHbaJ5588iCXy6nX66larVqLEZo2h2Foupz3Y5tpXN/v93V8fPzWROL7rvsod/FktNdz5XJZR0dHqtfrllwBMMf/7vV6NhEO8AlGpiSbUOh9Jf9d+N38A0hnOAXJXeIIwCs/pVmS9WirVqs2Nbrdbhtrk/P39wfGHrGOtGlHA+vI+3acI3qa/+MjADiFYahms2n+bxAEqlQqdv2AtuyfTqdjycyP4ePdpdw9pHXvmUp+vQ1t9M4Z1GVpMxrROyc+g+onZyDMHgFGURaLRVWr1cgkITJXi8XCep5A9UOIfT0qSC3ZAj99wTfa86wjQAdpI8Q4zzjv/vpBlD1wJsmy9HF0NQks+VjrPmUUfu+67b4AFAEs+fdC7URxYnjz+byxMQAyPZtMkpWP0ewVhppnRfmsLOAScoST4TNT/r6kUikDSxn5TtYC+fPPi9dolOd7qnBN8awC103D6HhQ5Y/9We42611ZFUpt4+9B111cXNjrvseQL9dBfiRZ+SX0asB4JhLW63XLDAFctdttCwI5zsXFhTncZKqYmIjsoCthGhUKhQg46TO33ukgM+d7NbDfcITo3eNZLTQyj/cSue2ef8j1kOTO20//Ow4bDAr0DffYByM+GIK9RkDD8Qjcrq+vTVbozybJMqXoIexkLpdTs9k0tgeJk62tLQPFYTvt7++rXC6rWq2ac1oul00H07uHJqQnJyeRniLSRn59hp8+O2Td6WsCm8AnH5jKFQTr5s79fv/W+/7/EmOExT31i/0PSxfAnOCWAIigJAxDy0LXajVVKpXIZDT/DKVNE2FJBhQVi0XTaZT8jkYjG28Nuxs5wk7SsN6XReLPDQYD03GDwSDCYAmCQM+ePdPu7q4ajYam06n6/b71AsHGY/Nh4IVhaCXy+IupVMpKi/ELSFLie3a73chkz4+57rvcJek49h+scOyMtOmJBNvw6upKV1dXNgnOM359FYHXk54Zzv0BWEI3FgoF7e7u2ndxPjAyYOp55gd/90kXnzDyjF2u2TOkCOAZzuKrLwAwJBmLBUAXmb+5ubGpiB5c9+VWsFBvmzD9odZ9lLu3xVT4NPjMvqUJ7+d5IiPoA58YpvcuusXHD9hOZA95wR/jmWHLvY7N5XL68ssvVa1WtVqtp/sCKlLG6KcOwxjiOtG72Ej8Nc9qAmCijx3DQYhdudcwPNlngL+9Xk/7+/vG9PKAEj6GB9Ifup19SOtBgUqsJOYIAgNtn0DEO78Imy8bSXKgfUaBYCo+9tjT7X1DNBwDwAaO6V+jvhknhOCfFUeYWRzL0yU9AIVyIaD0RhFnJL6x4pnSz8F9dN1mHLyS4vkC5KD0kROfTUWh4pQiTxh1gm/klmkRPrD2vSFwajk2jb0Jrj0VlXsyn891enqqXq8XCeJwgryBwLB5h8izlHDg/T3w4EAQBDYa9Lbn/7FBzfssd0lspNtekzYyRKYSXcW99r1seP6wE31fDu9UIxsYeCa1YKhLpZI1ViZgHo1GqlQqljVCNn02DT2L4xyGoQ0W8KOMfTCPrPmyX8/0o/8FgSVsGc+kQSbZg+122wKzu1z3We7iKwnI9MAyDqbPiHqnFNnw1HpKxeNMWmRIktHskVcabtIfBp1EVhKwplKpaD5fT6y8vLxUo9EwIInPI5e+PAAgCzvsp6B6H4Kf7CkAqzAMrd9FLpczoAnGggdsAdkoJ/brY7Hj/PnfxfpQcidtZIqsvWd/+IDbvxdfisQfLQsAiAje0ZOZTEaHh4cKw3UfkHK5rFarZbZ4MpnYcbDf+Xxe7XbbZBsw02fRKSOm5QJyQQAWhqFqtZp2dnZULBYNYDo/P4+w9TgPWEiAX8g8DZbRfbDyuZfIHdcOO/0uZOIhyp2/d0z18z6Q1wEkZvCZrq6uVK1WrWIhn89HEhfoMwAcDy75Z0zjbdiNviUHiZR6vW5TXsMwNNCHxAnxCufK3uB3rgO5YyiLvxfShvGHrp1Op8as83uO3nSSIrqfMtOrqyv1+31r9eHXQw7uPwSYiZ8ESA4ogr9GjOdLL2F9c4+J83ys4RlJ+PToT1Y8ZsROS7JnW6/X9eWXX0aqD0qlkukyhiOQ4PFgJufuYyHkD/uI/tze3jZdi99GD01kyMtwEKxZqMPh0Hp9Ybc9uDqdTjWdTm1SnU/ef8j1GVRKXg+6/C2J4YDjiFPqWRoe7PGjqT07ySPEngIaZy9RhjGZTLS1taVms2k1nUx3Y2NIMnZKqVRSv983IfdIKtfE5vTX6LNPAEp8BkeCaTa+9I2GbDBL4ssrl48ddN1HmurvWUlKiWeyvb2tR48emSJHSRIAQ19njPr29rY14vbZcEn2jAGEcE6Q60wmY+g97LNSqRRhQw2HQ21vb6tUKqndbhs9H6Xrez7hvBOMxwNGX/aGUcQIBkFgDjggqs+qXF5eqt1uJyrgu5K9hyx3SQB6Op22sefIQpzCTmNjnhNGvVqtajgcRhgc3Sg/AAAgAElEQVQnOCnQllerlU3PgIEpreXy9evXurq60pMnT0w2Aa3ot8R3kgX1LKfvvvvOnB8vb4D2Xq/xHmQTx4qFM41+BqzFwQjD0FgAb1sfS/Yeotwl6bhMJqOjoyPTMfFsuiQbRHF2dmbPl4b+9Xpdr1+/jvS3gb1BwIKDSNBD/xAca3oPUnaWSqWsB9PFxYUqlYrZWknq9XqqVCpqNBoGPNAraTgcWu8c9DP6DvDVM5YkWRNVqP70umNveCCKfdRut63xqAdD4vf5Q8vfQ5A7r9fi+o3BA7CPvLzxPPgbmWxKfoIgsPLG8XisRqNhDBOeS6PRsMau2DL6vgFaw9T861//qnq9rouLC52enloyJZvNWnN6acOCQl/CnKNcChAA1u5yubQeWwRd+BGDwUDS5jnSp4zycb8fYHuyL/nuy8tL031xxvHHWg9B7qQ34weC1adPnxp47lkVACXInLer0qa0x58X4BE2l8bCNCn+y1/+EilbQx+SwGm325pMJvZ3bOVsNrPeNiSJ+M7BYGAyhPziK1xeXmp/f99Ybtls1uIgzh+2KO0XkKf9/X27PkCig4MDaxJfKBQiyXVJevHihZXl+/Ux5O8hyF1cz+XzedMLR0dHtmfZyx5cZ5iJJGNmwhDyfVqlDeiF/OFTIUOU1aJvSNZIspjgyy+/1OPHjy0+pqIhDENVKhW9evVKkkxeALoZUkUMgp1nHwBI+UnZPgmFr0BVDclw5LVUKmk6narValnFEAluYo/hcGif932pPsb6XP6WvB4kU4l1m2OCAvaUdJ8p9UgvTJLt7e3I5iOw98grx/XBDxuXumI2N9/jS9H4PnqecIx4UO1BpfjfCNokWSDJ+eKQc56AC/FshT+mv5e33eMPte57RuG3rNvuByyheFkSWQTKxmBVwJzwrAymFniHxIM8NNMje0XfG2qvqZsHACKDBiWZbLnP+HrasxSdIsF14Mj6/cN7YcfFgytJkfHtb7uXHzqDEF8PTe6SgHK//LPDsMcBY15bLBbmhHrHz1PSMdy+jIMgnMaKyCLla14eADi73W5kKgcjj8MwtCmZOAie6u3LRuPlnTjcfMY7xMgd58V94m+9Xi+xMby/hx9T9h6S3CXZIR98YU98o0zPUPI/CeBhumGLKavAFuFMrlYrA3yQtXq9bmwVvhPdA3Wec8O5JMs+Ho/V6XR0eHhoNrbT6ej8/NwYk+hJACqfwfUAEPqQPcN3oNM9IOCf93w+V7vdfqPk92NkTOProcqdlzcWZY7IBctnrn1SEEYjDdOvrq6MMRSXYx/AoRtTqZSOj49NdqvVqoGb9OA6ODiQJPX7fZXLZZs4RNklckumPwzXQw3Oz881mUwMvJLWZXjeR4WtJK3tdKVSMfYodhiw3jP8fKnmcrkeuZ0U1H/Wd9Eklpc57AzJC/ybMNw0Sfb3GxYbbAp/XN/QmM/v7OwolUppMpmoVqsZ+3c+n9tkVSa7dTodk2Hs8mw2s2mB6MvxeGxJZs8W3t3d1dbWljWETqfT+vrrr81u+hKo1WplpWzL5XqaLz4APit+KaVw6HNfZuqZ0f1+P7GH3MdYD0Hu/L7D5hEb+HJf7in3bnt725rvw4L0lQphGNpwAGkDdPhEIEkTScZuJAlMrzlaFaCXYKn5Z4sviL8HgcGz9yBhoJ+xnegr5BF9hz9aLBYtAYSsk0RAn7NH0bFMjWPfhmFo07KZyJl0/z/U+sxUSl4PHlRK+l3aMH6grHvUFOexUCjYNCAEHEPggxbfKd+XAuFMkqX3Tmm8ORg1+9Dk/TFQtvzNg2Fsqji13m9Usrnca455c3NjVH2OfVvA+rEdXX99d7HuSu6kKLuM5+KVu6dgIpODwUBBsGa88Xzoa+OBKK6DQA5HAMqqZ8bhfC+XS1PCsFiCIDDHCAcBRzQONgJKShsWXDqdjpTy8X7fWI+FcfTlTfF1l4HWQ5a7OAjM/9FDGFSeoZc36u7JemWzWU2nU2vqyufL5XKkXxv9cwi6+T4PjiI/yBYTLNFvs9nMsr69Xs8AUI7lgUrkxZdoen2LowPIRMDGXkNH+ns1n8/te/26CzCJ9RDljr2YpOOWy6WNF46DL8gmYDafp9ExUwt9hh9A6OLiQrPZzFhIBMQEUEEQmC7xyRoc0OFwqOFwKGndBPnk5ERhGFoPxPl8bg2V6e/kxxT7/eLlA7DTlyojbwQB8XvHddFA912672OshyR3ST6clyvY13HwzgPr0qaHFy0O0EmTycR0FMkaStXolxSGobE3CVYoZZtOpxoOhwZuA0YFwXriYbPZVLPZtHI37j2yUSwW1e/39eLFC2Mpebmn3IlSGIIzgkeGI9A7BBYpDGLsN2C7tGYzkLG/K5aS9PDkzssetpDn4BO4PoHiS3UI9PHnkU+CdYBoQKhyuWzAJL25kE10z/7+vorFog3CAKj0sosdBPyhTxiME/bCwcGBnj9/LknWFJp98eLFC7teWEqDwcACcmwx1R6p1Lo3ZjabtUEe3m/kd5ij4/H4jbK3j2VzH4rc+VgL34akLExxWHD46dgh5MdPJUVfeWCdv3Ou3qbhw+Fz4Tv6EmP8R+QAJhsgpC+1u7i4MNuNbeXY/J/J1aVSSfP5PNL/EjCTqqLFYqHhcGjXiN7juNfX16pWq0b4mM1marfbajQapt+R4T9bD7mHtB5k+ZtfScwbDEY6nbYskqcGIwwERWwONgwgkhd+lCYGhc9zDGjPntKHgWGT4WRyLBxTKHw4CtJmAoN3pMhkoUQ4n/i9wAlnZLO/N/Hf/ec+ttPxEGiqv3UlGUgC7mKxaEEUz03a1J7jTFCiRFBPhh/HxlOwfXkS2UfKUXzAL22eI47mfD63Mjnoyt7Q+CwT54qj6wN/ZDGVSkXYA/4cAFT7/b4BXH59bBlLWg9R7uJ7MgkMBgh//PixBfPImF/euctkMur1elbSMZ1ObboXIA2MEUnG6CSAb7VaBir55w4wRKkRwQ+lt8iMz3Lxd++0e2cVHekBNAAm30fKMx0I6H3zeX8f/f3zn/kY66HKXRJbydtTxq0DyKAzfAkObCDs38uXLw0IBwQnEy9tJlcix97WSdLBwYGCIFCv11Oj0dDl5aWxNaU1a+Ti4sJ6hcBOms/nqlQqNmEwn89bSRBZeBxWn+1drVa2L5B1aa0vd3Z2jG0a14ur1UqdTkeTySRSjvexZc2vhyR3t/lv6KNGo2HNqHnNTznDVhJoMeGSVSwWDcyGKQ6oPp1OrTdHqVRSt9s13QQAIEnD4dBKLBmr7v2xMAwjLLZ6va7lcmkJPVhGvV5PYRha2Zok61knyc6Tc9za2lK9XjdZg71SLpctkJNk9wCQ4/j4+NYpvx9T/h6S3LG8/FE6xjQ2fHkSHiTufIWDJBtswWu1Ws2m+1KG1mg0IskQgMF2u22vP3v2TDc3N8bySaVSevXqlYrFop4/f67JZKK9vT11u139+uuvajab2traUrlcNpAd8AHgdbFY6KefflKpVNJ4PFar1ZIkA9nRWzDaSdrQogE5pKcUNnk2mxlYxvNYrVamh0ejkd3Xz3HFeiUlauibSrlvKpUyZhK2lftPoqXf71upY6lUslizUCiY3Hl298nJiaS1vmw0Gm/Yq62tLQMiu92uAaL0/KXkO51Oq9VqWWkZU1onk4kkWesBmOwMLOB9+AzYX85nOp0a+AqjHtDdJ4Fo98C50IcuCAK7dnrUxe/zx1ify9+S14NmKrG845vkpEiyjL1/v0ffKUnj9biD4z/nm3/yGpuUjCdKwbMIcDw8qo/z7QEEju3phSCx0HM9/d5fTxAExl6JN2WL3zN/vzwL4mOth5JR+C0r6b4hDwQkKG2Mg6eoM8aY0aAocY7n+9v4XkY8e18b78FPnrWXRWSB80POCOhxDsjcA2ZynVyfLwP1VHD/Xmi00+k0IpufAkxi/RnljuX1BKxJz2jkM8gD2aNer2dTqwAQCephd3Bc9Mr29rZNUQMsQHY8UO4HEcTLOX1fFNhTvmzYg/ieYQBwj/7j+uKgOvX08R5yd8FMiq+HKnfeNsSTET7gx+EDBCKw9/KGTgNgZIQ6bCN6G6EDx+OxZW951jBJaNJ5c3OjWq1m/QyZ9EIJRxiGBthjVyuVism1JNPPZISlqJOYy+WsCTLHkGQy6PUockgQl1T64X2Uj70ektx5cDcJIAbMI5Em6Q2fx/eN4zOUeBDso88AgWBneIAHANNPzsrlctY/ExBJkgGKvj8niZ9UKqV+v2/9xQj2GWpAH6RyuRwZEQ6oXi6XTb9Sznl5eWn9megDhsx5G01JlLcDd7Uektyx4r4bf+OZ+wRzXD49c5Zn4X1zZM9/hn6W8/k88szRcVdXV6pUKmo2m6aj0um0Go2GKpWKgiAwWatUKgbUS7Jpl/iUk8lEl5eX2tvbU7vdtjgHvUigPhgMItciRSso0KcMTuAeYeO5ZpJUyOddrYckd/G4wceIJAmpOIjbDE+IoAzN73v0GslBQJrJZKJKpWLMXV7z+o3eht1u13rAAqTHE30AnvhpzWZTq9VKjx49MoCT/QAYeXR0ZAnNbDYb6XlM/y6f4CHxxD2p1WpWVofPuVwujY0qrcF4mtmzPmbc8ZmplLwePFMpvuJGFKGESo9jkARAQffDmQTJR3iSHGwWU4gkRTL50lr4GEHqG9EmHYfzYhPjwGMEPGPFOxZ8lok2cUApDn7w/rsM9h9KRuG3riSHjedXLBatTt4zlOJGhWwA9czx7H8cCI1/NxlKMhVxRQdN+rbjeBCK1wGycDT4DjICHDcpoIfSf3V1lRiU8t67lME/i9wlAdzSJgAmu57k0HlgGhCg1+tZk2uCehgpXn8AEKB3AATISMUZoPRj8j11pKjj7o9L00WcFBwf9LSvp+favPPr9eHp6ekbgFI8uL8rnffQ5S5J3nwvhsPDQ0ky59EzankuYRiaLmBoALbVMy12d3cjNHuOy896vW4jjOntwWAEgCGCm7Ozs8Q94PVvHJRETmErcE0AFMiY33e+NIb/j8djdbvdWx3bz/ru3SsONGWzWbVaLWNO+MbqgHr4eZLU6XRsEmC73bbjUtZDqS59ktLptHq9nqR10NjpdMzPgrlydXWlYrFowCag0KtXr4zR1O12DRQNw3WpVK1W03A4NLYSY9wpD/JABL0SF4tF5JiwDprNpjGaAcx8X7nhcKjRaGRBFuuzvrt9JSUHM5mMTZH00yK9TsM/IiGMXPL/nZ0dSdLp6anZ1YODAwOEkGXKK6W1HoTZcX5+rlKppHq9HilthAH04sULPXv2zED0y8tL9Xo9Y5mgr/DFYHUSo/T7fUvOwJDL5/Oaz+fa2dlRu92OJA3K5bIxZnwCslAomDx2u11LdsZl7jNDLrq8jqPMMJ/P69GjR+Yv0arAx6LFYlEXFxfG3BwMBtb7iBYrJHFyuZxKpZLZSJpgSzKZOTg40GKxMGCJ0vGjoyNJG0YQOuz8/Fyp1LrH0dHRkbLZrPXims1mpjsrlYqV8sGyKhaLms1mOjk5UavVMrYluovphzCcsc+NRsNiG196xz3o9/taLBY28e2ufLzPTKXk9adgKsVXPNvF7wik78GB8Hl6K9kJKerYJh2b97EBfM0q2X+al/rg6rbzjh+XY2O4PODkM1Vk7Hy/gPix3/bdd7EeUkbht64kYIl7vFqtbCSn/3sQBJGeW8ikD7SRlXd9hweFfK8S5CTOjkuS69tkjrI4DKlvjouce/B0MplYFo5jvCtT+jlz//aVBCYmAZQEV5Th+jK4+DP2x/Qll8iMZ8x5sJFj+WP6OnwCed80lHOL650kPcr3ebnyJcJxNl88e0xfnqSyD/++u1oPVe5uA8slRZ4nYDO2DufVy148k+qTIDyndDptvRnijAFkggCcke5BEFjmHgBotVrZ5C5AIq8L/fP3IKlPNMEKRQ7JukobpmY8cyutnzVl9L6fQxxQuov1UOVOerPviCSTNcAXDwT6HkvoInwu7JUHDwmIYQ/NZjNjasznc2ucHQQbJkYQBMYigYkJe4PkShAEGgwGkeeN/fV9u1arlWXhKTkBYGUf0UOHkd30cYJpwrl5QF1al+n5sri7Xg9R7uIJXWmTqAiCIDLNz+s178tj60jQUEJOnyKYu2EYRti2Nzc3GgwGxgxh2hbAFfru5OREQRAYqNPr9dRqtQxg6Pf7Oj8/tyFA4/HYSvAoBae32Hg8tqQzQzlg+W1tbenZs2fKZrN2LgAV+LH4dr69B/uEUvekJPzHXA9d7qRNo3gSarw+mUxUKBQsoUJlAYBTo9HQ+fm5pGhLAI7p7SlAeS6XU7lc1nQ6tQQMAHWpVFKhULApha9fv1a9XreecT/99JOeP3+ur776SpeXl3r16pW63a4BSCSWr66uVC6XNRgMdHh4aGXD//znP01fwpDvdrva3t7W/v6+JTq5zyQvYf75iYUAT7D/2Gd3tT4zlZLXnxZUSgqUec1P6PK0ac7X1+zfFqDwuv8bm8UH8ShczxDwzlLcgebv/MSgwUbw9zPOMsEJuW3alj/3T7EeovJ/13rb/YTxQ7lEPBj2JUY0CPVAaNwoJAGDyBnsOt4HKw4HmO9MKkmLZ+95zfe78YCpZ73wOTIFOBW3gVXx77sLx+PPJHf+niU5D+gIf8/fVhLnn1VSP6b48f3zItjjnDxgHweV/Pkmnbu0aSSJfKHzfAIAmfOAgbTOyMI0jQNf8e++q/WQ5c7ft6R9jBMcBJvegNg3PwDAMy7JuBPIEBjzu7eBcR1BQI4MwOTgffTPwgZyjknLH8/LPMEcU5n88A2CTPRqvAQLQNOX0ScBqXexHrrcJek3dAC2iL9TiuHf73WFD4bx9WArhWEYGWTiwR3fG8z3P/LyQIkRgA99auLAgNe7ABbsB3/u6XTaGtoiZ76kLgxDC8RgrqPHb25uNB6Pzd5zf+5yPVS5S7IR+DvFYjHi5/uBFl4ur6+vrSwnCAKrTMjn85booJ9gOp3W+fm5er2eZrOZDSCAfTabzQwgohQKJnsmk9F0OtXjx4/tvUyAA3SFASUpYjM9M4Rr9eWcX331lZbLpU5PTy0xtFqtDGhgejCfgyUHQDWZTO40qGc9JLm7zQbEmeLergL2oEeQQSb4Al7TAoEED99HbzqavI/HYx0fH0d0V7vdNoB8Pp/r+PhY19fXxlhD55yenqpYLKpSqeiHH35Qu9224wRBoHK5rMlkosFgoNFopE6noyBY9zd8+fKlgaskn7Gjf/nLX7RaraxXFHtHkk1WZ29NJhMD4NDBAFp3KQufQaXk9acsf0ty5jC+1HNSxsPrbBoyD/QDeVvgGzdCbBAoqBgSzwLw5xN31OPZOQ8m0Q8gnsn3LIHRaGROR1JgxbprZ4P1EGmqv3fFnydIe6lUijQd9j1IYMnRLJGAh/U2OUGuwzC0xt3L5dIYSh448J9NCvB5jRIkarL9+3zGF/kjmHpbY+RPJXPSn1vu/PMks7q9vW39FbxT6eVB2oDR/X4/wpZ7GwjkvxMnCIcFYFHaON1ejm8DGVmcD6UpyCFyljQhjh4SBFRxQ/9Z7j7cij837Nz29raVEeHM8pySQAKy2jiwBNdeNnzyRYqWS9KHCUBekk5OTiL94bysJbGF4q+h6wjK4ot9hEzG19nZmZVX+c98ivVnkjtvmygd81MB0VnSRkY8e4dAA/CyUCjo/Pzcgi16lwCSej+OY/I9MEGfPXtmQADAgE8UedmNy7H3A/k/IBelKn4hk0EQGChATxQ+T0Df6XQ+qfw9ZLmLP+8gCKxtRrFYtKlvPjmMDPH58Xgc0Q2UMRKM+yScfzb0ReK7/bAeACsYJkwDHAwGlqyUNmVxHsRE9jy4L236JeELUMpJLy6Og67d2dmxmMhPF+a4MOQGg4F9x13K3p9B7vi9Wq0qn8+r0WjYdzGhEp9OklW+3NzcqFqtGmPNT3qOM4b9sKqtrS0bUlWpVCJxJABmOp3WeDzW/v6+Li8vlcvl1O/3NZ/Prbk4k9bwzXy8gS5MqpKIkymwrzDSAfxzuZy2traspx4MQEnWYsEzNONxzsdcn8vfktefkqkkJQdEKFucXR9gecBHUiQgSsrSJi2/WXy23h/DK/ek5TehJOuc788hfq6U1zHx4zYn+l336WOvh5RR+L3rtgAcZYlTjAzexuAByY8/46Tv84GWlz0cn6TviQNIngnAsdLpzehk77zyE2fCl72R2YoHgncpX7etP7PcseIy53uv+dIf/3xwAgiQ6E0T11FJoDR6ypeW+Cza2559XPY8C4GSEPpA8P74NEKv12jefJ8AJenPJ3dxgMgH8/9fe9ceI2dZfs9sd2bvN0pMrAVKrSZGa7FQLCiYGiGmJhZjpKFKq0QxoaQEbQmiJjVWkWoTSYX+Cl6CqRUjFYRUC4oV4Z9ardILLZA0aC1td7uXue5ud3fm98fmvHO+Z7/ZW3dnZ2fek2x2dy7ffDPfmed9nvNcXu4MpD8UyNVGEdbm2PY0Pkbtjp4HBxoz2GcWnZy263eYyK32kbYurK2XgibPwX7WbGMpBUEJKA/ehV13/q9Cs65HnCui9ouBmbaF0S/TIcxh14v3UUhkkogtP7Q9WpkOBCurgJFBPB/DY3P+CSuT9PqpUMpAUSuXcrnh6jz+EDPBv3LgHcHPT1uRuDYBwepfrUTXDoVYLOaGdVdXV7sqWl538o5rLvmlNojH5bEikYgL5rkroVav8fE8L/XVdGMBrShlWx2HbvM7Fo1G3fkA+RZmzpMqNPag2NybzbyziTZeK1YmsWKWXQf19fWBXZ3pK3EGJe2fzjy1AqhWlDc1NSGdTgd2JOQ6yMKKyy+/3M215PXXQeEUd1hNxN00dZC49R34ozNnaQsZ79I+s1owmUy6OZ4Us7RSqdixhq9UCkfZi0phGUslnw4X1UCZxp6wDq7NbOjj9G/bWqePt+KPOiHMqml7npZ9M7iis8EswlgKbSFnrRiYzcZ/LIQ5v/xNg1lfXx9wYjWw4jlz8aBaXwg2KOdvGmgr8Ix1vppRJffCuKSiKQBXncJSVvsaMx3YA5XBO2uDGHjoDBt1evk/wVJ727poX4d/qx1joMOWDX2MrUCxx6WtUweoqqoqsN27Bm3aLkIbrUNv+b68mDm9sBywO5Jq8MXz43pFaPsvd9MiCq23vI+co3OtAXWhxE2hBAuDvkgk3w5PMYIVwioM6PnQ/jGbXAooR97pmsnAl8EPkPeJrHhD+0KBc2hoeCdAtluqCKmvo1XgtqWztbXVVaFzBpPaJeWZZunDqjZjsZgTkigCECo80L5pZQxFfAZYo409KAbKiXf83MkxrWQEELBv7IDgdWcrHDc54ewtigAqWJMbDIrJXX0suxXI12g0ip6eHlcNqraJ52o3QggTvQA4sYrfK1bBcSg0PwOekyarmDhIJBKB1qNyDu6ns80cCHaosGqHora2yFHg5Hc/k8k4OwUMC4Dc2MkWTpC7jBk5s0irhrl7M0UedtwMDg66mUm0gTwnDm7PZvOtxOrv2Uo95TQ51dTUBCA/65OznNgSWl9f72w3EwWsji82vKgUjrIVlRQ2kCHh2bepWXd1LjTTAIQP3dRSaw3Kmd3UQMd+yazTzMfU1dW5Ej91YrkwaGtJMpl0Xzg9f4V3dmcWNLIcMqx8Ui5ks1nHR50BYQM4IDgoUnmnzkshWEGUAd/g4KAz4vw+6OP5Xng+/f39rvXNzh4rFc4BlcE7tStc/HV3IUIdD63YrKoangvDRdse1wZd9nbaU1txYh0ZG1iRf9zxgy1VevyBgQHngPB5AAJtb4UEsJlEOfNOEyBcdzhUmLdrsK3Dk+k4JxIJ9Pb2oq6uLpQ7hE3O8HHMpPKH56W8tFBbmc1m3e5O5B4TTHR2uT03RTMVDbgrDh3wUkE58k75BsDxRROBGkQTvN4cKs9ryh3+wmydPlcDIa7jnB2jg2ELVcVp8si+F/p4FJdULNX3xTVdZ4FS8Orq6kImk3FD7vU9Fxvlxjv6RLzuFMA1WcJrxvtZfcFWI/pxug27FaZ0PbVtRPzd39+PxsZGXHrppejv70c8Hh9xvWmL1ZaqoESQbwTbi5jcoe2j7xCPx5FOp1FXV+eek81m3bbzFM30XIqJcuIdfTcATmjUBEdPT09grlcsFkMikXAz4uj7U6CmKKn8C7NPXEMpFjU1NQU4yPiyq6srlFtql8lhXbc11uAcJ50/Fo1GUV9fj0Qi4YbANzQ0IBKJoKurC7FYzO2Myaq6CxcuzCj3SmnNLyVUjKikwozeriXvNoPODMJ4AnT+rQtEWDsGFyT+r3Mn+Jp0vDVzweOrAMaqFp5jIUHJnuN0g1Ur9qeYmGnehVWQ8DNgJkK5Yp+ru9DYaxgGdXTs7fa5moFVZ72mpsYN/FbxS8VQOrvMctCxLnR+pRDgl5PTMRoKfdbqDPK6qrAEwJVP8zYt77fHVyeBj6dYFRbQERqU84ezxKqqqtz2yGrnKEQACJR0Dw4OIplMhu50WSqCZrnzzmZXc7mcC07smqtOJAAn1LB0ni0YelyFnc9EkCd20LdN3Fi+AsPfC9qxlpYW1xZFYYzl91oxp++VCR0712emUa68s7YoEsnv1qfXnteKnNA2xrq6OnR0dAAYtnm6K6/134CRlef8rTNI1K+zIpJyTqtEtZVKdztSW8o2Fr4PihY8vwsXLiAej8/IjlthKBfehVWPaJzAKnJWltO/5fXXeZMUpjiLSCuHyVPlLqFjM2h3uAMYB3Tz+UD47C7LXZ6PrsP19fUulqB95ntlgokJH+5uB8CN26AQwdeYCZQL74BghRw/T525NWfO8E6pvG4AXJUux1ZQUNJuAwpHlicUGFmFxzWPcw8HBgbQ2tqK+vp6xzt9Ps8zTODU75HaSIqzfB1+d3RgPfnZ29uL5uZmlwSggBvW8ltseFEpHMLNnQUAACAASURBVBUhKlmoiGMz4ZrJBOBa0OysEf0S2QonOiZq9CORiOudpyNsHeBoNOoUZ+2b13LZXC7nDDoHO4dVKNnzmQwKiUNj/ZQCSol3ep1ZscRBeFpWz+vIslNmKuxsHDXkGiwpb2yPMY9tWwR4jPr6etTU1IyYJcLzz2az7rkcDMrhzFZIKAUhSVFOTkcYConGWgLPLKQVuzUzVlNT44J8Bj3qLIddW81Aqb0LC8psWxJnf7W2tqKpqcntCsZgja+tmTkAbutvzVIV+jxmEuXOOyA410/XQmujmLGn8MjKHw58HRgYcBl+IMgVnR8RxnUG30C4CADADfamDQaGRaPa2lo0NDS49js6slzvLWfpeGcyGcTj8THbjGcC5cY7e821IoMtHrb6g/aObRus4s1kMmhpaXFtE/S31F5Z382ei7Z52go5PYZdm3XtVVFMvyesvmNbC/0EFQTIv2Qy6XYZ0/c+UyhX3qn9Ive0TVaFIysQsYKJtq2vr2+E72djibA1lFzSnQEVYYlJIC/G8xyYoOGOYnwPWlnK89KWPL5fVvv19PQgk8m4OUtezJw6kE9aUEAhhsI4ux44u4txRV9fnxOGmMxhtw1b4ewu5ENDwxv7MJbUWcAA3K66rJgDgty0AijfA8UqzubihlOMURoaGlxMTPGS1UmcJcWd3/h6HMrNjan0XIqNUol1Sw3TLirRAJcaVEWNRCLOySVoKLko8AtHA6sZIyAYgGsliGY5bJ8+Pxc+R0vsdRaJfn6RSMRVJ9GwjOf9FcJowtFsRqlxLqxaiLxQQwzkd+mqqqpyjootS2bwptdZ29j0delU6G5J6qhwJwhm0tThsdkwBoVcZGYDT8rN6RgLVqxmhlsrMjV4IqfIOVYEqaCuGX/7Wuoo0Omw2X9CK5CqqoZ32qKAxXPg0Hc6S1qlkssNt11SULeY6cBKUSm8U9um18q2hhdKfMRiMRcca8LFrl3WToYJ7jyu2kN9Pa3CY6slnW/N1FKosOeRy+UHIyv/SklML3fehSX/WE2m14oVPlxPacM46waAa7XQ52lgHfa6akutTeRj1NZae6z8on/MwEoTR3xPetxsdngofSaTcQKUHnsmUY68s6IgAJf0U/+dQg+vEavPWM3D5/M2tvOEDVe3Iip/KGYyNuDf5Iw+X+ceVVVVuepLfie0+oXrMd+b2k9r1yhAqAgx0yhH3gH5OMDOx6TfzfhPh7vr8/ijuwRyQw36dNZGqR1kvKAFFzyerbgDMOJcKShxRpfavZqaGid25XI5F0+wYp4iqCY2Oc9J44+ZxEy/fqli2kUloDQCrdGgqr4G+UDe6GqWQgUBAIEvtGZobTCnzrI6vFxs6ERoea0KUDT+hQYjj4ZSaEkrJkqRc+qgkBNc7AtVgvA6kUcagOsxtR8eyDvZ6szQ0aGAVF1dHVgwrABsRVOKrGy7LJTJHUvILDbK1ekohLDPnjZHs5J63fkZkUMqJPGH2X77GnSqmb1Xx9RWjmjmU9stVdDKZrOBthatQmAWP6ztrdRQKbyzgZfaKoLXV6sxbVKlv78/EEjrEGW1jXwenVgej+stz0XFd20R5/dAucW5Eyo4qLNMZLNZpFKpUXdanWmUO+/0cyan7K5Z5BtthAqEGlAxOKO94fG04k5fCwjO0dTEoQZj5Je2FBEU6/V2Vm2qwKnJS54/qzQ5mDtMiJgplDPvrGhDO6UxAPnGjVYU9J14XTlLjmsxA2n1nzRhA+TFAhUedW2mSM7bOOxZfUj6gVxrdU1mx4bdbIGPYaUfB0P7CrnpgybRtKqINoF+nHbQzJkzx/lFKuhwrpLOM7QiugpR9M20e4GzjHRsh8YTFKD4HCaqyUPLVf3udHZ2ore31wlW7NgBgrtkMpFD/2+mUc7x88UgAmDaLYIOii0l6EJMMrNkT0sDSWoAzvmlwENjreWJHHqWzWZd+R4XBy1d5ZebSi4dWt3FTQ12b28vEolEET+h2Y1S453yjXxobm52wZeWQ+uPZsJsIKPOrN5HJ1uFID5eg3guUBq0qbBKbjI7wPLasLYjIFj6XyqwpeLTiVLinM0g1dTUoKmpKTAbgddJhSBtO9M2NBWfONSY9/FY5HUul3O7cmiwTzGBzq22FeRyucD8GoI8HhgYcDNEwgSlUuIcUHm804RJLBZDa2trQLTWYJ9OKtdMHU7KOQucD8HqIApHQH6rb/KmtrY2UCWnOyPZXZK4q5HOYeLcEHV4yVUG85y/xOHdVjAtFVQK73idotEoGhoaUFtb64JibfvN5XJudyoG3QziGZwkEglUV1cHdreizeHftKMqHvE4WlXM+SSsptQkpAqhDNTZbqKzlfj+lIsUk5R/nnfFA68Ht0xne44Vlim+AHB8opCkwuTg4GBg9yyufbRLrBi21STkJ/0y235khQ8VMLlmc13XmYY8HtdnW6HOtVc3ZikF/pUz78gLVsa1trYGZhJx3aRAyI1zLrnkkkAFOedxMXkCBMeuWAGdvlkul0M6nXa+mYUV2Omr8Xy00pz85YB3Lcbg90RnRREc3j04OBiIf2eae8Xk3WxC9dgPKV/Y0mQqskBwiB6QH17LPn4aX/anahBvy+Z162P94vLLo5nUvr4+dHV1FfmT8CgGlG90Buh0qrOqQbUaTj5GZ+VoNQmQL29mgBWJDLe3aWaK58EFh8dWR1UFMJ7reAUlj9KACnwUFmmD1O5Z3qkIDgzbPu6wxuCIgrqdDcHSfto8Bky24oltdXw+AFdBRygnmZkvNJjb825moUIy11EOcLVVIMo3ILiBgVaocc4C76MYyhkNLJ/nsWtqalz21lYU06lmlQh3wwHgBCU+nvZVvyccSMuBu8RMO7aVDl7vgYGBQIs3uaa2B8hfaxXPs9ksWltbnZhJnw4ICqWaXVfOctA8ucJdELUFSUUp3RCBopKt3LP2TG2gFTQ9igfyjfaN9gQIJnGi0ai7Vtp+SR5duHAhIIxr0oaJZcs5FXL4+urDqc+oHCL/7E6F9Ak16NeqKJ4X57dyZg99TM/B6YMml9mSXVNTg0wmg8bGRieWqxBIP0zjU4JJQCA4gsDuNMn7dJc1BSvLteKY58q/ydNUKhVI6LDIgm27FLk4DyqbzbqB3OQwbbsKtR6ljYoUldQgaiUIHVlu32qdX3456HwyQ6oGQLMZQLCvn8720NAQuru7Z+bNe8wotBqERlNbKWn41RFlME9DbEtIyTlmEjQDz4VFt1Rmib06DjbzxONWVVUFtu4ej6A0k87GTGcPdOvnUoBWIrF1LJfLuZkKBDmgDizFHyDPRwbsmnnX19EqAQ4k1cwTeUknRHmm56z8p0NrA3r7Pr2jO3MIS9DozCGuk7aUnzxj64VWTzKrSrtHx5otw9bm6Xko73RILatTGKTr7oJAMHDTQI8l9zNtXzzy0LVUW9o4kFbv12CZQRpFHWbqa2trAeR3/QOCOwUC+YoAvoZWPlGs4sxLnqOK8wqKlzrIGUDgXLn+UtDU3Yi9rSsulE+0IRQpKRZyTaQ4zt1xtQoSgKtqowiq8QMFJYI8oJ1iFSdtk24XT5GB6zkr6fTcAQSE94aGBgDBNij+ZqKIVVVhs8Y8ph9cS6urq5FKpdDc3BxoA6dgHY/H3fpIX5QbUqhgxMp1ID+PkNda1z22t/F1aDdp87LZrNsFmvYvk8kE1nlyjd8RtV9anUSfEEAgCcrqOG3X9ChdVGz7m5aUWjGIwZAG7qr0a5uRTqH3KC2UIu8ILWVmu0hTU1Og7Q0IOo6aBdBKOCDYskZ+qkBEo01BiguJBvmaneXvgYEBN8MrTFAqJCZdbIA/m4O3UuOdLsLM5re1tblgSueOaFuvcoLHsVlQvY/CDx1oOhJ0fpTbdFhUOOVx6bwwi59MJl3rp2Iq+TYdKDaHS4V3vBZ0Pqurq9Ha2hqYY6RZdeUZgzQNapRrOsyYzydf+cO5D5rFV9GejjUAN3eC5w3kZyuSz9xeuVDLRyXzrpQ4xxEGbE3SNjb9Tdum9kQrKW01kLZC6pwaQgc0q8DFTDz9SE3iqOCplUvK96GhIbetNxMC+j5KDeXOO11juFY1NjaipqYGtbW1qKurGzHDi0GxBtRcg9V3A+CqgTWYV4FRWzgpMnBuDdsjVSylaMnKFnKPx6SdBeAqlvjeOGCcFSJ2U6BS4mC58k7XOP7NeUX8TZulnTOpVMqNXWEVJRCc/WsLIWgPabfIC/XTyGdbvak+HQDnt7G6WCuu6uvrRyTMCZ3dRO5xhhI/h1LCbI5RphNFqVSaiQ9/rC+/rVRSkYgGWOeJ+Ja02YdS5J1CDTHbemjACXVAafApLoUFZ3ZRAPIik1ah6AKjVSMKBlRjCUphxn68C0A5GuZS4506JdrKCAR74tWBADCCH2ozdUcRPle5TKdYs2BWBFLuWO4xY8uWN+WzfZw9dqWiVHhns+Js1cjlcm44LUEe6GwaOqU6OwTIc1er41RoB/Kz5Hg/+aeiE29jZYoNFvkYZmC15bKQ31CpmCn7HcY7rlEMvuvq6gJVGoRm4QE4IZx/a+WkBt4MorT9XKt8GRBpC6dWp6gN5jnxnNX+cb3W9Vc/Z30vlcq/UuAdK3cZHGt3g7Ya0abV1NS4a6nbvGtwrrv7RqNRZDKZwO5xtE98Lfp7rOYkN/m6FCAAjBDP1Q7zPTDuYUWzVpyWehKnGJgp3tE+aTsaqyspdJODbW1tzr+bM2cOksmkm0+ouwBSeNS4Qmdt2SQzNwmgWMRz0IphHUbP6mS+HgUmXa9V4Ge7O+2zct+iUvk3GzByj+gSwZo1a5BMJt0Ph4UtXboUwPCXbMeOHTh79iw6Ozvx7LPPYt68eeM6Ng27ltfxd19fH+LxOLq7u9HV1YWenh4vKFUQxuIdEY1Gcfz4cZw6dWpSr6NZUwZLyWQSvb29buFipoHGXRV8OgEa3PBHS0wBOOeFLSXMzmspqw71i0QiSCaTbutYFZRs1ldLXCfz4zGM8fDuBz/4Ac6fP4/z58/joYcemtDxyQ1yKpVKoaenB4lEIsAVbZ2kg8mqTS1/ttVw5JiWWduh2zyODgJVcZPo7+9HPB5HOp12A5r5HvS9eMdialBXV4dHHnkEHR0d6OnpwUsvvRS4/0Mf+hBeeuklJJNJnD17Fhs2bBj1eDZ7ya2AU6mUcxRp91TQ1vYRCj6sHOEsNwbsDMzsIGVuLEDHl8EX76+urkZdXZ2rKlB+Ev39/UgkEkgkEkin004Q84LS1GI03m3cuBFHjhxBIpHAyZMnsXHjxlGPpdnwdDqNZDKJzs5OJzDptdLZS9zRiDzlGqkz5XSt1aCIvOaazXbKVCrlnkueKlfJU/6tFaI8Ju0ffYIwUdPzb+K44oorkMvlAmvtt771LXd/W1sbnnzySXR0dKCjowO7du1CU1PTiOPws+/t7UU8HkcqlUJ3dzdSqdQIfykajQa2R9ekzMDAADKZjNtRkpVMrBZimxLb1dkqyR/O7uImHK2trWhtbUVLSwtaWlrQ0NAQqIyi3aKoQAEpk8m4zyOTybj3Rf/AC0oXh7F4R7S1taG9vR0vv/xy4Ha1P319fc5HTCQSbk1lxS4wnFyJxWKIxWKOA/T7EomEs4sq+ujamclkEI/H3eY8bIHkDDHOQWIlUSKRcDOUeFw7h4u2mb4/P4fu7u5AvJFKpdxQ+EI88/wrXZTsTKXdu3dj9+7d7v9169bh29/+Ng4dOgQAuOeee3Ddddfhgx/8IOLxOB5//HFs374dn/3sZwGUZwWEx/RjLN4RmzZtQnt7OxobGy/6NW3ArzOWNLukZag03lrir21uzFwAeafYZkz5PEKH81G8UmfWf6emD2Px7s4778Qtt9yCJUuWIJfL4U9/+hNOnjyJnTt3Tur1tAWIQ7WtUEnBRyvl+Fsfp04mS/a1fU6DdluFp7drdRLbSApVKNljlSK4OUOp47HHHkN1dTXe9773oaurC1dddZW7b+7cudi3bx/uvfdePPXUU4jFYpg/f/6ox9OqH7VXrAjRuQ42I8oqNyCfSVc+aQUxM6FaJadDZLWaUytOWBEaBp0dYvmnfCt17s0GjMa7SCSCtWvX4vDhw3j3u9+NF154AadOncJvfvObgsfjNdGNA9LptAvEyTW9prFYzImZ2nYW9rc+jxxkgoY2tL+/P7CbklY9hQ1U1r/7+voCLSCsSrBtx557F4/W1tbQ+XxbtmxBW1sbFi5ciEgkgj179mDz5s34+te/PuKx6lOxbZfXsKWlZcTjOWuJO76pbVIuAPkZXkC+9Y3XnjOXrF+ndteeo4r4QL4ajsKSTQKw0sUe2/7tMTEU4h3x0EMP4fjx4yMqty1Ybc6EDNc0JmMI7u7Hx+laq+3e0WjUPY5+PxMyrBayP9rCSe6wVY1c5QxDVkEpd9T2scKOwrwmbrzNm12YskqlW2+9NaDC9vX1Yf/+/VN1eKxbtw6//OUv3f9XXnklnn/+ebS3t6O/vx9PPvkk3v/+90/Z63nMDhSbdwCwYMECfOELX8CDDz540cdXI60BkwY06izogGStHtFFyA7xVkeCGVGtFtJsw5kzZ9DZ2ekypKwSmA3BcTFRbN6tW7cO27Ztw+nTp/H2229j27Zt+OIXvzipY5Nrlm/sl9cARgfBUyQKO559joqh9n9CuclzoFNhW95sZVylYqp59973vhef/vSnceedd+L8+fPIZrMBAf1rX/sann/+eezevRsXLlxAKpXCiRMnxnVsW1XBwJm2jcK1DuBUQSmsJZIOuVZV6vxDK5zrBhy2JZivw//7+voCVSeFBCVbWVcJKDbvfvjDH+Jf//oXhoaG8MYbb+D3v/89PvKRj4z7+AyM2MJIrimvyAFtUePtfB65o2usHaitolF9fb2r0CTUxjGw1zWfg2g51JmVAWEz5CrN/k33Omtx5ZVX4plnnkEymUQikcDTTz89alyh11bXLlZnACNn46iQycCc1UasrtQqJs40AvLD3dWHCxOGlGu8n5zm0Hf6d1rlR+5VOorNOwBYvnw5PvCBD+AXv/hFwcfo9592iuuVJoNtuzfBOW86r6u/vx9dXV1IpVIjWszJCfJQNwyg8K2tdOSSck43WbHcpGDa29sbqMhU37DSbN5sx7QM6m5qasKBAwfw4x//GG1tbbj//vsLPratrW3M411++eU4efIkFi1ahLfeegsAcPXVV+Phhx/G5z73OfT09OCnP/0p2tvbce+9907V2/CYZSgG7wDgueeew89+9jN0d3dj165duOyyy9x9Ex3kp0E8HQy2btAZCRORtJRaK53UWPf09EzoXDwmh2LwrqenBzfffDP+/ve/Axi2f/v370dzczOAyfEOQKD10c5p0NYMPse2WtrbNLAvdJvOvNEAno55KTsTpSSuTgXvbr/9dmzatAl//vOfcfvtt+PMmTPYvHkzfve73wEAXnzxRRw5cgTLli3DokWLcODAAaxfv961/Y6Xd5oV1RY32jtWfNjZMlolovNrwgSn8UKFJtpM/q0D4UuRf+PFdPK0GLyzOHToEHbu3OkqM8fLO22JZEClQ7xt9RCAwFbt5AQDfbV1mtCxwgErBzTrrlzT2/j6mUwmMG8pjH+lnLWfbts4Fby74oor8NZbb+H06dOu4nfTpk3o7OwEAHzqU5/CXXfdhc9//vMAgD179uDZZ5/Fww8/DGB03uma2tDQ4CqTyD2tKtdWt2g0Ggi4gWC1HX/rQHhdV8lBrUJRgSlMjFTBiWtuIV6VKt+IcuBdVVUVDh48iK985StYvHgxvvzlL+OGG25wzx+Ld7Rx3GRK5xlRCIrFYqirq8OcOXOQTqedWM7h2QDc+kcRKCy5aAdsW/8wrMKI8QlFTI1TCnVOlDpKyRcsJUx5+1skEsHu3bvx17/+FY899hgATHj+h8XatWvx8ssvBwL7N954A//973/x9ttvY3BwEEeOHMHdd999Ua/jMXtRLN7dcsstqK6uxjPPPIOPfexjF3V8ACOMM4N43Y1DjbsN2P28r5lFsXjX2NgY2GUyHo+HznoYL3SxJ9/onLDkWXdEsg6rdQS0Gk6Pqxl+FQjoJLPdg9m1UhCUZoOzMFW8mz9/PhYvXow9e/Zg3rx5uO6667B371689tprOHHiBObPn4+lS5fipptuwpEjR7B161b8+te/xkc/+tEJvY62YRDkmA6qVb7REQ1rIeJnUOh19G9yiUGZZlTJOS27t/xWlHJQXwwUi3eKzZs3o6qqatQMfiHwenNml1a66c6Uys1cLud2UtKKNV53u+GFikq2Gk5Fo7DNLnS2TaHKOKLUuTed7b5Txbvz58/jmmuuwb///W/MnTsXjzzyCH71q1/hk5/8JIBh8TIWi7lg/8UXX8Sjjz46rmNr1VImk3FCJIUjIM8d3ehCK3Npgzi+QINva5+0gp2+Y9j6aVuUtEpU1277nFLmWrFQLN5t2LABBw4cwKFDh7B48eIJH19nGdnKXQ5w54wjiuU6YoPPZwucrZLUGMSKSPwbCHJM1107gzMs2cjjeN7Nbky5qPS9730PTU1NYw7zVFx22WV47bXX3P82WFq7di2+//3vB27bsWMHamtrcckllyCdTuO+++7DH//4Ryxfvvzi3oDHrEQxeFdfX4+tW7di5cqVF3/CBsxeecwuFMvepVIpV5UEAM3NzUgmk5M86zw0U9Tf3x9oK9IMqFYnEZoRZQDF40UiEedI29YSPocByHiCqUL3jYXZIBBNBlPFO7ZAbNmyBUNDQ/jb3/6G/fv34+abb8aJEyfQ29uLp59+Gv/4xz8AAN/5znfQ2dmJ5uZmJBKJCZ2zrapUx1IrmDRQp9BkBUf7o7cT1uHVCk9WoOjjC/1t30Mlo1i8I9avX4+1a9fihhtuCOx8NF6QE5zrwQ0ClHecKUI+sgWNwlI0GnWvHRaAh4mQ9n7lvA7UtccYjV+VzL2p4l06ncY///lPAEB7ezvuvvtunD17Fk1NTUgmk/jtb3+LV199FatWrUIkEsGPfvQj7Nq1C6tXrx7367ICiIE8q0i405vdEVDFKK613CCF9o+PHet1+VvFTLWdhZ5nz6eSuaYoBu8aGxuxYcMGXH311ZM6R73unL2lvhznZbIiSdfUbDaLeDzuRG0rDvG3fS3792TOVzGRSmOP0saUikqrV6/GbbfdhmXLlrmszDe+8Q088MADBZ/T1NSEU6dOFcy6X3/99Zg3bx6eeuqpwO1LlizBN7/5TXR3dwMAtm/fju9+97uYO3euyzJ4VAaKxbv3vOc9WLBggduZIRaLoaWlBWfOnMHy5cvxn//8Z9TzLNcAt1JRTHt37NgxLFmyBAcPHgQwbP+OHTs2Je9DA3ydH2Kr4ywKzQgh9FjWGRnN0bXB1VjOS6V9r6aSd4cPHx71tQ4fPhx6LS7GCdQMPQUkDbQt//gcW00SFrjb1+DxLEctp3wQNTaKyTsA+NKXvoT7778fN954I06fPn1R587rq4G6tr7ZVg/dFEN3XNXj2ao2G3wp18YjUtrHzLas/XTZ4elYZwlrz5YsWYK77roLmUwGAPB///d/eOWVVyZ13rqmMunCQF93YyO4nmqFG5Bfn62wXkjItLwMe6w+3j7XYxjF4t21116Ld77znU6I4u6kZ86cwbve9a4RAvR4jkvO2V1VtT3N+mxcX8P8Ot5/MShUPWer7jxmN6ZsptJVV12FF154ATfddBNeffXVqTgkAGDnzp2ora3FunXrArf//Oc/R3NzM+644w5kMhls2rQJ69evH3NnGo/yQjF5N2fOHFx66aXu/+uvvx4/+clPsHTpUnR0dLjdYCotyK1EFNveffWrX8U999yDT3ziE8jlhnvyt2/fPuEZI6NBg/nRsqOjBeYTqTQaT3ae8N+pYUw176qrq3H8+HE88cQTePDBB/HhD38Y+/btw7Jly/D6669jxYoV2LNnD1asWIFjx45h69atuOaaa3DjjTcCmPwMOf1fW+DsY/U5VrQERh9ePJYwaQOvcsF0fFeKzbs1a9Zg27ZtWLFiRehg+IuZXcjfyrswET0suLK272LngehxZjsHZwPvrr32WvT09ODNN99EW1sbHn30UbzjHe/Axz/+cQDAX/7yFxw9ehT33XcfAGDbtm1YsmSJa/ed7DqrPGFLEivlwqottapSORjGt7HagO3t9rw870aimLyLxWKBWUyrV6/GmjVrsGrVKpw7dw7A5Gdm8m9r28IESa1w422jiTxj3a+P03MpJC7NNnifNBxTtvvbqlWr0NbWhldeecVNzP/DH/5wUcesqanBrbfeiieeeGLEfRs3bkRfXx/efPNNdHR0YOXKlfjMZz5zUa/nMftQTN4NDQ3h3Llz7qerqwvZbBbnzp1zwY43NJWBYtu7nTt34rnnnsORI0dw9OhR7N271wlKUwU6FZzxwN099Ie7eehgUW19swGYdYz1WDy+7kRY6MdjGFPNu8HBQaxatQorV65EPB7H448/jrVr1+L1118HAOzfvx8PPPAA9u7di/b2dixatAhr1qyZ9OuFCYtsRVN+8W/drUh3mtEdZ5SDY3HRZl9HE6VmE6b7u1Js3m3ZsgVz587FwYMH3evt2LFj0q8XVomhvOMORJlMBul0Gul02u3IprsqsWpEjzsWh8bioD0vjzymmncLFy7Evn37kEwmcfToUfT39+O2225z999xxx1YsGAB/ve//+H06dNYuHDhpHdZtdDrTt719vY6+6Zc4w5blm88DlBYGLC2bTSOet6Fo5i8u3DhQiCuiMfjGBgYcILSZKDXW/00rpvWv7I7CAIjK3wLrZ/2Ne39owmh5bL+euQxLbu/eXh4eHgUD1NRqRQGW5o8XgfAC0GVgankXaEsJlHpzqf/TuUxHbwrVHUUZvdmc4Z9ulAJ/JzqdXasShD7GFttNx7+lUM10mjwvJscpoIX4zlGufKvEng3GUz5MmaSIwAAAQdJREFUoG4PDw8Pj/KDdQz8ouoxlQjLkOr/lQL/vSouwrLuYfcXuq3S+OkxdRirkmM08bIcW9k8ioep4Mp4OOg5WVnwopKHh4dHBcMHsR6lhHJxSv33qjIwW/npURoYTTCaSMta2O1eaPIoBnzlpgfh2988PDw8PDw8PDw8PDw8PDw8PCaMKRvU7eHh4eHh4eHh4eHh4eHh4eFROfCikoeHh4eHh4eHh4eHh4eHh4fHhOFFJQ8PDw8PDw8PDw8PDw8PDw+PCcOLSh4eHh4eHh4eHh4eHh4eHh4eE4YXlTw8PDw8PDw8PDw8PDw8PDw8JgwvKnl4eHh4eHh4eHh4eHh4eHh4TBj/D9ySqweLAUSgAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "mask_imgs = glob.glob('/home/oad4/scratch60/kpe_fsl/derivatives/fmriprep/sub-*/ses-1/func/sub-*_ses-1_task-Memory_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz')\n", - "len(mask_imgs)" + "anat_mean = '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1322/anat/sub-1322_space-MNI152NLin2009cAsym_desc-preproc_T1w.nii.gz'\n", + "\n", + "plotting.plot_stat_map(t_plot,\n", + " bg_img = anat_mean)\n", + "\n", + "plotting.plot_stat_map(t_plot,\n", + " bg_img = anat_mean,\n", + " display_mode=\"x\", \n", + " colorbar=True)\n", + "\n", + "plotting.plot_stat_map(t_plot,\n", + " bg_img = anat_mean,\n", + " display_mode=\"y\",\n", + " colorbar=True)\n", + "\n", + "plotting.plot_stat_map(t_plot,\n", + " bg_img = anat_mean,\n", + " display_mode=\"z\",\n", + " colorbar=True)" ] }, { - "cell_type": "code", - "execution_count": 3, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "mask_mean = mean_img(mask_imgs)" + "## The negative picture (in case there is less activation in the second session)" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 143, "metadata": {}, "outputs": [], "source": [ - "# visualize results\n", - "t_plot = nib.load('/home/oad4/scratch60/kpe_work/2nd_level/_cope_2/randomize/randomise_tstat1.nii.gz')\n", - "p = nib.load('/home/oad4/scratch60/kpe_work/2nd_level/_cope_2/randomize/randomise_tfce_corrp_tstat1.nii.gz')\n", + "t_plot = nib.load('/media/Data/work/fslRandomise/randomizeNeg/randomise_tstat1.nii.gz')\n", + "p = nib.load('/media/Data/work/fslRandomise/randomizeNeg/randomise_tfce_corrp_tstat1.nii.gz')\n", "# suggested threshold should be a=0.005 / .001\n", "\n", - "thr = 0.95\n", + "thr = 0.95 # shuold be 0.975\n", "t_plot_data = t_plot.get_data()\n", "p_data = p.get_data()\n", "\n", @@ -152,24 +234,24 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 144, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 8, + "execution_count": 144, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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Sr6DkfEblwQoVHe3ohOb9+ffnPVUKB3Sn7+P55eD9+36hklJVNiwHOxmSo0kYIWOY+4PfMwLH18htKkn+TCdNvxZmVfX+V6xYIUmaM2eOQgidwagwNkIIoRVhBlD6Ptigo49EacDEVPSDFfrj1Bin1mzE0peEdUcaOc1zeppGbcn4pc+FDW6fOweFrBfD/XM6nFOndITeuXOn9u7dq+7u7rpggXDgdKSxsWTJEkk1p6uTTjpJUu2B80ivlLWRiXN8k3PuulqPwg+Ul6V9MByLaX5d/tj1JOLLcWBYYaLzGX02DDt5d3Csulp1gKvuj85o7sg42i+lhTYMVWTn7vZQVq/mDbGy4XVc06SURInSe1VOluoldrfF96i/Z+QN00WX8n64s7dqY0XEPlULFixo2O4QQvvQkcZGCCG0AzZebbjZIKRxyYGRByvGBpoNPxt8HsVzOo5+DYMZv1QNOP3YqA4Js56WDH86WXPfNkaNjWnmDin5bNiIZa4QXxNf66pTdldXl7q6uurCusOB01HGxoMPPiiplhjHnv2cE/YIzA86q2FyVOmblVJlNXyMNzxVEu/DlHIQMD2xo1auu+66oV6GoPrf3rAolDsm/w6+7r433OFRnubvRj8E5u+gExwd8JhPg9EuJR8ROrdVz8HKhEMF3akyXJGZRKlEUJHwvew2WH429C/xs0DVr1Tm3PK7P//t3/6tpJGtFhtCODg6ytgIIYR2gtEdnMazscsIDY7G6Yhcmr41TKtfCrHmoIiGKvdbzRLKCJZSYUBDZYNtoVHMjKSEfi/MesppwqqiMn78eO3atUsf//jHdc8990jKlPbB0hHGhksEO5eC4/mtYHC+nUlgPGr0zeft+KAx90J1NMlOg6M2jnzpYOWROKMl3Nk4X8Tll1++z2sx2nFUj/103CHxujPDJ6M76IPBaBPeS96/16NvB2Vq30vM1ml8T/Ie9vF8n7DqbPXcqIZQNnYb6SdSCntk3g23xcoGQxLdNvp8lCR8nisVEBcpmzt3rkII7UVHGBshhNBOeMr3+OOPl1Q/7UfjlEqCv6dxTFXABiJH9TbgSqnmaZwzgoNGOHNmVPdhOFVo6CRPp2emD7BhXqqFQhXGcFDJTKLVqc6enh6NGTNGkyZN6p+GDAdHWxsb9lZ3OWbntvCIiHIbR7nMcOgRmG9GVrv0A0f/C6nsnESpj8f2MR0547bwYff6mb/eN8xTYejj4I7JzmYeVXPUz5wS7HxLvy87Wr4EvH/fY3YQ9N99Hj6O2+n7Y1+5MRhNYqXPeTdYLpzZSr0d00vzxeXt7WNhfyOfO6NMGPVF6Z5KDBVIZ+dNtdgQ2o+2NjZCCKEdsQHIKV9Wcy0V3qNCMdRRPnNQUEmhMcxoFhqc/judhKVyzhA6RZdCr91GXxsb5jZeqYRwqtrH5bQiry0zipquri719PTUTQOGA6OtjQ0/qFY0GMnhm9GSHyMImIjGIzrOORs6PPlBlMpOTaUHqRQB4CXn4qnWOEPmLbfcUrw+owk7cf36r/+6pHoJ1p0kC0n59/A9ZAWBHZa3d4fHtNEM52Pn7HvQ6/mzOziqaKTkA8R2SLV7kNEdjIQp4e+t6vhF4nPy332N/Nz52hlfC6/PLK08FzoQMjKISozz6SxatGif5xNCGHna2tgIIYR2wlO/p59+uqT6SqeM1OAghX4GjZK6Vf9eqqVC51sqGyWfDfpu0KiuTity+s3QX6SkznBQyCll7sd/p/9Kyf+FAwr6eHR3d2vcuHH9RvTSpUslSTfffLPC/tOWxoZ/dBYv8k3nz5TrWFei5BzlB5O5MjiSq8pu9NFgZ0Flgnk5OPfPcC1mHLWqs3LlSknSrFmzNJqxgx1roDDdcMmxzZ0ofycmUWLZbEu87pB8b7DolLd3+6iElSTlkpzOEMTqS4j+HL7XmG+mhPdtRcO+HvS9YO0TytT0kfJ+Nm3aNKA9JSmf7SesOhtCaF3a0tgIIYR2xIMEOjLTF4JTtnSq5eh/sEgPJoljqD5h9Asd2zmY8v6rBqANc37HHB/+zOm9krP9YNtTdeEgspRQz4wbN07d3d3q6uoa4K9hJ/5wYLSVseG6IR5RMedBo5umup5vLo/QeDPTW77kld9IjeADQdnTNy0rXTJDZMnz30v6mfh4oz0PBwtS8Xdg5+hICXbqJfnan3mPMeqE9wHvTXbaPH7J8Y+qBB33qu1gsiIqCFQcSpEyzATq7e0DwgJYfH6M72W/HAbzT/Hzzd+Sz6XVrGXLlkmS5s+f33B/IYSRp62MjRBCaGfsiGxDrTRNx+gRGp1UGGzw2eg2JV+M0veEmUvpA8LsnlVlo+Q073P1NiWjl34nPDYHFD62BxIOJ2cSutJ+qkaza6NMmDChvz1RNg6OtjA2PGp3AhzfnB4h2buddSP8gHiEV8oOWapzMVj63OoDyrLIbpP/7lEYc4HwIedoj/4jHE16OdrzcFDpoYNbKQyPDnb0b6ACVUrr7HuIShR9N+hjwQ6wlA6a7WZkSNW5raSe0E+ILwxDxzuGSfLvlLGZv8ZKBCOrDAtu+Zqx4Bb9oZgGO4TQurSFsRFCCO2Mo1DOOussSfV+B4wKYXI5Vi41TA7IadqSkcvtDZ1z3c6SU3Fp+ri6LSvX7mubRpRyh9Dgp0FuI9Z/5344hV09Jysb48eP7z+ep/ec/XXevHn7bHcYSEsbG8uXL5cknXbaaZJqP7bxzWqveY/yOA/uEZJVBd6kjO/3g+00tf5MRaSaZ8Prlhy+2JZGuTqk+nnp0giYnYdHi3ZAG23QT4C/FUfvjFJh+BsrpzIsjh1fKcqF9xplZ6oFVizoJ8HteX8xY2p1H35B+YXke6RUCMt/p4rGc2V9mJK/CacO6JfEZ8btLeUFYXExTx3kJRBC69LSxkYIIXQCpdIJjDZhmD2d0zlNx0yfpeqwNhA5JWVK1Vu9n1KBQcMpu+o50fma03BUdbhPpq3nwMDnzoEFB2wl35BSLpOuri6NGTOmrr1MXheGRksbG0zly5oJxjehFQ4+OL5ZrIzQMYnpaO0LsmXLFkn1D7pHXtUHz39jRlDjESvVmVLlTXZCfqB8rlZS/NnHc6TAqlWrJEkzZ85UJ+NMqtOnT5dU74fDkT9zQzDhEBWRRhKrVJ/kiEpJqWKwlyX1wPcR5XLmhOFLpHpfsWIwM376eWLOD+Pny+v53mX2VWZFLeWYMVTtmB6aDoTMz1HK/Et5/u6775Yk3XrrrQohtAYtbWyEEEInYMPMAyIbcqUQZzqrl/wSSqHyNIbpH8EID0KFhJVXmdejUdr8UqJDfi455JfaSEXD14YDDQ7ceG5UMqp+KtXvuD6nbMPQaEljw6PV3/iN35BU/8Bx/p1ymR84Rqn4AXdkCG9mr+9RJWs6cF6+OnLzvLT3Tecoho7xgWOyHdZnYZSKOxefk0d7dAzr9Boqvu5UFpiRk4qTr7tH6/6N/TLw9bNkavXL+2OHR0nYS0aPMAMpc0ZQlfC9yAyyvB+qHSqVOzrU8YVB5z+GU9L5kHI0O2HmJOH+WZWWdYKYQ4TJmfhM0YfE1zKE0Dq0pLERQgidhA0qT816sMEEaVQ2SlkzmSKexilD7zl6L/lJUF0w3L60rG5XMk5Lxyodm8oC/UeoXDAtQKkOTMlHpK+vT11dXdq7d692795dlzKhlIwu7JuWNDY8/1yq2so5Yz+ITrpSCnEylM9KaWuZY4HrVRUWKwweBfqzOwOOjA0lOe/bfiPuPJhXgc5WdOjyNZw6dao6GSsPzDdSknDZaTO0kH4JvK4ejbMKrPfj39tLZuHky8b3BUfjLKNtHx232+s3CokshQZSLWPnyc6bETlcj1I/nxMqgwzLpP8Mn1sqGqakcDLbawihdchTGUIITcKp1F3llcaqi9JRqbBRzGlARkZw+o4GIEfvXN+UUtbTEbnRQKu6XXXAxgR19POgcchw/pJvBY1mOlvbgPeyVJizNM23d+/e/n87d+7sN3r9W/laxBF5/2hJY4NZNvlg0GvdN59HSsybwTneEowIGWwk6JFblUaOUlL9PDnnxX1O9hlwqt3NmzdLqj30bhtzF9CBy/vv9DAtX7+SExr9CNjxGPpa8Denj4yvKztIjtJLSZlKSgt/L4Ya8iXj9avKhu8dL9lWFvuiU6FfHHyevPR6vGY+Z0Zt0VmRzwa3LymX7A98bfwc0t8mhNA6tKSxEUIIncDRRx8tSZoyZYqkemdbT6t5aYOJyoSNSxuAHL3TIKTTLROgceBVql9CB+pSjgsvq/4M/huTwlHJ4Ge2yUax287QaNaF4TVgBA9VmkblKHp7e9Xb26v33nuvP/Ta23mgx/aGfdNSxsbSpUslSWeccYak+vwaHPn4JvQIyjeFHxDfdL45BnMM8nG8Ph8kdwSNakrw4WTxH7fFnQ5zfuzrxpfKiobb7OOxcyiFtrU799xzjyTpN3/zNyXV+yXQOYxlrv17sbKoO2FGJtFBzvcmOx7mgvHvxIgJqmNUYnx/0D+B7eB9UN2HsapCRYL3GHOM+HsqhKZUL4ZhmP7Mc/U5lhwHS86Q/o3pX0P174EHHpAk3XjjjQohjCwtZWyEEEInYaOUhf5K4cWs+mpD0dOpHlAdd9xxkur9HhjizSJ5g2UOZUFJOqaXMpdykFVtO/1NODVYKgXAKWlfSw46aZSyvozbQeOXUSXVsPNdu3Zp7969euutt/r354HiYJVyQ2NaytgohX/RKapUKdUPBCt50gGICsdgIVmlEK7qg+VoAT7UXvqBogzKtriTKOVdYBhWSYKkZGglYOHCheoEeN7MBEpFh+mbmbeipHqxdk2pSmypUBVlZ/ojuJN2O3x/+D5gDgu3n3lZGiUa8rV5++23JdVeWIYKIZUNdtr0hSLMCUMVx52+XxqlKDGfCxNLef++ZrwWDiMtRaGFEEaOljI2QgihE3AyvVNOOUVSfU0TDi6YPp9Gqb9/4403Bvyd9UJKqeNJKfcFjW4umYm0lEm0em6cyizti5TKTtCJmoNGDj49EPSSWVVpzHZ1damvr089PT064ogj+o9nY5tRLK7ou2DBgobnET6ipYwN3sCsnMn1+HePMn1z8CbhzW784Hl+3iNB37RsD733q9uWigyVjs157tLIlT4E9PlgnQsuWZOl3WEEAz+Xii5xlF0K5TNU0/z70PmNFUoZrsd7yOwrZXJ1v1a6qJSYavspqVtFe+uttyRJGzdulFTLS1Mq/uVr6XMt5YRhBFRJ0aAcTvWG6o5fqL7nndPES/poUMnktQ4hjBwtZWyEEEInYAPIhpINPRti9KnwYMHbcdrN2OhkWQQ66ZYSnpUGI1Qm2C7vn7kqbNA2SgNgo9HGJZUMhn8btq2Ud4PrM5LGRrIjfTyN6AghJzzkVHd3d7fGjRunnp4eHX/88XWlJzjgYCHP0JhMaoYQQgihqbSUsmHZlFYy0xwz9LTkJMmkP8bTK6X0yk6GRKnd+7OlXD0e4+A5X0nnV3pUez6RWeroSOg2eMTBkE+PImjtO0SzU6DXPZ0XWY6c01f0VOf6pRGd4bwtR2c+nvfDMu+c1mGBN+/X7WHIM0dj1SkD/59pxb2tIxrcJoaY8xp6f74H/XdOQTFJGKchfQ5M2sew71KYMvMrMK06i995P0uWLJEkLVq0SCGEkaGljI0QQugEPM1hQ44VbD0o8ZJVimnw2RBjyGxpAFbKy1Iq525KScRKFXYNHVyrbaUjZqmu02BF4UpRg/xMPy4b2f5NHLXkQScHgN3d3Ro7dqy6uro0ceLEut+ATr6pxTM0WuoqMWSOoW9+wAxD9DxK9YPmB9vf+yZj2CK9o/lgmdI8qFROlc598sb1MZwwzEuO8jwvyAeKycSYnpvLToEdF8MmOZfNEFauz3vM9wadGE2p8+a8NF8mVhNY+I3qG1N1e3s6ddIhtnquzC/gdelP4LlsJqDj3DrPseRUSwdN78+du19Mbl/JqZYvXu+H16T0Ah3M+TeEcOjorDdQCCGMIA55nT59uqTaaNoGn6dgPVVLpcLr0cA66qijJNUMQw6kqDSYUl0ZQlWBiojbUyqqZqqGHQuxHWwSrKGWoqeiwfwrNsZ9Dpzi7uvrU3d3t/r6+tTX1+Gn5jUAAB7GSURBVFcXAcYoq9K1DwNpKWPDDxZlLlbv44/M+W2OvCh/eclRK0ehPg7nrDnfL9WnjfbSbWYmQcN6AT5XJgWjDwYz+PmcqNZ06qhuMK97Q/maigEVEP5uHF2XFBV2wtyOqpp9c3iPcf9ur8M9vV+/xOgbVP0/czYwiZefN6pkVlmYQM7PI8OM2fnznmTYtdU7+nTwmvlepk+JFRm3s+RL4vYvXrxYIYSRpaWMjRBCaGdo/DFplw0y5/KxYzjTmNPB2NNn/t7GJ+s1cerLlPwjSn4PHGDRMKQhSsO2ui8ODKiKlIzXEv6eyglDZOkbUvqeDsk7duzQnj171NfXp61bt9ZNy9nI9YDB+7Gqdcstt+yz/aOVljI2OE/uB80PKueimYWP1f54UzJJEeWzUqlresub6ii6NL/sYzC6wW3iw0yfDDqCMWUzi8XRkazk0NXulH4b/r3kv8Dfh05ipeJhrGVRLYBWbQd/x1LlSmZ+ZC0LKh+sCmqqKcRZeJAvGEbGUN2heuYkYJ4CoCTP54z5B1gwjSnm+Xz6mrIIoaEC42vEa8faFyGEkaOljI0QQmhnSpltGZ7vQYCVDSsdHBywNDxDoG3YUVngNGyp9g9H+0yM5SkrZnOmAsL28v9VSonEBqtZxTYy7Jv75YDDxqinNFnXyL/F9u3b+5WNLVu21KUfYEZcTy/6+9CYljI2BvNu59wuCzaVbkbmMPADxHTOxjcn0yLz5q5KhpQTKWfyAWLZerepVNCLvhg8Vx+XnVmj1OqdAO8Vjq75mb8Z85O4U6aPB0fHHtV7v0y9TYXE8OVjWZyqnSlVqqRjoH9nKzXV/9uvgxEyXrIIHNvKFw8jaCiLM6+Hz9X3dink0ZReTjwOf0v635ScF0MII0dLGRshhNBJ0PeCBpa/d3QK05pz4FRyRKcPhaEjM49bUjo4tUynXxqiHBBKZbWlVNtqqNV6mbacDs6lwanTk3Nw6UGlf4OtW7dq9+7d2rt3r954443+a8pAAv+mvvbePjSmpYwNz8FyFMcQJRYhY86K0lxtSV3gnLX3zwgBhkB5Drvadu+Lqor3SZ8N79vfszaBOxM+sKw3QN8Nt4cqTadAnweOrkvz9nTEM5RI6UNj6DPD4/t3GSxhEaNK3AGyqBnbU/JXsHog1e4lRnOV8ld4H8xbY6gc8EXo58Rt4DWh3xId9ghfEtwfM4iWXoydGokVQjvSUsZGCCG0M6UsmMbGKI1jw7B6hj7bYPN+WPG2lIRuqO2k30PJ0KRvSaNQe1bJphM3k8SVwsrZZk59MpEho1PofO3v7aPh9P1efvjhh+rt7VVXV5e6urrq/GQ4pe3fqtMSJw43LXV15s2bJ0las2aNpPqbijcP590ZzeKb3A9GaZ7fD4W384jQx2Vcv0dOlESrx2DbDBUPH6s0v1yaqy9FO7BNbvv8+fMb7r9d8b3y/e9/X1J91kuG27GWCvNoUPJlh8fOlI55VNX4UqDvjqF07HbyPLw9FRU6r1Xb6G2ZOpudtJc+JyoXXJ/nQLXHih9/Az4TfEkYKhmle50vJ6pZ9ocKIYw8LWVshBBCO0MHbxaXtMHnqS4blf47p2o9WLCywelSlmn3lBkTodFoLhmMbientLn0edEQrCo5pUybpfT3dCyuhnNXKQ1C+T0T7tFAp/O8Px9++OHq6elRT0+PpkyZUpcrxdeapSJKzv3hI1rS2NiwYYOk+gyCHE166ZvLDzAlRtZUKaW95aiWCgnXq6oIPqaXHtkyeyKrfNLTnlEUvJHpb0LJ0Ou5k3KOhE7FnbCvOztVKgbsOBi947+Xon54D7KTZVQSq/TSP6iE70FKuMyv4t+56rNBvw76DTFPhttEvxUqHINFdzBniZUF74/XnE6PpQRYzAzKLLxUKK2s3HDDDftsbwjh0NGSxkYIIbQjHAjZoKNvhnM9eIqL03gclDCpHMN8vb79Dmzg0UmYodk0ku3HYIONo/5S8btGPiLMc+F9lIxFRn1wirm0JNwf/V8Mpwmrior9NaxwVNs9mPN2aExLGhtO9/rQQw9Jqs+eaXzzUG5jMaPSKNLfc8RFqdIPYCl1r1Quzcw8ChyFlRLSuHNiZUzj7ahwuI1vvPGGJOnGG29seO6dggtTMZytFA1Sigrh6JoKE0f7VMV8LzKSwr+LVQYrHFQ66LdAqdjru330k/B1kGr3q9vKjKFUEBglwqqs9HkqJVuij4g/W3XxZ+/f19z7Z90avhipsDAaxqGHVkZDCK1DSxobIYTQjtx0002SpCeffFLSQD8Aqb6MgA0qRqHwsw00ThHbqOW0mo3RwQxFw5B5G6xULjhNWarAKtWnv2eCOjracxqOYeQ8JqdA6YjMkgO+NgwU4FRkb2/vAEOdSSSZXK5TS0IMNy1tbHDOdcWKFZLqZTiPaj2i4sio5EjEuWzf7JTFGN/fSNngDew2MPyLjl+l2h6lfAr0yfC8uDu50cbNN98sSVq1apWkclKiUhZKRjawMzWl4lGEmT2ZGZQvBaoLpYJchp2+7/1qe3xOvjeocLgNfIH5s/flz+xU+TwYfmZtFPsPeXt/72yqfn7piMfKx3Ts84vxl7/8pSTp1ltvVQihtWhpYyOEENoRKhcc+NDRm8apfSZsqNkgo9M8fTiYx6NUZNKwHQyxZ7g0o2VKieCkshrC6XA6U9sI5bQa28wBGaekGS3C6TxfE16rnp6efp+NMWPG1CVYtFFdqnsTGtNWxsacOXOGtJ5L/drBiE5S9MZnRAdvIkalsDRx9f8l6ZA1OiiT+oHwvLMdvUarYrG/UEJ150klqOQrwd+0pIKxsmhpyfA65s2ghMzQSKoNg4X5VSujHnPMMQPO1SN/5tFgPgtWWeaLkuvT4a7kPGjFwve41SiybNkySdKUKVMk1RRH+mTRR2PmzJkN9xdCaB3aytgIIYR2wMarDTgOdOiEznl/+iPQUGQ4PiMmmEm0ND1o6NNRSjFPRYMRJ9VEahyA0WD2Z4aLl6JHaMSyLUzd7890smZCPxrPY8eO1dixY9XT06OJEyf2D1b527E9ybOxbzrS2HA0Swn7fkybNk1S7abzzemOwTcpR3qNRpl8qEtZSxlF8Nprr0mSrrrqqqGeXmjAlVde2fDv69atk1S73u4MGT3Eqq3MrkkplU5qTD/NzptKFx3v+LJhXRG2i1E21XvR6zpHhztZVhj2/c4XWemced/Tb6V0r/PFVaLTstyGEGp0pLERQggjCZO+cXq1FD1ibJjR4ZhOvzb8bCzTwZjGNNvBaTiP4tkO1hXhtLANV0//SfVJ5EqRLcxPMVg+DTpp81pRFXLbfW7MqkqVZvz48RozZox6eno0adKkuoyhnBr35wULFiiUGZXGBn0/PPrlSI2likujWKl+rp7ZG72NO4uXX35ZkjR79uyDPp9Q5gtf+IIkafXq1ZLqfSacgdQdlVUByt8lf5+SPM2OlfcS16fPCZUxRs0wV0YjqN4wpNDn7nuSkVNMG81zHkweH0wJCSGMHvL0hxDCMMMICdYyYYKzUj0Pj6q9P0ZW2BC0isBpOu/f0Sw2mnkcllXw3zl1zNB8Vn2tGr+cPuM5UlmwAU1HZSocPjdOfdLZ20v/BpzapKpTzdI6ZswY9fX1qbu7u98YpwJCX5Gwb2JsqDb6/fu//3tJNW9+Pwx0RPLNZy9/qdYZlByz/P2LL74oqVa1NDSXlStXDvhMfwZKr5RGHRXk35wZQOlTwVos/nvJh6dU0diUHAGZybTayTPyhX9nJ+3PDrek0sEpgVLU1mA+HKWEUiGEzifGRgghDDOev1+7dq2k2tRVycGXWTJp4HFUzxwTNoq9Hxt6dO71Z06/uV02wjllbGWGkSKlqWap3ril3wjVEi+ZO4QMFv5NY9uGOSvn+lp5O4dom97eXm3btm1AhE31eP6NvN+wb2JsVPjiF78oSfre974nqVYsyQ+FH7RZs2YV92HfAD90ljvtm3HeeecNc6tDIx555BFJNdnYSgRH4aUslSUHOEa1sLS3Oy6G1/Hlwrwc9NWgCkCfIErBVaiOMELG+BrwRciqrfTlYP0XZvxk8iaqRSGE0UeMjRBCaBI22I466ihJ9VVgS1EjnFbj6J81VGx80sg1NpKZqp6+G5xWtHJCVYDGL6vWVteh6sGpQ58zo0xK03KlarIlxcNLKhQ2spktdc+ePdq7d696e3u1ffv2Op8NH8fXNE7+QyPGRgOuuOKKA972S1/60jC2JBwo7nStTjHHAxULJkPyZysVdMBzR+NOeNOmTZLqi0p56Q6NBa9YSdgdmSXdqVOnSqqF7VGB8XlUO9qSsyGP7X342vgcfUxfC2fqtErHRFR8EdIJ0ufm7UMIo48YGyGE0CTsS+EU7Bxtl0b5npbjFJSNY0ZkMNNnKbSaBmJJPWDFVDvD+/g0ZGmIVv/vY9Cg5hQklQZDhcRt8LVlZA7VI3/vcyqFrVePU53eZPZUG992qA5DI8ZG6EisKJTyYvizOy4v3SFye9ZS8Wd38t7enfLmzZsH7M8d3YFWJH366aclSUcffbSkege/qnzNImClCrYMo/TSqgrDJEsvSoYAUn2xDF2qiRJC6HxibIQQQpNYuHChJOmxxx6TVDPUmBKeU1E05DgF5s82CD0FRqOaDsic4iJMLsckd9zeo32vV90v/TuYJdUGvY9F342SszbT7fszw8H5mSqQj08HZ+fX6O7u1oQJE+qmVH0er7/+Oi9f2AcxNkJHws7WCgMzcTKlMuuFeDt2SCWlg4mMXnrpJUkHrmiY3//935ckPfHEE5KkY489dsDxquoFc7ww1LAUZsl8Ml76Gtn/xdtZGfE1YApu79dydwhh9BJjI4QQmsxbb70lqT47JovdGToO2wj2lJRH1/ZzYNI3Th8y7Hkw3xEvvX8btSwYaMPS61WzafpcvW8W/GPqfq9n6GdiZ2wfgzlE/Heu52lBDiwYAVT1X+nq6tKYMWN05JFH9u+H7T7YAcRoI8ZG6EjoAEf5198zZNAdEEP6WISJJb15HKsHlr2Hi6985SuSpEcffVSSdPzxx0uqyelSfTQKO3O2lamn3bkyDNKdtSNj/L3X93p+IdqRzlMJIYTRS4yNEEJoMh4Fr1q1SlJ9QjQbfnS2tSFoVcCKB6vB+nuGXlPBYK6KUrE85vdge+n4TENWqjfgvaxWV5VqhjKVDYZ3M1OnFQu2jTVX2B4rLlSFbCT39fUNqH/CKJhEoRwYMTZCR0K5uZQm2rBIE30zWDvFHRllbnd07uwdPTLcXHPNNZKk5cuXS5JOOumk/u8GK8ld6vyZIbT0IvOLyEsmlvLnRJ+EEEyMjRBCOES8+eabkmpVWD26Zip3G7U29Gw8W9nwVBYjNWwAej3DSBAbnh7llwpI0pA09AExjZLL0R+lFJFTqgPjczQ0lukMzoGFry2VDk4jespzz5492rNnj7q6uvT+++/X+YzY0A/7R4yN0JG4Q/iHf/gHSfWheaVqq6XaJYb1Q6gK+OXgJVMoDzfXX3+9pIHVbemrYay2uJP1Z4YIsnNmThJGq1D6dzbVEEIwMTZCCOEQsWjRIknSihUrJNUUBRrBVg5K4ct0TLbx6/VZpZUKBX0vHNbMyqzMEEpfD+YHqRq4pWk3OixzSf8SL1lSgPtj9IrhelRv6K+yffv2AbVhfI2SV+PgiLEROppXX31VUq0js/zMzpyOcKWOybCoFKVbqwVvv/32sJ5PiWol4jVr1kiql5eZ3Ii5QeiXUqrWytooluzdGS9evHh4TiqE0DHE2AghhEPMnDlzJEmPP/64pFrtFGa39OdShIUNRxvRNiBtENqItr+BDcpSfg6GRdMYZ+E/1lqpKhucguQxGK3ibUtVXel3YhrVNqleG0e7+JpyCtRUE/t1d3dr9+7d2rZtW3/pgRtuuKHh8cPQiLEROpr58+dLqsnWHq2zgytJqpSx6cRGGZnRKc41cSjZuHGjpHopnEmJWI6cLwNGo1DW9jm+8cYbkmrXOoQQSIyNEEIYIS6//HJJ0lNPPSWpfjqOkRxWOqwwlCI7mHzOsMAgE7F5eydw8/GtBlBloAHaCE45NsrYWd0368DYYK9mJ622iZE03u+kSZManovb7nM21XPq6+vT3r179cEHH+iqq64qnlsYOjE2wqjAsrX9GShPc/Tvzpy+HfSDoNJRqrB6KFmwYIEkacmSJZKkadOmSapJ7T43hg4yq6o/2zmQxcFmzpzZxLMIIXQSMTZCCGGEsXOtR+EMU2a4slUAKgulpQ1Lj/b9mUnqrCaUarewkiupOlJTaeBUZClNvo9ho5g1T+jYTGOZ6ox9Nnwc5ixx+6r+Lb29vdq1a1f/lGQ4eGJshFGF/QvceTrkj6GDjOBg51r67A6S6aVHAodZmqVLl0qqZTV1Z0x1xy8Bd8p2kLvlllua3OIQQqcSYyOEEEYYF6t74IEHJNWHYJeceQ2zbZbS6FMV8HZM2GaFw/VHqpEaUv2UWyOfDabJN56WY7FD1j4pZQr1+l76nG3Yl/J2MOGej0fH6TfffFM7d+7Ucccdl5T7w0iMjTCquOmmmyRJDz74oKRaB0Z5mR0VFQ4mEHLnbBXAqoCP1wqUOk4rHj6XlM4OIQw3MTZCCKFFuPHGGyVJ999/vyTptNNOk1Qzhk0py6bhVJgVDRvLnja06uD9MeMonYmtiFCV8H4b1Ubxd8xqyvov3pdzgHjpY/t7Kxg+N14Db8fcICWfEEa9LFiwQI8++qjC8BJjI4xK5s2bJ0m69957JUknnniipJoPB2VrdmjMnmlJ1h3Ydddd19wTGEYiFYcQmk2MjRBCaDEcvmxj2AqHQ7Y9amc0idUEf7Z/BI1kf/b6rNFCFcJGt5UNft9I2fAx2FYqC/7eCgYr0fp7OzTbsLcSQT8UqzX0R2GafX/va+RrHppDjI0wqmGExfLlyyVJRx11lKRah0fZms5mV1xxRfMbG0IIbUqMjRBCaFFoDLuWikf/VgM8OqfvhWGVVhvJVhsYwcH6IV6fvh7G++Hfq21i3RYrDN6nlQmfE0sG8Htv7wGBfTWYf8MKiv1YPPX51ltvSZLmzp1b1+Yw/MTYCKHC9ddfP+Dz3XffLanWUTKcz51+CCGEMjE2QgihTXAtlYcffljSQB8JqT7qxKN858uwiuAIDGbd9PqMJLGKQB8RTidWa7nQqZq5QWiwW5mwUuG2+lisF2Olwm1nJlD6rdjH47XXXpPUWmHpo4EYGyHsg+ScCCGEgyfGRgghtBkOrXa0ygknnCCplo+DGUO9tFpgtYEKhyM+rC4YKx1ez9u98847A45XLTzodbwvFvKziuLaJVYseCzmELGCwaKJDFO3b4bbaFUojAzdg68SQgghhHDgRNkIIYQ2hdEqjzzyiKSaj4b9IawCMGrEqoNH/87KyYgQ1hfZunWrpJr6cNxxx0kaGAXj1P30C7ECwdweVigMFQ7m5bDPhn0xrGTYR+Ptt9+WlKR1rUKUjRBCCCE0lUOibFx77bX67ne/22/ZSh9Zxj09PfrOd77TXw9A+mi+bceOHfqv//ovnXPOOYeieaFN2Lx5s6ZPn67p06frX//1X/v//vjjj+tP/uRPtGHDBp144om6/fbbdemll45gS0MYGWbPnj3gs5UO+0mw4KBVAisYViasFjDjqPH6c+bMGbRN3/72tyXVFz1kThB/9nr0A2G1VtZIsfKxaNGiQdsUDj2HTNm47bbbtG3btv5/dha6+uqrB/x96dKlOu2003T22WcfqqaFNuFrX/uazjzzzAF/+9WvfqVZs2bpzjvv1Hvvvac77rhDV111VX/CnhBCCCPPoMrGHXfcoX//93/XU0891f+3hQsXqqenR3fdddewN2jFihWaPXt2v5Ub2puXXnpJn/rUp/Tss8/q7LPP1uuvv66zzjpLTz75pM4777wh7+fHP/6xfvazn2n+/Pn9IyVJ2rBhgyZNmqQvfOELkqSLL75Yhx9+uF566SUdffTRw306IbQVVDqWLVsmqebTwbwc1WgSqaZoHEyWTR/DyoNVE/tW2HeD+TKMfTMc3TJr1qwDbksYOQZVNmbNmqX169f33yB79uzRqlWrdM011+jmm2/WpEmTGv4766yzBuxn6dKlmjx5ss4555wBhkuVV199Vf/8z/9c94CE9uUTn/iE/uqv/kpXX321PvjgA1133XW69tprdd555w35/unt7dUf/uEf6t57760zQn/rt35LZ555pp555hn19vZqzZo1Gj9+fN39F0IIYeQYVNk49thj9bu/+7t64oknNG/ePK1fv15TpkzROeeco3POOUdLly4d9CCLFi3SX//1X2vixIn6x3/8R82cOVPTpk3T7/zO7wxY75FHHtG5556rU0899cDPKOw3M2bMaOr+582bp7Vr1+rTn/60urq69Mwzz0j6yAAdyv2zZMkSffrTn9Y555yjn/70pwO+6+np0ezZs3XVVVdp586dGjdunJ544on+bIQhVGn2vd7qzJ8/f0jrOU3/cCS1u+aaayRJ9913n6Sa74XVlJKKzUib0N4MyUF0zpw5uu+++zRv3jytXLmy/+YZKlX/i4suukhXX321/u7v/q6hsfH1r399v/YdDp5mTIeRefPm6ZJLLtGyZcsGpDQejNdff11LlizRT37yk4bfP/vss7rtttv03HPP6eyzz9ZPfvITXXLJJVq3bt2of7GEeg7FvR5CqKerz+blPti5c6eOPfZY/cu//It++7d/Wz//+c910kknacGCBVq5cmXDbU4++WT97//+b8PvbrrpJk2YMEF33nln/99+9KMf6YILLtDGjRv7s9iFzmDbtm365Cc/qc997nNat26dfvrTn2ry5MlDun/WrFmjK664ot+DfceOHdqxY4cmT56sX/3qV/qbv/kb/ehHP9Lq1av7t7300kv1mc98Rl/96lcPyfmFEDoL+5M999xzI9qOTmJIxob00cj0P/7jPzRlyhT94Ac/2K+DPPnkk/q93/s9HXbYYXr22Wf15S9/WWvXrh3gIDh//nzt3LmzP1QrdA5z587V+++/r8cff1zz58/Xu+++218qezA+/PBDbdmypf/zqlWr9N3vfldPP/20pk2bph/+8If68pe/rGeffVYzZszQ888/r/PPP1+PPfaYLrjggmadUgihg4mxMfwMOc/GnDlz9NBDD2n58uX7fZC7775bc+fOVV9fn0499VQ9+OCDAwyNnTt36vHHHy86job25emnn9b69ev7fS3uvPNOzZgxQ9/5znd09dVXD7r9+PHjNW3atP7PEydO1NixY/v/9tnPflbf/OY39Qd/8Ad68803NXXqVH3961+PoRFCCC3EkJWNX/7ylzrjjDO0ceNGHXnkkc1uVwghhDAiRNkYfoaU1Gvv3r268847dcUVV8TQCCGEEMJ+Meg0yvbt23XMMcfo5JNP1vr16w9Fm0IIIYTQQQxqbBx++OH9mdtCCCGEEPaXVH0NIYQQQlOJsRFCCCPArl27dMYZZ+iEE04Y8Pcf/OAHOvvss3XkkUfqtNNO669nEkI7E2MjhBBGgDvuuKOuWODu3bv1pS99STfeeKO2bt2qVatW6Y/+6I/0P//zPyPUyhCGhxgbIYSwH6xatUpHHHFE/7/x48fvVwVjSXr55Ze1cuVK/fEf//GAv2/evFnvvfeerrnmGnV1delTn/qUzjzzTP385z8fxjMI4dATYyOEEPaDmTNnatu2bdq2bZtef/11nXbaabryyiv1l3/5l8Uqxk63bxYuXKjbb79dEyZMGPD3Y445RldeeaUefvhh9fb26sc//rFeffVVfeYznzmUpzjqmTFjRmorDTNDTuoVQgihxt69e3XJJZfoxBNP7K9oOhRWr16tBx54QOvXr9dzzz2nWbNmacOGDf3fr127VjfccIPeeecdSeovghlCOzPkdOUhhBBqfOMb39D777+vJUuWDHmb7du367bbbtP3v//9ht//4he/0MyZM7V69Wr9v//3//Tiiy/qi1/8oo477jhdfPHFw9X0EA45mUYJIYT95Hvf+54ee+wxPfnkkxo7dqwk6fbbbx/gy8F/kvTiiy/qlVde0bnnnqtp06bpsssu0xtvvKFp06bplVde0c9+9jNNnz5dF154obq7uzV9+nRdfPHFWrdu3UiebggHTaZRQghhP3j++ed1wQUX6J/+6Z/2e15/z5492rRpU//nf/u3f9Mtt9yi//7v/9bUqVP1yiuv6JOf/KSeeeYZfe5zn9P//d//6cILL9TXvva1TKWEtibTKCGEsB88/fTT2rJlywCnzXPPPXdI6sOYMWMGVDGePHmyuru7+//2iU98QsuXL9eiRYv06quvauLEibr66qs1d+7c4T+REA4hUTZCCCGE0FTisxFCCCGEphJjI4QQQghNJcZGCCGEEJpKjI0QQgghNJUYGyGEEEJoKjE2QgghhNBUYmyEEEIIoanE2AghhBBCU4mxEUIIIYSmEmMjhBBCCE0lxkYIIYQQmkqMjRBCCCE0lf8P0MofugiUQ6wAAAAASUVORK5CYII=\n", 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" + "
" ] }, "metadata": {}, @@ -177,29 +259,29 @@ } ], "source": [ - "plotting.plot_stat_map(p, threshold = 0.05)" + "plotting.plot_stat_map(p, threshold = 0.95)" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 134, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 5, + "execution_count": 134, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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\n", + "image/png": 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\n", 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\n", + "image/png": 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\n", "text/plain": [ - "
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" ] }, "metadata": {}, @@ -237,10 +319,11 @@ } ], "source": [ - "anat_mean = '/home/oad4/scratch60/kpe_fsl/derivatives/fmriprep/sub-1322/anat/sub-1322_space-MNI152NLin2009cAsym_desc-preproc_T1w.nii.gz'\n", + "anat_mean = '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1322/anat/sub-1322_space-MNI152NLin2009cAsym_desc-preproc_T1w.nii.gz'\n", "\n", "plotting.plot_stat_map(t_plot,\n", - " bg_img = anat_mean)\n", + " bg_img = anat_mean,\n", + " cmap = \"RdYlBu\", colorbar=False) # use RdYlBu because it is negative originally\n", "\n", "plotting.plot_stat_map(t_plot,\n", " bg_img = anat_mean,\n", @@ -263,7 +346,28 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": [] + "source": [ + "# plotting FLAMEO\n", + "\n", + "img = '/media/Data/work/2nd_level/_cope_5/flameo_ols/stats/zstat1.nii.gz'\n", + "pstat = '/media/Data/work/2nd_level/_cope_5/fdr_ztop/zstat1_pval.nii.gz'\n", + "#t_plot = threshold(img,pstat)\n", + "%matplotlib inline\n", + "plotting.plot_stat_map(img, threshold = 2.3,bg_img = anat_mean,\n", + " cut_coords=[-24,0,-20])# display_mode='y')\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "display = plotting.plot_stat_map(img, threshold = 2,bg_img = anat_mean)\n", + "display.add_overlay(pstat)\n", + "plotting.show()" + ] } ], "metadata": { diff --git a/task_based_analysis/.ipynb_checkpoints/ROI_analysis-checkpoint.ipynb b/task_based_analysis/.ipynb_checkpoints/ROI_analysis-checkpoint.ipynb new file mode 100644 index 0000000..0cab888 --- /dev/null +++ b/task_based_analysis/.ipynb_checkpoints/ROI_analysis-checkpoint.ipynb @@ -0,0 +1,2376 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## ROI analysis for KPE study - basic ROI will be: Amygdala, Hippocampus, Striatum, vmPFC, vACC" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import glob\n", + "import nilearn\n", + "from nilearn import plotting\n", + "import os\n", + "import subprocess\n", + "work_dir = '/media/Data/work/KPE_ROI'" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# build grouped mask\n", + "mask_img_temp = '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-*/ses-[1,2]/func/sub-*_ses-[1,2]_task-Memory_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz'\n", + "mask_files = glob.glob(mask_img_temp)\n", + "mean_mask = nilearn.image.mean_img(mask_files, n_jobs=5)\n", + "plotting.plot_anat(mean_mask)\n", + "\n", + "group_mask = nilearn.image.math_img(\"a>=0.95\", a=mean_mask)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(group_mask)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Compare before-after scans" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_008/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1223/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1253/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1263/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1293/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1307/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1315/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1322/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1339/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1343/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1351/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1356/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1364/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1369/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1387/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1390/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1403/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1464/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1468/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1499/con_0001.nii']\n", + "['/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_008/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1223/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1253/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1263/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1293/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1307/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1315/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1322/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1339/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1343/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1351/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1356/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1364/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1369/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1387/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1390/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1403/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1464/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1468/con_0001.nii', '/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1499/con_0001.nii']\n" + ] + } + ], + "source": [ + "tstat_list.sort()\n", + "print(tstat_list)\n", + "tstat_ses2 = glob.glob('/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_*/con_0002.nii')\n", + "tstat_ses2.sort()\n", + "print(tstat_ses2)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1322/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1322/con_0002.nii\n", + "1322\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1387/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1387/con_0002.nii\n", + "1387\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1339/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1339/con_0002.nii\n", + "1339\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1464/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1464/con_0002.nii\n", + "1464\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1315/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1315/con_0002.nii\n", + "1315\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1223/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1223/con_0002.nii\n", + "1223\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1468/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1468/con_0002.nii\n", + "1468\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1499/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1499/con_0002.nii\n", + "1499\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1307/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1307/con_0002.nii\n", + "1307\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1351/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1351/con_0002.nii\n", + "1351\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_008/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_008/con_0002.nii\n", + "008\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1390/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1390/con_0002.nii\n", + "1390\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1263/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1263/con_0002.nii\n", + "1263\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1369/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1369/con_0002.nii\n", + "1369\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1364/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1364/con_0002.nii\n", + "1364\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1293/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1293/con_0002.nii\n", + "1293\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1253/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1253/con_0002.nii\n", + "1253\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1343/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1343/con_0002.nii\n", + "1343\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1356/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1356/con_0002.nii\n", + "1356\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1403/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1403/con_0002.nii\n", + "1403\n" + ] + } + ], + "source": [ + "# create diff image\n", + "group = 'all'\n", + "contrast = '02'\n", + "tstat_list = glob.glob('/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_*/con_00%s.nii' %(contrast))\n", + "tstat_ses2 = glob.glob('/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_*/con_00%s.nii'%(contrast))\n", + "import os\n", + "os.chdir(work_dir)\n", + "\n", + "for ses1,ses2 in zip(tstat_list,tstat_ses2):\n", + " print (ses1)\n", + " print (ses2)\n", + " sub = ses1.split('id_')\n", + " sub = sub[1].split('/')[0]\n", + " print(sub)\n", + " diff_file = 'kpe' + sub + 'diff' + group + 'con' + contrast\n", + " cmd = ['fslmaths', str(ses2), '-sub', str(ses1), str(diff_file)]\n", + " subprocess.call(cmd)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['/media/Data/work/KPE_ROI/kpe1369diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1364diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1307diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1356diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1468diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1403diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1343diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1322diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1387diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1499diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1315diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1390diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1339diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1464diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz']" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "diff_list = glob.glob(work_dir + '/kpe*diffallcon%s.nii.gz' %(contrast))\n", + "diff_list" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "# create mask\n", + "mask_file = '/media/Data/work/KPE_ROI/binConjunc_PvNxDECxRECxMONxPRI_vmpfc.nii.gz'" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.image.resampling.resample_img...\n", + "resample_img(, target_affine=None, target_shape=None, copy=False, interpolation='nearest')\n", + "_____________________________________________________resample_img - 0.1s, 0.0min\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe1369diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1364diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1307diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1356diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1468diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1403diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1343diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1322diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1387diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1499diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1315diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1390diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1339diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1464diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 20),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 3.2s, 0.1min\n" + ] + } + ], + "source": [ + "from nilearn.input_data import NiftiMasker\n", + "\n", + "# here I use a masked image so all will have same size\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(diff_list)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from kpe1403diffallcon02\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.1s, 0.0min: Loading resample_img...\n" + ] + }, + { + "data": { + "text/plain": [ + "NiftiMasker(detrend=True, dtype=None, high_pass=None, low_pass=None,\n", + " mask_args=None,\n", + " mask_img='/media/Data/work/KPE_ROI/binConjunc_PvNxDECxRECxMONxPRI_vmpfc.nii.gz',\n", + " mask_strategy='background',\n", + " memory=Memory(cachedir='/media/Data/nilearn/joblib'),\n", + " memory_level=1, sample_mask=None, sessions=None, smoothing_fwhm=4,\n", + " standardize=True, t_r=1.0, target_affine=None, target_shape=None,\n", + " verbose=2)" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(diff_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(449,)" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[Memory] 6.4s, 0.1min: Loading unmask...\n" + ] + } + ], + "source": [ + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_all_Ses1_2' %(contrast))" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plotting.plot_stat_map(delta_img,threshold = 0.5)\n", + " #bg_img = anat_mean)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Run actual TFCE using fsl Randomize" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Group difference" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "KPE008\n", + "KPE1223\n", + "KPE1293\n", + "KPE1307\n", + "KPE1315\n", + "KPE1322\n", + "KPE1339\n", + "KPE1343\n", + "KPE1387\n", + "KPE1464\n", + "KPE1499\n", + "KPE1253\n", + "KPE1263\n", + "KPE1351\n", + "KPE1356\n", + "KPE1364\n", + "KPE1369\n", + "KPE1390\n", + "KPE1403\n", + "KPE1468\n", + "KPE1480\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "\n", + "ketamine_list = list(medication_cond['scr_id'][medication_cond['med_cond']==1])\n", + "ket_list = []\n", + "for subject in ketamine_list:\n", + " print(subject)\n", + " sub = subject.split('KPE')[1]\n", + " ket_list.append(sub)\n", + "\n", + "\n", + "midazolam_list = list(medication_cond['scr_id'][medication_cond['med_cond']==0])\n", + "mid_list = []\n", + "for subject in midazolam_list:\n", + " print(subject)\n", + " sub = subject.split('KPE')[1]\n", + " mid_list.append(sub)\n", + "mid_list.remove('1480')" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func = ['/media/Data/work/KPE_ROI/kpe%sdiffallcon%s.nii.gz'% (sub, contrast) for sub in ket_list]\n", + "mid_func = ['/media/Data/work/KPE_ROI/kpe%sdiffallcon%s.nii.gz' % (sub, contrast) for sub in mid_list]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Start with Ketamine" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for sub in ket_func:\n", + " plotting.plot_stat_map(sub, threshold=0.8, title = sub)" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "[Memory] 0.0s, 0.0min: Loading filter_and_mask...\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1307diffallco\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "[Memory] 0.0s, 0.0min: Loading unmask...\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# here I use a masked image so all will have same size\n", + "group = 'ket'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(ket_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(ket_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1)\n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Midazolam" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "[Memory] 0.0s, 0.0min: Loading filter_and_mask...\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1356diffallc\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "[Memory] 0.0s, 0.0min: Loading unmask...\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# here I use a masked image so all will have same size\n", + "group = 'mid'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(mid_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(mid_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Striatum - Ketamine" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1307diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1315diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1322diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1339diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1343diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1387diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1464diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1499diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 11),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 1.8s, 0.0min\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1307diffallco\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.masking.unmask...\n", + "unmask(array([-0.358917, ..., 0.006478], dtype=float32), )\n", + "___________________________________________________________unmask - 0.1s, 0.0min\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/binConjunc_PvNxDECxRECxMONxPRI_striatum.nii.gz'\n", + "group = 'ket'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(ket_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(ket_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Midazolam" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1356diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1364diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1369diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1390diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1403diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1468diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 9),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 1.5s, 0.0min\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1356diffallc\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.masking.unmask...\n", + "unmask(array([0.033937, ..., 0.211592], dtype=float32), )\n", + "___________________________________________________________unmask - 0.1s, 0.0min\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "group = 'mid'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(mid_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(mid_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1.5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Amygdala - Ketamine\n", + "I used neurosynth to generate a mask file. Used metaanalysis with the term Amygdala, then thresholded it accordingly. " + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=19\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.image.resampling.resample_img...\n", + "resample_img(, target_affine=None, target_shape=None, copy=False, interpolation='nearest')\n", + "_____________________________________________________resample_img - 0.0s, 0.0min\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1307diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1315diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1322diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1339diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1343diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1387diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1464diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1499diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 11),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 1.8s, 0.0min\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1307diffallco\n", + "[NiftiMasker.fit] Resampling mask\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.image.resampling.resample_img...\n", + "resample_img(, target_affine=None, target_shape=None, copy=False, interpolation='nearest')\n", + "_____________________________________________________resample_img - 0.0s, 0.0min\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.masking.unmask...\n", + "unmask(array([-0.945631, ..., -0.022562], dtype=float32), )\n", + "___________________________________________________________unmask - 0.1s, 0.0min\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "group = 'ket'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(ket_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(ket_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1.5)" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1356diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1364diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1369diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1390diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1403diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1468diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 9),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 1.6s, 0.0min\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1356diffallc\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.masking.unmask...\n", + "unmask(array([-0.252159, ..., 0.671368], dtype=float32), )\n", + "___________________________________________________________unmask - 0.1s, 0.0min\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "group = 'mid'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(mid_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(mid_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1.5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## vACC - Ketamine first" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/ventral anterior_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=4\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1307diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1315diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1322diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1339diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1343diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1387diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1464diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1499diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 11),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 3.4s, 0.1min\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1307diffallco\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.masking.unmask...\n", + "unmask(array([-0.142441, ..., -0.63876 ], dtype=float32), )\n", + "___________________________________________________________unmask - 0.1s, 0.0min\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "group = 'ket'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(ket_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(ket_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1.5)" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1356diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1364diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1369diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1390diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1403diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1468diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 9),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 2.7s, 0.0min\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1356diffallc\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.masking.unmask...\n", + "unmask(array([-0.0658 , ..., -0.253689], dtype=float32), )\n", + "___________________________________________________________unmask - 0.1s, 0.0min\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "group = 'mid'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(mid_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(mid_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1.5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Hippocampus - Ketamin" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1307diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1315diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1322diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1339diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1343diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1387diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1464diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1499diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 11),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 1.9s, 0.0min\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1307diffallco\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.masking.unmask...\n", + "unmask(array([-0.064044, ..., 0.438721], dtype=float32), )\n", + "___________________________________________________________unmask - 0.1s, 0.0min\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "group = 'ket'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(ket_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(ket_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1.5)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1356diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1364diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1369diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1390diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1403diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1468diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 9),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 1.5s, 0.0min\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1356diffallc\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.masking.unmask...\n", + "unmask(array([-0.314107, ..., -0.610047], dtype=float32), )\n", + "___________________________________________________________unmask - 0.1s, 0.0min\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/plotting/displays.py:767: UserWarning: empty mask\n", + " get_mask_bounds(new_img_like(img, not_mask, affine))\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "group = 'mid'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(mid_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(mid_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1.5)" + ] + }, + { + "cell_type": "code", + "execution_count": 121, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 121, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# surface plotting\n", + "from nilearn import plotting, datasets \n", + "from nilearn.plotting.cm import _cmap_d as nilearn_cmaps\n", + "\n", + "\n", + "view = plotting.view_img_on_surf(mask_file,surf_mesh='fsaverage5', threshold = 0.01) \n", + "\n", + "view" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/task_based_analysis/.ipynb_checkpoints/ROI_connectivityAnalysis-checkpoint.ipynb b/task_based_analysis/.ipynb_checkpoints/ROI_connectivityAnalysis-checkpoint.ipynb new file mode 100644 index 0000000..e29df65 --- /dev/null +++ b/task_based_analysis/.ipynb_checkpoints/ROI_connectivityAnalysis-checkpoint.ipynb @@ -0,0 +1,4547 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Connectivity betweeen ROIs" + ] + }, + { + "cell_type": "code", + "execution_count": 251, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import numpy as np\n", + "import pandas as pd\n", + "import nilearn\n", + "from nilearn import plotting\n", + "import glob\n", + "import os\n", + "from nilearn.input_data import NiftiMasker\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import scipy\n", + "import pymc3 as pm" + ] + }, + { + "cell_type": "code", + "execution_count": 244, + "metadata": {}, + "outputs": [], + "source": [ + "# put functional file, confound file and event file here - this is for one subject\n", + "func_file = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz'\n", + "confound_file = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_desc-confounds_regressors.tsv'\n", + "events_file = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/sub-{sub}_ses-{ses}_30sec_window.csv'" + ] + }, + { + "cell_type": "code", + "execution_count": 245, + "metadata": {}, + "outputs": [], + "source": [ + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 246, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['KPE008', 'KPE1223', 'KPE1253', 'KPE1263', 'KPE1293', 'KPE1307',\n", + " 'KPE1315', 'KPE1322', 'KPE1339', 'KPE1343', 'KPE1351', 'KPE1356',\n", + " 'KPE1364', 'KPE1369', 'KPE1387', 'KPE1390', 'KPE1403', 'KPE1464',\n", + " 'KPE1468', 'KPE1480', 'KPE1499'], dtype=object)" + ] + }, + "execution_count": 246, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "subject_list = np.array(medication_cond.scr_id)\n", + "subject_list" + ] + }, + { + "cell_type": "code", + "execution_count": 247, + "metadata": {}, + "outputs": [], + "source": [ + "def removeVars (confoundFile):\n", + " # this method takes the csv regressors file (from fmriPrep) and chooses a few to confound. You can change those few\n", + " import pandas as pd\n", + " confound = pd.read_csv(confoundFile,sep=\"\\t\", na_values=\"n/a\")\n", + " finalConf = confound[['csf','white_matter', 'framewise_displacement', 'dvars', 'std_dvars',\n", + " 'trans_x', 'trans_y', 'trans_z', 'rot_x', 'rot_y', 'rot_z',\n", + " ]] # can add 'global_signal' also , \n", + " #'a_comp_cor_00', 'a_comp_cor_01',\t'a_comp_cor_02', 'a_comp_cor_03', 'a_comp_cor_04', 'a_comp_cor_05'\n", + " # change NaN of FD to zero\n", + " finalConf = np.array(finalConf.fillna(0.0))\n", + " #finalConf[0,2] = 0 # if removing FD than should remove this one also\n", + " return finalConf" + ] + }, + { + "cell_type": "code", + "execution_count": 248, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=25\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "\n", + "masker_amg = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " smoothing_fwhm=4, standardize=True, detrend=True, verbose=5, t_r=1,\n", + " high_pass=.01)" + ] + }, + { + "cell_type": "code", + "execution_count": 249, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# hippocampus mask\n", + "mask_file_hippo = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file_hippo = nilearn.image.math_img(\"a>=13\", a=mask_file_hippo)\n", + "nilearn.plotting.plot_roi(mask_file_hippo)\n", + "\n", + "masker_hippo = nilearn.input_data.NiftiMasker(mask_img=mask_file_hippo, \n", + " smoothing_fwhm=4, standardize=True, detrend=True, verbose=5, t_r=1,\n", + " high_pass=.01)" + ] + }, + { + "cell_type": "code", + "execution_count": 250, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#vmPFC\n", + "mask_file_vmpfc = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file_vmpfc = nilearn.image.math_img(\"a>=5\", a=mask_file_vmpfc)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file_vmpfc)\n", + "\n", + "masker_vmpfc = nilearn.input_data.NiftiMasker(mask_img=mask_file_vmpfc, \n", + " smoothing_fwhm=4, standardize=True, detrend=True, verbose=5, t_r=1,\n", + " high_pass=.01)" + ] + }, + { + "cell_type": "code", + "execution_count": 254, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Dir is already there\n", + " Analysing subject KPE008\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-008/ses-1/func/sub-008_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-008/ses-1/func/sub-008_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-008/ses-1/func/sub-008_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "(1095, 559)\n", + "(1095, 1265)\n", + " Analysing subject KPE1223\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1223/ses-1/func/sub-1223_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1223/ses-1/func/sub-1223_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + 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Nifti1Image('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1499/ses-1/func/sub-1499_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1499/ses-1/func/sub-1499_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1499/ses-1/func/sub-1499_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "(1150, 559)\n", + "(1150, 1265)\n" + ] + } + ], + "source": [ + "# now start running subjects and generate average hippocampus and amugdala activity - and correlate between them\n", + "#subject_list = ['KPE008']\n", + "ses = '1'\n", + "output_dir = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/connAnalysis_ses%s' %(ses)\n", + "try:\n", + " os.makedirs(output_dir)\n", + "except:\n", + " print('Dir is already there')\n", + "scr_id = []\n", + "corr_amgHipp = []\n", + "corr_amgvmpfc = []\n", + "corr_hippVmpfc = []\n", + "\n", + "for sub in subject_list:\n", + " print(f' Analysing subject {sub}')\n", + " subject = sub.split('KPE')[1]\n", + " scr_id.append(sub)\n", + " func = func_file.format(sub=subject, ses=ses)\n", + " confound = confound_file.format(sub=subject, ses=ses)\n", + " event = events_file.format(sub=subject, ses=ses)\n", + " # get timeline for each region\n", + " amg = masker_amg.fit_transform(func, confounds=removeVars(confound))\n", + " hippo = masker_hippo.fit_transform(func, confounds=removeVars(confound))\n", + " vmpfc = masker_vmpfc.fit_transform(func, confounds=removeVars(confound))\n", + " \n", + " print(amg.shape)\n", + " print(hippo.shape)\n", + " # save timeseries for each subject\n", + " x = {'amg': amg, 'hippo': hippo, 'vmpfc': vmpfc}\n", + " np.save(output_dir + '/sub-' + sub, x)\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 465, + "metadata": {}, + "outputs": [], + "source": [ + "ses = '1'\n", + "output_dir = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/connAnalysis_ses%s' %(ses)\n", + "sub = subject_list[0]\n", + "duration = 120 #set duration of event in seconds\n", + "scr_id = []\n", + "corr_amgHipp = []\n", + "corr_amgvmpfc = []\n", + "corr_hippVmpfc = []\n", + "for sub in subject_list:\n", + " subject = sub.split('KPE')[1]\n", + " scr_id.append(sub)\n", + " # load the npy file\n", + " file = np.load(output_dir + '/sub-' + sub + '.npy', allow_pickle=True)\n", + " # load each matrix\n", + " amg = h.item()['amg']\n", + " hippo = h.item()['hippo']\n", + " vmpfc = h.item()['vmpfc']\n", + " # average for all voxels\n", + " amg = np.mean(amg, axis=1)\n", + " hippo = np.mean(hippo, axis =1)\n", + " vmpfc = np.mean(vmpfc, axis=1)\n", + " event = events_file.format(sub=subject, ses=ses)\n", + " events = pd.read_csv(event, sep='\\t')\n", + " onset = int(events.onset[events.trial_type_30=='trauma1_0'])\n", + " # correlate\n", + " corr_amgHipp.append(scipy.stats.pearsonr(amg[onset:onset+duration], hippo[onset:onset+duration])[0])\n", + " corr_amgvmpfc.append(scipy.stats.pearsonr(amg[onset:onset+duration], vmpfc[onset:onset+duration])[0])\n", + " corr_hippVmpfc.append(scipy.stats.pearsonr(hippo[onset:onset+duration], vmpfc[onset:onset+duration])[0])" + ] + }, + { + "cell_type": "code", + "execution_count": 466, + "metadata": {}, + "outputs": [], + "source": [ + "# fisher z transformation\n", + "corr_amgvmpfc = np.arctan(corr_amgvmpfc)\n", + "corr_amgHipp = np.arctan(corr_amgHipp)\n", + "corr_hippVmpfc = np.arctan(corr_hippVmpfc)" + ] + }, + { + "cell_type": "code", + "execution_count": 464, + "metadata": {}, + "outputs": [], + "source": [ + "# for ses 2\n", + "df = []\n", + "df = pd.DataFrame({'scr_id': scr_id, 'corr_amgHipp2': corr_amgHipp, 'corr_amgVmpfc2': corr_amgvmpfc,\n", + " 'corr_hippVmpfc2': corr_hippVmpfc})\n", + "df = pd.merge(medication_cond, df)\n", + "df = df.rename(columns={'med_cond': 'group'})\n", + "#df['group'] = medication_cond['med_cond']\n", + "df = df.replace(to_replace={'group': {0.0:'midazolam', 1.0:'ketamine'}})" + ] + }, + { + "cell_type": "code", + "execution_count": 467, + "metadata": {}, + "outputs": [], + "source": [ + "# for session 1\n", + "df1 = []\n", + "df1 = pd.DataFrame({'scr_id': scr_id, 'corr_amgHipp1': corr_amgHipp, 'corr_amgVmpfc1': corr_amgvmpfc,\n", + " 'corr_hippVmpfc1': corr_hippVmpfc})\n", + "df1 = pd.merge(medication_cond, df1)\n", + "df1 = df1.rename(columns={'med_cond': 'group'})\n", + "#df['group'] = medication_cond['med_cond']\n", + "df1 = df1.replace(to_replace={'group': {0.0:'midazolam', 1.0:'ketamine'}})" + ] + }, + { + "cell_type": "code", + "execution_count": 468, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ 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scr_idgroupcorr_amgHipp2corr_amgVmpfc2corr_hippVmpfc2corr_amgHipp1corr_amgVmpfc1corr_hippVmpfc1hippAmgDeltaamgVmpfcDeltahippVmpfcDelta
0KPE008ketamine0.3599010.3699960.3634230.3488470.3716710.3606710.011053-0.0016750.002752
1KPE1223ketamine0.4649470.4238130.5112210.4715710.4440400.501075-0.006624-0.0202270.010146
2KPE1253midazolam0.4715710.4440400.5010750.4475080.4479340.4876890.024063-0.0038940.013386
3KPE1263midazolam0.4475080.4479340.4876890.4715710.4440400.501075-0.0240630.003894-0.013386
4KPE1293ketamine0.4685260.4337990.5094810.4649470.4238130.5112210.0035790.009986-0.001741
5KPE1307ketamine0.4474380.4459860.4911380.4843390.4706490.509483-0.036901-0.024663-0.018345
6KPE1315ketamine0.4649470.4238130.5112210.4653300.4222670.510414-0.0003830.0015450.000808
7KPE1322ketamine0.4653300.4222670.5104140.4895890.4730590.512692-0.024259-0.050792-0.002278
8KPE1339ketamine0.4653300.4222670.5104140.4475080.4479340.4876890.017822-0.0256670.022724
9KPE1343ketamine0.4649470.4238130.5112210.4649470.4238130.5112210.0000000.0000000.000000
10KPE1351midazolam0.4895890.4730590.5126920.4694760.4618440.5018520.0201120.0112150.010840
11KPE1356midazolam0.4685260.4337990.5094810.4685260.4337990.5094810.0000000.0000000.000000
12KPE1364midazolam0.4685260.4337990.5094810.4715710.4440400.501075-0.003045-0.0102410.008406
13KPE1369midazolam0.4685260.4337990.5094810.4474380.4459860.4911380.021088-0.0121870.018342
14KPE1387ketamine0.4649470.4238130.5112210.4685260.4337990.509481-0.003579-0.0099860.001741
15KPE1390midazolam0.4653300.4222670.5104140.4895890.4730590.512692-0.024259-0.050792-0.002278
16KPE1403midazolam0.4475080.4479340.4876890.4475080.4479340.4876890.0000000.0000000.000000
17KPE1464ketamine0.4477800.4471800.4882370.4474380.4459860.4911380.0003420.001195-0.002901
18KPE1468midazolam0.4649470.4238130.5112210.4715710.4440400.501075-0.006624-0.0202270.010146
19KPE1480midazolam0.4685260.4337990.5094810.4474380.4459860.4911380.021088-0.0121870.018342
20KPE1499ketamine0.4653300.4222670.5104140.4694760.4618440.501852-0.004147-0.0395770.008562
\n", + "
" + ], + "text/plain": [ + " scr_id group corr_amgHipp2 corr_amgVmpfc2 corr_hippVmpfc2 \\\n", + "0 KPE008 ketamine 0.359901 0.369996 0.363423 \n", + "1 KPE1223 ketamine 0.464947 0.423813 0.511221 \n", + "2 KPE1253 midazolam 0.471571 0.444040 0.501075 \n", + "3 KPE1263 midazolam 0.447508 0.447934 0.487689 \n", + "4 KPE1293 ketamine 0.468526 0.433799 0.509481 \n", + "5 KPE1307 ketamine 0.447438 0.445986 0.491138 \n", + "6 KPE1315 ketamine 0.464947 0.423813 0.511221 \n", + "7 KPE1322 ketamine 0.465330 0.422267 0.510414 \n", + "8 KPE1339 ketamine 0.465330 0.422267 0.510414 \n", + "9 KPE1343 ketamine 0.464947 0.423813 0.511221 \n", + "10 KPE1351 midazolam 0.489589 0.473059 0.512692 \n", + "11 KPE1356 midazolam 0.468526 0.433799 0.509481 \n", + "12 KPE1364 midazolam 0.468526 0.433799 0.509481 \n", + "13 KPE1369 midazolam 0.468526 0.433799 0.509481 \n", + "14 KPE1387 ketamine 0.464947 0.423813 0.511221 \n", + "15 KPE1390 midazolam 0.465330 0.422267 0.510414 \n", + "16 KPE1403 midazolam 0.447508 0.447934 0.487689 \n", + "17 KPE1464 ketamine 0.447780 0.447180 0.488237 \n", + "18 KPE1468 midazolam 0.464947 0.423813 0.511221 \n", + "19 KPE1480 midazolam 0.468526 0.433799 0.509481 \n", + "20 KPE1499 ketamine 0.465330 0.422267 0.510414 \n", + "\n", + " corr_amgHipp1 corr_amgVmpfc1 corr_hippVmpfc1 hippAmgDelta \\\n", + "0 0.348847 0.371671 0.360671 0.011053 \n", + "1 0.471571 0.444040 0.501075 -0.006624 \n", + "2 0.447508 0.447934 0.487689 0.024063 \n", + "3 0.471571 0.444040 0.501075 -0.024063 \n", + "4 0.464947 0.423813 0.511221 0.003579 \n", + "5 0.484339 0.470649 0.509483 -0.036901 \n", + "6 0.465330 0.422267 0.510414 -0.000383 \n", + "7 0.489589 0.473059 0.512692 -0.024259 \n", + "8 0.447508 0.447934 0.487689 0.017822 \n", + "9 0.464947 0.423813 0.511221 0.000000 \n", + "10 0.469476 0.461844 0.501852 0.020112 \n", + "11 0.468526 0.433799 0.509481 0.000000 \n", + "12 0.471571 0.444040 0.501075 -0.003045 \n", + "13 0.447438 0.445986 0.491138 0.021088 \n", + "14 0.468526 0.433799 0.509481 -0.003579 \n", + "15 0.489589 0.473059 0.512692 -0.024259 \n", + "16 0.447508 0.447934 0.487689 0.000000 \n", + "17 0.447438 0.445986 0.491138 0.000342 \n", + "18 0.471571 0.444040 0.501075 -0.006624 \n", + "19 0.447438 0.445986 0.491138 0.021088 \n", + "20 0.469476 0.461844 0.501852 -0.004147 \n", + "\n", + " amgVmpfcDelta hippVmpfcDelta \n", + "0 -0.001675 0.002752 \n", + "1 -0.020227 0.010146 \n", + "2 -0.003894 0.013386 \n", + "3 0.003894 -0.013386 \n", + "4 0.009986 -0.001741 \n", + "5 -0.024663 -0.018345 \n", + "6 0.001545 0.000808 \n", + "7 -0.050792 -0.002278 \n", + "8 -0.025667 0.022724 \n", + "9 0.000000 0.000000 \n", + "10 0.011215 0.010840 \n", + "11 0.000000 0.000000 \n", + "12 -0.010241 0.008406 \n", + "13 -0.012187 0.018342 \n", + "14 -0.009986 0.001741 \n", + "15 -0.050792 -0.002278 \n", + "16 0.000000 0.000000 \n", + "17 0.001195 -0.002901 \n", + "18 -0.020227 0.010146 \n", + "19 -0.012187 0.018342 \n", + "20 -0.039577 0.008562 " + ] + }, + "execution_count": 468, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dfBoth = pd.merge(df,df1)\n", + "dfBoth['hippAmgDelta'] = dfBoth.corr_amgHipp2 - dfBoth.corr_amgHipp1 \n", + "dfBoth['amgVmpfcDelta'] = dfBoth.corr_amgVmpfc2 - dfBoth.corr_amgVmpfc1\n", + "dfBoth['hippVmpfcDelta'] = dfBoth.corr_hippVmpfc2 - dfBoth.corr_hippVmpfc1\n", + "dfBoth" + ] + }, + { + "cell_type": "code", + "execution_count": 471, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ttest_indResult(statistic=-0.6368133926734911, pvalue=0.5318447722366961)" + ] + }, + "execution_count": 471, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(x ='group', y='amgVmpfcDelta', data= dfBoth)\n", + "sns.stripplot(x ='group', y='amgVmpfcDelta', data= dfBoth)\n", + "scipy.stats.ttest_ind(dfBoth['amgVmpfcDelta'][dfBoth.group=='ketamine'], \n", + " dfBoth['amgVmpfcDelta'][dfBoth.group=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": 508, + "metadata": {}, + "outputs": [], + "source": [ + "# a difference between amgVMPFC coupling at sesion 2 but not 3\n", + "#lets pymc3 it\n", + "import pymc3 as pm\n", + "# first code new variable for group index (1=ketamine, 2= midazolam)\n", + "group = {'ketamine': 2,'midazolam': 1} \n", + "dfBoth['groupIdx'] =[group[item] for item in df.group] " + ] + }, + { + "cell_type": "code", + "execution_count": 509, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (4 chains in 4 jobs)\n", + "NUTS: [sd, groupIdx, Intercept]\n", + "Sampling 4 chains, 0 divergences: 100%|██████████| 8000/8000 [00:02<00:00, 3025.46draws/s]\n", + "The acceptance probability does not match the target. It is 0.8915758399676582, but should be close to 0.8. Try to increase the number of tuning steps.\n" + ] + } + ], + "source": [ + "# play with glm module of pymc3\n", + "from pymc3.glm import GLM\n", + "\n", + "with pm.Model() as model_glm:\n", + " GLM.from_formula('corr_amgVmpfc2 ~ groupIdx', dfBoth)\n", + " trace = pm.sample(draws=1000, tune=1000)" + ] + }, + { + "cell_type": "code", + "execution_count": 510, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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meansdhpd_2.5%hpd_97.5%mcse_meanmcse_sdess_meaness_sdess_bulkess_tailr_hat
Intercept0.460.010.430.480.00.01361.01361.01372.01500.01.0
groupIdx-0.020.01-0.030.000.00.01379.01332.01405.01478.01.0
sd0.020.000.010.030.00.01446.01426.01376.01471.01.0
\n", + "
" + ], + "text/plain": [ + " mean sd hpd_2.5% hpd_97.5% mcse_mean mcse_sd ess_mean \\\n", + "Intercept 0.46 0.01 0.43 0.48 0.0 0.0 1361.0 \n", + "groupIdx -0.02 0.01 -0.03 0.00 0.0 0.0 1379.0 \n", + "sd 0.02 0.00 0.01 0.03 0.0 0.0 1446.0 \n", + "\n", + " ess_sd ess_bulk ess_tail r_hat \n", + "Intercept 1361.0 1372.0 1500.0 1.0 \n", + "groupIdx 1332.0 1405.0 1478.0 1.0 \n", + "sd 1426.0 1376.0 1471.0 1.0 " + ] + }, + "execution_count": 510, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pm.summary(trace, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "code", + "execution_count": 511, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.03425" + ] + }, + "execution_count": 511, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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urmbz5s10dHQwa9Ysnn32WYxGoz9qFuKaDp5pxqPC17KStC7F6yYmRGDU6zh4poUV2SlalyM0NuQVuNFoZNu2bbz11lsUFBSwf/9+jh8/znPPPceDDz7Irl27iImJYfv27f6oV4ghFVU0E2UyBNT6l8MVptcxa0I0RRVN1LTZBr5kfpTQNGSAK4pCZGQkAC6XC5fLhaIoHDp0iNWrVwNw9913s3v3bt9WKsQwqKpKUXkTOVMthOmDs4dwTlosFQ3d/PVEPUXlzRSVN8v8KCFqWHdiut1u1q1bR1VVFffddx8ZGRnExMRgMPQfbrVaaWhoGPI8drud0tLSsVV8BX19fT45b7AIpfa50Omkpq2Xu7IiKC0txWGIoq7+8jUlZyYaB23LSsgYtO1q+w53m6+Oz06yoAKfVNQw1dK/SEVLgkJX/flBx3tTKL2ORsvfbTSsANfr9bz55pt0dnbyyCOPUFlZOWgfRVGGPI/JZCI7O3vkVQ6htLTUJ+cNFqHUPkcOngNg/dfmMjkxkpo2G6lW9bJ9zBERpFpTL9um0+kGbbvavsPd5qvj56TFEKYvp81lHPiZJdFCenzGoOO9KZReR6Plqza62h+FEb3HjImJYenSpRw/fpzOzk5crv63bfX19SQnJ4+9SiHG6IPyZtLjzUyyRGhdis+E6XVMskRS2dytdSlCY0MGeGtrK52dnUD/24MPP/yQqVOnsnTpUnbu3AnAjh07yM3N9W2lQlxDh81BZVM3xaebWTI5ntr2XmrabAE58+BwZCZG0tBpl2XWQtyQXSiNjY088cQTuN1uVFVlzZo13HrrrUybNo0f/vCHvPDCC2RnZ7N+/Xp/1CvEFXXZXfzhUBW9TjfRprCB2QcDcebB4ZiaFAU0UNnUzbz04HyOYmhDBvjMmTMpKCgYtD0jI0OGDopxpbyhC71OuRhuwW1CnBmTQUdlc48EeAgLznFWIiSVNXQxJTESoyH4X9Z6ncJkSySVTT1alyI0FPyvdBES6jp6aeqyk3Vx5ZpQkJkUSXO3nc5emRclVEmAi6BwqLJ/bpCslODvPrkk82JXkYxGCV0S4CIoHKpsIT4ijKQok9al+E1qbDjhYTrpRglhEuAi4Nldbj45305WSvSwbigLFjpFITMxispmCfBQJQEuAt7hs230Ot3MCKH+70sykyJp7XFQ19GrdSlCAxLgIuDtLWskTK8M9AmHkktDJj85L8ushSIJcBHw9pU1sjAjLiSGD35VcrSJSJNBllkLUaH3ihdBpbrVxpmmHpZlWrQuRROKojA1KZKj59tQVXXoA0RQkQAXAW1feRNAyAY4wNTEKJq7HfJhZgiSABcBbd+pRiYmRJCRYNa6FM1kJvUvuPLhmRaNKxH+JgEuAlaf082HZ1q4ZUZSSA0f/KqESCMpMSYOnmnWuhThZxLgImAdPtdKr9PNLTOCb/HikVAUhcUT4zl4pgWPR/rBQ4kEuAhYe081YTToyMlM1LoUzS2aFE+bzcmp+i6tSxF+JAEuAta+8kaWZVowG/Val6K5RRfnPf9QulFCigS4CEjVrTYqm3q4JSu0u08uSY4JJzMxkoPyQWZIkQAXAWlfWSNAyPd/f1nOVAsfnW3F5fZoXYrwEwlwEZD2ljUxyRLBlMRIrUsZN26Ymki33cVntR1alyL8RAJcBJzGzt7+xYsnBf/ixSOxLDMBkPHgoUQCXAScA6dbsLs8RJkMFJU3U1TejMMtw+csUSZmWqOlHzyESICLgHOosgWDTmFKYujNPjiUnKkWDp9rxe6SdyShQAJcBJyDlS0hs3jxSN0wNRG7y8OxKpleNhTIb4AIKGeauqlu7WVmaozWpYxL109JQKdA8WkZDx4KJMBFQCk82QBAtjX0Vt8ZjlhzGAsnxvPBxVkaRXCTABcBpbC0genJUcRFGLUuZdy6JSuJkpoOmrvtWpcifEwCXASMlm47R8+3ceN0mfvkWm6ZkQxAkVyFBz0JcBEw9pxqxKPCjdMkwK9l9oQYEqOM0o0SAiTARcAoLG0gNTacrBQZPngtOp3CTdOTKCpvwi3TywY1CXAREPqcborKm1mZnRLSizcM180zkmizOSmpkeGEwcygdQFCDMeHZ5rpdbpZOStF61LGJZfbQ02bbeD7aclRKMDOE/UsnBivXWHCpyTARUB4/2QjkUY9yzITaOqS0RVf1ev0cOxM62Xb0uPNFFU084RGNQnfky4UMe55PCq7Sxu4eUYSJoMs3jBcWSnRlNZ10trj0LoU4SNDBnhdXR33338/t912G2vXrmXbtm0AtLe3s2HDBvLy8tiwYQMdHTKFpfCNktoOGrvsrJLukxHJSolGBfZXyGiUYDVkgOv1ep544gnee+89/vznP/Pqq69y+vRptmzZQk5ODrt27SInJ4ctW7b4o14RggpPNqDXKdx6cXyzGJ60eDNx5jD2lUmAB6shAzw5OZnZs2cDEBUVRWZmJg0NDezevZv8/HwA8vPzKSws9G2lImQVljawZFK83H05QjpFYcnkePaWNVLV2kNNm42aNhsdNulSCRYj+hCzpqaG0tJS5s+fT0tLC8nJ/VdEycnJtLa2DnE02O12SktLR1fpNfT19fnkvMEikNunvqt/pfWNSxIGnoPDEEVdfd1l+81MNA7adrXtV9qWlZAxpuPH+vi+On52ShSFpY388r1jpESFAbBy1gSMru5B+w4lkF9H/uLvNhp2gPf09PDYY4/x5JNPEhU1uhspTCYT2dnZozr2WkpLS31y3mARyO1z8MBZAL5z6zwmWfqXT6tps5FqvfwGFXNEBKnW1EHHX2n7lbbpdLoxHT/Wx/fV8VMSI/i3fedodZlYYO3/DMGSaCE9PmPQvkMJ5NeRv/iqja72R2FYo1CcTiePPfYYd9xxB3l5eQBYLBYaG/sXlm1sbCQhIcFLpQrRr8Pm4L9LLjDZEoFepwx0AcjyacMXF2EkLd5MecPIr7jF+DdkgKuqyo9//GMyMzPZsGHDwPbc3FwKCgoAKCgoYMWKFb6rUoSkqlYbx6vamZIYNbB0miyfNnJZKdFUt9qwOVxalyK8bMgAP3r0KG+++SaHDh3irrvu4q677uKDDz5g48aNFBcXk5eXR3FxMRs3bvRHvSKEFFU0owJz0mTxhrG4NJywQq7Cg86QfeBLliyhrKzsij+7NCZcCF/4oKwRS6QRa0y41qUEtPR4M5EmA6X1nczPiNO6HOFFciemGJfabQ6OVrUze0KsTF41RjpFYaY1mvKGLlwej9blCC+SABfj0vsnG3B7VOk+8ZJZqTH0OT2ca7YNvbMIGBLgYlx670Q91phw0uLMWpcSFKYmRWHQKZTWdWpdivAiCXAx7nT2Odlf0cTNM5Kk+8RLjAYd05KjKK3vRFVlFE+wkAAX486e0kacbpVbZyRpXUpQmZUaQ7vNyemmHq1LEV4iAS7GnXc/qyMlxsSsCdL/7U0zrNEoQHFFs9alCC+RBR3EuNBhc9Bld2FzuNhX3sSd81NxumTEhDdFh4eRkRDBgdMS4MFCrsDFuNBld1FU3sxvDpzD4fIQF2GUOy59INsazan6Luo7+rQuRXiBBLgYVz6/0EmkycDkixNXCe+amdrfLVVY2qBxJcIbJMDFuOF0eyir72J2agw6GX3iE8nRJtLjzRLgQUICXIwbFQ1dONwe5qTFal1K0FIUheXTEvnwdAvddpncKtBJgItx47PaDiKMeqYkSveJL904zYLD7WF/uSy1FugkwMW4YHe6Ka3vYlZqDHqddJ/40tz0WOIiwnj/pHSjBDoJcDEuHDrbisPlYW66dJ/4mkGnI3dGMnvKGnG5ZahmIJMAF+PC3lONRBj1ZCaObrk+MTJ5s1Notzn5+OzQa9mK8UsCXGiuz+mm+HQLsyfESveJn9yclYw5TM+7JwYvhCwChwS40Ny+skZ6nW7myugTvzEb9eTOTOavJ/qn7RWBSQJcaO7tkjrizGEy+sTPbptrpbnbzuFz0o0SqCTAhaZ6HW72nGrk5hlJ0n3iZ7fOSMZk0PHeZ9KNEqgkwIWm9pU1YnO4yZ2ZrHUpIcPl9lDTZqPN5mBZpoW3P6ujqrWHDptD69LECEmAC029/Vkdlkgj8zOk/9tfep0eisqbKSpvxhoTTku3gz8crKJL7swMOBLgQjO9Djd7ShtZM8eKQScvRS3MtEZj0CmU1HZoXYoYBfmtEZrZe3H0ydp5qVqXErJMYXpmWqP5rKZdbuoJQBLgQjPvlNSRGGVk6RSL1qWEtAUZcfQ43Bw+16Z1KWKEJMCFJmwOF7tPNbBmjlVGn2gsKyUac5he5kYJQBLgQhO7Sxvpc3pYO3eC1qWEPINex5y0WPZXNGNzyAeZgUQCXGhix7FaUmPDWTolQetSBP3dKL1Ot1yFBxgJcOF3Z5u6+aCsiVtnJnOho5eaNht2p1vrskLaJEsEydEmCo7Val2KGAEJcOF3b316AbeqkhhlGhiPLAsYa0unKKyenUJRRTMNnbLgcaCQABd+t/PzBlJjw7HGhGtdiviS2+dNwO1Ree1ItdaliGGSABd+VdnUzcm6ThZkxGldiviKtHgzN0y18Ocj1XhkhsKAIAEu/Krg+AUUYH66BPh49K3rJ1Ld2kvxmWatSxHDMGSA/+hHPyInJ4fbb799YFt7ezsbNmwgLy+PDRs20NEht+GKobncHl47Us11k+OJMYdpXY64gtWzU4iPCONPH0s3SiAYMsDXrVvHr3/968u2bdmyhZycHHbt2kVOTg5btmzxWYEieOwra6Kuo4+7FqRpXYq4ApfbQ1OXnbxZKez8vJ7PatplhsJxbsgAv+6664iNvXymuN27d5Ofnw9Afn4+hYWFvqlOBJVXP64iOdrE8mly6/x4dGmWwtQ4My6Pyou7T8sMhePcqPrAW1paSE7un785OTmZ1lZZ0UNcW02bjb1ljXzrugwMevnoZTxLjg4nKyWKQ5Ut2F0yPn88M/jzwex2O6WlpV4/b19fn0/OGyzGQ/v87lgrCrA43kFLcwt19ZevAjMz0Tisbb7aNyshY0zHj/XxtT7+q9tnWXSUN7go+LiSr2cagfHxOhrv/N1Gowpwi8VCY2MjycnJNDY2kpAwvNuhTSYT2dnZo3nIayotLfXJeYOF1u3jcHkofGMPt85I5ubr5lLTZiPVevkwNXNEBKnW1CG3+WpfnU43puPH+vhaH//V7dYUlY9qT/N2aRubv34ziqJo/joKBL5qo6v9URjVe9nc3FwKCgoAKCgoYMWKFaOvTAS9guO1NHXZuT9nktaliGFSFIXl0xI529xDUYUMKRyvhgzwzZs3861vfYuzZ89y00038dprr7Fx40aKi4vJy8ujuLiYjRs3+qNWEYDcHpX/+OAMsyfEcHNWktbliBGYlx5LYpSRl/eeRlXlxp7xaMgulOeff/6K27dt2+b1YkTw2fl5PZVNPbx03yIUReb9DiQGnY77l03iF4UVHDjdTKLWBYlBZDiA8BlVVXl532kyEyNZM8eqdTliFO6YP4G0ODM/21kmV+HjkAS48JkPyps4UdvJ92+eKqvuBCijQcffr5xOSU0HB6ttWpcjvkICXPiE26Pyr++dIj3eTP5CufMykK1bmEZmUiS/O9YqCx+PMxLgwideO1LNqfoufnRbNkaDvMwCmUGv4/G8GZxvd/L7Q+e1Lkd8ifxmCa/r6nPy3K4yrpscz9fnSt93MFgzx8qiCWZ+vqtcFnwYRyTAhde9vO8Mzd0ONq2YTm17/5JpX/6S5dMCj6IoPLI0EYfbw0/fPql1OeIiv95KL4JXh81Bl91FRWM3W4oqWTPHijU2nKLywTeBLJwoc4EHogkxYTxyyzR+UVjOvYsbuXVGstYlhTy5Ahde0WV3sfdUEz9+4zPMYXqWTIyXdS6DgMvtGXjn5DBEccf8VDKTIvmn7SW09shUs1qTABdes6+8kQsdfeQvmECESd7cBYNLU8wWlTdTePIChypbeer2WbTbnPzT6yUyNlxjEuDCK8rqu9h7qpH56bHMmhA79AEiYE2xRPDwzZm8f7KBl/adHrhCl8Uf/E8uk8SYdfQ6+eeCE0SHh3HHvAlalyN8rNfpISUmnOnJUbzwfgW9dg9p8WZuykokNn19CMEAAA3NSURBVMKodXkhRa7AxZioqsrjr31KY5edb1+XIV0nIUKnKKxfkkGUycB/fXSeblm5RxMS4GJMfrW/kl0nG/jBLVOZaInUuhzhR1EmA99ZOoluu4s/fVyFyyN3afqbBLgYtT2nGvjX905x2xwr31iSrnU5QgNp8WbyF6RR2dzDC4UV8qGmn0mAi1Epq+/isT8eZ9aEGH7+jfkyVWwIWzQpnpumJ1Jw7AL/eeCs1uWEFOmwFCPW2NnHQ789TIRRz68eWEKE0SBjgkNc3mwrOkXh6XdLyUiIYPVsmULBH+QKXIxIR6+TB37zMW02B7/+myWkxpq1LkmMAzpF4Ue3zSDbGsOjrx7jvz+tlaGFfiABLoatz+nme9uOcKapm1fuX8y8dLklXnzBg8K6hWnERoTxP18r4U8fV9Mlo1N8SgJcDEuf083G3x/l8PlWns6fw5TESJmgSgwSYTLw0PIpmMP0bC0+S2VTt9YlBTUJcDGkPqeb7/3uCPsrmnhm3TxumJY4cHv1pS+Z90RcEmsO46Ebp6DXKTz6x+OcvNCpdUlBSwJcXFO33cV3tx3hwOlmnrlnHt+4LkPrkkQASIwy8b2vZWIy6Pj2rw5xvLpd65KCkgS4uKqzTd3c++8fcvBMC09+PZsbplqku0QMmyXKxC/vW0iM2cC3thxk1+f1WpcUdCTAxRWdb+nhga0fc7qxm/uWTiTSaJDuEjFiE+LM7PjBcmZYY3j4D0f59f5KudnHiyTAxSAHz7Rw10vFdNicPLR8CtmpMVqXJAJYYpSJP31vGatnWfk/75Ty6B+P0SOjU7xCAlwMUFWV3x86z/3/+RGWSCNbHljM5ESZ30SMndmo5+XvLOIf18zg3c/quOulYkrr5MPNsZIAFwDUtffy8O+P8lTBCZZMjuel7ywiKcqkdVkiiOh0Cj+4ZRqv/I/FtPY4uPOXB/jZzlNUtfbITT+jJLfSC05e6OQH/3WU8y02VmancMuMJD453y5rV4oxu7Qk25dlJkXy/ZunUnCslpf2nuGdkjryF6Zx7+J0mU98hCTAQ5jHo/LrA5U8t7Oc6HADG5ZPYVpylNZliSDS6/Rw7EzrZdsWToy7OBXtRD6pauPdz+r5f3tO09nr5PHVMzEb9RpVG3gkwENUeUMXT7xewidV7ayencKjudMoqZE+SeE/iqKweFICWSnRvF1Sx2+Kz/HuZ/VszsvinkXp6HUyw+VQJMBDTFefk3/fd4Zf7a8kymTg+W/M5+6FadS292pdmghR0eFhfPv6iTxsNvCr/Wf5x+0l/HLPaR5aPpn1SzKIlFWerkpaJkT0Od385Ug1LxZW0NLjYN2iNP557SwSIqXPUYwPCzLiKPjBDez8vIEtRWf43/99kp/tLCNvtpU7F0wgJ9NCeJh0r3yZBHiQa+tx8OfP2njnjb00ddlZlpnA1q9ny0yCYlxSFIU1c6ysmWPl6Pk2XjtSzbuf1bHjWC0mg47rpySwZFICsybEMGtCDBNiw0N6MREJ8CDUbnNw4HQzrx+tYX9FMy6PyvWT43ny6zNZMimeML0yaGSA3B4vtPbVESspMSY2rZzGxpsyOXq+jY/PtnL4XCsHKpq5dC9nrDmM7NRoJiZEkBprJi3OTGpcOKmx4VgiTcSaw9AFcV/6mAK8qKiIp59+Go/Hw/r169m4caO36gpJLreHXqebXqebPkf/f9tdbnSKgqKAXqegUy599R/T0euktcfB+RYbFY1dfFbbwecXOlFVsEQaWZZpISPCxdyp6fQ6POyvaGHhxDiOVV0+uZAMGRRau9qIlUuv1YUT41k4MZ4lk+Po6nNzsq6Tkxc6OVXfyd6yJpq67IPOqVMgLsJIfEQYCZFG4iOM/f9GGkmIuPhvZNjA9rgIIzHhhoC5qh91gLvdbn7605+ydetWUlJSuPfee8nNzWXatGnerO+aPB4Vj6ricKv0Od24PSpuVcXtVnF5VNweFZfHg+sr3/f/e/F7d/85XB4Vz8A+/dvcni++XB4Prov7O91fnKP/3B66+1z0Ot0D5/WoKjoF9DodHo+K3e2hz+Gmq89Fj8NFn9ON3XUxpJ0e+i4eOxZxEWHMtEazaUUWy6dZSIo2UXy6hbr6Oi+1uBDaM+p1pMQYSIlJ4tYZSQPbu/ucFJY20d7roLPXSY/dTUJkGF19Ltp7nXT0Ojnd2E1Hr5P2Xifuq/y+6XUKseYwYsINWCKNJEabBsL9UujHR4Rd/NdIhFGPQadg0Ovoc3pwuj0YdIpf/giMOsBLSkqYNGkSGRn904uuXbuW3bt3+yTA/+ODM7xQWI5H/SK0B7e9doupKgr9/8NQ0OkYuEoOD9Nh1OvQ6RRMBh1mox6douBweTAZ9ESZDITpdYQZdEyxRBBhNGAK02EO02MK06NX4Gxz/1tKj6qiqpCV0j9O2wOgqkSHhxEXEcaEuHBiwsMue9FIt4gIRle6Uof+q/WESONlH8xf7d3mJ+fbsLs89Nhd2BxueuwuEqNNnKrrpMfhxuZwY3O4cKsqZ5t7OHq+nXabY5gXWeeA/kzQ6RQUwBobzs5NN3n9Q1hFHeXUYH/961/Zv38/Tz/9NAAFBQWUlJTwk5/85KrHHD9+HJNJbs8WQoiRsNvtLFiwYND2UV+BXyn3h3rLcKUChBBCjM6oJ7OyWq3U138xQXtDQwPJycleKUoIIcTQRh3gc+fO5dy5c1RXV+NwOHjnnXfIzc31Zm1CCCGuYdRdKAaDgZ/85Cd897vfxe12c8899zB9+nRv1iaEEOIaRv0hphBCCG3Jgg5CCBGgJMCFECJABUSAt7e3s2HDBvLy8tiwYQMdHR1X3G/Hjh3k5eWRl5fHjh07BrY7HA6eeuopVq9ezZo1a9i5c6e/SvebsbbRJd///ve5/fbbfV2uJsbSRr29vWzcuJE1a9awdu1annvuOX+W7nNFRUWsXr2aVatWsWXLlkE/dzgcbNq0iVWrVrF+/XpqamoGfvbKK6+watUqVq9ezf79+/1Ztl+Nto2Ki4tZt24dd9xxB+vWrePgwYPeK0oNAM8884z6yiuvqKqqqq+88or67LPPDtqnra1Nzc3NVdva2tT29nY1NzdXbW9vV1VVVV988UX1+eefV1VVVd1ut9rS0uK/4v1krG2kqqq6c+dOdfPmzeratWv9Vrc/jaWNbDabevDgQVVVVdVut6vf/va31X379vm1fl9xuVzqihUr1KqqKtVut6t33HGHWlFRcdk+f/jDH9SnnnpKVVVVffvtt9W///u/V1VVVSsqKtQ77rhDtdvtalVVlbpixQrV5XL5/Tn42lja6PPPP1fr6+tVVVXVsrIy9cYbb/RaXQFxBb57927y8/MByM/Pp7CwcNA+Bw4cYPny5cTFxREbG8vy5csHrgZef/11Hn74YQB0Oh0JCQn+K95PxtpGPT09bN26lb/927/1a93+NJY2MpvNLFu2DACj0cisWbNoaGjwa/2+8uVpMYxG48C0GF+2Z88e7r77bgBWr17NwYMHUVWV3bt3s3btWoxGIxkZGUyaNImSkhItnoZPjaWNZs2aRUpKCgDTp0/H4XDgcHhnAeeACPCWlpaBm4SSk5NpbR08D0JDQwNWq3Xg+5SUFBoaGujs7F8m7MUXX+Tuu+/mscceo7m52T+F+9FY2gj62+ehhx4iPDzcPwVrYKxtdElnZyd79+4lJyfHtwX7yXCec0NDA6mpqUD/EOLo6Gja2tqGdWwwGEsbfdnOnTvJzs7GaPTOQirjZj7wBx988IrBumnTpmEdr17l1n6Xy0V9fT2LFi3iRz/6EVu3buWZZ57hZz/72Zhr9jdftVFpaSlVVVU8+eSTl/VtBiJftdElLpeLzZs3c//99w9M5BbohnrO19pnOMcGg7G00SUVFRU899xz/OY3v/FaXeMmwH/7299e9WcWi4XGxkaSk5NpbGy8YheI1Wrl448/Hvi+oaGB66+/nvj4eMxmM6tWrQJgzZo1bN++3ev1+4Ov2ujYsWOcOHGC3NxcXC4Xra2t3H///fz+97/3xdPwKV+10SVPPfUUkydP5sEHH/Rm2ZoazrQYVquVuro6rFYrLpeLrq4u4uLiQmZKjbG0EUB9fT1/93d/xzPPPMPEiRO9VldAdKHk5uZSUFAA9M96uGLFikH73HjjjRw4cICOjg46Ojo4cOAAN954I4qicOutt/LRRx8BcPDgQaZOnerX+v1hLG103333ceDAAfbs2cOrr77K5MmTAzK8hzKWNgL4xS9+QXd3N08++aRf6/a14UyLkZubOzAiZ+fOnSxbtgxFUcjNzeWdd97B4XBQXV3NuXPnmDdvnhZPw6fG0kadnZ1s3LiRzZs3s3jxYu8W5rWPQ32otbVVfeCBB9RVq1apDzzwgNrW1qaqqqqWlJSoTz755MB+r732mrpy5Up15cqV6vbt2we219TUqPfdd596++23qw888IBaW1vr9+fga2Nto0uqq6uDdhTKWNqorq5OzcrKUtesWaPeeeed6p133qn+5S9/0eR5+MK+ffvUvLw8dcWKFerLL7+sqqqqvvDCC2phYaGqqqra19enPvroo+rKlSvVe+65R62qqho49uWXX1ZXrFih5uXlBc3InCsZbRu99NJL6vz58wdeN3feeafa3NzslZrkVnohhAhQAdGFIoQQYjAJcCGECFAS4EIIEaAkwIUQIkBJgAshRICSABdCiAAlAS6EEAHq/wNmRk3Y1lF/zQAAAABJRU5ErkJggg==\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.distplot(trace.groupIdx)\n", + "sum(trace['groupIdx']>0) / len(trace['groupIdx'])" + ] + }, + { + "cell_type": "code", + "execution_count": 517, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Presenting differences between the groups using scatter plot for each group + \n", + "## The resulting Bayesian analyses plots (density of differences and boxplot)\n", + "\n", + "sns.set_style(\"whitegrid\")\n", + "plt.figure(figsize=(5,5))\n", + "grid = plt.GridSpec(2, 20, wspace=.1, hspace=0.0) # building a grid to put the graphs in\n", + "plt.subplot(grid[:, :10])\n", + "#fig.add_subplot(grid[0,0])\n", + "g1= sns.stripplot(x='group',y='corr_amgVmpfc2',hue = 'group', data=dfBoth, s=8)\n", + "#g1 = sns.boxplot(x='group',y='meanAct',hue = 'group', data=df)\n", + "g1.set_ylim(.35,.5)\n", + "g1.legend_.remove()\n", + "\n", + "plt.subplot(grid[:, 10])\n", + "g3 = sns.boxplot(trace.groupIdx, orient='v')\n", + "g3.set_ylim(.35,.5)\n", + "g3.set_yticks([])\n", + "\n", + "plt.subplot(grid[:, 11:13])\n", + "g2 = sns.distplot(trace.groupIdx, vertical=True, color=\"Green\")\n", + "g2.set_ylim(.35,.5)\n", + "#g2.set_yticks([])\n", + "g2.yaxis.tick_right()" + ] + }, + { + "cell_type": "code", + "execution_count": 413, + "metadata": {}, + "outputs": [], + "source": [ + "######## T test instead?\n", + "with pm.Model() as model:\n", + " ketamine_mean = pm.Normal('ketamine_mean', mu = 0, sd=.1)\n", + " midazolam_mean = pm.Normal('midazolam_mean', mu = 0, sd=.1) \n", + " \n", + " ketamine_std = pm.Uniform('ketamine_std', lower=1, upper=30)\n", + " midazolam_std = pm.Uniform('midazolam_std', lower=1, upper=30)\n", + " \n", + " ν = pm.Exponential('ν_min_one', 1/.05) + .01\n", + "\n", + "with model:\n", + " λ1 = ketamine_std**-2\n", + " λ2 = midazolam_std**-2 \n", + "\n", + " group1 = pm.StudentT('group1', nu=ν, mu=ketamine_mean, lam=λ1, observed=dfBoth.corr_amgVmpfc2[dfBoth.group=='ketamine'])\n", + " group2 = pm.StudentT('group2', nu=ν, mu=midazolam_mean, lam=λ2, observed=dfBoth.corr_amgVmpfc2[dfBoth.group=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": 414, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (4 chains in 4 jobs)\n", + "NUTS: [ν_min_one, midazolam_std, ketamine_std, midazolam_mean, ketamine_mean]\n", + "Sampling 4 chains, 0 divergences: 100%|██████████| 10000/10000 [00:02<00:00, 4000.37draws/s]\n" + ] + } + ], + "source": [ + "with model:\n", + "\n", + " diff_of_means = pm.Deterministic('difference of means', ketamine_mean - midazolam_mean)\n", + " diff_of_stds = pm.Deterministic('difference of stds', ketamine_std - midazolam_std)\n", + " effect_size = pm.Deterministic('effect size',\n", + " diff_of_means / np.sqrt(\n", + " (ketamine_std**2 + midazolam_std**2) / 2))\n", + " trace = pm.sample(2000)" + ] + }, + { + "cell_type": "code", + "execution_count": 415, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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meansdhpd_3%hpd_97%mcse_meanmcse_sdess_meaness_sdess_bulkess_tailr_hat
ketamine_mean0.0810.095-0.1000.2570.0010.0018707.06382.08702.06302.01.0
midazolam_mean0.0760.097-0.1140.2490.0010.0017741.05984.07741.06553.01.0
ketamine_std1.1590.1761.0001.4590.0020.0017754.07409.06124.03666.01.0
midazolam_std1.1830.2071.0001.5280.0020.0027356.06942.05478.03544.01.0
ν_min_one0.4520.1260.2250.6850.0020.0017035.06916.06845.05519.01.0
difference of means0.0040.135-0.2480.2580.0010.0018115.05015.08128.06273.01.0
difference of stds-0.0240.273-0.5370.4740.0030.0027699.06079.08201.06570.01.0
effect size0.0040.116-0.2100.2260.0010.0018399.05086.08405.06633.01.0
\n", + "
" + ], + "text/plain": [ + " mean sd hpd_3% hpd_97% mcse_mean mcse_sd \\\n", + "ketamine_mean 0.081 0.095 -0.100 0.257 0.001 0.001 \n", + "midazolam_mean 0.076 0.097 -0.114 0.249 0.001 0.001 \n", + "ketamine_std 1.159 0.176 1.000 1.459 0.002 0.001 \n", + "midazolam_std 1.183 0.207 1.000 1.528 0.002 0.002 \n", + "ν_min_one 0.452 0.126 0.225 0.685 0.002 0.001 \n", + "difference of means 0.004 0.135 -0.248 0.258 0.001 0.001 \n", + "difference of stds -0.024 0.273 -0.537 0.474 0.003 0.002 \n", + "effect size 0.004 0.116 -0.210 0.226 0.001 0.001 \n", + "\n", + " ess_mean ess_sd ess_bulk ess_tail r_hat \n", + "ketamine_mean 8707.0 6382.0 8702.0 6302.0 1.0 \n", + "midazolam_mean 7741.0 5984.0 7741.0 6553.0 1.0 \n", + "ketamine_std 7754.0 7409.0 6124.0 3666.0 1.0 \n", + "midazolam_std 7356.0 6942.0 5478.0 3544.0 1.0 \n", + "ν_min_one 7035.0 6916.0 6845.0 5519.0 1.0 \n", + "difference of means 8115.0 5015.0 8128.0 6273.0 1.0 \n", + "difference of stds 7699.0 6079.0 8201.0 6570.0 1.0 \n", + "effect size 8399.0 5086.0 8405.0 6633.0 1.0 " + ] + }, + "execution_count": 415, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pm.summary(trace)" + ] + }, + { + "cell_type": "code", + "execution_count": 416, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pm.forestplot(trace, var_names=['ketamine_mean',\n", + " 'midazolam_mean']);" + ] + }, + { + "cell_type": "code", + "execution_count": 472, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 472, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# check association with PCL score\n", + "## read pcl scores\n", + "pclDf = pd.read_csv('/home/or/Documents/kpe_analyses/KPEIHR0009_DATA_2019-10-07_1121.csv')\n", + "# take only KPE patients\n", + "pclDf = pclDf[pclDf['scr_id'].str.startswith('KPE')]\n", + "dfP = pd.DataFrame({'subject': pclDf['scr_id']})\n", + "dfP_PCL = pclDf[['scr_id','redcap_event_name','pcl5_1', 'pcl5_2', 'pcl5_3', 'pcl5_4', 'pcl5_5', 'pcl5_6', 'pcl5_7',\n", + " 'pcl5_8', 'pcl5_9', 'pcl5_10', 'pcl5_11', 'pcl5_12', 'pcl5_13', 'pcl5_14', 'pcl5_15', 'pcl5_16', 'pcl5_17',\n", + " 'pcl5_18', 'pcl5_19', 'pcl5_20']]\n", + "# remove NAs\n", + "dfP_PCL = dfP_PCL.dropna()\n", + "# set list of columns for analysis\n", + "colList = list(dfP_PCL)\n", + "colList.remove('scr_id')\n", + "colList.remove('redcap_event_name')\n", + "# set total pcl scores \n", + "dfP_PCL['pclTotal'] = dfP_PCL[colList].sum(axis=1)\n", + "sns.distplot(dfP_PCL.pclTotal)" + ] + }, + { + "cell_type": "code", + "execution_count": 473, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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redcap_event_name30Days90DaysScreeningVisit1Visit7
scr_id
KPE 1560NaNNaN77.0NaNNaN
KPE 1565NaNNaN60.0NaNNaN
KPE006NaNNaN36.0NaNNaN
KPE00856.049.0NaN58.061.0
KPE1205NaNNaN43.0NaNNaN
..................
KPE1548NaNNaN43.0NaNNaN
KPE1549NaNNaN12.0NaNNaN
KPE1556NaNNaN0.0NaNNaN
KPE1561NaNNaN57.0NaNNaN
KPE1563NaNNaN50.0NaNNaN
\n", + "

65 rows × 5 columns

\n", + "
" + ], + "text/plain": [ + "redcap_event_name 30Days 90Days Screening Visit1 Visit7\n", + "scr_id \n", + "KPE 1560 NaN NaN 77.0 NaN NaN\n", + "KPE 1565 NaN NaN 60.0 NaN NaN\n", + "KPE006 NaN NaN 36.0 NaN NaN\n", + "KPE008 56.0 49.0 NaN 58.0 61.0\n", + "KPE1205 NaN NaN 43.0 NaN NaN\n", + "... ... ... ... ... ...\n", + "KPE1548 NaN NaN 43.0 NaN NaN\n", + "KPE1549 NaN NaN 12.0 NaN NaN\n", + "KPE1556 NaN NaN 0.0 NaN NaN\n", + "KPE1561 NaN NaN 57.0 NaN NaN\n", + "KPE1563 NaN NaN 50.0 NaN NaN\n", + "\n", + "[65 rows x 5 columns]" + ] + }, + "execution_count": 473, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# reshape it to wide\n", + "df2=dfP_PCL.pivot(index = 'scr_id',columns='redcap_event_name', values='pclTotal')\n", + "list(df2)\n", + "df2 = df2.rename(columns={\"30_day_follow_up_s_arm_1\": \"30Days\", \"90_day_follow_up_s_arm_1\": \"90Days\",\n", + " \"screening_selfrepo_arm_1\": \"Screening\", \"visit_1_arm_1\": \"Visit1\", \n", + " \"visit_7_week_follo_arm_1\": \"Visit7\"})\n", + "#df2['scr_id'] = dfP_PCL['scr_id']\n", + "df2" + ] + }, + { + "cell_type": "code", + "execution_count": 497, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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scr_idgroupcorr_amgHipp2corr_amgVmpfc2corr_hippVmpfc2corr_amgHipp1corr_amgVmpfc1corr_hippVmpfc1hippAmgDeltaamgVmpfcDeltahippVmpfcDeltaleft_amgHippo30Days90DaysScreeningVisit1Visit7days30_1days30_sdays7_1
0KPE008ketamine0.3599010.3699960.3634230.3488470.3716710.3606710.011053-0.0016750.0027520.06908156.049.0NaN58.061.0-2.0NaN3.0
1KPE1223ketamine0.4649470.4238130.5112210.4715710.4440400.501075-0.006624-0.0202270.0101460.21689542.049.039.041.050.01.03.09.0
2KPE1253midazolam0.4715710.4440400.5010750.4475080.4479340.4876890.024063-0.0038940.0133860.07280133.0NaN58.063.058.0-30.0-25.0-5.0
3KPE1263midazolam0.4475080.4479340.4876890.4715710.4440400.501075-0.0240630.003894-0.0133860.51026637.034.021.054.056.0-17.016.02.0
4KPE1293ketamine0.4685260.4337990.5094810.4649470.4238130.5112210.0035790.009986-0.001741-0.0283488.03.033.036.06.0-28.0-25.0-30.0
5KPE1307ketamine0.4474380.4459860.4911380.4843390.4706490.509483-0.036901-0.024663-0.0183450.08489345.020.0NaN49.041.0-4.0NaN-8.0
6KPE1315ketamine0.4649470.4238130.5112210.4653300.4222670.510414-0.0003830.0015450.0008080.071384NaNNaN40.038.08.0NaNNaN-30.0
7KPE1322ketamine0.4653300.4222670.5104140.4895890.4730590.512692-0.024259-0.050792-0.002278-0.35156638.027.0NaN56.022.0-18.0NaN-34.0
8KPE1339ketamine0.4653300.4222670.5104140.4475080.4479340.4876890.017822-0.0256670.0227240.24254946.067.068.0NaN65.0NaN-22.0NaN
9KPE1343ketamine0.4649470.4238130.5112210.4649470.4238130.5112210.0000000.0000000.000000-0.17374820.019.028.038.020.0-18.0-8.0-18.0
10KPE1351midazolam0.4895890.4730590.5126920.4694760.4618440.5018520.0201120.0112150.0108400.26013933.025.0NaNNaN26.0NaNNaNNaN
11KPE1356midazolam0.4685260.4337990.5094810.4685260.4337990.5094810.0000000.0000000.0000000.07471852.0NaN61.063.056.0-11.0-9.0-7.0
12KPE1364midazolam0.4685260.4337990.5094810.4715710.4440400.501075-0.003045-0.0102410.008406-0.10919449.052.048.051.042.0-2.01.0-9.0
13KPE1369midazolam0.4685260.4337990.5094810.4474380.4459860.4911380.021088-0.0121870.018342-0.12436048.049.055.052.031.0-4.0-7.0-21.0
14KPE1387ketamine0.4649470.4238130.5112210.4685260.4337990.509481-0.003579-0.0099860.0017410.24944448.039.032.0NaN46.0NaN16.0NaN
15KPE1390midazolam0.4653300.4222670.5104140.4895890.4730590.512692-0.024259-0.050792-0.002278-0.0944916.025.038.0NaN21.0NaN-32.0NaN
16KPE1403midazolam0.4475080.4479340.4876890.4475080.4479340.4876890.0000000.0000000.000000-0.0855054.08.017.012.03.0-8.0-13.0-9.0
17KPE1464ketamine0.4477800.4471800.4882370.4474380.4459860.4911380.0003420.001195-0.0029010.04283721.031.035.0NaN14.0NaN-14.0NaN
18KPE1468midazolam0.4649470.4238130.5112210.4715710.4440400.501075-0.006624-0.0202270.010146-0.019087NaN9.028.029.029.0NaNNaN0.0
19KPE1480midazolam0.4685260.4337990.5094810.4474380.4459860.4911380.021088-0.0121870.0183420.220688NaN27.031.030.034.0NaNNaN4.0
20KPE1499ketamine0.4653300.4222670.5104140.4694760.4618440.501852-0.004147-0.0395770.008562-0.27654941.0NaN44.064.0NaN-23.0-3.0NaN
\n", + "
" + ], + "text/plain": [ + " scr_id group corr_amgHipp2 corr_amgVmpfc2 corr_hippVmpfc2 \\\n", + "0 KPE008 ketamine 0.359901 0.369996 0.363423 \n", + "1 KPE1223 ketamine 0.464947 0.423813 0.511221 \n", + "2 KPE1253 midazolam 0.471571 0.444040 0.501075 \n", + "3 KPE1263 midazolam 0.447508 0.447934 0.487689 \n", + "4 KPE1293 ketamine 0.468526 0.433799 0.509481 \n", + "5 KPE1307 ketamine 0.447438 0.445986 0.491138 \n", + "6 KPE1315 ketamine 0.464947 0.423813 0.511221 \n", + "7 KPE1322 ketamine 0.465330 0.422267 0.510414 \n", + "8 KPE1339 ketamine 0.465330 0.422267 0.510414 \n", + "9 KPE1343 ketamine 0.464947 0.423813 0.511221 \n", + "10 KPE1351 midazolam 0.489589 0.473059 0.512692 \n", + "11 KPE1356 midazolam 0.468526 0.433799 0.509481 \n", + "12 KPE1364 midazolam 0.468526 0.433799 0.509481 \n", + "13 KPE1369 midazolam 0.468526 0.433799 0.509481 \n", + "14 KPE1387 ketamine 0.464947 0.423813 0.511221 \n", + "15 KPE1390 midazolam 0.465330 0.422267 0.510414 \n", + "16 KPE1403 midazolam 0.447508 0.447934 0.487689 \n", + "17 KPE1464 ketamine 0.447780 0.447180 0.488237 \n", + "18 KPE1468 midazolam 0.464947 0.423813 0.511221 \n", + "19 KPE1480 midazolam 0.468526 0.433799 0.509481 \n", + "20 KPE1499 ketamine 0.465330 0.422267 0.510414 \n", + "\n", + " corr_amgHipp1 corr_amgVmpfc1 corr_hippVmpfc1 hippAmgDelta \\\n", + "0 0.348847 0.371671 0.360671 0.011053 \n", + "1 0.471571 0.444040 0.501075 -0.006624 \n", + "2 0.447508 0.447934 0.487689 0.024063 \n", + "3 0.471571 0.444040 0.501075 -0.024063 \n", + "4 0.464947 0.423813 0.511221 0.003579 \n", + "5 0.484339 0.470649 0.509483 -0.036901 \n", + "6 0.465330 0.422267 0.510414 -0.000383 \n", + "7 0.489589 0.473059 0.512692 -0.024259 \n", + "8 0.447508 0.447934 0.487689 0.017822 \n", + "9 0.464947 0.423813 0.511221 0.000000 \n", + "10 0.469476 0.461844 0.501852 0.020112 \n", + "11 0.468526 0.433799 0.509481 0.000000 \n", + "12 0.471571 0.444040 0.501075 -0.003045 \n", + "13 0.447438 0.445986 0.491138 0.021088 \n", + "14 0.468526 0.433799 0.509481 -0.003579 \n", + "15 0.489589 0.473059 0.512692 -0.024259 \n", + "16 0.447508 0.447934 0.487689 0.000000 \n", + "17 0.447438 0.445986 0.491138 0.000342 \n", + "18 0.471571 0.444040 0.501075 -0.006624 \n", + "19 0.447438 0.445986 0.491138 0.021088 \n", + "20 0.469476 0.461844 0.501852 -0.004147 \n", + "\n", + " amgVmpfcDelta hippVmpfcDelta left_amgHippo 30Days 90Days Screening \\\n", + "0 -0.001675 0.002752 0.069081 56.0 49.0 NaN \n", + "1 -0.020227 0.010146 0.216895 42.0 49.0 39.0 \n", + "2 -0.003894 0.013386 0.072801 33.0 NaN 58.0 \n", + "3 0.003894 -0.013386 0.510266 37.0 34.0 21.0 \n", + "4 0.009986 -0.001741 -0.028348 8.0 3.0 33.0 \n", + "5 -0.024663 -0.018345 0.084893 45.0 20.0 NaN \n", + "6 0.001545 0.000808 0.071384 NaN NaN 40.0 \n", + "7 -0.050792 -0.002278 -0.351566 38.0 27.0 NaN \n", + "8 -0.025667 0.022724 0.242549 46.0 67.0 68.0 \n", + "9 0.000000 0.000000 -0.173748 20.0 19.0 28.0 \n", + "10 0.011215 0.010840 0.260139 33.0 25.0 NaN \n", + "11 0.000000 0.000000 0.074718 52.0 NaN 61.0 \n", + "12 -0.010241 0.008406 -0.109194 49.0 52.0 48.0 \n", + "13 -0.012187 0.018342 -0.124360 48.0 49.0 55.0 \n", + "14 -0.009986 0.001741 0.249444 48.0 39.0 32.0 \n", + "15 -0.050792 -0.002278 -0.094491 6.0 25.0 38.0 \n", + "16 0.000000 0.000000 -0.085505 4.0 8.0 17.0 \n", + "17 0.001195 -0.002901 0.042837 21.0 31.0 35.0 \n", + "18 -0.020227 0.010146 -0.019087 NaN 9.0 28.0 \n", + "19 -0.012187 0.018342 0.220688 NaN 27.0 31.0 \n", + "20 -0.039577 0.008562 -0.276549 41.0 NaN 44.0 \n", + "\n", + " Visit1 Visit7 days30_1 days30_s days7_1 \n", + "0 58.0 61.0 -2.0 NaN 3.0 \n", + "1 41.0 50.0 1.0 3.0 9.0 \n", + "2 63.0 58.0 -30.0 -25.0 -5.0 \n", + "3 54.0 56.0 -17.0 16.0 2.0 \n", + "4 36.0 6.0 -28.0 -25.0 -30.0 \n", + "5 49.0 41.0 -4.0 NaN -8.0 \n", + "6 38.0 8.0 NaN NaN -30.0 \n", + "7 56.0 22.0 -18.0 NaN -34.0 \n", + "8 NaN 65.0 NaN -22.0 NaN \n", + "9 38.0 20.0 -18.0 -8.0 -18.0 \n", + "10 NaN 26.0 NaN NaN NaN \n", + "11 63.0 56.0 -11.0 -9.0 -7.0 \n", + "12 51.0 42.0 -2.0 1.0 -9.0 \n", + "13 52.0 31.0 -4.0 -7.0 -21.0 \n", + "14 NaN 46.0 NaN 16.0 NaN \n", + "15 NaN 21.0 NaN -32.0 NaN \n", + "16 12.0 3.0 -8.0 -13.0 -9.0 \n", + "17 NaN 14.0 NaN -14.0 NaN \n", + "18 29.0 29.0 NaN NaN 0.0 \n", + "19 30.0 34.0 NaN NaN 4.0 \n", + "20 64.0 NaN -23.0 -3.0 NaN " + ] + }, + "execution_count": 497, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# merging two data frames toghether\n", + "dfTest = pd.merge(dfBoth, df2, on = 'scr_id')\n", + "# create difference pcl score\n", + "dfTest['days30_1'] = dfTest['30Days'] - dfTest.Visit1\n", + "dfTest['days30_s'] = dfTest['30Days'] - dfTest.Screening\n", + "dfTest['days7_1'] = dfTest['Visit7'] - dfTest.Visit1\n", + "dfTest" + ] + }, + { + "cell_type": "code", + "execution_count": 478, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(-0.3348082469632209, 0.24196059319583937)" + ] + }, + "execution_count": 478, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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sRhyKxqbvNTorMEPWgAlxqjIWYpZlce+99/Lkk09SVVXFSy+9xK5du7o95/nnn6egoIDXX3+dr371qyxfvhyA4uJifvazn7FixQp+8pOfcNddd2XiW8iIjoTBwYiOkc3Ti9nQgv/p28DW3Q2OHcf9aOvu4+lg6u7PQI+m53pCDFEZC7HNmzczbtw4Kioq8Pv9LFmyhFWrVnV7zptvvsnll18OwOLFi1m9ejWO43D66adTVlYGQGVlJbquo+sD+A0xzRKGSVNHlk8vdrbgD9SdKCYvgouWQ34ZJNrcjxctT093oh6XJg4h0iRjLfaNjY2MHDky9XlZWRmbN28+4jmjRrmb2Pp8PvLz82ltbaWkpCT1nJUrVzJt2jT8/hMf0GgYBrurd/d4jDYeDkbSew6Ybhjs21eTlmvtURQKQ36CXof+WhSradpJ/QxPRPHsQgkVo3tz++68taREIsHWrVtP4k+Uw+yfHvrUAk7qz3fnURT8VhQn3opzktOp6f6596dsHjscf/yTps3q59GIw/U4xN566y127tyJph367fHWW2895Rd2jvKGpSjKST1n586dLF++nKeeeqpHr6mqKpMqJvV4jLplEexI72LdfftqGDu2Iq3XDPi8FOf6UT19X1jvrt7NpIk9/xn2mBpyT4v29t3vVVu3bmXatGl9dv3jsgy3gcP0AYUn/cf77OfeD7J57JD94x/sevSut2zZMl5++WV+97vfAW71U1dX16sXHjlyJA0NDanPGxsbGTFixBHPqa93z8QyTZNwOExRUREADQ0N3Hrrrfzrv/4rY8em8WZ7FtJMi6aOBLFsnl404gP/Ptmp6uxAPPy4HCFEr/UoxDZu3Mi//du/UVBQwK233spzzz3XLYBOxYwZM9izZw81NTXouk5VVRULFizo9pwFCxbwhz/8AXCDc86cOSiKQkdHB1//+te5/fbbOeecc3o1jsHCchyaoxqtsSzuXrT0wbdVleNA5IAEmBB9pEdzN8Gge2pwKBSisbGR4uLiVLv7Kb+wz8eyZcu4+eabsSyLK6+8ksrKSh566CGmT5/OwoULWbp0KXfeeSeLFi2isLCQBx98EIDf/e537Nu3j8cff5zHH38cgKeeeorS0tJejWkwiGgGhmX3eEf8tdXNPLe+hob2OCMLQ1xzbgWzJ2bw55jaqmoEBHIzN450iTaDHsn0KIQYtHoUYp/97Gfp6Ojga1/7GldccQWKorB06dJev/j8+fOZP39+t8duu+1QC3MgEODhhx8+4s/dcsst3HLLLb1+/cFKMy0OhhMU5qjk+tVjPm9tdTMPvbkT1auQH1RpiWo89OZOboPMBlnn+imGQaAgc+PorXhb9m23JUSW6VGI/d3f/R1+v5/Fixfzuc99Dk3TCAQCfT020QuW49AS1dFMh6KQiuewphmA59bXoHoVgqr718D9aPLc+prMhhiAY0O4yb2fFCrK7FhOhRZOnnSdpVO7QmSJHt0T+9KXvpT6b7/fT35+frfHxMAV1Qyawhq6dWRLd0N7nICv+y75AZ+XxvaBsgWS4wZB5GB2bFXVSY+7B1pKgAnR545biTU1NdHY2EgikeDjjz9OtbxHIhHi8YHyRidORLcsmsI2hTkqeV2mF0cWhmiJaqlKDNypyLLC0NEukyGOu9jY0t3TovuwBT8ttLAbYAN9Wy0hBonjviP85S9/4cUXX6ShoYH7778/9Xhubi633357nw9OpE/ngZu64VCU404vXnNuBQ+9uRMwCfi8aKaFYTlcc25617GlhRGD9hr3HlmwcOCFmW1DrBkSHUgFJkT/Oe47weWXX87ll1/OypUrWbx4cX+NSfShqN7Zvagye2Ipt+HeG2tsj1M2ELoTj8e2IN4KWocbZqEi8AyAQ0ONBESbZBspITLguCH2q1/96qj/3emmm25K/4hEn9Mti4MRm8KQG2QDNrSOpWuYhYohkJ+ZMHMcdxzx1uy6ZyfEIHLcEItGZYftwcp2HFpjOrp5aHox69iWe/8p1gJqjruuLJDfP68t1ZcQA8JxQ6w3eyOK7NB1evHwTsWs4djugmI94t6TyikFNZj+17Et9396RKovIQaIHrXYf/LJJ9x444184QtfAGDbtm2pnTJE9nOnFzUimpHpofSeEYeO/RA+4HYKmrobNkaCAPqpbWkVb4Pmamjd6zaXxFokwIQYIHoUYj/4wQ+444478Pncwm3q1Km8/PLLfTow0b86pxdbojpWtr9BO457vyzc6IZOyyfQvh8n3OhuadXTM8w6N+6NHnSrPceW8BJigOlRiMXjcWbOnNntMa83S6eexHFFdYOmjgQJI4t3xO/KcdzwIXnmWueWVtoJ9jM0Em5Fp4X7Y5RCiFPUoxArLi5m3759qbO8Xn31VYYPH96nAxOZY9g2TRGNtngW74h/PJ1BFmk68ugXx3GnDzvqpGlDiCzQoxWj99xzDz/4wQ+orq7mggsuoLy8nOXLl/f12ESGhRMGmpHlTR/H4jju5rxa2O1oVDxgm+7OIBJeQmSNHoVYRUUFv/71r4nFYti2TV5eXl+PSwwQumVxIGyRF1ApCB17R/ys5diy07wQWeyEIVZdXc3vf/97qqurAZg0aRJXX301EyZM6PPBiYEjohkkDBOzZzPQQgjRL477jrRx40a+8pWvkJuby9VXX83VV19NKBTihhtu4IMPPuivMYoBwrQdmiPa4OhgFEIMCsetxB577DEeeOABZs+enXrswgsvZM6cOTz66KM8+eSTfT5AMbA4TnKBtJm8V6YOsntlQoisctxKrKampluAdTrvvPOoqanps0GJgU+3LQ5EErTEpCoTQmTOcSux3NzcY34tJycn7YMR2SeqGSR0k/ygSm7Al517MAohstZxQ6y+vp4f//jHRzzuOA6NjY19NiiRXSzHoS2uE9GMVJgpSJgJIfrecUPsrrvuOubXpk+fnvbBDCSG5VDXYaA4jlQXPWTa7tZVkYRJfshHrn8QtuQLIQaUEx6KOVR97/VGfr+lnZKQh9nlQeZWBDl3dJD8gLSYn4hh27REdeK6TUFIxe+Vn5kQom/0aLHzN7/5zSMey8/PZ/r06VxzzTUEAoG0DyzTyvLcH01L3OaVnTFe2RnDq8AZI/ypUDutRE1txSWOFDdMNNOiIKiSH5SqTAiRfj0KsfLyclpbW1myZAkAL7/8MsOGDWPPnj18//vf56c//WmfDjITbj+/lC9MzaVqaztrahN80KChW7C5UWdzo85/vt9BaY6HOeVBZpcH+dSYIHl+qTgOZyfvl+mWe5K0zyM/IyFE+vQoxLZu3cozzzyT+nzBggVcf/31PPPMM6lgG2wURWFCsZ+rpudz1fR84obNhnqNtbUJ1tQkqI9YNMdsqnbEqNrhVmnTy/zMKQ8ypyLIpGKp0rqK6Sa6aZEfUsmTe2VCiDTpUYi1tLRQV1fH6NGjAairq6O1tRUAVR0ab0gh1cP5Y0OcPzaE4zjsazdZkwy0TQ0ahg2bGnQ2Neg8sb6D4TlezisPMLcixLmjA+RKleY2fkR1YppFYWgQbiosxABlmmbqPMjBpkff1Xe/+12uu+46KioqAKitreWee+4hFotx2WWX9ekAByJFURhXpDKuSOVL0/OJGTYb6zXW1CRYU5ugIWLRFLO6VWkzRwaYXR5knBcqHGdIV2maeWhT4cKQKt2fQvTSY489xooVKxg1ahTFxcWcccYZvPXWW8yaNYsNGzawYMECFi9ezN13301LSwslJSXcf//9jB49mu9+97t89rOf5fOf/zwAs2bNYuPGjaxdu5aHH36YoqIiPvnkE84991x++MMf4hlgtwR6FGLz58/ntddeo7q6GsdxmDhxYqqZ46tf/Wpfji8r5BxWpe1tN1lTk2Bt8l6aacPGeo2N9RqgMOLDBs4b4zaHnDOEq7SIZqAZFvkhHzl+WVsmxKn48MMPee211/jjH/+IaZpcccUVnHHGGQB0dHTwu9/9DnAb9C677DIuv/xyXnjhBX784x/z+OOPH/famzdv5uWXX2b06NHcfPPNvPbaa6mwGyh6FGKWZfHOO++wf/9+LMtizZo1ANx00019OrhspCgK44tUxhepXDPDrdI21GmpqcfGqMWBqMVLO6K8tCOaqtLmlAeZUx5kQrFvSFVpne34kYRFbtBLroSZECfl/fffZ+HChQSDQQA+97nPpb528cUXp/5748aNPPLIIwBceumlPWrImzlzZmoGbsmSJbz//vvZGWLf/OY3CQQCTJ48ecCVkgNdjurhM+NCfGacW6Wt3lrLXquINTUJNjd2r9J+tq6dEbneVMfjuaMD5AyRKk23LPSoRSRukhd0KzOZZhSid0Kh0DG/1vnLstfrxbZtwN2NyTCMI55zrM8Hgh6FWENDAytWrOjrsQx6iqJQngefHpvPtTPyiek26+uSHY+1CQ4kq7Q/bY/yp+1RfB6YWRZgToVbpY0vGvxVmmHbtMZ0OuIGecktrLyD/HsWojfOPvts7rnnHr7xjW9gmiZvvfUWV1999RHPmzVrFlVVVVx22WWsWLGCc845B4AxY8bw0UcfcfHFF7Nq1apuIbZ582ZqamoYM2YMr7zyylGvm2k9CrF58+bxl7/8hc985jN9PZ4hJcfvYd74EPPGu1XaJ60mq2vde2mbk/fSNtRrbKjXePy9dspyvalAO3t0gBx18FZpluPQHtcJJwxyAz7yAj5ZYybEUcycOZMFCxbwxS9+kTFjxjB9+nTy8/OPeN73v/997r77bn75y1+mGjsArr76am655RaWLl3K3Llzu23uftZZZ/HAAw+wY8cOzj33XBYtWtRv31dPKY5z4nM0Xn/9de68805s28bn8+Eku+s2bNjQH2NMm61bNjFt5LF35j+cblk0diTSOoZ9+2oYO7bihM+LJqu0zgaRppjV7euqB85MdjzOrQgytrB/qrSejj/dPIpCyO8jP+hDPcUw2129m0kTJ6V5ZP1Dxp45xx1/oADyR/TvgI4iGo2Sm5tLPB7n+uuv55//+Z9TzR2nau3atTz11FM88cQTaRpl3+hRJfaTn/yE5557jilTpgz66ayBItfvYf74EPOTVdruVoO1NQlW1ybY0qhj2LC+TmN9ncZj77UzKs/L7ORC67NHBQgNsirNdhyimkFcN3sdZkIMNsuWLWPXrl1omsbll1/e6wDLJj0KsfHjxzN58mQJsAxRFIXTSvycVuLn+jMLiOg26/e799HW1CZojtnURyz+uC3KH7dF8XvhzC730ir6qUrrD13DLMfvI0/CTAgeeOCBtF9z9uzZRz0UeaDpUYgNHz6cG264gXnz5uH3+1OPS4t9ZuT5PXx2Qg6fnZCD4zjsajFYU5tgbU2CLQd0dAvW1Wmsq9N4ZG07o/MPdTyePTpA0Jf9b/q24xDRDKKaQVD1EfJ7CKnS0SjEUNPjDYDLy8sxDKNb54rIPEVRqCz1U1nq54YzCwhrNuvrEqndQ1riNnVhixe3Rnlxq1ulndW5Lq0iSEVhdm8b5uDulh83wKsYhPw+cvxe2dJKiCGiRyF26623dvtc0zTefPPNPhmQ6J38gIfPTcjhc12qtNXJ5pDOKu29/Rrv7dd4eG07Y/K9zO7seBwVJODL3krGSlZnEc0gpPrI9XsJ+QfnfnFCCFeP/4VblsVf/vIXqqqqePfddznnnHO46KKL+nJs6de2D/a+BcOnwYhpkDsCBvH0U9cq7StnuVXauuS9tLXJKm1/2OLFj6O8+LFbpZ09KphqECkvyN4AcKszE3/CTO0EIoQYfE74L3vdunWsWLGCP//5z8ycOZMNGzbwxhtvHHcl+IClhWHdk4c+D5W4YTZ8avLjNMgrG7TBlh/wsGBiDgsm5mA7DjubjdS048dNbpXW2Szy0BooL/ClWvjPGhnIyiqt604gBh4cHNnWSgxKtbW1fPOb3+Sll17q0XM3btzIJZdckpbXfvbZZwmFQhnZEP64ITZv3jxGjx7NNddcw1133UVeXh4LFizIzgCDZGidAc07wdIh3gJ733X/l3pOsRtqw6ehDJuCNzgBK3fwBZtHUZgyzM+UYX5unFVAh2bzXrJCW1OboC1hU9thUvtxhP/5OELAqzBrVIApuXBxkcnoLOSp1eAAACAASURBVKvSDNumJaLR2J4gL+STPRrFkLZ//35eeumltIXYtddem5brnIrjvhP9zd/8DatWreKVV17B6/WycOHC7G7VLhgFV/8GLANaqqFpKxzY6n482BlsrbBvNexbjQqMBqxAIXrJZIySKeglk9FLpmDljhxUwVYQ8HDhpBwunORWaTsOGqlNiz9u0tEsx/0chae3N1BR6EttWnxmllRpjpPc1iqqE01Y5AW9snu+yIi3th3giberqWmNUVGcwzfmTeSzU9O3aLqmpoZvf/vb/OhHP+LVV1/lvffeQ9d1rr/+eq655hoeeOABdu/ezaWXXsrll1/OhRdeyF133UU8HgfgBz/4AWeffTZr167lkUceobS0lG3btrFo0SImT57Mb37zGzRN47HHHmPs2LE88sgj5OTk8LWvfY0bbriBmTNnsnbtWsLhMPfddx/nnnsulmWxfPnyI8bSW8cNse9///t873vfY82aNVRVVfFv//ZvRCIRXn75ZebPn09ubs93vxhQvCoMn+L+7/Rk+WsZ0PoJHNiWCjfn4A4US8OrtROqX0eofl3qElagEKO4Er1kCnqpG25W7qhBEWweRWHqcD9Th/v56qwC2hMW6/ZrrK5JsHpflLChUNNuUtMe4fmPIgR9bpU2tzzI7Iogo/MHfpWmWxYtUYtw3CQ34CNH9mgU/eStbQdY9qePUL0KRSGVA+EEy/70EfdCWoKsurqa22+/nfvvv5/NmzeTn5/P//zP/6DrOtdccw3nn38+d9xxR7fdOOLxOL/61a8IBALs2bOH22+/nRdffBGAbdu28fLLL1NUVMTChQu56qqreOGFF3j66af57W9/y/e+970jxmBZFi+88AJ//vOfefTRR/n1r3/NCy+8cNSxdO6Sf6pO+G6jKApz585l7ty5GIbBO++8Q1VVFT/60Y9Yu3Ztr158QPGqMGyy+z++CIBhaLTUbEdt2YG/ZTv+lu2orbvwJIPN27CeYMP61CUsfz5GyeRUtaaXTMHKG531wVYY9KaqtD17o8RyRrA2eS9ta5NOwnTcgKtJwGoYV+jjvOS9tDNHBvB7B+73b9g2bck9GmXDYdEfnni7GtWrkJNsNsrx+4jpJk+8Xd3rEGtpaeGWW27hkUceobKykp/97Gds376dlStXAhAOh9m7dy+q2n1pjWma3HvvvWzbtg2Px8OePXtSX5sxYwYjRrjjGjt2LOeffz4AkydPPmYGdO6xeMYZZ7B//34A3n333aOOpc9DrJOu61RXVzNmzBjuv//+1Nb9g5rHh1E8CaN4ErFJyU5M20Tt2Ifash1/yw78zZ3BlsCrh/E2vE+w4f3UJWx/HnpxZ6hNJqgVgFOetcHmUeD04X5OH+7nprMLaOtSpb23P0F7wmZvu8neLlXaOaPdPR7nlAcZNUCrtK4bDodUH0HVQ8jvlalGkXY1rTGKQt1DJKR6qW2N9fra+fn5jBo1ig0bNlBZWYnjOHz/+9/nggsu6Pa8w8Pn17/+NcOGDeN///d/sW2bmTNnpr7WdYMLj8eT+tzj8WBZ3fd0PfzPdH3OscbSWz16R3nrrbe45557GDt2LI7jUFtby49+9CPmz5+f1sFkBY8Po2giRtFEYhM7g83C17EvWa25VZvashOPlcCjRwg2biDY6G6WPAywN+Whl1SmqjWjZDJm/hhQsm8njaKgl0WTclg0KQfLdth2UHebQ2oSbDtokDAd3t2X4N197kbK44p8qWnHmWUDr0qzHYeobhDVwRdXyA1IdSbSq6I4hwPhRKoSA4gbFuXFOcf5Uz2jqiqPPfYYX/va18jJyeEzn/kMzz77LHPmzEFVVT755BPKysrIzc0lGo2m/lw4HGbkyJF4PB7+8Ic/HDOceuNYY+m6a/6p6PEGwL/5zW8YN24cAPv27ePrX//60Ayxo/F4MYsmYBZNIDYxeeqpbeEL1+Bv3p4KN7V1Jx4zjseIEGzcSLBxY+oStpqLXlyZnI6cgl46NeuCzetROGNEgDNGBPjbswtpjVu8t98NtPf2a3RoNnvbTPa2RXhuS4TQYVXayAFWpZl29+os1+8loMpOIKJ3vjFvIsv+9BEx3SSkeokbFobl8I15E9Ny/ZycHJ544gluuukmvvWtb3HaaadxxRVX4DgOxcXFPP7440yZMgWv18sXv/hFrrjiCq677jq+/e1v8+qrrzJ79uxeB8vRXHXVVezfv/+IsfRWj45iuf7663nmmWdSnzuOw5e//OVuj2WDjB/FYls07VjHuEBHslrbgb9lBx4zfvSn+3LQSyoPdUWWTsXMLz9qsG2uaafqw3oORDRG5AVYMmMUMysK0zf2pFM9iqWzSlvTpUo73PgiX2rT4pllAdQ0V2npOEbG51EIqD4CPoWg2n8VWjYfZ5LNY4e+OYqlszuxtjVGeR90Jw4lPQqxe+65h7q6Oi666CIUReHVV19lwoQJnH322YDbip8NMh5iHOWN1LHxhWtTFduhYDv6/PihYDt0n21DewFPr6nF5wG/z4Nu2pg23Dh3XNqDLF3nibXELd5Lrkl7rzZBWO/+1zCkKpw7OpDauLgsr/dVWrrPQvMoCiHVR0j1EOzj+2fZHATZPHbIjvPEhrIevTPous6wYcNYt85tMS8pKaG9vZ3/+7//A7InxAYkxYNZMBazYCyxCclTUx0bX3h/MtQ677PtwGNE8Zgxggc2ETywKXWJhQSYpJSzzzuWPc449nrHsscZRtWH9X1SjaVDScjL5ytz+XxlLqbtsLXJvZe2uibBjmaDuOHwzt4E7+x1f4mYWHxo95AZZQF8nszfozr8/llQlc2HhehvPQqxzmOsRT9RPJgFFZgFFTD+Qvcxx8YXqUNtPtQ84m/d4TaOoDHV2c1Uc3fqEgkC7DHGULR+VqqBxCwYC56B9wbr8yjMKAswoyzAzecU0hzrei8tQUR3qG41qW6N8OyHEXKSVVrnHo8jcjN/L820D20+7Pd6yPH7CPm9+OSsMyH6VI/+9dfU1HDffffxwQcfoCgKZ511FnfffXev+/vFSVA8mPnlmPnlxMcvdB9zHLyROl5e9X+MSFQzyalhvL2PXOLJYKuG7dWpS9jeIEbxaal1bEbJZIzCceDJfAh0VZrj5aLKXC5KVmkfN+mpU613NhvEDIe39yZ4O1WlqcytcKcdZ5T5M16l6ZaNHtfpSLjTjbkBqc6E6Cs9eve64447uO6663j00UcBqKqq4vbbb+f555/v08GJE1AUrPwxjDrnEp5evde9J+ZVKDKbGGvt44uj2yk39qK2bMerh/FYCQIHtxA4uCV1CdsbSAWb0dnyP4CCzedRmFkWYGZZgL87t5CDMSvVwr++rrNKM6huNXhmc5hcVeHcMcHUvbThuZkLj0PTjQYBn5ecgJccObhTiLTq0TuV4zjddie+9NJLs64zcTCbWVHIjYyj6sN6miIaOXmjmTLjHAIVhTSBW7FF61P31jrvs3m1djyWRuDgRwQOfpS6nu31YxQlg620M9jGD4hgG5bjZcnkXJZMdqu0jw7oqfPSdrUYRA2HP++J8+c9bsfnpBI1tcdjQQbX52umhWZatCtGvzWDCDEU9Kg7cfny5RQUFHDxxRejKAovv/xyagNHgKKioj4faDqcfHeiu1msYVmc8IfUQ+nukDtljoM32nhoDVtyWy2v1n70p3v86MWTaFFHExh3jhtwRRMHRLB1Ohi1WLvfbQ5Zvz9B1Oj+/1qOz+G88hzmJKceh+Vkdoqvs7vRr7ofj9eun80dftk8dhhc3YmrVq1i9+7dfP3rXz/ia7NmzWLjxo1H+VOnZsGCBbzwwguUlJSk7ZpH06MQW7BgwbEvoCisWrUqrYPqKycbYl2Zto1lO9i2g4WDbbtrn2zHwbQd7OTXT/TDHDAhdjSOgzd2wO2K7NJA4tXajv50j4pRNCm5hs1t9zcKJ7r7UGaYaTt82KinjpbZ3XLkurTK0kNV2ukjMnsvTQFCfndBdVA98heDbA6CbB47DK4QO55sDbEe/Rr95ptv9ukgsoHP48F3gkYzh85Ac1IBZyXDznLcoFN9XhRIW2WXVoqClVtGPLeMeMU89zHHwRtvSoWatX8ThfG9eBOtKLaBv2Ub/pZtsCv5dI+KUTSx2ybIRtEE8PqP/bp9wOdxd9afNSrANz9VSFPU4uVNdeyM57Buf4KY4R4KurPZ4LebwuT5Fc4b41Zos8uDlPZzleYAMd0kppv4vabbqq968HulIWRQ2vE6/PUhaNsLRePg07fB5EW9umRtbS0333wz55xzDps2bWLKlClceeWVPPzww7S0tLB8+XJ27drFli1bWLZsGTU1NXznO9/BNM1u+xlGo1FuueUWOjo6ME2T2267jQsvvJBnn32W5557DnC3qRozZgy//e1veemll3jiiSdwHIf58+dz5513HjG2W265hYaGBjRN4ytf+Qpf+tKXADc4r7vuOlavXk1BQQG33347P/3pT6mrq+Puu+9m4cKFJ/y+jxtiq1evZu7cubz22mtH/bqsD+tOQUH1KHCcsIvmeBldlINpOzi2g+nYOA6p8DMdB9tyQ89xTlzZ9TlFwcoZgZUzgkTFBewrrmFsRXm3YOuckvQmWpLB5k5NwgoAHI8Po3BCl2NrprhTkf0YbMNzvXyuHG4cW5qs0rTUqdbVrSYR3eHNT+K8+Yl7L21yZ5VWEeT04X68/Vil6ZaFHrcgDqrHQ0D1YuHBdhxpChkMdrwOr3wHPH4IFkO40f2c5b0Osn379vHQQw9RWVnJ0qVLWbFiBc8++yyrVq3i5z//ORdeeGHquffddx/XXnstl112Wbceh0AgwGOPPUZeXh4tLS186UtfYuHChVx77bVce+21GIbBjTfeyE033URjYyPLly/nxRdfpKCggL/927/ljTfe6PY6AP/yL/9CUVERiUSCpUuX8jd/8zcUFxcTi8U477zzuPPOO/n7v/97/uM//oOnnnqK3bt380//9E+9D7F169Yxd+7c1KLmw0mInTwn+Ubk9yrghQDH/k3btG23mrPcKUzLcis8w3awLPdrGQm5w4INSFZsB7stzva3bMcbb0axTfytO/G37oTd7tHph4It2e5fOgW9aCJ4A0DfbqPlVmlBZo0K8q3zoDFipqYd19dpxA2HHc0GO5oNfrMpTL5f4VNjgqk2/uJQ/1VHhm1jaDYHIxo5bTECqo+gz4Pf55G2/Wz114fcAPMn9yf054CefLyXIVZeXs6UKVMAOO2005g7dy6KojBlypTUkSidNm7cyCOPPAK4zXrLly8H3Peof//3f2fdunV4PB4aGxs5ePAgw4cPB9zwmzNnDgsWLOCNN97gvPPOS00ZXnLJJaxbt+6IEPvtb3/L66+/DkB9fT179+6luLgYVVWZN8+d9Zk8eTJ+vx9VVZk8efIR4z2W44bYP/zDPwDwwx/+kJUrV7J///607m789ttvc99992HbNlddddURNxt1Xeeuu+7io48+oqioiAcffJDy8nIAnnjiCV544QU8Hk+fbO8/EKQWyh7jvcpyHCzbdsMtdW8Ot7rrMqXZL0GnKFg5w7FyhpMo/0zqYU/8IP7mLuextezAFz94WLBVAeAoXoyiiTQExlN/oJhS71gMtZy2mM7Tq/dyR3MTM5v+hC9aj5k7ivDp16KNmXNKww3sX0P+x8/ii9YzLHcU1vAv8pE+hmkBDV9+Dvn5BVS3O3zSZhI+rEqbMuzQvbRp/VSlOY475ZgwTBLJ23s+j0LA5zaGBH2ysDprtO11K7Cu1BC07ev1pY91bIqiKEd971aOUtmvWLGClpYWXnzxRVRVZcGCBWiaBsCLL75IXV0dy5Yt6/GY1q5dy1//+lf++7//m1AoxA033JC6nqqqqTH09JiXw/Xontgtt9xCQUEBp59+OoGA+5vy0b75k2FZFvfeey+/+tWvKCsrY+nSpSxYsIDTTjst9Zznn3+egoICXn/9daqqqli+fDn/8R//wa5du6iqqqKqqorGxkZuuukmVq5ciXeI3T/wKor7PR/n27adzvtx7vSkmXw3tGz3fp1NMux62JhysuzQMBLlw0iUfzr1mCfe3GUacjtq8w588SYUx8LfupOx7ORmABssw8N+zyhanXwmflSDLycPx5+PN95M8boHaeX/nXSQBfavoXjdgzgeFcdfgBluYtyBR6nwXU0sMAPdjBNuifOdueMoK85NbVr8fp1G3HTYftBg+0GDpz8IUxDwcN6YQOpeWn9WaabtYCa3vVIA1ecl6PMQ9Hnxqx5p3x+oisa5U4j+LjvFG3EoGtuvw5g1axZVVVVceuml/OlPf0o9Hg6HKS0tRVVV1qxZk6qItmzZwlNPPcUzzzyDJ/kL08yZM7nvvvtoaWmhsLCQqqoqvvzlL3d7nXA4TGFhIaFQiN27d/PBBx+k9fvoUYg1Njbyy1/+Mq0vvHnzZsaNG5fa9WPJkiWsWrWqW4i9+eab3HrrrQAsXryYe++9F8dxWLVqFUuWLMHv91NRUcG4cePYvHkzs2bNSusYBwOPorj3UXrwS3qqMcVyMBzbreo6G1QsN+S8afht3w6Vkhgzl8SYuYfGGW9JBdu2D9dxGjWUOq14sRlr7yf1zzsWxYk14nj9OIpK0fqHafXnYRSfhuML9uj18z9+Fsejgi8EQIvuwYuXS+1V/JSZ7jSdaVH1YT3/38VTuXRqHpdOzUO3HDZ3uZe2t82kQ7N5ozrOG9VxFGDqMDXVwj91WP/dS3MA3bTQTYsODDyKQlD1EvB58Pu8+L1SpQ0Yn77NvQem41ZgRhxs3X28H33ve9/jO9/5Dr/5zW9YvHhx6vFLLrmEb33rW1xxxRVMmzaNiRPdI2KeeeYZ2tra+MpXvgLA9OnTue+++7j99tu58cYbcRyHefPmHTGVOG/ePJ577jkuueQSJkyYwFlnnZXW76NHLfY/+MEP+PKXv5yaa02HV199lXfeeYf77rsPgD/+8Y9s3ry5W5n6hS98gSeffJKRI0cCcOGFF/L73/+eRx99lDPPPJNLL70UgLvvvpt58+bx+c9//rivuXnjenKN5rR9D6dC07RUNZs9lNRB1Lquo/r92A7YKO7HZAemkazmLNt2m1JOsaz75fvNhDWLYZ4o451aJjg1fNF6DR82Po4+xeCgEMsZQyRvAtG88cmP47C9h4JNNwz8qsrZ792G5cuDZKXSEDVQgDxi3O6/x72e4xA3Hb7zmWO3TzfFYdNB2NQMHzWDZncPrHzVYUYpnDUMZpZCfi/6WDrHfio8HiVVpaleBZ+SnJvspzuq2fl3/pDjjX/StFmn1mKf6k7c51ZgaehOHKqOW4ldcsklgDv19+KLL1JeXt5tznXFihWn/MJHy87DpyiP9Zye/NmjUVWVSRWZXa8yKNbMTDj24X0ODoblTk+ajoOZbEYxLTtV1Z3IlUoBT6/eS7uniK2+EjaZ05lm7WB8KE7AH0CxNBQzgceMgm3hsXUUHHJjteTGauHAO+5YkicEdB5ZU2MUUzL101BYgT/enKrE1ISF10rQ7BmGX3X/fmumxagi/3HX9I0Fzkn+XqdbDpsbtNTuIXvbTcKGwl8b4K8NblxOG+53t8OqCDJ1mHpSnYbpXF+oAH7VS8jn7ZcGkUHxdz7d45+8SEIrTY4bYj//+c/77IVHjhxJQ0ND6vPGxkZGjBhxxHPq6+sZOXIkpmkSDocpKirq0Z8VmaHQ2Xl59Okrw7axkoHW+T/LsjEsO1UXHL6N1vC8ALHTriO45xc4toGj5uAoHhyvSuun/h9G6VTU1p2pVn9/y3Z8kXoUx0Zt34PavofcT1ZSDDib3QYUjxbG9gVw1DxKVJuoZfG/noU4OKnz2JbMGNXj79vvdfdsPHdMkG8DdWGTtclpx/frNDTL3cj44yadpzZ2UBT0cF6y4/FTYwIUBvvvXpoDaIaFZrhVrerx4Fe9BHwKAWkQEVnmuCE2ZsyYPnvhGTNmsGfPHmpqaigrK6OqqooHHnig23MWLFjAH/7wB2bNmsXKlSuZM2cOiqKwYMEC7rjjjtQ6hT179jBz5sw+G6tIH9XjQT3Km2S3Cs52+PRpw5g9qRTTtDFtG4eptA3PJf/jZ/EepTtRG/UptFGfSl3Po3UkDxjtGmx1KDj4Ygfc51hx0NrwAT5/KQt5n9HxBlpyJnL6zPM4vRct/aPzfVx+eh6Xn56HZjpsatDcBpHaBDXtJm0Jm9d2x3htdwyPAtOG+ZldEWRueZDJJ1ml9VZnG39UO9QgEkreT5M2fjHQZWzjO5/Px7Jly7j55puxLIsrr7ySyspKHnroIaZPn87ChQtZunQpd955J4sWLaKwsJAHH3wQgMrKSi666CIuvvhivF4vy5YtG3KdiYPNiSo407ax8j+LM2U+enLZQMiGgONgOe7Us2HaGLa7y68dKEAbdS7aqHNT19i/exsTc6PdTtFWI/vdLZ/0Zs6jmfMAIuD8VcH8sDy5hu3QKdqOevLblgV8CueVBzmvPMg/AHUdJmuSB4BurHertI+adD5q0nlqQwfFQQ/nJVv4M1GldTaIwKE2/oDqHvp5vP0dhciEHjV2DBa92TsxXeT+QN8ybBvDtFN7Wlq2G26mbbOvpuaIM/AUPdxld3+3YlPDtce+fn556iw2N9gqcfz5pzxezXT4oOFQx2Nth9nt6x4FTh/uZ2q+xuenl1FZ2r9VWled99ICXg9+r7uTSE/GMtD/zpzIUNk7MVsNnC3IhUgD1eNB9R9ZzVmOQ6w1QGHIj27ZaIblLgT356ONPAdt5Dmp5yp6JDUFeXiwqeFa97/3Htr02sgbcyjUkhsh9zTYAj4ltcbsNqC2w2RNsjlkQ30C3YItB3S2HFB4YfcBSkJulTa3PMinxgTJD/Tf/avD76Wl2vhVd9rxaNPEQvQ1CTExJHgVBS82BUG3Tb2zgcOwbXQzORWZPHLH8eehjTwbbeTZqT+v6BF3h5FUsO3A11GDgoMa2Y8a2U/OvkPbsx0RbMWTcQInDrbyAh9Lz8hj6RnuvbSN9QnW1Gr85ZMwjXGFlrjNqztjvLozhgebswJ1nDc2n0+dXkllqdrrTQhOhu04yU2L3c87q7PASVRpQvSWhJgYkhTcTrwAXkiuGjFtO3l4pYNuWKn7a5AMtrJZaGWHFtQrRqzbNKS/Zftxg83MG53cK3JyakrSDhy7eSTgU5hTEWJORYgrxoRRCst4f8t23tvdwFpjEjoqG7RyNuyEn+90q7TZ5W7H47mj+7dKA/f8Pd2yCXNo6jHoczcvdnBkBxHRJyTEhEjyeTz4/B5yk6GmWxa6aaOZ7vSjddjtY0fNQSs7C63s0A4EihE71O6f3DPS17HP7YqM1OGL1JGz763U883ckakja/TSyRglU44ZbBWFKrNi/8k3ipqJe/NZq43nz1olf05MotYupSVu88rOGK/sjOFVYPoIt+NxTnmQ00r6t0rrOvV4MKKR2xbH7/Oget0F1+7H9G+Ntba6mefW19DQHmdkYYhrzq1g9sTStL6GGFgkxIQ4Br/Xi9/rJS9waPpRM20SppVqHjmco+agjzgTfcSZqcfcYNvV7dgaX8deFMfGF23AF20gp+bPqee7wdZZrbn32Dr5ovU4/gJCmHw2uIvPBnfhFDjsTQRYMeUnrKlN8EG9hmHDpkadTY06v1jfwbAcT+re26fGBMk7yn3DvuI47tRjwrBIGId2XPEoCqrPXXKh+hRUjwef13PKHZBrq5t56M2dqF6F/KBKS1TjoTd3chtIkA1iEmJC9EBq+tHnpQAV23HQDIu4aaMZJqZ97CZfR81hvTaOqmo/ByKVjMgL8MVPFzMr98ChBpLm7ahHBNvbqWsMC5RifXK6O5JEK46/ADzuP1/FSlBRkMvV0/O5eno+ccNmQ73mHi9Tk6A+YnEwZlO1I0bVjmSVVuZPnZc2qbh/q7ROnT9DDQvcTc1RAG9ymyzVo+BLVm09ORz0ufU1qF4ldTK2+9HkufU1EmKDmISYEKfAoyiE/D5CfgB/auoxbrih1jXSNte08/Tqvfg8kOf30hbTeeq9Rm6cO46ZU2aknqeYiWTFtj15r207avteFMcioDVD7TuHLhpvwlF8OF4VR/ESG78QT7wFO1RCSPVw/tgQ548N4TgO+9rN1E78mxqSVVqDzqYGnSfWdzA8x8vsZKCdOzpAbj9WaYdz6Nyd3yTe5fHOqs3fZTry8GBraI+TH+y+v2TA56WxPY4YvCTEhEiDrlOPpq2SMCw64gaW41D1YT0+D6ndL7rukt/1oE/HF0QfPh19+PTUY4qZQG3bTWTXWspwKze1tRoFG8UxUUx3XVnRh7+i6MNfYYaGd1mc7U5FjisqZVyRypem5xMzbDbUubuHrK1N0BCxaIpZvLQjyks7ongVmJGq0kJMLPZlpEo7XKpq6zId6R5F5ElOQypMG5VPS1RH9XpxbAcbCGsmo4tyjn1hkfUkxIRIM5/HQ17AQ8jvoyNuENEN/L7u1Y3f56Epop3wWo4viD7sDBpiBfiTGwArpobatrvbtlpqWzWKY+GLN+GrbSJU+27qGlaoNBVowZIpzBs+hc+MG4bjOOxtN1MLrTc1aJg2fNCg80GDzs/XdzAiN1mllQc5J8NV2uEsx8EyLfTkyQbnjC3h2XX7UD0eQn4vpu3gVRQuO2s0Ec09nsbnVfB6Tv2+mxh4JMSE6CNeRaE4x8+E0jza4zq66RDX3Tdc3bQZnndqx5M4vgD6sNPRh51OtPNBS8PfVo3a9RTtZLB5482E9v+V0P6/pq5hBUvQS6ZQWDqFqSWTuX7SFMLeUbzfoLM2uSXWgajFgajFiu1RVmx3q7QzRwZSoTZhgFRpndyqdmy3jaOXzBjFuGE5tHYuZsO97+ZR3DBzQ03B51GSU8ReWQqQZSTEhOhjF08fxeN/3k1xjo+8QIDmiHbSu+SfkDeAXjoNvXRag99RPgAAHPdJREFUl2DTUduqu22CrLZVo9gm3kQLobrVhOpWpy5hBUsYWzKZJSVT0M+fzG7vJN4+mMeaWo3Nje6YN9RrbKjX+Nm6dkbkelPNIeeMDpCjZr5Km1lR2G2K9mgcklWcZaF3OZ5OAUapOXglw7KKhJgQfayzM+659TU0hhOML83lwqkjGD+8j/fx9PoxSqdilE49LNg+SVVrqalI20gG2xpCdWsAGA58KliMXjyZ2JmVbHEm8Ua4gpX1eRyI2RyIWvxpe5Q/bY/i88DMsgBzk6dajy8aWFWaGLwkxIToB7Mnlh7R5h3TTdrj+nHb89PO68conYJROqVLsBmo7dVutda8HbV1B/7WahRbx5toJVS/llD9WuYD84EfBopoK69kmzKRd6IVVLVWUGMPS1Vpj73Xzsi8Q/fSRhz9MG4h0kJCTIgMyfH7CKheoppJJGEcsSNIb2yuaafqw3oORDRGJO8NHXOazatiJBdWR09zT3PHNrtUbG67v791txtsWhul2jrOZx3nA98NQMJXyCe+CaxOjOM9fQJbohP4323D+N9tUXwKnLW9iTnJ3UPGFkqVJtJHQkyIDPIqCgVBldyAj3DCIJwwen3No61Le3r1Xm5k3AnvF6V4fBgllRgllYcqNttEbd+TWpztTkXuwmPpBM12ppkfMI0P+Nvktl0dSj6brPF8aE/gw4YJ/LF+Ao+uHc6oPB9zktOOZ48KEBoA99JE9pIQE2IA8CoKRSE/IZ+X1pjebfPhk9XTdWknzePDKD4No/g0mLTEfcw2Udv3dtsEWW3dhcfSKHDCXOD5kAs8H6Yu0erksUUbz5adE3h7+wT+U5lASVlFcqPjIBUFUqWJkyMhJsQAElC9jCgI0hY3iGqnVpUdiGjk+bvvZtHTdWknzePDKJ6EUTyJ2KSL3MdsE7VjnzsF2bIDp34zedEaPFaCYiXCBd4tXMCW1CXam3PY0jSBD9+fwKuBSYRGTWPS+PGcPSZI0CdVmjg+CTEhBhiPolCS4yfk89B2Co0fI/ICtMX0VCUGvVuXdtI8PoyiiRhFE4lNvIh9+2oYWz4aX8e+7l2RLTvxWAkKlRjnez/ifD4CC6iFjpocPnLG05RzGt4RUxk18QyGjx4HioSa6E5CTIgBKuT34Ve9tMeMk5piWzJjFE+v3gumhd/nQTft9K9LO1keL2bRBMyiCcQmft59zLbwhWvcjsiWHVgHtpHTvouAHadAiTFX+RgSH8O+P8E+CJNDY3Ai1rApFJafjjN8Kmb+GAm2IU5CTIgBzKsolOT6GZbnR/V4enSvbGZFITcy7oidK3p1P6wveLyYheMxC8fDxMUARGwLX7gW68A22ms+Rm3ZwRhtN7kkyCdGfmIL1G6B2v8BQPOE0IoqUUZMTR1fYxZUSLANIRJiQmQBLzZlhUEiCZOOhHHUs8y66snOFQOSx4tZOA4Kx1FQ6QbbQdtiU80eGj/5CJq2MyqxizOUPeQrcQJ2nEDLZmjZnLqE7QuhF1dilB7aBNnMrwDPiY9zEdlHQkyILKHgHvYY9Hv///buPTaK++73+Htmdmd3fb9gY0oJLSQkhJCkjUjDA0p0DDZpwAkhpNJJiwqpRNXQAEGNlItSqUlPpNBWJCo9FKpKoerpqZJSE1FSVCAJYJ6noqjJQyCkh6RQSAo2YHy39+Y5f4x3udiAwZfZ8X5e0gp7vTZfw+5+5ved3/x+tHYmaI8NfDq+H5imxbjxExk3fiIALdFu/nCig6PHjhKr/5gJiX8y1TjKFPMoBUYnZqKT8OkDhE9fHGzx4pvSo7VY6c0KthFCISbiM0HTpCTXJhw0h3/FjwxQEDKZfWMe3DiVbuc2/t+ZODs+6+J/He+g/ewJbjOOcpt5lKnGUW4zj1FgdGAmOgmdPkDowmCzwsSLbyRW6o7W4iW3QMEtYOlt0U/0vyXiU6kVP5o74lkzKruUaRjcUmZzS5nN4q8U0NRVxt8+n8J/nejif3/eRUtXghuMBm4zjjHVPMrt5lHusI6S67RjJrsInTlI6Mz56f5OIAyjbobyW6BsMpRPhgFcsydDTyEm4mOpiR+hoEFrZ2JAF0mPBEVhi6qJOVRNzCHZ7fCPs3H+eqKQv342jrdP39Oz47bDOKOBqcZRZkT+xTT7GF+K/xM70YqR6IJT/+3eenzZtOGDVKj1/FnyZTD19pkJ9L8gMgLk2kEiQXfpqrZo4qoTP7KBZRrcWmZza5nN418t5Fxnkr997u5qve+zMbwdHc3b7ffgrqvlcGPwDKu/co6vBo7B6cPQ8DFEmzG7Y3DqgHtL//AQjLoJvlXr0W8nKQoxkRHCNAwKIzbhoEVTR5xYUsvHX6g4YlF9Yw7VN7qjtI/PuBuA/vWzLj4+HeeTeBlbk5P46r09iyA7DrSe5NTB96gwzvUE20fQ1QzJKNQfvPJfKMNCISYywoQCFuUFJi2dcVoGYUHhkcgyDaaUh5hSHkqP0o6di/M/bio6/yDDgIIv0F7xNZjgzozEcaDtFDQchtMfe1O8XEQhJjICGbijslDA5FxHnESWnyu7muKIRUnEuvru1IYB+WPc28TK4SlOrkiXtYuMYOFggPKCMLl20OtSRIaEQkxkhEvNYCzOsTG1zYmMMAoxkSyRFwpSlh/CtrRKhYwcCjGRLGJbFuUFIfJCai/KyKAQE8kyBgbFOTaluSEstRfF5zQ7UXzGANN0LzYN2GDZ7owxxwEcSCYgGXev4+lOnr9fesmxAwQsk6aOGNGErikTf1KISQbrCSwzCIEQWEE3vIJhN7iuprsbkjHojkMyjhk5A4Gw+7njKOAA2zIpyw/R1BGnLaprysR/FGLiIQMsC4yAu4mhYbpbYxhmT2DZbnhdb8vLNMEMA2EAosEiKPqi+7WkG2x0xyERd8MuGQWnuyfXsifcUu1FO2DQ3BEnqSWrxEcUYjL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Unnamed: 0Event.NrCDA.nSCRCDA.LatencyCDA.AmpSumCDA.SCRCDA.ISCRCDA.PhasicMaxCDA.TonicTTP.nSCRTTP.LatencyTTP.AmpSumGlobal.MeanGlobal.MaxDeflectionEvent.NIDEvent.Namescr_idscantrial_typemed_cond
0010.00.90160.40520.32460.32460.74021.411312.33601.301615.65690.782955KPE14644trauma11
991-1.00.6380.11620.20630.20630.74231.994312.29201.363713.67810.996755KPE14643trauma11
181810.00.6579-0.395-0.4127-0.4127-0.23150.605712.7850-0.348319.21130.079955KPE14642trauma11
272712.0-1.10472.23712.07432.07431.28061.037111.33802.204714.13522.544955KPE14641trauma11
36361-1.0NaN-0.5283-0.5194-0.5194-0.5895-0.19250NaN-0.333313.00940.000055KPE14804trauma10
454512.0-1.0119-0.3137-0.3186-0.3186-0.33562.19350NaN-0.432816.43140.004355KPE14802trauma10
545410.01.70122.64792.64942.64942.66210.85100NaNNaN7.60361.056755KPE14801trauma10
636311.01.0568-0.08470.64610.64610.57652.327511.83302.42292.84020.015255KPE13873trauma11
72721-1.0NaN-0.7928-1.0284-1.0284-0.19812.27880NaN-0.33334.58910.001955KPE13872trauma11
818110.00.48342.60382.64062.64062.63181.76340NaN-0.48494.39480.692555KPE13871trauma11
90901-1.01.05840.48920.98540.9854-0.0878-1.103413.10501.33610.05670.174355KPE13644trauma10
99991-1.01.46370.50390.40990.40990.4436-1.356113.20500.40436.82890.239955KPE13643trauma10
10810810.00.677-0.3778-0.1953-0.19530.0338-1.01720NaN-0.36499.95260.132455KPE13642trauma10
11711710.0-0.31330.63020.76260.76261.24480.128211.97700.32649.37870.250155KPE13641trauma10
12612611.00.5426-0.5826-0.5854-0.5854-0.55540.518412.2810-0.21744.23360.034955KPE13903trauma10
13513511.0-1.66182.25322.36492.36491.6086-0.89770NaN-0.63033.90651.092655KPE13902trauma10
14414411.0-0.09402.66072.65832.65832.63661.869211.86202.661615.74441.088355KPE13901trauma10
15315310.00.4695-0.4381.66061.66061.72320.75340NaN-0.540713.31850.615355KPE13394trauma11
16216212.0-0.2056-0.4125-0.4331-0.4331-0.66491.26060NaN-0.817611.51760.587255KPE13393trauma11
17117110.00.13610.96081.20421.20421.84982.069511.50401.30113.70530.305055KPE13392trauma11
18018010.00.03752.62442.63032.63032.6288-1.096911.70702.66287.91781.196655KPE13391trauma11
1891891-1.0NaN-0.8582-0.8380-0.8380-0.69470.354413.9690-0.24123.61220.001355KPE13152trauma11
19819810.0-1.7728-0.3381-0.4779-0.4779-0.43850.73480NaN-0.43814.91840.000655KPE13151trauma11
2072071-1.00.52820.3457-0.0817-0.08170.07480.35700NaN-0.471928.27220.001255KPE13434trauma11
21621610.0-0.3553-0.6013-0.6499-0.6499-0.60931.441721.73901.428.13900.026855KPE13433trauma11
22522510.0-0.4958-0.4394-0.6157-0.6157-0.7353-0.144711.43700.31187.38170.014555KPE13432trauma11
23423411.00.21872.50122.34652.34652.31351.203512.16302.509111.78310.581555KPE13431trauma11
24324312.0-0.8518-0.4893-0.5349-0.5349-0.59680.127513.4510-0.55348.17230.027155KPE12234trauma11
25225210.00.5943-0.0942-0.1871-0.1871-0.64980.747531.574-0.09189.93740.499355KPE12233trauma11
2612611-1.0-1.02651.05071.62771.62771.52771.284612.90701.72029.85390.316055KPE12232trauma11
27027011.00.5223-0.4497-0.5267-0.5267-0.38802.26630NaN-0.589616.13220.000055KPE12231trauma11
2792791NaNNaNNaN2.66232.66232.66371.98820NaNNaN4.24320.089655KPE12934trauma11
2882881NaN-1.0909-1.0868-1.0922-1.0922-0.86640.832431.909-1.07823.69050.070055KPE12933trauma11
29729710.0-0.92611.27571.07431.07430.9665-0.997031.1260.3391.97660.205355KPE12932trauma11
30630610.0-0.82482.49662.57342.57342.32030.377311.13702.55125.83750.479355KPE12931trauma11
3153151NaNNaNNaN0.61390.6139-0.43682.07940NaNNaN2.20000.001055KPE13564trauma10
32432410.01.72632.28152.30482.30481.3996-0.41360NaN-0.732114.69894.232455KPE13563trauma10
33333310.0-0.43121.30851.70211.70211.4030-1.08480NaN-0.342611.92785.683355KPE13562trauma10
34234210.01.18832.40491.91111.91111.1299-0.842611.98102.630710.43032.502455KPE13561trauma10
\n", + "
" + ], + "text/plain": [ + " Unnamed: 0 Event.Nr CDA.nSCR CDA.Latency CDA.AmpSum CDA.SCR CDA.ISCR \\\n", + "0 0 1 0.0 0.9016 0.4052 0.3246 0.3246 \n", + "9 9 1 -1.0 0.638 0.1162 0.2063 0.2063 \n", + "18 18 1 0.0 0.6579 -0.395 -0.4127 -0.4127 \n", + "27 27 1 2.0 -1.1047 2.2371 2.0743 2.0743 \n", + "36 36 1 -1.0 NaN -0.5283 -0.5194 -0.5194 \n", + "45 45 1 2.0 -1.0119 -0.3137 -0.3186 -0.3186 \n", + "54 54 1 0.0 1.7012 2.6479 2.6494 2.6494 \n", + "63 63 1 1.0 1.0568 -0.0847 0.6461 0.6461 \n", + "72 72 1 -1.0 NaN -0.7928 -1.0284 -1.0284 \n", + "81 81 1 0.0 0.4834 2.6038 2.6406 2.6406 \n", + "90 90 1 -1.0 1.0584 0.4892 0.9854 0.9854 \n", + "99 99 1 -1.0 1.4637 0.5039 0.4099 0.4099 \n", + "108 108 1 0.0 0.677 -0.3778 -0.1953 -0.1953 \n", + "117 117 1 0.0 -0.3133 0.6302 0.7626 0.7626 \n", + "126 126 1 1.0 0.5426 -0.5826 -0.5854 -0.5854 \n", + "135 135 1 1.0 -1.6618 2.2532 2.3649 2.3649 \n", + "144 144 1 1.0 -0.0940 2.6607 2.6583 2.6583 \n", + "153 153 1 0.0 0.4695 -0.438 1.6606 1.6606 \n", + "162 162 1 2.0 -0.2056 -0.4125 -0.4331 -0.4331 \n", + "171 171 1 0.0 0.1361 0.9608 1.2042 1.2042 \n", + "180 180 1 0.0 0.0375 2.6244 2.6303 2.6303 \n", + "189 189 1 -1.0 NaN -0.8582 -0.8380 -0.8380 \n", + "198 198 1 0.0 -1.7728 -0.3381 -0.4779 -0.4779 \n", + "207 207 1 -1.0 0.5282 0.3457 -0.0817 -0.0817 \n", + "216 216 1 0.0 -0.3553 -0.6013 -0.6499 -0.6499 \n", + "225 225 1 0.0 -0.4958 -0.4394 -0.6157 -0.6157 \n", + "234 234 1 1.0 0.2187 2.5012 2.3465 2.3465 \n", + "243 243 1 2.0 -0.8518 -0.4893 -0.5349 -0.5349 \n", + "252 252 1 0.0 0.5943 -0.0942 -0.1871 -0.1871 \n", + "261 261 1 -1.0 -1.0265 1.0507 1.6277 1.6277 \n", + "270 270 1 1.0 0.5223 -0.4497 -0.5267 -0.5267 \n", + "279 279 1 NaN NaN NaN 2.6623 2.6623 \n", + "288 288 1 NaN -1.0909 -1.0868 -1.0922 -1.0922 \n", + "297 297 1 0.0 -0.9261 1.2757 1.0743 1.0743 \n", + "306 306 1 0.0 -0.8248 2.4966 2.5734 2.5734 \n", + "315 315 1 NaN NaN NaN 0.6139 0.6139 \n", + "324 324 1 0.0 1.7263 2.2815 2.3048 2.3048 \n", + "333 333 1 0.0 -0.4312 1.3085 1.7021 1.7021 \n", + "342 342 1 0.0 1.1883 2.4049 1.9111 1.9111 \n", + "\n", + " CDA.PhasicMax CDA.Tonic TTP.nSCR TTP.Latency TTP.AmpSum Global.Mean \\\n", + "0 0.7402 1.4113 1 2.3360 1.3016 15.6569 \n", + "9 0.7423 1.9943 1 2.2920 1.3637 13.6781 \n", + "18 -0.2315 0.6057 1 2.7850 -0.3483 19.2113 \n", + "27 1.2806 1.0371 1 1.3380 2.2047 14.1352 \n", + "36 -0.5895 -0.1925 0 NaN -0.3333 13.0094 \n", + "45 -0.3356 2.1935 0 NaN -0.4328 16.4314 \n", + "54 2.6621 0.8510 0 NaN NaN 7.6036 \n", + "63 0.5765 2.3275 1 1.8330 2.4229 2.8402 \n", + "72 -0.1981 2.2788 0 NaN -0.3333 4.5891 \n", + "81 2.6318 1.7634 0 NaN -0.4849 4.3948 \n", + "90 -0.0878 -1.1034 1 3.1050 1.336 10.0567 \n", + "99 0.4436 -1.3561 1 3.2050 0.4043 6.8289 \n", + "108 0.0338 -1.0172 0 NaN -0.3649 9.9526 \n", + "117 1.2448 0.1282 1 1.9770 0.3264 9.3787 \n", + "126 -0.5554 0.5184 1 2.2810 -0.2174 4.2336 \n", + "135 1.6086 -0.8977 0 NaN -0.6303 3.9065 \n", + "144 2.6366 1.8692 1 1.8620 2.6616 15.7444 \n", + "153 1.7232 0.7534 0 NaN -0.5407 13.3185 \n", + "162 -0.6649 1.2606 0 NaN -0.8176 11.5176 \n", + "171 1.8498 2.0695 1 1.5040 1.3011 3.7053 \n", + "180 2.6288 -1.0969 1 1.7070 2.6628 7.9178 \n", + "189 -0.6947 0.3544 1 3.9690 -0.2412 3.6122 \n", + "198 -0.4385 0.7348 0 NaN -0.4381 4.9184 \n", + "207 0.0748 0.3570 0 NaN -0.4719 28.2722 \n", + "216 -0.6093 1.4417 2 1.7390 1.42 8.1390 \n", + "225 -0.7353 -0.1447 1 1.4370 0.3118 7.3817 \n", + "234 2.3135 1.2035 1 2.1630 2.5091 11.7831 \n", + "243 -0.5968 0.1275 1 3.4510 -0.5534 8.1723 \n", + "252 -0.6498 0.7475 3 1.574 -0.0918 9.9374 \n", + "261 1.5277 1.2846 1 2.9070 1.7202 9.8539 \n", + "270 -0.3880 2.2663 0 NaN -0.5896 16.1322 \n", + "279 2.6637 1.9882 0 NaN NaN 4.2432 \n", + "288 -0.8664 0.8324 3 1.909 -1.0782 3.6905 \n", + "297 0.9665 -0.9970 3 1.126 0.339 1.9766 \n", + "306 2.3203 0.3773 1 1.1370 2.5512 5.8375 \n", + "315 -0.4368 2.0794 0 NaN NaN 2.2000 \n", + "324 1.3996 -0.4136 0 NaN -0.7321 14.6989 \n", + "333 1.4030 -1.0848 0 NaN -0.3426 11.9278 \n", + "342 1.1299 -0.8426 1 1.9810 2.6307 10.4303 \n", + "\n", + " Global.MaxDeflection Event.NID Event.Name scr_id scan trial_type \\\n", + "0 0.7829 5 5 KPE1464 4 trauma1 \n", + "9 0.9967 5 5 KPE1464 3 trauma1 \n", + "18 0.0799 5 5 KPE1464 2 trauma1 \n", + "27 2.5449 5 5 KPE1464 1 trauma1 \n", + "36 0.0000 5 5 KPE1480 4 trauma1 \n", + "45 0.0043 5 5 KPE1480 2 trauma1 \n", + "54 1.0567 5 5 KPE1480 1 trauma1 \n", + "63 0.0152 5 5 KPE1387 3 trauma1 \n", + "72 0.0019 5 5 KPE1387 2 trauma1 \n", + "81 0.6925 5 5 KPE1387 1 trauma1 \n", + "90 0.1743 5 5 KPE1364 4 trauma1 \n", + "99 0.2399 5 5 KPE1364 3 trauma1 \n", + "108 0.1324 5 5 KPE1364 2 trauma1 \n", + "117 0.2501 5 5 KPE1364 1 trauma1 \n", + "126 0.0349 5 5 KPE1390 3 trauma1 \n", + "135 1.0926 5 5 KPE1390 2 trauma1 \n", + "144 1.0883 5 5 KPE1390 1 trauma1 \n", + "153 0.6153 5 5 KPE1339 4 trauma1 \n", + "162 0.5872 5 5 KPE1339 3 trauma1 \n", + "171 0.3050 5 5 KPE1339 2 trauma1 \n", + "180 1.1966 5 5 KPE1339 1 trauma1 \n", + "189 0.0013 5 5 KPE1315 2 trauma1 \n", + "198 0.0006 5 5 KPE1315 1 trauma1 \n", + "207 0.0012 5 5 KPE1343 4 trauma1 \n", + "216 0.0268 5 5 KPE1343 3 trauma1 \n", + "225 0.0145 5 5 KPE1343 2 trauma1 \n", + "234 0.5815 5 5 KPE1343 1 trauma1 \n", + "243 0.0271 5 5 KPE1223 4 trauma1 \n", + "252 0.4993 5 5 KPE1223 3 trauma1 \n", + "261 0.3160 5 5 KPE1223 2 trauma1 \n", + "270 0.0000 5 5 KPE1223 1 trauma1 \n", + "279 0.0896 5 5 KPE1293 4 trauma1 \n", + "288 0.0700 5 5 KPE1293 3 trauma1 \n", + "297 0.2053 5 5 KPE1293 2 trauma1 \n", + "306 0.4793 5 5 KPE1293 1 trauma1 \n", + "315 0.0010 5 5 KPE1356 4 trauma1 \n", + "324 4.2324 5 5 KPE1356 3 trauma1 \n", + "333 5.6833 5 5 KPE1356 2 trauma1 \n", + "342 2.5024 5 5 KPE1356 1 trauma1 \n", + "\n", + " med_cond \n", + "0 1 \n", + "9 1 \n", + "18 1 \n", + "27 1 \n", + "36 0 \n", + "45 0 \n", + "54 0 \n", + "63 1 \n", + "72 1 \n", + "81 1 \n", + "90 0 \n", + "99 0 \n", + "108 0 \n", + "117 0 \n", + "126 0 \n", + "135 0 \n", + "144 0 \n", + "153 1 \n", + "162 1 \n", + "171 1 \n", + "180 1 \n", + "189 1 \n", + "198 1 \n", + "207 1 \n", + "216 1 \n", + "225 1 \n", + "234 1 \n", + "243 1 \n", + "252 1 \n", + "261 1 \n", + "270 1 \n", + "279 1 \n", + "288 1 \n", + "297 1 \n", + "306 1 \n", + "315 0 \n", + "324 0 \n", + "333 0 \n", + "342 0 " + ] + }, + "execution_count": 479, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "## Loading GSR data\n", + "dfGSR = pd.read_csv('/home/or/kpe_task_analysis/testing.csv')\n", + "\n", + "# add KPE at the beginning of each scr id\n", + "dfGSR['scr_id'] = \"KPE\" + dfGSR[\"scr_id\"].map(str) \n", + "# pclDat[((pclDat['redcap_event_name'] == 'screening_selfrepo_arm_1'\n", + "dfGSR_trauma1 = dfGSR[(dfGSR[\"trial_type\"]=='trauma1')]\n", + "dfGSR_trauma1" + ] + }, + { + "cell_type": "code", + "execution_count": 480, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MultiIndex([('CDA.PhasicMax', 1),\n", + " ('CDA.PhasicMax', 2),\n", + " ('CDA.PhasicMax', 3),\n", + " ('CDA.PhasicMax', 4),\n", + " ( 'med_cond', 1),\n", + " ( 'med_cond', 2),\n", + " ( 'med_cond', 3),\n", + " ( 'med_cond', 4),\n", + " ( '3rd_1st', ''),\n", + " ( 'begin_endPE', '')],\n", + " names=[None, 'scan'])\n" + ] + } + ], + "source": [ + "# make it wide\n", + "dfGSR_wide = dfGSR_trauma1.pivot(index='scr_id', columns='scan', values=['CDA.PhasicMax', 'med_cond'])\n", + "dfGSR_wide['3rd_1st'] = dfGSR_wide['CDA.PhasicMax', 3] - dfGSR_wide['CDA.PhasicMax', 1]\n", + "dfGSR_wide['begin_endPE'] = dfGSR_wide['CDA.PhasicMax', 2] - dfGSR_wide['CDA.PhasicMax', 1]\n", + "print(dfGSR_wide.columns)\n", + "gsronly = dfGSR_wide[['3rd_1st','begin_endPE' ,'med_cond']]" + ] + }, + { + "cell_type": "code", + "execution_count": 481, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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CDA.PhasicMaxmed_cond3rd_1stbegin_endPE
scan12341234
scr_id
KPE1223-0.38801.5277-0.6498-0.59681.01.01.01.0-0.26181.9157
KPE12932.32030.9665-0.86642.66371.01.01.01.0-3.1867-1.3538
KPE1315-0.4385-0.6947NaNNaN1.01.0NaNNaNNaN-0.2562
KPE13392.62881.8498-0.66491.72321.01.01.01.0-3.2937-0.7790
KPE13432.3135-0.7353-0.60930.07481.01.01.01.0-2.9228-3.0488
KPE13561.12991.40301.3996-0.43680.00.00.00.00.26970.2731
KPE13641.24480.03380.4436-0.08780.00.00.00.0-0.8012-1.2110
KPE13872.6318-0.19810.5765NaN1.01.01.0NaN-2.0553-2.8299
KPE13902.63661.6086-0.5554NaN0.00.00.0NaN-3.1920-1.0280
KPE14641.2806-0.23150.74230.74021.01.01.01.0-0.5383-1.5121
KPE14802.6621-0.3356NaN-0.58950.00.0NaN0.0NaN-2.9977
\n", + "
" + ], + "text/plain": [ + " CDA.PhasicMax med_cond 3rd_1st \\\n", + "scan 1 2 3 4 1 2 3 4 \n", + "scr_id \n", + "KPE1223 -0.3880 1.5277 -0.6498 -0.5968 1.0 1.0 1.0 1.0 -0.2618 \n", + "KPE1293 2.3203 0.9665 -0.8664 2.6637 1.0 1.0 1.0 1.0 -3.1867 \n", + "KPE1315 -0.4385 -0.6947 NaN NaN 1.0 1.0 NaN NaN NaN \n", + "KPE1339 2.6288 1.8498 -0.6649 1.7232 1.0 1.0 1.0 1.0 -3.2937 \n", + "KPE1343 2.3135 -0.7353 -0.6093 0.0748 1.0 1.0 1.0 1.0 -2.9228 \n", + "KPE1356 1.1299 1.4030 1.3996 -0.4368 0.0 0.0 0.0 0.0 0.2697 \n", + "KPE1364 1.2448 0.0338 0.4436 -0.0878 0.0 0.0 0.0 0.0 -0.8012 \n", + "KPE1387 2.6318 -0.1981 0.5765 NaN 1.0 1.0 1.0 NaN -2.0553 \n", + "KPE1390 2.6366 1.6086 -0.5554 NaN 0.0 0.0 0.0 NaN -3.1920 \n", + "KPE1464 1.2806 -0.2315 0.7423 0.7402 1.0 1.0 1.0 1.0 -0.5383 \n", + "KPE1480 2.6621 -0.3356 NaN -0.5895 0.0 0.0 NaN 0.0 NaN \n", + "\n", + " begin_endPE \n", + "scan \n", + "scr_id \n", + "KPE1223 1.9157 \n", + "KPE1293 -1.3538 \n", + "KPE1315 -0.2562 \n", + "KPE1339 -0.7790 \n", + "KPE1343 -3.0488 \n", + "KPE1356 0.2731 \n", + "KPE1364 -1.2110 \n", + "KPE1387 -2.8299 \n", + "KPE1390 -1.0280 \n", + "KPE1464 -1.5121 \n", + "KPE1480 -2.9977 " + ] + }, + "execution_count": 481, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dfGSR_wide" + ] + }, + { + "cell_type": "code", + "execution_count": 482, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/reshape/merge.py:618: UserWarning: merging between different levels can give an unintended result (2 levels on the left, 1 on the right)\n", + " warnings.warn(msg, UserWarning)\n" + ] + }, + { + "data": { + "text/plain": [ + "Index([ 'scr_id', 'three_one', 'begin_endPE',\n", + " 'med_cond', ('med_cond', 2), ('med_cond', 3),\n", + " ('med_cond', 4), 'group', 'corr_amgHipp2',\n", + " 'corr_amgVmpfc2', 'corr_hippVmpfc2', 'corr_amgHipp1',\n", + " 'corr_amgVmpfc1', 'corr_hippVmpfc1', 'hippAmgDelta',\n", + " 'amgVmpfcDelta', 'hippVmpfcDelta'],\n", + " dtype='object')" + ] + }, + "execution_count": 482, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "gsrMerged = gsronly.merge(dfBoth, left_on='scr_id', right_on='scr_id', how='outer')\n", + "# drop NAs\n", + "#gsrMerged = gsrMerged.dropna(subset=[('3rd_1st', '')])\n", + "# change wierd column name\n", + "gsrMerged=gsrMerged.rename(columns = {('3rd_1st', ''):'three_one'})\n", + "gsrMerged=gsrMerged.rename(columns = {('med_cond' ,1): 'med_cond'})\n", + "gsrMerged=gsrMerged.rename(columns = {('begin_endPE', ''): 'begin_endPE'})\n", + "gsrMerged.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 484, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(0.2845731067763817, 0.45798341866666903)" + ] + }, + "execution_count": 484, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "gsrMerged\n", + "sns.lmplot(x='three_one', y='amgVmpfcDelta', data=gsrMerged)\n", + "naMask = np.isnan(gsrMerged['three_one'])\n", + "scipy.stats.pearsonr(gsrMerged['three_one'][~naMask], gsrMerged['amgVmpfcDelta'][~naMask])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Lets load the AAL atlas and look only on the right amygdala-hippocampus" + ] + }, + { + "cell_type": "code", + "execution_count": 493, + "metadata": {}, + "outputs": [], + "source": [ + "first = np.load('/home/or/kpe_task_analysis/trauma_ses1.npy')\n", + "second = np.load('/home/or/kpe_task_analysis/trauma_ses2.npy')\n", + "\n", + "deltaMatrix_each = np.array(second) - np.array(first)\n", + "deltaMat_zfisher = []\n", + "for mat2, mat1 in zip(second, first):\n", + " mat1z = np.arctanh(mat1)\n", + " mat2z = np.arctanh(mat2)\n", + " deltaMat = mat2z - mat1z\n", + " deltaMat_zfisher.append(deltaMat)\n", + "\n", + "deltaMatz = np.array(deltaMat_zfisher)\n", + "\n", + "#first = \n", + "#second = np.load('/home/or/kpe_task_analysis/trauma_ses2.npy') # load second session 21 subjects using AAL atlas" + ] + }, + { + "cell_type": "code", + "execution_count": 494, + "metadata": {}, + "outputs": [], + "source": [ + "left_amg_hippo = deltaMatz[36,40,:]\n", + "\n", + "gsrMerged['left_amgHippo'] = left_amg_hippo" + ] + }, + { + "cell_type": "code", + "execution_count": 495, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(-0.40536030243234233, 0.2790884151578712)" + ] + }, + "execution_count": 495, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.lmplot(x='left_amgHippo', y='three_one',hue='group', data=gsrMerged)\n", + "scipy.stats.pearsonr(gsrMerged['three_one'][~naMask], gsrMerged['left_amgHippo'][~naMask])" + ] + }, + { + "cell_type": "code", + "execution_count": 501, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(0.6587333583234611, 0.007571957688924434)" + ] + }, + "execution_count": 501, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dfTest['left_amgHippo'] = left_amg_hippo\n", + "sns.lmplot(x='left_amgHippo', y='days7_1', data=dfTest)\n", + "\n", + "maskNan = np.isnan(dfTest['days7_1'])\n", + "\n", + "scipy.stats.pearsonr(dfTest.left_amgHippo[~maskNan], dfTest.days7_1[~maskNan])" + ] + }, + { + "cell_type": "code", + "execution_count": 502, + "metadata": {}, + "outputs": [], + "source": [ + "# lets scale it and run bayesian to make inference better\n", + "dfTest['left_hipAmg_Z'] = (dfTest.left_amgHippo - dfTest.left_amgHippo.mean()) / dfTest.left_amgHippo.std(ddof=0)\n", + "dfTest['Days7_1Z'] = (dfTest.days7_1 - dfTest.days7_1.mean()) / dfTest.days7_1.std(ddof=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 212, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (4 chains in 4 jobs)\n", + "NUTS: [sd, left_hipAmg_Z, Intercept]\n", + "Sampling 4 chains, 0 divergences: 100%|██████████| 40000/40000 [00:05<00:00, 6753.17draws/s]\n" + ] + } + ], + "source": [ + "# run pymc3 GLM\n", + "# play with glm module of pymc3\n", + "import pymc3 as pm\n", + "from pymc3.glm import GLM\n", + "\n", + "with pm.Model() as model_glm:\n", + " GLM.from_formula('Days7_1Z ~ left_hipAmg_Z', data= dfTest, \n", + " # priors= {'Intercept': pm.Normal.dist(mu=0, sd=2),\n", + " # 'left_hipAmg_Z': pm.Normal.dist(mu=0, sd=2),\n", + " # }\n", + " )\n", + " trace = pm.sample(draws=5000, tune=5000)" + ] + }, + { + "cell_type": "code", + "execution_count": 213, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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meansdhpd_5%hpd_95%mcse_meanmcse_sdess_meaness_sdess_bulkess_tailr_hat
Intercept0.0420.244-0.3540.4390.0020.00217211.07825.017703.012051.01.0
left_hipAmg_Z0.6710.2430.2791.0690.0020.00117035.015917.017614.012540.01.0
sd0.8970.2060.5891.1910.0020.00111779.011316.012123.09485.01.0
\n", + "
" + ], + "text/plain": [ + " mean sd hpd_5% hpd_95% mcse_mean mcse_sd ess_mean \\\n", + "Intercept 0.042 0.244 -0.354 0.439 0.002 0.002 17211.0 \n", + "left_hipAmg_Z 0.671 0.243 0.279 1.069 0.002 0.001 17035.0 \n", + "sd 0.897 0.206 0.589 1.191 0.002 0.001 11779.0 \n", + "\n", + " ess_sd ess_bulk ess_tail r_hat \n", + "Intercept 7825.0 17703.0 12051.0 1.0 \n", + "left_hipAmg_Z 15917.0 17614.0 12540.0 1.0 \n", + "sd 11316.0 12123.0 9485.0 1.0 " + ] + }, + "execution_count": 213, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pm.summary(trace, credible_interval=.9)" + ] + }, + { + "cell_type": "code", + "execution_count": 188, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(200,)" + ] + }, + "execution_count": 188, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "trace['Intercept'][-200:].shape" + ] + }, + { + "cell_type": "code", + "execution_count": 216, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 216, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "t=trace\n", + "x = dfTest['left_hipAmg_Z']\n", + "y = dfTest['Days7_1Z']\n", + "sns.scatterplot(x='left_hipAmg_Z', y='Days7_1Z', data=dfTest, label='data')\n", + "for a_, b_ in zip(t['Intercept'][-300:], t['left_hipAmg_Z'][-300:]):\n", + " plt.plot(x, a_*x + b_, c='gray', alpha=0.1)\n", + "#plt.plot(x, a*x + _b, label='true regression line', lw=3., c='red')\n", + "plt.legend(loc='best')" + ] + }, + { + "cell_type": "code", + "execution_count": 503, + "metadata": {}, + "outputs": [], + "source": [ + "def pearsonr_ci(x,y,alpha=0.05):\n", + " from scipy import stats\n", + " ''' calculate Pearson correlation along with the confidence interval using scipy and numpy\n", + " Parameters\n", + " ----------\n", + " x, y : iterable object such as a list or np.array\n", + " Input for correlation calculation\n", + " alpha : float\n", + " Significance level. 0.05 by default\n", + " Returns\n", + " -------\n", + " r : float\n", + " Pearson's correlation coefficient\n", + " pval : float\n", + " The corresponding p value\n", + " lo, hi : float\n", + " The lower and upper bound of confidence intervals\n", + " '''\n", + "\n", + " r, p = stats.pearsonr(x,y)\n", + " r_z = np.arctanh(r)\n", + " se = 1/np.sqrt(x.size-3)\n", + " z = stats.norm.ppf(1-alpha/2)\n", + " lo_z, hi_z = r_z-z*se, r_z+z*se\n", + " lo, hi = np.tanh((lo_z, hi_z))\n", + " return r, p, lo, hi" + ] + }, + { + "cell_type": "code", + "execution_count": 505, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(0.6587333583234611,\n", + " 0.007571957688924434,\n", + " 0.22106909036290767,\n", + " 0.8755474295202351)" + ] + }, + "execution_count": 505, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pearsonr_ci(dfTest.left_amgHippo[~maskNan], dfTest.days7_1[~maskNan])" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/.ipynb_checkpoints/ROI_timecourse-Alternative_scripts-checkpoint.ipynb b/task_based_analysis/.ipynb_checkpoints/ROI_timecourse-Alternative_scripts-checkpoint.ipynb new file mode 100644 index 0000000..72ffc8b --- /dev/null +++ b/task_based_analysis/.ipynb_checkpoints/ROI_timecourse-Alternative_scripts-checkpoint.ipynb @@ -0,0 +1,5025 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Time course based ROI analysis\n", + "In this notebook we will take ROI timecourse in the first 30sec of the trauma script and compare different groups and sessions" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/sklearn/externals/joblib/__init__.py:15: DeprecationWarning: sklearn.externals.joblib is deprecated in 0.21 and will be removed in 0.23. Please import this functionality directly from joblib, which can be installed with: pip install joblib. If this warning is raised when loading pickled models, you may need to re-serialize those models with scikit-learn 0.21+.\n", + " warnings.warn(msg, category=DeprecationWarning)\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import nilearn\n", + "from nilearn import plotting\n", + "import glob\n", + "import os\n", + "from nilearn.input_data import NiftiMasker\n", + "import matplotlib.pyplot as plt\n", + "from connUtils import removeVars, timeSeriesSingle\n", + "import scipy\n", + "work_dir = '/media/Data/work/KPE_ROI/timecourse'" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# put functional file, confound file and event file here - this is for one subject\n", + "func_file = '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz'\n", + "confound_file = '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_desc-confounds_regressors.tsv'\n", + "events_file = '/media/Data/KPE_BIDS/condition_files/withNumbers/sub-{sub}_ses-{ses}_30sec_window.csv'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Amygdala" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=19\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# here I use a masked image so all will have same size - create a function that does that\n", + "def generate_timeSeries(sub, ses, mask_file): \n", + " nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4, standardize=True, t_r=1,high_pass = .01,\n", + " verbose=5) # cache options\n", + " fmri_masked_ses = nifti_masker.fit_transform(func_file.format(sub=sub, ses=ses), confound_file.format(sub=sub, ses=ses))\n", + " # memory= os.path.join(work_dir,'nilearn_cache_alternative'), memory_level=0,\n", + " return fmri_masked_ses\n", + "\n", + "def plot_series(time1, time2):\n", + " # recieves two time series and returns a graph of the two with std's\n", + " time1_mean = np.mean(time1, axis=0)\n", + " time1_std = np.std(time1, axis=0)\n", + " smooth_path = time1_mean\n", + " under_line = (smooth_path - time1_std)\n", + " over_line = (smooth_path + time1_std)\n", + " time2_mean = np.mean(time2, axis=0)\n", + " time2_std = np.std(time2, axis=0)\n", + " smooth_path2 = time2_mean\n", + " under_line2 = (smooth_path2 - time2_std)\n", + " over_line2 = (smooth_path2 + time2_std)\n", + " plt.figure(figsize = [10,5])\n", + " plt.plot(time1_mean, \"blue\")\n", + " plt.fill_between(range(120), under_line, over_line, color='b', alpha=.1)\n", + " plt.plot(time2_mean, \"red\")\n", + " plt.fill_between(range(120), under_line2, over_line2, color='r', alpha=.1)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "KPE008\n", + "KPE1223\n", + "KPE1293\n", + "KPE1307\n", + "KPE1315\n", + "KPE1322\n", + "KPE1339\n", + "KPE1343\n", + "KPE1387\n", + "KPE1464\n", + "KPE1499\n", + "KPE1253\n", + "KPE1263\n", + "KPE1351\n", + "KPE1356\n", + "KPE1364\n", + "KPE1369\n", + "KPE1390\n", + "KPE1403\n", + "KPE1468\n", + "KPE1480\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "\n", + "ketamine_list = list(medication_cond['scr_id'][medication_cond['med_cond']==1])\n", + "ket_list = []\n", + "for subject in ketamine_list:\n", + " print(subject)\n", + " sub = subject.split('KPE')[1]\n", + " ket_list.append(sub)\n", + "\n", + "\n", + "midazolam_list = list(medication_cond['scr_id'][medication_cond['med_cond']==0])\n", + "mid_list = []\n", + "for subject in midazolam_list:\n", + " print(subject)\n", + " sub = subject.split('KPE')[1]\n", + " mid_list.append(sub)\n", + "mid_list.remove('1480')" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-008/ses-1/func/sub-008_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1223/ses-1/func/sub-1223_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. 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Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1464/ses-1/func/sub-1464_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1499/ses-1/func/sub-1499_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_amg_sad', ket_func1)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-008/ses-2/func/sub-008_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. 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Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1364/ses-1/func/sub-1364_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1369/ses-1/func/sub-1369_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1390/ses-1/func/sub-1390_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1403/ses-1/func/sub-1403_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1468/ses-1/func/sub-1468_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_amg_sad', mid_func1)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1253/ses-2/func/sub-1253_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1263/ses-2/func/sub-1263_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1351/ses-2/func/sub-1351_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1356/ses-2/func/sub-1356_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1364/ses-2/func/sub-1364_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1369/ses-2/func/sub-1369_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1390/ses-2/func/sub-1390_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1403/ses-2/func/sub-1403_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1468/ses-2/func/sub-1468_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_amg_sad', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_series(ket_func1, ket_func2)\n", + "plot_series(mid_func1, mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.03701083835421825" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Calculate correlation between first and seond session in this timecourse. \n", + "cor_mid = []\n", + "for i in range(len(mid_func1)):\n", + " cor = scipy.stats.pearsonr(mid_func1[i], mid_func2[i])#, rowvar=False)\n", + " cor_mid.append(cor)\n", + "np.mean(np.array(cor_mid)[:,0])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# removing one subject that has problems in data in session 2 (1351)\n", + "np.array(mid_func2).shape\n", + "del mid_func2[2]\n", + "del mid_func1[2]\n", + "\n", + "##\n", + "del mid_func1[4]\n", + "del mid_func2[4]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## generating boxplot to show the activation around the peak (3-15 sec)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "105\n", + "27\n", + "14\n", + "51\n", + "12\n", + "95\n", + "104\n", + "43\n", + "7\n", + "104\n", + "72\n", + "31\n", + "20\n", + "118\n", + "115\n", + "114\n", + "55\n", + "0\n", + "78\n", + "49\n", + "5\n", + "53\n" + ] + } + ], + "source": [ + "# before that, lets see where are the global maximums of each subject (location = second in the script)\n", + "ket1=[]\n", + "for mat in ket_func1:\n", + " print(np.argmax(mat))\n", + " ket1.append(np.argmax(mat))\n", + "ket2 = []\n", + "for mat in ket_func2:\n", + " print(np.argmax(mat))\n", + " ket2.append(np.argmax(mat))" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "11\n", + "6\n", + "22\n", + "28\n", + "1\n", + "103\n", + "21\n", + "47\n", + "56\n" + ] + } + ], + "source": [ + "mid1 = []\n", + "for mat in mid_func1:\n", + " \n", + " mid1.append(np.argmax(mat))\n", + "mid2 = []\n", + "for mat in mid_func2:\n", + " print(np.argmax(mat))\n", + " mid2.append(np.argmax(mat))" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# lets plot the locations of maximums for subject\n", + "plt.figure(figsize = [10,5])\n", + "plt.scatter(ket_list + mid_list,ket1 + mid1, color = \"blue\", alpha = 0.6)\n", + "plt.scatter(ket_list + mid_list , ket2 + mid2 , color = \"red\", alpha = 0.3)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'whiskers': [,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ],\n", + " 'caps': [,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ],\n", + " 'boxes': [,\n", + " ,\n", + " ,\n", + " ],\n", + " 'medians': [,\n", + " ,\n", + " ,\n", + " ],\n", + " 'fliers': [,\n", + " ,\n", + " ,\n", + " ],\n", + " 'means': []}" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# boxplot on the first part of script\n", + "#ket1_mean = np.mean(ket_func1, axis=0)\n", + "mid1_mean = np.mean(mid_func1[5:20], axis=1)\n", + "mid2_mean = np.mean(mid_func2[5:20], axis=1)\n", + "ket1_mean = np.mean(ket_func1[5:20], axis=1)\n", + "ket2_mean = np.mean(ket_func2[5:20], axis=1)\n", + "plt.figure(figsize = [10,5])\n", + "plt.boxplot([ket1_mean, ket2_mean, mid1_mean, mid2_mean])\n", + "#plt.boxplot([ket1_mean[0:15], ket2_mean[0:15]])" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "# now lets built it around individual global maximum\n", + "def maxVec(funcArr):\n", + " vec = []\n", + " for mat in funcArr:\n", + " vec.append(np.argmax(mat))\n", + " maxi = []\n", + " for i, x in enumerate(vec):\n", + " maxi.append(funcArr[i][x])\n", + " return maxi" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "ket1_max = maxVec(ket_func1)\n", + "ket2_max = maxVec(ket_func2)\n", + "mid1_max = maxVec(mid_func1)\n", + "mid2_max = maxVec(mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[0.48530178854124845,\n", + " 0.9579921965558685,\n", + " 0.6502333562978941,\n", + " 0.6860335774339564,\n", + " 0.9817369767251184,\n", + " 0.3701222630514509,\n", + " 0.61746369714301,\n", + " 0.6350203046007926,\n", + " 0.5663094551094203]" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mid1_max" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " T test for ketamine group diff Ttest_relResult(statistic=-2.079497697701076, pvalue=0.06425194015449509)\n", + "T test for midazolam group Ttest_relResult(statistic=1.3897800238420321, pvalue=0.20204691887761733)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize = [10,5])\n", + "labels = ['','Ket_ses1', 'Ket_ses2', 'Mid_ses1', 'Mid_ses2']\n", + "x_pos = np.arange(len(labels))\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "plt.xticks(x_pos, labels)\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Hippocampus" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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OaEGy6lhfPmnOXTJo+9h8f0aMmxYdWpvcVyrgRXEd9lXbujF16lSt66CvtGSWEXs0O/ScoUUk8lF7Qc7r5+vu5zSfR0y58pz1PcM5X+7PucTPiDlzP94fHgNm43A8aUWg9r7b89hFapDRb0OB9EknEolEItGlSFWRRCKR6BKYEZItS+3KhWTIZtC2jJjpsqaAEVX0s+WDViOCEdHM6a/TdWiyjDYhskQxZijSs7D16OWXX649LuN2yMDL82Lc1FBhSF7SDgix3nNUbaUE04UYQNFUiMCI0peaTMNR1ZWoDqnPqTR30/QZmUSjYxrsIwMxopQIgxOfNzNTsuqkJL2NSzUuXLhQknTwwQfX9rkbYTOqVM1Fm3Spg0yRED/AGIzjMYxKTro9BlVFuscM6nF7UZBf6Tqpc2+UcyGa49Ru9ifvOYP3EoPdmMYWBVfyHFju0wVgHLyXKVqJRDLpRCKR6BrYTzx27FhJrVHFXAyxzreZdBSlzzgb+qINLhSNTgkQ/cclmDFAn3NTTEcUrxNJmlJ3nuSLFgtqBzCCXqoW8CeddFLb+Q0FBvUlfemll0pqL4ZBkwELUEjV4HlVb8d+08WJUl24em+S1ozSlhhAwBujNKdEpSl5k0TBEUZTIFmTNYBlE23a8cR1ChwnYtmmb3TD53L11VdLko466ih1K8ygS7EcM+Wo+g2lLynUQGbt+clKQmyPohRN1hAfl2Y9IgoSLOdj9MBjwI/PkUya6Sy00ETFRthHBhrRChWVif36178uSTrllFNqzzWRWBeQTDqRSCS6BMcdd5wk6eabb5ZUrwZIguLFFpk06w3QzeWFIwlR5Kc1mohOp9uXf4uYNP8eEZOIZEU534zyJvky6DIs9xkuDMpL2ukt9l8ygMCpFkxRKhmcJ5Qnjj8pbkJmzKAHMpomf3jESMgamj7LPjS13VRAI5L/ZLvcj5YKj7uDUVwO1AyzThCmFJgp4T64Det5f/KTn6zdfiRgS87o0aMltVoDaOaKynpGcQT0v9os6U8++CKhB/pz6aelxCIDWMr+urDGypUr28x55f9tBWCBjciKEInoRPWGmd4YCQhRdpL+fVs73F+3P1yiEYlENyKZdCKRSHQZnn/+eUkVS5baF/1eXHkx6sU3iUmkBOftyS7prjT8d5ILoq8aBJH7MiIe9GuTKdN1Ql80F4YRIWKuOUldWW7TC/PhwoBe0nPnzpUk7bzzzpKq0H8zuRdeeEFS5RPlxS99WCwR6InH0n70a9EPxshRSmIanGC8GD4ev3uV73MqTR/2V/o86QPkZ1/Sf3XnFN0UrNHqPjlK1gxl8803b+lfHfuKbkwfgyIg3YALL7xQUsXyHcldSvvx+hFRKVPe3HygeYx9k7OAAH3ftCZxLtAnTv+w9y/nRDkvyrkUPWzJ4mkWbZqXtAYYUX3hqHgIg358zp6nVib08f7pn/5JkvTUU09JkmbMmFHbv0RibUIy6UQikegysCa31O428IKNFZtILKjC5UUd3V7enoqQXkx5Acp69UYUsV0iYuFcGHIBR9cfq1XRXcpFMheWEcnweNNFVDJpp2MOFwb0kt5mm20kVSteFon3QJtt+LNO4pCrbUrNccLRL0b/mL9HgQX0afsimBHR/OF++OYxky6Z2XPPPddyLJ8Lc7+ZW0v5PZ5jFO3tvrtvNsOYSft4ZiY8bl0wBi0PzNf1p9vuBklHp6tQ4rOcX7zZbBmISuNFxU44T/3d88CfjI5nO5y3UcALH4RNVpXyd0ZtU2SiyYcc5Tlzf/rLydTp846iwyPfuM/JsQa2lDiv+thjj60di0RibUAy6UQikehSlAyOrg5/0iVFhbGo4hSjw1m9z4sjt0uVLvq0m6K++wIXZNQRp9uJY+E+e7uI/XMBaOZNMmeSVlfvoJPKdIOJ1XpJO7L3He94h6R2E4NPzBffk4JstGQJXH27LU8ETxCu4un3agrRJxt1X31R3DezURZa8EQeM2aMpNYgAk8c+j+pbsWCGUyNiIqIcCIzPcDjbEZpNuexJCtmu+U2tCB4PMgUfc6OTxjOalnXXnutpIpJs+xk+XDw/HC/m5i0EcUy8KFAnzQLY3D/SAEvsp7UnVPEpg33jQ9T9y1irJHinbfnPRWVGTSikq28Z6OCNJzv3M+MWkpWnVj7kEw6kUgkugxeuHvxJ8XBsvSfMuiVC0Z/t/vR7koGMRpuj9K4Ub1wkoZyoctj0CXibU0OqKbGBSNJl/czqSstEeVxvKCn1YDfSeKkOE11qLBaL+m3v/3tktoZNPOf/Z0l8Pz38sTpP2NQBAMA6NOLyuEZEcP2BDeD9kT0xY2iyetMOGawvBk8ccjaqPfMvOVImYzmLk88CuuTOUWayyUizWrf0DxXt+kc+eGA/eATJkyQVN3ANP/VsU7Os6ZSpBHDrlOck6rx8/xhHEBUMpX9bNJ1b/qt/J2CDhwf+p4jFk9EJTBpEeJDnw9a9ieyLlBd0NfdvmqpO/P3E4mBIJl0IpFIdAnswnGwZ+lCsGvNhIIkiUyaVZoo6EORKbfHRRHFqdy+F/JedDHo1i6ykoz5vMjC3Qcvck0KmP8cuYncN6f9eqxoRYjSDw1v777XMXK3cc4550ga+kIwq/WSNmPrVHGI+ZdkdlI7g2OEri8iV+tNOcZR0rwnvy+GJ6wvBhm9P3kRy+P74tE37fMma/fv3o5i8Ow7GTjHhupsLOfGxH+aiMq+mUH7022ychLHc86cOZKkWbNmaahgHzQrTvVlPWHkPNW2yBY5rxjIEqluMWc9yoOmWc1gPEInuu3lNuX/+UCLHkxEpA0fbccx8FyI1AD5EqDPOVKFi8oTlvB9e+6550qSZs6c2ec5JBLdjmTSiUQiMULwYmLixImSKlciXTdSxS6feeYZSdLSpUslVYtVRmkzWptgQZNogejFf1QoiVHlJjDuZ3kOJngGF60mBWbfrFbF4EWm0Eaky2AKJBfjJiw+vo9nC0AJk6OhRr9e0lZ22m233SS1R19GJdCi7cqVcKTFHUW3ss1IPq4p/J8TlKYf+159UW1OqWuXqlBUPfMn0wK4fyQmb0QFzjlhfRNFjMfXp4xQ9+R2H5mqwHOj39sPmaHA/PnzJUnbbrutpPa83b7K2nGeMLI+0kfnA877M7qb1atYOYr3RhSk05ekYtkv63bXbcO2OvWH8xidIrKg8fqwX+x3dO8zhsUPclqkpHbd9tT9TqzpSCadSCQSIwQLQplhllK2UuuCie4dL2ZMJKIo7UjdiwG9ZNJR4KvB1DumhHpRVeYY+zcualmalaydKZNN6mZcfJP9s2/Mi7ZgDoOkyzad2nj99ddLkg499FANBfr1knbHGS1K0wHLqzHauW7lT1m3iGkYEfOOtovUvLziZtS4L4BvGptReA6lKYfn5TY8HmYAjDBm4EcU5RqJ0FOv3CALZB4x4wDK82E9ZZrQKBrg7fygGAqYJfE8mvy45W80k1ETnpkJ9CVzPlKSkeMRVdGKHjJNPugm60rdvkxTiaKuI/SXWdOEyOP6HooCkniu3t7M2Z9urzShsoqYX2AXX3yxJOmEE07o17kkEiONZNKJRCIxzLAZfvvtt5dUMT8v+ug2kdoX7wxujRg0BaJIiAymwjEQlW47LsYiyds6IsMFNYMIWbwlKlxDd1JZNUxqZ/kcVzNoilaxilYpvOX/e1Fp8jBUC8F+vaSpjRxNCuZNm31FJouyzaZgh4gRRb69aD8f29YBn1vEPjoRjzc40VgByeNAn3Knhc05QXkz+uZjuzT9UHNZqiY5GTQ1pNkn5sQPJpwXPX78eEntVpQ6qwYRMVjvwxrGdfWby08++GiRYfwF75G6euTl/gbnYYQ6VtxpLnZ0zL403kvwHKJ8azJpW6cYmMTniq+NH4oGMw2kap7yxeJjjoQyXiIxECSTTiQSiWEG/cckNFQRk6qFBlM7o4UeF0lRTWXWUGYgqhekFA1qChz29nVFXyLXHStwcQFJdyMZuUkCXXp0pdA9xWDnyBpRnhf92JaKHmz06yUdDXDECjgBI39bXZvRBIyiuYmIJdC8UleRqwTLvNG3WLLQSOM4qtgVRbmSKUdMx6A1gewtGvdI6azuN6ZbRAEcPvcLLrhAkjR9+vS2tvsLPhxKE6DUXqErOgep3URH8xfz5KN5aTQx3E59ztH3JusK/1+XPx3p1hNNvuem/Zp83Dw+c8oNlivkg5lqhCWT5vWifnldKk0i0c1IJp1IJBLDDCpokbnViTTRxcffm2RYuT19zlGaq/tKt5K/e5EVpTeWi+qoaIr7EgVqklk3RX3TGlCnI15+p+uMC8NyTKNSrHaZDraQTr9e0lRJilb39JVyIhp9rdw5OFEuaNRWxFjYx6ivrAIV+aZL9kYfGlf+DIbguXaqNBZZB3iu0fhy4pfnQB8tq18xuIQT1mAqyerAk9150WRgfGiQYZd9ivrTlG/fhKZrEv3exKCbcp/Lzzq9gbq2m+ZDtH1kDYgsahGjZuoPXxK0bvEeZdwKtfKl6n7li4PqfFdccYUk6eijj67tayLRLUgmnUgkEsOEiy66SFJVHMaIXBN1Cyv6U70wodAQ0yjpbvAiKRKVoVuOPnHuR7nnphKmdfvw/Cnfy4UbF3idBloSXJAyX7tEk/z1YKeh9usl3eR7ivIgueKu8+dG+aBNDDpCxFicY/n4449Lqiawk9aZZ8m60r54Vuly7rNUMQT3mUEQnAiW+Xv22WclVfmerigVVRPqNJc2YjxGX9fB50u/IScv00DY9kDAiHve0E0R0nVWjqh/ZGnRg63JqsE+dBqx38S8o/38/7rjNFmXovnUqeWm0+hv9sdj7dQVW2Mo4ei5RhbsGAX/7ntUai+naHgueB/7sV2LOutQJ7oVyaQTiURimEARIC7+KKpULi65CKJLyosekwVGV3vR08QWIzJG/y4D+1hA6Pnnn285Ttm3KCXR4AKSPudOC9BEeded1L4u968jMoT7MhiuvhL9ekmTuURVbqKB9Imy8Hb5N6PTKNhO/Wbui0Xff/zjH7f8vt1220mSfv/3f19SlT/tie+JZwbtvztqVKomoH8zE/QE8SR+6KGHJEmLFy+WVJVD22GHHSRV5hLmHHM8m2IDiE78ocy1pg+aD5VIGnAgcC7rVlttJSlWrOP5UPmufMhE1h/PRT/QqNVOdJInX6Lpho7a7YRR1/Whr35FcR5NPmuj6Vw6jUynnoLHmg97BhFRf4EV26T2FxFfZLTuuc3zzjtPkjRjxoz6k08kRgjJpBOJRGKI4ZRELwa9mDCjoyxtXbAp00C9kHZ+LosCUdKYQbBU3Yrck2SzZNRuly6yurrWLlDkv3FxzIWbEUVlG1GQMutWe1HuhTxL8RpRBHcJnyfP121bhGnq1Klt+/YH/XpJe0IxrzFKbu80B1SKJwDNPxFboskmymflxbvjjjskST/4wQ8kSR/60IckSbvuuqskaeutt5ZUseOSOTfBfTJ7/9nPfiZJWrBgQe3273znO1v2i0xARGQaarJ81LXLa8c63mStkRmqv1HSJcygXTfac8EPm4ihRXWIy/76XP0wcByArRc0VUXyhUR/c4ybmHiTD7s/aGLpTYhMiJ0qkLGdKD6AOgNMo/H+ngdkx1K7KZclDinp6L9TTjKR6BYkk04kEokhgs3oFlFhEKRZLBkfS8NK1QLSCwovhsxGWfwmCuQ1/HcGwdI9ycVVtGC1C9B9fuqppyRV7FmSxo0b19JHs28G/EUFbSIGTell/07LhMeOwYp2ndj16O0YUFr2kWm6Jq/exyTjkksukSQdf/zxWh306yXNzpBVUZ2LbLcv9ssSYvRLUR2LZoiIHZDZuR2zNWLRokUt/XjyySclVUL4jgKvi172sRww8cgjj0iSHnvsMUnSbbfdVnvMAw88sKVttmdE0bSst0vdaZaco6xgaVoi42AcAa85g08oTrA6sPnONz0l/dh2J9HsPlfffDav+RicR1EePRHpXEc+/Cgymug077qvNqJ9m3zIRpOPuWl7I/KF8wHM+RilGvn69xXR7nlMs7H34b3i/TLaO9FtSCadSCQSQwSnU5qJRfK6ZGcsGSu1M2kvWppUtBh4Z3hhWpb6lNqFizXIDVAAACAASURBVBj5TKlVu4rcV7qnvCAqt2WxITNYnz8VyCKXnUmE+xKVjjUY5e0x8WLdoCWj3M+sn3EFhvchWV1d9Osl7cFmsAMl25p8X3XmF084FuOmw54Xi5HU3I4T2BPJZpc/+ZM/kSR9+9vfliQdcMABLfs9+uijkqoJ9653vUtSu69Wqib3fffdJ6li1D6H/fffX5J0++23t/TJilo2W9FcFfn2fWxP8F/+8peS2q0PhicVxftLJs3glMgqQqEDBqOsjmb3vHnzJEnveMc7WvrPetsUNoh88eXN4evFqHxagZpUtZpyi41Oo7Sj7Zsir2kl6ItNR8IYERNe3Qj2iKFH8SFR/j/TXsiOWemq7CfnLy1AfDlS+MPfB1vaMZFYXSSTTiQSiUHGVVddJalyYUWR0pRapmuqJB9exJswRMpfXKxy4cLgSS9YvaDxsRmg5z5OnDhRUpWeyjQ3styShXJBZuZrhm3f8NKlS1vapDUg8t1zUcbSx1zAMxqc9aPrSu9Gwk4sKOVj+hped911kqTDDz+8rc2+sFo+aTM3g2YQr3Dpi/YE5IQs2/ZFiVgSTTBu2xPYIBugT9Ls1Rdh5513ru2HJ40ZmI9nf3N5g2yzzTYtx/D5kb3tvvvuLdsx8CNid6x25d+jqHuDkdhkMqVJKGJb9N1R69oT1uO1OqAWM+X2qI3OuUCWVJoK/RCwaY9qbkYUgRz5ljtlyk3542yPZjo+zCN0ot3d9Bkx7P7m6XO/KDuhyVfu/Xw9fT/VKZUxt9pt0jTs333/s1RhaaJNJEYSyaQTiURikOFFIQMSozRVLkzqWLIX9V5YkMExt5ipbZFgFPtGV54XPl5E+9wctf3cc8+19IvnXJ4bF7tuw+dmN6S/kwxxDJrccxxvkjuCssD+Xi4ESRLoWqFL0Me25aG/WK160h5oO9C9SqUYOgeKk6j0SZu5lupB5e+M+GSofacRrobb88CxkLePS1b29NNPS5LOP//8tmOcdtppkipzkH3S3tdMmmanptSGJp80x5dpDWQVkZmmL/CYjOJ2Godv2P7A/r9Jkya1tMnCAb4xGaASBXCU1hWPPeMn6mT/yvOLmHNk5aC1g/7gTlW5on6UD52enp4+WW2TSl+EKGKdfY7uuSZ9hAidClTQtFla5BgJbsuO72cWlWDaEgOREomRRjLpRCKRGCS4BKarXHEhETE7Lnz8e7nwpKKY4QUGVbUYYEnFMUaa0y1hUsa+Pvzww5KqhTkV0CgUVC7SWEfbrlMzavfR5MmsnTnIBl2rUd40x9Xg2Bk+F18vn6vULj3LBV5ETt3mNddcI0k68sgj1Qk6ekk7IX/HHXeU1B5d6YlkFurVa5T3WBd5HSlc+eIwkIID06lfjBJunKBul8zagQw2v9ThJz/5iSRp/PjxkqpJSlH5Js3zvsrU1YFCCL4ejvbmxOVY1N1ENN0YZK8Molgd7W7nrPvGdBuuEuZ+Ms2CVccoa1je0FFObmQh4DXiJ/P6y0pMUnu0cGSGMzgHyPg7RV951E350px/jA2I7jGm6ERWiibza3QOkY+cGQZSe9wMrX20PhlRsFUiMdLImZhIJBKDBC80WcKVgYpeQHqRS/EmL0TKYFAvSr34p7ATmaxh0uQFZbS4MqLgUC/+TWAcbGt4IWSi4wC/Mg/bffWxzZTti3YbJkUMBOTiNZKDdl8ZWOyx8SKb/n3DZNBjU14HkoGovjSFoNyW1ec6RUcvaU88TzjWXPZ3RttGEav+e6mX64tF/ynD++n7M5r8tkbkW+RKmjm5nmj+tEpYCY8Dw/h57IghN/kQI981K1FFx2H1sboJyGpfkSnHv7MmsFnvpZdeKkk67rjjas+1hOXzzJR9HpQrjCwzkQh+XcAK5wPnE608nB9MEfGnx9AM2vPE48M0F1oqmph0HYst50EUz1B37k3snPONc8DwsWiViu5/1nJmZDWP3ynK82E8g78z8t/nRguQ/+7r2Z95nEgMBZJJJxKJxCDBizQvaFhe02DktBcTJCOlm8bsjvrTho/lfbwwmTHjrpbvS5ascgV8+tP/XnsOZ521a0sfvbgyA/Qna2P7nO1qIHko++5tvUD3uPmYXqB7ERz59I3/83/ubTl3f1500ftb+kCfOIVymKrrxR592WVfaNHgJ4mnF6cXXXSRJOnEE09sa7tERy9pswCufMlCIt8RAw/IOsq2yfI8EN7XE4B5u0TkazR4MZt8kB5wm3CoH1z+jVHwTePSXx90FGFtcxajon1z+5OMs4yOtR/YjJFC82RV9LVGkdZ1sPD8nnvuKakySdEv6PNy276BqcfOrIISkVUnKmRPPXSPi7XcHeXvsf7Xf/3XluN95CMfkdQu8+hr4GtN0yTnSuSbLs/n9ddf77PqWKeZD0350bzWHEsy6cjS4xeRr7efL34eRHnbnUTGR6bHSNDDfaSEZZ1qXSIxEkgmnUgkEgOE60XvtNNOtX8ng6PbyMSF5nkvTMvfGH1t0B129NGLWr5Xbgi7KRw4qjd+V8sxmabqz6i4jn936qmjwMsFpBXY7M+my8TnZPenx8nlfjlOX/ziAy3nMGqU/cCrxtVWBLdz1VUfbumrf+cC0WPpRXiJSGwpCg6NGLfPsQkdvaSZl2jmwpV0U/1jsqvy75GT3fuQ4XB7o2nVbUQstimXlIn6Zbu80E1RtLzYUV+JqOQcWaz9omYsZsU0LZU+aT4ImJtMRkKTG1lSX4gCYPzJ4BsyarN9RvvW6WvT50ilNMY+2A9u1k59dP/93/7t32rPzSklkW+bNy77HM2B8oFrv/Ty5ctrVb2arExRJH5UQ5uMmn2P/OjMJvBY+7s/GfvC9tl/HrfclybhKK6jfAmWqHtJJhIjgWTSiUQiMUB4URotvMl+uRA1Y2PAW52UauQOaCI2LNqywQatj3///qUv/Y8k6Stf2aPl3NwXpmGyXfusn3jiCUmt7jS7exhVTfclS43aJeLF75e+9NAbLXox67FodbGYWbvdyZMXtpyLYYbNMa0r50sXaJQOHBUl8mcnREbq8CXNgzCtIAKZdhQlKlWTlTrfjNYkm2ekedSH6DNS/YpgRkl97vI3okkruamvvPhkY5HSG9kDJxWjcsvfuA/zfhmdTJbUSZ4px4tqUAy+cZs0CUbjWDJFskHOLzNlm+rMoD3vvL3bjhi0wWhwXgtG2rMwQDQXSv+umXQ598tzjqxETSw9OhcybIOm206ZOn3Ukd+Y59OXWhyj62mSpbYDrVKct5HeeCIxXEgmnUgkEgMEFapoqo8W6FyI+pNuJ6ldCtmg6f4Tn7hZkvT6615UtUvKln0kYfH3z33up5LaI6QZCMhzcgCtixjZRSRJW2+9ddt5SbHAkvtCl9d669nV0eruNKqFooMaW4+z3nr2H9cv/CiIVFbD8jhHvuem3O7IVRuho5c0J0WnkdVRkIQHvG4fMjKvsj0xPAFYezmaMJ3miEardq602fdSaSoaj8gEZnSaPx35LVmuzZOIn5HZq2RiNMPRn83I9Sg3vhNQMtFj2VSEIHqw9cV6IvZHS4oR1SPvNAKfrNLXgD5vCvlH1a7Yz3JedsqMm75H+0cZEnyQse9MI+ILyA9cmk/9d7bXpJgmtc8dVojzd6Y8MdWG+dKJxEghmXQikUgMEJFuNhl1lPJZ5/ssf5fatbS5WGF+MlG15UWvWX7rIiyScyWTZruMbrbcb6k4xnK0dKFQi5vuIWpsN7kSqwXm6/j0ua5q92Mfu1GSdPXVH2k5LmWipfZgQpJREoC6ksBS59Kz6XBJJBKJRKJL0dGrnOkILCYQpWrQ9s4gmTLgg6Y0BqvY3EpJQSOqlWpEJuMoiIt+G/pMHGVYltb0uHi1GKWq8BgRItETt+cxot+EwVD+ZMUXf5Z1TplmE6kYMYLUiPSA60BmEBW34Fzw+XJV3td48m8+PxZsYWCgA8lsmjX2339/SdLtt9/e5/G4yqYf0HmcHgtHmTYFNK5YsUI9PatKVfqT6K95m9s1Ba8ZTfKh9MkxaKu/crl9mbt5j/mZZXM2U+4YrMg+1uXJJhLDiTR3JxKJxADhBQoj1JsELqIaBHXm77oYEqlaOFsVj2brdqxs+YzqyztgzAtIL2xoouc5MVamrhpdlLFCwhct/KpsC71xjNbxbjvjQHGQpmkuZKk3X44Hx5njTcW9ThelREcvaV98MrVIYrE9H6+VpTjAqWTDZNceCMooOl+OjCQKuOGkN3gxouIVbNeM6jvf+Y4Iq+hQmaepcAb7yIjQSGeWAhaeSO6jj282QBEJb8/6tCUoj8k2yJgja0uJOXPmSJL22msvSe0pfWTWDOZhQY3IilLHHHmd/Z3FY+xHczSq5zyD8d797ndLai9ZyVKJrLnLyE6f65Qp/yxJuvLKg2vPpWStPT096unp0QYbbNBW41aKHwK8ZlF0L//Oe4MP2Ehy0+DDqkmqd3XSn+jDZACf4d/pO/Y5Uh40wn777SepsqzxpdLfNDii7He0L/OjH3zwV6rHqv1//evHJUn33//1N/ZvfWn7OFOmXNVyDk3BlNFLquxvJIEctRlZRqw/XrUbpbX2/k91YH8OPvgbjf3rT3BsuW8kbPTWt75Vd9xxR7h/+qQTiURikOEFVNPfo3+jRo3SqFGjWn6L4Hz5Bx74lR54IHpBS6teVNULZuXK8iVWtVPm35esvdN+rFixouWlVp4Dj+F/UdscF/dp5coVLf9WrFipFSva2+U5R+dqLF78nBYvfq7td1+PTv7xXJvG64knnuglLnXoiEmbFdCnzJU1mTRTL6LUIKmKnjOjYYqVLyD1apuELCLfdJTiQgbN/d2f979/lSnIY1P2jZKZTYwgiqaMmA39m+4z06bIdilEYtSJmbBoQiTlGPnyytzIJkTatjQJ0icdCYDURVNGJqby3Ou2IzOiJG50TMYueDwoo9qe+rWqvY9//CZJ0vz5f9bSfjlX/DDfcMMNa6V5m3zS0T0S+aLJdqL92Q7jGGj2i8ymRlMEbx3b5L1AkR4jkmVlcZcIZkC33XabJGnMmDGSKktM9CxoSses246WS5+rrTWOUI6ecYYZ9K67zpRUXQ/mZl9yyZ9IqhTEPIYcE1rAGLNQZ92J0vVo5ub99otf/EJSVcGL9ynfD1Uf/Nl6n2600apn4pve1Bo1fs01h0iqv06c91HMBt9zTAf0u+O+++6r7bORPulEIpEYICJTJnUcIjdbpA1Qd4zIFOwSk//v//2soz5HBSBeeWXVy+R//meVPKgX99RU98soCvzsBFHKGX9/9tlnJVXV5yJ1uv6aov3SvuKKD7W0Q6JZF5zIRVOU7093XbTojdDRS9qrQso40vnOCcmJS63XcsVFfyPFHQxOiCjvkH7ziHFH5TYjP7DHYvz48ZKqySNVFV4iZaBoEjetfLl9FOXt62DBFxYriURPSmsAo7Y5ASMmbUQ5miVmzZolSfrBD37Qsk/0AIuCb8jUOH5lQZeI+XMuRjdOlMEQMWn/7nvG18TxHaed9h8tfa5ufLdrv+AqH7UfIrzW9kmzYEi5bafnZETnGIHj7rF0LIT99JEUJyV+m8Rsmu4XqZozvl89vu5TFFxFvzktH4nEcCOZdCKRSAwQZEteLEWslwzapKSvRUFkXmUEskVK6IvlgiQqAOHtvKBcvHixJGmXXXZp2S4KiKL7qS5wzGgKHjRz/vnPf97S5699bVXApqVL+woWLUHXYhRQ3AkjZ1AtGTT1/nmM6DvR0Uvafh2veKNoP67c3cmIlZUrag+e92EeNBlx0+BGpQEjn1DEVqNiFRMnTpQkjRs3rncfR57TpxYxE95kkSoRz8XbH3vsv0iq/JbuI5mJj0MGal+W/aZSuwUiYpAGzU5GJyYvTuqmtunzMiuq/Eut1peSSZvN8UHCyFj7i5oeOJF/l3PdD0779VxDlu3SN8755trA8+Yd1DsGDrhZsWJFW1pI2SbbJiImzb5E6UGMHfB1sYWG8p/e3hYds13e87zOBiOzy/utyQLmY/Clygeu0TR2icRQI5l0IpFIDBAMrPR3mva54KE7jy6dvnyhhhciXgCed977JEmzZv2wdnsem+2ee+4fS5IeeeQRSdKTTz4pqaroZoJiF05EoOoW6iQiXBB6/HzsRx99VFK1oHPRDh/budwe75kzf/BGn3yuredMa8I3vrF/n3+vc5fSfcvyonR5NaXannLKKeoL/SqwwXxn+vMif2WU71pH8yMWajB6durUW1v+/t//vUoh6vjjV0Vbnn/+Pi3HYtlDRuQxcjIqx1nnM4/ynGklILOl8AEtDSec8J2WdngcV72JwFqpfV2HJr8ff2ffOZ59ISpNSaZGtskiFWRWdf5Zmh8ZtR2JKzTFFUQPQLfnh4dLXzr694IL9pVUKZr93//7k5ZzNNivKVNufuP7qrm+yy6j9dprr7XpC5R9ZACL4d/98DU8t2mRofUpig1gXr7HnqVu/aCl9oHbYa65x4BFX+qYdKRCx3vTfY8icfvK908khgPJpBOJRGKAoEk/Em6JmDRTjqKcYSmOQGbaaqS+xXb8/dJLPyipWph4EeVF0jPPPCOpWoS9613vktRe9IKV2kpGHZEe47HHHpMkLVmyRFK1oLNb0UJRPleO49///ftajslFuK0LF164X0v7RsSky8U4XWQMiKRbM/L5dxqJ3i8mTR+qJwMLqUcBCt7e7ZR+TKte+YJzcBiJPH36nW/sWe87dV+OOeaWlj5ddtmq3D+u3iOVL45B5Jfraxuer5kCJ6zH0f7HqLZqdJM5YKSamPXqWv67mUjJsKIoZ54bddnpBzaLmjt3riTp5JNPFuGb31HxkQ86Yjf+zrxvpkKU/6cmOY/lTz54jCj+wuA1pwa0GbUfNv5sZ3Yu19hqZSitUytWrNDixc9p8uSFhRWimlOXXfbBlvHxuPjB5HuAljDfi6yRzIwIjgmvE60R1Jinxr239wvP97qZPkuTeo6V/YmuRxQw5H3dZx/bn88995wSiZFEMulEIpEYIFhikYGJTe4fpiHWsazItUJC4QXHOee8R1K7a2fKlFXSl3YFGqytzTRCL7K8uPaCM3J/0k9fIgo6tOiP2zJj9jGi9DwW66E7yn2aM+e9tcc3mlJ2y7a9KI0YdESmosVuhI5e0tFq1AMXrUoZvcvOl9Gcngj0Q/rTF+9Tn/p+SxvRJyNNjeOOW+XDdt1QDiSViSITU13uaZNSU6Qc5rbJHDyOvslomomixan0NnnyQkmVb9rHZRUpKY60jqo5GWRRncA55g4GqVJI6h9wNC8ZFDSgr7v8P7WdWaGNCkeRT7pJZY+aAH6w+Rq7fQf7uB8cf5oM6x4qy5cvr1XUskWG94Qfzr5/7Sf3Q9VteB6SCdP6xHuNFaZodfIY0xLn/Vixyu1H2Q/lS6BJaTAKXKIFyLECn/zkJ5VIjCSSSScSicQAwQInURBppzLFdWwrihbmopaLfMrtelFUpl6Wv9NdRL+vF0VPPPGEpMplw0WyfdhlOd8JEyZIak/n9aLIfSIpYOEeMmoGRzINmK5YEp9I2KcvWdAobdeILB3sWxP6fElHFV7oAO9EAahEX9txEnsgFi/+5Rv79t22K7z89KfntrRnJScf+6MfvVxSu588UgOL+leH6Px4k5EV2Q/GKjb2NbvSSxOiB8WkSbMlSbvuOibsZ9P5RdaBKJLfN9WCBQvCNs8//3xJseJU1DZvOLKjOl9lU/RvdP6dXlP+3lSmLgoq+cUvXuyzP5Lneo9++tNKnL/cvkpD8f256vvRR1/ccuwmi4/R9HKIlAYZkxLl1EdzitkQ9JH3hf7OZz84N998c+2xxx465JBDGo+RSAwlkkknEonEAMHoboNBjQajvaOFS13wI4tJcNEUuYfo9jDDbRLoiQqi2F318MMPS5LGjh0rqb2AhL9LlR/bCy2z/gcffFBStUjyuVHQhuPEwGL6oilW475HQbmRPHTJhpsWqU2klfnVTejzJe0KL4sWrfJt2XdlEwGZC/2VnqCsvlRnQoiiZX0RXRUo0tw1XOHlHe84pWW75cs9cVdNmDPO2FGS9M53vrOlb/SHkW30pTwV5Ufz75QAXLp06Rt9v1+SNGfOs2/83VWe1Ge7BHPCfW7/+I9/Lqn9OtW1R1EGjksUBc4C9B/4wAf67KskXXjhhZKk3XffXVJlPrNJjPnR/mSlI9bPLvN//Ruju42IBfY3b5zR4R57RiwzAtr9cpyAI69nzLirZQzK+ea5vttuswKzXCubd7T/3Ln/W1L73I5UuPgwYWS8t/dc8Sdrc/v54evKHHJ/54PX/fDYsJ56XeUv+qupBMecblsLjzvuOCUS3YRk0olEIjFAnHrqqZKkW29dFZhKEz0JCheBXDTWyZT6/xSXYUAfC+g0lZWlbzRawPo4W2yxhaRqsWx1MPuoiZL9mnVbxay0FJRt89i0CnAcGahp0DpA/7zBxVxUNrWuTfrwI/82U0opIhSho5e0zSJeyUYr7yh520zH5pC6mp+RML23vfzyAyVJ06bdLimOsq6CHJz/qpY+vf76qj47qMEJ+9ttt52kdn9XxNzJLKWKMdCE4jYYFWvm4JJw3i5SRYvMUpVJxtHirWNwySUHtPSZUfklC/N1YDpGVHaNfehveoEknXTSSZKk66+/XlK7ibApKp4SjP5eqkX5/8xZpwmQaNKMZ3yBPz1urJPua+p7yv1i/Wk/jCzRaBGGaPzr5mk191uDayyd6CIFTVrzZrqe675nmHpDc6zP2c8NRrAzz5kPSmaJcL7W1Tf2g8/jOm3aNCUSazKSSScSicQgIZJEpu85WtzRdVAuQLzw80KNLhV/Oq3P4GKIKZqR1jTdHk6RdPs+N/um/enjcVEmtfvH3ZYZtF0hPle7zejyivoaERim/3kByRQ8L/xIlOrcSXRxkaBEQch0tTSho5e0WSd9QuwEGQ41fTmQ5cXzat2fHhz7sTwhzztvb0mVr44soLoZWk+NJhu3b7PLlltu2fI726V5xTdPabIwk476RDbuc/XEcx823PCRlmNW50C5ub5931acco65bx77Oz22JXOlH7IM+iiPRYtDpN/cHxx66KGSpBtvvFFSxdiiqG3eoFGx9XIbxkfQ7MWbnDceH748X8YD8O/UxfY5cLxZjaldpa9HPT09ciWsOhMb2T9Vy3xMmk8jU6zTZPx3zneaWz3PqBBGkQs+Hxh74LHwS8AP1OnTpyuRWNuRTDqRSCQGCV5QROV5GVTLBX0krSq1Lwzph/WiioVHKC5DWWAuFCOXlReW9K/bjekFpI9nllySDTNjj4eJAl2ptBIwB9x99X50oTK3m2VRyfK9IGSUeF/BtZH6WeQaM3yOnRZv6eglPXPmTEnSNddcI6liOJxoNC1Qq5e+pDLJ3b44/+Z97dPzvt7uC1/YWVJV9LtiRK0DRLPI7Nl/IKkKduDq3sfjzcMLYr1p1wmuO09aDtimz5VR37YWnHLKj9GHeiWzr371D1uO54lIFscHSGQeK9vmPn1pl5fHpFBCf/DhD3+45btzrPlQ8o3pG9DjR2W2cl/uEwkNRFHrzLdm2gtZItmg+8gIf+bru79u76yzdpVUPRA/9anvtzyIOqk6Flk/WOeZsRCRP91jacbs7Sgj6XOPSvoxytuWn1T7SiSSSScSicSgwQsNBsmSWZM8dKJ7HbktuICmy4V51SxrykA+uiHowybp8HG9WHPFqroqXN7Gx2L6LgmIF3qUAqYrJkrz9Xe6mUikuCjmYrwEjxHlSzOQmoviv/zLv2xruw79ekkzIIArbCoLeQAZBeoBr8tj9QlQ15eVctyXz39+J0mV2eOgg1pZguv2mtm5qo3bYXm3JnjAfe51ZpBIaJ3bctJ7PMxELrpoP0nV+DHq1efk3Fu3z+ticH+zvFJD3cdyHxhBGwVFGG772GOPrf376sDn4XH1+fHaRWks5f+pT8264GS0NCWSUXM/3wMUS/B3VlliLjstFLzxvV81t0Zpgw02aCsPWO5bKY+t+vzyl9/Z0jcGL7Eut8/NFhozXQYBRQp6jN/wvLXpMxlzIhEjmXQikUgMEo4//nhJ0ne+8x1JccBhVKiFWtNlACYXo2R5DJj03ymba3BRxQV4JKXLdujWiLStS5BBc5HJsqpUPaPPmq4WLpqjvGcSKpMS5jyX+0V+avryI2Uy5oY3oV8v6WOOOUaS9O1vf1tSeyABWQXZAOXqSlNOFK4e5chyQHzikyatYtR/+7f/S1K16rcZykzak9+C75F8X6cVrco+R+kXjJ61b9/j5b5xEpgxGlQB8zhyvKPqY+xnGcFNhskIXhY45+Q2qx9MMF7AimQM/vAn88ClWHHKYMpF9EmmTJMWMx9oefEnA2DIrOkXZtT93/7t/9IJJ7xFo0aN0ty5/7tNhavclteMsRC8bynJyPGnLrsZsUGlMB/P2/letABIIpGIkUw6kUgkBhledHGBTUQypnWyu1EOsEEWyAVfFI1M8hAxcfeNC0Iu6ugaK/vNvnBB7WMwiNHf2Td+RkVYuKimWytKtSQBKP/G7yRl7DuDcTvFar2krTXNxHwPuBElmJNlSO0nQl9eJLMXqRU5p9OMxYzan2SKTbWg+6qwFJ0Dw/g5EchcnnrqqZa/e0KSzZIVRv5URtFy8lCmruw7rSP0/5IB+jOSBhwIPA5UuuJcIDsuTVSMova5u9/UmyZD5kOFMRN84JEBM9DFf2dgjFmnrxnNeuUcev3117VixQq98MILbYIW5bF4r/CB57/TVMhSh97O18G/+x7zWEbCHJEEZiKRiJFMOpFIJAYZNu1TnYsgY6NPtiQDUREikgLKqHpxFflQIxeeF1t2azLwlJHS/s6I9rK/JAgUumFwaCQJG5UgbSqdy35EAaIcq/I6sC3uQysA62zTPdSE1XpJT5kyRVKVN+1cYQ9o06SoU0fyzywmKwAAFZRJREFUidPcYb8XQ+bJWpk+YCUx+78cQXr22WdLqlhDFAEd3Qhk1CWiQu/8bpDZelwYPeu0Bd8ETNBnyTrvxwdApJZVN+EZqR9Nao+7VelmzZrV1tZAwbzuKBiE41CCPnX6ipmDHV1/XjMG8USxFdyPJkNbKrzdo48+KqmaC772zmLYaKON9Nprr6mnp0cvvfRSG2suj8X5x/FifnmUhRAFEvnvZtScf3xIMZ0mkUjESCadSCQSg4xPfOITkqTbb19VEChaKFNhjG67OkTStVHEON1iEbiII8nwAtDEiYyagat1x6NPmISB6br+nS6bKEo+kilmzjf7E6UR1gWaUuLXi1Qu9BlE6r/3l8gM6CV95JFHSpLmzZsnqV2JjFHEjDIt4b950MwYPCA0c1C1zFHFlpmbPHlybZ/N+j3AnBxNTIgsoy9GzW3qfPFSNTEsMm9zyIwZM2rPYe7cuZKq8WaVIU40ygL6XOtSATjBmMrgc/B1efrppyVVD6WhgK8x83KjTz8cyhiJkoF20lZUG5wPDwbX+Br4O/XE3Q4fOrQWeJ5b7Y+YO3euXnnlFa2//vp69tlna+UReR9GZjlKITLP3m0zst1j6HPlPUWRDOdH96dCWiKxriOZdCKRSAwRHMBK1hWVWY2il6U4cpnuhahyU1RrmZ+R5K3btavQx2UkuxdtzJsuz9/n4G24oDRbZx41XSWRP50pvFGaKl03kTxvSc54LAZMMzLffbbrtb8YlJe086eHAuedd56k9lV/xDCuvfbaPtvbYYcdJLXX8/XEI6IE/qi2c7ltXznVUjvjsB54nfZ0iZNPPrn29zlz5kiqzE9UMqMMnbevM7943Gl+8kMl6sNQwMe66aabJLULDZDJGaUQhG8c6k0zbSTSwObNHDHvyF9LsyYDZxjd3VTh6eSTT+7VNJ8yZYrOP/98SVUOudQerR1VS2M+NBXdPK4es0h4g+X+mLJD6cVEItGMZNKJRCIxRHj88cclVWmUTD+Lql4xx1lqd6mwOJAXXVycRZHlRsSkySq96KW6F9XR+PeSpET50IYXyxRVYsAn2SrPoSlKmwHIDOhkf8rcZh4jcqVRbMquwf6i61/SkV92dfHQQw9JavfDmYEwanx1EEUIk22Z4Toy2hczshI0ob8BCX1tP9jjPhhgiT3qYfthxUpT5bb0o9rqYJYYpaXUmR/rEKWI0FTJh5HhaO7+wtkLF154Ye9vjNZmBDofdMyw8KfTiCjRaNCU64eTrVQMXDrllFNW6xwTiXURXf+STiQSiTUVlj51uqoXOhS7MWmgb7RcaEZyrV4MUZSGRYkoLhVFiRsMcqQcsY/DcyLK3/1/983n7TZZJChaNHP8GPVNthtFe3tMmWZo+NzrikFRTCmKTHdQc6dVr4h17iV94okn1v5+xx13SKr8wpFYel9oCsygwpdNYU3+x8Qq+GHka8Tyc8weKINM6Csma6SJLioiX5fj38l2NBn6XHx8BxgNNL7jpJNO6v2/fdaMzo5K6kUWII4F86GpSGYwAImKcIlEohnr3Es6kUgkhhtOV120aFHL75Q7ZpBf6ZP2/yN/bFSUKPqdfWCaIX/3QtauGgc5epFMHe46gsOFYlTy1aAeOd1OZNBNUtT8jJg7g3/LdFUek9YQ+qQHKpWcL+k38MADD0hqZ1RGJBtX56Pk5Kaf0gz6ox/96OCdwDoAa5tvtdVWktp1rSkeED2USjDNhPnMVFqLmDQDYJiL7BvWMRH2Pbv9MhJ9sGCNffvbmfseMWjO9chXzahuRq57O59bf+UQE4lEvqQTiURi2OAIX0ZiM386khIuf2N6KJldpwzbiErdchFs5my3hxk1j0uBKqkiQVwoGlwIMm+cfY9cNE3lebmQp8wvRZ1Klw+FjHi+9t3bhTXQdNV8Sb+BE044QZJ05ZVXSpJ22WUXSRVba1Kk4v/rvrte9JIlSyRJH/zgBwfvBNYBOOr9X/7lXyS1m6gi32iJqLpVJIpP9Pd3H88PMpsK+6rYNVhwhL61Azg+kUIdFcFoguS8Zl604YeWsxdWN2shkViXkS/pRCKRGCZMnTpVknT99ddLqlip0ReTpq+YiysvkrxoMguNxGwivzDZJkVpqDxmN4bdGlGt5rJPdIl4wcgiOZQjNiJhHv6dvn5qozM9MCJhZfuRX5xS1YcffrgGA/mSBqz57ZtowoQJkipGHVUWKkGzkyfxz3/+c0ndmYO8JsF+XftaedPU5UlHPmPenHxARb7nyJQYpXxQF5tqaU7TGExYUY7jQUU6Pxip006wapo/Karh7Tzvh1OdLpFY25Av6UQikRhmHHrooZKkW265RVK7K6JuwURXDfdhIR1/p5StQWbOwEtGNlPq1ttbTc3+dgcs+u8lC2VBIwvlWIKWJWWbUh6bygMbdNkYVB4z+hKzihbgHm8HuA4W8iUdwDeRfdRUXaqLHPZEoA6zfdH2eycGBueVW8vb0d5kxc5FltofSKzJzVrcNCkysKdJEIIPOLfvymVu13PkuOOO68cIdAYryl1++eWSqkAWsn1W4GIgEj+pd+7qVscee+ygn0Misa4jX9KJRCIxQjD79CKwr6BHRnN7sUV/LZkdgyLJBN0O/bZclHEByz6bUTvquy6Y0sdwyWDvQ6EnStc2RapHBXDob48K5ESFcjg2Zd/o3rHL6vjjj28774GgbyHiRCKRSCQSI4Zk0g1wIJnBEo4lvErzyirN20OLP//zP5ckff/735dUBURRAUhqVzSi8hHTiJryK719pClMFsKoVs8f+++GEjZD/83f/I2kihFtvfXWkqpzohgJx8afdiMMZYnadQW+NpZwpeBM6UdmdDVrMPP5w5rIBudodMyo1C7L1hLbbLONpIppl/vTtRLVxKZfnJW5CEZrM8Ld7fi4Tc8DpmaWx3WbthiYQfNdMVhIJp1IJBKJRJcimXQ/kelT3QeLw+y8886S2qNfpVjAg3q7jHRloFi0QmcQVhR0Zfh7Wad2qPGZz3ym5fsll1wiSRo3bpykKmXKkqVZUnL4cNhhh0mqtL3rGKPnHutKkwmzMlQEzu3In0trkOH7i7Kw9jMz77oE/bnMh/ax3IYtT96OIlP0E9O3TUUx+v7JxA2ORV0fn3322bbzG0wkk04kEolEokuRTDqxxsMqTldddZUkadKkSZJaV8ssFhH5ohlBS1Wh6DNi0hG84q+LbRguDHYUamLgYLR3iagKlucQWSKZMGVbGcVNK5Pb45ymrjbnfpn6WP4uVf5bs27HkTASPGK+3s6/R3rj9C33936mNaIcO2pzD7XFKZl0IpFIJBJdimTSibUGH/vYxyRVBSUs6Sq1R2tH/rsowpVRp02+56hMpvcz+7EQSyIhVVahG2+8UVKrpcWskeyOc5VzmEyamQj0TTNnmFHatD6xdKk1vB1vUfqyzbLdpvf1d35SoIhVqcywWS2LsSXcjn3jmNDXXUbIv/TSS5KGRoCoDsmkE4lEIpHoUiSTTqx1OOKIIyRJl156ae9vEydOlCS95S1vkdTuS6bvivmbRiQHGukiM/KVlYqOOuqofp5dYl2A8+cdKS1VEraeo55D9pEyf9rbcc557vpeKLMgpHarEIvRUIHM7Jj6BKxsVR6bLN2+6ajetO9X+paZz8xzp8WMJWOpSMax8Dk6J1qqni/DhWTSiUQikUh0KZJJJ9Za1PmMXIJ0zJgxkuLyjMwNrdMhLmG2Yn+Vc40dzepiF4lEItEf5Es6sU7B1c1effVV/fCHPxzh3iQS9bCksCu9SVU5R5aUjALDKBBCUzPN3UzZioIj3Q5Ny/7sK72QddVp3mZAGOu3U9LU5mjWTKf7iUIslFRlAQ5K4Q61YElfyJd0Yp3EhhtuqH333Vfz58+XVKluRTe5wYeDyzTah3jyyScPXacTicQ6hxF5Sf/zP/+zZs+erfvvv18bbbSRDj74YH3ta1/rXdmddtpp+ta3vqWnn35aW2+9tc444wwdffTRI9HVRBejaR7ttttueuSRR3q3f+WVV/ShD31ICxcuHKkuJxL9wqOPPtr7fweRmXWahUaCOJGkrcFAM4OuHgrzmA1HpTK9n10/5d8dIOZ71MemfCcZNgO/nOZl5s3AzyhV0mPF1C7D1gimkTk1biQwIi/pl156SZ/73Oe0zz776He/+50mT56s008/XRdccIEkaeONN9bChQu100476e6779ZBBx2kHXbYQX/8x388Et1NdCma5tFPf/rT3m1XrlypSZMm6fDDD29pY8qUKbVtn3vuuZLaa/CmdnsikRhONL6kv/rVr+pHP/pRb8CNJM2cOVPrrbeezjnnnNU6aFnS681vfrOmTZumz3/+872/nXnmmb3/f8973qO9995bP/zhD/MlvQbjwQcf1Lvf/W7ddttt+sM//EM9+eST+oM/+AMtWLBA++2332q12TSPStx5551aunRpr086kVgTUC4KLXvrhaPZKFOzotKSFPRhuVWzVvqmKfBhUD6UPm+Wn5Sk0aNHS6oYbVSKkv5uFrZh2+5LlPLodszkN91005bjuF0zaH8+9dRTGmk0vqSnTJmiL3zhC3rxxRe12Wab6bXXXtM111yjRYsWacaMGbryyitr9xs/frx+8pOfdNSJO++8U7vttlvt337729/q7rvvTgazhmPSpEn6yle+oo9//OP6j//4D02dOlXHHnus9ttvv2GZR/PmzdNhhx2mjTfeuKO2Zs6c2dF2iUQiMZRofElvueWW2meffXTddddp2rRpuuWWWzRmzBjtueee2nPPPXXeeecNqAO33nqr5s2bpx//+Me1f58+fbp23313HXjggR21t8ceewyoP4mhw7Rp07Rw4UK95z3vUU9PT6/04XnnnTek8+g3v/mNFixY0Hu8tQU519ctWPZ2wYIFkqRtt91WUns5R7poDPphHYXt7bx/xIQjIRFGRkfCIFK7D9k+40iMhLKc7jvb8TlQqpRMm4U4aFWwD9qFTqZNm9Z2DsONjsRMjjnmmN4o2Pnz5+sTn/hExwe46667tMkmm2iTTTZpYzk/+tGPNHnyZC1YsEA77bRT276nn3667r//fl177bVhtC1xzjnnrLYZPjH0mDZtmu6//37NnDmzttJPhIHMo29+85saPXq09t133wH3v5uQcz2RWPvRszKqBFDglVde0ZZbbqm77rpLe+21lxYvXqzx48dr+vTpvS9vYsKECS2BO8Q999yjAw88UJdccokOPvjgtr9//vOf1/XXX6/vfe972nzzzftxSoluxbJly7T77rvr/e9/vxYtWqT/+q//0ujRo4d0HknSBz/4Qb33ve/VF7/4xUE5j0SiG3DddddJqgrJ2M9qRmz2SIJz2GGHSZIuuugiSRWjtj/YLNZ+Wu9vlktGzohoC/k4PbEUCtpyyy0lVTnfLGxD/zbzoiM/OVk7X2uM/iaztuzn448/Lkn6yEc+om5BR0x6o4020mGHHabJkyfrj/7ojzR+/HhJ0gUXXKBly5bV/uvrwXr//ffroIMO0rnnnlv7YJ09e7auvPJK3XrrrfmCXotwyimnaM8999TFF1+sP/uzP9P06dMlDd08klbddN/97nd1zDHHDMk5JRKJxFCiIyYtSd///ve1995769JLLx1wztjUqVM1b9683kg7qZUx9fT0aMMNN+xdXUnSGWecoTPOOGNAx02MHL71rW9pxowZvex52bJl2mOPPXTmmWfq4x//+Gq12TSPpFULvptvvll33XXXgM8hkehG2Aq1/fbbS6oYNXONzTqdhnjZZZdJalckY6QzWS5LY3L7F198UVLFTsvnuJl0VNzDbdhH7HvbzJslY8mk2TdGtEdlNR3F3U0M2uj4Jf3oo49ql1120dNPP907CRKJRCIxssiX9Nr9ku5IzGTFihX62te+pqOOOipf0IlEItFFsCDPhRdeKEnaYYcdJKnXVUgfNaO56bP2C9L+W7/IXCyG5SOpIc586bJ9qpf55cqXJ/OmWbqS+uT0v1N/3Ofkspr2lz/xxBOS1K9g6OFG40v617/+tcaNG6cJEybolltuGY4+JRKJRCKRUAcv6Y033ril4HUikUgkug8nnXRSy/dvfvObkqQttthCUmUyNttkNDerXDH32FrcziWmSbk0a0sVSy7LvJrRmjEbZr5uwyzfEeVk2syrZt4zj+d3mKtZLVmyRNKaURCno+juRCKRSCQSw48sVZlIJBJdhFdffVWTJ0/Wv//7v+uRRx7Rd7/73RZ9+3POOUdz5szRc889p0022URHHnmkvvrVr7YFYf3FX/yFpMpX7cAys1bmRxtk0gYDxVisxnCVOTJtqWLhhoPbWP2K+dLej/WjIx+04XO079mBYZ0qWHYDkkknEolEl+F973uf5s+f32uqLnHwwQfrP//zP/Xyyy/r/vvv13333ac5c+aMQC8Tw4Fk0olEIjEAXHPNNTr++ON7vy9fvlzvfe97dccdd6xWextuuKFOPfVUSa1qXcakSZN6/79y5UqNGjVKDzzwQNgefdWzZs2SVKlrve1tb+s9bgn7c6nxHTFog8JCc+fO7f2/I86prb3ZZptJatfsNnxsM2ymlXl7+56dBvbYY49J6g4N7tVFMulEIpEYAI488shehbwnn3xS22+/vT72sY/pr//6r7XZZpuF/waCK6+8UptuuqnGjBmj++67r+1F3BcmTJjQKyWa6H50LGaSSCQSiRgrVqzQhz/8YW277bY6//zzB6XNbbbZRvPnzw9rri9ZskRXXHGFPvWpT9WaxjuBRU3Gjh0rqb3GstnpEUccsVrt18G64ePGjZNUMWyLlzA/OqqF7U8z50ceeUSSBqyK2U1IJp1IJBKDgM9+9rP61a9+1S//8KOPPtpb3c0pUv3BjjvuqN12200zZszo976JNQPpk04kEokB4uqrr9ZVV12lu+++u5f9ffnLX9aXv/zlcJ9ly5Zp/PjxA9aheO211/Tggw+u9v4jwTpPPPHElu+XX365pMo/btlQ+snty7ZimOs+r82LlGTSiUQiMQDcc889mjlzpm644YZek7G0qihQVN2t6cX8u9/9rjdg69VXX9Urr7zSGzx18cUXa+nSpZKkxYsXa/bs2frABz4wRGeXGGmkTzqRSCQGgC984Qs6++yze3N3JWnvvffWokWLVrvNiRMn9vpXjYceekgTJ07U1KlTdfPNN2vZsmUaO3asDj/8cJ111lktx0+sPciXdCKRSCQSXYo0dycSiUQi0aXIl3QikUgkEl2KfEknEolEItGlyJd0IpFIJBJdinxJJxKJRCLRpciXdCKRSCQSXYp8SScSiUQi0aXIl3QikUgkEl2KfEknEolEItGlyJd0IpFIJBJdinxJJxKJRCLRpfj/6ettk+XvW58AAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-008/ses-1/func/sub-008_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1223/ses-1/func/sub-1223_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. 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Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1499/ses-1/func/sub-1499_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_hippo_sad', ket_func1)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. 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Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1499/ses-2/func/sub-1499_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_hippo_sad', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1253/ses-1/func/sub-1253_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1263/ses-1/func/sub-1263_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1351/ses-1/func/sub-1351_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1356/ses-1/func/sub-1356_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1364/ses-1/func/sub-1364_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1369/ses-1/func/sub-1369_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1390/ses-1/func/sub-1390_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1403/ses-1/func/sub-1403_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1468/ses-1/func/sub-1468_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_hippo_sad', mid_func1)" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1253/ses-2/func/sub-1253_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. 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Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1390/ses-2/func/sub-1390_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1403/ses-2/func/sub-1403_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1468/ses-2/func/sub-1468_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_hippo_sad', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_series(mid_func1, mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(239,)" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "x1 = np.array(mid_func1)\n", + "x2 = np.array(mid_func2)\n", + "a = scipy.signal.correlate(x1,x2)\n", + "a.shape\n", + "#plt.xcorr(x1, x2)\n", + "a[0].shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## vmPFC" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-008/ses-1/func/sub-008_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1223/ses-1/func/sub-1223_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1293/ses-1/func/sub-1293_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1307/ses-1/func/sub-1307_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1315/ses-1/func/sub-1315_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. 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Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1499/ses-2/func/sub-1499_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_vmPFC_sad', ket_func1)\n", + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_vmPFC_sad', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1253/ses-1/func/sub-1253_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. 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Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1356/ses-1/func/sub-1356_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. 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Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1468/ses-2/func/sub-1468_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_vmPFC_sad', mid_func1)\n", + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_vmPFC_sad', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_series(mid_func1, mid_func2)\n", + "plot_series(ket_func1, ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " T test for ketamine group diff Ttest_relResult(statistic=-1.7284446110008738, pvalue=0.11460208705196923)\n", + "T test for midazolam group Ttest_relResult(statistic=-0.7919238989812749, pvalue=0.4512459076460358)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "ket1_max = maxVec(ket_func1)\n", + "ket2_max = maxVec(ket_func2)\n", + "mid1_max = maxVec(mid_func1)\n", + "mid2_max = maxVec(mid_func2)\n", + "plt.figure(figsize = [10,5])\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Striatum" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
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Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-008/ses-1/func/sub-008_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1223/ses-1/func/sub-1223_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1293/ses-1/func/sub-1293_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1307/ses-1/func/sub-1307_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1315/ses-1/func/sub-1315_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1322/ses-1/func/sub-1322_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1339/ses-1/func/sub-1339_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. 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Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1403/ses-2/func/sub-1403_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1468/ses-2/func/sub-1468_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_striatum_sad', mid_func1)\n", + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_striatum_sad', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_series(mid_func1, mid_func2)\n", + "plot_series(ket_func1, ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " T test for ketamine group diff Ttest_relResult(statistic=-0.4844343887119178, pvalue=0.638512577891704)\n", + "T test for midazolam group Ttest_relResult(statistic=-0.5164282142034169, pvalue=0.6195234395514337)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "ket1_max = maxVec(ket_func1)\n", + "ket2_max = maxVec(ket_func2)\n", + "mid1_max = maxVec(mid_func1)\n", + "mid2_max = maxVec(mid_func2)\n", + "plt.figure(figsize = [10,5])\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## vACC" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-008/ses-1/func/sub-008_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1223/ses-1/func/sub-1223_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1293/ses-1/func/sub-1293_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1307/ses-1/func/sub-1307_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1315/ses-1/func/sub-1315_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. 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Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1499/ses-2/func/sub-1499_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_vACC_sad', ket_func1)\n", + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_vACC_sad', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + } + ], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_vACC_sad', mid_func1)\n", + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_vACC_sad', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for i in range(len(mid_func1)):\n", + " plt.plot(mid_func1[i]) \n", + " plt.plot(mid_func2[i]) \n", + " plt.show()\n", + "#plot_series(ket_func1, ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.plot(ket_func1[0])\n", + "plt.plot(ket_func1[1])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket1_max = maxVec(ket_func1)\n", + "ket2_max = maxVec(ket_func2)\n", + "mid1_max = maxVec(mid_func1)\n", + "mid2_max = maxVec(mid_func2)\n", + "\n", + "plt.figure(figsize = [10,5])\n", + "labels = ['','Ket_ses1', 'Ket_ses2', 'Mid_ses1', 'Mid_ses2']\n", + "x_pos = np.arange(len(labels))\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "plt.xticks(x_pos, labels)\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Compare timecourse of different regions" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "vmPFC = np.load('ket_func1_vmPFC.npy')\n", + "amygdala = np.load('ket_func1_amg.npy')\n", + "hippo = np.load('ket_func1_hippo.npy')\n", + "vACC = np.load('ket_func1_vACC.npy')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_series(hippo,vmPFC)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for i,x in enumerate(ket_list):\n", + " plt.plot(hippo[i])\n", + " plt.plot(vmPFC[i], color = \"red\")\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/.ipynb_checkpoints/ROI_timecourse-checkpoint.ipynb b/task_based_analysis/.ipynb_checkpoints/ROI_timecourse-checkpoint.ipynb new file mode 100644 index 0000000..1ec2812 --- /dev/null +++ b/task_based_analysis/.ipynb_checkpoints/ROI_timecourse-checkpoint.ipynb @@ -0,0 +1,3036 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Time course based ROI analysis\n", + "In this notebook we will take ROI timecourse in the first 30sec of the trauma script and compare different groups and sessions" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import nilearn\n", + "from nilearn import plotting\n", + "import glob\n", + "import os\n", + "from nilearn.input_data import NiftiMasker\n", + "import matplotlib.pyplot as plt\n", + "from connUtils import removeVars, timeSeriesSingle\n", + "import scipy\n", + "work_dir = '/media/Data/work/KPE_ROI/timecourse'" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [], + "source": [ + "# put functional file, confound file and event file here - this is for one subject\n", + "func_file = '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz'\n", + "confound_file = '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_desc-confounds_regressors.tsv'\n", + "events_file = '/media/Data/KPE_BIDS/condition_files/withNumbers/sub-{sub}_ses-{ses}_30sec_window.csv'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Amygdala" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=19\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [], + "source": [ + "# here I use a masked image so all will have same size - create a function that does that\n", + "def generate_timeSeries(sub, ses, mask_file): \n", + " nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4, standardize=True, t_r=1,high_pass = .01,\n", + " verbose=7) # cache options\n", + " fmri_masked_ses = nifti_masker.fit_transform(func_file.format(sub=sub, ses=ses), confound_file.format(sub=sub, ses=ses))\n", + " #memory= os.path.join(work_dir,'nilearn_cache'), memory_level=1,\n", + " return fmri_masked_ses\n", + "\n", + "def plot_series(time1, time2):\n", + " # recieves two time series and returns a graph of the two with std's\n", + " time1_mean = np.mean(time1, axis=0)\n", + " time1_std = np.std(time1, axis=0)\n", + " smooth_path = time1_mean\n", + " under_line = (smooth_path - time1_std)\n", + " over_line = (smooth_path + time1_std)\n", + " time2_mean = np.mean(time2, axis=0)\n", + " time2_std = np.std(time2, axis=0)\n", + " smooth_path2 = time2_mean\n", + " under_line2 = (smooth_path2 - time2_std)\n", + " over_line2 = (smooth_path2 + time2_std)\n", + " plt.figure(figsize = [10,5])\n", + " plt.plot(time1_mean, \"blue\")\n", + " plt.fill_between(range(120), under_line, over_line, color='b', alpha=.1)\n", + " plt.plot(time2_mean, \"red\")\n", + " plt.fill_between(range(120), under_line2, over_line2, color='r', alpha=.1)" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "KPE008\n", + "KPE1223\n", + "KPE1293\n", + "KPE1307\n", + "KPE1315\n", + "KPE1322\n", + "KPE1339\n", + "KPE1343\n", + "KPE1387\n", + "KPE1464\n", + "KPE1499\n", + "KPE1253\n", + "KPE1263\n", + "KPE1351\n", + "KPE1356\n", + "KPE1364\n", + "KPE1369\n", + "KPE1390\n", + "KPE1403\n", + "KPE1468\n", + "KPE1480\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "\n", + "ketamine_list = list(medication_cond['scr_id'][medication_cond['med_cond']==1])\n", + "ket_list = []\n", + "for subject in ketamine_list:\n", + " print(subject)\n", + " sub = subject.split('KPE')[1]\n", + " ket_list.append(sub)\n", + "\n", + "\n", + "midazolam_list = list(medication_cond['scr_id'][medication_cond['med_cond']==0])\n", + "mid_list = []\n", + "for subject in midazolam_list:\n", + " print(subject)\n", + " sub = subject.split('KPE')[1]\n", + " mid_list.append(sub)\n", + "#mid_list.remove('1480')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_amg', ket_func1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_amg', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# mean and std - plot timeseries\n", + "ket1_mean = np.mean(ket_func1, axis=0)\n", + "ket1_std = np.std(ket_func1, axis=0)\n", + "smooth_path = ket1_mean\n", + "#path_deviation = 2 * ket1_std\n", + "under_line = (smooth_path- ket1_std)\n", + "over_line = (smooth_path +ket1_std)\n", + "plt.figure(figsize = [10,5])\n", + "plt.plot(ket1_mean, \"blue\")\n", + "plt.fill_between(range(120), under_line, over_line, color='b', alpha=.1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# mean and std - plot timeseries\n", + "ket2_mean = np.mean(ket_func2, axis=0)\n", + "ket2_std = np.std(ket_func2, axis=0)\n", + "smooth_path = ket2_mean\n", + "#path_deviation = 2 * ket1_std\n", + "under_line2 = (smooth_path- ket2_std)\n", + "over_line2 = (smooth_path+ket2_std)\n", + "plt.figure(figsize = [10,5])\n", + "plt.plot(ket2_mean, \"blue\")\n", + "plt.fill_between(range(120), under_line2, over_line2, color='b', alpha=.1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.figure(figsize = [10,5])\n", + "plt.plot(ket1_mean, \"blue\")\n", + "plt.fill_between(range(120), under_line, over_line, color='b', alpha=.1)\n", + "plt.plot(ket2_mean, \"red\")\n", + "plt.fill_between(range(120), under_line2, over_line2, color='r', alpha=.1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Calculate correlation between first and seond session in this timecourse. \n", + "cor_ket = []\n", + "for i in range(len(ket_func1)):\n", + " cor = scipy.stats.pearsonr(ket_func1[i], ket_func2[i])#, rowvar=False)\n", + " cor_ket.append(cor)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "np.array(cor_ket).shape\n", + "np.mean(np.array(cor_ket)[:,0])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_amg', mid_func1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_amg', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_series(mid_func1, mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Calculate correlation between first and seond session in this timecourse. \n", + "cor_mid = []\n", + "for i in range(len(mid_func1)):\n", + " cor = scipy.stats.pearsonr(mid_func1[i], mid_func2[i])#, rowvar=False)\n", + " cor_mid.append(cor)\n", + "np.mean(np.array(cor_mid)[:,0])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# removing one subject that has problems in data in session 2 (1351)\n", + "np.array(mid_func2).shape\n", + "del mid_func2[2]\n", + "del mid_func1[2]\n", + "\n", + "##\n", + "del mid_func1[4]\n", + "del mid_func2[4]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## generating boxplot to show the activation around the peak (3-15 sec)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# before that, lets see where are the global maximums of each subject (location = second in the script)\n", + "ket1=[]\n", + "for mat in ket_func1:\n", + " print(np.argmax(mat))\n", + " ket1.append(np.argmax(mat))\n", + "ket2 = []\n", + "for mat in ket_func2:\n", + " print(np.argmax(mat))\n", + " ket2.append(np.argmax(mat))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid1 = []\n", + "for mat in mid_func1:\n", + " \n", + " mid1.append(np.argmax(mat))\n", + "mid2 = []\n", + "for mat in mid_func2:\n", + " print(np.argmax(mat))\n", + " mid2.append(np.argmax(mat))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# lets plot the locations of maximums for subject\n", + "plt.figure(figsize = [10,5])\n", + "plt.scatter(ket_list + mid_list,ket1 + mid1, color = \"blue\", alpha = 0.6)\n", + "plt.scatter(ket_list + mid_list , ket2 + mid2 , color = \"red\", alpha = 0.3)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# boxplot on the first part of script\n", + "#ket1_mean = np.mean(ket_func1, axis=0)\n", + "mid1_mean = np.mean(mid_func1[5:20], axis=1)\n", + "mid2_mean = np.mean(mid_func2[5:20], axis=1)\n", + "ket1_mean = np.mean(ket_func1[5:20], axis=1)\n", + "ket2_mean = np.mean(ket_func2[5:20], axis=1)\n", + "plt.figure(figsize = [10,5])\n", + "plt.boxplot([ket1_mean, ket2_mean, mid1_mean, mid2_mean])\n", + "#plt.boxplot([ket1_mean[0:15], ket2_mean[0:15]])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# now lets built it around individual global maximum\n", + "def maxVec(funcArr):\n", + " vec = []\n", + " for mat in funcArr:\n", + " vec.append(np.argmax(mat))\n", + " maxi = []\n", + " for i, x in enumerate(vec):\n", + " maxi.append(funcArr[i][x])\n", + " return maxi" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket1_max = maxVec(ket_func1)\n", + "ket2_max = maxVec(ket_func2)\n", + "mid1_max = maxVec(mid_func1)\n", + "mid2_max = maxVec(mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid1_max" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.figure(figsize = [10,5])\n", + "labels = ['','Ket_ses1', 'Ket_ses2', 'Mid_ses1', 'Mid_ses2']\n", + "x_pos = np.arange(len(labels))\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "plt.xticks(x_pos, labels)\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Hippocampus" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_hippo', ket_func1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_hippo', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_hippo', mid_func1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_hippo', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_series(ket_func1, ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_series(mid_func1, mid_func2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## vmPFC" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/binConjunc_PvNxDECxRECxMONxPRI_vmpfc.nii.gz'\n", + "#mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_vmPFC', ket_func1)\n", + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_vmPFC', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_vmPFC', mid_func1)\n", + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_vmPFC', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_series(mid_func1, mid_func2)\n", + "plot_series(ket_func1, ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket1_max = maxVec(ket_func1)\n", + "ket2_max = maxVec(ket_func2)\n", + "mid1_max = maxVec(mid_func1)\n", + "mid2_max = maxVec(mid_func2)\n", + "plt.figure(figsize = [10,5])\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Striatum" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/binConjunc_PvNxDECxRECxMONxPRI_striatum.nii.gz'\n", + "#mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_striatum', ket_func1)\n", + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_striatum', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_striatum', mid_func1)\n", + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_striatum', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_series(mid_func1, mid_func2)\n", + "plot_series(ket_func1, ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket1_max = maxVec(ket_func1)\n", + "ket2_max = maxVec(ket_func2)\n", + "mid1_max = maxVec(mid_func1)\n", + "mid2_max = maxVec(mid_func2)\n", + "plt.figure(figsize = [10,5])\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## vACC" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/ventral anterior_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=4\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_vACC', ket_func1)\n", + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_vACC', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_vACC', mid_func1)\n", + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_vACC', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for i in range(len(mid_func1)):\n", + " plt.plot(mid_func1[i]) \n", + " plt.plot(mid_func2[i]) \n", + " plt.show()\n", + "#plot_series(ket_func1, ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.plot(ket_func1[0])\n", + "plt.plot(ket_func1[1])" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " T test for ketamine group diff Ttest_relResult(statistic=1.5433996488468762, pvalue=0.15376419602078736)\n", + "T test for midazolam group Ttest_relResult(statistic=0.7009216115690157, pvalue=0.501070531766361)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "ket1_max = maxVec(ket_func1)\n", + "ket2_max = maxVec(ket_func2)\n", + "mid1_max = maxVec(mid_func1)\n", + "mid2_max = maxVec(mid_func2)\n", + "\n", + "plt.figure(figsize = [10,5])\n", + "labels = ['','Ket_ses1', 'Ket_ses2', 'Mid_ses1', 'Mid_ses2']\n", + "x_pos = np.arange(len(labels))\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "plt.xticks(x_pos, labels)\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## dACC" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/dacc_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=4\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_dACC', ket_func1)\n", + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_dACC', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1253/ses-1/func/sub-1253_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1263/ses-1/func/sub-1263_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. 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Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1464/ses-2/func/sub-1464_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1499/ses-2/func/sub-1499_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/rostral anterior_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=2\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "\n", + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_rACC', ket_func1)\n", + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_rACC', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. 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Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1403/ses-2/func/sub-1403_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1468/ses-2/func/sub-1468_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1480/ses-2/func/sub-1480_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_rACC', mid_func1)\n", + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_rACC', mid_func2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Compare timecourse of different regions" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [], + "source": [ + "vmPFC = np.load('ket_func1_vmPFC.npy')\n", + "amygdala = np.load('ket_func1_amg.npy')\n", + "hippo = np.load('ket_func1_hippo.npy')\n", + "vACC = np.load('ket_func1_vACC.npy')\n", + "dACC = np.load('ket_func2_dACC.npy')" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "plot_series(hippo,dACC)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for i,x in enumerate(ket_list):\n", + " plt.plot(hippo[i])\n", + " plt.plot(vmPFC[i], color = \"red\")\n", + " print(np.corrcoef(hippo[i],vmPFC[i]))\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Midazolam\n", + "vmPFC_mid = np.load('mid_func1_vmPFC.npy')\n", + "amygdala_mid = np.load('mid_func1_amg.npy')\n", + "hippo_mid = np.load('mid_func1_hippo.npy')\n", + "vACC_mid = np.load('mid_func1_vACC.npy')\n", + "for i,x in enumerate(mid_list):\n", + " plt.plot(hippo_mid[i])\n", + " plt.plot(vmPFC_mid[i], color = \"red\")\n", + " print(np.corrcoef(hippo_mid[i],vmPFC_mid[i]))\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [], + "source": [ + "## Build a function that takes group, regions and plot timelines + correlations\n", + "def timeCorr(group, region1, region2, session1, session2):\n", + " region1_mat = np.load('%s_func%s_%s.npy' %(group, session1, region1))\n", + " region2_mat = np.load('%s_func%s_%s.npy' %(group, session2, region2))\n", + " if group=='ket':\n", + " group_list = ket_list\n", + " elif group=='mid':\n", + " group_list = mid_list \n", + " for i,x in enumerate(group_list):\n", + " plt.plot(region1_mat[i])\n", + " plt.plot(region2_mat[i], color = \"red\")\n", + " print(scipy.stats.pearsonr(region1_mat[i],region2_mat[i]))\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(0.4480781783740552, 2.869739194878977e-07)\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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bi382FH6hADz33Jk/bxUMSITf2+RAb7MDx6fiOD4ZR7ZQxK2Xks3DBs9UtoBT4RRGgqlSFpgq9u2T/+YTAsbHgZYW+tstfZfKQW/bNuDxx+nvc+D6LAQSUsbTay5rU42psZz6uhR+PItGh2lW4TNfLAThq7VMKfF+D6BbFMXLADwJoOoaf1EUvy+K4gZRFDf4/Rf3ZtV7RkJYpygvsKRBXtDRwSv8b30LuPdeOeoPYNOyRjQmIxAKBaC9nTqjGuFv3w684hXAU08hlFQs6+YVPgAEqlfxu1KqpjmnfHzpRren4nURPgC0eSz1bZzOPPwzSSx79xLJLV1Kvxdhu8m54PhkHI12ExrsJvQ1ORBJ5Uq22w0rmmDQCSVLh18t/UJ/dfuuZOcAssJPJIjAmMJ3SSW7ldf+858HvNKMVVE07HzFH/aPIZ7J481XqetYlmJZU+GXCD+zaHYOsDCEPwqA/6QdAMb4A0RRDIiiyIa3HwC4YgHOe0FjOpbBSDBVUV5gSaNM8mV1dCIRIJcr64yrWl3oy0kdrq2tOuGzqXV/P8LJHDy8SmEdtkfKi1ebdX3ta8Cf/oRWtxVtbgt2D8+d8D2p2KwBW4YWt7W+6pyLaekcPQr84AeVjzM75847Se0nz24d9P7pOHqaHACA5c1OAMDDe0/BKsV4Wj3ytpGM8A06AS8M1CjPu3cvCQiTSSb8calsA2/pAOWEv307FfD7xCcAg+GCUfg/3zGCviZHRV9lcFkMMOqFylx8VQ8/u2gBW2BhCH8ngD5BEJYKgmAC8CYAZQnIgiC0cv/eCeDIApz3ggYjTT5gCwAOs6E0RWznrJ7SzfPii6WHdDoBr7DTTSbWInxWvGlkBOFkFh6bQuGbzUBHB/2vDNymUsCnPgX8+MdSe72l2ENdkG70dqRmDdgytLotCCSys+8itFiWzuQkreB973srF7Jt2UKzoZUr6f+z6OOLoojjkzH0SYTPfh+diOGSVif0OgFtbnnl8sBUHDoBuPXSZmwbmKm+uG3vXmD9eiJ3ZunUQ/j/9m8U/P/gB+n5C0DhhxJZ7BsJ43Xr26vaMIIgSKtt67d0FgunTfiiKOYB/C2Ax0BE/itRFA8JgvAFQRDulA77e0EQDgmCsA/A3wN4x+me90LH7uGQtIlCpepd0mhDs8sMi5GrT89unu3by45dbyCFOWzxyISv7MgS4RdODiGRLcBr4xR+OEydk9lrSoX/0ksUmJMeX7/Ei7FIGuNcueRirSCu1O5LrcW6fUtWknmqVoXOfF4m44Uk3UwG+Ou/BkZH6f8QN7gVClS75/rrq1saZxDT8Qyi6Tx6JaL3O81wWSgYyArs8dtGDkwnsKTBhhtWNGEmLpfkLkMySbObdetI5c9F4R87RtahwwF4PBeEwh+T7vOljfaax1E9ndoKXxRFBBKZRaujAyxQHr4oio+KorhcFMUeURTvkx77jCiKj0h/f1IUxUtFUbxcFMUbRVE8uhDnvZCxZyiMS9vc5aQu4e517bhng8IvrEL4ywsx5AUdnovqifBTqfIbDZAJf5jqqniUHr7bTcoMqFT4W7eWPX6FVPBs9xCptyPjUVz62cewtYonXJSUTZ+p/lzwVonwx2vV4OcrEC4ksfz93wMvvADcfTf9zxP+gQM0QN5wg0z4Z1Hh90/KGToAKc0+ydZhQqLDY8VkNI1coYj+qTh6mxy4ppe+6xf6VWydgwepNtHatWQTViH8FwPS98l//pkZ+T66QBQ+Ex3N7sq6TzwaHSoVM2MxWh9jMgHxOJLZAtK54qKVVQC0lbbnJHKFIvafClf1BN+2uRsfvXVF+YOMxE+eLCuf4AlOIehswAuDITmDQmnrSESPYSL+Cg/f7aYMH6CS8Ldto9+Swl/V5oLFqCsFbn/0/Ams7d+Db1ZJ9StEqN1Lhfpr/JRtq5iqQvo84c+HdPN5siD4wSIQoNWzf/d3wN/8DT3GEz7LK9+8WV3hnmH0T8sZOgzM1rm0TVb4RZFy8QdnEuhpcqDdY0V3o019kN67l36vXUsKn7d0jMbSffKZZySbkH1+USwn/AtE4bPtNtUK/fFotJsqs3TiccDppJ94nFt0dY4r/Isd208EcGxCZfo7T6gtuJoVsZi8uIpT+cLYGNL+ZmwdCKDQRGl4FYQvKXzD+CkIYhFepYfvdlOQzestt3REsVzhiyKMeh0u6/Bg93AI4WQWA3/agl/88l9gfOZp1ewdUVL4rWL9S/yZpRM/NkBtY4MOj3oU/uRk9cHgqaeAj3+c6sIwsFjH9dfLmSY84bNr09qqrvCPHAG+/W36uf/+RQ/oHhmPwmkxoNklK8bNPY1ocVmwooWUPkv5ffFEANlCET1+GhCu7vXhxRMqJa/37gXcbmzJ2vFURE/3XSwmp2QKAkRRxEhBuofYtY/FaBC9wBT+RCQNQaDNiWqh0WFGUE3hO51UjiIex0yClVXQFP45i3gmj/c8sAtf+/PCuVTbT9D+tVeo1IOviliMiMhgKLd1xsZgWNKBSCqHAZ2k9HjCj8ep43V2QpfLwZcIw2NTKHyPNPAoV9sODlI53OXLqTNLHXj9Ei8OjUXwvy8OoTVAU/7OQgLf2zJQ3mZRhCFJxOxM1j9gOi1GOMwGFI69TJlJBw9WHsRSMs3mSlLP5YD77gOWLAE+9jH1k7BsG+bVA7KabW9XJ/xgkM5ntaor/I9+lGYHbIbADyaLgBdPBLGxu6EsNnLX2na8+C83laxCFvh/9mX6Xtls4NpeHxLZAnaeDJa/6Z49wNq1+P3+cTwalN53fLxs0VU0nUdKZ0DWYJI/P7tvFlDhn5iO47ZvPDenDcIXGpPRNBrtZhj1tam0wW5CIltAKsslGsRiFM9wOIBEojQgLFbhNEAj/NPGb3ePIpbJL2jVwaePTuGSFida3fVlrUAUieCamqhKIU/4p07B09MNANiakFbv8YTPVOs11wAA2qLT8PI3HAvaAhS45RU+U/d3SrF5zsfPFUR8+y/9uNJIKvamdiueODyJ41wgsJhMQSeSghTmqPZa3BZkJyTrakqlxC9T+G1t5cQyMQFcdRXw6U/TdTtxQv0E8yH8QIAsDUFQV/iTk1RYjJ1zfPF2oGIWzeaexprHMYX/3HH6XpnCv2GFH16bEfc/NygfXCgA+/cD69ZhPJLCmE1671Onygg/JAUnExZ7dcJfAIW/fzSCI+NR9eDyGcJENI0W9+yKnBVDK7N1mMJ3OMjSWeSyCoBG+KcFURTxwNaTAGQv73QRS+ew82QQN6xoqv9FiQSRl9NJZLZjB3XOVAoIhWBbugRLGmzYFRVoBsATPvPvOcJX9fCBSoW/bRvdrDfcQP+XMnVoRpDOFXGtha7LZr8RVqMe3+VU/pF+brlGUKEkZ0Gr2wKRDT5qJZ+rEf6DD5JK/dWvgNtuU68PlEwCO3fS30rCFwSyLtisR6nwWaxDjfBnZqg93d3kdy/iSvKtUh49C8CWkMuVlUOgbSPNiKbz8DvNpZWiNpMB77pmKZ4+OlUqtIZTp+jarFqF8Ugakw6pqN/YGN1TEuEHk0T4MZO1kvDZ9fF4SKSolV6oE5FUjs5Xrdb8GcBEJF2KKdUCy60va6uC8GcWuXAaoBH+aeH5/hkMTCewvNmBcDJXPl2b73sen0G+KOKVl8yB8FnA1ukENm2i/48elTt2WxuW+uw4GU7RxhQ1FH5nIgCbVEoXhQJ1yloK/6qr5GCw9Fyjw4zuRht8DjOWpojIbZkU7rmyE7/fN4bpGCmZnfuH5PcKzSF3HxQk07FVv2qEzyydtjZafcxKQkxMENm+/vXVC8Jt20bEaLdXEn5zM73eaKSOqlT4DRIJ6vX0en6wYUFLQaDZmNrMZL747/8G/vVfS/9uHZhBg92EFVJWTgk//CFZcFyMo91DhNXrd5Qd+varu+E0G/Cdv0iDtPRZRK8XEzzhnzxJn026D5jCj5hsEGspfOC0spgY4VfdTeoMYDKanjVgCwANavV0lAo/noXdpIfVVJmZt1DQCP808MDWk/A5THjXNUsBzJImWCeePjoFl8VQUsl1gSf8q66iv3/1qzILorvRhqGZJETl4quRESKg1auRNVuwNBmQPV/WGZUKn1lI+/cDV1+tmrJ53+vW4Jv3roWOtSEaxds2dyFXEEvb6u0/Kj1ns82Z8FvdFljCNQifV/j8Z5mYILIVhPLPw2PLFkqXu/POSsJv58pENTSoWzoMfE34ZJJmXOx55eB5uvjd74B//3cgk4EoitjaH8DmnsayrfYA0KrqRKLMymIlp3uaynPJ3VYj3ra5C48eHKdNVKTPkrTYkcwWkDDbUHA4gd276QVM4UuEHzXbUGS2jZqHD5yWj18i/NkUvigCn/1sdftunkjnCgglc3UpfJ+k2mfi1S2dYGLxNi9n0Ah/nhgOJPHU0Sncu3EJuqRFF3Ut96+BYlHEMy9P47rlfhhmCQKVgSf8vj7aU/QLXwDe9jZ6vK0NXY12xDJ55HxN5QQ5MkId1WhEoKEFHXFO8bLOyDqn30/KNxYjy6NYpBRElUVZ1/T6cHWPTybMWAw9fgeu7fXh59uHEYhnMDwsKdwlS+ZM+C1uC7wJqX21PHy2EIgR7+SkPCPx+9W3QNyyhRYWrVpFRMXqEykJ3+stt6KCQVnhA2TrsGvIZiOM8Baa8NmAsn07BmcSmIimcbWaf8++e57wJR9fqfAB4N3XLoXZoMN3nxkoXcMZnUxKuaZmOR2VefjM0jHbUQxzCt9gkK0uJiJOw8eXFf4sQduJCeoP//Vf8z4XQDOXm/79mZLFVW8OPiArfKWlk7XZkbXaJA8/u6gBW0Aj/HnjmZenIIrAGzd0lhYCjZ0m4R8ai2I6lsGNc/HvgXLC1+moXsm3v00kqtcDHR3o9lHdnainsdLD76RFXFMeP1qiHOGzzsgrfICI6sEHqQNv2kQK3WarJLB8Xg5MSmTx1k1dGIuk8fnfH4aVbY7e2UnPz8HPbXVb0JDiSFwJ3tIBZOKdnCRbBkDIJpEPb+uk0xT0vv56uZwEm6WoET4bqESxtsJXKtyFJnw2wP3lL6U6ONf0+CqPq0H4PU0OWim8Y0fpuUaHGbetbsXz/dOlzzIJmZRSTa3AkGTNlRQ+EXHMZAci0ucPBGQ7C1hQhT+rh8/uBRaIr4GP/9++ymwyCUcmohiYTuAZaSvPyVh9OfgAYDfpYTboEEhkIYoiDp6KIB+J4oEDATx0PAJR8vAXa6crBo3w54mTM0nYTHp0eK2lvPCJ07R0/nJsCoJA2wXOCTzhA0TyH/oQ+fjPPAO43eiWZiHTdi91+qKUXz0yQgobwJjLj6YQR56sM/IePkArTe+/H3jf++RsFTUCGx+XzyO18eaVTWhzW/DIvjH4QR2WnX8uaq/ZZUFDUiKTYJBmHjwYATI1zyv85macCqfwmeelgY9v944dVD6BJ/zRUVLPwWB1wk8kqA084fMKX0n4C+3hc4S/bWAGbW5LqZR2GVQI/+peHzZ0eXFZhwf48IeBf/mXspf0NTswGc0gHaDPOlaUSSnp48SJIksnZrZBiHKf38cNQAuq8Osk/D17ag4whaKIh/eO4Rc7hlWfn5QSM9h+wGxGX4+lIwgCfA4zfrVrBJd97nG87j//AkM+h5Z2P8bzeiCRQCCWXtSALaAR/rwxHKS6I4IgwGLUo8Fuqq9kbw08fXQKl3V45r7wQkn4DG1twLXXAgA6vDboBGDc4qZgbCBAqnRkpKTwh+0+uCMBuQaNkvBZh/34xynX/DOfkc+lFgBldo5OVyJcg16HN19FBL+W7aYlnX8utk6r24qGVARFvfQeSvJMJKiNbECKRGjwmZxE0d+ED/9iD0b1NAiKPOFv2UIq9BWvKFf4LABejfCZZaO0dGop/Hi8rJz1aUFaxCVu24bdR8dwda9PvTaRCuEvb3bi/z5wNWXoTE5WzJiW+eg6hcbpM4wU5SyuWIMkAgShNHMKJrPQCWTp6BNxuu4zM+WD4QIo/GjJw5/F0mH9o1iUU4lVcDKQQCZflPaMrlwUx/o3I3w2ANRD+ADwmsta0eN34K51bfjqrcsAAH91zXL0LWuBIIqIh6OLmpIJaIQ/bwwFkmUKqsVVZ432KpiOZbBvNPGHkQsAACAASURBVIxXztXOAaoTPgeTQYd2rxUv26X3376dFGsqBXR2QhRFDFolsmIWRjWFPzlJm3Q3cW1VU/iM8Ht6yrIx7rlyCZqcZlzZKBHHPAjfa9HDm4oh0NFND6gRvt1eng0SCgH5PLZE9dg1FELPKnrt9CC3icfWrcDq1UTmjNxHR8tz8EuNUCF8paVTTeFXK0Y3XyQSwNKlELJZLDu+v7THcBkKBbkdagFMUaT2KK7lUh95+9GpACAIGMkIMBuIOsJe6R7w+8niAyn8dq8VUbMNgijS/VlN4fOEPzQkzwjrQN1BWz5GU8PW4VfLbx2ozN5iin5wJoF0roCJSBoWow4ua327U33y9pX4zQeuxpdeuwZ3L5c+v9OJG68g8rdm0pqHfy6iWBQxFEyWgrUAecqnQ/hPH52EKAK3rGqe+4vrIHwA6G6044m21UTU99+PJ/8s5ZovWYJktoARh9QhRxR1UPiVtgApuY9+tPzN1Qifvc+qVWUF2/xOM3Z86masdOpK5wcwJ8IXwmHoxSKGW6mzVPj48ThlP/DEIh3z27EcXn9FBz74+o0AgLF+LhNnaIjSFgG6nm53bcJPpWhGxIK3SkuHV/iCUG6BAQtK+BObrkde0OEtyRO4Y01r5TEzM0SoDgetklaSazhMcRR2nISuRhsEAUhOBwGXC+PRDJZJAd6QW7onWuXzBZNZdDfaETdLgigSmd3SmZmhstL/9E91f2RG+OFkDnllCQgejPAbGmoS/tGJGHQC1bJRKxzH+ndRpMFhIko5+DWrvObz6ls5cn3W2kDXwpZL110ifL7QCH8emIylkc0XyzYgafVYTsvDf+LwJNo9VqxsrU3aqmA3j712idauRhv6Izngne+E+Ic/4MVfPEpPdHYilMxi3Cl1SLYYSxm0dTiAO+4AvvlN+ptHNUvHZiNCV8u3jsfJ7mGB1bksvpKIst8vbcWoJHym8PkyxdIxcXcjPn/npVja0468TofAEKfwlYHZjo7ahA/QQKVm6bjd9N0wZe31UnwFkGdH8yH8J58Edu2S/y8UgEwGvxsv4HjnCrx6+khlOiYgX6ONG2mQUq70ZW0pFsu+C4tRj3aPFZlgGHC5MBFJo6vBBqNewLQK4YcSWSxpsCFuke7HcFgO2jIYDOXrFAYGiBz/4z/qCq7mCkUkswX4pRo2bLGXKhjh33YbXTe+zhKHYxNRdPvsuLbPh60DgYr9ACYi6ZK9dWQ8Wl8O/m9/C6xYUbZPBYBykSb1pZ/eswo3r5yH4JsDNMKfB4YC5O/xlk6r24rQPBdfpbIFPHd8Bresap7fXpasJoeu9tfZ3WhHJJVD5M1vh1Ao4B3PPQgAKLZ3IJzMYcylovCtVlpkBJBC/cMfgDe+sfLN/X7qSHz1ytFRIkyXi9qozHdnKpyR5FxSM6XBZb9HIuBqhG+xUPnZaBSiRHBdq3pgNxsg6HRIODxIjUuvjUbph3n3QDnh8wMIUE741RQ++5xKwmMKf66B22iUSjN/7nPyY5J/nzCY0fra26HftbMy1RSQr9HmzfRbaevwbamwdewoRCKk8CNptLgtsJsNmHJIn1ci/EJRRDiVQ6PDjIJD+vzDwzQo+RRZQx6PLCrYPedyAe94R2UJbwWYumcEXDNTh73XHXfQoFLFxz86EcMlLU5c0+PDTDyDlyfLr+FENI0N3V44zAYcHo9KZRVmIfyxMbrv+XgX3yaO8LvN4tzSsecBjfDngWGJ8Ls5S6esZK8Czx+fQTZffcr53PFpZPLF+Y/ubAHHLGDtPeFpxfDaTeiITiGrM+CUyYlwMoe00YKct0FW+HxZhdmgZlHwhF8sVlaHZISvVpdmNkjnOWhshGi1qls6bMYjZctMHqfPtfZKubR0vtEHQyhIC2KYiq9G+O3tclohUJ/CB9QtjflaOj/8IX3f/IxJUqxNrQ3wvOZVRGrPP1/52tkIn2+LgvCX+ewQojHkHU7EM3m0ui2wmwyYdHhpQJVsuUgqB1EEGmxGiOzzD0hpjkrC52McjPD/93/p/qtW1E5CifD99B3XzNRhg9+tt9IMS2UGkczmMRxMYkWzC1f30iDG7+ubzRcxE8+g1W3FJS1OHB6LYjKamT1gy879xBPy5vaAKuGrDtILDI3w54GTgQQMOqGUfw9U35TjwGgEb/3hdvzpYPVCWU8emYTTYsBVyxqqHlMT9RK+lIs/FEji1+teTe11+dAfSJYWyxQ6OssV/ukQPssAYkpXqdoY4ZvNc19tK51n0uxEUS3FMZGQO5KUD3/q2CCyOgOuubKvdJipuQneZBS7TobkILOS8CcmqHwAb+cAlYTvcBD5MfD1dNQ87LnW08nngW98AwAwM8HZXxLhWz1OsmsA2oxFCd7S0enmpPCX+R2wphJUHwe08M1hNiBaEIhAP/xhALLS9tpN0HkUhM/PfoByhT88TPfAHXcA7343bZlZYwN4WeHTd1wzcBuPy7X6r7hClfBfnoxDFIEVLQ50eG20HwAXuJ2KpSGK1M9XtrqwfzSCbL6IptkIPxajc7e00Gpf/nFAI/zzAUPBJDq81rLpV6u0eGU8XK7wXzxBym8srB7QLRRFPHVkCjesaJq1xGpV1En4HV4Kvu0dCeMHjZcj4fRgzOVH/2QcYYnwha4lVLddFMtLI88GZXkFtuiqo0Num9LHZ1YUULlqdTZI5wnZXMg0+KtbOkBJ4YcHRxF1eeHnOqmtvRmN6Sh2nQxWJ3xRpDIStQifL5zGUEvhC8LcF1899BAwNISgzYVsWM5uyUibyDi8bnk7SrVA4eQkDUg+Hw3Ec1D4S312OLJJTIE881a3FXazHolMgRbfSdeCCYcGuwl6r3TvsPPMpvA7O+m69PXRmoYqXjtQqfA7vv3/ym0uHkxYAFQzaufOisHk2ATdmytaaJCm/QCCpWBwKedeIvys9PisCj8Wo8/5yU8Cf/kL/bDHAbkePmvnIkMj/HlgOJDEEsUeltUsne2DRGJTMXXC3zsSQiCRnV92DkOdhG8x6tHmtuK3u0eR1hsxev//4ju3vw/Hp2IIJakD6e+6izI4XnihvDTybFAq/MlJ8m2ZpcPayYPviHyKYz2YnkbB7kDGYELc01ib8N1u5EJh6KYmUfCXX2e93w9/OoZdQ5zCZ0FkQCb/TGZ2hd+gmKHxAWMl4QN0zebi4X/960h3duPx3k0wpWR7bGaS7jGXTyLYvr7qhN/cTKS6bJm6wnc66Xk1ws8kMVygFMRWycOPZ8pXR5cUvs0EQ4PUnmqWjtLDZ+m5apVIFWA5+F2NtL6k4y9/Bn76U/WD+fvM56PvUrH5/NGJGCxGXSkR45oeH+KZPA6O0UDAMnRa3eWJFbOWRmZ9873vJZXPyjuoKfwaA9xCQSP8OUIURZwMJNDVUL6K0WrSw2MzVmzevWtIIvwqG25v7Q/Q6lq1vOl6USfhA9RBouk8XBYDev76NuTXXYHjU3GEkznYTXoY7n0TvdcPfnB6lg4jz87O6gr/NAlfkM4ZsLlVPXzRbkcmXwBcLiSmg/AlwrB1tpUf5/PBmYzi0GgI+aERyp4xc52YV/tKwueJSU3hM8IfHyeCUSP8ehX+zp3Atm144TVvQcxsgzWTLCUIhKaJNN2M8JcvB15+ufI9uLISWLaMBnYe09NESj5fRbvaPFY4s0kM54jwm11k6SQUhB/iLB2b24m8Ti+fpx6FD9QV02EK32MzocFugjkUoPOobXnJ948q5HpsIoblzU7opeymtVLxwgOjdG35RVYrWpylUM6sWTrs3BYLFRpkVls8TvEEs1mzdM5lhJM5xNJ51WXrrW5rmaXDiBSorvCHgkk0Oy2lOuTzwhwIv1vKanhFHxVo62t2lCwdj81EqvjNbwZ+/WsiqnoJ3+2mG5hZOiwOwCt8NcJn7VZWnpwNMzPQ+X3wOcw4ZXYRQbHccVEEEgkcCOdx6Wcew9aZPDLBMJpTETiWVBK+rliEPRlD4sTJcoJn7WdQEj5fIllN4bNrx5S0ckCoRvj79lGxLx579gAAftG+HkmjFfZcGqMBIojQDJFSo59T+GNjlQSiJPzx8fJA+tQUDXgqMRE9RDiyKcRMVvgcZpgMOthVCJ+lRzbYTHDbTIia7TTYmUyVqbxM4WezFCdh6zEY4dcouxCR+pXbakSDzQhbNETfu9pAxwsLNutTIXy+lHSb24IGuwkHTtGANB5Jw2rUw2U1wGYyYKk0w29y1kn4ALByJc12sln5cUGgTDhB0Aj/XMRQkKVkVua8Kxdf7ZC2h7u804OpmLrCHw4my/L554W5EL40ULEZRV+TA7FMHkcmYvDapUHnPe8hpTQXha/TlStD3g9nbZvN0plrHr7fj94mO07qHUT2LFMmmwUKBYzn9dDrBIwUjbDEo2hMhCG0KhYkSaqzIRmlUs5KUne7ZZJQPsfazQi/msKv5mE3NakXnHvLWyjAx18vifxeDAG+NjrP2Bh93niASKmxWSLKPiko3d9f/t5KwgcoGM0gXVNVq0kio5jJVkpQcKhYOqFEFhajDlaTHm6rEXEpyFtWOI3B7Savvr+fyHoOlk4klYPNpIdRr0O7Pg9jXqqldORI5cGzEP50LINAIlva5xeg2jer2904cEqum9PqlhdZrWpzoclJA19N8OdeuZJszuPHy/usTlfa13axsSCELwjCqwVBOCYIQr8gCJ9Qed4sCMKD0vPbBUHoXojzng0MBehGUVP4LW5LmYe/YzCIZpcZG7q8mIpmKhZyAMBoMImOhtNcXTcHwt+8zIdlfjtulDZY6W2i1x2diMJjlTJMrrgCWLuW/q43aAuUK9bRUZrGNjTUVvinYenA70eP34GjovRdMFtH6jhhwYjuRjvecMMquDMJ6At5mfD4NgPwpqIwTY5XKnxBkB+rRvjBILVdSfgOB72+moft99M14f3k734XOHSI/uYVbjiMosGAuN6E1cupHVNjNJtKhIjwTW7pOrOVwryPXywSiSsJn/fxayh89t3FzbZS7rndrEciWyi7r4OJHBpsdB+5rUbEzBLBKq8NIN9bbE/iWpbO2Bjwn/9ZCrZGUrnSrHhJkVPrR1X2llYjfI5cWUmFS1pcZS9b0+7C8ckY0rkCxiOpspz7T9x2Cb73tivonz/9qfpshO+bq1bR78OHK/usVBN/sXHahC8Igh7AfwG4DcAqAPcKgrBKcdi7AYREUewF8B8Avnq65z1bYDn4aqq8zW1BMJFFOkedYOdgEBuXNqLJaUYqV6hQQ5l8AePRdOV7JRK0oUWNtLQS8nlS43US/poON57+2A2lFYp9zdQRRBHy5uWCQCofqF/hA+WEz2ddqCl8VmOFdcSGBrniZD2YmZEUvgMjRun9GeFL6i0AE3xOE3RebtBSEr5Ewm3RaZgjoUrCB+gxnU6uvMnD6yWVXCxWWjpsb9tqCl8Z95iepgU67HrxhBcOI2VzwmTUY6VE+NPjpPBTIWkgtUn3UW8v/ebtjWCQ1CX7/Etp055S21iBM7+/NuGbbGiTiM9mMqBQFJHh1piEktnSnshE+Db1zw7I9xbztZWEz5Poz38OfOQjpdLePOG35ziiVFP4NTz8XKGI720ZgFEvYFWbkvDdyBdFHJ2IVWxl2OG1Yf0SL31nt98OfOc7ledVnnvFCronjhw5fwkfwEYA/aIonhBFMQvglwDuUhxzF4AHpL//D8BNwryWlJ59DAWTaHaZYTFWbkPWIm06Ph5JYySYwkQ0jY3dXjS5iFyVts5YmHJ7O70Kwv/0p2k1pVoutRLsJqmT8JVotJvglYjea+NyyN/6VtpI5eqr638zVl4hnaYyw93d9LjVSv4+r/DTabmuCzC3xVdsRa/Phx6/AzM2idAVhD8jGqjcLL86tgrhXx6UarqrEX5vL9DVVSoOVgavV7ZO1FSs2125+QmDkvA//Wkigvvuo/8VCj9ssmFDlxcmD32ekJSdk4lK9wBTr3Y7ZRrxCp9dG/b5fT669mz2EQrRgMAUPvPWGcoUPt3nDjNdD17IBLlNPDy8wlcj/GoKn31f/L3AYkNSOyKpHFwS4bdk6POLzc1zsnREUcTnHjmE5/tncN/r1lQULlvdTgPSvpEwpmIZ9VW1bMBkn0EJnthtNrqPznPCbwcwwv0/Kj2meowoinkAEQAqvQMQBOG9giDsEgRh1/QibvI8XwwFEqr+PQBcInmA73lgJ+5/nm4EUvh0o+R/9X+kUiQMS/GATl7hj47StB4A9u6dvUF1Fk6rBkEQ0CfZOoz4ARBRPfkk2Tv1gin8r3yFVC8rhMWULq/w2c2tJHylj//jH1NNfx7svpAU/oxdIg6mSqX3nioYqNwsP0tRqnSJiNbMnKT/1Qj/vvuAxx9X+8RyATWgUuEDMnnpdJX2GF9PZ2yM9hj40IdK+wvzhJedCWDaaKNNyaVrFp0JQhRF5KNxiIJAFhrD8uW1CV8QgEsuIXsBkK8dU/hAeW0kiWibO/ylBYJ2ifD5wG04mS0JB5fViGi9Ct/rle8FvZ6e4wc81hbpHuIVvi9NbctsvoZmNQVFeRMVws9FY/julgH8bPsw3nf9MrxxQ2dF89o9VnhtRvzl2BTyRbFsoWUJLAOJXUcebBbL981Vq9QJ/zzy8NWUutKLqOcYelAUvy+K4gZRFDf4/aeRqrgIEEURgzOVKZkMq9vd+NE7r0QmX8RPtg3BbTWir8mBJsk+sf/+IdpsWrJqWM3tMkvni18k5Wsy0WKf2XCahA8AvZKt47adZmlWv58I+ytfocDjLbfIzzmd5QpfOTOppvD/+Z+BL3+5/DHW+f1+tLgsyLncKBgMlZaOYKK9BWopfJsNsFqxfFxSumqE39go2yRKsHaz45RgpNbYiC/88Sj+4Zd75Of4ejq/+Q197+9/v+q1SEzOIGp20LaF0jWLz0QQTeVhSCeRs9jKg6J9feWWjpLwASoDzZQpG0SZwmftYpDSJ7/2rleQlQHAYaZZbjWF765X4Q8MyOqeQRnTYe2T7qEoR/iNSRoYQldsongIn25aKFAmkkT4U0UapL7wix342p+P4dZVzfjnV11S2TbIgdutUuVMNrMpAwt6Hz1aOdCkUvSd8n1z5Uo6NhKpVPjnSR7+KAD+2+oAMFbtGEEQDADcAOaQknFuYPtgEDPxLDYtU52cAABuXNGEJz5yPT58Ux/+8dbl0OmEksLXTU3STSB9sSPBJEwGXWlAwMAA8D//QztJrVlD6XkMg4N0s7zvffIeosCCEH5fE3WGMoU/H7BO7XAAX/96+XOzKXy1AmqZDJHO3r3l8QzW+X0+6HQCljU5EHF6Kwg/aTSj0c4pfKOxnKC5dnujku2iFpithdkInw02Ph92nAxgxyB32/OWzq9/TQS8cqVMhJzCLQTDiFvsuLTNXbpmQjyGY5MxWPMZqifEY/lyGhjZ9axG+BMTdByv8NUKu7HBmhs8mcJPSusBcoUioul8SeG7bbMQPj/zUhK+xzOrpcMI3xULI20wYWr5ajqGt3VY2ql0zb6/m67DBr8JP3rHlfjOW9arVxaVsKbdXXtVLRtclAMNoN43V66kY0dHy9NUzyNLZyeAPkEQlgqCYALwJgCPKI55BMD/J/39egBPi2opK+c4Htw5AqfZgNvVao1zsJr0+Mgty/G2zd0AAJfVAJNBB2NAIiqpI42EqERD6Yb7/OeJlD71KeCyy8oV/iOPkDL4yU+ADRuAD3yAHl8AwmfpaCyQO28wsvza18o3RwGqK/xaHj4rZsYsDwbO0gFo8+0pq0eF8C2k8BmxsFWmSkhkFLU4Zi0xXQGe8NUsHU7hT0TSmIxlUChKt77HA9FgQGLnS1Ts7A1vkF8jCGXXQh+NQN/gpTRA6ZrZsmnsPBmENZepbDdLzWS2zuQkxSD49q5ZQ78PHZpd4dcgfKbw2ZqTBim912EyIG6xlT5/BXiLi+XgM3i96pZONIpcoYhEtlAifHsshBmbG6OtUqlsPlNH0T92TlFc4q4+D268pGnW6pRr2uVBSdXDHxyUrTSlraO8xwE5U4drU+mY84HwJU/+bwE8BuAIgF+JonhIEIQvCIJwp3TYDwE0CoLQD+CjACpSN891RJI5PHpgHHeta4PVVBmwrQVBENDkNMMalFSk1JGGg8nygO3DD5MV0tJChD81JZPYs89SEHR8HHjNa0gRAgtC+JuXNeL+t29Q3/R6LrjjDqoK+O53Vz7HbwYC1Ofhs1x+oDyewVk6ANDjd2DC7EJBkZaZMlnIw2ckpbRzGCTCH3c2olicow5hJM9vbsJDOnehsREz8SwKRRHTLHgvCIg7vdD/+tc0g2GEr9MR6UuEXyyKsCZjsDVJpCl91/ZcCtsHg7Dl0tA5FYua1Ai/qam8hPZqSREfPCiTe2Ojeq1+9t1x95lD4eGzOjosS0enE5B3yDOcCths8v4As1k6nIfPyiowwreGgwja3JgUrNR3eIXP3WfJbB4HAmmKd9RJrms6iPCNeoFmi0qcPAnceCP9rST8agqf4XwkfAAQRfFRURSXi6LYI4rifdJjnxFF8RHp77Qoim8QRbFXFMWNoiiq7K92buPhfaeQyRfxpiuXzH6wClptejjikmKRiGkkmJL9+2yWOlWXpFIuv5x+79tHZPDcc8B115EquvFGyvwIBBaE8AVBwM2rmmtObeuCyQTcfLO6inY6yy0d9jcjfLXFNjzh7+G87+lpmglJZNrb5MCkowHFYSl3QFL4CTWFrwZp4Bh3+EpL9usGI3mPRyYvHlIbU055MBjjym8E7W5Y8lnkV64qJwOuzszQqQAs+SzcbRIRS9fMnk3hpZNB2HIZGBwKhd/TQ98DT/jKz9/aSu0/eJCuqddL15VV8lQqfLu97DMqg7asjk4DFwvKs2uvnPEB1D72vdeydPJ5+e9otPQdMcI3BAMI2dy0t+3KlVUJ/8BoBEUIKNjsdfvlLHDb7LJU9o9ikXZIW7OG2l8P4Xs8cuLA+Ur4FwN+uWMEl7a5Sqlac8UykavxMTVFG5Gkcuhki66Ue6Ky6fb+/cCxY9Qhr7uOHlsh1XM/dmxBCP+MYDaFbzQS8fIkz/5ubS1X+NPTZSs3e5ocOO7rhHF6iq4jZ+k0OkzytalD4c+6IbYSjPDV7BygNNhEHfJ9M8Gtxp620IAw8ao7y1/HKdxjx2gg83dI7TcaIZrN8BSyZG2IWQhKS8dsJvHAArdqhC8IpPIPHJAXXbHHlbn40Wh58Btk2QBAPCPV9EmUK3wAOLzuOvzwHZ+SF/IpwQYENYXPLJ1gUI7hqBC+MD2NuNNLAw4jfHY8d5/tHaH3080hQCoIAq7p9WFlq6vyyfFxEmpLl5JVwxbMMVTrm8zWURJ+JlP/OpR5QiP8OnDwVASHx6N405WVqVv1oqvAqdupqVKGTsnSURK+z0e51Pv3k50DnP+Erxa05dvd2yvnhQNE+G43cO215QqfLRCS0NVoQ39TN/1z6BAVThME6KxW2EwGUqWbNskbfyghEf6E04eZWhtpcMjmi1QojxG+mkcNlEgyaJUJYyxMg3+hKGLCRAPevk03l7+OI/zB4xTL8C+RCVtwONAsUFudhax67KGvj65HMqlO+ICcqTM1VXZN6yF8u5SlU1L4XGlkBovbgd9vuE191gfICl/p4Xs81O5stiI9lBE+y8PH9DTS3gb67i65hDJgpAVafP/YOxJGZ4MVOkf9Ch8A/uOetfjOW9ZXPsGCtIzwjxwp3ye4Wt9kMzllWiaw6Jk6Fw/hT08DDz5Im2/fc4/6HqtV8Pt9YzDqBdy5do4ZHBw6Mtz5eMJnlg67qXmv8/LLydJ59lnqrCw1sLubFDEjfL2+PAf7XASzdFSUVwk9PeX1X0ZGKE1y7Vpa4BKJ0PR+1y55pSgAs0GPRJ+UWnfwIJBIIGOxwefigtDbtgF/8zfqbSspfF/tnZM4fP2Jl/HK/7cFYZPUUWdR+FNm6txGvVBS+FOxNJ5augG/W3UD9tgViQCcpTN6kjbPMfDncDjQCCI+ez4jr7LlwQL/bCP2aoQfidB9xtsuyno60WjFqmuDXgezQVci/IlIGnqdUEb4bqux5Lmr5mmwAHWt0tM84cdi5Qo/mQSSSeQbfJiKpmUyZbYOd5/tGQ5jXad3zjnvRr1Ofa8KRvjd3UT4qRRZPFxbAdRH+GeoYqbK0sELFDffTDe/Tkej8Ac+ANxwQ10v3XYigHWd3tOqaNmcojxm0WiEMDVVuehKqfAB6rBPPknPXXedrJIMBiL/Y8fk8sPn+sJll6tUxbLkV7JKgQy9vcDPfkZTW7NZ3iJx3Tp6ft8+IsFTp4Bvfavs7d09XYhZHXAePAjk80ibLLTKth6UFH4jgnVYOulcAQ/uHEYqV8AfRlN4KzCrwh8z2OHUG+B3mDEu1VsaDaXwu9WvxO9WvxI3Tis6uqTwi0URMyNSMJrPanE64SlSW1WzdADgS1+ie3zbNrLE7ryz8hgWuA2HKxU+v3BLReED5QXUhoNJtLotZeTothoRSeVQKIp4x492oLPBhi+/bo38Bh4PDUQmRUCUL6/ACF9arV0WtJ0mJW9qbcaJmQTE7h5a9MOqtbJFeEUDJqJprO30LFzOO8vB7+qS++/hw7IYURM1AM1YLRYSOAxniPAvDoWfSJBP+ZGP0M0P1Cy9yiOazuHgqQg2zXf7QQk+aXFIqmc5KfxQEm6rUR5EqhF+LkcEx+wchhUrZIV/rts5QGVNfLb6kR+oentpUGDKiRE+83/37qWFa21tlKnEobfZhWONS1A8QAqfUjLrXEh27bUo3nUX9ravqMvSeezQBELJHBxmA367X8p+UVuwBQCXXgo0NuKQpx2tbgta3BaMS5YOm+Wtbnehvwrhn5hJwByPyo8xOBxw52ngMGdS6oRvsdB1uu8+4I9/lFfwKtvHwCv8OiwdAGUlkkdUKr8ywv/elgE8d3wGR8YVM+sPflAuJcGDD+IzK1avewAAIABJREFUwl+ypNLDlzKJHB2tiKXzCDilfsosHYlAD0SojWuXeOhaLQThDw7SvWixyKqdD9xWU/iXX04zE34xH1/jZ2oKeOqp02+fCi4Owj94kIjkuutkFVNnZcaXToZQFFFzsVU9cEcCSBnMiLZ1ApOTGA6m5IAtIN/UPOGzTB0AeMUryt9wxQqyP8Lh84Pwlbte8YXTGJji6e8n73Zykoi0tZVU4EMPUWXCd7+bLC0Oy5sdOOZbAvHgASAeR8Jgrl/ht7ZC99BDMDQ01BW0/dn2YXQ12vDBG3uweziM0Yf/DHyiSqaxtADqkLkRLW4rWt3WkqUzGiLif0WfH6OhFNI5bqWmxwOkUjg0OAlXJiE/xuBwwJ6l9zGmqxB+PWhspOsLVCr8REImxhqEz4K2w8FURV0ot9WIfFHE15+g4HEyo1iNevPNwLveVdku3tJh6aFLl5YsHatRT2sSpOcaummfg8EUqD+MS3tIS4S/K5CjAmmtroUrYzA4KNeL8nrpOioJ32JRr8GknJGzvrBrF8Wb7rlnUdT+xUH4LMNj7dq6Nlfg8eKJAEx6HdYtUcmxngMc4QCm7R5aETo1hVGlGgoESsv8S1i+nKa6Ho889WZYsYLU/4ED5wfhV1P4PJjiGRigDsvXSF+7lvYD5St5clje7MQxXxf04TDE/n5E9WbK0JkDGu2mWT38/qkYdgwGce/GJXjdunYIAvCrmH3WMtLjkTRaXRa0ui2lxVejoSSanGasanXRxGaGU53Sfdp/7BQaciqE73TClU/j767rhi6XVffw6wXLCFMqfKC8pIEa4Zv0SGTySGULmIlnykUM5EyaBrsJr7ykqaJibFUoLR2Hg9okKXw3F7AFgNYeCvoOTico7ZEP2ppM2D2exKpWFxU9nKul86c/UfVaJU6eLIslYdWqSsKvt2+yvvD+91PbHn20sn8sAC4Owt+3j4JDXV100ypWMfJ4oX8G331GzhR58UQAazs9c15spYQ5OIMZuxcBmwfizAzGAvFyNaS2gYbRSKP9q15VmePNMnUGBs4PwlfWxOd3u2JobKTvqb+/ckNx5uPffntlRgdo8dXLfmkNw5Ejcg7+HNDomJ3wf759BEa9gNdf0YFWtxXX9Pjwuz2j6gFJCdl8ETPxDFo9ZOmwxVejoRQ6G2zo8VPH7p/iFJ1E7sMnTmGpIU8xDT4w73BAl4jjY9dKA+J8FT4giwmlwgfIXhDF2pZONo+RkEohQFCdKJ0AfO2vL0OH14pEtk7CV1o6Pl9ptXYZ4Uu2U3NvJ4x6AQMzcVLanMIXHQ4cOBUh/x6Yu6Xz1a9STSce+TzFCdQIn90LcyF8FhC/5BLgxReBjRvrb98ccPEQ/mWXEdGzVYxVFP7Pdwzjq38+ihdPBBBL53BgAfx7ABAmJxFzN2DS6oYgirDHI7h+BdfB1Da5Bsh7/dGPKh9nhA+cX4TPLB01hS8IcqYOv0UiAFx5Jf1+//tV395q0iPRS5k6gigiZZyHwneYMaNi6bx4IoAP/uwlvOF7W/Gz7UO49dKW0mDyunXtGAmmaBP0KpiMUhnsVrcFbR4i7bFIqlRaY5nfTvuk8D6+pHBHToyh25CrXMXrdNI1ZMR1OoTPYiR8pgy77gMD5DcXi1WDtolMvjLrTMLmnkbs/tdbcOMlTapbIlaFUuH7/aW1HBUK32iE3uNGV6O9UuHH4yjY7EhmC7iE5dLPlfBjMbon+e0gR0aoWBqzdAAi/3hc5pa5EH5fH/DLXwJbt5YPIguMC5/wi0UifN4PVxZm4jAjLXv/8qNHsGMwuCD+PQBgchIprw8vxsnPe98lDlzNlzJQU/gAkaKyMBZAx7LjzwfCr8fSAeRcfKXCv+suSk+9/faqp2ju6UBQWtGakPZenQuqWTrffWYAW45NQycIuPXSFvzDTX2l5169ugUWow5/3D9e9X3ZLmgtbitaXPRdjoZSGA+n0eG1wmLUo8NrxcC0TEJH09Q11zpErLEVKy0jh4MIhRHX6Vg6b3oTZYPxImLVKrrvtm9XraPDYDfrkcgUSllnyqCtIAi0VzJocMgVRNpYfjaYzXR+XuG7XEAyiVgiU5aDD78fEAQs9dnJFlMQfs5KbSrVwmGEz+fM10I8Tqqdt2tYhg5Pzm3Sfsms7pNanKoaBIF8e7XyHAuIC5/wT5ygL5df6acszMRhJp6B02LA/tEIvvzoERj1wmn798jngZkZZH1+nNSTEnvncoUiq0b4tcA66PlA+PUofIAU/uAgdSiHQ36dXk+B6xrpp33NThxtILtnXgrfbkYklUOuIBOBKIrYNxrGay5rw4Pv24xv3bsOfdxm13azAes6vXiphsJn+xzzCn/vcBj5oliy9Xr8DgxIls6J6Tg+8TTNcD6ywQ9DNKJO+JlMqWzxaSl8o5E2u1E+tmFDHYTPFH4KVqNevd4MO9bEFmrVQfiALMzYymrp/LlQpFzhS1bUMp8dQ4Ekii0t1OZkEojFkJFq8jezDcfZfZdKoQKveQ3wuc+VP8buWX5DIj4Hn4EFv/mA8TnWNy9MwhdFefRmJYaVCr8q4Wdx5+VtuLTNhYHpRKV/Pz6ufqPUwswMIIowtLYg5SFSN85MVx6jZunUwvlE+EqFX0399PbSALltG6n7OawvYJk6gFRWod4sHQlsgGAlAgBgKJBEOJmjdL4qWN/lwZHxKFJZdSKbkGrntLgtcFuNsBh12CltcN/BEf6JmTiS2Tw+8L+7EbcRuTnTCbpXlYTPridLnTwdwq+GTZuA3bvlc1SzdLJ5DAcTWNJgQ62N7NQ2TKkJJsx4Dx9ANhSWB3Oe8P12ZAtFhPjUzHgcSTPNqsoUPlBp60xOkoXKlx8H5GwZJeHrdOUlIdQU/jnWNy88wg+HgVe+knYPAojwdbryfOMqG2Zn80VEklk024z41B2UV7tZaedceSXwr/86tzZJxdJuumENfvBPkiXB5zgXCtTuC1nhm82kGmdT+CxTZ8+e6rntVdDXRJk6AJA0WSu2rJsNLG+fz8Vn9VdKAT8VrF/iRb4oYv+ouogYC6fhMBvgshghCALa3FYclvLRO7xERr1NDqRzRfztz/fg2GQM//pWqQxEKKRO+OzasQqhi0X42axc2qOKwi+KwMuT8YoMHSXUtkSsCa+XBFYiIXv4AEzJuPzdcoS/1EfXZNQiXavxcSAeR9xogVEvyPs9VCP8J5+k38q9l9UI/+BBsnP49GCm8DXCP4Nwu4lAP/1pmu7u3UvEyPvgVRR+IJHBvz36Ddz7j2/G1T0+/ORdG/HuVyyTD0gkaBHUY4/NrU1SpzS3t6G5q5XsCZ7wQyG6sS5kwmebmUejcidSazfLxRfFORN+b5MDx5ukTB2bHfo5Vv9slDx/Phd/70gYNpMey5urX2Nm+b00rG7rTETSZbXUWaaOIACtksXDMnWePjqF912/DNev6ZQ97HC40ttVEv7pePjVsGkT/WbbO1YhfEAq9V1lJzgG21wVvscjr/blLB1HNlVO+FJG0VIfEfmgQfquJIUfNVjQ5LTIs49qq1qfeIJ+82VXkkk564YRfj4PPP10pQ1mt1MbmaWjEf4ZgCAA//mfNA384hdJ4Ssr9VVR+Lmf/hxvOPgkGvqp2t51y/3l5RRYIOjgwfL6HrOB321Ip6usU6JWR6ceqKXTnctgFTMzGRqU1RR+a6s8OCsrKM4Ci1GP5PJVGHX5Md3VM/sLFGD+Mx+43TMSxpp2d83Bo8FuwjKfHbuH1BX+eDRdth8qI/8WlwVmA9mFvdKuY2s7PfjHW6WBnN2noVB1S2cxFX5bG30HbHW6qqUj253KRVfVjp2Twud2NysRfiZJ31UmQ6Qq3f8+hwlOswHHBOlaSIQf1pnKNy9RU/iiKBO+Whnvvj661tPTclzj1lsr29zaSgq/lqg5i7jwCB8A1q8H3vlO4BvfAIaHy/17oLwSH8PICFo/9TEUBB306bT6KrdxLhPjuefqb49yeznlsnW1sgr1oLcXeOEF4O675/a6swVWQI2pNjXC1+lklT9HhQ8AHUuacO0HfoSBK2+Y82uZwp+Jk8LP5As4Mhat6d8zrFvixZ7hkGo+/kQkVbY9Xpu0NyqzcwAaNP77bVfgB2/fINei8XppRpnPV7d0mAhZDMIHgKuukkv2qi68kleRzqbwZQ+/zqAtP6vhPHxHNkUlmBU7nwmCgKV+Ow5ljTSLHh8HYjEEBDOa+UJ6aoR/+DARtd1ervAZ4V99Nf0+cIBmPDodWcdKtLXReVkq6yIsnjodXJiED1B9DqYUlYSvXG1bLNIAkcvh25vfSI/xhMzAEz7zNevB5CR52PzOSwtB+ADdiMrCU+cqXC5KubzzTurAino4JZwG4bP9eeeaoQMALosBRr1Q2sjj8FgU2UIR62r49wzruzwIJLIYCiTLHs8VipiKZdDqkcmdqc0OhSJ+1aUt5dtMejxyNshsCn8xLB1AtnX4c3JgvjxQmZKpBBsc5mTpMHAK356VFL6C8AHK1BkIpElUnToFpFKYgbG0rzS9gUT4vKhj6v7229XLeLPS2ozwN25UT6Fsa6OBQ6389zmAC5fwW1oovcpiAa64ovw55SbRBw8CTz2F7e/6B+xpk8rs1iL8NWuALVvqbwurRc48xKYmuaMC87d0zje4XNRhZmZouTqf0saDBW7nQfjMa59rDj5ACrGBy8WXA7azp+Wul3z83QoffyqWKS26YmCpmbzCV4XXK5fbPRtBW0AmfItFVVjYOcKf7fOoBW1T2UL1XcZ4QuWCts6M5OGrEP5SnwNjkRSKLa2lUtshpaXDFypjePxxKmWyZg1l4eWlNjLy7+2l/vnss8COHbT6XQ1sle85uk/FhUv4ANW+Hx+v9LiVG2ZLi3xe7l6NuEdK6eIJmWF8nAoh3X03BYPrrMdTsfnEQlk65xt8PiKNhx+mHO9q2LyZCG4eKw77mqkz110pU4FGu7lk6ewdCaPFZVHfvFqB5c1OOMyGCsI/FZJTMhnaJLU/mwUCr5d8avY3D57wdTqaQS4G1q+ne17FzgFkwvc5TGXkX+tYXuHf9+hhvP1/dqi/gH1mtl+w9JnduRQNHiwbhm0ZCGCp3w5RBJINvhLhJ03W2pZOJkMC7pZbZILms8kAenz1airgVyyq+/cAKfx0Wl4prhH+GYZaUSulwpdunGGLG6JfIuZqCr+lhWqMiyLw/PPVz7ttG6lYQJ3w+UqEgQCld51jft+C48tfJnWk5n3yuPtuUm/z6Cx9TU7csqoZ1/bNL5Dd0+TAMy9P48uPHsFLQ6Ga6Zg89DoBazs9FYHbRw+Mw6TX4TJua8wVzU78xz2X468ua6v9pvy9W83SYUX3Fms/BKuVkh6qED5T7Up7Sg0mgw4mvQ5xrp7OUCCJkzMJ9Rewz9zQQJ68wYCs2QKfmKGMm+Fhep4L7i+TMnWCrsZSfCNhtKDZVSNou3Uree633lpZ84nfe3nNGrnERLVaNyw189gx+q0R/jkApcKXCP+EwQl9s0QU1Qi/tZUCWSZTbR//4x8H/uqvqK61GuED8pSULSw51zcxOV10dFTGU9QgCOolZeuAyaDDD96+oW6iVuJLr12NN27owPefPYHRUKqugC3D+iUeHJ2IIixt9ZfI5PGbl0Zx+5qWUkAYIOvodes6Zi/Ix6t6JeEz0hLFxbNzGD75SdpLQgVsm8PZ/Hv+eL5EMtvbmV/dXAL7/JzVmbTY4S1IewIPD5MA42Y3vU0OGHQCTpnlASphsqkTPlPvbPvMq6+urfBZVdGbbqp+f7LFVxci4QuC0CAIwhOCIByXfquanYIgFARB2Cv9PHI651wQqCl8vx+TKREer5Ny+atZOixtcOPG2j7+0aOUeviGN9DgoUb4bFCZT1kFDYsCt9WIr9x9GX753k141aXNuGNN6+wvkvDq1XTsvz9Otd8f2nsKsUweb9vcNb/G1FL4Op1MXItN+HffTRuVqMBmMsBq1JfWEcwGZQG1kDQ4/v/tnXlwZFd1h7+jpVtLq7XMaJ3F63gZG4ONitgG28EMYDuUx6ZiYkKIKSBDqiAhCVXBxH8QUpXKBlmcEIgrQByHwk4cJkyCAxiHFJVKjD1OWMb2DB5sPIvGM/JIM63R1urpkz/ue+rX0mst0y1193vnq1J1v0V69+lKv/frc889138twhf8QEh2MtlGdy4g+Asqp7Y0N3JxX4qDjQWhnUwscPiJhPtE7Tv8o0fdGMWGDUs7fD+9u1T8HgoO3188PkqCD9wLPKGq24AnvO0wplX1dd5XyDpr68xCh+8J+atnZtnYkVycRePjCz7ATTe5KdjBEX2fkyeda//whwtLKgYFv39B2MgEv+a49sIN/M17h5ePswfYPpTml687n3/43sv876FxHvqfl9k+mJ4f0F01Szl8KIQA11rwl6CxQfiXD7+RD96wsvGW4JKIAKem3IDt2GSI4Pv3HHD4E82tpOe80iYhgg+uH/blC/2m7amibCKguGLm0aOuUqg/ORAWO/xUyo077dnjMvpKsTCkU2Nh2nIFfyfwoPf+QeCOMn/e+tDS4j4GBhx+fnCQsamsy+5YOKgKLmf/1VcLHXrjjc7B+5NSgvidfeut8Oijhfifj+/w/U8R51JHx6hJPva2S+jrSPKrDz3D/lcmeO915y1ZX2ZJfMFvb1+0whdQEJO1SslcIZcOdCw7YOvj188HyJ3NMzHj3o+FrUMQEtI53dxKKjvtQlmlBH8wzcGGgtC2doeMP4QJPoSvzOaXBRFxYdql0qD9gn9+Om3EHH6/qh4D8F77SpzXIiJ7ReRJEVnyoSAiu7xz9476Me61IDjbdmSE2b4BVKE3lVicNgmFB4Av+Ndf7waSwuL4vuBfdpkb4B0fhze/uXC8r899r/+xzxx+ZOhoaeZTt1/BiYlZOpJN7HzdMgOzS+E73FKrafliUkWHv1qCSyJmZgpO/2SYw0+lCgsX4SbCnW5upW12EsbGXPpkiOBfMdTJiVRhDYu2DSGfsFKpgnsfGSkIfliRv9WK9uBgoXhjjTn8ZR/LIvJtYCDk0H2ruM5WVR0RkQuB/xCRH6nqT8JOVNUHgAcAhoeHSy8jVC5+PZ2zZ+GVVzjT455VG1NeSGdhfN7PwfcFP5Vy+f1hgr9/v3MBfp75wgGe1lb3APjqV+EP/sAEP2K8/YoB3nf9+Zy3oY22xLkNPgMFh1tK8GsgpLNaUslGRrxF3INx+9AYvohb49X7nxufnGMi0UrL+NFChk4Jhz/aXviddfaGCL7v8FWXdvilivwtxdCQM32treecfLBWLNsaVd1R6piIHBeRQVU9JiKDQEjgG1R1xHt9UUT+E7gaCBX8dcN3+CdOQD7Pqa6NMIOL4ff1ORHO5QodtlDwwYV17r/f5d0Gl5/bv9/V3li4LGGQd70Ldu1yD5azZy2kEyFEhN+9/YrlT1yOlQp+lUM6q6EtURi09eP3QOmlJf1JeLiidpOJNpJTZ0JTMn0625rZ2NfNdGs7rdOTdPZ2LjpnXvDHxlwefqUdfvBn1RDlhnT2APd47+8BvrbwBBHpFpGk934j8EbguYXnrTu+w/dSMl/1amjPx/ChkDYJBcEPTPLgxhtdbP+pBRNHDhwoXj0ojHe+0z0QPvc5t20O31hIBEM6wUHb09MFkQ8dtF3A2GSWM8lWmqYml3T4AFcMpTne1s1sYxO9PSVi+GfOOHcPhXTKpibnzMt1+BBJwf9D4K0i8gLwVm8bERkWEa8gPZcDe0XkB8B3gD9U1eoLvr+4gifkr6R8wU8szqIBd55IcbbNm97k9gXDOnNzrl7MZZctff0NG2DHDti9u7BtGEFSKWcKSi17V4chHbckYg5VnXf4icaGlQt+oo2GbNYV4EsmS1aK3T7YySttXUw1t4bPlE6lCuXOoXg9X7+MN5Tn8Gssfg8rCOkshaqeBN4Ssn8v8EHv/X8Dr1l4TtXxl0/zHP6R1m6STW6hikV58uAEf+PG4myJ7m6XfRMU/BdfdKGg5Rw+uLCOX1vfQjrGQkRcaPCiEqWefSGqo5COv2DKzFyecU/wz9vQVrQGQSnGJrNMeMsVsm+fc/clMqCuGEozku6l/8zJ4rIK8w3xQjp+eYag4KfTxQ4/eGwl1LDDr60RhfXEd/hHj4IILzem2JhSl0JXSvAHQybh3HgjfOlLztk3N7v4PSzv8AHuuAM+9CH3gDCHb4Tx1FPF40NB6tDhBwuonZ7KIgLnbWjn0FiJ8goBxiazTCW8Am379sFVV5U8d/tQmrtueC/d0xk+nw75/fmCvzCkA+U7/BoW/HiWVgDn8M+edamRfX0cn8m7AVsohG2CqZlLCf7kZGF6tp+SuRKH39PjCjaBCb4RTkdHeA4+1KXgB0skn5qeo7O1md6OxIpCOicns4UsmtHRkvF7cNVJpwY3sW/g4uKS0z5+WubRoy4sFMytX+jwbdA2Avhx0eee82bZZl0OPrjc3+bmlTn8G25wr35YZ/9+N7DbGZIZEMbHPw6/9Eul47SGUYo6HLRtDzj88ak5utsS9LQnGJ+aI59fOgt77EyWhuD/1RKCLyJsH0rT056YX1WsuCHtLjvn0KHFIZuFDn+1sXgT/BrEz3w4cACGhlxZBb/AlR/W8QU/n3duP0zwBwbg8svhi190bmD//pW5e5+bboKHHop+4TSj8tRhWmYqUCL51FSWztZmetqTnM0rmZkSdfE9xiazNHUFMm6WEHyAX7nhQn795ovDD/oPyRdeKA7nQGFlttlZF6pdrXCnUu4hstrY/zoQ7xg+wOwsOjjI2GS2eNGM/v7i0ge5XLjgg8vFf/vb4YMfdA+Qu+5a27YbBtRnSMerrjmZzXF6eo6e9kRhLeHJLF1tpcsWjE1l2d4TSFFdRvB/9tI+KOW9/N/ZSy8tLtftr70crKOzWp5+euWf8tcRc/jAdG8/Z/NavGhG0OGHTboKsmOHW1LxkUfcRI6VDNgaRrnUYUgnFVjX9lQgpAPL5+KPTWZp6QmEPle5yH1xQzwRz+fDQzoTE+WtWjU4WJOfvOIr+IGY+YRXViFYs7xI8P2FoksJPrhY/J13uvcm+MZ68PrXu3WBr7mm2i1ZMcFVr8bnQzqewy812xY4m1fGp7K09VZI8IMPyYWCn067Oj1+ccUazKc/V+Ib0gk4/EzXRjgJXW2BbAg/pKO6vMMHF4N/8EG3OMJyKzoZRiXYuBH+9V+r3YpV4Qt+ZmaOiZkcXW3N8wvOL+XwT01lUYV0T6crOd7TU56DXkrwfUfv5+jX4ODruRJfwe/sdCKtynjXRiBHuiUg+H19btBmYsIN7EBxWYUwOjpcDXzDMEJp91b5GjnlFjHpam2mu80X/NKTr/yHQU9Hi/s/WyZ+vyxB1x7m8KEg+BFy+PEN6TQ0zHfsyU6XA59uXSD44BYr/8u/hNtuq8mYnGHUE02NDSSbGjjiLe7e3Z6gpbmR9kRjeIlkD/9YT1vC/d+WE86BYocflqUD5vAjR3c3TEww2tIFHCfdEvh1+JOvdu1yBdLuv78qTTSMqJFKNnHUK5Hc6ZmsnlSC8SUE3z/W056Az3ymcoKfTC6e9Bhhhx9vwe/qgtlZTs+5CR+hDv/AAfjkJ0vXMzEMY1W0J5s4Mj4FMJ+G2dOeXNLhv+od25BKVCbt2Rf8oaHFc2DM4UcUrxja6ek52hKNNDcGIly+4F90kcvAMQyjIrQnmzg05gm+Z7I2tCc4npkp+T1Hx6dpbpTiuTLl4Lv2sMlR5vAjyqc/DbkcmZfmigdswWXkvO99bjJVa2tVmmcYUSSVLJQ66J53+AmeP5Yp+T2Hx6fY3N1GY0OFZqT743Fhgh90+A0Nkfr/j7fgv/a1AGSee4Z064JfRUODq4JpGEZF8VMzRaDDGzfb0J7g5GQWVQ1d9P3w2BSbuysovI2N7hP+tm2Lj/kO//hxJ/4RKnsSb8H3yMyEOHzDMNYEX/A7W5tp8Bx7T3uCbC7PZPbs/GzcIIfGpvi51ywxD+ZcePLJ4gWNfHyHn89HKpwDcU7LDJCZmSsesDUMY81IeSWSuwN1c7r98gohs20zM3OcmppjS0+F06Ivuihc0P1lDiFSA7Zggg9AZjpXnJJpGMaaEXT4PoUCaosnXx32Bni3Vlrwl8IXenP40eP0tDl8w1gv/EHbYCkTv57O+NRih394zOXsb+leR8H34/jm8KNFPq9MzMwVuQ3DMNYO3+F3FTl8l275akhIxxx+5Yi94E9mc+QVG7Q1jHViXvADMfyBzhaaGoSXTy5e2/bw+BQdLU10tq3j/6gv+ObwC4jIXSLyrIjkRWR4ifNuEZEDInJQRO4t55qVJjOTA1iclmkYxpqQmhf8goAnmhq4YGM7B16ZWHT+obGp9XX3UAjpmMMvYh/wTuC7pU4QkUbgs8CtwHbg3SKyvczrVozMtFtWzRy+YawPbV7FzK4FYdRLBzo4cHyx4B8em1rf+D2Yww9DVZ9X1QPLnPYG4KCqvqiqWeBhYGc5160k84JvMXzDWBd8h++nYvpcNtDB4bFpzszm5vfl88rh8Wm2bjCHXwnWI4a/CTgc2D7i7QtFRHaJyF4R2Ts6OrrmjZsP6ZjDN4x1YUtPG82NwkW9xWJ6Sb9z0z8OuPzRM7Nkc/nK5+AvR1wdvoh8W0T2hXyt1KWHzUvWUier6gOqOqyqw729vSu8xLlzet7hWwzfMNaDLT1tPPd7t3DlpuJFvi8bcK76x4E4vl9kbUslyyqshIg6/GVVTlV3lHmNI0CwePVmYKTMn1kxLIZvGOtPUWVaj83drbQlGtkfEPyqpGRCfB1+BXga2CYiF4hIArgb2LMO110RmRkn+B0209YwqkpDg7Ctv6MoU+fQ2BQisKlaDt8Ev4CI3CkiR4DrgK+LyDe9/UMi8hiAquaAjwDfBJ4H/lFVny2v2ZUjM50jlWyiKcRxGIaxvlzW31EUwz/cXusdAAAL70lEQVQ8Ns1AuoVkU+MS37UGRHTiVVm2VlV3A7tD9o8AtwW2HwMeK+daa4WrlGnu3jBqgUsHOnhk72FGJ2bp7UhWJyUT4MorYWAgvHxyHRN7W5uxOjqGUTNcOuCctR/WOTw+tf4ZOgCXXw7HjsHmzet/7TUk9tb29LTVwjeMWmFe8I9PcDwzw7HTM1y1uXOZ7zJWSuwFPzOTY1NXS7WbYRgGsDGVZGMqwTf2HeNHR09z7YU9vOdntla7WZHBQjrm8A2jprikv4OnfzpOuqWZ+999tSVUVJDY/yZttSvDqC2u3NRJY4PwV794DX0d9um7ksQ6pJPPK2dmcyb4hlFDfOTmi7nz6k1cPpiudlMiR6wFf2I2hyqWlmkYNUS6pZn0oJmwtSDWIR2rlGkYRpyIteCftjo6hmHEiFgLvl9HxyplGoYRB+It+NNWC98wjPgQb8H3HH6nxfANw4gB8RZ8G7Q1DCNGxFvwZ3KIQEfSYviGYUSfeAv+9BypZBMNDWGrMBqGYUSL2Au+DdgahhEX4i34VkfHMIwYEW/Bn87ZWraGYcSGeAv+jIV0DMOID7EW/ImZnM2yNQwjNsRa8M3hG4YRJ8oSfBG5S0SeFZG8iAwvcd5PReRHIvJ9EdlbzjUrxXwtfIvhG4YRE8pVu33AO4G/WcG5b1bVV8u8XsU4k/Vq4VuWjmEYMaEswVfV5wFE6m/ikl9WwbJ0DMOIC+sVw1fgWyLyjIjsWqdrLsnEjFXKNAwjXixrb0Xk28BAyKH7VPVrK7zOG1V1RET6gMdFZL+qfrfE9XYBuwC2bt26wh+/egoO3wTfMIx4sKzgq+qOci+iqiPe6wkR2Q28AQgVfFV9AHgAYHh4WMu9dinmHb6lZRqGERPWPKQjIu0i0uG/B96GG+ytKn4tfHP4hmHEhXLTMu8UkSPAdcDXReSb3v4hEXnMO60f+C8R+QHwFPB1Vf1GOdetBIUYvjl8wzDiQblZOruB3SH7R4DbvPcvAq8t5zprgcXwDcOIG7GdaTsxm6OluYFEU2x/BYZhxIzYql1mes7cvWEYsSK2gj8xY2UVDMOIF7EV/MyMOXzDMOJFjAU/Z3V0DMOIFbEV/InpOaujYxhGrIit4GdmclZHxzCMWBFjwZ+zQVvDMGJFLAV/Zu4s2VzeYviGYcSKWAq+X1bBYviGYcSJmAq+K6tgMXzDMOJE5ARfVXnyxZMcPHGm5DkZc/iGYcSQyAk+wPu+9BSPPH2o5PF5h28xfMMwYkTkBF9E6E+3cDwzW/KczLQ5fMMw4kfkBB+gv6OF45mZkscthm8YRhyJpOD3ppOMTizh8OdXuzKHbxhGfIik4C/v8HM0CLQnTPANw4gP0RT8dJLJ7FnOzOZCj2em50glm2hokHVumWEYRvWIqOC3AJR0+RNWKdMwjBgSScHv60gCcKJEpo6ro2OCbxhGvIim4HsO/8REuMPPzORswNYwjNgRScHvTzuHXyqkk5mes5COYRixoyzBF5E/EZH9IvJDEdktIl0lzrtFRA6IyEERubeca66EVLKJtkRjyZDOhDl8wzBiSLkO/3HgSlW9Cvgx8ImFJ4hII/BZ4FZgO/BuEdle5nWXRETo60hyvEQuvsXwDcOII2UJvqp+S1X93Mcngc0hp70BOKiqL6pqFngY2FnOdVdCXzo8Fz+fV87M5mzxE8MwYkclY/jvB/49ZP8m4HBg+4i3LxQR2SUie0Vk7+jo6Dk3pj/dwokQwT+TzaFqhdMMw4gfywq+iHxbRPaFfO0MnHMfkAO+HPYjQvZpqeup6gOqOqyqw729vSu5h1D6O5KcmJhFtfhStviJYRhxZVnVU9UdSx0XkXuAdwBv0YXq6jgCbAlsbwZGVtPIc6EvnWTKm23bEYjXZ6atcJphGPGk3CydW4CPA7er6lSJ054GtonIBSKSAO4G9pRz3ZVQmG1bPHBbcPgm+IZhxItyY/h/BXQAj4vI90Xk8wAiMiQijwF4g7ofAb4JPA/8o6o+W+Z1l6Wvw5t8tSCO//RPxwAY6mpZ6yYYhmHUFGUFslX14hL7R4DbAtuPAY+Vc63V4k++OhFIzZzK5vjCf73ETZf0cmFvaj2bYxiGUXUiOdMWCuUVgqmZX3nqMGOTWX7t5tDnlGEYRqSJrOCnkk20JxrnY/gzc2d54Ls/4doLexg+v6fKrTMMw1h/Iiv44OXiewXUHn3mCMczs/zazduq3CrDMIzqEGnB7+1IciIzy+jELH/xxAtcvbWL6y/aUO1mGYZhVIVIC35/uoWR09N89OH/IzM9x+/f8RpEbJUrwzDiSaSnm/ankxwZn+bI+DR//PNXsX0oXe0mGYZhVI3IO3yAXxjewruGtyxztmEYRrSJtMN/2/YBTkzM8ltvvaTaTTEMw6g6kRb8rRva+J3bLq92MwzDMGqCSId0DMMwjAIm+IZhGDHBBN8wDCMmmOAbhmHEBBN8wzCMmGCCbxiGERNM8A3DMGKCCb5hGEZMkPB1x2sDERkFXj7Hb98IvFrB5lQTu5faxO6ldonS/az2Xs5T1d6wAzUt+OUgIntVdbja7agEdi+1id1L7RKl+6nkvVhIxzAMIyaY4BuGYcSEKAv+A9VuQAWxe6lN7F5qlyjdT8XuJbIxfMMwDKOYKDt8wzAMI4AJvmEYRkyInOCLyC0ickBEDorIvdVuz2oQkS0i8h0ReV5EnhWRj3r7e0TkcRF5wXvtrnZbV4qINIrI/4nIv3nbF4jI97x7eUREEtVu40oRkS4ReVRE9nt9dF299o2I/Kb3N7ZPRL4iIi310jci8kUROSEi+wL7QvtBHPd7evBDEbmmei1fTIl7+RPvb+yHIrJbRLoCxz7h3csBEXn7aq8XKcEXkUbgs8CtwHbg3SKyvbqtWhU54GOqejlwLfBhr/33Ak+o6jbgCW+7Xvgo8Hxg+4+AP/PuZRz4QFVadW78BfANVb0MeC3uvuqub0RkE/DrwLCqXgk0AndTP33zd8AtC/aV6odbgW3e1y7gc+vUxpXydyy+l8eBK1X1KuDHwCcAPC24G7jC+56/9jRvxURK8IE3AAdV9UVVzQIPAzur3KYVo6rHVPV/vfcTOEHZhLuHB73THgTuqE4LV4eIbAZ+Dvhbb1uAm4FHvVPq6V7SwI3AFwBUNauqp6jTvsEtb9oqIk1AG3CMOukbVf0uMLZgd6l+2An8vTqeBLpEZHB9Wro8Yfeiqt9S1Zy3+SSw2Xu/E3hYVWdV9SXgIE7zVkzUBH8TcDiwfcTbV3eIyPnA1cD3gH5VPQbuoQD0Va9lq+LPgd8G8t72BuBU4I+5nvrnQmAU+JIXovpbEWmnDvtGVY8CnwYO4YT+NPAM9ds3ULof6l0T3g/8u/e+7HuJmuBLyL66yzsVkRTwz8BvqGqm2u05F0TkHcAJVX0muDvk1HrpnybgGuBzqno1MEkdhG/C8OLbO4ELgCGgHRf6WEi99M1S1O3fnIjchwvzftnfFXLaqu4laoJ/BNgS2N4MjFSpLeeEiDTjxP7LqvpVb/dx/2Oo93qiWu1bBW8EbheRn+JCazfjHH+XF0aA+uqfI8ARVf2et/0o7gFQj32zA3hJVUdVdQ74KnA99ds3ULof6lITROQe4B3Ae7QwWarse4ma4D8NbPOyDRK4AY49VW7TivFi3F8AnlfVPw0c2gPc472/B/jaerdttajqJ1R1s6qej+uH/1DV9wDfAX7eO60u7gVAVV8BDovIpd6utwDPUYd9gwvlXCsibd7fnH8vddk3HqX6YQ/wy162zrXAaT/0U6uIyC3Ax4HbVXUqcGgPcLeIJEXkAtxA9FOr+uGqGqkv4DbcyPZPgPuq3Z5Vtv1NuI9oPwS+733dhot9PwG84L32VLutq7yvnwX+zXt/ofdHehD4JyBZ7fat4j5eB+z1+udfgO567RvgU8B+YB/wEJCsl74BvoIbe5jDud4PlOoHXBjks54e/AiXmVT1e1jmXg7iYvW+Bnw+cP593r0cAG5d7fWstIJhGEZMiFpIxzAMwyiBCb5hGEZMMME3DMOICSb4hmEYMcEE3zAMIyaY4BuGYcQEE3zDMIyY8P8taOTbViw34wAAAABJRU5ErkJggg==\n", 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sSRXdAxEyqKlBlVELuycA39JlwNatqZ+bAsNOH9z+YNKErQCpn05qCPr9yiSEb9SJgiEhwo9L+B+jtagac2dV4v1D/eCWLAEq+JhyDq8eT1NZp5efmnYgE8L/+c9Jak2UwJ4AskH43QDEEXslgCi25DhumOM4IXP5JIAzsvC+kwMhwk+D8IWiK8HGd8m8Uty6qg5n8o2+AIrwrU7fhDU8IbIXhnJMCBYL/cRz6AhI05rZMjCKJqMG6O6GurEeAMIDLgCQrLNxY8LEarfVjUGHN3yxTIqOiPVTIObheYvp/gn27hGa31WlkHQAqraVIvzk2NwyiFmluSgSrXZjUcCfGwAihG82kwuHR9uAA2XHDsC96Ax8eUklemxuHO4VySMzZlDtyHQlfP58TTvC9/mA558HzjkHUKVY8Y4D2SD8HQCaGGN1jDEVgGsBvCnegDFWJvrzcgDTt1Iigwi/w+JEqUEDjVIOgKowf3LZHGhV8vA2Rr0KgRAHuzsFQXAcWQwT5A56eMLvyYakI9jZEkX4ACVuOzuTaqPUR8iFhXInEAxCXlcLk16FfofoorRmDWC3E+nHwZ6uNPV7IEL4lZVhrb29YR7dN0FZp8ua2oMvQGqRnBrH+hwpL+JGvQpOXxAefzBywQ6Fos69V17bDJPbjrq152HN7GLIGPDeof7Ii6hUFLhMU8IX5iIf6XXAFxA1ikuUI3z7bWpJ8vWvT8r+TJjwOY4LALgLwHsgIn+F47hDjLH7GWOX85t9lzF2iDG2D8B3Adw00fedNKQg/B3tFvTbaZvOYReqTckJwpQjFF/FWDMfe4x+9uyhYpKVK8nVclt8x6oQ4Y9bw7/ySuB//od+T4fwZ8ygi1Bra8JNuqxu+IIhzPHyMlNNDUoMGgzYRYS/di1587/xDSr0isFhsx0quQyzSnNT/w+dnVRZqVaHP/dDpY2AQjFxwucj/MqC5Bo+QNZMaepVYoRCHKwuP0z6xNE9ABTw7RVsLj8RoJK3w/KJ21CIQ++HVGiVu/psmHLUWFpjxPuHYlZzc+YAhw5l95/IAkIhDv12D6qMWviCIRzvd9ADW7dSO5N4NSTPPkutIi6+eFL2KSs+fI7j3uY4bgbHcQ0cx/2Kv++nHMe9yf9+L8dxczmOW8hx3Pkcxx3NxvtOCpJIOqEQh68/vR03P7MDvkAIHRby4CeDUR+ngdrwMHDnnfSzZAm1Jxb60LzzDg0kiYEQKfSOjEPSMZuBf/wD+M1vSFoRCL++PvFzBKfO9u0JN2nl3Th1Lr6Vck0NSgxq9IkJPzcXeOklGopy221jLJoWpxdGvQoKeRqHYkcHJWlBq6k8rRLtrhCwcOGEdfwuiwuFOSron30a+N//TbrtdBhk7g0E8ewn7bj+qa3hhn3TBQ4PdRMdUzQXA6FjpsXpowh/Id8zidfxrS4f5nYfQ1CloipbABfNLcHRPkc4fwaAnDotLVQ7MlG0tlJNQBYwNOqFP8jhojmlAESyzoEDdPtIzBCfoSHgX/8CvvY1CmImAVKlbSyECD+OS6fX7oHLF8ThXjt+995RDDq8YYdOIgjtFYbE1bZCYuqRR4AXXwT+9CdyzTz1FDUCe+yxyLYDA4DNBjOvBY4rwhciib4+4L336L2qqgBtkmh23jz6ufNOckTEgWDJLLXyJ0h1NUoMmmgNH6AGbb/6FXXnfPzxqIesLn+46jIu7riDngvQ5yZU8gKoMmqpHcLy5cCOHWlXBsdDl9VFMtHjj9P3kQQne8zhuiP9OP93G3Hfm4ewpWUYuzuylMjPEoRiKoHQE0GI8K1Ovg/TmWfSA/z5MeDwYmHvcdhnzgvr2QJ5vn9YFOXPmUNS0Hga/sXiyiup+V8WYOaDsxX1JuRqFNjPE763lQI67s03o6fDvfgi5S8mSc4BJMIfC3GEHxONdvBFRk3FOXjy4xMAgGpT/KISAcIA7L4REVELhH/WWdRK+PbbAZ2OnAdf/CLw9NO0H21twLx5CHzjdlicPuhVcgw7faR5ZoING6hPfVERVRInc+gIUKnoefPn0z69/PKYTVoGRlGUq4bG3E3LUK0WJQYNhka9CMQOtrjnHmD16jHTsGwuX3LCf+UVqnx+660xhF9t1JEUs2IFMDo6IR23y+Im/T6NBDANQTl5Ef5P/3EIGqUcj1y3GMA4V32TCKEhWr4uVYRPjzv6BilZ2dhIc5X582PQ6sS8/lb4Fi8JP6fapMOMkhxsPCaybGfTqdPZmVTGzAS9fHBWnq/BvPK8cITfvO0g7Cod8csTT0Se8Je/AIsXh1czkwGJ8MXgOIrwtVoi3JHozPqJYSL8//3q4vAkpFSSTmGOClqlHJ0WEeELxSW8PBGFu+4iB82jjwKXXgoMDiJ4jCIXoX1Dxif4hg0kG11/PfDmm6R3piJ8ACgsJEvl8uXALbeMSeC2Do6isSiH+uDzRFxi0IDjgMHRmChfJgPOO49OKJHdzObyhyO9MXC7I7r/9dfTkl30mVUV6NBtdSO0jI8MM9TxgyEOwRCHQDCEHpsb9ZoQffbDw0ktcbkaJTz+0EmZ1mR1+tBjc+OaZVX4woIyqOQy9E03wuflS2MKwhckH28Xv5ouLaXvlyd8374D0Ps9kJ11VtTzzm4oxK4OayQJOnMmHV8T1fG9XjIYZGkmsxDhl+dpsaAyD0d7SYrytJ7A4ZJ6HF64kqbD+Xwkt+7eTSNGJxES4YsRCNDSsKGB/o7R8duHnFArZJhRnIv/uWYRzmkqxMwUyUbGGEWiVpHm2NlJ1YLx6gxWryZN8p57gBMngKVLwXh56QyB8DORdTo7aaVw/vnAzTfTktHhSG7JFMNgoFJ2lyuqopXjOLQMjKKhWE9RcZjwKWcxRtYBKGcQCkUNMUkq6QhOhv/8z4hcI4rwK406+IIhDJRWAwUFGev41z2xFSsfXI/fv38cwRCHmV6RNJJEx83VKNAw1AXff2VnqlcmEPzc8yvywBhDaZ5m2kX4Qr4qVSFdPt+XKNDNn2dlZVGEr9xB+SP96pVRz1tRb4TbH8T+bj4YUKspgJko4QuFnr29WenP1GtzQ6OUIV+nxLyKPPiCIXz3pT2osPXDV1GFx+deRKvJ1auBH/4QuOYakjAnERLhiyFEsAkI/8SQCzUmHWQyhuX1Jvz11uVhS2YyVAnSg4DOTtLQ45WcMxbREJ95BvjCF6CyDEEV8GMZ7+/PyJop6Pfnnw8sWEBJYiC9CF/AueeSg+KDD8J3DY36YPcEMCNPSRcUPskrSFj99jgkJCSJ+aQ0x3G8pJOAGATCP+880tY1mqjlruDF77TyOn4GEb43EMTuTit8wRAe/4iW8LWjIpkgSWuNXI0SX933LvT/+e9pteDIJg6aifDn8pO4SvM00y/C5yWdVElbhVyGPK0SXB//GZaW0nnBr4AN+3fDojNAN3tG1PPOrKPum1vbRBPVmprimh0ywsAA3YZCWZnJ3DviQXmeFowxzOe/r0PtgygdHUbJgln4V/lCeCur6Lj9yU+oA6g6ubNpopAIXwwhYSsQU2yEP+xEbQrNPh6qjTp0WlyR4quuLjqwE+GWWyjC/OpXwxWFxU4LFlWRr9mcSfHVhg2AyUQJWCBi+xR0z3SQk0P5BhHhCwnbua4Bir7nzgWQgvCFCyl/Yjp9QQRCXOLulMLnX15OzgW7nap3eVTk03uZbW7gjDNoEEaaJeknhpwIhDjc94U5eOs7q/CjS2dhptcS2SDJCW/QKFBj5fdtx46E200GDvaMoNqoC0/bKsvTRLuipgGsLj+Ucga9KnUwZNSrIBdWU0KEb7MBdjtKj+zFsZo5YwIjo16FWaW52Nom+r5EF4pxQyB8YFyyzoajA7jn1X3h89w84kYZf4zWmHTI1ShQ77GCcRyqFs0G5HK8/u//Rc68++/P2uS2ZJAIXwwhwhcIX+TUCYY4dA67UFc4HsLXwuULRlosdHbG1+/FKC6m28pKAMDcoB16tQKFOepwuXZKCMVc550XOZjuuIOaUQkdMdPFhRdSzcAQWTAP8AOp6wb4BDR/ATHpVZDLWHzCLy2lKJ0nfEHrzdemiPDL+Lo9ZfSFoYifOzDg8JClLxhMO3F3rI880TNLczGvIg+3r26AXFzWnyLCr7XyjyexrY5BV1f8bpAZ4EDPSDhaBCIR/nTpxgjQ91qgUyXtOiqgQKeEcrAfIbUG/72tD7ZCcuHgwAGUmU+gozF+AnNFvQk7OywRHb+qinIvLlfc7dPCBAjfbHPjey/twWu7usPNA3ttHpTlkROOMYbvXzADP55Hq1LdzAYsqS7Ai6yM7NhTBInwxRCiQ5MJyMuLivB7R6jIqHYchC9Ub3ZaXKQNms2pCV8AH+HPCFI5eUW+Jn1J58QJuricf37kPpmMouFMccEFdLtuHUa9AfxpUyuW1RagoL2ZXpOXdGQyhuJcdXwNXyajHiG8C8LGd0pMquErlfR9xIFBo4BGKcOA3RvxcKc58vB4vwMKGUN9YU7kTiEXwVjSCD9XyVA1wj+eSYT/jW+QC0OY2hSLLVvoAn3iRFR7AQE2lw9dFnfUYPVSgwa+YGhadWS1OH2pG+HxMOpVCPSY0a3Jw8PrW7DBzVuFX38dADAwd3Hc562oN8HjD0V0fGHFPJGE6zgJPxjicPcre+HlLz6ftA4jEAxhwOFBeV6kr9atq+pwjoq/INXW4vxZxTjQMzKldRQS4YshEL5GQzKCiPDbh6I7Y2YCQWvusrjoNUOh5JKOGHyEX+ehhGJZnjb9JJ1Yv58oli6li+AHH+CxjS0YGvXhx5+fA3bkCK2IRJ5+8uIn2Mf6+nCEb3On0HrNZloVJFjqMsZQnMsPi29ooH1Ik/CP9TlQX6SPnlvb0UGvU1iYNMI32gahDgYQ0GiJ8NONrvfsoTkLa9eObTWxfTuwahVVW9fX008M6QstdudVGML3CW6x6ZS4tbp8iZ1XMbhiUQVmMxf0tVUw6lU4puQvZq++ihAYnAviE/7yOspnhXV84XyaiKwzOEgaulab0es8+XEbtrZZ8Isr56GyQItPWofQ7/AixAGleTG1Lu3tFFBUVuK8mWTa2HR8aPz7nCEkwhdDkHS02jGEL1gyxyPpCH1fuiyuiAc/zQg/lGuAS6lGpYsIvzxfC7PNnd4SfvNmio5nz069bSooFMDnPofAe+/jqU1tuHJRORZW5ZOEEpMPKDGo4xL++qP9OKorIsLnqPweiLg1xqC3l76HJCjOVVOEJJdTQjddwu93YEZJjMNKiPBLS5Nr+N3ttPnKNYDVmp5ve2CAfn74Q1rlXHop8PHH9BjHAd/7Hr3ve+8B3/oWRZgxnSMFh868crGkQ4QynRK3VpcfBSmKrgR8YWE5ZoZGYWqoRl2hHgeCOvouu7vRYqqCoTR+t80CXsf/NJuEPzBAUmplZdoRft+IB//1/jGsnVeKq8+oxNkNJmxts4TbIgsafhjt7bRqV6kwp8yA4lw1NhwbGPvCkwSJ8MUQR/gVFTERvhMapQwluXEGhqSAViVHca6aJJ1kHvw4GHb50ZdjQpGdooDyfA1cviBG3H4EQxye3nwi8XL+k0+As8+O7wYaDy68EIruLtRaevDvl8yiCPT48XDCVkDcalsAj3/Uhn85tWQLHR4O90JP6NIxmyP6fQIUG9QU4QMk6+zblzLidnoD6LK4wwNrAJAHu7eXksJlZUkjfG0nFd0dWn0p3ZGOrHPwIN2uWQOsX0/f/+WXU6L5hRfIUvrAA8BFF1ExHhBpgcHjQM8IKgu0USsiIcKfSOK2ud+B257diRFXdorJBA0/bfT2AmVlqDHpcMLmDcuYe8pnRs2WiMWKehN2dVjhDQTDK+GpJvxXNx3DR//7ddzvPwLGGM5uKMSI2491RygRXR4b4YsszIwxLK7OR7PQY2cKIBG+GLGSTm8vyS8gwq816SGTjY88BadOOGpLU9Ix29zoyy1EgYWigPJ8LX+/B+8c7MX9bx0O2wqjMDhIZLxy5djHxgnfeSQNfS/Ujop8LRGS3x8nwtdgxO2PqggOhTgcMdtxRMtHbK2t6Wn4KSN8DQbtIsK3WlMOr2nmk2ozxDUUol77qSJ8eVsbvHIlDs4/i46VTAhfmPX7zjskH6xdS3UGZ5wRKfcvlvQAACAASURBVKkXLLMxK4dDPSNR0T0AFOaoIZexCUX4j33Uig+P9OPFHalnGAOgC+q//Rv5x2NAjdPS1/Dh8ZArp7QUtSY9zCMehPhzY0/5zKTtlc9qIB1/b6eNPsvi4okTflHRWMJ/803gtdfGbO4PhrDvrY0odwyhaB9N5Tq7gfJNb+yhYzBuhC9ymhn16inNv0iEL0aspOP3h10pJ8ZpyRRAbQDcdEAWFJDVMQ0Q4ZugGyICEiI6s82NP2+mSPNvu7ujW68CwKef0m0WCb+vqAqtxgos3cXnBgRHTBzCB6KtmV1WFxzeADryeBdGWxusLh9y1Aoo4zVO83io6jVFhF+Uq4bDG4DbF0w7cXtccOiII3xRr32UlRHhJ1optLbCbCyDNcCoriGeU2doiFYyAg4coNxASQn9XVdH7SIGB+kC9fDDeG2PmYi7rIyOQVGEb/f40T7swvzKaMKXyxhKctXj1vBtLh/e2k+rmb9+2oFgKIVUyHHAd79Lg8Q//nhMB1S7x48Ql7qtQhjChZWP8AHAWUzf+Z6KWUkJf0W9CTIWGbYyYWumOMI3myPFfj/8If3EYN2RflS08Z3e+YtzsUGDxuIcDDi8yFErYNCIgplAgC4kIsI36VWwuvwIpfrcswSJ8MWIjfABwGxGMMShy+Ial0NHQJVRB/OIGyFRx8d00MMTvrKPVhsVfIT/rwO92NNpw+dmFWNo1If1R2MqQ7dsIYfLeBw5CWC2e/DP2atRtHsrnRCHD5NcNGtW1Hbxqm2FhGNXPk94bW2wJauyFYggDQ0f4K2ZCxbQnSkI/2ifAxoFQ/Uffge8+irdKSb80lIqd7cmaErW0oK+okpqoLZsGZXEiyszHQ66EIjL5A8epOheLK8tXQq8/z7w1FOwLFqGe17dh+e3ddA2DQ1REf4HfA94sUNHQGmeBn328bXNfn13D3yBEL63pgk9Njc+PJKkUyTHAd//PvCHP1BdBjBmKpqQl0nVOC0M4XvmI3wA6K2fDWdRKZpNVShOIqHmaZVYVJWPTc1ZIHyOo4uvQPiBAF0ArFaS3Vpboy/gAP5vayfOtLbTH6LvSojyy/Ji9r2nhy4iompxo16FYIjDyBS125YIXwwhwo8hfLPNDX+QQ11h5g4dAdVGHTgO8J/oSN+hA5JuLPlFYIEAMDiIwhw1lHKGN/b0wKBR4H+uXYRSgwYv7aADfXjUi689tQ22dR8R2SfriJkh+kaI8BnHUVOzw4cpWtFFfy7xIvxDfIWoR6mBp6iEJ/wkWq+QP0mp4QtefC+1gairSx3h9ztwz5F3Ifv5z6mqORgkwpfJ6GQX3jOejs9xQEsLBkur4PD6ifDd7mj//333EfG8/Tb5wkMhIvx4TbFWrgRuvTXcBVWYoobGRqClBYfNdtzw5234t1f3odqow5I4Q0XG216B4zg8v60DS6rz8Z3PNaIiXwv17bdRAjkeHn2UOrz+4AdUBQ6MIXxBnkhbwxfVWgiE/9FlN+KpP78LyOUppaFzmopwoNtG+aCJEL7TSd+jQPgARePi1ZvQ1hhA2+AoNrcMYbmlnb+jLSz/hgk/P45DB4iO8MPzMqZG1skK4TPGLmGMHWOMtTDGxqx9GGNqxtjL/OPbGGO12XjfrEOI8AVJBwB6enCC75I5IUmHX67KerozivDNNjf8pZF9kcmofwoAXLe8GgaNEl9ZWomPjg+iZWAUtzy7E9uP9kK/f09W5RyAKgdbTVUILlxIPe4PHx6TsAXiE/7BHnt4dWIrreQlnTT66KQifCHCt8ckbpNAu+0T3Pz3R+nE6+4mi2RHByULlUqK8IH4On5fH+ByYaSsiqaYCS19BQltzx7g4YeBRYvoeNqwgfIDo6ORauc4EGorOoQWHA0N4FpbcfOft+Jgzwh+/PnZeP8Hq5GrGft5lRq04yq+2tpmQdugE19dXgOFXIYbVlRj8a6NCD7zl7F1ANu2EdFfdhnw+9+TbVShGBvhp9lHJwyRpJOnUyJfp0S71Q2zl4XzE8mwekYhQhx531FVRdXYdnvS58SF4MEXE35XV3R/JtFx9equbuiDPpg6W+g5Xm84SFlRbwJjiPLgA4heRfIQPiehHcVkY8KEzxiTA/gjgLUA5gC4jjEWW7d/KwArx3GNAP4bwG8m+r6TgliXjskEfPgh2idgyRRQbdRB53NDabNmRPjdNld0xAHK/CtkDDedXQsAuHoprRiueuwTHOi24Sx7J5R+Hzl0soi+EQ8MGgXk111HBHDoUNwWDUJBVHSEb8eKehN0Kjn6Cyv4pG0afXQykXQAIvzm5oQVl9a2LvzqxV9gtLyKTua8POC556LcE0kjfF5Xt1fW0hCUxkb6Pr/zHeCb36RK5sJC4N13Ab2edHohMkzS9jYS4dOxhsZGMK8XrLcX31vThNvOqU/Yt6ksj5xbDm9mDb+e39YBg0aByxbQ/3tdhQx5XifkDjsG3hENnh8eBq6+ms6JZ5+llZBSSaQfG+G7xhHhMxZuJFhj0qNj2IXBUW9S/V7Awsp85KoV+Lh5cGLWTIHwi4qii7g+/ZS+t/z8KMI/MejE+f5+sGAQuOoqupOXdfJ1Kvzyynm44awaREGI8EXnv/A5DY+eIoQP4EwALRzHtXEc5wPwEoArYra5AsCz/O+vAVjD0qm7nmqIk7YKBbXk/fvfsXn7MZTnadI6ABOhKEeNGleMZzgFAsEQmvtHkd9YS3fw7pMbz6rFjy6dHS7brjLqcF/XRvzi5V/hwfMqcLWXjySyTPhmoVT8mmvojmAwLuEzxqKsmQN2D4ZGvZhbbkBpngbd+SVAdzecDmfyPjoKBZFnEhToVFDIWLQ1MxRK2Dlx5M9/QbHTiuY/Pk0J1K98hao6jx6NEH6yCJ8/qd01daThM0b1DrfdRjLHjh2U0CwpIYulmPDjrIbC/y5P+DaXn/Rcvu9Qrc2MhuLkCX5hxZeJU8cXCOHDI/24YlFF+EKS1xwZRPfmA0/hgbePUDLxe9+j3k6vvkr96gXMnDmG8G1pNk4Lo7eXImR+wlOtSYf2YScGHJ60zjeFXIazGkzYdHwI3ESsmUKnzOJiOuZUKlqZbdtG+YqYlaPF6cOiAV63v/pquhXp+Ncvr8HcGEcV2tspmNBEIn9B0pkqp042CL8CgPgT7ubvi7sNPwN3BED8evmTCY+HohdhvNgttwA+H0rfegNfO6smrd4giSCTMcwP8UvNNCP89mEnvIEQqmbXhYtRAODzC8pwy6q6yIa/+Q1uev73uPzIJnzlzquwbOc6dOSXwmYwJnjl8aHPzjeDqq2NJO0SNGGrK9RjR7sF3kAwnLCdW25AqUGD1txigOOQ229OXnSVpMpWgEzGUJSrjkg6QuJ2//4x24ZCHHo278SQLh/V5/P7f+ONpN/290cIPzeX8hKJInyFAoGqKtg9fpJRqqpI325pAd54g5reASR/dHeTz76mhnIMCWAWkXXnsCtszay29qGhKDnhj6fa9kCPDR5/CCsbRachf2HyLV6Cz3fvwROb2rBz836S777zHUoyizFzJq2mRJPGLE4/VHJZWo3TANAFUpT0rzHpYba5YbZ5knrwxThnRhF6bG505fDBwUQi/OLicCUs1q8nF9KKFUT4Bw6E/9dhpxezelvoArhqFXFGqgI88SqShyDpWGJnXk8SskH48VgwVkxMZxvakLHbGWM7GWM7B4Wr7lTB7aarr0DsCxeip24WvnJwHa5blr4Mkwiz/byFLU3CP9xLroDZlfkUGcTzl//612QZu+46ssk5nSg5vA87K2aHO1pmC30jnojz4JvfpEgoAeHfuqoOvSMevLKzO5ywncNH+Ie0tHyvsvZNqOhKQLjaFqCLkVIJtLTglZ1dOPNXH+Ife3vAcRx++94xaFuOwTdjZsT9sXJlpFmecDIyltiL39IC1NYiV6+FP8iF+6fQP1RFI/KE4+dSvjDr0KGk+j1AEX4hH+11WJxAVRWCcgWa7H0oNSQv9otE+Ok7dbafIAeS0HIbAF0kq6qguuFrKOtpQ+VIPwqeeYIS1d/5ztgXmTmTtGtRRbDVSRPM0gqOenooal67NnxXXaEOIY4i3nRX1Oc0EtF/5FBQgDBRSQcgwt+zh34/6yzKyTidYVK3OH2o7zxKxgilko6dmEK5KHR1kTwkWId5qBVy5KgVp1TSthuAWKOoBBA7ATy8DWNMASAPgAVxwHHcExzHLeU4bmlRvAEhkwlh2hUPm8uHp2ecj3l9LShoOTLhl69zWxBkMnBpEtmRXjuUcoam4lzST2MJv6sL+NGPSGJ57jmKNLZvh/MLV+ClhReHu/aNB8OjXix/4ENsOk4XXW8giKFRX1hGwo03UlSsj5/XWNVYiGW1Bfjj+hbs6bTx7WGVKMvTYI+aTtCmoY7EJfhpFF0JKMrVRCJ8uZwuqO3t2NNpxYDDi++9tBdXPfYJHt/Ygjm2HpSdFRmZB8bofwGi3BMJq21bWoCGBhj4lYk9mZ2utDSS1E0xts5sc2N5PUXbHcMuQKHAYGEZZrkGUxb7FedqwFhmEf72E8NoLM6BKUdEqgcO0Arp858HAFx6dDOqX38e+NKXxkSmACIdV0WyjiWToqt336Vb4cIIivAFJLNkilFj0qHKqMWmEzb63sZL+Dk5kfNfkIfy86kxoKjGIxji4HK4UNLZGpkvEWOjHYN776UL5733jnnIqFedUpLODgBNjLE6xpgKwLUA3ozZ5k0AwmTeLwNYz02nfq4CPJ4ofe3F7V14beZqhFSqiA1tvPD7sXDHBrQZK9DnSi+5dqTXjoaiHGrwFa/cW0gC3XJLRIaqrobm729gX90CtA4603qfHpsbFzz0UVSJ98Zjg+i3eykZBqB/hAi1VOw8SCK3MMbwgwtnoM/uwbqjA5hbbuCfr8WANh+jtQ1Y2bEvcWvkTCJ8gzq642BdHXDiBPrtXswqzcV/XDITB3pGcEUxg8Y1Charpd95J/Dtb0e7muJF+LwlE42NMGjo87anGmZ+2WV0myTC9wVCGHB40ViUg6JcdThxeyKvFLW21ANWVAoZTHp12hp+MMRhZ7sVZ9aJonufj/IY8+cDTU3gGhrw/S0vQO0YSWzTjEP4Sa22sXjnHQpkRJ+N2AmXboTPGMPyOhN2d1jBpWHNDIY49Ns9ONA9EqkGF4quBAiEv2IFHedz5lAwsW8fbC4fGgc7IA/4owcKJSL87duB558nC3CcC2fBqUT4vCZ/F4D3ABwB8ArHcYcYY/czxi7nN/szABNjrAXA3QDGlq1NBwiSDihh+tdP2zFnbi1kV15JA4YznJkahUceQUHbMfz23K+juT+9yPtIrx1zynjdN16En8DJIpcx1Bfq047wtzQPoWVgFK/tilxQhIZOh3tJfzfzcsGY3iBJcHZDIVbUE6kICawyXp5oXngWVnQeRIE8zlxYr5ecIWlG+CW5Glhd/ki1cW0t0N6OfrsHFfla3HleIz69dw0emsevJmJlqKIiKiYSr1biRfgbN9Kc47lzwxWUKYeZX389kUaSjqX9dg84DqjI16LGqEPHsAtuXxDHckpQMtCVVjfOTAahHOm1w+EN4IYP/wr8619057FjZMVcsABgDOzzn4fO70Vv49zE9t6iIoqAxRF+uq2R/X4aqHPppVHFaAU6JXL5i2kmJonF1fkYdvrgKkkQ4a9fD+uAFfe8ug+zfvIOlj+wDl/4w2Y8vI6fTyAUXQkQEz5AvDBrFrBvHyxOH+b38fKNUNjY0EB6vyVGuOA4srOWlMSt1gWo2vaUIXwA4DjubY7jZnAc18Bx3K/4+37Kcdyb/O8ejuOu5jiukeO4MzmOm+AsskmCSNJ591AfzCMe3LyylqbRGI3AOedQci7TxUlPD/Czn8F3yVp80Lg83MslGSxOH/rtXswWCL+ykir9xB7jJF71huKctAlf6ML49sFecBwN9RaknMNmOziOC0ePY3qDpMA9F82EQsbC7WyFFcIntYugDXhRemj32CeJvNnpoJiv7A0PTq+rA/r7YRsaCRdmFeaoIT/Gu1DSmfZVWkonsGDV9Xopb1FfD9x0EwxaPsJPVSFZX0/abZKLl+DBL8/XotpEPZfahkbRmV8GlcsZbu8RxpNPAv/4R/Tu5mnQm+YktO0nLND4PZj1p4coeg+FIk4iIel9OcVqGy+9PnHzPcbGOHWS1laI8ckndCyL9Ht6SRaO8tNN2gLA4ip+3nNuERG++BwdHATWrME7V9yKv+/pwTXLqvCLK+ehqTgHuzv4aurYCF+Q98RON96pYx2w4EuH1iNgyIvkf4RpbrFR/ltv0f/6y1+SGSAOTjVJ5/SBKML/8+YTqDXpsGZ2CR3Uu3bR1Kdvf5sKazLB3XcDgQBUf/wDTDlqtAyk7o53hI+sZ4sjfCA6yu/tJfuYcawbp6EoB11WV1QDs0TY3zMCuYyhy+LGIbMde7tssHsCWFFvhNXlR++IJxzhjykXT4GltUbsu+8iLOWTg8Lz3zTOgF8mR/6Wj8Y+KU0PvoBI8ZUocQtA29sdbvMAgArFjMboEzsRhIuNcPF58EFqRvfYY4BWK4rwJz7sWrBkluVrUGPUo8/uwWGzHe0F/D6Ik4Ht7SRB/f73Ua9RwbfNTgfbT1hwnttMHvLWVmrvsH8/JR/5QTZYswbf/MGT+OiMC5O/mIjwQyGaUWzUq2hgzo9/nPh5b79N77dmzZiHhJ46mUT4M0pyoFPJ0azKp/NY1Bajde9xAMAX97yLt2+aj19eOR83rKjBinoTDpntZD0VGqcJWLuWbKjC4B+ACL+rC7OuvhRLeo5i4P4HIxfDRIT/xhu0ChK32YiBSa/CsNM3JVPLJMIXg4/wd3VYsafThptX1kUq/QoKgH/+k0rpX3wx/dfcupXaENx7L1Bfj8binLQknQjh81FBPI+xYF2ME4E1FueA4xCuEk4EfzCEI712XLmoAnIZwzsHe7Hh2ADkMoY7VtNBfNhsR9+IB3laJXQqRRr/dDT06shzjHoVVHIZjrlk2Fs+E+oN68Y+Ic0qWwHF4VGHoggfQKWtL1z1S/8I37s/HQeJ4MXftYukhwceICfURRcBQDhp60gl6aQBgajL87SoLaQWHBuPD6JTIHwxifz619TnJYZYKvK1cHgDKSUmjuOwo92CS5y8syY/H/jjHynCnzMnaozkUNMc2FMVc82cSUHI6Gi4cVqBVklR7Z/+FHdyFwDS71etimtVXVFvwuwyQ0bHmkIuw4LKPOxl/PkiOk8+3ED+ea3XjRn/fCV8//yKPIx6A+gYGh0r6SgUwJe/HH2s8IlbXXsbbv/Sj6G4+abIY0KkL/5eOI4S0xddFMmxxYFRr4IvEILTlzo4mygkwheDT9o+vfkEDBoFvnxGZfTjMhk5GHbuHKvVJcKDD1JUeffdAICmkhw0D4ymvJof7rWjOFcdcVEIVs7YuasJSLGR926nsmY294/CFwhh9YxCnFVvwtsH+rDh6CDOqCnAsjojGKN9oaKrzGcBxIKxSGuInU1ngO3eTXq9GML/mG6EbxCqbXnC5yP8ypGBSITPcQkrg+NCuMB++ct0wup0VFDFIxzhu7MQ4Y94YNSroFXJw9PRNh0bBGrriHAEuaWzk8wDOTn03YuqiSNts5NH+a2DTgw7fVjcd5z+x7vuIh1/y5YxTqI8rTJ1Uy8hcXv8eFiWKGZ+irKHhsjLPmYnWul/ErlzxPjaihq8871zkr9vHCypLsCOAJ+H4Qm/d8SNlv38Cqm+nnoB8Y3u5vKTw44e7aT7Uq38zjkHuP12vP7b57C+8czo4jKdjs5FMeHv20ffU4xsFQvhdaxTIOtIhC+G2w23XIl3DvbiuuXVUZFpGBdeSJpnvAM5FocPk9b6ne+E2yE3FedixO2P6M0JcKTXEZFzAJJ0ZLJIPw4gqZOlvkgPxpBSxz/I6/fzK/Kwdn4pTgw5cbjXjvNmFiFHrUCtSU8Rvt2dFcIHIjr+gbkriIjXxUT5u3dTkisd6QW0JGYMGBQkndJSBNUaVI30R6x9g4N0kU6X8OfPJ6vr00/Td3jwYCTqB6BRyqCQsdRJ2zRgtrlRzudGBFuiwxtAdYWRJI/f/Y5+HnyQnvDTn9JtWyQVJjw/FeELE6LKjx8ky+gdd9BxNTIS0e95GDIh/GPHwv1gilyilskvvRS9fShE76nXU5VzFrG4ugA9el7e5KXPv2xpR6GwP7/4BV00//Y3AMCMklyo5DJ0HOXPqVTHm04H/OlPOFwzGwZNnLbesU6dd96h2xRDyk36qWugJhG+GB4POlwhMMbw9bNq429z5pm0DH3//dSv95vf0EFy113hu5r4MvmWJLKOLxBCy4ADc8pFhK9UEumLCT9JhK9RylFZoE1J+Pt7bGFiv2hOaXgFe/5MOvjnlBlwuJcknTHzOccJ4cLRP2NueE5uFHbsIOkszcpmhZxsieEInzGMlpSjcqQ/Iukk6N2fEIwBN9wA3HwzJTArKmIeZjBolamTtmnAbHOH3U8FOiVy+UCjoUhPF5svfxn4j/+g/MHNNwPnnUdPFJGL0JhOGK2XCH/b3Y1F+iCU7W30GVdWAlfwnVDiRPgp/7/GRvqsjh+HxUnbmpy8fl5VReTqESWTH32ULvAPPZRRT6l0sKgqH0P6AoRkMqCnBw6PHy9s68QyjY8uMNdeS/vLr9SUchlmleWiv4VfUaZZ92Nx+eM7kRoaovMt77xDQ+tFgUI8TGW1rUT4YrjdGPTLMK/cEF4ij4FCQVHX++8nd+t0dFBJ/Te+EdUPprGECP94krFmrYOj8Ae56AgfIA+vQPheb8oBIQ1F5NT5tHUYP3rjQNzZmQd67Jhbbgi3KFhRZ0J5ngaz+GlQc8oN6LS4MDTqG9v9b5wQIvy8XB0N7RZ/lg4H+cGXLcvoNanaNnLCDBdXoHqkPxw9ZUz4acCgUVA/nQmA4zj0WN3h440xFu6s2lCUQwHDSy8BP/sZff/33hs3QViYo4ZKLkNPEqfOkV479nTa8E0dT8hCUdiPfkTVpIIFUfj/tEo4vIHkwzk0GiLKnp5whJ9v51//rrvIiSMUWB0/TheutWvpvMgyinLVKC/MgT3PBPT04Jkt7XB4A1is8tCKUSYjp9W2beEalnkVeRhp540Qaa4oLU5vfMJftIhW3f/4Bzm8PvkkpZwDACY9yY5T0UBNInwxPB4MBWUpe5fgwguJeJubE28jOHl47V5AUY4aeVplUmvmjnbKD8xJRvhpWBcbi3JwtM+B657cihe2deKn/ziIQDDiexcStvNFQzUeumYhnrt1ebg0XrwPpdkifD7qztcqgYsvpmX2Ud4yuWsXkX+mhB9TfNVXUIoq+0CkSvXwYVqZpZkXSAcGrXLCko7dE4DTFwxH6ECk+CjcNE0mox77wng8o5GSrSLCl8kYyvI1SSWdF7d3QqWQ4dyRExSVCx7yM84gcsqP7rVv0CjAcUjdhZOvERFcUgY7n5O57jq6GLzwAhkXLrqILhBPPZW9OcsxWFxVALPeiJ6DLXjog+O4ZG4pChzWSJTNVxHjvfcA0ED4kgE+wZvmsTE86oNRH8dB9M1v0md5003An/9MfXfSIHzjFDZQkwhfBM7jgTUoS9mdUHBqJJV1Nm2ipXfMspUxhqbinISEHwpxePaTdsyvyKMlvRg1NVRtGwik5WS5YlEFLltQhoevXYSHr12ELosb7x6KVI8KCVvx2LyyPC0aRf//XJGslHDVkyEESSdfp4rom0IUKMyHzZDwy/O16Bx2hZPhnYZi5LvskSlFmTh00kSuRjFuSUfQxs0iD74AwZZYn6wdNz8gRYzyvMTWTLcviDd29+Dz88ug3bOLiojyxk7PEiMvnfYRQJjwWwedKM/TQDU8RJ9zWRl1knz1VWr/kZdHCeIsXnRjsbg6H93aAjjaOnDRnBI8fN0iCo4Ewp85k85JnvDnV+Th4uOfwjZnQfqSjtMXWTmKoVYDL79MeYp77qH/N2bVFA96lRwqhSzcWnoyIRG+CJzbDa9CNZZoY9HQQBn/WO05/EIcRf8xo/8ENJUkLor6uGUIrYNO3LKqdmwDqpoaihrM5rS86vMr8/CHry7hib8cdYV6PLGpLUyKB3oomTU/ztg8AUW56nBTr6xF+CK9GjU1wOzZkQTXjh0UxaZoixyL2WUG2D2BcBFTq55/fnt7ZOJUFuUcgJw6mfrwgyEO//3BcSy6/338/J+Hwpp7uaig7foVNfj91Quj+9zEIk7vlvIkXvy39pvh8AZw3bKqSI4kBQTracrEbZjwRylY6u+nWRIKBdUMnH02uYt27450WZ0kLK8zoT/XhCqPDX+8fgnUCjkRvjBLmDEKMj78EPD7McNnwaLe49i7/ILkL8yD4/gh7TkJqokbGmgFA5ASkMSOKYAxBqNOBYsk6UwhQiHIfD54FCrUp5J0AIry16+P7zMeGCDtsqkp7lMbi3NhcfowHMep8/TmEyjKVePz8+MQudCHo6MjY6+6XMZw2zl12N89gq1tJBkd6BkJJ2wTgTEWziVky6VTVUADXMJR7dq1wEcfUTfCNMkoFsJK5DDfivmwhm/7e+IErcT4astswqBRZuTDtzp9uPkvO/DwumbMKjXgmS3t+OW/KLcglnQq8rVjLcGxaGig40A0S7cin9or+INj21W8sL0TjcU5WCYfJUIW9PskSDvCLy8HhobQabaQHNrfHyHYuXPJ8nnTTdSLZpIxp9yAL6xdBv3oCJQ+L/UIsliiE6cXX0wrv61boX6TKpbfakwdiQMkwfmDXPwIX8DVV1Otzi9/mfZ+T1W1rUT4AngngU+pCi+pk2L5chpbJ3bNCDhOlX3hqsUYCE6dWFmnZcCBj44P4sYVNdQwLRaxhC+Tpb0MBYCrllTCpFfhoQ+O4Z5X9+GVnd1YVJWfshvj6qYizCzJHVfRVTyYctR47wercfki/qJ2ySV0Yr76KkXk4yD8xFVpAQAAIABJREFUWaW54ZoBjz+II2qe8NvbyXtdWkpulyzCoFVk5MO/68Xd2No6jAe+OB9vf3cV7ji3Hu3DLijlNM4vIzQ0ENmL6jLK87UIcdGjJQGSjfZ02nD1GZVggmSWAeGnFeEDyLEO0epYTPgnAflNtfSL2Rxpeywm/DVr6OLz3nvAa6/BXDMT6wJ5aVW6WtId4XjttRHLahow5agkW+aUgid8nUFPy8BUKKDeHRgZGfuYkMxNRPi8U0eophXwzJZ2qBQyfHV5AruakA8QCL+kJKOoSaOU4+tn12JHuxVvH+jFl8+oxG++vCDl876xuh7v/WB12u+TDhqKciI+5tWryY3ywAP09zgIX6dSoK6QagYGHV5YtAb4tTqK7t95hxJqqjS7OKaJXI0Sbn8w0rRNhFd2duE9Ub7kQPcItrQM456LZ+Cry6vBGMMPL5mFey6agcsXVqS86I5BHKdORYFQfBVN+JubqRfPeTOLKSmuUIzx3MdDRpIOgBLH8NgI/2RANI86bG4Q709eHklLL7wAbNmCwYsvg9XlT1mVDoiGtKfbAjpNiCP8w2Y7trYNp3jG+CARvgCe8A0FiacSRUFIeMUj/OPHyTefwGdcaiDb4wvbOsOWt74RD17b1Y0vLqpIrN3qdBTRd3Rk1D5YjDvOrcfjX1uCrT9agwe+OD9KSjhpUKvJntncHO0eyRBCzUC/3QMwBm9VDSUJlUoq9skyhBbJ8WSd3713DHe/vBe9fA+iJz9uQ45agWvPjBwTjDHc9bkm/NdXFo55fkrEIfxE1babW4ZQnKvGjJIcqv6cM4c+8xQISzqpZCue8EsdwxEN/2QSvrjvVH8//R7rhb/kEpL7ABTffD0AYP3RsbblWAiknFTSGQeMelW40vbX7xzBnc/vTqsPVqaQCJ9H0Ell6gWmLBF+Q0PChA1jDN86rwHNA6N4/zBFIA+va0aI43DX5xqTv69gzUxSdJUMaoUcl8wrC7cGmDYQ3DqzZiXsKpgKc8oN6La6I1KZIIF95Sspi1/Gg0g/nWhZx+byYdDhhdMXxP3/PIwemxv/OtCL686syt7nXl5OFkcx4fPJ8B4R4YdCHLa0DGFVYyGZAPbuHTN1KRH0KjnkMpY6wucj6mqPDcXyIEmd04Xw40X4AOn4ADB3LspWLMbMklx8eKQ/5UsLxVFpD3lJE0adCg5vAJ+0DuHj5iHcsTrx0PqJQCJ8HgOD5FgxFSa3qoWRjPCbmxPKOQIuW1COWpMOf9zQitbBUbyyswvXL69BlTFF/mCChD9tIfiVxyHnCBBqBjbwkZqigW9oFW88XxaQqCe+cMFZUW/EOwf7cNcL1AL6ppV1yBpkMnKKiQhfq5LDqFdFEf6RPjuGnT6sbCwkPbu3lwqE0gBjDAaNIjXhG43wKVSYEbSDCZr5ySR8g4Eqa83mxIS/ZAlVwfIrvzWzi7Gj3Zryfx0OR/gZ5lxSQHD93P/PwyjMUeGGs+JMGMsCJMLn0d1L1YFFRRMk/FCICD+BQ0eAXEZR/oGeEdz+3E6oFTJ8+/wU0T0QIfyBgdOL8Ovrae6AqA1FphCGrGxpGYJKLoP6W3dQD5rly7O1l1GIjDmMjvCFKupff2kBGor02NNpw2ULyrIvn8WW8oPsnWJJR9DvVzUVkpwDpB3hA0J7hRSJacYwYDChxmONSCgnk/AZiwwM6u+nc1Ub89nLZGQT5YOBNbNLEAxx+Oh48jnallEftEo5tOkOaU8TgkR0tM+BO1Y3ZM0gEYsJET5jzMgY+4Ax1szfFiTYLsgY28v/xI4/nBbo6yPCLy3JT7ElD6Gtayzhd3VR24MUET4AfHFxJcryNGgddOK2VXXp9f+uqaF8A8edXoQPAD/5yYQi/KJcNYpy1XD6gig2qMEWLKACmElCbnjMYUyE3z8KnUqOGqMOv/7SAhTmqPHNcxuyvwMNDdRATeQuie2Lv7llCDNKcqin0DgJP1XU6/D40aMzosQxPD0IHyCZSZB00tiXRVX5MOpVWJdC1kl7oleGECp3C3PU+NqKyYnugYlH+D8EsI7juCYA65B4dKGb47hF/M/lCbbJPjguvuQSBwODtF3aSVulkpKosa+fwqEjhkohw90XzkBTcQ5uW12f3vuKZ2KeboSfBQiyTlQf/ElCop74zQMONBXnQCZjOLPOiJ0/vmBsX6RsoKGBahf6IyRVnq9Fj9UNjuPg8Qex/YQFqxp56+7evRT5ZlDUlqhj5mu7unHNnz6FLxBC26ATAzlG5NuGEksoUw0hwhdX2SaBXMZw/sxibDw2GNV+JBbDTh9MiYquJoDyfBpEf+d5DVlfPYgxUcK/AsCz/O/PArhygq+XXTz3HJGizZZy0yFewxcPMU+JvLyxhC948FNIOgKuXlqFD+4+N/1knpjwJ7FE/VSF0GG0dCoIX4jwx0g6o2gqGV/iOSPEs2bma+H0BWH3BLCz3QpvIIRVTXxNwr59aev3AhL1C/ro+CC2nbDg5R2daB0cRV+uCdrBvsjFJ81GZJOGioqIhp9mwv6C2cUYcfuxs8OKzmEXtrUNj/HmW5wZDGnPAJUFOqy7+1waqTqJmCjhl3Ac1wsA/G2ib1nDGNvJGNvKGEt6UWCM3c5vu3NwMLmelhJ/+QsNYuhPI/s+zHviY7W+ZEhE+Drd5JGxFOEnhRDhFxuym1SLB71KARmLlnQEh05Tqn5M2QA/2Uvo/AhErJlvH+jF7949Aj0XwPI6E8mAR45kJOcAiVskd1nI1fbI+hYc6BnBgKEQMrebxh0WFGS95iFjVFRQMV9bW9qrjVVNhVDKGW748zas/t0GXPPEVuwUZt7ySNhHJwuoL8oZ204ly0hJ+IyxDxljB+P8XJHB+1RzHLcUwFcB/A9jLKGgyXHcExzHLeU4bmlRBlWkY9DXRw3MgEgDrQQYcfnhG+WnB000whccOpP1xeXnR2yLJ3vZPA0hRPhTIenIZAw56ugGaoJDZ8ZURPjiQjweQmL43r8dwDUv/De2//Uu6D1Oah4XDGYe4WtI0omNdLutLswuM2DQ4cXzWzsRLOWDj927J8UCmzEEa2YwmPb+5GqUuPvCmbh8YQV+ehn1XdrZPpbwJ0PDnyqkTAVzHJewqxBjrJ8xVsZxXC9jrAxA3MoFjuPM/G0bY2wjgMUAWuNtmzX87W/kmAFSEv6JYSc0Ab6sOVPCj5WLjh8nu9dkgTGK8vv6Tn4UNQ1RX6jHfV+Yg7Xzpmb1Q5JHRNIR5hU3TkWELy7E4zGjJBfnzijCBXIbrvv9mzSo/P77qacNMK4I3x/k4PGHwtqyyxfA0KgPN6+sQ0W+Bh8eGYCmpoqecOwYcO65Wfn3JgTxCjuDC9C3zovEos992o49nRHCd/uCcPuDiRunnQKYqKTzJoCv879/HcA/YjdgjBUwxtT874UAVgI4PMH3TY1XXolUE9rtSTdtH3JCLRD+RCQdv5+q99JI2E4Is2dH9FsJUWCM4eaVdVnr7JkKsQ3Ujvc7oFPJp66CWTwjAeTFf/aWM3HDu8+AqdXAl75EvYReeYW86RkeNwYtxYTixG2XhVxAVUYd7rl4JhgT9a/huOmx8hRPKBvn/iyuLsCeLlt4dTPMF11NlqQzFZgo4T8I4ELGWDOAC/m/wRhbyhjje4RiNoCdjLF9ADYAeJDjuMklfEHOueoq+jtFhN8+7IQmOM4IX0z4J07QEnKyCf/RR4HXX5/c95CQFmIbqLUMjKKRd+hMCWIIHwAlZ196Cfj+92ksol5PjcLmz8+4Y2W8BmqCfl9VoMWsUgNe/9bZuOZyUbfJ6UD4ZWURWXWcEtOiqnwMOrwwj1DblYM9FDhWG1O0T5/GmBDhcxw3zHHcGo7jmvhbC3//To7jbuN//4TjuPkcxy3kb/+cjR1Pitdfp0jj1lvp7xQRfsewC4VyXqOcCOELQ6Xr07RYjheFhWNmrEo4OcjVRLtYjvc70FQ8Bfq9AIHwxRr7j39MuZ577iG3zM9+RvdnKOcA8fvpdFl5wuerwpdUFyDPmEs98IHpQfhKZcQpNO4In2pyBFnn/UN9yNcpsaw2brnRKYHTs9L21VepQZQwbSaNCL9IGSJNXJbBR5KXRy4goSe+4AaS3DOfGRg0ERfLiMuPAYeXmpRNFWpq6BgcoopatLUBb70F/Nu/RTq6fvvbwG23ATfemPHLC3bhEVe0pKNVysdKG4JuPh0IH4gEReO0iM4qNUCtkGFvpw3+YAgfHunHBbNLoJCfurR56u55Ijh5R8JXvkJ6vEyWloZfKA9lFt0DY9srCH1ETrYHWcKUwaCNDDJvHqDAommqCR+IWDP37KFboRkdQNHuk0/S5KkMEVfSsbpQZdSOtRAKBDtdCL+8nFYd4zQ3qBQyzKvIw54uG7a2DcPuCeDiudPAgTQBTE7DhpMJvZ4q7Lxe0vAMhqQR/ojLD6vLjwJ5KLOELRBN+IV8cyqNBsiZwhNewkmFQaOEwxtAMMThED9ta0osmQJqa+m2o4PaUuzfT0FOlsY5xpV0LC5UFcRp8jfdCP/GG8fdalvA4qp8/HVrB97a1wudSo5zmjIbvTndcPpF+ABFNALp5uYmjfA7LDT0IA+B7ET4xcWT58GXMO0gtFcY9QSw6fggakw6VMYjw8mCeAoaQITf1ESWzSxA6BckRPgcx6Hb6o7f1XW6STpXXx3JX4wTi6rz4Q2E8Lc93ThvZtGktCyeSpx+EX4sUkT47cOUgMpFMHuEL+EzA4EQB0e9+KR1GFcvTTGLNtvIz6djXEz4E4xqxVDIZXxxGclWNpcfo95AfMK/7DLy4Z9GLT8WV1MexB/kTnk5BzhdI3wxUkX4/Fgzfcg/MUkHIMKfLtGNhCmBkNTccHQAbn8Q586YQHX4eCE4dRwOStqOw42TDOKOmWGHTkGcc+XMM4GXX044+OdURHmeBsW5aijlDOfPOvWDudPnm0kEgyFpx8wTw06U5Wkg93qyE+Fn+WSTML0hFCb9c78ZKrkMK+pNU78TAuEfPEh/pzGvNhPkioagdFqiLZmnOxhj+NKSSox6/dNvStw4cPoTfm4u9ahPgI5hF2pMOmouNRHC5zhJ0vkMQiCB/d0jWNlogl59Ek6pmhpg82aSc4CsE36eqGOmuMr2s4Ifrp11snchazj9JZ0UGn7HsBO1Jj15mSci6YyMUHc+ifA/UxBHfSdFzgGI8G024OOP6Xivrk79nAxg1KvQOeyCxx9El9WFAp0SOSfjwiZhwjj9CT+Jhu/w+DE06kONST++CP//t3f3QVbV9x3H3x+QuyjPiICwYjChaZD4kG6J1CSND2PQWIl5mOhkRqamYWzrxDqdqTpM69Q0nXZ0+hgbw2hr0lptYkOkigqatCZ/+LAmxkARRXxaEV0VAaWwLHz7xzl39rrcy+5y7u7de3+f18zO3nPuj3t+P8/62d9+77nnN25c9kti505fg5+ockkH4Ld/rUHnvnylztq12ey+zleJXbJ4Htt37eUff/xcdklmQrP7VtP6v6bLM/yIQ/5HeCm/Qmf+jLykM9QZPvTdXsGBn6TyTHf25PEj+wnbSuVr8XfsqHs5B7K/XL74G+3c8j9bmVAayycXNOgvGSssjRl+RPYJ3H5efCvbd2K5pDPUGT448BN31NgxzJjYxtkfmTnsi1fUVLkozjAEPsCffnYh0yeU2LW3l/bpI3QnUKu71g/88mLjVer45Rn+Eb9pC4cGvi/LTM4PrljCdY18Y2/mzL6f3WEK/CnHjOObn1sEwAdn+JPkzar1A7+8OlSVOv6Lb77HzEltHFM6qn4lnSEsEG2tYf6MCUxq5CV7Ut8btYsWDdthzjt5Nv915SdYdnrrfLAqNWnU8OH9M/znn2fj0TO4f8N2Fs+fnpV8ipR0XnklC/zp07M3cs1G2vz50NvbN8EZJh9tnzKsr2/Dq/UDv/8M/6c/hU99iuuvuo3Js07kLy/+aPY/ysEjuHkavH+G7/q9NcpNNw14G3CzQiUdSV+StFHSQUkdh2m3VNJmSVskXVvkmEPWb4a/d+MmACbtfJvbL1+cLYX3f9mHSQrV8F9/3YFvjbNoESxZ0uhe2ChXtIa/Afg88EitBpLGAjcD5wMLgUsl1eferYPRb4b/woYtAFz1yRP7bmO7N1vC7IgDf8+e7JbMDnwzG8WKLnG4KSI2D9BsMbAlIrZGRA9wF7CsyHGHpN8Mf9/LrwKw8Ni2vjblwD/Skg5k9zLxFTpmNoqNxFU6c4HKm9l05fuqkrRCUqekzu7u7kIHfmzrW/zFI13ZRj7Dj+3bASgd6Ft4unBJB7L3ATzDN7NRbMA3bSU9BFS7EfTKiLhnEMeo9mmUqLIveyJiFbAKoKOjo2a7gTzybDdf+14n+/YfYOXYsSif4bd15+vO7tvX17hoSafMgW9mo9iAgR8R5xY8RhdwQsV2O7Ct4Gse1sObXuf3/+3nHD91PC+9tYeeCRNp272b3gMHmbQjX+y5p6fvH5TDv63t0BcbiAPfzJrESJR0ngAWSJovqQRcAqwZroPteK+Hr9/5Cz48exI/+oMzmXL0OPaUjoFdu3jl7T0c996OrGHlDN+Bb2YJKHpZ5sWSuoAlwH2SHsz3z5G0FiAieoErgQeBTcD3I2JjsW7XNm1CiVuX/yZ3fO3jTJtQ4uQ5k9k57mjYvZsXn9/G+N58Zl+vwC+/KQwOfDMb1Qp98CoiVgOrq+zfBlxQsb0WWFvkWEOx5IN9qw6dPGcyb49pY97OnWzf/EJfo+GY4fsqHTMbxVr+XjqL5k5hd+lo9u3YyY7nKy4WqncNv1R6/2zfzGyUafnAP3nOZN4tHc3+HTvZ+3JF4Ndrht/Wln3NnFn3hSfMzOqp5QN//oyJ7B0/gdi1iwPbXut7ol6BD9ks3/V7MxvlWj7wx44RbdOnMPa9d5m88y0OlErZ7RbqGfhTpzrwzWzUa/27ZQITj5vOMXv3MOvdt9g/czZj9+6pXw0f4IYbfB98Mxv1kgj8abOOZQzBiTu2M6Z9NrzaVd8Z/pe/XLyTZmbDrOVLOgAz5maLLp+041XGtc/Ngr3arRWONPDNzJpAEoE/a05Wbpmy9110/PFZsPcv6UhwVBJ/8JhZopII/KOmTe3bmD370Bn+vn3ZPl9WaWYtLInAf986n8cfn31Iqlrgm5m1sDQCv/ITsLVm+Edya2QzsyaSRuD3n+FXq+F7hm9mLS6NwK+c4bukY2aJSiPwyzN8KftEbK03bc3MWlga1yGOH59dcjl9evbdgW9mCSq6AMqXJG2UdFBSx2HavSjpV5KektRZ5JhHRMpm+bPzpXldwzezBBWd4W8APg98ZxBtz4qINwse78hNnpzV78E1fDNLUtEVrzYBqBk+sHTZZXDSSdnjaiWdiRMb0y8zsxEyUjX8ANZJCuA7EbFqhI7b54Yb+h67pGNmCRow8CU9BMyu8tTKiLhnkMc5MyK2SZoJrJf0TEQ8UuN4K4AVAPPmzRvkyw+RSzpmlqABAz8izi16kHxRcyLiDUmrgcVA1cDPZ/+rADo6OqLosatqa4P9++HgQRgzxoFvZkkY9uvwJU2QNKn8GDiP7M3eximHe7ms48A3swQUvSzzYkldwBLgPkkP5vvnSFqbN5sF/EzSL4HHgfsi4oEixy3MgW9mCSp6lc5qYHWV/duAC/LHW4FTixyn7kql7Hu5ju/AN7MEpHFrhf7K4e7AN7OEOPAPHIDeXge+mbW8tAO/p6f4AuZmZk0izcCvrOGXA98LoJhZi0sz8CtLOp7hm1ki0g58l3TMLCFpBn61ko4D38xaXJqB75KOmSXIge/AN7NEpB34ruGbWULSDHzX8M0sQWkGvks6ZpYgB74D38wSkWbgl0s6ruGbWULSDHzP8M0sQWkGvt+0NbMEFV3x6kZJz0h6WtJqSVNrtFsqabOkLZKuLXLMupCy0HdJx8wSUnSGvx5YFBGnAM8C1/VvIGkscDNwPrAQuFTSwoLHLa5U8gzfzJJSKPAjYl1E9OabjwLtVZotBrZExNaI6AHuApYVOW5dtLU58M0sKfWs4V8O3F9l/1zglYrtrnxfVZJWSOqU1Nnd3V3H7vXTP/DLdX0zsxY14CLmkh4CZld5amVE3JO3WQn0AndUe4kq+6LW8SJiFbAKoKOjo2a7wipr+KVSVtc3M2thAwZ+RJx7uOclLQcuBM6JiGoB3QWcULHdDmwbSieHRXmGv3evV7sysyQUvUpnKXANcFFE7KnR7AlggaT5kkrAJcCaIseti8qSjuv3ZpaAojX8bwGTgPWSnpJ0C4CkOZLWAuRv6l4JPAhsAr4fERsLHrc4B76ZJWbAks7hRMSHauzfBlxQsb0WWFvkWHVXWcN34JtZAtL8pC14hm9myXHgO/DNLBHpBr5LOmaWmHQD3zN8M0uMA9+Bb2aJcOA78M0sEekGvmv4ZpaYdAPfM3wzS4wD34FvZolIN/BLJdi/P7t5mgPfzBKQbuCXQ373bge+mSXBgd/T48A3syQ48Ps/NjNrUekGfuWShl4AxcwSkG7ge4ZvZolx4Pd/bGbWogotgCLpRuB3gB7geeB3I+KdKu1eBHYDB4DeiOgocty6qCzpOPDNLAFFZ/jrgUURcQrwLHDdYdqeFRGnjYqwB8/wzSw5hQI/Itbla9YCPAq0F+/SCHHgm1li6lnDvxy4v8ZzAayT9KSkFYd7EUkrJHVK6uzu7q5j9/px4JtZYgas4Ut6CJhd5amVEXFP3mYl0AvcUeNlzoyIbZJmAuslPRMRj1RrGBGrgFUAHR0dMYgxHBnX8M0sMQMGfkSce7jnJS0HLgTOiYiqAR0R2/Lvb0haDSwGqgb+iPEM38wSU6ikI2kpcA1wUUTsqdFmgqRJ5cfAecCGIsetCwe+mSWmaA3/W8AksjLNU5JuAZA0R9LavM0s4GeSfgk8DtwXEQ8UPG5xLumYWWIKXYcfER+qsX8bcEH+eCtwapHjDAvP8M0sMf6kbf/HZmYtyoHf/7GZWYtKN/BdwzezxDjwwYFvZklIN/DHjIFx47LHDnwzS0C6gQ99s3wHvpklIO3Ab2vLZvlj0v7PYGZpKHQdftNra8sWMTczS4AD34FvZolIu5ZRKrl+b2bJ8Ax///5G98LMbEQ48B34ZpYIl3Rc0jGzRKQ9wx8/Hnp7B25nZtYC0g78q6+Gffsa3QszsxFRuKQj6RuSns4XQFknaU6NdsslPZd/LS963Lq48EL4whca3QszsxFRjxr+jRFxSkScBtwL/Fn/BpKmA9cDHydbz/Z6SdPqcGwzMxukwoEfEbsqNicA1RYy/wywPiLejogdwHpgadFjm5nZ4NWlhi/pm8BlwE7grCpN5gKvVGx35fuqvdYKYAXAvHnz6tE9MzNjkDN8SQ9J2lDlaxlARKyMiBOAO4Arq71ElX3V/hIgIlZFREdEdBx33HGDHYeZmQ1gUDP8iDh3kK/378B9ZPX6Sl3Apyu224H/HuRrmplZHdTjKp0FFZsXAc9UafYgcJ6kafmbtefl+8zMbITUo4b/V5I+DBwEXgKuAJDUAVwREb8XEW9L+gbwRP5vboiIt+twbDMzGyRFVC2ljwodHR3R2dnZ6G6YmTUNSU9GREfV50Zz4EvqJvur4UjMAN6sY3cayWMZnTyW0auVxjPUsZwYEVWveBnVgV+EpM5av+WajccyOnkso1crjaeeY0n7bplmZglx4JuZJaKVA39VoztQRx7L6OSxjF6tNJ66jaVla/hmZvZ+rTzDNzOzCg58M7NEtFzgS1oqabOkLZKubXR/hkLSCZJ+ImmTpI2Srsr3T5e0Pl88Zn0zrSUgaaykX0i6N9+eL+mxfCz/IanU6D4OlqSpku6W9Ex+jpY067mRdHX+M7ZB0p2SxjfLuZH0z5LekLShYl/V86DMP+R58LSkjzWu54eqMZYb85+xpyWtljS14rnr8rFslvSZoR6vpQJf0ljgZuB8YCFwqaSFje3VkPQCfxwRHwHOAP4w7/+1wMMRsQB4ON9uFlcBmyq2/xr423wsO4CvNqRXR+bvgQci4teBU8nG1XTnRtJc4OtAR0QsAsYCl9A85+Z2Dl1Po9Z5OB9YkH+tAL49Qn0crNs5dCzrgUURcQrwLHAdQJ4FlwAn5//mn/LMG7SWCnyy1bS2RMTWiOgB7gKWNbhPgxYRr0XEz/PHu8kCZS7ZGL6bN/su8LnG9HBoJLUDnwVuzbcFnA3cnTdpprFMBj4F3AYQET0R8Q5Nem7I7qN1tKSjgGOA12iScxMRjwD978VV6zwsA74XmUeBqZKOH5meDqzaWCJiXUT05puPkt1dGLKx3BUR+yLiBWALWeYNWqsF/qAXWhntJH0AOB14DJgVEa9B9ksBmNm4ng3J3wF/QnZjPYBjgXcqfpib6fycBHQD/5KXqG6VNIEmPDcR8SpwE/AyWdDvBJ6kec8N1D4PzZ4JlwP3548Lj6XVAn/QC62MZpImAv8J/FG/JSSbhqQLgTci4snK3VWaNsv5OQr4GPDtiDgdeI8mKN9Uk9e3lwHzgTlkS5OeX6Vps5ybw2nanzlJK8nKvHeUd1VpNqSxtFrgdwEnVGy3A9sa1JcjImkcWdjfERE/zHe/Xv4zNP/+RqP6NwRnAhdJepGstHY22Yx/al5GgOY6P11AV0Q8lm/fTfYLoBnPzbnACxHRHRH7gR8Cv0XznhuofR6aMhMkLQcuBL4SfR+WKjyWVgv8J4AF+dUGJbI3ONY0uE+Dlte4bwM2RcTfVDy1BlieP14O3DPSfRuqiLguItoj4gNk5+HHEfEV4CfAF/NmTTEWgIjYDrySr/0AcA7wvzThuSEr5Zwh6Zj8Z648lqY8N7la52ENcFl+tc4ZwM5y6We0krQUuAa4KCL2VDy1BrhEUpuk+WRvRD8+pBePiJb6Ai4ge2f7eWBlo/szxL5/guxPtKeBp/KvC8hq3w8Dz+Xfpze6r0Mc16dRgTEnAAAAj0lEQVSBe/PHJ+U/pFuAHwBtje7fEMZxGtCZn58fAdOa9dwAf062Ot0G4F+BtmY5N8CdZO897Ceb9X611nkgK4PcnOfBr8iuTGr4GAYYyxayWn05A26paL8yH8tm4PyhHs+3VjAzS0SrlXTMzKwGB76ZWSIc+GZmiXDgm5klwoFvZpYIB76ZWSIc+GZmifh/RvZjOtZEQMAAAAAASUVORK5CYII=\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# amygdala\n", + "timeCorr('mid', 'vmPFC','vmPFC', '1', '2')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/.ipynb_checkpoints/RSA-checkpoint.ipynb b/task_based_analysis/.ipynb_checkpoints/RSA-checkpoint.ipynb new file mode 100644 index 0000000..1601992 --- /dev/null +++ b/task_based_analysis/.ipynb_checkpoints/RSA-checkpoint.ipynb @@ -0,0 +1,17130 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "# Map beta of each condition and correlate between sessions" + ] + }, + { + "cell_type": "code", + "execution_count": 327, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [], + "source": [ + "# import relevant packages\n", + "import glob\n", + "import numpy as np\n", + "import scipy\n", + "import nilearn\n", + "import nilearn.plotting\n", + "import nilearn.input_data\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import statsmodels.stats as sm # for FDR correction" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## No apperant contribution to before/after treatment in general. \n", + "- Lets look at group differences in ROIs $\\rightarrow$\n", + " * Amygdala\n", + " * vmPFC\n", + " * Hippocampus\n", + " * Striatum\n", + "- We compare pattern of ROI activation in the trauma > relax contrast on the 2nd day" + ] + }, + { + "cell_type": "code", + "execution_count": 376, + "metadata": {}, + "outputs": [], + "source": [ + "thr = 0.05 # set threshold\n", + "def fdr_corr(p, thr=0.05):\n", + " # FDR correction\n", + " # takes the p from the t test, flatten and return a 36x36 mask\n", + " # flatten p\n", + " pflat = p.flatten()\n", + " fdr = sm.multitest.multipletests(pflat, alpha=thr, method='fdr_bh')\n", + " fdrArr = fdr[1].reshape(36,36)\n", + " return fdrArr " + ] + }, + { + "cell_type": "code", + "execution_count": 234, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Amygdala as mask\n", + "mask_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=21\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "\n", + "\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " smoothing_fwhm=None, verbose=0).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 405, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# now lets do the same with vmPFC\n", + "mask_file = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=5\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None, standardize=True,\n", + " detrend=False, verbose=0).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 406, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [], + "source": [ + "# compare between groups\n", + "import pandas as pd\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "medication_cond\n", + "\n", + "group_label = np.array(medication_cond.med_cond)\n", + "group_label = list(map(int, group_label))\n", + "\n", + "sub_list = np.array(medication_cond.scr_id)" + ] + }, + { + "cell_type": "code", + "execution_count": 407, + "metadata": {}, + "outputs": [], + "source": [ + "subject_list = []\n", + "for sub in sub_list:\n", + " sub = sub.split('KPE')[1]\n", + " subject_list.append(sub)\n", + "#subject_list.remove('1351')" + ] + }, + { + "cell_type": "code", + "execution_count": 408, + "metadata": {}, + "outputs": [], + "source": [ + "# function to find ev number (lookin in run.fsf file)\n", + "def findEV(txtFile, condition):\n", + " # takes the txtFile and the specific condition\n", + " with open(txtFile) as f:\n", + " datafile = f.readlines()\n", + " lines = []\n", + " for line in datafile:\n", + " if condition in line:\n", + " # found = True # Not necessary\n", + " #print(line)\n", + " lines.append(line)\n", + "\n", + " return lines[0].split('evtitle')[1].split(')')[0]\n", + "\n", + "def getCorr(sub, condition):\n", + " fsf_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses{ses}_Nosmooth/modelfit_ses_{ses}/_subject_id_{sub}/level1design/run0.fsf'\n", + " betaTemplate = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses{ses}_Nosmooth/modelfit_ses_{ses}/_subject_id_{subject_id}/modelestimate/mapflow/_modelestimate0/results/pe{betaNum}.nii.gz'\n", + "\n", + " # get beta files for session 1 condition X\n", + " beta1 = fsf_template.format(ses='1', sub=sub)\n", + " number_1 = findEV(beta1, condition)\n", + " # find beta file\n", + " betaFile_1 = betaTemplate.format(ses='1', subject_id = sub, betaNum = number_1)\n", + " beta1_transform = masker.transform(betaFile_1)\n", + " # get beta files for session 2 condition X\n", + " beta2 = fsf_template.format(ses='2', sub=sub)\n", + " number_2 = findEV(beta2, condition)\n", + " # find beta file\n", + " betaFile_2 = betaTemplate.format(ses='2', subject_id = sub, betaNum = number_2)\n", + " beta2_transform = masker.transform(betaFile_2)\n", + "\n", + " #correlate it\n", + " cor = scipy.stats.pearsonr(beta1_transform[0], beta2_transform[0])[0]\n", + " return cor, beta1_transform, beta2_transform\n", + "\n", + "def generatCor(cond_list, beta1Arr, beta2Arr):\n", + " # this functuion creates a simple matrix of correlation between session 1 and 2\n", + " x = np.zeros([len(cond_list),len(cond_list)])\n", + " for i, cond in enumerate(cond_list):\n", + " \n", + " for j, c in enumerate(cond_list):\n", + " x[i,j] = scipy.stats.pearsonr(beta1Arr[i], beta2Arr[j])[0]\n", + " return x" + ] + }, + { + "cell_type": "code", + "execution_count": 409, + "metadata": {}, + "outputs": [], + "source": [ + "# get condition list\n", + "events_file = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/sub-1464_ses-1_30sec_window.csv'\n", + "cond = pd.read_csv(events_file, sep='\\t')\n", + "cond_list = np.unique(cond.trial_type_30)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 0 subject\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. 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Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + } + ], + "source": [ + "corTot = [] \n", + "corAll = []\n", + "corAllz = []\n", + "for i, sub in enumerate(subject_list):\n", + " print (f' Running the {i} subject')\n", + " beta1Arr = []\n", + " beta2Arr = []\n", + " conditions = []\n", + " for cond in cond_list:\n", + " cor, beta1, beta2 = getCorr(sub, cond)\n", + " corTot.append(cor)\n", + " conditions.append(cond)\n", + " beta1Arr.append(beta1[0])\n", + " beta2Arr.append(beta2[0])\n", + " corMat = generatCor(cond_list, beta1Arr, beta2Arr)\n", + " # adding z-fisher transformation\n", + " corMatz = np.arctan(corMat)\n", + " corAll.append(corMat)\n", + " corAllz.append(corMatz)" + ] + }, + { + "cell_type": "code", + "execution_count": 382, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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uBh6hSOLhIAiC2UYklWirR0qWWlV/DUz/rXctcGf+9Z3AR2pcriAIguo5znvexVikqjsA8n8XWjsWapv89G+/X+HpgiAIKkBSybY65KhPWBZqmzy5/mBomwRBMHNEtMnb2CUiS1R1h4gsAXYncVquW0zbsBMxMqb2TDnA2JQ9075ila9PsqDX9l242PddssD+xt6xxw516Jrj/0wbHLK/45pLJB85MG7XoxcxArCj367nMxbat/i8ZaP8bputf7F5u33eqcX+vW3J2HWxbautEwLQv8+OFho6ZYHre6jf1nn53z9iR8ikxI+gOOXA46Zt/zw7igXgjLW29skr6/3IqLZWuxGbnHDDcjg0aN+DvXttvZztr77uHnffNv/ew4Ul7Amo0151Eiq9svuB6/Ovrwf+rjbFCeoRr+EOglmlgce8S/a8ReQu4FKgV0T6yC2HvxW4R0Q+TU6g6rqjWcggCIKKaOCed8nGW1U/Zpgur3FZgiAIaktomwRBENQhoW0SBEFQh6Qi2qQm7EovM21zs7bmQ8/oTve481L2ZfyHS+a5vks2/sq0jZzlz/5n03box7r555q2pzb4s+w9XXZv4R0nHnB9l/KGaZvX96zrm83YkTfyxGbTdgrw3Pl/bNrPXmpnTOl2MigBDKmd6OG/HvIX9ravtLVnDr6wyfXtOf0k05Z5daXtOOVntNl72iWmbUT86KZ/t+BB09bU7Ad87TjxYtM2WiKaa8F4n2lrW2R/NlNn2RE7ADLhZ3aqSbRJA/e8K9U2+YaIvCIiz4vIT0Wk5+gWMziW8RruIJhVRJJtdUil2iYPA2eq6tnAq8DNNS5XEARB9TTwCsuKtE1U9SFVPazH+Riw/CiULQiCoDpq2PMWkStFZL2IbBSRt43ZSY6/ytufF5HzC2w9InJvfsTiZRF5d7WXVouvnE8B/2AZC7VNfnL3D2pwuiAIgmRoOp1oK4WIpIFvA1cBa4GPicjaabtdBazObzcA3ymwfQv4haqeBpwDvFzttVU1YSkit5BLPvwja59CbZNnN+wJbZMgCGaO2g2JXAhsVNVNACJyNzl11ZcK9rkW+IGqKvBYvre9BBgC3g98AkBVxwF7Fj8hFTfeInI9cA1web6wJfnHl3pNm6ptu2D1iHvc7JT9s6d13M/U0rHiHNfuMZFpMW2L0/tM2+kn2FEQAN2t9iz9qgn/C3tz0+mmbeJEu7wALZN2Fp6eQTsryrmv3cXLp/6BaT803m7aVo6/4Japd8p+xpveeb5pA9AuO0fIPC/VESBtdgTGoVUXmLZ01v9MbplcZdo27/SjTT7UY0f80G0KewKwf9KOukqn/AiZ1sE9pk2dUDzN+EI8I3Pt6DOAUsoniahd470M3hLK1Qe8K8E+y8h1cPcAfy0i5wBPA59X1aFqClTRlYnIlcBXgA+rqv2JD44LvIY7CGYTFUm0FQ7v5rcbph2qWA9xeqfV2icDnA98R1XPI9cTrzqBTaXaJjcDLcDDkhvsf0xVb6y2MEEQBDUlYc+7cHjXoA9YUfD/cmB7wn0U6FPVw5KS9zITjbehbXJ7tScOgiA46tQuhvtJYLWIrAK2AR8F/mjaPvcDn82Ph78L6D+ctEZE3hCRNaq6npwu1EtUSSyPD4KgYUkSSZLoOKqTIvJZ4EEgDdyhqi+KyI15+3eBB4CrgY3AMPDJgkN8DviRiDQDm6bZKiIa7yAIGpcaLsBR1QfINdCF73234LUCf2L4PgvYM90VMKONd5NzttYW++fNZNa/Ae0Ze4Z/aMKPsNjZdoJpy8ikaQMYV3s2fWjMnivfusefhT/BSfKyvetk17cNWy9iSvzbPZG262p02WmmbdXQOn564FLTnnE6PwuXneqWaWjKjlQ5o8PXvMHRvCmFOD22Pc12lMS8yV3ucUfG7DJl0n7Q1o52W2tH3jZ39lZe2WErWAwO+0MLJyyzo3Yka0eqNI/YEUoAo82drr0WaJ2unkxCRdomBbYviYiKiB3nFzQ8XsMdBLNKaJu8TdsEEVkBXEEuk04QBMExh0oq0VaPVKRtkucvgS/z9ljHIAiCY4NUOtlWh1S6SOfDwDZVfS7Bvm8Gv//LL7wwyiAIgtqSdJFOPVL2jI6ItAO3AB9Msn9h8Pv//fNky+iDIAhqQp0OiSShkun4k4FVwHP51ZXLgWdE5EJVLTH9b+N9+fW0+Cvw56RtiYCs2jPlAJNq/2QS8b9r0pI1bf2jduTGCQsmGJ6wz/vGXjsaRcTPDHRSl30Lmqd8jRgPr3fykXm/4od97zftwyN2PWaX+h+urNr23SunS0tM8xW7jtsW+VEu3W88b9p+s2mJ47mES0+2sxmlJuy6mHQ0ekqRLfEjWtU+dv+A/RwDrBM7K9SYeiFkMLfV/uxu3tflnvcPXWsytOiK9cag7MZbVV8A3lTBEZEtwAWqureG5WpovIa7HvEa7uMNr+E+3vAa7pmiXicjk5AkVPAu4LfAGhHpE5FPH/1iBUEQ1IAGzqRTqbZJoX1lzUoTBEFQQ7J1GkmShFgeHwRB41KnkSRJiMY7CIKGpZHHvKPxDoKgYTmuo01E5A5y6c52q+qZBe9/DvgsuRQ/P1fVL5c61qd3/V+mLTXfVmMau3+De9y9/+bzpu3soV+7vvrPD5m29EV+FMVol53OrKN70LQdmPLDF3va7HRYrRlfLMsTKPJC50r5pqbsdHKf7rrXPW7KCUSaOGinBQNA7TA2LwUXwMTPf2LaOtbYIk8A/c/Y6dlO+v5/N23Z93phhLBwzL5/Z5zupwXruM6efto7f43r+65ltopF58JiC6iPMOUIfDWLLYS2L+PXxdz2UonOfFG5JBzvPe/vA/8TeDP1u4j8Hrlkm2er6piI+An0giAIZoPjecxbVX8tIiunvf0Z4FZVHcvvs7v2RQuCIKiOUr8265lKf1OcCrxPRB4XkV+JyDutHQu1Te741dMVni4IgqB8GllVsNIJywwwF7gIeCdwj4iclM8k8RYKtU2G7/hqaJsEQTBjHNcTlgZ9wH35xvoJEckCvcCempUsCIKgSuq1V52EShvvnwGXAY+KyKlAM1BS2yS1wo4smJhrR26kF9mpygC2Dtmz2l0dfrE6um1xnPE2O3UUwEiz7btr3I6e6euf4x7Xo7PV70mkxS7z/Gb/2ENZO+XYRLc985/p9KMkelN2ouxDXb6vx/wtT7l2Oz4GaGl1fduXO89jW+UNwqKzVlR0ToDxVl/IyWNgynnm/Kx8LN1rKz97adDG5/t1vGqOnb4wv0cJe2nqVe41CUlCBe8CLgV6RaQP+CpwB3BHPjXaOHB9sSGTIAiC2aSRJyyr0Tb5eI3LEgRBUFNizDsIgqAOiTHvIAiCOiR63kEQBHXIcd3zLqZtIiLnAt8FWslpm/yxqj5R6li/XvhHpm18yq7krs4x97hPr7cjIYZWnu/6nvs+O8JiF0td391DnaYtnbLnbw8O+g/UqoX29Xqp1wAe32CXqWuOH60wd44dOdDZah93fNK/noW9dhSFp6cC0JM5aNoGlp/h+naea2dymVh6suub6bGjhd7932xtGp3ytWeyp51n2rb3nuP6vnLAjsw5eMCfmBu2JUhYONePqurusiOA5xy0MweNZezPFkD/ZLdrrwWN3PNO8rX0feDKae99Hfiaqp4L/Fn+/yAIgmOKLKlEWz1SqbaJAoe7cd3A9toWKwiCoHq0ThvmJFR6ZV8AviEibwDfBG62dizUNnng3u9VeLogCILyUSTRVo9UOmH5GeCLqvoTEflD4HbgA8V2LNQ2eei58VjIEwTBjFGvDXMSKu15Xw/cl3/9Y+DC2hQnCIKgdkTP++1sBy4BHiWnceKnusnTnLajGVozthLF+JRfzJExOwJj8w5/Fr51xWrT9twmXwyktcW+6asW2dfTVKLW9w/ZYhOZEqt92xztk8U9rtoHWechHhi1C93V5h93cMLWuJjT5IRBAOKoLpRa+jyxeKVp2zvXz6SzYNLWY0kvO9F2bPb1PKaa7Owxg1N2BiWAbXvt691/0P5sgZ+TYGjE78NddLr9PG5baEdzbRuyI3YAxqaO/tL1em2Yk1Cptsl/BL4lIhlgFLjhaBYyCIKgErLauBOW1WibvKPGZQmCIKgpjdzzbtyvpSAIjntqOeYtIleKyHoR2SgiNxWxi4j8Vd7+vIicn9S3EqLxDoKgYVGVRFspRCQNfBu4ClgLfExE1k7b7SpgdX67AfhOGb5lE413EAQNSxZJtCXgQmCjqm5S1XHgbuDaaftcC/xAczwG9IjIkoS+ZZNkwnIF8ANgMZAFblPVb4nIPOBvgZXAFuAPVfWAd6yLtt9t2tSZpR/qXemWceBkO1Kxq83XRVnb9IppW3LmIte3y7ncdNbWuBjs9rUkfvO6nTlo6Tw/+0hzkx0hs26zP7s/MmJHLMyZY/vesPxR97ijbbYWSPu+ba7vk11XmbazdYfrO9xpa6q0TQy4vq/MfZ9pW91sJ9LuL5FVaOHmx0zb2vV+gu6eC//AtKXUjzbp3Ws/56kJ/zOyX043bdtH7IiSloyv87KwzdatyWFnyEpK0glLEbmBtwZe3JZfo3KYZUChkEsf8K5phym2z7KEvmWTJFRwEvjPqvqMiHQCT4vIw8AngEdU9db8GM5NwFeqLVAQBEGtSDqeXbiY0KDYgabHsVr7JPEtmyTRJjuAHfnXAyLyMrlvkmvJhRAC3Eku5jsa7yAIjhmSjGcnpA8oTEC6nLdrOln7NCfwLZuyxrzzAlXnAY8Di/IN++EGfqHh86a2ye0PPFpVYYMgCMqhhtEmTwKrRWSViDQDHwXun7bP/cD/lo86uQjoz7eNSXzLJvEKSxGZA/wE+IKqHpKEWZkLf46MPvTXoW0SBMGMUauet6pOishngQeBNHCHqr4oIjfm7d8FHgCuBjYCw8AnPd9qy5So8RaRJnIN949U9bCmyS4RWaKqO/IzqrurLUwQBEEt8VOXlIeqPkCugS5877sFrxX4k6S+1ZIk2kTIqQa+rKp/UWC6n5xA1a35v39X6liTm161C7LQjgxoT/lREvPnn23azpp8yvVtffKfTVv3Cb7+hWTtGf6RXlv/YjDjR5tMOU/c8Lh/yxZ12zojLSVEVYbHbA2L+Z32tabG7Yw1AK1OPaUH+13f7gVDpq2pf9D1bRmw+xPZJl+DpGWunUWpZYvdaVrQ40fATLy8zrTplB8xsnibE42ifjOV2uuUq0SqsOGldmCEiP1jujnlR5s0ia+JUwuO6+XxwHuAfw+8ICLP5t/7U3KN9j0i8mlgK3Dd0SliEARBZdRwwvKYI0m0yW8oHuoCcHltixMEQVA7GlnbJLLHB0HQsGQbOEQiGu8gCBqW6HkHQRDUIcf1mLejbfIN4PeBceA14JOq6osVeLPpU/bMtBfVAdDmZOFpObjXL9KQHc2Q6d/n+uqcLtM2mfajGSplaNSfPZ83z9apKBWa395iH7unzdZUyQ63uMdNj9g6IuPz7agOgEPj7abtYLetAQN+r2skNcf1fWWPrdmxcrkdhTTebuu4ALTNsZNOTQ3azyL4nwMtEZHlMuZnM/Lqcf+Qfe+Hm+zoJYCxFt9+qmtNxlQDN95J4mgOa5ucDlwE/ElezvBh4ExVPRt4FSeDfBAEwWxQK0nYY5GSjbeq7lDVZ/KvB4CXgWWq+pCqHu4uP0ZuvX4QBMExg2qyrR6pRtukkE8B/2D4vKltcsdvnqukjEEQBBUR2eN5u7ZJwfu3kBta+VExv0Jtk8Fvf7lOv+OCIKhHjvtQQUPbBBG5HrgGuDy/rj8IguCYIZutz151EirWNhGRK8npd1+iqr64xWEusLOT6IitUzG48GT3sDsGOk1b26L3uL4nZW1NiO1LzzdtANvHbD2WlNjHPTTgR2fs3mtHFezf70cGLLjYnsE/MOTf7s4257xORMnGuX5SkLEuu0wtaV/f4umX2kxb9qRVrm9ns11XoxN2xiGA7XvsD/22teeYtpGsH2V0+gm2vk+qRP/n+cVXm7ZSURVLl9raJi2T/sf3hb12dqB/+udDpm3+AjtSCGDRQj/i5z1VZ3kkaYqzuqQabZO/AlqAh/PysI+p6o1HpZRBEAQV0MjjAdVom8AxtJUAABaASURBVNRU3jAIgqDW1GsYYBJihWUQBA3LcT9hGQRBUI8c18MmQRAE9UojL4+XUhF+lrZJgf1LwDeABarqCom8ct0HzZMtOt/Wi5gcGnHL2H6iPRs+2W/ragC8/o/2wqETLjnT9W09/XTHaM+0j/WuMG0Au7ptVYfhrB19AbB6j50ZSDbYWVwAOMm+ntQeO9n16Kqz3MM2P/OoacuO2ZopAIOX/VvT1jpywPVt3W5Hdnj3B2Bg8RrTtvtPbSWIRef4ETCSsTVIDm7c5vou/cRHTdtUh5+dKTVp1/NUS4frq44ozt4e+3O7d6LXPW4pLjytu+qW98ePJRs4ue6iVN218kl63oe1TZ4RkU7gaRF5WFVfyjfsV5DLpBMEQXBM0cjDJhVrm+TNfwl8GWjgKgqCoF7JqiTa6pGKtU1E5MPANlV1BUsKtU3u2dRXcUGDIAjKpZGFqSrSNiE3lHIL8MFSfoXaJt6YdxAEQa2Zshc61z2Jet5FtE1OBlYBz4nIFnJysM+IiL1ePAiCYIZpZD3virRNVPUFYGHBPluAC0pFmxzcaifamb/GjihpW+5/J8ja80xb8+b1ru/gbjt7Sakol6Fn7RGjjnNt/YtSZMsbzXoLry14r2nrXHS26/ti/0rT1uVk6Dlr8in3uKmVdkRCqt+PGElP2VESe7v8yI7lOzaatmyrH2HRMmo/q3tf3W/a2ub6USwH37CPm530M0YtG+g3bZlR/1klY+vLpAb9BFg7T7Y1iQ5M2ZmDhkrox0xp5c95Uup1SCQJSWrvsLbJZSLybH6zFXKCIAiOEbKabKtHqtE2KdxnZa0KFARBUCsauecdKyyDIGhYovEOgiCoQxo52iQa7yAIGhYn10rdkyTaxNQ2EZHPAZ8lF/f9c1X9snesRWfYUSMdq2y9j9SyE9wy7u9dbdo6n3nM9U032XO2Y/12dh+ApjlOlpeeBaZtKuNn0hFnwep89ri+LwzYdbGk05+fHhixdTc6nHoaabUjDgDSPXZGGz8eAYZa7GNn1M/Co212RMlEW7frO9Fs+57+ETtqR9J2HQK0L7A1SLRUSzNpX692z3ddx7vs57HlgK1bA9A8Zd+/+Wk7wEyb7XOCn20qh/85ScLxPmxSVNsEWARcC5ytqmMistA9ShAEwQxzXDfeqroD2JF/PSAih7VN/iNwq6qO5W27j2ZBgyAIyqVewwCTULG2CXAq8D4ReVxEfiUi7zR83tQ2uWv969WWNwiCIDGqmmirRxI33oXaJqp6iFyvfS5wEfBfgHvyqzHfgqrepqoXqOoFH1tzYo2KHQRBUJqpqWRbtYjIPBF5WEQ25P8WnawRkStFZL2IbBSRm6bZPpe3vSgiXy91zkq1TQD6gPs0xxPkJjOrU18PgiCoITOoKngT8IiqrgYeyf//FkQkDXwbuApYC3xMRNbmbb/HkTnEM4BvljphRdomeX4GXAY8KiKnkgsccLVN5q6xo0ak2Yk7cDQdAFom7KiQprV+lpcTLrazl2Ta/Nnu1kX2d9WUo52xv2O5e9yByTmmbTjlZ9KZ22ZrXDTJpOt78vxDpq05bWuMzN32onvcse5Fpi2b8eNNJsXW5NhwyK/HA8vnuXaPFrGvd+VpjlbLnE7/wE7EyNQhu/5L+XrZbgCaBuyPZvaNza7voZWXmbYdw3aUy5a9/rPa0+F3ec93rcmYwTHva4FL86/vBB4FvjJtnwuBjaq6CUBE7s77vQR8hjLnEKvRNrkDOElE1gF3A9drvQ4eBUHQkCTteRfOzeW3G8o81aJ8cMfhII9i0XfLgDcK/u/jSGKbRHOIhVSrbfLxUv5BEASzhSbsehfmHbAQkV+SW+8ynVsSFqdYO3q4gIVziO8kN4d4ktchjhWWQRA0LLVcHq+qH7BsIrJLRJao6g4RWQIUG/boAwpXIy4HthfY7ss31k+IyOE5RHNV3tEX1A2CIJglsllNtNWA+4Hr86+vB/6uyD5PAqtFZJWINAMfzfvBkTlEks4hRuMdBEHDMoPRJrcCV4jIBuCK/P+IyFIReSBXFp0kJyfyILlE7veo6uHZ/rLnECvWNhGRc4HvAq3kltD/cT5k0ESdTCFTA46OSIlZ+OZVtn1gyWmu79wr7d9VE92+NoNk7eu5bYedr2L/S74mx3O/fc20nbhmqev7tQ+uM227m/04+84m+x6ksa/12UUfco87OmlHjLw07Eck9D9lnzeT8SMsmk+1o3Ze2OxHEi1baH9uVp5yhmnT1191j/vi/7rftC06w7+3LZ+92bRtSdmaNgCb9neZthPfNeD6rtts++7YZUcwtbT4YxY/u8fOdATwry9c49qTMFMhFKq6D7i8yPvbgasL/n8AeKDIfuOUOYdYjbbJ14Gvqeo/5KNPvs6RUJkgCIJZJ9vAAXDVaJsocPgruZsjA+9BEATHBHo8S8IWMk3b5AvAgyLyTXJj5xfXunBBEATVMDXVuD3varRNPgN8UVVXAF8ktwqzmN+bwe/ff/KlWpQ5CIIgEce9MJWhbXI9cPj1j8kt/XwbhcJUn3jn2mrLGwRBkJjjOnu8o22yHbiE3Br+y4ANpY41ut/WKGk71daLmNjuD6ePtdpZUTo3P+P6Tmy0i910YgkVxCZbl+P0E+xZ+IllfraVdMqui7k9/i0ba7IjLCaydtQHQMbTPnECO5Zn+tzjTjq6NYMLV7q+usA+8WSJ8cy5LUOmbdF8P9qko9mOcknttaObxnfuco87enDMtvXbujQAvbvtZ3XxMltLBwBH5qW3yQ0npr+31bT1zKl8nd/wu0+q2DcpSVdY1iNJav6wtskLIvJs/r0/JZeM4VsikgFGgXK1AIIgCI4qdToikohqtU3eUdviBEEQ1I4arZ48JgltkyAIGpZsA0ebROMdBEHDclwv0gmCIKhX6jUMMAlJok1agV8DLfn971XVr4rIPOBvgZXAFuAPVfWAd6zus22dkanlJ5u2pg4/O0l/s23PrrrA9bVVG0Db/Bn8/qVn2sfN2lEFB0bt2XuAeXPt2zKv29fz2Je2s9bsG/HrMeuElHiRG1NpP3omhR0W0pLxQ0YWtNuRHcMTfj0uzW41bTvbvDsPZ3RtMm3ZZ7eYtolDjkYPMO+koqkNAeheWUy//wgHF59u2vom/axCB0fsumrt9J+LprR9j3ranMxA6j+rLS3+c1MLGnnMO0mc9xhwmaqeA5wLXCkiF5EgZ1sQBMFsMoOqgjNOkmgTBQ53J5rym5IsZ1sQBMGsMVXLbAzHGElXWKbzMd67gYdV9XGS5WwLgiCYNTSribZ6JFHjrapTqnouubQ9F4qIPdg7jUJtkzsefarScgZBEJTNcd94H0ZVD5IbHrkS2JXP1YaTs+0t2iafutSfPAyCIKglx7u2yQJgQlUPikgb8AHgzzmSs+1W7JxtbyG1fKVpm0jbuhupdn82fNPEKtN2OnZmGYDsTls3Zeqsd/m+Ys+Wi9hPREva1s0AyGTs25JO+U/agTFb22TvkK/nsbRr2LRNqX2tXVP73eO2j9j2TKefVahtwo7eSKX8eux+5hem7d1n+NmZWn/7z6Zt92PPmbbmznb3uB0L7Ge5dX6P69uftjViWtSvx5Ym+/PVJQdd31RbZePGgv+sTpziZ6qqBfXaq05CkjjvJcCdIpIm11O/R1X/XkR+Sy49/aeBrcB1R7GcQRAEZXNcx3mr6vPkEjBMf79ozrYgCIJjhUaONokVlkEQNCzH+7BJEARBXRKNdxAEQR1yXAtTOdom3wB+HxgHXgM+mQ8lNJnssGfTNWPPpPet8HMbp8fsG3THS+90fS+66CzTtu1Am+t7xeQTpq3vkK2Lkikh6TDqXM9oi68XMTppRxX0dth6KwA//63te+rJdhTLvh4/wuLgsH3cte17XN/1QytM24Zt/uM7nDnbtJ3mVwUvNb3XtF33lW2mbVD9bEUnb7IjYCbm2ro0AIfE1kUZHPd1Xjxtmqf22ZmbACan7Gduw+t2xM/WzXbmLIDuueOu/fffUX3fspF73tVomzwMnKmqZwOvAjcfvWIGQRCUTyMnIK5Y20RVHyrY7THgD2pfvCAIgsqZKpXotI6pRtukkE8B/1DrwgVBEFRDI/e8q9Y2EZFbgEngR8V836Jt8rMHa1HmIAiCRGg2m2irR8qaEcgvkX+UnLbJOhG5HrgGuFyNry9VvQ24DWDwsfvr8ysuCIK6pJGTMVSsbSIiV5LT775EVW1RjAK2LzjXtI2rHW2yfXCee9yXXrdn+LeUmPGeP9eOgNna58+GzzvnbQtP38Sboe9yso8ATE3ZtyWT9qNN1m2x62JgwPcdGBgxba/32T/SXu8TVq2wzztkH5bBuX5Ez0tb7NAcRwIGgIkJ+4O7eYcf8pPJ2L7rDy41bWOT/o/ZeSfYz8xgkx1NAvDE1iX2ef1HleUL7M9XqVGDeR3289rTZd/3yeV+tqJ0iWe5FtTrkEgSqtE22UgufPBhEQF4TFVvPHpFDY5VvIY7CGaTbANPWFajbeIHhwZBEMwyWT2OG+8gCIJ6pZEX6UTjHQRBw9LIjXdZmXSCIAjqiZmK8xaReSLysIhsyP8tOvssIneIyG4RWTft/W+IyCsi8ryI/FRE/MwczHDPuzVr6yt0qB0Vsh0/2mTciSpYucqf8V7YbWszTE3ZM/QAXS0Dpi3jZLyZ0zzqHndeT7dpW9zjhxXs2GPf0oEBP8pl/y77eryJn9074dorbH2TQ612mUplW5GUHZGwfFGJTC3z7YgSLxoIYLeTHGh5ly3hc2jc13lpGbfruGnSCcsBeruWmTbveQNY1GFnDhot8Zy3pu1nbuec+aYtlfInsjv8QKOakJ25GO6bgEdU9VYRuSn//1eK7Pd94H8CP5j2/sPAzao6KSJ/Tk5upJj/m5TseYtIq4g8ISLPiciLIvK1afYviYiKSG+pYwWNiddwB8Fskp2aSrTVgGuBO/Ov7wQ+UmwnVf018Laugao+pKqT+X8fI7cg0qUaYSpEZAVwBbk0aEEQBMcUSbPHF64Ez283lHmqRaq6AyD/d2EVxU4kN1KxMFX+/78EvkyC5MNBEAQzTdIJy8KV4BYi8ktgcRHTLeWXzDyHKzdSSMXCVCLyYWCbqtqptHmrtsnf3H1PktMFQRDUhKxmE21JUNUPqOqZRba/A3aJyBKA/N/d5Za1QG7k31lyI4UkmrBU1Sng3PwM6E9F5Gxy3zYfTOD75jfa1g0vN27cThAExxwzGCp4P3A9cGv+b1mjEZXIjVQqTHUtsAp4Lr80fjnwjIhcqKo7Lf/e3S+Zx5YJe0Z7zXJ/Nnxohb3YM5P2b96ZPVtMW2+Hn9lkWdN207Yvbc/fTqmvq+HNn/SP+LdsyQL7x9TkZIvrm8nYkQPd3XbkwNPr4bp32NMew+12VqHOlB0FATC/x44WOrHH160ZmvCv1+ONHfYz1+t0qua02tcK0L7pNds45NfFiWecbNpS4vcelw++Ytqyaf+Z6sucatrmzpk0bV3tfkRPa1OpiUL/c5+EGVQMvBW4R0Q+TW4O8DoAEVkKfE9Vr87/fxdwKdArIn3AV1X1dnIRKGXJjVQsTKWqCwv22QJcoKp7y7veoBHwGu4gmE1qFElSElXdB1xe5P3twNUF/3/M8C9bbqRiYapyTxQEQTDTHNeSsJYw1bR9VtaqQEEQBLWiXhMtJCG0TYIgaFgaWdskGu8gCBoWDUnYIAiC+iM7OTMTlrNCUtWto7EBN8y072ycM3zj3oZv9b6xvXWbbUnYcvUDauE7G+cM35nxrbfyhm9QMbPdeAdBEAQVEI13EARBHTLbjber4nWUfGfjnOE7M771Vt7wDSpG8pMIQRAEQR0x2z3vIAiCoAKi8Q6CIKhDZqXxFpErRWS9iGzMJ+tM6rdCRP5JRF7O59P8fAXnTovI70SkLHEtEekRkXvzGZ5fFpF3l+H7xXx514nIXSLS6uz7tuzS1WSmTpqV2spqnbeZeUqdbNify9/jF0Xk62WU91wReUxEns0n8bjQ8C36LCSpK8e3ZF2VegatuvL8StWVU96SdSVGDtqE9WT5JqmnyH17tJnpwHIgDbwGnEROsPc5YG1C3yXA+fnXncCrSX0LjvGfgL8B/r5MvzuB/5B/3Qz0JPRbBmwG2vL/3wN8wtn//cD5wLqC974O3JR/fRM5Sd6kvh8EMvnXf16Ob/79FcCDwOtAb8Jz/h7wS6Al///CMsr7EHBV/vXVwKPlPAtJ6srxLVlX3jPo1ZVzzpJ15fiWrCtAgDn5103A48BFCevJ8k1ST0V9kzxTsSXbZqPnfSGwUVU3qeo4cDe55A4lUdUdqvpM/vUA8DK5xjERIrIc+BDwvXIKLCJd5Bqa2/PnHlfVg2UcIgO0iUgGaAfMLA5aPLt0xZmpNWFWauO8cCRPadGZbcPvM8CtqjqW36do9gLDV4HDGRi6MerKeRZK1pXlm6SuSjyDZl05fiXryvEtWVeao1gO2iT1VNQ3YT1Z54USz1SQjNlovJcBbxT830cZDfBhRGQlOanax8tw+x/kHppy1WpOAvYAf50fcvmeiPgpU/Ko6jbgm+Sya+wA+lX1oTLPX6vM1ImyUh9GEuYpLcKpwPtE5HER+ZWIvLMM3y8A3xCRN8jV280JyrmSI89CWXXlPEcl66rQt5y6mnbOsupqmm+iupIiOWhJWE+GbyFmPRXzreKZCqYxG413sdxIZX0Di8gc4CfAF1TVzx11xOcaYLeqPl3OufJkyP28/46qngcMkfupmeS8czmSNm4p0CEiH6+gDFUhZWSlzu/fTi5P6Z9VcLoMMJfcT+z/Qi49lJ8T6wifAb6oqiuAL5L/teOUs+xnoZRvkroq9M3vm6iuipwzcV0V8U1UV6o6parnkushXygiZ5YqZxLfUvVUxPdw7ttKnqlgGrPRePeRG/M6zHKcYYTpiEgTuQf4R6p6XxnnfQ/wYcmlbLsbuExEfpjQtw/oK+h13EuuMU/CB4DNqrpHVSeA+4CLkxcbqDIztZSZlTrPyRzJU7qFI3lKFyfw7QPuy/90foLcL52kE1PXk6sjgB+TG2YrivEsJKor6zlKUldFfBPVlXHORHVl+CauK8jloAUeBa6kzGdqmm9Zz1SBb2Hu2y2U90wF05iNxvtJYLWIrBKRZuCj5DIvlyTfI7kdeFlV/6Kck6rqzaq6XHNZfz4K/KOqJuoBay6p8hsisib/1uWAnU35rWwFLhKR9nz5Lyc3ZlkOhzNTQ5mZqeVIVuoPa8Ks1ACq+oKqLlTVlfk66yM3aWYmmC7gZ8Bl+fOfSm6CN2l+0+3AJfnXlwEbiu3kPAsl68ryTVJXxXyT1JVT3pJ15fiWrCsRWXA4GkSO5KB9JWE9FfVNWE/FfH9XxTMVTEdnYZaU3Mz4q+SiTm4pw++95IZYngeezW9XV3D+Syk/2uRc4Kn8uX8GzC3D92vkPjDrgP+HfGSBse9d5MbGJ8g93J8G5gOPkPtwPgLMK8N3I7k5hsP19d2kvtPsWygebVLsnM3AD/PX+wxwWRnlfS/wNLkopMeBd5TzLCSpK8e3ZF0leQaL1ZVzzpJ15fiWrCvgbOB3ed91wJ/l309ST5Zvknoq6pvkmYot2RbL44MgCOqQWGEZBEFQh0TjHQRBUIdE4x0EQVCHROMdBEFQh0TjHQRBUIdE4x0EQVCHROMdBEFQh/z/KIQ/NuClmJ8AAAAASUVORK5CYII=\n", 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\n", 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\n", 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\n", 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\n", 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zEEwrKUm21ShJvl6+C2we995XgXtV9UTgXiZIFhsEQTDdiKQSbbVK2ZKp6n3A+PGHy4Ebiq9vAH6vyuUKgiConDnQg56IJaq6G6D410xhXarF8ZtfRJh0EATHEUkl22qUYz5JWKrFcc3/1tDiCILg+DFHozj2iMhSVd0tIksBW2yhhKeetHUIjhy0Z+Trm/zsF/MW2Fk5VlzoR2KsOGe9aWtY3un69o/aM/aZZrvMXpQGgC5ebtoGm80fKwB0rZpn2tZ2+rPmaUc7YdFJdrTLwf/3/2HZ5z5t2sWJmEiNlMm6Mc8+b67B1oEAGMra9pT6uSX2D9rXKNVkR1PsGvWvT2urfU+l8SN01jv9m7G8/yif3P6qaesY2On69jXYUSttKTtSo3HE1/hIaZmURdWghnvHSZhq6W8Hrii+vgL4h+oUJ5iJeI1zEEwrM3wMumwPWkRuAs4DFopIN4Wl3VcDt4jIpyiIJv3+sSxkEATBlJjhPeiyDbSqftQw2VqbQRAEtUBocQRBENQoocURBEFQo5RZPl/riB7HyLfbH86ZJ9vU/rLp197b7R63Ycdzpu3u5f/R9c04WV5WtdoaEgArjjxj2h6te49p6xvxM5sc6rO/N09a7OsmnPrQ/2faRvb4nyd79rtN2z1NdjYPgD2H7QdhfqsdndDW4GtIZFP2TP+axh2ur3ff5LJ+FEfz1sdM20unfMi0dfd2uMd95hW7nlbbwTsAfCB7r2nL9viBVHkn4mVg3jLX97FRO9vR8mY7MkvxhxeOjPpROOee3Frx+MTQL76dqIFr2PzpmhwLmaoWxzdE5HkReVJEfiIi7ce2mEEt4zXOQTCtiCTbapSpanHcDWxU1U3Ai8DXqlyuIAiCyqniSkIR2SwiL4jIFhF5i/6QiGwQkftFZFhEvlyN4k9Ji0NV71LVo79NHwBWVKMwQRAEVaVKPWgRSQPfAi4GTgE+KiKnjNvtIPCfgG9Wq/jVmOL8JPBzy1iqxXHnbX9XhdMFQRAkQ9PpRFsCzga2qOpWVR0BbqYgGvfGuVT3qupDQNXSlVcUxSEiV1FIGHujtU+pFoc3SRgEQVB1kg9fXAlcWfLWdcW26yjLgdJZ6W7Azo5RJabcQIvIFcClwIWaMBQk50gNbBlYZdpWtvkz7gtX21ERZzQ87/qOpG3NjHmDe1zfupefNG0rz1xr2vZnFrrHbW+wL8uSzGuur648wbRlV9tZQgD6O1aatoUpOxPIwmboPmzPyDdl7UiM9vpBt0xpJ4qjLufreGRGbK2UVN7v5Ayu2mjaVO2fxM11vt7Jwg67nha3+NlYUr12Xcmg75sesHUxGspEtNQ32pE2ObV7n81pP+ONZMs1G75mTSISNtClHUnrSBO5TaVIk2FKDbSIbAb+FHifqtpPbjAn8BrnIJhOtHoRGt1AV8n/K4Bd1Tq4RZIwu5uA+4GTRKS7qL/x/1P4ertbRB4XkWuPcTmDIAgmT/WiOB4CThSRNSJSB3yEgmjcMWWqWhzfOQZlCYIgqC5V6kGr6piIfB64E0gD16vqMyLymaL9WhHpBB4G2oC8iHwROEVV/ey5DrHUOwiCWUvCCI1kx1K9A7hj3HvXlrx+jSqHHEcDHQTB7GW2y41Wk+Vt9qxuc8aea5w/7EcuNO2xdTwGVp3l+g6pHcWRqZ/v+tat2mDaFh2wo0ca23zRhd56W8+hZdDWPgBI9R5yjH5voiljR8PULzjRtK1bcJi6lB0V0cZh+5wjvraIjNlRHPVDvm+mZ79pyzfaWXgA8i12XXQN2Nov7U1+RpXsEvvaL6iz6wlAB5zHVf1sLDiBVpk+554BGlvsaztPbN95R3a7xx2ta3LtsLSMvTw6wxvoKWlxlNi+LCIqIn7cWDCr8RrnIJhW5qgWByLSBbyfQkaVIAiCmkMllWirVaakxVHkr4CvcByCtYMgCKZEKp1sq1Gm9NUhIpcBO1X1iQT7vq7F8ZNbvjuV0wVBEEwJFUm01SqTniQUkSbgKuADSfYvXUL52+d7orcdBMHxo4aHL5IwlSiOdcAa4AkpfPOsAB4VkbOLcYAmJ4zY2hUHs3b44IF6P+PDwJp5pq2t348ASTXYs9+tvVNfyZnpt2fk2/sP07fY1sxYueVn9oHL/Bx7ecPvmbbhfJ3rm1f7Zm4to6vQPmJn9PCiLdI5X7siPWhrSOxbusn1Tc2ztUVa+/0MJK8021ocUmZUb+XQC6ZtXdrWzKg74q9n0LQdWTK81L6fwM8g03DE15zZuPdO09azeL1pG2xop8V5hva32vo7AItcazLKZXWpdSbdQKvqU8DrsUQisg04S1XtmKbgTXiN80zEa5znGl7jPNfwGufjRS1PACZhqlocQRAEtU8VM6pMB1PV4ii1r65aaYIgCKpIvoYjNJIQS72DIJi91HCERhKigQ6CYNYy08ego4EOgmDWMuujOETkegqprfaq6saS978AfJ5CTsKfqepXyh3r6fSZpq0TWwSofXSfe9zRdL1p+/ttv+P6rllqh9md1OFLjCwa3mHart9+sWlbVe/fNE2dtsDT2S12qCJAx5gdMlUuPKy/zg5X/NU2O4XXb+63BacABnrt1FSt7b5gzrIVdtqjVLdfj/V1du+po318QuY3c0q9Hd73yFZbaCmX8++Zea12mZfO90MO3z12j2nrb/VDUV/K2WJXW0f9jDgfTt1i2poG7OCtJ5v9Z+/eB/xUW19f55oTMRd60N+lkEHle0ffEJHzKWS03aSqwyLiS3gFQRBMB7N9DFpV7xOR1ePe/ixwtaoOF/eJQNggCGqOvMzsKI6p9v/XA+8VkQdF5Fci8g5rx1Itjtt/dP0UTxcEQTB5Zrqa3VQnCTPAfOAc4B3ALSKyVvWtquClWhz3PdMfWhxBEBw3Zv0koUE3cFuxQf6tiOSBhYA/mxcEQXAcqeXecRKm2kD/FLgA+KWIrAfqgLJaHN2H7Bn7pkX2DPaKfQ9OvoRFhoZOcu39w/YFzIqfKaT1VVttddM6O2Ilk/LTEy1ssiMIcupfsgVbnbo64qdU2nHap03bwcN2md/3Xj9yYcs2ux67ltsCQACL59kpr37+z3Y9ASxeYkcnpNN+z+rlfXb0yA+v/ZXr69F18hrTtmGTn+Jp44PfNW318/xIjLNOtM+78YzzXd/ULlvEaeey95i2hrwflTI05F/7akQB17KUaBKShNndBJwHLBSRbuDPgOuB64tpsEaAKyYa3giCIJhOZvokYSVaHB+rclmCIAiqylwdgw6CIKh55uoYdBAEQc0TPeggCIIaZdb3oCfS4hCR04FrgQYKWhx/pKq/LXesoRH726wtY8/Ij7QscI+bHbSjEzoX+ZMEY3aQAK/2d7q+C5fbESKdTXaap8ND/oz7aM6e3e7P2noZAAtyY6YtPzjg+i5K2wtCVy1rM21jOX9+uKHBfkga6nzfbNqOHvlXH/B1PIZG7fMO+AEGpJ1Imw/9oa0xcfCQH/mzb699DVJlIksWnv9u06b9fkSLLLDVGHqa/eiR9OJh+7xOD7UxZWuwALznDDtSplrM9B50kq+X7wKbx733F8Cfq+rpwNeL/wdBENQUeVKJtlplqlocChztUs0Dpj/5WBAEwTi0hhvfJEy19F8EviEiO4BvAl+zdizV4vjVP143xdMFQRBMHkUSbbXKVCcJPwt8SVVvFZEPA98BLppox1Itjuv/qYwgcRAEQRWp5cY3CVPtQV8B3FZ8/SPg7OoUJwiCoHrM1R70LuB9wC8paHK8lMTJm7Ff2P+qaas/tNM9ruTsUIxnt/iRCx49K/xMIWve1mXajgzaEQYHBuwMMAA7R+xMEw11/sz3SsemI37owu5RO2pl/2H7u/xfr3rEPe5DjaeZthR21An4uiX1Gd/XyyDTU+YavObIltTX2Q90Q4MfNVTfMPXIVh2y7+WRPb5O2djL20xb5wFfzn3Puz5s2npG7ewyq9L2OQHaG8tFcZTT6ihPLTe+SZiqFscfAteISAYYAq48loUMgiCYCnmd2ZOElWhxvL3KZQmCIKgqM70HPbO/XoIgCByqOQYtIptF5AUR2SIiX53ALiLy10X7kyJiaw4nJBroIAhmLaqSaCuHiKSBbwEXA6cAHxWR8anhLwZOLG5XAn9bafmjgQ6CYNaSRxJtCTgb2KKqW1V1BLgZuHzcPpcD39MCDwDtIuKvoy9DkknCLuB7QCeQB65T1WtEpAP4IbAa2AZ8WFUPecc6t9MO9mh69knT9uw1N7llzDbas70H33GJ67toqT2TvHVrn+t7ZIOtT7G6fodp6yozk//wXjv7RUu9H7nw7F/+wLQt2bjc9T3pHPsa/NPhd5m21tZt7nHPbbWjD+r7/OiDXL2tW7KzZaPru3KPnV3m4NINru/Qcvu8fXnb9sh2P7vMrp12xFF9nd9f6n30BdN2aMtu13ek347gWTLq31M3ZteZtg+cYWuAHE75dbEkUy5DXuVaHVWcJFwOlD7U3cA7E+yzHPAvjkOS0o8Bf6KqJ1NIEvu5Ytf+q8C9qnoicG/x/yAIgpoh6Rh06Yrn4jY+Mm2ibvb4OM4k+0yKJFEcuyl+A6hqr4g8R+Fb4XIK4XcAN1CIif7TSgoTBEFQTZKMLxf2e2PFs0E3ULrwYQVv1SBKss+kmFT/vyiadAbwILCk2HgfbcQn1DMs/Wb6Xzf/sJKyBkEQTIoqRnE8BJwoImtEpA74CHD7uH1uB/5DMZrjHKDnaBs5VRIvaxKRFuBW4IuqekQSZsst/WbatuXF0OIIguC4kbQHXf44OiYinwfuBNLA9ar6jIh8pmi/FrgDuATYAgwAn6j0vIkaaBHJUmicb1TVoxoce0RkqaruLs5U+utFgyAIjjO2UMDkUdU7KDTCpe9dW/Jagc9V8ZSJojiEglrdc6r6lyWm2ymIJl1d/PsP5Y7Vi50NpH3l20xbueiDsUE748N559mZJACyGbtTP5bzv33bU3tM25JH/rft2OBrfJy/7izbWOaXS9+qDtPW0uVniBlJ2dEwb99gRx+kXt7uHrep/4hpG33hWdc302bP5Pe+8xzX9/DCE03ba/llrm/PoH2N/uVxe2Swp8eP/BkatDOu9PX50RS9O+yoh1TG1wCpa66zfdO+72Vn7TdtC3L2MzBv31b3uANt5SLQ1paxl2fWL/UG3g18HHhKRB4vvvdfKTTMt4jIp4DtwO8fmyIGQRBMjWoNcUwXSaI4fs3E4SMAF1a3OEEQBNVjpmtxRFbvIAhmLfkZHpYQDXQQBLOW6EEHQRDUKLN+DNrR4vgG8LvACPAy8AlVdfJQQLsesM+Tt2ew29aucMs4fMA+bUOdH2jTkLV/A42UieLoU0croMnWa6BMZpOU2hET6VHfd+FpduRC9sSTXN++rJ0FZlHWjk7ILbO1QwDEKbOk/DrODw6atpG8f/sOO59ndMSPXBCx74t02i7zhvV2hhGAoWH7vliywHVlyeAmu0wtU9et0DX+fZFygtXGnMiffNbODATQ0+BHWC1yrcnIzfAGuhItjruBjaq6CXgRJ7N3EATBdFAtudHpomwDraq7VfXR4ute4DlguarepapHu70PUFh3HgRBUDOoJttqlUq0OEr5JPBzw+d1LY4bb75lKmUMgiCYEnMmq/d4LY6S96+iMAxy40R+pVocO156toa/q4IgmG3MiTA7Q4sDEbkCuBS4sLgOPQiCoGbI52u3d5yEKWtxiMhmCvrP71NVO2VGCQ0jdvaFuh57Tf9Yyh+JaVhmzwb39Pu+L+yzo0cWzvdn+puytu7FCS3tpm2wwx+uz4zY1TlWZ0cmADQstusi75QJYJd2mbaeYVubIjVsR1oAjDXbGizZrlWuL3X1pulfnvajBNassLUctu7wo3sOH7IjT3J5W/vFi/AAqK+z7dkyT2NmgZOhpNG/L3IdS0zbYBlNjM6hV0zb7ga7jluzvn7aqwP+eU9wrclImM6qZqlEi+OvgXrg7qL06AOq+pljUsogCIIpMNN/11eixXHHBO8FQRDUDLUcQpeEWEkYBMGsZU5MEgZBEMxEZv0QRxAEwUxlpi/1nrIWR4n9y8A3gEWqaqdeAESdmXOxoy0GLvqIW8bDdXbkwrllcja+2mHPjG99zUdtMN4AABXCSURBVP/6vf1uW5/i5A+9w7TtGPJnr4+M2ZELTzzt33Cb377BtI3m/aiUjkyPaRvL29cnX+9niJGcHSnTe4JdTwAjGfvYn7n1C65v3aH5dpnq7QwjAKmV9jUaefF522/N+e5x9y+wdS+Gxa/Hb+3+z6bt1C47UwtAV4udjSWDn8nlnpfsSJtVi+3zdjTb9Q9w7iN/5do5tXL1iLnQgz6qxfGoiLQCj4jI3ar6bLHxfj+FjCpBEAQ1xUxvoKesxVE0/xXwFWCGV0MQBLORvEqirVaZshaHiFwG7FTVJ8r4vK7F8b0f/XTKBQ2CIJgsM10saUpaHBSGPa4CPlDOr1SLY//T99dwVQRBMNvI+QtGa55EPegJtDjWAWuAJ0RkGwWp0UdFpPNYFTQIgmCyzHQ96ClpcajqU8Dikn22AWeVi+JoOvCqbdy1zTQ1ttqaFwB5saMTfrH7dNfX+3mz+zVbcwHg4F476mFQbW2EpoyfFWV4zL4suZwfidGS7jdtu4YdLQdgd862v7jb/jwb2+ysGgDpYVtbpH7IrkOAdNauq8ZTT3V9ydmZaRjy5WNGX3rBtGXabW0RzfnRFC1DdlahbJ2fjWVg0I4sGSuT/cdrhHLO8wP+Yo8jQ/a9ur/V76+1rj/DtVeDWh6+SEKSHvRRLY4LROTx4nbJMS5XEARBxeQ12VarVKLFUbrP6moVKAiCoFrM9B50rCQMgmDWEg10EARBjTLToziigQ6CYNaSn+0NtKfFISJfAD5PIS76Z6r6Fe9YPUtsnYh5GTsSYKyu2S1jw7AdCdDc4F+hpnrb3r/E12s4fNDOUDKstr5BW8bOLANwEPvzLuv0L1nH0C7Tlmv0Z+tz2PZF82x9kKHmRe5xW/pfMm2SdyItgLG0kzVlxI+Gyffa90WqpdX3HbWvX2rUjtSQMV/XQlN2HTc69zGAJ2UzMOpf2zG175tyWhyebMnpS3aatpW77nePezyYC0McE2pxAEuAy4FNqjosIrZiURAEwTQw6xtoVd0N7C6+7hWRo1ocfwhcrarDRZufgCwIguA4U8shdEmYshYHsB54r4g8KCK/EpEJdSNLtTh+cMutlZY3CIIgMaqaaKtVpqTFoapHRCQDzAfOAd4B3CIia3Xcpy3V4tj9/OO1WxNBEMw6vMWkM4GpanEAdAO3aYHfUphA9NcSB0EQHEdmvZrdRFocRX4KXAD8UkTWA3WAq8UxmLVnznOL7EwT/Wlb+wCgJXfYtHVmBl3fzgZbG2F5q60/AdDYYH8fdYit5dBUZrZeWuw7pq3ejhwBGErbdSzi34kpJ0xgRdsR01bfX+bz9NrXJ3vIvWVIL7B9B9f5OivucXN+BEi9E5+1+8zLTVtdzr/f6kfsLDy5tB81tGKp97j60Upjakd5NKVs/RaAk5faZT4yat9v6kRmAQw3L3Dt/tOXjOM1Bi0iHcAPgdXANuDDqnpogv2uBy4F9qrqxnLHrUSL43pgrYg8DdwMXDF+eCMIgmA6OY496K8C96rqicC9xf8n4rvA5qQHrVSL42NJTxQEQXC80cRd6IolRy8Hziu+vgH4JfCnbymP6n3FYItExErCIAhmLUmXeovIlcCVJW9dVwxwSMqSYkgyqrq7WutCooEOgmDWkk/Ygy6NNrMQkXsorKgez1WTL1kyooEOgmDWUs1ZMVW9yLKJyB4RWVrsPS8FqrJwb8paHCJyOnAt0EBhOfgfFcPtTDp3PmLaxprtSI2mOnsmH/yMKhtSz7m+LTu3mjYpkx1jRecJpi3TP2TaRrO+tkhTzo6YWDT4suu7q9XWO6kXu0wALSNvmXR+ndG0rcWxpeVM97j1p9iT1cN5P3KhPW1f+8M5P6KlU22diKbBg67vyFq7zCm1g2vrxvwojqZD3aYt/5T9fACcftE601af8qNSUmL/1m/M2VEaAGtTdpROf9Z+brsXv9097sERPzrrXa41GccxbOF24Arg6uLff6jGQZNEcRzV4jiZwqKUz4nIKcBfAH+uqqcDXy/+HwRBUDPkVRNtVeBq4P0i8hLw/uL/iMgyEbnj6E4ichNwP3CSiHSLyKe8g1aixaFAW3G3eYAtoxYEQTANeAqAVT2P6gHgwgne3wVcUvL/Rydz3EmNQY/T4vgicKeIfJNCT/zcyRwrCILgWJPLzeylGYnFksZrcQCfBb6kql3AlyisNpzI73WxpOtvv6caZQ6CIEjEnBBLMrQ4rgD+uPj6R8C3J/ItDV8ZuO+W2q2JIAhmHTNdbrQSLY5dwPsorJi5ALDTZhQZabW1K4Ya55u2F3K2TgfAwX47wqAcqzrXmLau0S2u746sHcXxsyftGepVy6Ye3Xjuildc+31blpm2tZ3+TP+aFjsa5tCoHTHxzb+zoz8AGprs69PX4/uuWj9R2GmBbMbPIrJwkR2JcUKX68qqdjt6pA47uqclb2u7AOBkkMks6HBdf7PFtm/f7kfovPLCa461xfW94UOPmrZM+wrTdufBs93jPv60H/HyrpNdcyKSrySsTZK0FEe1OJ4SkceL7/1XCoL91xRlR4d48yqcIAiCaaeGRy8SUakWhx/oGARBMI0kXUlYq8RKwiAIZi35GR7FEQ10EASzliotQpk2ooEOgmDWUsshdElIEsXRANwH1Bf3/7Gq/lnSDAKljNbZGhRjKTv7gpT5mdIzYM/mD/qT29Rn2mxb20rXd2+fnU1ibNQucybtf56RMVubdv7gbte3p3eVaTvQ4me48LK17B+wr52Ir5Uy2GdfhKE+fyZ/oM+OPFm91tdyyGTsesyVGZsczfsRIhaHm+yok3JkW+xIJoDtD9n1uPNVX1vk0Gt2dEljm68NI8MDpq35wKumrb5uwjzSr9PRMfXoq6TM9DHoJAtVhoELVPU04HRgs4icQ/IMAkEQBNPCrM9JWExjdVTuKlvclIQZBIIgCKaLXFLF/holaVbvdDEGei9wt6o+yLgMAkBVMggEQRBUC81roq1WSdRAq2quKCu6AjhbRMpmoz1KqRbH937006mWMwiCYNLM9AZ6UlEcqnpYRH5JISttogwCpVoc+555sHZrIgiCWUcNt72JSBLFsQgYLTbOjcBFwH9jChkEPO2KJY6c9IoGT0cAWGTPnP/1dXtc1/deZGtxDI/5ozbiJALeu6fXtK3u8jOB9A3Yd9WeFatd37NOsqMeUvh3a33a1ph47AXbr7GlwT1u3hkHLOc7f0GTaevp8TPedC6xowRGnUgZgLZMv2kbytvHPZKzo4IAhhoaTZs0+Nfn4nfbtuFzFrm+jzxvPyO9vX499nbadTGWtjPijO7z63jXTvsZKeBH6SShlnvHSUjSg14K3CAiaQpDIreo6j+KyP3ALcWMANuB3z+G5QyCIJg0sz4OWlWfpCDSP/79CTMIBEEQ1AozPYojVhIGQTBrmQtDHEEQBDOSaKCDIAhqlJkuliTlBtEdLY5vAL8LjAAvA59QVVeU4acP2aIaefVnfD06W+1Z5tP3/8L1lW12eIKu9jO5aMbWttCUreWQ7ve1Kw6uON205cXXiBhO2VECWibsvfPQc6Ytu7/btA0s8+up4dBO05Y6vN/1HV1uR/5kD9jHLYfW+dEjuUZbZyWzd4ftt2i5e9x81j5veuCI63t4yQbT1jDc4/o2bX/atOkhPwvMb07/smnblH7StImTPQYgO2I/twDzzrxo6o1CkSu+/lqiFvqG/7uz4nMdCyrR4rgb2Kiqm4AXga8du2IGQRBMnlmfNNbS4lDVu0p2ewD4UPWLFwRBMHVyYzM7iqMSLY5SPgn8vNqFC4IgqISZ3oOuWItDRK4CxoAbJ/It1eK46yd/V40yB0EQJELz+URbrVKJFsfTInIFcClwoRpfQ6VaHN4kYRAEQbWZ6YL9U9biEJHNFPSf36eqdsqFElob7DX/SxvtjBCDeX/GvW/Utv9T879yfRe/w55J7hn2z9veYGcDOTJi+7bP96vrxX12Zo3WRn9mfN08W3tEy0TKHGy3dUn2t53t+i5I2dEYfY0Lbcdl7mHZp0tM2yLnswKk1K6robSfRSTnPBqr9mw3bX3tXe5xe+pszYzmNj8Soy9ta7iMpMvooay2P0/Dwn2u78F+W2+jd9EC07ZnxNcHWTDPj2aqXIljDiz1xtbi2EIh9O5uKagGPaCqnzl2RQ1qFa9xDoLpJD/DJwkr0eKwA1SDIAhqgLzO8gY6CIJgphJLvYMgCGqUaKCDIAhqlLkwSVg1vEiNBaO7TZs3Gw+wLbPetP3P79vnBOhaa89CL+20Z68B2lrszBoZRzJjdJ4fft6QtcfNvCgNgPZRe0b+SNb+rABbBlaZtie22p8V5rNpjZ3JpTk7bNoyKX+McDhn65083OdrgLTUj5m2vmH/1s+m7XL1nfzvTNvBQT86REfsSJo1LX5j0pjvM21ptT8rwGC9HRPh6cYAXJj7jWmr22c/X61tdhYXgIePvGVq603YT3Vy8jUc45yEsgtVRKRBRH4rIk+IyDMi8ufj7F8WERURJ5YqmM14jXMQTCf5XC7RVqsk6UEfFUvqE5Es8GsR+bmqPiAiXcD7KaS8CoIgqClm+hh02R60FniLWFLx/78CvlLyfxAEQc2geU20VYqIdIjI3SLyUvHvW1abiUiXiPyziDxXHI3443LHnbJYkohcBuxU1SfK+L6uxXHLzT9IcrogCIKqkNd8oq0KfBW4V1VPBO4t/j+eMeBPVPVk4BzgcyJyinfQRJOEqpoDTheRduAnIrIJuAr4QALf17U4nt2yK3raQRAcN47jEMflwHnF1zcAv6QghfFGWVR3A7uLr3tF5DlgOfCsddCpiiVdDqwBnigu814BPCoiZ6vqa5Z/ndiz+W17XrRP3P2KW65T2x4ybWef+0eub8apgTF/YpyNy2zthJTY38qeDeCel20tjtHcUtf3sj23mra2fXtd364Np5m29LpLXd/12ZdMWy5lV3JfyldcaE7bUQ+r2/37QsX+gbi/abHrmxF74mhF//O2Y+Op7nGf6O4wbSM5PxvLe1K/Nm11PeZjB0C+wY4uyfT4S/W/n/qEafu9Zb81bYfq/SiOs/RR1w7vLGMvT1KlOhG5Eriy5K3rip3LpCwpNsCo6m4RcW8wEVlNYYX2eOnmNzFlsSRVXVyyzzbgLFUNUYY5iNc4B8F0kjRCo/SXvoWI3ANM9K1z1WTKJCItwK3AF1XVzXM2ZbGkyRQoCIJgOqim3KiqXmTZRGSPiCwt9p6XUpivm2i/LIXG+UZVva3cOacsljRun9XljhMEQXC8OY5i/LcDVwBXF//+w/gdpDAe/B3gOVX9yyQHTRTFEQRBMBM5XmF2FBrm94vISxTWhlwNICLLROSO4j7vBj4OXCAijxe3S7yDhhZHEASzFj1OcqOqegC4cIL3dwGXFF//GvCzZowjGuggCGYt+bHaXcadiKRZb4/FBlx5vH2n45zhG9c2fCv3nYvbdI9BX1l+l6r7Tsc5w/f4+M608oZv4DLdDXQQBEFgEA10EARBjTLdDfRkllJWy3c6zhm+x8d3ppU3fAMXKQ7cB0EQBDXGdPeggyAIAoNooIMgCGqUaWmgRWSziLwgIltEZCJha8tv0hkJJjhGWkQeE5FJCT6JSLuI/FhEni+e/12T8P1SsbxPi8hNItLg7Hu9iOwVkadL3iubrcHx/UaxzE+KyE+Kmt6JfEtsZt5Jy09EvlC8xs+IyF9Moryni8gDxWWwD4vI2YbvhPdCJZktktRVuXvQqivPr1xdOeUtW1di5BRNWE+Wb5J6ilym1eB4B14DaeBlYC1QBzwBnJLQdylwZvF1K/BiUt+SY/xn4H8B/zhJvxuATxdf1wHtCf2WA68AjcX/bwH+wNn/d4AzgadL3vsL4KvF11+lIPea1PcDQKb4+r9Nxrf4fhdwJ/AqsDDhOc8H7gHqi/8vnkR57wIuLr6+BPjlZO6FJHXl+JatK+8e9OrKOWfZunJ8y9YVhaXFLcXXWQr6w+ckrCfLN0k9Teib5J6K7Y1tOnrQZwNbVHWrqo4AN1NIAFAWVd2tWlD5VtVe4GhGgkSIyArgg8C3J1NgEWmj0Jh8p3juEVU9PIlDZIBGEckATcAua0dVvQ8Yn8v+cgpfEBT//l5SX1W9S1WPph54gEJyhaTnhTJ5Jw2/zwJXq+pwcZ8JpRcNXwXaiq/nYdSVcy+UrSvLN0ldlbkHzbpy/MrWleNbtq60wEQ5RZPU04S+CevJOi9ELtPETEcDvRzYUfJ/N5NoZI8iCTMSjON/ULgxJqugshbYB/x9cXjk2yJip6goQVV3At+kkPl8N9CjqndN8vxvytYA+OlAbD4J/DzpzpIw7+QErAfeKyIPisivROQdk/D9IvANEdlBod6+lqCcq3njXphUXTn3Udm6KvWdTF2NO+ek6mqcb6K6kglyipKwngzfUsx6msi3gntqTjIdDfREak6T+iaVSWQkKPG5FNirqo9M5lxFMhR+iv+tqp4B9DNxUsiJzjufN1KELQOaReRjUyhDRYjIVRSSVt6YcP8mCpkivj6F02WA+RR+Dv8X4BYRSari9VngS6raBXyJ4q8Wp5yTvhfK+Sapq1Lf4r6J6mqCcyauqwl8E9WVquZU9XQKPd2zRWRjuXIm8S1XTxP4Hs1lOpV7ak4yHQ10N4UxqKOswPnJPx6ZZEaCEt4NXCaF9Fw3U9BkTZpmvBvoLuk9/JhCg52Ei4BXVHWfqo4CtwHnJi82AHukkKUBcbI1WIjIFcClwL9X1aRfhut4I+/kNt7IO+knmivQDdxW/Jn7Wwq/WJJOBl1BoY4AfkRhSGxCjHshUV1Z91GSuprAN1FdGedMVFeGb+K6gkJOUQrJTDczyXtqnO+k7qkS39JcptuY3D01J5mOBvoh4EQRWSMidcBHKGQjKEuxZzGpjARHUdWvqeoKLWR/+QjwT6qaqCerhUS4O0TkpOJbF+Jk4h3HduAcEWkqlv9CCmOIk+FotgYwsjVYiMhmCtmFL1PVgaR+qvqUqi5W1dXFOuumMFHlZyct8FPgguL511OYVE2ar3IX8L7i6wuACRMeOvdC2bqyfJPU1US+SerKKW/ZunJ8y9aViCw6GmUhb+QUfT5hPU3om7CeJvJ9rIJ7am6i0zAzSWHG+UUK0RxXTcLvPRSGQ54EHi9ul0zh/Ocx+SiO04GHi+f+KTB/Er5/TuGheBr4PsUZe2PfmyiMVY9SuIE/BSwA7qXwAN4LdEzCdwuFMf+j9XVtUt9x9m1MHMUx0TnrgB8UP++jwAWTKO97gEcoRPc8CLx9MvdCkrpyfMvWVZJ7cKK6cs5Ztq4c37J1BWwCHiv6Pg18vfh+knqyfJPU04S+Se6p2N7YYql3EARBjRIrCYMgCGqUaKCDIAhqlGiggyAIapRooIMgCGqUaKCDIAhqlGiggyAIapRooIMgCGqU/wPuX+oGAtvrEAAAAABJRU5ErkJggg==\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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mxupfWeck+lWS6ut9T5WKUKUywCQUfWcicpuI7BaRtSNe6xSRVSKyMf/TP3KCmsabuINgQklJskcVkuRr6bvAilGvfQV4SFUXAw9RgZI+QRAElUYklehRjRTttar+GhhdrfVa4Pb877cDH6hwv4IgCMrnFD/zLsSMY7XZ8j/NW9ne4G3yk1+NcXdBEARjIG6PHzuqupL8zTt9v/wn/wpGEARBJQm1yXHsEpFZqrpTRGYBdvmWEWQ22FVG0tNtH4rhXbvcdvdtsP0v2s97k5ubnW8XEuhvs/sEoCn7wEivsf1Y6jyfCSDlVBXqr/f9ItJHeu399hxxc4cOOr4oafu9Dh0+QqNTpSdbZx9m2YOjV+RGte14tTS/+Vw3lz7bd0OLKCEG9h4wY/VddgWl7FG/Qs++5+3qMrOXnOnmHnaqPg3W+XVQUnMzZizrHMfgV9rpPdM2m2vZucFtd3iyPY4Vo0rPqpMw1nd2P3B9/vfrgR9XpjtBNeJN3EEwodTwmnfRM28RuRO4DJgmIt3kboe/CbhHRD5JzqDqQyeyk0EQBGOihs+8i07eqvoRI3RFhfsSBEFQWcLbJAiCoAoJb5MgCIIqpMjF2GpGil11ryS7b/wTc2d7X7ArjMxa7l+Fb+i0787POhV6ADRjX4VPF/ECkfm258P2Be8wY12HNrntpo8etINZu78Aqd22B8nh1X5VoUmnLzBjh57f6OZO/uCHzVhvu+1p03zYroIEkGloMWP1a37n5qamOK4NRf6oXz37SjM2c91DZuzoQt9Lp/HIXjOW3mt/dgCZnXY81eSrTYbfdKG93yO2sgYg43iqpLfaipLDz6xx2x3qtf2MAObccnfZax79P/t2ogmuacWnqm59ZazeJjeLyDoRWSMi/yIiU05sN4OTGW/iDoIJRSTZowoZq7fJKuBcVT0P2AB8tcL9CoIgKJ8avsNyTN4mqvqgqh7z8nwUmHsC+hYEQVAep/iZdzE+AfzUCo70NvneM/4dV0EQBJVE6+oSPaqRsiZvEbmRXPHhO6xtVHWlqi5T1WUfv2BJObsLgiAojRpeNhmzVFBErgeuAa7QhJKV+ha7Ms20s+3qJE0Xv9VtN7PueTOWKlJtJdvbZweL/DvVveBdZqyzz1EGDPW77fZ1zDFjG9PnuLmLumwlS3uDPxak7cOhoXunGetf9QCN773GjB9tsK9ntw5ucbskmjVjqc5pbq4esSvEZA771WNmtD1h5zqqj4aZi9x2902zlVNTixxvOsNWAx1s96sz7cJW/LRPtf1jijFrwPbSmXTVfDc3tXPLmPebmCqdmJMwpslbRFYAfwlcqqr2pxecEngTdxBMJFql69lJSCIVvBP4A3CmiHTn/Uz+HmgDVonIahG59QT3MwiCoHQquGwiIitEZL2IbBKR46qHSY5v5uNrROTCpLljYazeJt+pxM6DIAhOKBU68xaROuAfgCuBbuAJEblfVUf6XF8FLM4/Lga+BVycMLdk4vb4IAhqlgoqSZYDm1R1M4CI3EWuHOTICfha4Hv5a4CPisiUfL2DhQlyS6Z2V/ODIAgqt2wyBxjp4dGdfy3JNklyS2Zcz7ybz3CuxG/eYoYyL/qeHBlHMVLMnyTTb/sr1DfbvhoAQ1pvxhqP7jNj/a2+SqK70a7us3Gn/36WvurUCXWUGwC02aqQtKMUyvz2IRreYldUmbnZ8SA5aI8TgE6bYQfT9vgDiBM/vH6Lm9vR2mrGUmecZcY2T7nA7xO2MKux3b/XrX7YPs4H6+zPB6D+tXvqCux32Ncc/HSrXbHovQvtqlDprO8rNPWI4+FTITT5evYNwA0jXlqZL+H42iaFmh/djLFNktySSVKM4TZyksDdqnruqNiXgJuB6apqO+4ENY03cQfBhJJwzXtkrV2DbmCkHnMuMLr+orVNQ4LckhmrtwkiMo/cAvzWcjsRBEFwIlBJJXok4AlgsYgsEpEG4Dpy5SBHcj/w8bzq5BLgkKruTJhbMknUJr8WkYUFQn8HfJmoXxkEwclKhfy8VXVYRD4L/ByoA25T1edF5NP5+K3AA8DVwCagF/hTL7fcPo31Jp33A9tV9Vkp8m/JyLWkv//UH/PJ91w8ll0GQRCUTCVv0lHVB8hN0CNfu3XE7wr8edLccil58haRFuBG4L1Jth+5ltR/99fHr/JDEARB3B7/Bk4HFgHHzrrnAk+LyHJV9cuiTJtphmSLvXS+95n1brMNbbYqpOOit7m5TbvsCj6ZebbqoyjP/N7eJ76nymmXvc+MHZ7qv58DP37ajHVcbnuxADBkqwMkbf/7OfTsU6TfYvvPiFPdZ3ivf517+OUtZqxpWZELpU79wuyQrb4AkEa7Ms3QJLtCz8IDT/FMy6VmfO9RWxXSOvWI26cj9bYaaM/gVDe3OW2rqoqt+c7ptBUlGbGnkExdmvqsvd/+2b5RnV8bKBlaUOhRG5Q8eavqc0DXsecisgVYFmqT5LhmWFWIN3GfangT96mGN3GPF0mlgtXIWL1NgiAITn5OZUtYw9tkZHxhxXoTBEFQQbI1XD0+vE2CIKhdatgSNibvIAhqllpe847JOwiCmuWUVptY3iYi8jngs+RqWP6rqn65WFs9v7JNk175zToztuv3+80YwFu+cJEZ2z33QjMGsGvm1WZsTsq/879ZbEMfOc/uU8P+XW677LH3u/zgM27q2idfNmPt137AzdX6Bjs4zy7fNVTkD6Rhul32beCcd7i5vY22PK7hVf8mtb4ZttRz0qd8GahXqC6Ttsfpome/6bb78g9+YcZaltilygAm/xv71oqpj/3BzW0+601mbGj26W7u2xp2m7H92OXXpm17ym0329zmxivBqX7m/V1ylXO+d+wFEXk3OT/a81R1QES6jNwgCIKJ41Re8za8TT4D3KSqA/lt7K/mIAiCCSIrtas2Gev/FEuAd4rIYyLyiIiYawQicoOIPCkiT37vaf9OySAIgkpSQVfBk46x9joNdACXAH8B3COGQ5WqrlTVZaq67OMX2uumQRAElUaRRI9qZKxqk27gvryL1uMikgWmAXsq1rMgCIIyqdaz6iSMdfL+EXA58LCILCFXKaKot0nbpbbvw7nnnWPHPlvkm7HVvmr9EpPd1N29TrmrVr8s1fCQfWDM2vmKGRvq7nbbzX0nFubQBrtdgMygU+qsWBk0h+F621Cpv8Ef4/oe+9CoH+jx99tsXwtPHfAvtTTWN5qx3sm+smMobed6Z2rNc33lRucZtkKmdYFf1nD7AluZM7vRL9l3cOppZqyv3ld9NHzzRjM288MfNmN77vkXt92uy32TNSpgmVNJS9iTjSRSwTuBy4BpItIN/A1wG3CbiKwFBoHr1ZtxgiAIJoBavmBZjrfJxyrclyAIgopSrevZSYg7LIMgqFlizTsIgqAKiTPvIAiCKuSUPvMu5G0iIkuBW8lVKhoG/pOqPl6srf3zbZ+RSZ07zVj9IV9VIHvs3AODvhJi+157CPYcsstdAczptMuG7V71GzPWudTXu6eXnG3GphS5ev7C3bZHjGTsclYABzvt/e6vs1UfdZJx2+3c63y2Wze5uTPn2kqV3kXnu7kD9ZPs3CIKmamHtpix/mb7uNg/0x5DgM4P2BfQ9nb5uQ9vWWTGLl7gq03qsD+jRvGcXKDjQlsJ1j95hhnr+oDtGwTwyuJ/48YrcVdILZ95J/la+i6wYtRrXwe+pqpLgb/OPw+CIDipyJJK9KhGxuptovCagLod2FHZbgVBEJSPVunEnISxvrMvADeLyDbgG8BXrQ1Hept8/+57x7i7IAiC0onb44/nM8AXVfWHIvJh4DvAewptqKorgZUAO9aviRt5giAYN6p1Yk7CWM+8rwfuy//+A2B5ZboTBEFQOeLM+3h2AJcCD5PzONmYJGmwrsmM9bbaaoY97UvddhdOetKMnZHa4OY2zLc9H/oz/vBMbTxsxlpnTzNj6Xa7OgzAvrn2+506OODmzn7r02ZMMkVUIRt/Z8baO21VQZ2jJgHIHjpoB+v825fFkXo17fc9Ypodx4aOIX8cObjPDKVOP8+M7W73K/TIgF19qeOQ71szf5rtmzIZZ4yBabttT5Vix4UuPteMeb429Z2z3HbHg2qdmJMwVm+TPwNuEZE0uYpRN5zITgZBEIyFrNbuBctyvE3eUuG+BEEQVJRT+sw7CIKgWonJOwiCoApRjck7CIKg6sieymfeIjIP+B4wE8gCK1X1FhHpBO4GFgJbgA+r6gGvrecO2cqOtzY+Ycamyi63j0NN9hXv1h5fCbEkbXe5afOzbi71DXaf2u3qJINLfPXMlL22eOf+9k+4ue/9r7baYWjY97DYN8X+fLp2rDZjg5tfctsdOnzEjKWKqE2GNmw2Y89dd6ubO6/F9sSZs9tW5QAc/tmDZmzy/v1mrPndM912n575b83YoX67eg/AZc/8NzOmQ75vjTqKkuyA7dED8NQV/9WMZQbtyfHX685y2z13if/Zn+kXJUpELV+wTPLOhoH/oqpnkSs4/OcicjbwFeAhVV0MPJR/HgRBcNJQyzrvopO3qu5U1afzv/cALwJzgGuB2/Ob3Q584ER1MgiCYCyoSqJHuYhIp4isEpGN+Z8FrSdFZIWIrBeRTSLylVGxz+Vjz4tIUbO/kv6nyBtUXQA8BsxQ1Z2Qm+CBgnfZjPQ2+dl9/6eU3QVBEJTFOJ55F12JEJE64B+Aq4CzgY/kVzEQkXeTOyE+T1XPIecZ5ZL4gqWITAJ+CHxBVQ9LwqrMI71N/u9Tw+FtEgTBuDGOapNryd3MCLmViIeBvxy1zXJgk6puBhCRu/J5L5Dzi7pJVQcAVNUvYkDCM28RqSc3cd+hqsc8TXaJyKx8fBZQdGdBEATjSTbhY+QKQf5R6l3jSVYi5gDbRjzvzr8GsAR4p4g8JiKPiMhFxXaYRG0i5FwDX1TVvx0Rup+cQdVN+Z8/LtbWkX776rI22d8jQ3X+Vfj2o7YPRd2Ol93cuh7bn0SL+W602fH6LturZV/bbLfdxkZbndHU7//zUucoSup3+KqQaU6lncyzthqoYbb/fkRsxU+m3/cYaZpq+8Cc2ehX4enYZfvayIbn3Nzux2yVy1mLF5ix/nSr2+6BI7a/T3P9sJubmux44gz4SiKPnuft6ksAQxn7b7O1wVaqXHBWvdvulOYi/jI0F4kXJ6naZOQKgYWI/IKc6m40NybsTqF/A479QaeBDnKikIuAe0TkNFXboCfJssnbgf8IPCcix/Rif0Vu0r5HRD4JbAU+lKz/QRAE40Mll01UtaDtNYCI7BKRWaq601mJ6AbmjXg+l9cL2XQD9+Un68dFJAtMA/ZY+0zibfJbCn9jAFxRLD8IgmCiGEcZYJKViCeAxSKyCNgOXAd8NB/7ETmH1odFZAnQANgFXBm7n3cQBMFJT1aTPSrATcCVIrIRuDL/HBGZLSIPAKjqMPBZ4OfkJNf3qOoxr97bgNNEZC1wF3C9t2QCcXt8EAQ1zHideavqPgqsRKjqDuDqEc8fAB4osN0g8LFS9hmTdxAENcspbUzleJvcDPwRMAi8BPypqrrlPA722ANZN9lWOjQO29VHALJ19lXtzLZtZgygd7utcJy00FdRpNtsTxWvQsxu8SuMnD74jBk7p9OvtlK/xlZYDBUZi/q0PY7bn3jBjE35su3XAdDa/qK9z76jbi6Dtpqh6HGRtlVK6SJKovlvX2znTrWrJO3stysOAfQO2CuV6VSRVcwG20unGJmZ88xYy2FbcQVwVrPttTNYZytCOjptZQ0kUYKUrzbJ1PDkXY63ySrgXFU9D9iAU0E+CIJgIhiv2+MngjF7m6jqg/kFeIBHyclegiAIThpUkz2qkXK8TUbyCeCnRs5rdy799gFXAx8EQVBRatlVcMzeJiNev5Hc0sodhfJG3rn0rZ9Rpd9xQRBUIxWSAZ6UJJq8DW8TROR64BrgimKaxCAIgvEmm63Os+okjNnbRERWkHPNulRV/cv+eZoci5KDLbYCYwj/KntTvV0NR4pUGJGU8+FKkVWlvj475ihR5g7ZvhkADevtKi9zpna7uep4tWR6nf4CvGSrCg5us4VEczbYvieAq5LIHnSLLyGOAqb1Dz/x9+swuMqVXOcAABb1SURBVN/f7/5Nr5qx5g+fa8aGs/4x09yQNWNTmop8Po7yZvhVv2KU94c+7FTZAWg/bB9z9bu32onF1DO9RZRGZ3zejyfglC6Dhu1t8k2gEViVt4d9VFU/fUJ6GQRBMAZqeT2gHG+T4+4SCoIgOJmoVhlgEuIOyyAIapZT/oJlEARBNXJKL5sEQRBUK7V8e7wUU/hZ3iYj4l8Cbgamq6rrP3v09/eZO+ueYVf9mXHYVkEA7GtfaMZ2DUx3c5vq7Cv4M17zSS+MOGPXufpnZix7xK6UA6BnLTVjB6YtcXOfOHiWGWtr8iu1LGi1FRYHhuwqLudtvtttl0bH4+KgXQUJoG+d7dWy8d/d5Oa2pm0RVNeAo5IA2tY+YsYGF19gxho22r40AHTYx6Pu2u6mbnvbx81Yf9b3EenK2G2nsr7aZPXQeWbs4syvzdjjde902x3I+P4y11yYLnvm/cGjyRZOPnSJJzs7OUly5n3M2+RpEWkDnhKRVar6Qn5iv5JcJZ0gCIKTilpeNhmzt0k+/HfAlyHunAyC4OQjq5LoUY2M2dtERN4PbFfVZ4vkvOZtctuPHxxzR4MgCEqllo2pxuRtQm4p5UbgvcXyRnqbeGveQRAElSZj39Ba9SQ68y7gbXI6sAh4VkS2kLODfVpEZp6ojgZBEJRKLft5j8nbRFWfA7pGbLMFWFZMbVK31/ZfmNVoV2o52upXJ0lnbf+Sf/6p/9W76LROMzZ/ZoebO6fd9maYMvd0M5Y6uMdtd8ipALMtM9/N7Ru0v4/XbfE/7pemLDBj23faqpyzzvat3NM9jqKkw65KA5CeZPtqiPj/yKXE/uwzdb5fTtbxrZGMfbzteWS0W/IbaWxvNWNN0+1jESCDrc5oSNmfD8DknbZia2iSv9/Ne+yxmrLAVokdOewfb8PjYBpVrUsiSUhy5n3M2+RyEVmdf1xdLCkIgmCiGcfq8eNOOd4mI7dZWKkOBUEQVIpaPvOOOyyDIKhZYvIOgiCoQmpZbRKTdxAENUv2VJ68PW8TEfkc8Flyuu9/VdUve21pm+2P4fmEtPb66oxUs321/Mjhfje3v3+SGevp9b0X9tU3mzEZcq7+Dwy47db19Zixg84+Abom2/vtHXBKGQGtTfZn0NdhV7Sp37zWbddVbtT5Yzx4yBmLfn8smlrtcR6s871A+rbaXiAtTmWgxo42t93GjnYz1rDAVvsApLBnooGs/9mmdm6x+zTFHmMAca549WfsKWSdvUsA5s4s6R7BMXGqL5sU9DYBZgDXAuep6oCIdLmtBEEQjDOn9OStqjuBnfnfe0TkmLfJnwE3qepAPrb7RHY0CIKgVKpVBpiEMXubAEuAd4rIYyLyiIgUVOuP9Db5zk9+WW5/gyAIEqOqiR7VyJi8TVT1sIikgQ7gEuAi4B4ROU1HjcRIb5O+X91RnaMUBEFVkvGtyquasXqbAHQD92mOx8ldzPTvdQ6CIBhHTmlXwULeJnl+BFwOPCwiS4AGwPU22TTvPWasI2srSo7U2SoVgL0DtgfJ/EW2SgJg/mxb7TCl1a88c1q73WfttxUJOm2W225fp+0VMtWpDgO+n8cZM3zd1Oxm+/3snOJ8Lz/vnwOkWmw/D7fKDtA83z51mtFyyM3NqN2vrPgql8ZptoJp/7JrzFiH42kDgKeu6Tngpg6qo3JJ+QomHKVXsdPTOkfI0lpv7/fMhb4aqL3ZV4KBf2wkoZbXvJMsmxzzNnlORFbnX/sr4DbgNhFZCwwC149eMgmCIJhIanlGKtfb5GOV7U4QBEHl0MSn3tVnC3viVfJBEAQTRCab7FEuItIpIqtEZGP+Z8G1XBG5TUR251csRr5+s4isE5E1IvIvIuKvFROTdxAENUw2q4keFeArwEOquhh4KP+8EN8FVhR4fRVwrqqeB2wAvlpshzF5B0FQs4yj2uRa4Pb877cDHyjcH/01sL/A6w+q6jGFxKPkqpO5jNnbRESWAreSuyQ8DPynvGTQ5IxtvzBjQ888YffhFbsCD8D2T91uxq5a7l/R7nEsSDJFKn3sHbB9KppmXWDGNvfMcdvddcBWFQwN+306rctWo+zv9f0vhrN2xaL+YVslceTst7vt9jRPN2Mp9ZUOjcP2+5kzsMnNTf3f75uxl3+xxs3dM2Arjd58xplmbGDNajMG0DDTqQrVNtnNnaJ2RaJe8T1VehYutXfb/byb+/vf2jdPDyy3XTHmTfc/24WtO9w4nFYkXpykE7OI3ADcMOKllfl7VJIyI383Oqq6s0y7kE8AdxfbqBxvk68DX1PVn+Yr63wduKyMDgdBEFSUbMLZe+TNhBYi8gtyJ7GjubH0npn7uJHcnHtHsW3L8TZR4NipQjtQ7Gs0CIJgXNEKWsKqqnmjiojsEpFZ+bPuWUDJXk8icj1wDXBFEtl1SX7eo7xNvgD8XES+QW7t/G2ldjYIguBEksmMm9D7fuB64Kb8zx+XkiwiK4C/BC5VVf9OvDyJL1iO9jYBPgN8UVXnAV8kdxdmobwwpgqCYEIYR2Oqm4ArRWQjcGX+OSIyW0QeOLaRiNwJ/AE4U0S6ReST+dDfA23AqnyR91uL7TDRmbfhbXI98Pn87z8Avl0oN4ypgiCYKMbr9nhV3QdcUeD1HcDVI55/xMg/o9R9luNtsgO4FHiYnMfJxqJtHT1sxg5u2GrGOs9b4ra7pGmzGXt50K9OMpyx1Rt7e3xflOmOOGBr1vYv2XXYVpMAbN1hL9Tt3m1XpQGY8y677Z37/H+00tPtw2Ffj602GZ7le1C80mera2Y0H6eaegMH6myPkbYGvwLMnPNthcWCAUdmBOzf6FzCcfxJXDUJQMpRCxVZoPX8WNqGfV+UIa9yUJFqRhuefNGMzV1o30sya6o/vQyqr36qBMnvsKw+yvE2+TPglrw1bD9vlNkEQRBMOOFtYt/4/5bKdicIgqByVOjuyZOSqB4fBEHNkh0/tcm4E5N3EAQ1S9KbdKqRmLyDIKhZarnEQBK1SRPwa6Axv/29qvo3ItJJ7v77hcAW4MOq6l7yHli3zowd2WVXRema5ldXOyS2IqEYkxpt1UFD2r/67/l9HOizr6Tvsi0qANizx1aUZIr4V+47YitkWooUJpncZI9FTi1amM1FVE49A3bu3qN+VaGeXlsh82+nPOfm0m+PY6rRV/x0nG73q/9J28Knb7evnskO234fqbSv+uh9878zY01Fchsy9li8uuASN3fpu20FzTuX2pPjwknb3HanH37Jjedu5C6PWl7zTnKTzgBwuaqeDywFVojIJSS3QAyCIJgQTukalvl77I/kn9bnH0rOAvGy/Ou3k9N7/2XFexgEQTBGiv2nWs0krR5fl9d47wZWqepjjLJABMqxQAyCIKg4mtVEj2ok0eStqhlVXUrOIHy5iJybdAcjvU2+++ja4glBEAQV4pSfvI+hqgfJLY+sAHblrQ/xLBBVdaWqLlPVZX9ySeI5PwiCoGyymuxRjSRRm0wHhlT1oIg0A+8B/jtjsEBsnDPbjE2e61TLyfgVOaYOv2rGNvXaVVwA9jueHeXw1gXbzdgZHb5nyoZZtrrmQI//fbt0pr3f323xr957F26a0vZnML3BV1jMrh+w2x0+6uYemGavxtXvtr1yALJTbZVEQ6dvt3zwBbtKT/OK95mxpr1+1SeOHjFDmcP++9mv9mff3uvvt77fbru3rVB9gdc57fTFZmzzLturZVpLq9vu5Ca7ElWlqNaz6iQk0XnPAm4XkTpyZ+r3qOpPROQPwD15S8OtwIdOYD+DIAhK5pTWeavqGnIFGEa/XtACMQiC4GShltUmcYdlEAQ1y6m+bBIEQVCVxOQdBEFQhZzSxlSOt8nNwB8Bg8BLwJ/mpYQm+y+8yoxlLvqAGes7aqtJADo2214Tlz670s1tnGUrEjJnL3Nztc4evvRvHrUTF/uSyXmTbLXJbTvf5eYuevz7druH3I+Hwz/ZYsZa59iqj1S9fxjpO1eYsfQzv3FzJ4utZvjFeX/t57bZXi1Ll/v3lE1dsMiMbZj+DnufXf4YT9u33oytm2K3CzBZ7MpBLzed4+a2tNreJnMP+B4xPT3DZmz+TFut1X3YrrID8GLfVDf+UTeajFo+8y7H22QVcK6qngdsAL564roZBEFQOuNYgHjcGbO3iao+OGKzR4EPVr57QRAEYyczXLtqk3K8TUbyCeCnle5cEARBOdTymXfZ3iYiciMwDNxRKHekt8n37763En0OgiBIhGaziR7VSElqk/wt8g+T8zZZKyLXA9cAV6jx9aWqK4GVADvWr6nOr7ggCKqSWi7GMGZvExFZQc6/+1JV7U2ys6ZB21+h/cheMzbU7F+11v127sB+3y9CHd+Ulnl+yZu+aQvMWNr5Ns80NLvtZuts75MG3xYF2uwKMKmBfje1vtUutXNoU5GqKP/ervJyoNVW9LSd/za/T/tsr5Y5k+3qSwBtdbaPSNP2l91cDtl+Lafv+a0Zyza0uM2mj9jFpqZO84+3QezqTIMZ/095Up19PNb12SoWgHmz7YOuTuy/n0kNQ267qraSKN96kXhxqnVJJAnleJtsIicfXCU5OdejqvrpE9fV4GTFm7iDYCLJ1vAFy3K8TfzChUEQBBNMVk/hyTsIgqBaqeWbdGLyDoKgZonJOwiCoAo51S9YVoyeZruqTVbsK8tDaV+d0bDArvQxedCu4gIg9faVdHV8NQAka19pz/TYSod0j68q0JQ9Fg31fp+2LrzMjM1u9VU7bbPnm7HmzRvMWGb9WtLtdtvNnXPNmKcmAaDf9uQoprAYStmfbbZlspub3WR7kKRm274nOMcE+AqlTBF1RduwrVRpaPCP89YB23NFhnwVUsck+z2d3mEfy6/2+sfbeJCtUg13EorepCMiTSLyuIg8KyLPi8jXRsW/JCIqIrabUlDTeBN3EEwk2Uwm0aMaSXLmfcyY6oiI1AO/FZGfquqjIjIPuJJcGbQgCIKTilpe8y565q05jjOmyj//O+DLI54HQRCcNGhWEz2qkTEbU4nI+4HtqvpskdzXvE3++a67K9DlIAiCZGQ1m+hRLiLSKSKrRGRj/meHsd1tIrJbRNaOen2piDwqIqvz8+XyYvscqzHVecCNgO+Gn8tdqarLVHXZR6/790l2FwRBUBHG8cz7K8BDqroYeCj/vBDfJecNNZqvA1/Lz7N/nX/uMlZjqmuBRcCz+Vvj5wJPi8hyVTXL3gyIrRrRJruqxlHa3H61tNreJg2Llri56viIZBtsrw+A9ICtKEldeIkZ65nqqBWAnqZOMza0yz/QhtR+P32TZ7q5DY4vR+NBXyEzvOBMM+Z5tfTO8j+fbMo+RJvSdqUcgClZ+7hIHfbfz4ENr5ixyc4fe/2ZZ7vtZqbbfwN1+BfO6odt5c3ulO1pA5BqsNtOT/ePxw6xxzmLrX4qNic2pItdKKyAt8n4qU2uBS7L/3478DA576c39kf11yKysEC+AsckUO3AjmI7HLMxlap2jdhmC7BMVe2/lqBm8SbuIJhIkipJROQG4IYRL63MO6ImZYaq7gRQ1Z0i4tfZO54vAD8XkW+QWxHxHdsow5iqxI4FQRCMO0ktYUdaV1uIyC+AQv++3lh6z47jM8AXVfWHIvJh4DvkTpRNxmxMNWqbhSV0MgiCYFyo5LKJqpqTqYjsEpFZ+bPuWeTEHaVwPfD5/O8/AL5dLCHRBcsgCIJqZBwvWN5PbgIm//PHJebvAC7N/345sLFYQkzeQRDULKrZRI8KcBNwpYhsJHfj4k0AIjJbRB44tpGI3An8AThTRLpF5JP50J8B/0NEngX+G29cfy9IGFMFQVCzZIfH59Z3Vd0HXFHg9R3A1SOef8TI/y3wllJ3OmEP4Ibxzp2IfUZufLaRW35uPN74mOhlk6L/GpyA3InYZ+SOT2619TdygzEz0ZN3EARBMAZi8g6CIKhCJnryLuUOpkrlTsQ+I3d8cqutv5EbjBnJX0QIgiAIqoiJPvMOgiAIxkBM3kEQBFXIhEzeIrJCRNaLyCYRsXxvC+XNE5FficiL+Xqany+edVwbdSLyjIiUZK4lIlNE5F4RWZff/1tLyP1ivr9rReROETG9ZguZtZdj9C4iN+f7vEZE/kVEChactEzi8zGzTqljLv+5/Gf8vIgU9CY2+pvIlN46FpKMlZNbdKyKHYPWWHl5xcbK6W/RsRKjBm3CcbJyk4xT1L490Yy3sJycSe9LwGlAA/AscHbC3FnAhfnf24ANSXNHtPH/AP8M/KTEvNuBT+V/bwCmJMybA7wMNOef3wP8ibP9u4ALgbUjXvs68JX8718hZ8mbNPe9QDr/+38vJTf/+jzg58ArwLSE+3w38AugMf+8q4T+Pghclf/9auDhUo6FJGPl5BYdK+8Y9MbK2WfRsXJyi44VIMCk/O/1wGPAJQnHycpNMk4Fc5McU/FI9piIM+/lwCZV3ayqg8Bd5IzMi6KqO1X16fzvPcCL5CbHRIjIXOB9JHDsGpU3mdxE8538vgdV9WAJTaSBZhFJAy04Ruuq+mtg/6iXryX35UH+5weS5qrqg6o6nH/6KLnCGUn3C0XqlBp5nwFuUtWB/DYFHdaM3ESm9M6xUHSsrNwkY1XkGDTHyskrOlZObtGx0hyFatAmGaeCuQnHydovRO3bijARk/ccYNuI592UMAEfQ3LVKC4g942elP9J7qAp1YnmNGAP8I/5JZdvi0hrkkRV3Q58A9gK7AQOqeqDJe7/DUbvQKlG78f4BPDTpBtLwjqlBVgCvFNEHhORR0TkohJyvwDcLCLbyI3bVxP0cyGvHwsljZVzHBUdq5G5pYzVqH2WNFajchONlRSoQUvCcTJyR2KOU6HcMo6pYBQTMXkXqptU0jewiEwCfgh8QVUPJ8y5Btitqk+Vsq88aXL/3n9LVS8AjmLXqBu93w5eLxs3G2gVkY+NoQ9lISI3AsPAHQm3byFhndICpIEOcv9i/wVwj4jY9bLeyDFT+nnAF8n/t+P0s+RjoVhukrEamZvfNtFYFdhn4rEqkJtorPT4GrTnFutnktxi41QgN3Ht26A4EzF5d5Nb8zrGXBLUazuGiNSTO4DvUNX7Stjv24H3S65k213A5SLy/YS53UD3iLOOe8lN5kl4D/Cyqu5R1SHgPhKUOBrFLskZvCNjMHoXkeuBa4D/oKpJvyhP5/U6pVt4vU6pXwgzRzdwX/5f58fJ/aeT9MLU9eTGCHKm9GYVbeNYSDRW1nGUZKwK5CYaK2OficbKyE08VpCrQUuutuIKSjymRuWWdEyNyB1Z+3YLpR1TwSgmYvJ+AlgsIotEpAG4jpyReVHyZyTfAV5U1b8tZaeq+lVVnau5qj/XAb9U1URnwJorqrxNRI4Va7wCeCHhrrcCl4hIS77/V5BbsyyFMRu9i8gKcoVQ36+qvUnzVPU5Ve1S1YX5Mesmd9HMLDA9gh+RM5RHRJaQu8CbtL5pIlN651goOlZWbpKxKpSbZKyc/hYdKye36FiJyPRjahB5vQbtuoTjVDA34TgVyn2mjGMqGI1OwFVSclfGN5BTndxYQt47yC2xrAFW5x9Xj2H/l1G62mQp8GR+3z8COkrI/Rq5P5i1wD+RVxYY295Jbm18iNzB/UlgKvAQuT/Oh4DOEnI3kbvGcGy8bk2aOyq+hcJqk0L7bAC+n3+/TwOXl9DfdwBPkVMhPQa8pZRjIclYOblFxyrJMVhorJx9Fh0rJ7foWAHnAc/kc9cCf51/Pck4WblJxqlgbpJjKh7JHnF7fBAEQRUSd1gGQRBUITF5B0EQVCExeQdBEFQhMXkHQRBUITF5B0EQVCExeQdBEFQhMXkHQRBUIf8/T69biZelW4cAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "for cor in corAll:\n", + " sns.heatmap(cor, cmap=\"coolwarm\")#, vmin = -.5, vmax = .5)\n", + " plt.show()\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 383, + "metadata": {}, + "outputs": [], + "source": [ + "# seperate ketamine and midazolam\n", + "group_label = np.array(group_label)\n", + "ketArr = np.array(corAllz)[group_label==1]\n", + "midArr = np.array(corAllz)[group_label==0]" + ] + }, + { + "cell_type": "code", + "execution_count": 385, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot mean matrices\n", + "fig, ax_list = plt.subplots(1, 2, figsize=(16,4.5))\n", + "ax = ax_list[0]\n", + "ax.title.set_text('Ketamine')\n", + "sns.heatmap(np.mean(np.array(ketArr), axis=0), cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax)\n", + "ax = ax_list[1]\n", + "ax.title.set_text('Midazolam')\n", + "sns.heatmap(np.mean(np.array(midArr), axis=0), cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax)\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 391, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 391, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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8tlDoZgPuvCPrdj1W2s8OO73p/qNWX9ujSMq3LfEhYe18jUYk/YisHpxoSUSkjmI7OiI2SZoOLJf0WET8tNHBKV0c23NxrJa0C/CgpOXAcuDCiNgq6VKylb3PTwzSzKzryhzFERF1F8Zu8xyb8p9bJN1Otp5rwwq641wcEbEsIrbmh60EZhYN3sysTBFpWy9I2jlv5CJpZ+BEsoeLDRXJxVHrE8DdDco4F4eZ9UWvcnFI+o/5mq1HAT+QdE/++b6S7soP2xu4T9Ia4H7gBxHxw2bn7TgXR83nS8i6QW6sV865OMysX3o1zC4ibgdur/P5JmBh/vpJ4B3tnDepgm6QiwNJi4GTgfkRvfpDwcwszfj4kM8kbJSLQ9ICsoeCx0TEK90L0cy6acb79+p3CF0z9Ete0TgXx9eBt5ANFQFYGRFndiVKM7MODPrf9UVycdxV5zMzs8oY+mRJZmaDqoe5OLrCFbSZDa2h7+IwMxtUqVO9q6rjXBw1+z8HXA7slZpCz8yqY/bXLul3CF0zGVrQdXNxRMSjeeX9AbIVVczMKmXQK+iOc3Hku78KnEeWQs/MrFLGQ0lbVXWci0PSKcCzEbGmRRnn4jCzvqhSsqROdJSLg6zbYwlZNqamnIvDzPpl23i/IygmqQVdJxfH24H9gTX5IogzgdWS6iWzNjPri9QVVaqqo1wcEbEWmF5zzFPA4R7FYWZVUuXuixQpLejtuTiOl/Rwvi3sclxmZoWNR9pWVUVycdQeM7usgMzMyjLoLWjPJDSzoeUK2sysogZ9FIcraDMbWuMDXkG3fEgoaZakH0vaIGm9pM/U7Pu0pMfzzy/rbqhmZu2ZDBNV6ubiIFuhdhFwaES8Kml607OYmfVYlSvfFCmjODYDm/PXL0nanovjk8AlEfFqvm9LNwM1M2tXlYfQpeg4FwdwIPA+Sask/UTSEQ3KOBeHmfVFRCRtVdVRLo6IeFHSFGB34EjgCOAWSQfEhH+tc3GYWb9s29bvCIrpNBcHwBhwW2TuJ0vmv2d3wjQza9/QPySsl4sjdwdwPLBC0oHANMC5OAbYVx6c13Dfn7/r/h5GYlaOQe+DTuni2J6LY62kh/PPPg8sBZZKWge8Biye2L1hZtZPg14jFc3FcVq54ZiZlSeSm9DVTDnqmYRmNrQGfap3W8PszMwGyfh4JG1FSfpLSY/k6ZiXSdq3wXEL8tnXGyVd0Oq8rqDNbGj1cBTH5RFxaETMBb4PXDTxAEmjwDeBk4CDgY9JOrjZSVNGccwCbgD2IRtKd3VEXCFpLnAVsAPZdPA/y4fb2YDySA0bNr16SBgRL9a83Rmod+V5wMaIeBJA0s1k6TIebXTeIrk4LgMujoi78xVWLgOOTfnHmJn1wngPh3FI+hLwJ8ALwHF1DtkPeKbm/Rjw7mbnbNnFERGbI2J1/volYHsujgB2zQ97G7Cp1bnMzHopxtO22pQU+XbGxHNJ+pGkdXW2RQARsSQiZgE3AmfXCafeUJGmv0HaGsUxIRfHOcA9kr5MVtG/p51zmZl127ZtaS3o2pQUTY45IfGy3wZ+AHxhwudjwKya9zNp0bBNfkg4MRcHcBZwbv4b41yy2Yb1yjlZkpn1Ra+SJUmaU/P2FOCxOof9HJgjaX9J04BTgaaVYlILukEujsXA9uT93wGuqVfWyZLMrF96ONX7EkkHkQ2k+EfgTIB8uN01EbEwIrZKOhu4BxgFlkbE+mYnLZKLYxNwDLCCLCfHE23/k8zMuih9JmHB60T85wafbwIW1ry/C7gr9bxFcnF8ErgiTzv6r8CbOtXNzPppsufieFe54ZiZlaeMWYL95FwcZja0xhNHcVSVK2gzG1q9nKjSDa6gzWxoDXqK+pbjoCXtIOl+SWskrZd0cf75HpKWS3oi/7l798M1M0vXq2x23ZIyUeVV4PiIeAcwF1gg6UjgAuDeiJgD3Ju/NzOrjKFfkzBfxurl/O3UfAuyLEzH5p9fTzYe+vzSIzQz69C2Ac/Yn7qq92g+BnoLsDwiVgF7R8RmyBIqAdO7F6aZWftiPJK2qkqqoCNiW56IeiYwT9IhqRdwLg4z65dBr6DbGsUREb+VtAJYADwnaUZEbJY0g6x1Xa+Mc3GYWV9UuO5NkjKKYy9Ju+WvdwROIMvUdCdZwiTyn9/rVpBmZp2YDC3oGcD1+XpaI8AtEfF9ST8DbpF0OvA08JEuxmlm1rZBHwedMorjEbIk/RM//ydgfjeCMjMrw6CP4vBMQjMbWlXuvkjhCtrMhpYraDOzihr0ZElFcnFcLukxSY9Iun37SA8zs6oY9FEcRXJxLAcOiYhDgV8AF3YvTDOz9vVq0dhu6TgXR0QsqzlsJfDh8sMzM+vctq2DPYqjSC6OWp8A7i47ODOzIga9BV04F4ekJcBW4MZ6ZZ2Lw8z6JcbHk7aqKpKLY52kxcDJwPxo8GvIuTjMrF+qnIw/Rce5OCQtIMv/fEpEvNLdMM3M2jfoXRxFcnFsBN4CLJcEsDIizuxeqGZm7Rkf8IeERXJx/F5XIjIzK8l4DHkFbWY2qKo8CSWFK2gzG1quoM3MKqrKDwBTuIK2/2/JDxsvNfmlBes6Pu+X/v5NjzDeuOb7Hur4vGatjFd4jHOKjpMl1ez/nKSQtGf3wjQza9/4tm1JW1la1YeSnpK0VtLDkh5odb6UFvT2ZEkvS5oK3Cfp7ohYKWkW8AGyJa/MzCqll33QbdSHx0XEr1PO2bIFHZk3JUvK338VOK/mvZlZZfQ43Wjp9WHHyZIknQI8GxFrWpR1Lg4z64vxGE/aauupfDujneuk1odklfcySQ+mXCPpIWFEbAPm5lO+b5d0KLAEODGhrHNxmFlfpLaOa+upRiT9CNinzq4lwOdJqA+BoyNik6TpZLOwH4uInzY6uNNkSYuA/YE1+TTvmcBqSfMi4lftnNOqo8hIjWY8UsP6pcxMdRFxQr3PJf0hifVhRGzKf26RdDswD+i8gpa0F/B6XjlvT5Z0aURMrznmKeDw1I5vM7NeKHOERiMRsRZoWR9K2hkYiYiX8tcnAl9sdu6OkyW1908wM+u9fqcblbQvcE1ELAT2Jusihqzu/XZE/LBZ+Y6TJU04ZnZqwGZmvdKPZPy19WHepbEwf/0k8I52zuWZhGY2tJyLw8ysosLpRs3Mqml8a/cfEnZV6pIw3diAM3pdth/XdFn/t3XZ4mUn45Y0k7CL2pqtU1LZflzTZXtTdtDidVlrqt8VtJmZNeAK2sysovpdQTed+96lsv24psv2puygxeuy1pTyjnszM6uYfregzcysAVfQZmYV1ZcKWtICSY9L2ijpgjbKzZL0Y0kb8vURP9PBtUclPSSprYRPknaTdKukx/LrH9VG2XPzeNdJuknSDk2OXSppi6R1NZ/tIWm5pCfyn7u3UfbyPOZHJN2e5/ROKluzr+E6a43KSfp0/t94vaTL2oh3rqSV29dskzSvQdm634WUe9WkbMt71eo72OheNSvX6l41ibflvVKDNUUT71Ojsin3yWuZlqHXA6+BUeAfgAOAacAa4ODEsjOAw/LXuwC/SC1bc44/B74NfL/NctcD/zV/PQ3YLbHcfsAvgR3z97cAf9rk+PcDhwHraj67DLggf30BWbrX1LInAlPy15e2Uzb/fBZwD/CPwJ6J1zwO+BHwlvz99DbiXQaclL9eCKxo57uQcq+alG15r5p9B5vdqybXbHmvmpRtea8AAW/NX08FVgFHJt6nRmVT7lPdsinfKW9vbP1oQc8DNkbEkxHxGnAz2QIALUXE5ohYnb9+CdhAVgEmkTQT+CBwTTsBS9qVrDK5Nr/2axHx2zZOMQXYUdIUYCdgU6MDI1td4TcTPl5E9guC/OeHUstGxLKI2Jq/XUmWTDz1utBinbUG5c4CLomIV/NjtrRRNoBd89dvo8G9avJdaHmvGpVNuVctvoMN71WTci3vVZOyLe9VZOqtKZpyn+qWTbxPja4LXss0WT8q6P2AZ2rej9FGJbudpNlkaVBXtVHsa2RfjHYzqBwAPA/8Td49co2yhNstRcSzwJfJVvrdDLwQEcvavP7eEbE5P99mapKDt+kTwN2pByt9nbWJDgTeJ2mVpJ9IOqKNsucAl0t6huy+XZgQ52ze+C60da+afI9a3qvasu3cqwnXbOteTSibdK9UZ01REu9Tg7K1Gt6nemULfKcmpX5U0KrzWVu/SSW9FfgucE5EvJhY5mRgS0Q82M61clPI/hS/MiLeCfwL2Z+FKdfdnTeWCNsX2FnSaR3EUIikJcBW4MbE43ciW2vtog4uNwXYnezP4f8O3CKp3n/3es4Czo2IWcC55H+1NImz7e9Cq7Ip96q2bH5s0r2qc83ke1WnbNK9iohtETGXrKU7T9IhreJMKdvqPtUpu30t006+U5NSPyroMbI+qO1m0uRP/okkTSX7kt4YEbe1cd2jgVOULUdzM3C8pG8llh0DxmpaD7eSVdgpTgB+GRHPR8TrwG3Ae9LDBuA5STMA8p91uwwakbQYOBn4o4hI/WX4dt5YZ+0p3lhnrd6imRONAbflf+beT/YXS+rDoMVk9wjgO2RdYnU1+C4k3atG36OUe1WnbNK9anDNpHvVoGzyvYJsTVFgBbCANr9TE8q29Z2qKVu7lulTtPedmpT6UUH/HJgjaX9J04BTgTtTCuYti2uBDRHxlXYuGhEXRsTMyFY7OBX4u4hIaslGtvDjM5IOyj+aDzyaeOmngSMl7ZTHP5+sD7Edd5L9z0j+83upBSUtAM4HTomIV1LLRcTaiJgeEbPzezZG9qAqZVHgO4Dj8+sfSPZQNXW9yk3AMfnr44En6h3U5LvQ8l41Kptyr+qVTblXTeJtea+alG15ryTttX2Uhd5YU/SxxPtUt2zifapX9qEC36nJKfrwZJLsifMvyEZzLGmj3HvJukMeAR7Ot4UdXP9Y2h/FMRd4IL/2HcDubZS9mOx/inXA/yF/Yt/g2JvI+qpfJ/sCnw78G+Besv8B7wX2aKPsRrI+/+3366rUshP2P0X9URz1rjkN+Fb+710NHN9GvO8FHiQb3bMKeFc734WUe9WkbMt7lfIdrHevmlyz5b1qUrblvQIOBR7Ky64DLso/T7lPjcqm3Ke6ZVO+U97e2DzV28ysojyT0MysolxBm5lVlCtoM7OKcgVtZlZRrqDNzCrKFbSZWUW5gjYzq6j/B71bDxOkZ3fCAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# compare the groups\n", + "t,p = scipy.stats.ttest_ind(ketArr, midArr)\n", + "tArr = np.array(t)\n", + "fdr = fdr_corr(p, thr)\n", + "tArr[p>.01]=0 # set p value to cut\n", + "sns.heatmap(tArr, cmap='coolwarm')" + ] + }, + { + "cell_type": "code", + "execution_count": 247, + "metadata": {}, + "outputs": [], + "source": [ + "# saving to mat\n", + "from scipy.io import savemat\n", + "mdict = {'ketamine': np.mean(np.array(ketArr), axis=0), 'midazolam': np.mean(np.array(midArr), axis=0)}\n", + "savemat('averagedMat_acrossSessions.mat', mdict)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Use PCA to see if groups differ" + ] + }, + { + "cell_type": "code", + "execution_count": 392, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(21, 36)" + ] + }, + "execution_count": 392, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# use the vector of correlations for each subject\n", + "listCorsubs = np.array(corTot).reshape(21,36)\n", + "listCorsubs.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 393, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.decomposition import PCA\n", + "pca = PCA(n_components=2)\n", + "X_r = pca.fit(listCorsubs).transform(listCorsubs)" + ] + }, + { + "cell_type": "code", + "execution_count": 394, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "explained variance ratio (first two components): [0.20078809 0.17124796]\n" + ] + } + ], + "source": [ + "print('explained variance ratio (first two components): %s'\n", + " % str(pca.explained_variance_ratio_))" + ] + }, + { + "cell_type": "code", + "execution_count": 395, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "colors = ['navy', 'red']\n", + "lw = 2\n", + "y = np.array(group_label) # make it an array so we can get mask for each place\n", + "target_names = ['Midazolam','Ketamine']\n", + "for color, i, target_name in zip(colors, [0, 1], target_names):\n", + " plt.scatter(X_r[y == i, 0], X_r[y == i, 1], color=color, alpha=.8, lw=lw,\n", + " label=target_name)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 396, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Try Hirarchical\n", + "from scipy.cluster.hierarchy import dendrogram, linkage, cut_tree\n", + "# That's the hierarchical clustering step\n", + "hier = linkage(listCorsubs, method='average', metric='euclidean') # scipy's hierarchical clustering\n", + "# HAC proceeds by iteratively merging brain regions, which can be visualized with a tree\n", + "res = dendrogram(hier, get_leaves=True) # Generate a dendrogram from the hierarchy" + ] + }, + { + "cell_type": "code", + "execution_count": 397, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[1 1 1 0 0 0 0 1 1 1 0 0 1 1 0 1 1 0 1 0 0]\n" + ] + } + ], + "source": [ + "# the order of merging above give us a good order to visualize the matrix\n", + "order = res.get('leaves') # Extract the order on parcels from the dendrogram\n", + "print(y[order]) # print group of subjects, according to order" + ] + }, + { + "cell_type": "code", + "execution_count": 138, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0 0 0 0 0 1 1 0 1 2 0 3 1 1 0 0 0 0 0 0]\n" + ] + } + ], + "source": [ + "part = np.squeeze(cut_tree(hier, n_clusters=4)) # Cut the hierarchy\n", + "# Each entry of the vector part is a parcel, and codes for the number of the network of this parcel\n", + "print(part) # e.g. parcel #7 is in cluster 5. What is the cluster of parcel number 10?" + ] + }, + { + "cell_type": "code", + "execution_count": 380, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Run same with hippocampus\n", + "## Hippocampus\n", + "mask_file = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=15\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None, standardize=False, \n", + " detrend=False, verbose=0).fit()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Lets try another thing - Using RSA for the same scan. \n", + "- Hypothesis here will say Ketamine will be fatster to recover, hence lower correlation in trauma" + ] + }, + { + "cell_type": "code", + "execution_count": 398, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 0 subject\n", + " Running the 1 subject\n", + " Running the 2 subject\n", + " Running the 3 subject\n", + " Running the 4 subject\n", + " Running the 5 subject\n", + " Running the 6 subject\n", + " Running the 7 subject\n", + " Running the 8 subject\n", + " Running the 9 subject\n", + " Running the 10 subject\n", + " Running the 11 subject\n", + " Running the 12 subject\n", + " Running the 13 subject\n", + " Running the 14 subject\n", + " Running the 15 subject\n", + " Running the 16 subject\n", + " Running the 17 subject\n", + " Running the 18 subject\n", + " Running the 19 subject\n", + " Running the 20 subject\n" + ] + } + ], + "source": [ + "cor_OneSes1 = []\n", + "cor_OneSes2 = []\n", + "for i, sub in enumerate(subject_list):\n", + " print (f' Running the {i} subject')\n", + " beta1Arr = []\n", + " beta2Arr = []\n", + " conditions = []\n", + " for cond in cond_list:\n", + " cor, beta1, beta2 = getCorr(sub, cond)\n", + " corTot.append(cor)\n", + " conditions.append(cond)\n", + " beta1Arr.append(beta1[0])\n", + " beta2Arr.append(beta2[0])\n", + " corMat1 = np.corrcoef(beta1Arr)\n", + " corMat2 = np.corrcoef(beta2Arr)\n", + " cor_OneSes2.append(corMat2)\n", + " cor_OneSes1.append(corMat1)" + ] + }, + { + "cell_type": "code", + "execution_count": 399, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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yW+8s7KdlyPAyjXh6F17UBcBTt9hZVV73CX/lvvn19k839d8O445WRlOTHVlxw9Nnc8Fr95j2BcttHZSuFv/9tHYvN20dPX60zuCA3c6NLb6vF13h7RRLi8rwoj0aW5tc35ERO6xm2Mm4AtDqRLA01fuZbRa12pFAuVHbLy2qafGiox+VUY2hcFlIrbWI3Cgie0RkS8FrC0Vkg4j8Ivlrf/KCeY/XKQfBrFIj2R5VRpavk6+TV+Mv5CrgblVdA9zNNNmxgyAIZhuRmkyPaiO1RonK/lQtw4uBm5LnNwHvrnC9giAIymcej5inY6mq7gJI/nZbBxZqZWx79FslFhcEQVACc3RL9lGvUaFWxglrfdH6IAiCilJbm+1RZZQalbFbRJar6i4RWQ5kWv1p72w1bY2Nno6G//0x7EjzDw75K8OOdEEqff3jps3LNJKmd+FFXjzyNw+7vjp1NaCANK2MiYnSGuOOh5bwhlPtthhucqIN/IAA2h2dlJMbnewzQGfnEtO2eKmtHQHQ32vfVAd22yIcHd2L3PNOjNnt1LV0oet74IBdp5YWXzekt9++ts2Nvu+Snp+atnNOtev8wmK/LUR8LY2KjBurcDSchVJrfQdwWfL8MgryWwXHHl6nHASzyhydY04dMYvILcBbgcUi0kN+C/YXgdtE5MPkxYx+72hWMgiCoCTm6Ig5tWNW1UsN0/kVrksQBEFlCa2MIAiCKiO0MoIgCKqMmuqLuMiCaJqAQgX5wUPjZmFvbN5k+rVv2uCe99BDj5k2+eifub4v1rzStO3s93Uc9vba32tbn7N1GrqX+BoBzU2l612svPAU07b2o6e7vgtWv8K0NZ5mZ2QBuGrbr2QVO0L/IVs/YtGSNve8TU5mjuOW++24Z78TKZKSXaPGyWzjRRDVpPx0bm2xfdtafd/Hn7S1ZmpSFrAmnfCj8XE/XKfOydji3Y9NTf647+QTfW2QD51H2fMQIz/+WqYOrmn9R6pqzqNUrYxrROQpEXlURL4rIp1Ht5pBNeN1ykEwq4hke1QZpWplbABOV9W1wDPAZypcryAIgvKZrzv/ptPKUNW7VPXw78SNgJ/NMQiCYDaYxyPmND4E/MgyFmpl/Pj2r1aguCAIgmxobW2mR7VRVlSGiFxNPhHrzdYxqno9SZJWb/EvCIKg4lThNEUWSu6YReQy4ELgfM0Y2vH0844exsn2qv/pa51UIUCns+Isz/vaEhOr7SbQNv8nzsiYLfQw4QhTpGlWeK2Z5utFXjz61S2mDeBV77EjSToG7ciK/8aD/NfWa037+JgdATHq2MCPyhgd82+7kWH73HV1/rWtd7Lm9Pfa92NaPzAxYetSHDzkv58FC2xtkMFB/zMyOmLb+3v9rCsdi2yNm+FBO4WJTvpaJsM5PyqjIhxLHbOIrAc+DZyrqkOVrVIw1/A65SCYTbQK54+zkCVc7hbg58ApItKT6GP8DdAObBCRTSJy3VGuZxAEQfHM0aiMUrUybjgKdQmCIKgsc3TEHFuygyCYt1RjxEUWomMOgmD+UoXTFFmY0Y553357BbfnoL1Cu2T5Kve8rzzJjkSQx+53fbtaHD2Mpa4rox12820ct2+IwUE/EmHc8U3LMuLpXXhRFwBP3vwL03bqpXa5V/IevnDi35t2KUOI3Mswk8uVHn1Z62hhALS22COt3kP2fUxKUo5czj6gr8+/Pqedat+rz+/wC65vtO9VSfm572llNDrnHR316zQwmBJiVIFtFjpHO+aStDIKbFeKiIrI4qNTvWAu4HXKQTCrVHDnn4isF5GnRWSriFw1jf2tItKbBERsEpHPZvWdSpYR89fJR2F8Y0olVgJvJ5/BJAiCoOqo1IhZRGqBr5Dv83qAB0TkDlV9YsqhP1PVC0v0PUJJWhkJfwV8CojdfEEQVCc1tdke6awDtqrqNlUdBW4FLs5Yi6J9S/o6EZGLgBdVdXOGY49oZWy6N6LsgiCYOVQk06Own0oel0851XHAjoL/e5LXpvJrIrJZRH4kIoe3M2f1PULRi38i0gJcDbwjy/GFWhlXfXUkRtdBEMwcGacyCvsp60zTuU35/2Hglao6ICIXAN8D1mT0fRmlRGWcCKwGNieruSuAh0Vknaq+5Dn2946Ytn0H7X31L3V2uRVasOgk01azxdRXAqBjwl45XjTqawjoSnvRIDey0rTtGRmnpcXOvtHU5GsMeHiZRjy9C/AjL566Zatp+x3ewreu/BfT7kVleFoL4GuOLF7Y7vp6kRcNjhZGGmkZP8ZyduYUsK/7UL8flbFsoX2v9g/62VwOTDcZmZH6OkevBPu9pgXjzMTeDy0/CcpheoDCD/UKYOfLylLtK3h+p4j8bRIYkeo7laI7ZlV9DOg+/L+IbAfOUtV9xZ7rWMXrlOciXqd8rOF3ysFMU8FwuQeANSKyGngRuAT4g8IDRGQZsFtVVUTWkZ8q3g8cSvOdSmrHnGhlvBVYLCI9wOdUNSaLgyCofirUMavquIh8AvgJUAvcqKqPi8jHEvt1wO8CHxeRcWAYuCRR3pzW1yuvVK2MQvuq9LcVBEEw80xWMEu2qt4J3DnltesKnv8N+dDiTL4esSU7CIL5S4gYBUEQVBdzdUt2dMxBEMxbKhiVMaNIWlYoEbmRfAqpPap6esHrfwx8gnzOvx+q6qfSCvsft9g5/+pSRGU8hp0UQn19fjjW8uUtpu2UV/ptc8pCOzpw1fN2pMJQ94nueXc1nWDbBv3QwR/ea6cQyo34EQO5Ibutck5qoj+49jz3vKdeaocztq9c4vouOOM1pu2z+//Q9fXSVh3Y0+/6TjghcavW2NIwnkhR3m5fA08QCOBzr/9X01b7xIOu79A2Wzmh74Xdru933/0D07Z3rx3il9a31Df487//8wMNZfeqex+/L9PeiSWvfmNV9eAlaWWIyNvIbylcq6o5Eek2fIMgCGaP+TrHrKr3isiqKS9/HPiiquaSY/ZUvmpBEATlMSlzUyi/1Jnxk4G3iMh9IvJTEXmDdWDhHvQH7/5qicUFQRAUj0pNpke1UeriXx3QBZwNvAG4TURO0GkmlQr3oHtzzEEQBJVmri7+ldox9wC3Jx3x/SIyCSwG9lasZkEQBGVSjaPhLJTaMX8POA+4R0ROJq/MkqqVMdBvr+zX1toNmJaixhO6SaPRWfgdGPG/bQ/kOkzb6t22RklznS9StGC5HXkx3GSn4ALoP2S38bgTpQC+2JBn86IuwBdAOuEiP2qmvs2Omtk93Ov6NjTVm7axnN1OAC3tzaZtaMj2HUu5Vz3SxJGG2+xcZ21r7PRqAK0Ntj5LbbN/Py7qtK/9/v22rfegLVoGMDLsXwPwI3ayoPN18W86rQzgRuDGJN3UKHDZdNMYQRAEs8lcXfwrRyvjvRWuSxAEQUU51uaYgyAIqp5jbY45CIKg6okRcxAEQZUxb0fM02lliMgZwHVAE3mtjD9U1fvTztXXa++rX9Jtr76Pj/nfek1t9opzv1MmwOCQvRI+qf5FXdBsr9wPPv0L09Yy7q9Gd7UssI12IAgAi5asMm2edkQaXgqoNL0LL/Ji2x22hgNAraOn0L9kwPWtq7dv76G+Idd3ctJey/aigLzoIgB1zlufopWxu8FOVza6xI/WWejYmpw6ASxeYOt7vNhq17m/32+LsdGjn+1lro6Ys3ydfB1YP+W1LwGfV9UzgM8m/wdBEFQVk9RkelQbpWplKHB4WNdBSmLBIAiC2UCrsNPNQqm1/iRwjYjsAK4FPmMdWKiV8cTGr5dYXBAEQfEokulRbZTaMX8cuEJVVwJXAGZyVlW9XlXPUtWzTjv7AyUWFwRBUDzHWsd8GXB78vwfgXWVqU4QBEHlmKsdc6nhcjuBc4F7yGtm2CEIhYXV298D9Q22LS0LSY2T/SRNZ2NoyF4ZHk7RytjVbEeD7H+6x3as8b8PW7uXm7b2ejsSBKCp2c6O0tTsb0/1Fue9SIQFJ9pZRsDXu/CiLgB+8e3nTNvkR31tibHJNC0Gm9o6u16TTluk6ZE0NNgfOUnRdejpt2Mr+hpbXd+ck6lnaa2tKQLQ3TJo2hZ12WFCBw/63UtaW1WCaux0s1CqVsZHgS+LSB0wAlx+NCsZBEFQCmkhr9VKOVoZr69wXYIgCCrKvB0xB0EQzFWiYw6CIKgyVKNjDoIgqCom5+iIWdL07UVkJfANYBkwCVyvql8WkYXAPwCrgO3A76vqQe9cX/1nzMJGnQX0pQv91feRUbvxn3jGj+ioq7N9F7T731ue72Ob7YQuTc3+KnhHlx15cfKJfraJnPN2R8f8a53L2Xbvve7c6Weq2L3TzjTSf8jXu5h0snp89Kvvcn1Xvt2OblnxplNc3+Y3vdm0/aD5PaYtLWGGZz+Yoi1xsNdui45233fcCYDIjfr3xW+/2g66Wvb8Rvu8Dz/gnve5DZtc+xl3/azsXvXhZ/ZnSuBx5smLqqoHz7JkOQ78Z1V9Ffnkq38kIqcBVwF3q+oa4O7k/yAIgqphrsYxp3bMqrpLVR9OnvcDTwLHARcDNyWH3QS8+2hVMgiCoBRUJdOj2igqyC8RM3odcB+wVFV3Qb7zBroNnyNaGff+8PryahsEQVAEc3XEnHnxT0TagO8An1TVvrRdSodR1euB68GfYw6CIKg01TgazkKmEbOI1JPvlG9W1cMaGbtFZHliXw7sOTpVDIIgKI3JjI9qI8uWbCGvHvekqv5lgekO8mJGX0z+fj/tXB2tdhP0DdnfEQPD/vfHwJA9ED+wz89UsXCxrSGQFsXgaXQM9NrlDthBCgAMDthZVzo7/WwhuVG7jUeGS9cmqPX0SNL0IZrsKBQvywj4ehde1AXAjg27TFtTh5/xY8XK40xb/aucLCR1/j3TWGu31fiErb0C0D9oX4NaX3KESaf3SbkE1E06oT45OyLHy9YC0Hm8l1elMszbLdnAOcD7gMdE5HB8y38h3yHfJiIfBl4Afu/oVDEIgqA05upURhatjH8Dc3b8/MpWJwiCoHJUcmFPRNYDXwZqga+p6hen2N8DfDr5dwD4uKpuTmzbgX5gAhhX1bO8smLnXxAE85aU2ZTMiEgt8BXg7UAP8ICI3KGqTxQc9hxwrqoeFJF3kg96eGOB/W2qau88KyA65iAI5i0VHDGvA7aq6jYAEbmV/F6OIx2zqv57wfEbgRWlFjY3Z8aDIAgykHWDSeF+i+QxVWP+OGBHwf89yWsWHwZ+VFgV4C4ReWiac/8KWaIyLK2Ma4B3AaPAs8AHVfWQd65JZyJ+zNHKGB7xf4/s3Wc71zf6y9WNjfZ3U1qodkuTfcDB3QdM28iAnRECoLHF1spYvLTd9W1wMoJ4ehfgR140OBlmtm/td887lrOvz1CfHzXjkaZ34UVeeJlRADpPWGbahk+026K9yddmaa23I24mUhaqDjbaURueRkrebn+GRkb8gLG9YrfFgmWrTVvTpB+t07346EdlpLXpYQr3WxhMd6JpG1VE3ka+Yy4UXDlHVXeKSDewQUSeUtV7rcLK0crYAJyuqmuBZ3AyZQdBEMwGFdyS3QOsLPh/BfkUey9DRNYCXwMuVtX9v6yH7kz+7gG+S0qe1JK1MlT1LlU9nDCvrPmUIAiCo4FqtkcGHgDWiMhqEWkALiG/l+MIInI8+STV71PVZwpebxWR9sPPgXcAW7zCytHKKORDvHw+pdDnyNzN3d8PrYwgCGaOSmllJIPQTwA/IT84vU1VHxeRj4nIx5LDPgssAv5WRDaJyIPJ60uBfxORzcD9wA9V9cdeeSVrZRS8fjX56Y6bjTd0ZO7m1n/P+N0UBEFQASoVLgegqncCd0557bqC5x8BPjKN3zbgtcWUlaljNrQyEJHLgAuB8zVNcT8IgmCGmZycpzv/LK2MZBfMp8kHVGdaWt/r5DfJ5eyV4bQMCxMTtr221p+tGXW0JTwtDIDBYbvcBQs7TNukl04CyA0Nm7b+Xj9byJJlbaat3omsAGhtSRFcMJhwsowAtLTbUSaTKUOa2jq7Tl6WEfD1LryoC4AHvvRz09ZzpldnX+9ieYfdVgcH/cw2fQO2b1oEkRd5cfCgf0/lJux6DbUsNm0TK/22kBWvcu22ik125mpqqXK0Mv4aaHGvzzYAABUCSURBVCQf+gGwUVU/Nv0pgiAIZp65+ju+HK2MO6d5LQiCoGqYtyJGQRAEc5VKLv7NJNExB0Ewb5m3UxlBEARzlaxbsquNkrUyCuxXAtcAS9Ik7S465RnT9tzI8aZteMyv5tad9urv5k2+joPH0JAj4AEMN9ur1a0d9ppyTZ0fHeHlUzyw209/suKVC0xbf6//fnoP2YIL407kxao19so8+O04MeFHdEw69h80v8f19TKNeHoX4EdevPoSO5rg7Kvf4p635eQTTdvEiae7vv978gLT1tzkvx9PS6Ory8/mcstP7Cih7qVrTduCdr9OK5b41/63XGs25vOI+bBWxsPJtsKHRGSDqj6RdNpvJ5/BJAiCoKqYqx1zyVoZifmvgE9hqCwFQRDMJpMqmR7VRslaGSJyEfDi4dQpjs8RrYxv3foPJVc0CIKgWCooYjSjlKSVQX5642ryKkkuhVoZz299ugqbIAiC+UrKEkbVkmnEPI1WxonAamBzkmRwBfCwiKOoHQRBMMNUUI95RilJK0NVHwO6C47ZDpyVFpWxeM/jpm18mR3hsDu3xK3j5KStD7G3Z79pAxhZaGcEmRgbN20Ay463MzDs32VnMPG0MNLsHd2LXN8aJ6JD0r6GHQmPsZzdFrmUKJOxUfvEaVom42O2b5o+RH2d/QMtLdOIp3nhRV5s/MLP3LOe9Ns7TNvSM190ffsX2z9Qa2t9nY3xMU9Pxm/IkWE7qsaL1hkb96/tTISyVeM0RRayjJgPa2Wcl2iMbhIRO24nCIKgSpjUbI9qoxytjMJjVlWqQkEQBJViro6YY+dfEATzluiYgyAIqoy5GpURHXMQBPOWyfnaMXtaGSLyx+QTFI6TTzD4Ke9ctT3bTNuSJic6osOvZke77VuTsupfV29nyEiLGGhocHydzBuastrgZThJixRpbbHrPOFkogDI5bzMKnaUQs6J2EgjrS0aGuxrnxaV0Vhrv5/W+pzr62Ua8fQuvKgLgK23bzdtzV2tru/kQrutxpyoi7zdfj9p4WJNjiZMU5N9nzc2+OetkaM/zzCfpzKm1cogn/n1YmCtquZEpNs9SxAEwQwzbztmVd0F7Eqe94vIYa2MjwJfVNVcYttzNCsaBEFQLNUYCpeFkrUygJOBt4jIfSLyUxF5g+FzRCvjhn/eWG59gyAIMqOqmR7VRklaGaraJyJ1QBdwNvAG4DYROUGnvMtCrYyR266tvhYIgmDeMuEnpK9aStXKAOgBbtc895NfGPQV04MgCGaQeasuN51WRsL3gPOAe0TkZPLL9q5WxmhPj2lraLMzbyxq8Ferl3Xa2kmDvQOub3Nbs2nzMomAH8XgRYO0ddnvFaCx1c4o0bXU1ucAaGu163zwkH8H9vXZkQpD/bata7F/fTw9hfpG/xb0rsHB/hSdjQk7kiRNp+HgoB2J4GUaSdO78CIvHrvB1pIBGFvr6Yb4ETc1jh5Ga6t/DQ7st7Vbep2sOCMj/vWpSalzJZirc8xZpjIOa2U8JiKbktf+C3AjcKOIbAFGgcumTmMEQRDMJnO1RypXK+O9la1OEARB5UiLk/8l1SX9GTv/giCYt8SW7CAIgipjco5OMkfHHATBvGWuzjFL2nqdpZUhImcA1wFN5Ldt/2ESNmdy7e3219dLu0dMv7qUDBleBoYPn2tHggB073vCtNU89Yjre2jTk6Zt46U3m7atvpwCIyP2768DB+x2Al8/YsGCRtd3Wbe9Sr5soR0R8Ov82D3vcNtS07a7YaXr29NvR6E8ts3WaQCoq7Mbo7nRn1PsG7CvgTcK6+/3dUM83zEnWwvAeX9ypmk74w/PcH2bFnWYtpaTVru+nx+8wrQtWGDfM2laJgMDflt94UMpFykDX7h1IlPXfPUlKWlcZphytDK+BHxeVX+UZDT5EvDWo1fVIAiC4pico0PmcrQyFDgckNsB7DxalQyCICgFnaOLf+VoZXwSuEZEdgDXAp+pdOWCIAjKYWJCMz2yICLrReRpEdkqIldNYxcR+evE/qiInJnVdyqZO+apWhnAx4ErVHUlcAX53YHT+R0RMdp41/VZiwuCICibSokYiUgt8BXgncBpwKUictqUw94JrEkelwN/V4TvyyhHK+My4PDzfwTWTeerqter6lmqetbZ77g8S3FBEAQVoYJZstcBW1V1m6qOAreS16Mv5GLgG4l+0EagU0SWZ/R9GeVoZewEzgXuIa+Z8Yu0cy3qsr8HcqN2xEBTk//9MTpqTyQ9fuiVrm/vQnu1+qTT/FX/rhq7Xg11TgaMZv+8w8P2ndLSkpaFxF7pHhy0dQ0Ant9hRwX0D9q6E7/R/6B73rY1trbE6BJbFwSgr9HWluhob3N9a51mzo26rm5EQbNzP9bW+tfHyzSSpnfhRV5s+ttNpg3ghIuON20LB20tDIDaU+zG8CJfvGw6AG2tRc2klkTWnX8icjn5Ue5hrk+UMQ9zHFAYT9UDvHHKaaY75riMvi+jHK2MjwJfTuQ/R3j5mwqCIJh1sgZlFMoTG0z3DTT17NYxWXxfRrlaGa9P8w+CIJgtKrjzrwcoDLpfwa9GolnHNGTwfRlH/7dEEATBLDE5oZkeGXgAWCMiq0WkAbgEuGPKMXcA70+iM84GepNw4yy+LyO2ZAdBMG+p1AYTVR0XkU8APwFqgRtV9XER+Vhivw64E7gA2AoMAR/0fL3yomMOgmDeUkmJeFW9k3znW/jadQXPFfijrL4eWaIymoB7gcbk+G+r6udEZCHwD8AqYDvw+6p60DvX3gN2pIIXWeEEPwBQ76wMv3TQj4BoabBX9g91rnJ9l3TvMm1LW+3MKeNL2t3ztjbbq/O9/f6N9vwLduTF6IgfleFlEzlwwPYb2vGCe97WBjuiw8/HArnlLaZt04QflTHp7PrKjfrt6OmVeBEd407UBcDYmHOfp8g1eHoXXtQFwLY77GtU89spH7BTbNPwsB3Jk7ZxYyaiMuaqulyWlskB56nqa4EzgPXJ/MlVwN2quga4O/k/CIKgapi3Of+S4fnh4V998lDyAdJvTV6/iXw886crXsMgCIISmZijSvlZd/7VJjHMe4ANqnofsDRZcTwsdNR99KoZBEFQPDqpmR7VRqaOWVUnVPUM8vF360TE3so1hUKtjPs2hFZGEAQzx1ztmIuKylDVQyJyD7Ae2C0iy1V1V7IffI/hc2RHzZe+U4UtEATBvGWu9jhZojKWAGNJp9wM/DrwF+QDpC8Dvpj8/X7audL2zlukre72D9grw3v35Vzfutpm09aybIXr295tZ35Yqc+ZtvpO/7xN9fbqe3Ojr6fw7DZ7Tq2/19dEkLSUEwZ9L+x27bXNjg5KyidnqaM9kRv1M2/UO3e3F3UBcPCgnSmmq8vW9/Cy6QCoOtoSrf7H0cs0kqZ34UVebL19u+u77P12VE05TPgJWypCNY6Gs5BlxLwcuCmRrqsBblPVfxKRnwO3iciHgReA3zuK9QyCICiaSsYxzyRZojIeJS+OP/X1/cD5R6NSQRAElWCuRmXEzr8gCOYt83kqIwiCYE4SHXMQBEGVMVezZEva5LijlXEN8C5gFHgW+KCqHvLOddVXR0pqpZEROysHwPCgLV7Q0uavKHd22hEDY+N+dQcH7HL/9DdsbQI15a3ziKOhveTpn7q+n9n+PtM2Pu7Pt9XV2Sv39XW25sjSZX4WkkWd9vtdvMC/tt0tg7atzo8GqZu0r89eWeb65ibsaJBbfmK308iwr0fS5OigpM2HtrXb92paNIjHsqX+Z+SEd59q2l59mW1b8gZ/u0PuTe907Qtf8+bS31TCZZ99KVOfc9N/X1Z2WZWkHK2MDcDpqroWeIbIkh0EQZVRqWSsM03JWhmqelfBYRuB36189YIgCEpnIuVXYrVSjlZGIR8CflTpygVBEJTDXB0xl62VISJXA+PAzdP5FmplbLr3hkrUOQiCIBM6OZnpUW2Uo5WxRUQuAy4Ezlfja6dQK6PUxb8gCIJSmKtC+SVrZYjIevL6y+eq6lCWwpYvs1eV+xy9i7SfGrkRe+Df32trHgDU1tq+DQ1+9pNWJ+Jjc//Jpm1fn9/sXoaMc071c344Eh1u9ApAo5PBZBQ7emLb1hztHXZkxv799oL3iyn6EIu6bN2QD9SlyLPk7Gu/YJmvszHUsti0dS9da9rSIl+amux7qrfXj+hoa7Pbqs7J4gN+ppE0vMiLx296yrSdmKLNsmphSv6a17zZt2egGqcpslCOVsZW8iF0GxLxm42q+rGjV9WgWvE65SCYTSbn6OJfOVoZJx2VGgVBEFSISZ2nHXMQBMFcJbZkB0EQVBnRMQdBEFQZ83nxr2Is6rRtNTX2anVjgx9u7WXeOLjfDxgZG7VXq9OiMuqdlfCtPbbv4JC/Qj46as+LvbB4kevb1OREt0zaUTH5cm3fGmfRv793hLYF9rl7nWwg/f3+tT140L5FcwMPuL7eaKlp0r8GEyvtiJsF7Xadx8b999PYYDfkiBNdBOAlmEnLDpSWBcjD07zwIi+e/d7z7nm7Ttjk2psqkHpjsgpjlLOQusFERJpE5H4R2Swij4vI56fYrxQRFRE7viiY13idchDMJpMTE5ke1UaWEfNhEaMBEakH/k1EfqSqG0VkJfB28qmlgiAIqoq5OsecOmLWPL8iYpT8/1fApwr+D4IgqBp0UjM9qo2SRYxE5CLgRVXdnOJ7RCvjX+64vgJVDoIgyMakTmZ6VBuZFv9UdQI4Q0Q6ge+KyFrgauAdGXyPaGV882dzdIk0CII5STWOhrNQqojRxcBqYHMSEbECeFhE1qnqS5b/4LC9rCxiN+CqV/j1WulocDz0qP9tWOMsdXvaBOCvkj+7rd+0tbb6GSMWL7LtIv5Cxckn2tujh3P+1umBQbutvPcK0Ndva2l4WT3GRv0MJuNj9vt97mF/Vb/zeFuLoXuxr9MgK15l2lYssdtpQv2GqnHu8xqxs5sA9OzMmba2Vv/Hr2dPW/vyMo14ehdpURcP/uX9rv03/8KvVxaqUTkuCyWLGKlqd8Ex24GzVHXfUatpULV4nXIQzCbVGHGRhZJFjI5utYIgCMpn3sp+WiJGU45ZVakKBUEQVIp5O5URBEEwVzkmFv+CIAjmElqFoXBZiI45CIJ5y+T43Fz8y5xF9mg8gMtn2nc2ygzfuLbhW77vsfTItPPvKHL5LPjORpnhOzO+c62+4RtMy2x3zEEQBMEUomMOgiCoMma7Yy5H1ahU39koM3xnxneu1Td8g2mRZEI+CIIgqBJme8QcBEEQTCE65iAIgipjVjpmEVkvIk+LyFYRuaoIv5Ui8q8i8mSSf/BPSii7VkQeEZGihJhEpFNEvi0iTyXl/1oRvlck9d0iIreIiKm/KSI3isgeEdlS8NpCEdkgIr9I/nYV4XtNUudHReS7iaZ2Jt8Cm5nX0fITkT9OrvHjIvKlIup7hohsFJFNSYKFdYbvtPdClrZyfFPbKu0etNrK80trK6e+qW0lRs7OjO1k+WZpp8gVWg4zHTgN1ALPAicADcBm4LSMvsuBM5Pn7cAzWX0LzvGnwLeAfyrS7ybgI8nzBqAzo99xwHNAc/L/bcAHnOP/A3AmsKXgtS8BVyXPryIvu5rV9x1AXfL8L4rxTV5fCfwEeB5YnLHMtwH/DDQm/3cXUd+7gHcmzy8A7inmXsjSVo5valt596DXVk6ZqW3l+Ka2FSBAW/K8HrgPODtjO1m+WdppWt8s91Q8ZmeDyTpgq6puU9VR4FbywvupqOouVX04ed4PPEm+48uEiKwAfhP4WjEVFpEF5DuRG5KyR1X1UBGnqAOaRaQOaAF2Wgeq6r3AgSkvX0z+i4Hk77uz+qrqXap6WDB5I/mkBlnLhZS8jobfx4EvqmouOWZPEb4KLEied2C0lXMvpLaV5ZulrVLuQbOtHL/UtnJ8U9tK80yXszNLO03rm7GdrHIhcoWmMhsd83HAjoL/eyiicz2MiKwiL0d6XxFu/4v8DVGssskJwF7g75NpkK+JSGsWR1V9EbiWfCbxXUCvqt5VZPlLVXVXcr5dQHfK8RYfAn6U9WDJmNdxGk4G3iIi94nIT0XkDUX4fhK4RkR2kG+3z2So5yp+eS8U1VbOfZTaVoW+xbTVlDKLaqspvpnaSqbJ2UnGdjJ8CzHbaTrfMu6pY4rZ6Jiny71T1DeniLQB3wE+qap9GX0uBPao6kPFlJVQR/4n99+p6uuAQfI//7KU28UvU3G9AmgVkfeWUIeyEJGrgXHg5ozHt5DP6/jZEoqrA7rI/+z9M+A2kbTkVEf4OHCFqq4EriD5leLUs+h7Ic03S1sV+ibHZmqracrM3FbT+GZqK1WdUNUzyI9s14nI6Wn1zOKb1k7T+B7OFVrKPXVMMRsdcw/5OabDrMD5aT8VEaknf3PerKq3F1HuOcBFkk+DdStwnoh8M6NvD9BTMFr4NvmOOgu/DjynqntVdQy4HXhT9moDsFtElgMkf6edGrAQkcuAC4H3qGrWL8ET+WVex+38Mq/jsgy+PcDtyc/Z+8n/Qsm6yHMZ+TYC+EfyU1/TYtwLmdrKuo+ytNU0vpnayigzU1sZvpnbCvI5O4F7gPUUeU9N8S3qnirwLcwVup3i7qljitnomB8A1ojIahFpAC4B7sjimIwkbgCeVNW/LKZQVf2Mqq7QfLaVS4B/UdVMI1fNJ5jdISKnJC+dDzyRsegXgLNFpCWp//nk5wiL4Q7yH0KSv9/P6igi64FPAxep6lBWP1V9TFW7VXVV0mY95BegzGS7BXwPOC8p/2Tyi6VZ80HuBM5Nnp8H/GK6g5x7IbWtLN8sbTWdb5a2cuqb2laOb2pbiciSw1ET8sucnU9lbKdpfTO203S+j5RxTx1b6CysOJJfQX6GfHTG1UX4vZn8tMejwKbkcUEJ5b+V4qMyzgAeTMr+HtBVhO/nyX8YtgD/l2QF3jj2FvJz0WPkb9wPA4uAu8l/8O4GFhbhu5X8nP7h9rouq+8U+3amj8qYrswG4JvJ+30YOK+I+r4ZeIh8tM59wOuLuReytJXjm9pWWe7B6drKKTO1rRzf1LYC1gKPJL5bgM8mr2dpJ8s3SztN65vlnoqHxpbsIAiCaiN2/gVBEFQZ0TEHQRBUGdExB0EQVBnRMQdBEFQZ0TEHQRBUGdExB0EQVBnRMQdBEFQZ/x+Qa+Wd6e2BnAAAAABJRU5ErkJggg==\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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CIKgvDRoGmIV4PD4IguYlRt5BEASNRyxY1onxCfsWprXFjuzoydkr/wBjaq/CT0z4q/AFR+Kirc3/4r2MN54+iRdNArBu+XrTlhaT2tliR+a0ih9VsL9gX8+EE9GzbyzH2IQ9wpko2NlWhvf7I6P8PDviYIb4mXT2j9ll9jLlADy3csC0LTnRjvjZtdXPpDM2Yuvh7NzlR6osXmi384626heNR8b972BkzdOmrX2vk298hh3tAzCjfbprr0e0SaOGAWYh9cpE5EYR2SIiK0o+6xWRe0XkmeSv/y0FTY3XcQfBlNIi2bYGJMt/3bcpJtMs5SrgPlVdBtxHmazxQRAEU41IS6atEUktdZIkc8ekjy8Gbkpe3wS8u87lCoIgqJ0jfORdjnmquhkg+Ws+GhbaJkEQTBnxeHz1lGZl/s7P8FeJgiAI6klEm7yCF0VkvqpuFpH5wJYsToPDdt+9cXCaacvPtFfoAUYL9mVoys/F3iE7OqOtw46SABgasqMDvIw3afokXkTJs3e+4Pr2/Xc7O8me8W7Xd3DUzqWxazglK8o2O9ohn7evZ3zcj5KY0WVfz/ReX6tlj6NfsnOnr5czvHvItHU67aK13W8zuVa7Hof3+NFAu3bbvu2t/uhxv3to33fbk+tM29xW+3rb2v3cLLlxOyNR3WjQUXUWqr2y5cClyetLgX+qT3GCRsTruINgSmniOe/UkbeIfB84B5gjIgMUH4e/BrhVRC6jKFD13oNZyCAIgqpo4pF3auetqu8zTH4W3SAIgqkmtE2CIAgakNA2CYIgaEBaItqkLvzx4kdMW8+K+03b8Oo17nGHN9kZVd546W2ub1fKirjHrA47YuHuockPpf4OL9sN+PokXjQJwJaTzjBtJ3zgeNf3Nefa5dp92jttxz64bd0ppnloj72g+dvNfsTI8F77+1lyhj+qmt5ln/e4Y/3vffOGY+wy7bGjJLZu2Ooed2zEDvs44WQ7axDAG46328V4wa+L7la7zIMjfrapHVffbNr252wtl5z4majStHZmuNaMNPHIu1ptk2tFZLWIPCEid4jIzINbzOBwxuu4g2BKEcm2NSDVapvcC5ykqicDa4DP1blcQRAEtdPET1hWpW2iqveo6oEnZx4E/KdOgiAIpoIjfOSdxoeBH1nGUm2T79x6ex1OFwRBkA3N5TJtjUhNC5YicjXF5MPmikaptsmWp34d2iZBEBw6GnRKJAtVd94icilwIXCeapqCSJEtbfbsyvS+ftPWnXJb0zFvrm1r9Ys2rc3WJxka8XUqWqS6x8K7c36EhbcKn6ZP4kWUPPX3dkYUgNYuO5PO7KMXmrbLOlbw7dEPmHavdezf52ePGRqyR0WzZLJS8cvpbrPX0ScKKW2qy85as2/Y/n7aOv3MTZ592TF+mUbG7X9XLyMUAE5TlhS9OHWyKPXoTtPWNuZnFcpN+NEmsDTFnoHovF+OiJwPfBY4W1X9nihoeryOOwimEm3Q+ewsZAkV/D7w78DxIjKQ6Jn8T2A6cK+IPCYi1x3kcgZBEFROHaNNROR8EXlaRNaKyCuyh4nIOSKyO+kTHxORL2T1rYZqtU2+VY+TB0EQHFTqNPIWkRzwdeDtwADwsIgsV9WnJu36b6p6YZW+FdG8E0JBEBzx1DHa5HRgraquU9VR4BaK6SAPtq9JdN5BEDQvGadNSkOak+3ySUfqBzaUvB9IPpvM74vI4yLyIxE5sULfijik2iart5upLulaeLpp65njJ+rpGLa1TU6d4UdYrB9bZNp27vE1H8DWGRkbd7LHqF/t+wt2RIKX7QZ8fRIvmgTg8f/9hGl7reP3Lpbzw3f9wLRPpIZC2OTz9vjiuf32dwewa69dzyNj/u10/8Ie07b++V2mbdHx893jtrXZo7zWnF9PuRY7umla3o/aaWuxs1G15X0NkqExu920iH29uZTj5vJ+tNYc15oNzTifXRrSbFCuwUz+wh4FjlHVPSJyAXAnsCyjb8VUpW1SYvu0iKiI1KOegwbF67iDYEqp3xOWA0BpvOwCYFPpDqo6qKp7ktd3Aa1J35jqWw3VapsgIgspTsCvr7UQQRAEBwOVlkxbBh4GlonIEhFpAy6hmA7yJUTkKJHiL4GInE6xf92exbcaskSbPCAii8uYvgp8hshfGQTB4Uqd9LxVdVxErgDuBnLAjaq6UkQ+ltivA94DfFxExoF9wCXJA4xlfWstU7UP6VwEbFTVxyXlliOZ+L8c4PKrvsHb3z15HSAIguDgUM+HdJKpkLsmfXZdyev/SfEZmEy+tVJx5y0iXcDVwDuy7F+6EHDbQzWsXAVBEFRKPB7/Mo4FlgAHRt0LgEdF5HRV/a3n+MJm+1dwdtfRpq2lxV/B7509ZNqWPfr3ru/4699t2vbNsvU8AETs36IXXrRv1+7fPY+lR9mr/xOOlsSuYf8r8zLeePok4EeUeJEoC//38Wy5x47q6Zlm18WcPl+rpaPT9n30Wf+WeHzc/n7yKS1/4dH2Dqp+jpf++baQSN4pcj5ntwmA2R12Ox8v+Bc0ofaJ9435vhu22TovhYIf/eRJveyzk/sAcPIy354FLRvo0RxU3Hmr6pPASzF/IvI8cJqq2vF6wcvwOu5GxOu4jzS8jvtII0Wj65CQNVSwEalW2yQIguDwp4kz6VSrbVJqX1y30gRBENSRQmSPD4IgaECaWBI2Ou8gCJqWZp7zjs47CIKmpZmjTSQtg5mI3Egx3dkWVT2p5PM/A66gmMPyX1T1M2kn+97P7ZONT9iVvHuPX8YJR/9m6dG++M2CHltkqNUR8wFoFzvWaeNeOzXbhPqjgcH9dsTCugHXlY4Oux5zLWkPVNm2djtajL532KnXAE7/7BtN2/S3vtX1HZ73KtO2fKt9XIAJ56tPS9w36ug8FZzHFUZG/AO3tzvhsn4EIhd0/9S0TbSmhOztcBrOWv9hv7/p/oJpa2u1r6fVsQGkKbFecUHtcx5bVz6U6dmSuSee0XC9fJaR97cpPjX0nQMfiMhbKerRnqyqIyJiywUGQRBMFUfynLehbfJx4BpVHUn28TVbgyAIpoCCNG+0SbWz+ccBbxaRh0TkZyLyBmvHUpHzf13uyeUGQRDUlzqqCh52VLtgmQdmAWcCbwBuFZGlWmYCvVTbxJvzDoIgqDfNvGBZbec9ANyedNa/EpECxcQXW+tWsiAIghpp1FF1FqrtvO8EzgXuF5HjgDYgVdtk1EkN9uI2OzRg08Zh97gzZ9kr7Z3H+NEmM/K7TVuL+r7DOs20LeyyNbo27p/nHnei4Agb5f2RxNAeu8xp9z1eujJPXOpCJ5oE4Fd/9UvTduJvd7i+vScsMW27X/X7rm93l11X0zr9yujosetx5x67LjqcaBKADidqZ9zPGsb6aSeZtoGhWa7vrLm274L5tg1g7y/sgu3YYUdkdXXVGonsVFZG6ikJe7iRWruJtsk5wBwRGQC+CNwI3JikRhsFLi03ZRIEQTCVNPOCZS3aJu+vc1mCIAjqSsx5B0EQNCAx5x0EQdCAxMg7CIKgATmiR97ltE1E5BTgOqCDorbJn6rqr9KO5a2mDw/bq9ZbN9sRIQAFZ61U8TUfJtSugv3qZ0V5fnCOaTu78BPTtqnTVxMY3m83uPFxPwLmt5v3mrb9+xzBjhS8dGVp+iReRMnKm1a7vksvsq/nhTY/CmnpErvMaVleejrtutq914k2afPX7TvbnKiq7f7i2uptdntbvc5vF12ddmTU4v7fc31H99saPpvX7zRtndP8Sh4bScsodVSKPZ1mHnln+Vn6NnD+pM++DHxJVU8BvpC8D4IgOKwo0JJpa0Sq1TZRoCd5PQPYVN9iBUEQ1I42aMechWqv7FPAtSKyAfgK8Dlrx1Jtkwd+GNomQRAcOhTJtDUi1XbeHweuVNWFwJXAt6wdVfV6VT1NVU97y4WXV3m6IAiCyonO+5VcCtyevP4BcHp9ihMEQVA/mrnzrjZUcBNwNnA/RY2TZ7I4zZ5uh5tov61jMDzs6zb09toRJcP2QjkAO9rt9CWjE371bBu07bkX7OCb487wtU3yTvaYGV1dru/wXrsuhob8aIZ83v4t7+i0fb1sN+Drk3jRJADrlq+3j/seP5Jozkzb5kV9AEwU7Lpoy9sRJY48DADjBbujaPODm9g/apdpdMyP3PCy2gw50TMAixZ59dxrWto6/OPu21t99FNWGrVjzkK12iYfBb4mInlgPxDzIUEQHHYUUlIONjK1aJu8vs5lCYIgqCtH9Mg7CIKgUYnOOwiCoAFRjc47CIKg4Sg08chb0nIoiMhC4DsUhQYKwPWq+jUR6QX+AVgMPA/8saraQgfAr1bvriphw0TKr+fecTtS5bYf73d9T3mtHZIwvcsv7jG9trbGs1ttLYnXHO0nHWoTexU+7VHeCWeBZpb4WWue27/ItD36rB1xMKvH/352D9n1+MJ6X5+kd7Z93td98ETX9+SP2hliZp/xWtf3X1/zedP25Fr7ep98dLN73HEnKuTCixa7votm7zNt3a1+WNW4Ez0zoX5UyPyOF01b/1N3m7aRVU+5x934S99+wh331dzzPrpme6Y+53XHzU49l4icD3wNyAE3qOo1k+z/Afhs8nYP8HFVfTyxPQ8MARPAuKqelvUaLLIsxY4Df66qr6aYcPgTInICcBVwn6ouA+5L3gdBEBw21CvOW0RywNeBdwInAO9L+sFSngPOVtWTgb8kSbxewltV9ZR6dNyQofNW1c2q+mjyeghYBfQDFwM3JbvdBLy7HgUKgiCoF6qSacvA6cBaVV2nqqPALRT7wJJz6S9LZh8eBBbU9WImUVEQZCJQdSrwEDBPVTdDsYMHyuqclmqb3HHrt2sqbBAEQSVkHXmX9lPJNvnZlX5gQ8n7geQzi8uAH72sKHCPiDxS5thVkXnBUkSmAf8IfEpVByVjVmZVvZ7k9qHaOe8gCIJqyBptUtpPGZQ7UNn+TETeSrHzflPJx2ep6iYR6QPuFZHVqvpApsIZZBp5i0grxY77ZlU9oGnyoojMT+zzgS21FCQIgqDeFDJuGRgAFpa8X0AZKWwRORm4AbhYVbcf+FxVNyV/twB3UAc9qCyPxwtF1cBVqvrXJablFAWqrkn+/lPasXaP2JEDu/fbwg7bd/u/Me12sAmz5/q+XkaVlpSftu17O02bd2OyYbev1bJ/zHbes88v1PQuuyl2tzliH8CuvXZzGB+3b5omHL0OgO4u2+5luwFfn8SLJgF44psrTNuJo74WyDnH32XaHi/8oWnr6/freHzM1vdpafFvTAd22v8/hYLdFsFvj62OVgvAJllsG0/4A9M0b64/5bu4b65rrwd1fDz+YWCZiCwBNgKXAH9SuoOILKIo2PcBVV1T8nk30KKqQ8nrdwB/UWuBskybnAV8AHhSRB5LPvs8xU77VhG5DFgPvLfWwgRBENSTej2ko6rjInIFcDfFUMEbVXWliHwssV9HMavYbOB/JdPKB0IC5wF3JJ/lge+p6o9rLVMWbZOfU36+B+C8WgsQBEFwsKjn4/Gqehdw16TPrit5/RHgI2X81gH+gwVVEE9YBkHQtKRJ9DYy0XkHQdC0hDBVEARBA3JEC1M52ibXAu8CRoFngQ+p6i7vWLv22REl23bZq8IDm3zdhtmz7XCTnun+Jc7stlf/J1JiiEbG7YaRcyIHBlMiRja+aPvu3OlrtRx3rB2RkBYVMuJEueSdakyRx2Fap72DF+0DfsabNH0SL6Jk5U2rXd+3vPbfTNtwlx1h0dXlp8PZZ8uT0JLSz2xxpGlE/C8h58iXdLT7J17zjN3mCifbWZJe0+dHwMx7/RzX7ueMykaaLlIjU4u2yb3ASclz/GtwMsgHQRBMBXV8PP6wo2ptE1W9R1UPDG0O+nP8QRAElaKabWtEatE2KeXDvPw5/lKflzQDfnKn9/RpEARBfYns8bxS26Tk86spTq3cXM6vVDPgBw82c+BOEASHG83c42TqvA1tE0TkUuBC4DxNy+oQBEFwiCmkLNI3MlVrmyRZJT5LUXx8b5aTPb7aXv3f9IIdqLLm16vc4x532qtN2zv/wF/R9lbph0f8DCNeVEjPNLvRPLV60LQBPLdywC7T7iHXd/8HjasAABcJSURBVPOGY0xbR5cjAgP0L+wxbQuPtpvKXj8Aho4eO2Kkp9POGgQw4WSA8bLdgK9P4kWTADzwn5ebtsL/+kvTdtLvpYTPYH8H+Zw//nl23R7TNrjD/xfMt9pteVqPHaEEsPLBp03b049PN20PnegppkLv7De49v/bl67JRDOnQatF2+RvgXaK8oYAD6rqxw5KKYMgCKqgmecDatE2sYc1QRAEhwGNGgaYhXjCMgiCpuWIX7AMgiBoRI7oaZMgCIJGpZkfj5e0CD9L26TE/mngWmCuqm7zjvXU2k3myZ7eMc/0e2KNLzIy5mR5WXi0H2HR5Sy0p/1qe1EWGzbaeiw7tjsCF0C+1Y6w6OzwtTOG99jn3Tc86vq25O3zLjxmhmnrneWPAbo77X+gtGxFbU6Wlxc2+e2i4JiHh/1MOgXnfvvNf2prqpz139/uHrfjlFNN27YlZ7i+D2w50bRt3WmaABgb8zIh+b5bt9oNvcVJ0SMp321Hh99uvvTB1pp73qzPlrz3zDRlmcOPLCPvA9omj4rIdOAREblXVZ9KOva3U8ykEwRBcFjRzNMmVWubJOavAp/ByKIcBEEwlRRUMm2NSNXaJiJyEbBRVR9P8XlJ2+TWW75bdUGDIAgqpZmFqarSNqE4lXI1xSzILqXaJt6cdxAEQb1Jm89vZDKNvMtomxwLLAEeF5HnKcrBPioiRx2sggZBEFRKM+t5V6VtoqpPAn0l+zwPnJYWbbJp72zTtnGb/TvywrPb3TJ6URKvO6HX9V1ny4iwa9CPSNi1w44a6Zlhh7GM7vf1PHZttY/b2u5Hm2zdsNW0taWkrVl0/HzT1j/fPu+u3f7wxsvU0tHm34x5sQJPPrrZ9e3rn2na0jLeeBolXkTJL/7rve5xf+99z5m2/vf4IjFP7zretA0P+20ql3OiQpyIEYDN6+1QluHdw/ZxUwI48q0p3c8H7Sw9WWnUKZEsZBl5H9A2OVdEHku2Cw5yuYIgCGqmoNm2RqQWbZPSfRbXq0BBEAT1oplH3vGEZRAETUt03kEQBA1IM0ebROcdBEHT4kkkNDpZok1MbRMR+TPgCopx3/+iqp/xjtWamzBt405gx+ioH/WRm3C0QFrtcybepkVTVjL2DNrRAd3TbE2ViZThwNiIfb25lBX6sRFbvyQt2qStza6LvJNUqN2JJgHocORlOtv8uhh30liNj/ntYnzM/u73+fIyeBlvPH0SL5oEYPX315q2+ee6wVqMOe2mvd3P+uRNH3g6LuBHjUxM2HVcGPX/9wqHYFh8pE+blNU2AeYBFwMnq+qIiPS5RwmCIDjEHNGdt6puBjYnr4dE5IC2yUeBa1R1JLFtOZgFDYIgqJRGDQPMQtXaJsBxwJtF5CER+ZmIlM0mWqpt8s8/uLHW8gZBEGRGVTNtjUhV2iaqOigieWAWcCbwBuBWEVmqk2qiVNvkZyv3NmYtBUHQkDhT8g1PtdomAAPA7VrkVxQXM+ccnGIGQRBUTj1VBUXkfBF5WkTWishVZewiIn+b2J8Qkddl9a2GqrRNEu4EzgXuF5HjKC7Pu8vlp+7/N9O26MRjTVt/39K0Ypo8u9mPhJg+zbbvG/FX8I9ZauumdHfbvn19/truzl22TsXwHj8bzgkn2xmJlh3j10Vrzm7F+Zwd2dHmhaIA487oZ9N237fNkSC58KLFrm9Li309aXlT8k5deBlv0vRJvIiSn370e65v//IvmrZcyjCsu9O2edcKUJiYZdqOPX6uaWtv9wvVN8f/7utBvea8RSQHfJ1i8pkB4GERWa6qT5Xs9k5gWbKdAXwDOCOjb8VkmTY5oG3ypIg8lnz2eeBG4EYRWQGMApdOnjIJgiCYSurYI50OrFXVdQAicgvFaLvSDvhi4DtJP/igiMwUkfnA4gy+FVOrtsn7azl5EATBwSTtWY0DiLRcDlxe8tH1yXrdAfqBDSXvByiOrknZpz+jb8XEE5ZBEDQtWZ8DKg2sMCg3gJ38y2Dtk8W3YqLzDoKgaUl7erQCBoCFJe8XAJsy7tOWwbdiKorzDoIgaCTqGG3yMLBMRJaISBtwCbB80j7LgQ8mUSdnAruThxyz+FZM1domInIKcB3QQfER+j9NQgZNHm4727T1jNur9L3dfoSFx+/32loSAL2bV5i2lm4/g8++lStN27V9XzVt8/ocsQ9g8ULbvmu3/5W94Xi7HkfGfd9ci32PObtjyLQtlifd466fdpJpW73Njy7dP2qPLxbN9gVKBnba2Yy27HBdeXbdHtM2ftqJps3LdgO+PokXTQKw+CL72G/4tD+F2rXAzlCYX7DI9d2+6BOmzcuS1DfDD7LubB1x7eBr8WShXguWqjouIlcAd1MURLpRVVeKyMcS+3XAXcAFwFpgL/Ahz7fWMtWibfJl4Euq+qMks86XgXNqLVAQBEG9KNQx3ERV76LYQZd+dl3JawXK/tKV862VWrRNFOhJdptBHeZwgiAI6okeyZKwpUzSNvkUcLeIfIXi3Pkb6124IAiCWpiYaN5HTzIvWE7WNgE+DlypqguBKyk+hVnO7yVhqh/eVnaXIAiCg8IRL0xlaJtcCnwyef0D4IZyvqXxk/c9ub8xaykIgoakmSVha9E22QScDdxPUePkmbRjjYzZWgYTrfaqdU+brxexeWi6aVtVWOb65nttTZUZ8/e6vkuOsSNVhu+3I2R6l/mr6B1Odpn2Vv9mabxg29Ma8rS8rakyXrCbykSrHdUBMDBka2OsXudPSo462XJefZQfrVAo2IIeIn5lDO6wv/utO+32Njxs1yH4GW/S9Em8iJKHv/KQ63vyR+2In5kpDePoMxzNGydCqbvdr4vphyLapIl771q0TT4KfC2Rht3Pyx8tDYIgmHIadEYkE7Vqm7y+vsUJgiCoH3V8wvKwIx6PD4KgaSk0cbRJdN5BEDQt9XxI53AjOu8gCJqWRg0DzEKWaJMO4AGKS7954DZV/aKI9AL/QFFo/Hngj1V1p3esgjl1Dh05Ozqjo8VflR5zsta8sGOa69vdbq+WS0q2lb2ddiadvnldpq3TOWca+1NkXrq9FXwnKw1AW4sd2TGhdh137hhwjztrrh3p0NXpfz+tThSSF1kD/veXS0nikm+1dxgbszuEXM5vNF5f4mW7AV+fxIsmAXjim3Zk1NKLBl1fcaJNOlvtNtOe87VNWuTgP/7YzHPeWR7SGQHOVdXXAqcA5yeKWVcB96nqMuC+5H0QBMFhQz1zWB5uZIk2UeCAxFprsinFND7nJJ/fRDHe+7N1L2EQBEGVTGTNxtCAZM0en0tivLcA96rqQ8C8RLTqgHiVn1U3CILgEKMFzbQ1Ipk6b1WdUNVTKGaAOF1E/Am2Ekq1TX58+zerLWcQBEHFNHPnXVG0iaruEpH7gfOBF0VkvqpuTjIkbzF8XtI2+eGj441ZS0EQNCQN2i9nIku0yVxgLOm4O4G3AX9FMY3PpcA1yd9/SjvW6Lg90B8ctaMzxvJ+mMTwqJ15ZnDYX/0XscvUlvdDEvZ0zjRt/UfZvj0dfsjIiFNPaTdLgyOOnkdKztO2vB0dsG/MaSpr/aQgC+bbN2qL+3/P9R3a6+jhOBEwAK15+3q9DDAA03psvRZvGlVSQpS86Id8zv9+vIw3afokXkTJuuXrXV/9rH1NE2rb9qdlbhI/GqUeNOqoOgtZRt7zgZtEJEex57hVVX8oIv8O3CoilwHrgfcexHIGQRBUzBEd562qT1BMwDD58+3AeQejUEEQBPWgmaNN4gnLIAialiN92iQIgqAhic47CIKgATmihakcbZNrgXcBo8CzwIdUdZd3rI1b7ZXptrydNaO3fcgtY3uXHb1x++N2JArA4I5h09Y5zc/kcVT/PNP2kTetsf1W3uMed2TN06Zt25PrXN8dV99s2tSJDAAYGrOvd8M2ux7/pvsL7nH3/sKOKhjd7+vWLFpkR33M73jR9d0ki03bmmf87EwrH7S/g9a3nGDaNq935X2QFvs7KEzYGYcAti/6hGnzst2Ar0/iRZMAtJ/1atN2wmUnmrbek49zj5tfvNS18+ra87s088i7Fm2Te4GTVPVkYA3wuYNXzCAIgso5ohMQW9omqlo6fHwQeE/9ixcEQVA9E+PNG21Si7ZJKR8GflTvwgVBENRCM4+8a9Y2EZGrgXGg7GRrqbbJL358fT3KHARBkAktFDJtjUgt2iYrRORS4ELgPDV+vkq1Tf6/f2nQn7ggCBqSZk7GULW2iYicT1G/+2xV3ZvlZN2dTiYdR1ejVcbc4+5TOyJheHCf69vRZUdRdKdFm/TZmitbJ2yF3DnzbI0KgPa9dgTM3FZf52V/zr7eHj/RES0y37QVCnYdz56VY2iPPXrZscPOtpIWnQF2tqL+wt2+6wl/YJoKJy9xXZ9+fLppa3H0S4Z3298dwMSE3c6PPX6u6+vpseRb/NGjl/HG0ycBP6LkyW/ZujZLL/KjxGYt9TMwHXVBHaJNmni8WIu2yVqK4YP3JmI8D6rqxw5eUYPDFa/jDoKppNDEC5a1aJu86qCUKAiCoE4U9AjuvIMgCBqVI/0hnSAIgobkUGXSEZFeEblXRJ5J/r7icVkRWSgiPxWRVSKyUkQ+WWL7byKyUUQeS7YL0s4ZnXcQBE3LIYzzvgq4T1WXAfcl7yczDvy5qr4aOBP4hIiUai18VVVPSba70k54SKdNpnfZ80/T2mytCcVfDc87GTmmz7AzywDMnmtn8Glv9zO1HD3H/tJHJ+yq1VxKtc+wNS7a2u2oD/Czk7SN+ZE3OSfip9MJvOlsb2HnoF0XXV329abpx7R12N/ByKqnXN95cxeYttf0+e3ioRP7TZuTfMnVLgEojNp13N7uj6X6Zti+3e1+RFZ7zvZNy3jjaZR4ESVpGXpe9X/413uUa81G4dDFcF8MnJO8vgm4n2I03kskidoPJG0fEpFVQD/gN2SD1JG3iHSIyK9E5PFkqP+lSfZPi4iKyJxqChA0Pl7HHQRTSWFiItNW+jBhslUapzgv6ZwPdNJ2rDAgIospBoKUPq1+hYg8ISI3lpt2mUyWkfcBYao9ItIK/FxEfqSqD4rIQuDtFNOgBUEQHFZknc8ufZjQQkR+QvkbgqsrKZOITAP+EfiUqh5ILvoN4C8BTf7+vxRlR0yqFqZK3n8V+AwZkg8HQRAcauoZbaKqb7NsIvKiiMxX1c0iMp+iDlS5/Vopdtw3q+rtJcd+sWSfbwI/TCtP1cJUInIRsFFVH0/xfel25Cd3hrZJEASHjoIWMm11YDlwafL6UsoMaKX4NOO3gFWq+teTbKWPN/8RsCLthJkWLFV1AjhFRGYCd4jIyRRvFd6Rwfel25EfPNjEQZdBEBx2HMI472uAW0XkMorTyO8FEJGjgRtU9QLgLOADwJPJYBjg80lkyZdF5BSKsxrPA/8x7YTVClNdDCwBHk8ejV8APCoip6vqby3/WV32inhbi629kMNeKQeYwIlIGLGPC35EybRu/8ZkRqedBebFPXYUy7bZfoaRGe22rkZu3M880yp2VqHchG0DyOXtEcg+57Qd7cLYeHX/JGMp38++vXab2fhLf5F+cZ+tFTLv9f76eu/sN5i28TH7WvOt/r9Uwclm3jfHj27qbLW/hOmODaBF7PN6EUrgZ7zx9EnSoknW3v68az/etWbjUCkGqup24Lwyn28CLkhe/xzKh86p6gcqPWfVwlSq2leyz/PAaaq6rdICBI1PtR13EBxsCo4QWKNTtTDVwS1WEARB7RzRkrCWMNWkfRbXq0BBEAT1olETLWQhhKmCIGhamlmYKjrvIAiaFg1J2CAIgsajMN68C5aZVbcOxgZcfqh9p+Kc4RvfbfjW7hvby7eploStJUldtb5Tcc7wPTS+jVbe8A2qZqo77yAIgqAKovMOgiBoQKa6865Fqapa36k4Z/geGt9GK2/4BlUjySJCEARB0EBM9cg7CIIgqILovIMgCBqQKem8ReR8EXlaRNaKSLksy5bfQhH5qYisSvJpfrKKc+dE5DciUpG4lojMFJHbRGR1cv7fr8D3yqS8K0Tk+yJiZhFO8tdtEZEVJZ/1isi9IvJM8rdsfjvD99qkzE+IyB2JJnsm3xKbmafU8hORP0u+45Ui8uUKynuKiDwoIo8lSTxON3zLtoUsdeX4ptZVWhu06srzS6srp7ypdSVGDtqM9WT5ZqmnyH17sDnUgeVADngWWAq0AY8DJ2T0nQ+8Lnk9HViT1bfkGP8Z+B7wwwr9bgI+krxuA2Zm9OsHngM6k/e3Av+Xs/9bgNcBK0o++zJwVfL6KoqSvFl93wHkk9d/VYlv8vlC4G7gBWBOxnO+FfgJ0J6876ugvPcA70xeXwDcX0lbyFJXjm9qXXlt0Ksr55ypdeX4ptYVRf3oacnrVooJb8/MWE+Wb5Z6KuubpU3Flm2bipH36cBaVV2nqqPALRSTO6SiqptV9dHk9RCwimLnmAkRWQD8IXBDJQUWkR6KHc23knOPququCg6RBzpFJA90AZusHVX1AWDHpI8vpvjjQfL33Vl9VfUeVT2Q8eBBiokzsp4XfpentOzKtuH3ceAaVR1J9imbz8/wVaAneT0Do66ctpBaV5ZvlrpKaYNmXTl+qXXl+KbWlRYpl4M2Sz2V9c1YT9Z5IaVNBdmYis67H9hQ8n6ACjrgA4jIYopStQ9V4PY3FBtNpWo1S4GtwN8lUy43iEh3FkdV3Qh8hWJqpM3AblW9p8Lzz1PVzcnxNgN9KftbfBj4UdadJWOe0jIcB7xZRB4SkZ+JiJ2W5pV8CrhWRDZQrLfPZSjnYn7XFiqqK6cdpdZVqW8ldTXpnBXV1STfTHUlZXLQkrGeDN9SzHoq51tDmwomMRWdd7k0QBX9AovINIoZmD+lqoMZfS4EtqjqI5WcKyFP8fb+G6p6KjBM8VYzy3ln8bu0cUcD3SLy/irKUBMicjUwDtyccf8uinlKv1DF6fLALIq32P+FYm6/sumfyvBx4EpVXQhcSXK345Sz4raQ5pulrkp9k30z1VWZc2auqzK+mepKVSdU9RSKI+TTReSktHJm8U2rpzK+B3LfVtOmgklMRec9QHHO6wALcKYRJiMirRQb8M2qensF5z0LuEiKKdtuAc4Vke9m9B0ABkpGHbdR7Myz8DbgOVXdqqpjwO3AG7MXG4AXJckunfwtOw1hISKXAhcC/0FVs/5QHsvv8pQ+z+/ylB6VwXcAuD25df4VxTudrAtTl1KsI4AfUJxmK4vRFjLVldWOstRVGd9MdWWcM1NdGb6Z6wqKOWiB+4HzqbBNTfKtqE2V+Jbmvn2eytpUMImp6LwfBpaJyBIRaQMuAZZncUxGJN8CVqnqX1dyUlX9nKou0GLWn0uAf1XVTCNgLSZV3iAiB3Kingf42W9/x3rgTBHpSsp/HsU5y0pYTvEfleTvP2V1FJHzgc8CF6nq3qx+qvqkqvap6uKkzgYoLpqZCaZLuBM4Nzn/cRQXeLPmN90EnJ28Phd4ptxOTltIrSvLN0tdlfPNUldOeVPryvFNrSsRmXsgGkR+l4N2dcZ6KuubsZ7K+f6mhjYVTEanYJWU4sr4GopRJ1dX4PcmilMsTwCPJdsFVZz/HCqPNjkF+HVy7juBWRX4foniP8wK4O9JIguMfb9PcW58jGLjvgyYDdxH8Z/zPqC3At+1FNcYDtTXdVl9J9mfp3y0SblztgHfTa73UeDcCsr7JuARilFIDwGvr6QtZKkrxze1rrK0wXJ15Zwzta4c39S6Ak4GfpP4rgC+kHyepZ4s3yz1VNY3S5uKLdsWj8cHQRA0IPGEZRAEQQMSnXcQBEEDEp13EARBAxKddxAEQQMSnXcQBEEDEp13EARBAxKddxAEQQPy/wMvNVypffU5xQAAAABJRU5ErkJggg==\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "for cor in cor_OneSes1:\n", + " sns.heatmap(cor, cmap=\"coolwarm\")#, vmin = -1, vmax = 1)\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 400, + "metadata": {}, + "outputs": [], + "source": [ + "# seperate ket from mid - numpy way\n", + "group_label = np.array(group_label)\n", + "\n", + "ketArrSes1 = np.array(cor_OneSes1)[group_label==1]\n", + "midArrSes1 = np.array(cor_OneSes1)[group_label==0]\n", + "\n", + "# second session\n", + "ketArrSes2 = np.array(cor_OneSes2)[group_label==1]\n", + "midArrSes2 = np.array(cor_OneSes2)[group_label==0]" + ] + }, + { + "cell_type": "code", + "execution_count": 401, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(10, 36, 36)" + ] + }, + "execution_count": 401, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "midArrSes1.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 402, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot mean matrices\n", + "fig, ax_list = plt.subplots(1, 2, figsize=(16,4.5))\n", + "ax = ax_list[0]\n", + "ax.title.set_text('Ketamine')\n", + "sns.heatmap(np.mean(ketArrSes2, axis=0), cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax)#,\n", + " #vmin = -1, vmax=1)\n", + "ax = ax_list[1]\n", + "ax.title.set_text('Midazolam')\n", + "sns.heatmap(np.mean(midArrSes2, axis=0), cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax)#,\n", + " #vmin = -1, vmax=1)\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 403, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot mean matrices\n", + "fig, ax_list = plt.subplots(1, 2, figsize=(16,4.5))\n", + "ax = ax_list[0]\n", + "ax.title.set_text('Ketamine')\n", + "sns.heatmap(np.mean(np.asarray(ketArrSes1), axis=0), cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax)#,\n", + " #vmin = -1, vmax=1)\n", + "ax = ax_list[1]\n", + "ax.title.set_text('Midazolam')\n", + "sns.heatmap(np.mean(np.asarray(midArrSes1), axis=0), cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax)#,\n", + " #vmin = -1, vmax=1)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 299, + "metadata": {}, + "outputs": [], + "source": [ + "# saving to mat\n", + "from scipy.io import savemat\n", + "mdict = {'ketamine': np.mean(np.asarray(ketArrSes2), axis=0), 'midazolam': np.mean(np.asarray(midArrSes2), axis=0)}\n", + "savemat('averagedMat_session2.mat', mdict)" + ] + }, + { + "cell_type": "code", + "execution_count": 363, + "metadata": {}, + "outputs": [], + "source": [ + "thr = 0.05 # set threshold\n", + "def fdr_corr(p, thr=0.05):\n", + " # FDR correction\n", + " # takes the p from the t test, flatten and return a 36x36 mask\n", + " # flatten p\n", + " pflat = p.flatten()\n", + " fdr = sm.multitest.multipletests(pflat, alpha=thr, method='fdr_bh')\n", + " fdrArr = fdr[1].reshape(36,36)\n", + " return fdrArr" + ] + }, + { + "cell_type": "code", + "execution_count": 404, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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9cy7IdLOkMyVNHrx/P3E2m5nZYCVkc7+3LJoWEY/n8XyV1I/QzMzGSN0zxEr9Yo8HdgMWAfMknR8Rv2vabA/Se6ubkPLkRGBHSeuR3kvdPCL+IulsYF/g1FoHOcaczWZmNpwSsrnfWxY1QlXAFMCFMMzMxtCEiWpracEOwB0RsTAingXOAuYM2mYOcHrukjMXmCZpel43CZgiaRLppm1xPVc6fjibzcxsOCVkc9+3LJJ0Cqni5GbAcUPs77YIZmZd0IH3htYD7m36fVH+bMRtIuKPwDHAPcB9wGP58d9+5Gw2M7NKJWRz37csiogD8lfsxwHvAU6p2MZtEczMuqDd/n6SDgYObvropPxv9gubVOw2+N/xym0krUOaad4QeBT4oaT3RcT32hpkb3A2m5lZpRKyue9bFkF690jSD4BPURGsZmbWHRMmtReszTc+Q1gErN/0+wxWfAxqqG3eDPwhIv4EIOlHwOuAfrzpdTabmVmlErK5b1sW5YpgGzd+BvYiV6A0M7Ox0YFHqOYBm0jaUNKqpGIX5w/a5nzgAzkXdiI9KnUf6dGpnSStnnNiV+CW+q52XHI2m5nZckrI5k580wuktgiSXk1qiwCpOuP7gAdZvi3CT5TaItxIRVuE/PjTL5XaIjxMegRrdWCCpD8Dfx8Rl1YMQcBZkjYHJpIey9qmYjszM+uSdh+hGklEPC/pUNLN3ETg5IhYIOnDef03gYuAPYE7gKeAA/K6ayWdQyru9Dzpkd/hZq57nrPZzMwGKyGbFdGZ12TynbmqGs9LWhIRU0dxzL8CIiJul7Qu8Bvg1RHx6BDbnw38KCLOkvRN4LcRceJw5/B7Q2Zmy2w0c2atfQzu/MDb2vo3dubpF9bbR6FwzmYzs97nbG5fT7UsiojfR8TtABGxmDQz/dIhxiJgF+Cc/NFpwN51Xq+ZmbWnA49Q2QiczWZmNpwSsrlnWxZJ2gFYFbhTFW0RgH2ARyPi+bxLVansxrHcFsHMrAs0YUJbi9XG2WxmZpVKyOaebFmk1Lj4u8AH8yNaK7RFkFQ1y1z51b3bIpiZdUevzhD3AWezmZlVKiGbe65lkaS1gAuBz0fE3GGO/RAwTdKkPKNcVSrbzMy6qIRgHaeczWZmVqmEbB6rlkWNCpFttUWQtB1wLzCd9E7Se4Y6eaQKXfcAiyQFcAjw47ouzszM2lfCI1TjnLPZzMyWU0I2d6xlEXA5sDnVbREa2m2LsA2pJcIf8ti/J2lxRFwzxBgOJ7179GJgHeA79V6imZm1o4TZ5HHO2WxmZsspIZs7cas+salC5Nqk934CuCwi7szbNB6zeprUl2kCsCNwWETcRWpAvLGkyaTHp6aSZp2PiYhVImJ2RMwCfkd6x6hSRFwQEbOBPwIHRsQzNV+rmZm1oYTZ5HHK2WxmZpVKyOZOfNO7Kam58HmkKo07kN4hOl/SGyKiuVhGo0Lk45JeAsyVdH5EzJPUqBA5hREqRHbgGszMrBPU/7PJ45Sz2czMqhWQzZ24Vb87F7F4C8sqRF4PbEaqENmsUSHyJuCnLKsQCalC5G7AdqTWCMt2WlYh8oCIGKhqiyBp91YH7LYIZmbdUUIvwHHK2WxmZpVKyOa+qN4cESu0RWiH2yKYmXVHrz4W1QeczWZmVqmEbB6r6s0N7VaIXBU4Fzg9In7YwbGbmVkHlDCbPM45m83MbDklZHPHqjdHxGWSXk11hchGW4R2K0TuBLwJeJ2kLwMPAHtHxI1VY8jH3Zp0nfdIOjMiDuzMFZuZ2UhKmE0ez5zNZmY2WAnZXOtNb67uOAtAKU2Pi4hjKzZ9Mm//EPDaivV3AafnbZaSqkciaRHww4i4XdK6wG/ytkM5HLg4/3wGcF1bF2RmZrXq1RniXuZsNjOz4ZSQzbXe1kvaQNItTW0RviBpnqSbJB1Zsf1USVdIul7SfElz8ufb530mS1pD0gJJsyLi9xFxO0BELCbNTL90qPFExEWRAb8GZtR5vWZm1p4SHqEab5zNZmY2nBKyuRPfZW9Kmgn+DKni4w7AbGBbSW8YtG2jLcI2pEej/luSImIe0GiL8J+M0BZhpAqRklYB3g9cUjVgV4g0M+uSCRPaW6wuzmYzM6tWQDZ34p3euyNirqRjWNYWAVK1x02A5l6AjbYIbwAGWNYW4X5SW4R5pPD9ePMJmtoifDAiBoCRKkSeAFwdEddUrXSFSDOz7lABvQDHKWezmZlVKiGb+6Jl0XAkfTGf45D2L8XMzOpUQrGMccrZbGZmlUrI5r5uWSTpIGB3YL8862xmZmNIkya2tVjtnM1mZracErK5r1sWkcL5OeBhSc8A/xMRn+/A5ZqZWQt6tQBGv3A2m5nZYCVkc7+3LJoWEY/nfb9KCnczMxsjUv8/QjXeOJvNzGw4JWRzv7csaoSqgCmAC2GYmY2lCWpvsZXmbDYzs2EVkM1937JI0imkipObAcdVDdhtEczMukMTJrS1WG2czWZmVqmEbO77lkURcUB+9+g44D3AKRXbuC2CmVkXlPDe0DjlbDYzs0olZHPftyyC9O6RpB8An6IiWM3MrEsKeG9onHI2m5lZtQKyuW9bFinZuPEzsBe5AqWZmY0NTVBbi9XO2WxmZsspIZt7rWXRlsAuLGuL8BCw1xBtEQScJWlzYCLpsaxtOnO1ZmbWkh59F6hfOJvNzGwFBWRzr7Us+jnwzYh4Js9S30wK6qqxDEhaCBwTEWdJ+ibwd8CJo75AMzNbKflGy7rI2WxmZsMpIZt7rWXRsxHxTN59teHGn4N9F+Cc/NFpwN51Xq+ZmbVpwoT2FltpzmYzMxtWAdnccy2LJK0v6SbgXuArEbG4qi0CsA/waEQ8n8+1KI9nBW6LYGbWHSW8NzROOZvNzKxSCdnccy2LIuJeYCtJ6wLnSTonIlZoiyDppRVjq2x54LYIZmZdUkCFyHHK2WxmZtUKyOaea1nUkGeRFwB/w7LHpJo9BEyTNCnPKM8AFo/ukszMrBY9OkPcB5zNZmZWrYBs7rWWRTMkTck/rwP8NXBb1ckjIoArSY9SAXwQ+HEdF2ZmZqMjTWhrsdo5m83MbDklZHOvtSyaDnwrF8IQcE5EzB9mGDcDp0o6k/Qe0ifqvk4zM2tDAbPJ45mz2czMVlBANitNunbgwDn8ImKgYt2SiJg6imOumo/Z3BbhdRFR+WiUpNcAjwBXAdvlNgzD8ntDZmbLbDRzZq1J+NR3Dm/r39jVD/z3/k/iLnI2m5n1Pmdz+/q2ZRFARNyQ+xOamdl4ILW32EpzNpuZ2bAKyOa+bVkkafdWB+y2CGZmXVJAL8BxytlsZmbVCsjmvm1Z1A63RTAz65IenSHuA85mMzOrVkA293PLIjMzG2fUozPEfcDZbGZmlUrI5rFqWdSoENluW4Qd8ztGN0q6BdiTIdoi5O2/L+k2YF3gWEmr1Hh9ZmbWLk1ob7G6OZvNzGx5BWRzx1oWAZcDm1PdFqGh3bYIq5FmlweApcBE4M/DjOEJUohPAN4JbEDqH2hmZmNAEyeO9RBK52w2M7PllJDNnbhVn9hUIXJt0ns/AVwWEXfmbRqPQz0NPJXHsSNwWK7oeAuwsaTJpMenppJmnS+OiC0jYmtg57zvkCLiwxExIyImAZ8jtUcwM7OxMkHtLS2Q9FZJt0m6Q9JhFesl6Rt5/U2Sthm0fqKkGyRdUNNVjkfOZjMzq1ZANnfim95NgQOA84B9SBUiBZwv6Q0R0Vwso1Eh8nFJLwHmSjo/IuZJalSInMKgCpHAhcDGwKeG6gPYLD869X7gE7VdpZmZta/mx6LyN47HA7sBi4B5OUd+17TZHqRiTZuQbuJOzH82fIJ0Q7dWrYMbX5zNZmZWrYBs7sQ3vXdHxFxSdchGhcjrgc1IF9WsUSHyJuCnLKsQCalC5G7AdqTWCECqEBkRW5GC9YOSXt5CW4QTgKsj4pqqAbstgplZl9TfC3AH4I6IWBgRzwJnAXMGbTMHOD2SucA0SdPTcDQDeBvw7fouclxyNpuZWbUCsrkvqjcP1xZB0hfzOQ4Zahu3RTAz65L6K0SuR+oN27CI5WeKh9pmPeA+4OvAp4E16x7YOONsNjOzagVk81hVb25ot0LkDElT8s/rkApfDFch8iBgd2C/iBio57LMzGzU2qwQ2fxtX14OHnzEirMMvkGq3EbS20kZ9Jtarq03OJvNzGx5BWRzx6o3R8Rlkl5NdYXIRluEditETge+pXRAAedExPxhhnES8BzwsKRngP+JiM/Xfa1mZtaiFgtgNDR/2zeERcD6Tb/PAAa/TzrUNvsA75C0J+lby7UkfS8i3tfWIHuIs9nMzFZQQDYrojNPDDXCr2oWV9KSiJg6imOumo/5TJ6lvhl43VAFMyStFRGP55+/Spo1OHq4c/gRKjOzZTaaObO9JBzB0z/+n7b+jZ0859Bhzy9pEvB7YFfgj8A84O8jYkHTNm8DDiX1j90R+EZE7DDoOG8EPhkRb29nfL3G2Wxm1vucze2r9fFmSRtIukXL2iJ8QdK8XIb6yIrtp0q6Qqmp/XxJc/Ln2+d9JktaQ9ICSbMi4tmIeCbvvtpI428KVZEqTTo0zczGUs3FMiLieVJoXkqq8nh2RCyQ9GFJH86bXQQsBO4AvgV8tDMXNz45m83MbFgFZHOt3/RK2oA0+NeRykvvQypSIeB84D8j4urGbHKeBVi9uS0CsElEhKSjSF9pTwEWRcSX8zkGt0U4XtK5wIaDhvOZiLhU0imkGYTfAW+LiBX6B+bn0A8GOOqoo7bdb999a/s7MTPrZbXPJl9wYnuzyW//SK3nL5Gz2cysvzib29eJd3rvjoi5ko5hWVsESNUeNwGaewE22iK8ARhgWVuE+0ltEeaR+gV+vLFDRNwLbCVpXeA8SecMVyEyIg7I7x4dB7wHOKViG1eINDPrhtZaHVj9nM1mZlatgGzuRPXmwW0RZudl44j4zqBtm9sizAYeYMW2CGs2ffaC/K7QAuBvRhpQRCwFfgC8axTXY2ZmdWmzQqTVxtlsZmbVCsjmvm1ZpGTjxs/AXuQKlGZmNkYmTGhvsbo5m83MbHkFZPNYtSxqaKUtwkbAzZJ+BEwDTs/h+gjw2WHaIgg4R9Jm+ec/ADsMsa2ZmXVDAY9QjWfOZjMzW0EB2VzrTW9E3AXMavr9WODYiu2m5j8fAl5bcai7gNPzzwPAwoj4maQ1gLfmc8zK7/sMNZYBSc8CbyIV4biINPt8cdsXZmZm9ejRx6J6mbPZzMyGVUA2d+yb3sFyKJ5Najw8EfgSsCnp0aYpwC+BQ3J1yG2Bk4GngJ83jhERTwI/bzwaNcL5pgNrRcSv8u+nA3vjYDUzGzsFzCb3EmezmZmVkM3dvK1/K7A4IraOiFnAJcD/RMT2+fcpQKPx8CnAxyOiaqZ5BZLOlXRj80IqjLGoabNFpAqUVfsfLOk6SdededZZo7w8MzMbUQHvDfUYZ7OZWekKyOaufdMLzAeOkfQV4IKIuEbSuyR9GlidVBFygaSrgWkR8X95v+8Cewx34Kq2CJK2J80eL7fpEPu7LYKZWRdEAbPJPcbZbGZWuBKyuWs3vRHx+/xo1J7AlyVdBnwM2C4i7pV0BKn9gRgiANu0iPS4VsMMYHENxzUzs9Eq4L2hXuJsNjOzErK5a1eYG9Y/FRHfA44BtsmrHsqtE/YBiIhHgcckvT6vf+9ozhcR9wFPSNopt0X4APDjlbkGMzNbSQX0AuwlzmYzMyshm7v5ePOWwH9JGgCeAz5CesRpPqki5LymbQ8ATpb0FHAt0Ojp92LSLPFk4DlJewNviYjfDXHOm4BrSMU5TsCFMszMxlQJj1D1GGezmVnhSshmRYzv12QkbUB6z2hWrjL5Gpa1RTh0hH13Au4Gbm+0YhiJ3xsyM1tmo5kza03Cp675YVv/xq7+N+/u/yTuQc5mM7Ox42xuX9+2LMrbz83nrvFKzMxs1Hq06mO/cjabmVkJ2dwvLYuuHdwWQdKWrQ7MbRHMzLojpLYW6zhns5lZ4UrI5n5pWbTjygzMbRHMzLqkRwtg9DFns5lZ6QrI5n5uWWRmZuNMFBCsvcTZbGZmJWRz37YsMjOzcUhqb7GOcjabmVkJ2dy3LYskrZ6P/Uzi+9wAACAASURBVEpgkqTHga9GxBEduTozMxtRCbPJPcbZbGZWuBKyuZuPN18KXDro4+uAz1ds+xtga3ihLcKb86qngd1osS0CcFBEXClpVeAKUkibmdlY6dEZ4n7lbDYzsxKyuW9bFkXEU8CV+ednJV2fz21mZmOlgNnkXuJsNjOzErK5iJZFkqaRAvyKIfZ3WwQzsy4ooS1Cj3E2m5kVroRs7vuWRZImAWcC34iIhUPs77YIZmbdUMBsco9xNpuZla6AbC6hZdFJwO0R8fUaj2lmZqMQ9OYMcb9yNpuZWQnZ3Astiz5CU4VISVcC3wTe0MI57wT+FthV0jclTazzmszMrD2hCW0t1lnOZjMzKyGbe6VlUcPTwGbAUmAzSYsYui3CDGAj4NZ8vn1JM9WH1HtZZmbWsh4Nyz7mbDYzK10B2dzNm96fA/eSqjROAWYCzwKPAK8AFgJHVuz3HHAHvFAhcrqk/UmPXg3ZFiEiFpGCFEmrAD8CflbTtZiZ2Sj0agGMPuZsNjMrXAnZ3BfVm4cj6VLgQeAJ4JyVPZ6ZmY1eCY9Q9Rhns5lZ4UrI5m6Oej7wZklfkfQ3EfEY8Kbc0mA+sAuwhaS1WbFC5LCGa4sQEbsD04HV8jmq9ndbBDOzbpDaW6zTnM1mZqUrIJv7onrzcG0R8vqnJZ0PzAEur1jvtghmZl3QqzPE/crZbGZmJWRzL1Rvfu8ozzdV0vT88yRSoN+6EpdgZmYrKVBbi3WWs9nMzErI5l6p3txoi7AbcAEwMf2q9wA7V1WIBNYAfippI9LN/a2MMqTNzKweJcwm9xhns5lZ4UrI5m4+3nwpcOmgj68DPl+x7W+ArQEkbQC8Oa96CNgwIhZLmgVcOkSoEhEPSHqS9K7QXOAiYDfg4pW+GDMzG50efReoXzmbzcyshGzu2k2vpDWAs0ltESYCXwI2BfYiVYf8JXBIRER+v+hk4ClSOwUAIuKGpkMuACZLWi0inqk433RgrYj4Vf79dNLstYPVzGyMRFfrJ9pInM1mZlZCNvdyy6J3ATdExDNVFSKBNwCLmrZfBKxXdSBXiDQz646BCRPbWqzjnM1mZoUrIZu7+U7vfOAYSV8BLoiIayS9S9KngdWBFwELJF3Nim0R9mg+kKQtgK8Ab4HqCpGStq8YQ2X1R1eINDPrjl4tgNHHnM1mZoUrIZt7rmWRpBnAucAHIuLOYU65iPS4VsMMYPHKXYWZma2MEopl9BJns5mZlZDNPdWySNI04ELg3yLiF8OdLyLuA56QtJMkAR8AflznNZmZWXtCamuxznI2m5lZCdncUy2LgK8Bs4DvSfouaXb4dRHx4BDnvAm4hlSc4wRcKMPMbEyV8AhVj3E2m5kVroRsVsT4fk0mt0W4ICJmSXoN8MCgtgiVBTDyvjsBdwO3R8TUVs7n94bMzJbZaObMWpPw3tt/19a/setvsnn/J3EPcjabmY0dZ3P7+rZlUd5+bj53/RdkZmZtK2E2uZc4m83MrIRs7tuWRZK2bHVgbotgZtYdoQltLa2Q9FZJt0m6Q9JhFesl6Rt5/U2Stml13wI4m83MCldCNvdty6J2uC2CmVl31D2bLGkicDywG6ky8DxJ50fE75o22wPYJC87AicCO7a4b79zNpuZFa6EbO7nlkVmZjbOdKAtwg7AHRGxEEDSWcAcoDkc5wCnRypiMVfSNEnTgQ1a2LevOZvNzKyEbO7blkVmZjb+BGpraX7ENS8HDzrkesC9Tb8vyp+1sk0r+/Y1Z7OZmZWQzX3bskjS6vnYrwQmSXoc+GpEHFH/pZmZWSva7e/X/IjrEKoOOPgbyaG2aWXffudsNjMrXAnZ3M3Hmy8FLh308XXA5yu2/Q2wNbzQFuHNedU3gM8NaoswVB9AgIMi4kpJqwJXkELazMzGSETtFSIXAes3/T6DdNPVyjartrBvX3M2m5lZCdncty2LIuIp4Mr887OSrs/nNjOzMRL1v1UzD9hE0obAH4F9gb8ftM35wKH5vaAdgcci4j5Jf2ph377mbDYzsxKyuYiWRfl9o71IM8orcFsEM7PuaPe9oRGPF/E8cCjp28pbgLMjYoGkD0v6cN7sImAhcAfwLeCjw+1b9zWPc85mM7PClZDNSgWzOk/SX5EGfzZNbRGA5rYIx5HKVc+PiFfm/bYCzsjh2zjWFqTZgbeMVCVS0iTgJ6THrb4+0jjdFsHMbJmNZs6s9Zmn2+68t61/YzeduX7tz1zZMs5mM7Pe42xuXwkti04Cbm8lVM3MrLPq7gVoK8fZbGZmJWRzX7csknQUsDbwT7VdiJmZjVrdj1DZynE2m5lZCdnczy2LZgCfA54BnpT0JCmQv9WBazMzsxZ0oEKkrRxns5lZ4UrI5r5tWRQRiyStHRGPSxJwDvBEHddiZmaj06szxP3K2WxmZiVkc9+2LMrbP55/nETq+eRCGGZmY6iEYO0lzmYzMyshm/u+ZZGkS4EHSTPJ51QdyG0RzMy6YyAmtLVYxzmbzcwKV0I2d/Od3vnAMZK+QlNbBEnNbREWSLoamBYR/5f3+y6wR/OBcluErwBvAYiIHYc6aUTsLmky8H1gF+Dyim1OIlWSdFsEM7MOGihgNrnHOJvNzApXQjZ37VY9In4PbEsK2C9LOhw4AdgnIrYkNSXuRFsEIuJpUu/AOSt1EWZmtlJKqBDZS5zNZmZWQjb3Qsuij5ArREraBbgdWAU4QdI7hznfVEm7S5ov6Q5StchbO3BpZmbWogi1tVhnOZvNzKyEbO6VlkUNOwMDwGOksZ8t6ZURcV/F+dYA/he4n9QaYQ3gD3VekJmZtadXZ4j7mLPZzKxwJWRzN99E/jlwL+kRqSnATOBZ4BHgFaSwPbJiv+eAOwAi4osRsUZEzCZVlnwY+NMQ55sALIqIjSNiC+DfgHfUdzlmZtauEmaTe4yz2cyscCVkc89Vb5a0o6QFpFnoD0fE80Ocbz1gUdPvi/JnK3CFSDOz7ijhvaEe42w2MytcCdncc9WbI+JaYAtJrwZOk3Qx8H/AaoPOd3TFGCqLcLhCpJlZd/TqDHEfczabmRWuhGzu2k1vRPw+N7bfk1Qh8jLgY8B2EXGvpCNooUJk0/FukfQkMKuqLYKk6cARTR/NABav9IWYmdmoDYz1AGw5zmYzMyshm3uhevN7m46xoaRJ+edXAZuSCm2sIBfQeELSTpIEfAD4ce0XZmZmLSvhvaFe4mw2M7MSsrlXqjdvnD//AHBYykkCODYiHhrmnDcB1wATSX0HL67rYszMrH29+i5QH3M2m5kVroRsVsT4fk1G0gak94xmSVodeDYins+PSP0WWHeoghmSdgLuBm6PiKmtnM/vDZmZLbPRzJm1JuEvfrekrX9j/3rzqf2fxD3I2WxmNnacze3r2je9ktYAzia9vzMR+BLpEai9SNUhfwkcEhGR3y86GXiK1E4BgIh4qumQkxnh/aKImJvPXd+FmJnZqJUwm9xLnM1mZlZCNvdFyyJJ10q6cdCyZasDc1sEM7PuGIj2Fus4Z7OZWeFKyOa+aFlUVSGyHW6LYGbWHSXMJvcYZ7OZWeFKyOa+aFkEXNe5kZuZWV16tepjv3I2m5lZCdncty2LzMxs/Ilob7HOcjabmVkJ2dy3LYtyNcn5wCuBSZIeB74aEUfUe1lmZtaqgQIeoeoxzmYzs8KVkM1927Iob7tjRFwpaVXgCuA/ImLYfoB+b8jMbJm62yL89KZn2vo39s1brdb/SdyDnM1mZmPH2dy+vm1ZlLe9Mv/8rKTr87nNzGyMjPN51uI4m83MrIRsLqJlkaRppAC/ompgbotgZtYdgdparOOczWZmhSshm/u+ZVEurnEm8I2IWFi1jdsimJl1R6/29+tjzmYzs8KVkM0ltCw6Cbg9Ir6+stdgZmYrZ2CgN2eI+5Wz2czMSsjmvm5ZJOkoYG3gn+q9GjMzG40B1NZineVsNjOzErK5n1sWzQA+BzwDPJlnnv8tIr5V83WZmVmLSiiW0WOczWZmhSshm/u2ZVHed62IeFwpic8BfhgRw1bD8HtDZmbL1N0W4fzrlrb1b+w7tpvYm1PKfc7ZbGY2dpzN7evblkV5+8fzj5OAVUfa3szMOquEYhm9xNlsZmYlZHPftyySdCnwIPAEaUZ5BW6LYGbWHRHtLdZxzmYzs8KVkM1937IoInaXNBn4PrALcHnFNm6LYGbWBb3a36+POZvNzApXQjZ37ZveiPg9sC0pYL8s6XDgBGCfiNgS+BZttkUAGm0RRtr2aeB8YM6oL8DMzFbaQLS3WGc5m83MrIRs7tuWRZKm5oIa5H32BG6t+7rMzKx1JTxC1UuczWZmVkI2D3vTK2mapI/WdK4tgV9LupHUruAo0gzyfOA8VmyLcLykXwF/afr8CFKLgyDNDn90qLYIwBrAjZKeAZaQZqi/WdO1mJnZKJQQrJ3mbDYzszqVkM3Dtixqbkkw6POJEbG0s0OrHM9rgEeAq4DthglVJO0J/CNpFnlHUt/AId8vavB7Q2Zmy9TdFuGsX7YXl/u+Tv3/olGbnM1mZmVzNrdvpEJWRwMz8wzwc6RZ2fuA2cDmks4D1ie973NsLjqBpCURMTX/vA/w9ojYX9KppNnhzYBXkWaNPwi8Frg2IvbP+5wIbE+qGnlORHwRICJuyOtbubY5wOmR7urn5pnx6RFxXys7m5lZ/Xp1hniccTabmVltSsjmkd7pPQy4MyJmA58CdgA+FxGb5/Ufiohtge2Aj0t6cQvnXIdUqfGfgZ8AXwO2ALaUNDtv87mI2A7YCthZ0lbDHbCqLQIpvO9t2mwRsN4Q+7stgplZF3TzESpJL5J0uaTb85/rDLHdWyXdJukOSYdVrP+kpJD0kpUbUW2czWZmVpsSsrndQla/jog/NP3+cUm/BeaSZpU3aeEYP8kzvPOBByJifkQMAAuADfI2fyfpeuAGUuhuXnmkLCJ2jIjZzQtp5nuFTYfY/6SI2C4itttv331buAQzMxuNLleIPAy4IiI2Aa7Ivy9H0kTgeFL7nc2B/SRt3rR+fWA34J6VHk3nOJvNzGzUSsjmdm96n2w62RuBNwOvjYitSSE4Oa9u/uuYzPKeyX8ONP3c+H2SpA2BTwK7RsRWwIUVx2jFIlLYN8wAFo/iOGZmVpMItbWspDnAafnn04C9K7bZAbgjIhZGxLPAWSzfQudrwKdpoV3PGHI2m5nZqJWQzSPd9AqYPsS6tYFHIuIpSZsBOzWte0DSqyVNAN7Z6mCytUgB/pikl5Pu8NNgpEMl3UF65+hFIxzneuAESc9I+gbwmN8ZMjMbW12uEPnyxr/7+c+XVWyzHkM8bivpHcAfI+K3Kz2SejmbzcysNiVk80iFrAKYKOlmUpGLB/LJJgKXAB+WdBNwG+kxqobDgAvyYG8GprY6oIj4raQbSI9ULQR+0bR6fVK7A4CrJV0QEQcNcahzSbPdbwbeDezV6hjMzKwz2n0sStLBwMFNH53UKMyU1/8UeEXFrp9r9RQVn4Wk1fMx3tLqWLvI2WxmZrUpIZtbqd68GvB8/n0NSWcAsyNi89xn7znSs9bHRsRVebtTB1eIbDrmrpI+Rq4QKelkllWIPCdv8xfSjPIGpAqRpwJExGeAz0i6ixHaIkTEg8C7JR0BLImI60a4VjMz67B2Z4hziJ40zPo3D7VO0gONysCSpgMPVmw21OO2M4ENgd/mqsQzgOsl7RAR97d3FbVzNpuZWW1KyOa+qN68slwh0sysO7r8CNX5pNY75D9/XLHNPGATSRtKWhXYFzg/F3J6WURsEBEbkAJ4m3FwwwvOZjMzq1EJ2TzSN72DVVWIbLwX1KgQ+ecRjvGTiAhJL1SIBJDUqBB5I6lC5MF5fNNJs9U3VR1M0gHAJwZ9/IuI+FirF9U8W7HwzjvHc7ESM7OeVkPVx3YcDZwt6UBShcd3A0haF/h2ROwZEc9LOhS4FJgInBwRC7o6ypXnbDYzs1ErIZvbvekdqkLkU5Kuot4KkdtHxCOSTq04xgsi4hTglDavw8zMxkANM8RtnCv+DOxa8fliYM+m3y8CLhrhWBvUPb4aOZvNzGzUSsjmkR5vfgJYc4h1Xa8QaWZmvW3p0vYWq+RsNjOz2pSQzSN907sUeHBwhcis6xUiJf2QFNQTgZuHqxAp6aPA1/O2IelTwCYR8XirYzEzs3p1cza5jzmbzcysNiVks2KYq5S0AXBBRMwa9PnEiOj6fb6k1wCPAFcxQoVISa8DbsmPYe0BHBERO450Dr83ZGa2zEYzZ650F/pmx1/ceiN5gI/tUdm2oGjOZjOzsjmb29dKy6KZkm4ktT9YAtwHzAY2l3QeqUjGZFJbhJMAJC0Z3BYhIvbP7wD9BdiM3BaBVLWr0RZh/7zPicD2wBRSW4QvAkTEDXn9iBcWEb9s+nUuqaS1mZmNoeEmWqv1XK52g7PZzMxqU0I293zLIkkHSLpx0HL8oM0OBC4e5hhui2Bm1gVdbovQr5zNZmZWmxKyuedbFo1UIVLSm0jB+vqhtnFbBDOz7hgYGOsR9CVns5mZjVoJ2dzzLYuGk2ehvw3skctjm5nZGOrVGeJxztlsZmajVkI2923LIkmvBH4EvD8ifj+aY5iZWb0Gor3FKjmbzcysNiVkc9+2LCLNIm8AXCEpgHsiYrNWx2FmZvUrYTa5C5zNZmZWmxKyuZ9bFk0FnszvKG0FnN1KsPq9ITOzZepui3DMj9qbI/7k307ovRKRHeZsNjMrm7O5ff3csmhJ069rQHv9p8zMrH69+ljUOONsNjOz2pSQzX3dskjSOyXdClwIfGiYY7gtgplZF5TQFqELnM1mZlabErK5r1sWRcS5wLmS3gB8iVTRsmo7t0UwM+uCgRKmk7vP2WxmZqNWQjb3dcuihoi4WtJMSS8Z7l0jMzPrrF6dIR7nnM1mZjZqJWRzP7cs2lj5BSNJ2wCrMvJMt5mZdVAJj1B1gbPZzMxqU0I291rLouuArfO475F0ZkQcOMSh3gV8OleKfB74xxiuVLWZmXXcgP8ZroOz2czMalNCNo900zsNmDJEW4RnGGKmNyLOAc6p+Hz/pp/vAmYNsW5/qh0OXJx/PgO4bpixzwd+DewJ7AgcC5w8zPZmZtZhMTDWI+gLzmYzM6tNCdk80uPNL7RFkDRP0pWSziCFFpLOk/QbSQtycQvy50uaft4nv/uDpFMlnZiPs1DSzpJOlnRLY5u83Ym5YuMCSUc2Po+IiyIjheaMYcY+Bzg9bz4XmCZpeqt/MWZmVr+IaGuxSs5mMzOrTQnZ3JMtiyStArwfuGSYtgjrkR7haliUP1uB2yKYmXXHwEB7i1VyNpuZWW1KyOZebVl0AnB1RFwDXENFWwRJF1acu3Jqwm0RzMy6o1dniMc5Z7OZmY1aCdnccy2LJH0ReClwyAhjXUQK+4YZwOIR9jEzsw4qoBXgWHA2m5nZqJWQzT3VskjSQcDuwH4RI75yfT7wASU7AY9FxH1tjsXMzGoUA9HWYpWczWZmVpsSsrmnWhaRHnN6HnhY0lPAcRFxxBCHuhN4DWmW+n5gr1bHYGZmnbF0aW+G5TjjbDYzs9qUkM291rLo7SzfFuGBIbYDeJgUpnuTZr2Ha6FgZmZdUMJ7Q13gbDYzs9qUkM1927IoIh6MiHnAc+38hZiZWefEQHuLVXI2m5lZbUrI5n5uWdQyt0UwM+uOgYi2FqvkbDYzs9qUkM1927KoHW6LYGbWHSU8QjUGnM1mZjZqJWRzP7csMjOzcWagR6s+jnPOZjMzG7USsnmkx5tFms2tMhZtEeaSHuvaBPh2fpSqeuDSe3P1yo8Ah0raus1xmJlZzSLaW6ySs9nMzGpTQjaP9E1vABMHt0WQNJGxaYuwPXAXqQDGO0mzykO1O3gMeDEwBVgD+LWkl0bE462OxczM6tWr/f3GGWezmZnVpoRsbqV682qk/nsAazQqROa2CM+QQm5z4IyIuCpvd2pEzIyINwJXsbxdJV0J/Az4WKNCJLzQTgFSiD9Jeo9ofkScmtdPzMedDfw7y79LtJyIuCAi1ouItUjvND3kUDUzG1slFMvoAmezmZnVpoRs7vnqzS2cD+BAlvUQXIErRJqZdUcMRFuLVXI2m5lZbUrI5p6v3izpAOATg87xi4j4WD7um0jB+vqhBuQKkWZm3dGrYTnOOZvNzGzUSsjmnq/eHBGnMERbhDwL/W1gj4gYKfDNzKzDCsjVseBsNjOzUSshm0d6vPkJYM0h1o1FhciDgN2B/SJiYLiDSHol8CPg/RHx+zbHYGZmHVDCI1Rd4Gw2M7PalJDNI33TuxR4cHCFyGwsKkSeRCrc8bCkp4DjIuKIIQ71bdIjWVdICuCeiNis1XGYmVn9okcLYIwzzmYzM6tNCdk80k3vNGBKRMxq/lDSxFwhco+qnXKlx3MqPt+/6ee7gFlDrNufam9nWdGLM1g+6Af7W+DJ/I7SVsDZw2xrZmZdMNCjM8TjjLPZzMxqU0I2j3TTezQwU9KNpPYHS4D7gNnA5pLOIxXJmAwcm4tOIGlJREzNP+8DvD0i9s/vAP0F2Ax4FXAA8EHgtcC1jUCVdCKp798U4JyI+CJARFzUGJikXwMzhhp4RCxp+nUNln+XyczMxkAJs8ld4Gw2M7PalJDNPd+ySNIBkm4ctByft3unpFuBC4EPDTUgt0UwM+uOEt4b6gJns5mZ1aaEbO75lkXANQxRITIizgXOlfQG4EukipZV27ktgplZF/RqWI5zzmYzMxu1ErJ5pG96BxuqLcLWwA3U2xZh14jYijQTXNUW4V9aHXREXE16FOwlre5jZmb1G4hoa1kZkl4k6XJJt+c/1xliu7dKuk3SHZIOa/p8tqS5+VvK6yTtsFID6hxns5mZjVoJ2dzPLYs2lqT88zbAqow8021mZh3U5UeoDgOuiIhNgCvy78uRNBE4npQ1mwP7SWo8JvyfwJH5MeLD8+/jgbPZzMxqU0I2j3TT29wW4b8GrbuENPt7E+nxpKq2CD8jFddoWUT8ljQzvQA4mRXbImxLaovwqKSjhjnUu4CHJD1DeszqC1HCW9pmZuNYRLS1rKQ5wGn559OAvSu22QG4IyIWRsSzwFl5P0jfjK6Vf14bWLyyA6qJs9nMzGpTQjb3WsuiaRHxeB7DV0kVK4cyH/g1sCewI3AsKajNzGyMLH1+2C8C6/byiLgPICLuk/Syim3WI/WtbVhEygyAfwIulXQMaZL4dZ0cbBuczWZmVpsSsrnXWhY1QlV53XBTDXOA0/MM8lxJ0yRNb/wlm5lZ97U7Q5wLJx3c9NFJjazJ638KvKJi18+1eoqKzxqD/AjwzxHxv5L+DvgOQxRd6jJns5mZ1aaEbB7ppvcwYFZEzM7FMS7MvzeqRH4oIh6WNAWYJ+l/I2Kkd3MabRHeQWqL8NfAQXn/2RFxI6ktwsP5ee4rJG0VETcBSDqFNEP8O+BfJR0AfGLQOX5B9QzBelQ80tX8P9xRRx3FfvvuO8IlmJnZaMRAe7PJzRV8h1g/ZNBJeqBxQyVpOvBgxWaLSDeIDTNY9qjUB1mWLz8Evt3O2DvI2WxmZrUpIZt7rmVRRByQA/c44D0RcQoVbREkXVhx7sppDLdFMDPrjoHutkU4nxSOR+c/f1yxzTxgk1yd+I/AvsDf53WLgZ2Bq0g3hLd3eLyj5Ww2M7NRKyGb273pHaotwlOSrqLetgjbR8Qj+bGr5Y4REUsl/QD4FEP0AWT4GQIzMxsDXa5ZdDRwtqQDgXuAdwNIWhf4dkTsGRHPSzoUuBSYCJwcEQvy/v8AHCtpEvA0yz/KNZ44m83MbNRKyOaRbnpXqi0CcBupLcITrQwmq2qLcFV+V2hmRNyRf94LuHWY45wPHCrpLNKLz4/5nSEzs7FVQ6uD1s+VHundteLzxaRHcRu/XwRcVLHdz0lViccbZ7OZmdWmhGwe6aa3uS3CX4AHmtZdAnw4t0W4jeq2CPcCNwNTWx1QRPxWUqMtwkKWtUUQ8AtJa+WfH2RZFa8qdwKvIc1S308KYjMzG0PdDNY+5mw2M7PalJDNPdWySNImg9oiNJ4Hr/IwKUz3Js16XzfEdmZm1iUD0dW2CP3K2WxmZrUpIZsnjLD+hbYIkuZJulLSGaQ+e0g6T9JvJC3IxS3Iny9p+nmf/O4Pkk6VdGI+zkJJO0s6WdItjW3ydidKui4f98jG5+20RYiIByNiHqmdg5mZjQMxEG0tVsnZbGZmtSkhm0e66T0MuDMiZpMKU+xAalmweV7/oYjYFtiOVC3yxS2cs9EW4Z9JbRG+BmwBbClpdt7mcxGxHbAVsLOkrRo757YI95P6CR4n6YAc/M3L8S2M4wWSDs5Bft2ZZ53Vzq5mZtaGEoK1C5zNZmZWmxKyuW9bFrXDbRHMzLqjyxUiS+FsNjOzUSshm0f6pnewodoibA3cQL1tEXaNiK2ACwcfIyKWAj8A3tXm+M3MbAwNDAy0tVhLnM1mZjZqJWTzSDe9K9UWQdIEUluEdlS1RUDJxo2fGbktgpmZjTMlPELVBc5mMzOrTQnZ3LctiyR9FPg6qaFxSPoU8EKFSTMz674ooEJkFzibzcysNiVkcz+3LLoReHlEPCJpD+AIh6qZ2djq1RniccbZbGZmtSkhm0e66X2hLQKpvcAS4D5gNrC5pPNIRTImA8fmohNIWhL/f3vnHixnXd7xzxMChNwQpOAlE8CoOChRokSUqFCpRQVvpVCrqQGsN2qd0aJOa7GjjBbbaR11FJEBvNERNV6gwmiLSEEkMCEXIFyq3FTwRqIpV8N5+sf7HrPZnN09J2x2f/uez2fmmXf3fT+75zl7ztnved99398vc259+3jg2MxcUU998CDV6I77AydRheMLgGvGAzUiPgMcRjX1wdcy84Mw5WkRfthy90fAgkm8HiIishOZDsE6AMxmERHpG9Mhm6fLlEWn4yETUAAAEj1JREFUAJd0ashpEUREBsNYjk2pZELMZhER6RvTIZsbP2VRRBxFFazLOjlOiyAiMhimw9HkIWA2i4jIDjMdsrnRUxbVR6HPAV6dmb0CX0REdjI5NjalkklhNouIyA4zHbK5105vUB3NnYhhTItwYUSsrUelPBv4ccfGI04BrqUa5fKCiOh4NFlERAbDdJgWYQCYzSIi0jemQzb3Or05gV3ap0WoT2EaxrQIC6l21IPq6PN9XZ7qRcADdc0Fvkc1wIaIiAyJ6TAtwgAwm0VEpG9Mh2zu9UnvPwO7A1vq+3Mi4gJgfT0twsNUI0ceDFyQmZfX3vmZuSgzjwQuZ1teGhHfBy4DTo2IcyNiA/xhOgWoQvx+quuI1mfm+Zk5lpmHZ+YhwCH18z7UqfHMXJGZe9UDfZwE3NHjexURkZ3M2FhOqWRCzGYREekb0yGbR3705m5fKCJeGxE3U117dHIXzxEiRUQGwNiWR6dUMiFms4iI9I3pkM0jP3pzNS0g72r7Gldl5qmZ+Q3gGxHxYuDDVIN7bIcjRIqIDIbpcArVEDCbRURkh5kO2TzVnd5OI0Q+EBGX098RIg/LzI0RcX77c2TmoxHxFeC0zDyWLtMi1P4VEbEoIvbJzF/3/jZFRGRnMKoDYBSO2SwiIjvMdMjmXqc3bwbmddg2jBEinzp+GzgOuLnTk0TEU2uPiFgC7EbvI90iIrITmQ7TIgwAs1lERPrGtMjmzOxawAVUozxeC1zcsn534BKqU5u+SjV4xZH1tuOppiy4HPgU1eAZAOcDx9e3DwBuaHm+1m3nAxuorvdZCayg2kG/Clhf9/NlYH6Xvt9HNcrkGuBqYFmv77XLc71FR0dHR8cqpczm8v42dHR0dIblWL1r6A2MQgHX6ejo6OhYVjlV2t+Gjo6OzrAcq3f1Or1ZREREREREZGSZ6kBWxRERJ9FhhMhh9CMiIjLdMZtFRKQkRn6nNzPPo8cIkX3gbB0dHR0dkclhNuvo6OiYzSUR9bniIiIiIiIiIo3Da3pFRERERESksbjTKyIiIiIiIo3FnV4RERERERFpLO70thERMyPirRFxaUSsi4i1EXFJRLwtInadxOPPrpe71M/z4Yg4os35QL2cHRHvjYjTImJWRKyIiG9HxMciYq799O6n9v40Ij5Tb/tWffuYXr3Ujz297XlOiYgD2pyT62VExAkR8ef17ZdGxCci4h0RMaPteeynQz+1u19ELImIQyNiv8n0Uj9ubm+r6+P37rDefrr0IzJsSsse+zGbm9ZP7RaVPfbTvR+ZGg5k1UZE/AewCfg88NN69QLgTcDemXlil1++ANZm5oKIOAeYDawClgM/yMx3119jdWYuiYgLgbuBPYCDgA3AhcBxwBMyc7n99Ozn48DTgS+09fNXwG2Z2T5lxrYNRdyVmQsj4iPAMmB1/fwfz8xPtvXzaWBfYDfgd8DuwEXAK4BfZOa77KdnP88BzgL2BH7W0s8m4B2ZuXqS/RwCfA54MnAJ8L7M3Fg7qzJzaVT/sJ0DjAEnA2cAi4BdgRMy82r76d5Pt68lMkgKzB77MZub1E9R2WM/ZvNOITOtlgJu6bLt1nr5KPAT4PaWGr//SO2sa3ncTKrhxldSvdlcX69fUy8DuJetByFi/PH207OfWzv0ElTBAdWb/ES1GdhSO+uBmfXtxwHfAf69vj/ez/p6uSvwG2C3lv7X28+k+lkDPH+Cfg6n+qcL4N0d6j3AfbVzJXBM3cvfATcCi9r6WQUcArwA+DWwrF6/hGq+UPvp0Y9llVKUlz32YzY3qZ+issd+zOadUZ7evD0b61NAWk9BmRERJwIb61U/AY7MzANb6imZeSDwi9rZbfzxmbklM99C9UdzGbDNaQ5Z/TZ/p16O30/7mVQ/D0XEUrbnMOCh+vYm4GmZOb+t5gH31M7MzNxSP/8mqiOm8yPiqy29jm//PXBtZj4y3j/VPxP207ufOZl5TXszmfkjYE599yPAXsC8tprL1ksy5mbmpZm5KTP/Ffgb4NKIOJytvxu7Zub6rI6K/iozr6y/1mqqTyjsp3c/IqVQWvbYj9ncpH5Kyx77MZv7Txaw511SAQcAXwF+Bdxa1y/rdQfWzqnAszs8/p318kvAMRNsfzPw+/r2OVR/AO3OIuBK+5lUP0uAa4CbgO/WtaFe99zaOQNY2qGfM+vlxcBLJth+BjBW376kQz9PAFbZz6T6+QTwn8CJwAvrOrFe96na+eF4bxM81931ci2wZ9u2xcBtwG/GnZZtr2lzb7Cf3v1YVilFedljP937KS177Kd7P0Vlj/1078fasRp6AyUX8Hhgnw7b/mQSj99hh/p0oVbHfjr3U795Pxd4HtU1Re3+M3t8nT2AJR22Pbnb81Ad5du31bGfrv28leramIuoAvss4BUt2w/q8nu1X738S+DwCbYvBD5X334VMHsCZxHw3pb7L7efzv1YVmlFQdljP937KSx7SsvC0voxm0eoH2vqNfQGRrWA1To6OjvN+aTO6DiWVUoV+F6mo9Mkp6js0enuWNuW1/TuOKGjo7PTnCN6KzoFOSKlUNp7mY5Ok5zSskdHJo07vTtO6ujo7DRHRGRHKO29TEenSY7IyOJOr4iIiIiIiDQWd3p3nDt0Rsp5RGeknNJO6dIRGQ3u0Bkpp7Ts0elOadmjI5Nn2BcVj1Kxk0c97OQA86knr25zFg/JeQL1KIPAHwGvo21kwEE6XV7DZwzLoZpnrd3ZZxgO1cGtGfXt3aimSti7zR+YM8mf3Qqd0XEsa5g11UztlzPg3DWb++AMKncn4wwydyfjTPJnt0JndByr7TUbdgOjVMBdg3aAE4CfU00OfyNwWIuzegjOW4HbqY7gvp1qTrlzgVuAUwbtFPjzOgr4KdVcid8FDpjgNRyk8xrgF1QT2b+6fg0vqx933KCdHq/h2YN2gF3q37MPA0e0OR8YgjMbeC9wGjALWAF8G/gY9TyLg3QsaxQKsxnM5l4/L7PZbDabp3lF/QJLTUR8u9Mm4I8zc86AnTXAyzPznohYCnwB+PvMXBkR12fmoQN21gPPp5ob7k7gqZl5b0TsBXw/M58zYOcTXV7DN2Xm/AE711IdfbsxIo4HPgosz8wftbyGg3Sup5pbbg+qSdEPy8xbImJ/4OuZ+bwBO3t3eQ3XZuaCATvnUAXMKmA58IPMfDdARKzOzCUDdi4E7q5fw4OADcCFwHFUn6osH6TT4fUTGThms9n8GB2z2Ww2m6c5M4fdQIG8CHgj8H9t6wNYOgRnl8y8ByAzV0XEUcDFEbGArSPtDdL5fWY+ADwQET/OzHtrf2NEDMM5CXgP8DDb8/ohOLtl5o11n1+LiA3Ayoh4P1tfw0E6jL9uEXFXZt5Sr7szImYMwfkV1T9JrdeiZH1/3yE4SzNzcd3zp4BPR8RKqp9nDMF5emaeEBFBdVT+6MzMiPgfqn9WBu2IlILZ3N0xm81ms9lslm5kAR83l1TAJcBRHbZdMQTnh7RdxwPMA/4beHgIznXU16kAC1q8WVRH6AbtXAa8sMNrePsQnOuor3Nq2baA6rS0zUNwrmfrdTxLW7xdgBuG4NwGLOzwGt49BOfmCbadDlwF3DYEZ03LtnPb3LWDdiyrlMJsNpsfm2M2d3fM5u6O2dyAGnoDVo8fEDyb6tSh9vW7Am8YgrMQmDmB82Sqo1GDdvYGZvd4DQfpHA08e4L1jwP+YQjOYcCsCZwDgDcOwTl1op7rbe8cgvMl4JgJtr+Z6tOMQTvnMME1O8Ai4MpBO5ZlTVyYzWbzY3PM5u6O2dzFsXasht5AqQUcPMG6I3XKdCyr6QXVGAylOJY1jCote3S6O5bV9DKbR6ccyKoDEXED8EWq0dJm1cvnZeYLdMpxohpQo+MvcWYu1inHab0fEc8CDqb6mY47X9Ap0xEpgVKyR8dsbpLTer+07NExm/uFA1l15vnAmVTX0swDvgwcoVOcc2y9PLVefrFevgF4QKc4B4CI+CBwJNWb+XeoRpa8kmpUUp3CHJGCKCV7dMzmJjlAedmjYzb3lWF/1FxqUU3e/S9UAw/8L/AXOkU7V/Vap1OUsx6YwdaBG/YDLtIp07GsUoryskfHbG6SU1T26JjN/aw/DGcu23Et8CDVAADLgNdHxNd0inXmRMSy8TsR8UJgjk6xzoOZOQZsiYj5wC+Bp+gU64iUQmnZo2M2N8kpLXt0zOb+Mey97lKL6rqU9nXLdYp1nks1f9kdda0BlugU63yaaiTLt1FNX3A9cJ5OmY5llVKUlz063Z3SskfHbG6MY02tHMiqBxGxL9teQH6XTtHOfKrR7X7bvk2nPKf2DgDmZ+Y6nfIdkRIoMHt0ujtFZY+O2dw0R3rjTm8HIuI44N+AJ1GdUrA/sCEzn6lTnlN7rwSeybbh+yGdYp3FVPMEzmxxVuqU6YiUQGnZo2M2N9ApKnt0zOZ+4ejNnTkDOBz4r8w8NCKOAl6vU6YTEWcBs4GjqCb2Ph5YpVOscy6wGLgRGKtXJ7BSpzxHpCCKyh4ds7lhTlHZo2M295Us4BzrEgu4rl6uBWbUt1fpFOusa1vOBb6rU6xz0yT+BnUKcSyrlOpjZuiYzTpm80g71tTKT3o7syki5gJXAF+OiF8CW3SKdR6qlw9ExJOA+4ADdYp1ro6IgzPzJjqjU44jUgqlZY+O2dwkp7Ts0TGb+8ew97pLLaph3HehOgX8TcDfAo/XKdb5R6pR7v4MuBe4B/iQTrHOi4HfArcA66jmo1unU6ZjWaUU5WWPjtncJKeo7NExm/tZftLbgcy8v+Xu53XKdoCbgUcz8+sRcTCwBPimTrHOucByqjfxMSZGpxxHpAhKyx6d7g7lZY+O2dwkR6bCsPe6SytgM/C7ltrcutQpy2n5uY1fo7KM6lSrVwPX6BTrXDaJv0WdQhzLGnb1KzN0zGYds7kpjjW18pPeNjJzns7oOC08Wi9fCZyVmd+KiH/SKda5OSIuAC4CHh5fmdsOxa9TjiMyVErLHp1JU1r26JjNTXJkCrjT24WIWAY8LTPPi4h9gHmZebtOkc7PIuKzwNHAmRGxOzCDbdEpx9mD6k38ZS3rkm2H4tcpxxEphsKyR8dsbpJTWvbomM39o9dHwdO1gA9SHV25tb7/JOAqnWKd2cDrqMIX4InAy3TKdCzLsnakCsweHbO5MY5lNbkiM5HtiYg1wKHA6sw8tF63LjMX65TnyGgREedRHbHchsw8Wac8R6QUSsseHbO5SZSWPTpmcz/x9ObOPJKZGREJEBFzdIp2ZLS4uOX2LOC1wM91inVESqG07NExm5tEadmj092RqdDtY+DpWkAApwOfBX4C/DVwNfBOnfIca/SL6rqiriMV6pTjWNYwqrTs0TGbm16lZY+O2fxYyk96JyAzMyJeA7yPahj+g4DTM/N7OuU50gieBizUGRlHZOCUlj06ZvM0oLTs0ZEdxp3ezlwNbMrM03RGwpERIiI2U12rEvXyXqp/nnQKdEQKorTs0TGbG0Np2aNjNvcTB7LqQETcBDwduBO4f3x9bjuIg04hjoiINJ/SskfHbBaR0cCd3g5ExP4Trc/MO3XKc2T0iIi9qE7XmTW+LjOv0CnTESmB0rJHp7sjo0dp2aNjNveNLODCYsuyplcBbwbWAxuB7wMP0jZAg045jmVZltX8Ki17dMzmvv5+D7sBy7KmX9Vv5LOANfX9ZwBf0SnTsSzLsppfpWWPjtncz5qBiMjgeSgzHwKIiN0z82aq0T91ynRERKT5lJY9Ot0dmQKO3iwiw+CnEfE44JvA9yJiI9tPuq5TjiMiIs2ntOzRMZv7hgNZichQiYiXAHsCl2bmIzplOyIi0nxKyx4ds/mx4k6viAyUiJgBrMvMZ+mU74iISPMpLXt0zOZ+4zW9IjJQMnMMWBsRC3XKd0REpPmUlj06ZnO/8ZpeERkGTwRujIhVwP3jKzPzVTpFOiIi0nxKyx4ds7lvuNMrIsNgLnBsy/0AztQp1hERkeZTWvbodHdkCrjTKyLDYGZm/qB1RUTsoVOsIyIizae07NHp7sgUcKdXRAZGRLwdeAfwlIhY17JpHnCVTlmOiIg0n9KyR8ds3hk4erOIDIyI2BPYC/go8P6WTZsz8z6dshwREWk+pWWPjtm8M3CnV0RERERERBqLUxaJiIiIiIhIY3GnV0RERERERBqLO70iIiIiIiLSWNzpFRERERERkcbiTq+IiIiIiIg0lv8HnqZBQwtB5RUAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# t test between groups\n", + "t,p = scipy.stats.ttest_ind(ketArrSes1, midArrSes1)\n", + "tArr = np.array(t)\n", + "fdr = fdr_corr(p, thr)\n", + "tArr[fdr>.05]=0 # set p value to cut\n", + "\n", + "fig, ax_list = plt.subplots(1, 2, figsize=(16,4.5))\n", + "ax = ax_list[0]\n", + "ax.title.set_text('First Session')\n", + "sns.heatmap(tArr, cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax)#,\n", + " #vmin = -1, vmax=1)\n", + " \n", + "t,p = scipy.stats.ttest_ind(ketArrSes2, midArrSes2)\n", + "# threshold the t\n", + "tArr = np.array(t)\n", + "tArr[fdr_corr(p, thr)>.05]=0 # set p value to cut\n", + "ax = ax_list[1]\n", + "ax.title.set_text('Second Session')\n", + "sns.heatmap(tArr, cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax)#,\n", + " #vmin = -1, vmax=1)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 351, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[False, False, False, ..., False, False, False],\n", + " [False, False, False, ..., False, False, False],\n", + " [False, False, False, ..., False, False, False],\n", + " ...,\n", + " [False, False, False, ..., False, False, False],\n", + " [False, False, False, ..., False, False, False],\n", + " [False, False, False, ..., False, False, False]])" + ] + }, + "execution_count": 351, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fdr" + ] + }, + { + "cell_type": "code", + "execution_count": 326, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([[ True, True, True, ..., True, True, True],\n", + " [ True, True, True, ..., True, True, True],\n", + " [ True, True, True, ..., True, True, True],\n", + " ...,\n", + " [ True, True, True, ..., True, True, True],\n", + " [ True, True, True, ..., True, True, True],\n", + " [False, False, False, ..., True, False, False]]),\n", + " array([[0.55911574, 0.27955787, 0.18637191, ..., 0.0452669 , 0.20294128,\n", + " 0.01553099],\n", + " [1. , 1. , 1. , ..., 0.0452669 , 0.88390054,\n", + " 0.43333141],\n", + " [0.55911574, 0.27955787, 1. , ..., 0.0452669 , 0.20294128,\n", + " 0.01553099],\n", + " ...,\n", + " [1. , 0.27955787, 1. , ..., 0.0452669 , 0.20294128,\n", + " 0.43333141],\n", + " [1. , 0.27955787, 1. , ..., 0.0452669 , 0.20294128,\n", + " 0.43333141],\n", + " [1. , 1. , 1. , ..., 0.0452669 , 0.88390054,\n", + " 0.58816355]]),\n", + " 0.0014237991678133222,\n", + " 0.001388888888888889)" + ] + }, + "execution_count": 326, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fdr" + ] + }, + { + "cell_type": "code", + "execution_count": 194, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(21, 1296)\n" + ] + } + ], + "source": [ + "vecSes2 = []\n", + "for mat in cor_OneSes2:\n", + " vec = mat.flatten()\n", + " vecSes2.append(vec)\n", + "vecSes2 = np.array(vecSes2)\n", + "print(vecSes2.shape)\n", + "from sklearn.decomposition import PCA\n", + "pca = PCA(n_components=2)\n", + "X_r = pca.fit(vecSes2).transform(vecSes2)" + ] + }, + { + "cell_type": "code", + "execution_count": 195, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "explained variance ratio (first two components): [0.19413337 0.12311924]\n" + ] + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "print('explained variance ratio (first two components): %s'\n", + " % str(pca.explained_variance_ratio_))\n", + "colors = ['navy', 'orange']\n", + "lw = 2\n", + "y = np.array(group_label) # make it an array so we can get mask for each place\n", + "target_names = ['Midazolam','Ketamine']\n", + "for color, i, target_name in zip(colors, [0, 1], target_names):\n", + " plt.scatter(X_r[y == i, 0], X_r[y == i, 1], color=color, alpha=.8, lw=lw,\n", + " label=target_name)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Lets just look at the trauma features\n", + "for mat in cor_OneSes2:\n", + " " + ] + } + ], + "metadata": { + "celltoolbar": "Slideshow", + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/.ipynb_checkpoints/RSA_seperate_sessions-checkpoint.ipynb b/task_based_analysis/.ipynb_checkpoints/RSA_seperate_sessions-checkpoint.ipynb new file mode 100644 index 0000000..4b3ae25 --- /dev/null +++ b/task_based_analysis/.ipynb_checkpoints/RSA_seperate_sessions-checkpoint.ipynb @@ -0,0 +1,692 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + " # Map beta of each condition and correlate between groups\n", + " - Mask for amygdala, vmPFC, hippocampus and caudate\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [], + "source": [ + "# import relevant packages\n", + "import glob\n", + "import numpy as np\n", + "import scipy\n", + "import nilearn\n", + "import nilearn.plotting\n", + "import nilearn.input_data\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import statsmodels.stats as sm # for FDR correction\n", + "import dask # for paralleliz" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [], + "source": [ + "#thr = 0.05 # set threshold\n", + "def fdr_corr(p, thr=0.05):\n", + " import statsmodels.stats.multitest as sm\n", + " # FDR correction\n", + " # takes the p from the t test, flatten and return a 36x36 mask\n", + " # flatten p\n", + " ptri = np.tril(p)\n", + " pflat = ptri.flatten()\n", + " fdr = sm.multipletests(pflat, alpha=thr, method='fdr_bh')\n", + " fdrArr = fdr[0].reshape(9,9)\n", + " return fdrArr " + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Amygdala as mask\n", + "mask_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=21\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "\n", + "\n", + "maskerAmg = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " smoothing_fwhm=None, verbose=0).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# now lets do the same with vmPFC\n", + "mask_file = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=6\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "maskervmPFC = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " smoothing_fwhm=None,\n", + " verbose=0).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Run same with hippocampus\n", + "## Hippocampus\n", + "mask_file = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=15\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "maskerHipp = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " smoothing_fwhm=None,\n", + " verbose=0).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/caudate_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "maskerCaudate = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " smoothing_fwhm=None, \n", + " verbose=0).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['KPE008', 'KPE1223', 'KPE1253', 'KPE1263', 'KPE1293', 'KPE1307',\n", + " 'KPE1315', 'KPE1322', 'KPE1339', 'KPE1343', 'KPE1351', 'KPE1356',\n", + " 'KPE1364', 'KPE1369', 'KPE1387', 'KPE1390', 'KPE1403', 'KPE1464',\n", + " 'KPE1468', 'KPE1480', 'KPE1499'], dtype=object)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# compare between groups\n", + "import pandas as pd\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "medication_cond\n", + "\n", + "group_label = np.array(medication_cond.med_cond)\n", + "#group_label = list(map(int, group_label))\n", + "\n", + "sub_list = np.array(medication_cond.scr_id)\n", + "sub_list" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "subject_list = []\n", + "for sub in sub_list:\n", + " sub = sub.split('KPE')[1]\n", + " subject_list.append(sub)\n", + "#subject_list.remove('1390')" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "# function to find ev number (lookin in run.fsf file)\n", + "def findEV(txtFile, condition):\n", + " # takes the txtFile and the specific condition\n", + " with open(txtFile) as f:\n", + " datafile = f.readlines()\n", + " lines = []\n", + " for line in datafile:\n", + " if condition in line:\n", + " # found = True # Not necessary\n", + " #print(line)\n", + " lines.append(line)\n", + "\n", + " return lines[0].split('evtitle')[1].split(')')[0]\n", + "\n", + "def getCorr(sub, condition, masker):\n", + " # takes subject, condition (relax, trauma, sad) and masker object\n", + " fsf_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/allScript_ses{ses}_Nosmooth/modelfit_ses_{ses}/_subject_id_{sub}/level1design/run0.fsf'\n", + " betaTemplate = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/allScript_ses{ses}_Nosmooth/modelfit_ses_{ses}/_subject_id_{subject_id}/modelestimate/mapflow/_modelestimate0/results/pe{betaNum}.nii.gz'\n", + "\n", + " # get beta files for session 1 condition X\n", + " beta1 = fsf_template.format(ses='1', sub=sub)\n", + " number_1 = findEV(beta1, condition)\n", + " # find beta file\n", + " betaFile_1 = betaTemplate.format(ses='1', subject_id = sub, betaNum = number_1)\n", + " beta1_transform = masker.transform(betaFile_1)\n", + " # get beta files for session 2 condition X\n", + " beta2 = fsf_template.format(ses='2', sub=sub)\n", + " number_2 = findEV(beta2, condition)\n", + " # find beta file\n", + " betaFile_2 = betaTemplate.format(ses='2', subject_id = sub, betaNum = number_2)\n", + " beta2_transform = masker.transform(betaFile_2)\n", + "\n", + " #correlate it\n", + " cor = scipy.stats.pearsonr(beta1_transform[0], beta2_transform[0])[0]\n", + " return cor, beta1_transform, beta2_transform\n", + "\n", + "def generatCor(cond_list, beta1Arr, beta2Arr):\n", + " # this functuion creates a simple matrix of correlation between session 1 and 2\n", + " x = np.zeros([len(cond_list),len(cond_list)])\n", + " for i, cond in enumerate(cond_list):\n", + " \n", + " for j, c in enumerate(cond_list):\n", + " x[i,j] = scipy.stats.pearsonr(beta1Arr[i], beta2Arr[j])[0]\n", + " return x" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "# get condition list\n", + "events_file = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/sub-1464_ses-1.csv'\n", + "cond = pd.read_csv(events_file, sep='\\t')\n", + "cond_list = np.unique(cond.trial_type_N)\n", + "#cond_list" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Lets try another thing - Using RSA for the same scan. \n", + "- Hypothesis here will say Ketamine will be fatster to recover, hence lower correlation in trauma" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 0 subject\n", + " Running the 1 subject\n", + " Running the 2 subject\n", + " Running the 3 subject\n", + " Running the 4 subject\n", + " Running the 5 subject\n", + " Running the 6 subject\n", + " Running the 7 subject\n", + " Running the 8 subject\n", + " Running the 9 subject\n", + " Running the 10 subject\n", + " Running the 11 subject\n", + " Running the 12 subject\n", + " Running the 13 subject\n", + " Running the 14 subject\n", + " Running the 15 subject\n", + " Running the 16 subject\n", + " Running the 17 subject\n", + " Running the 18 subject\n", + " Running the 19 subject\n", + " Running the 20 subject\n" + ] + } + ], + "source": [ + "cor_OneSes1_amg = []\n", + "cor_OneSes1_vmPFC = []\n", + "cor_OneSes1_hippo = []\n", + "cor_OneSes1_caudate = []\n", + "cor_OneSes2_amg = []\n", + "cor_OneSes2_vmPFC = []\n", + "cor_OneSes2_hippo = []\n", + "cor_OneSes2_caudate = []\n", + "\n", + "for i, sub in enumerate(subject_list):\n", + " print (f' Running the {i} subject')\n", + " beta1Arr_amg = []\n", + " beta2Arr_amg = []\n", + " beta1Arr_hipp = []\n", + " beta2Arr_hipp = []\n", + " beta1Arr_vmPFC = []\n", + " beta2Arr_vmPFC = []\n", + " beta1Arr_caudate = []\n", + " beta2Arr_caudate = []\n", + " conditions = []\n", + " for cond in cond_list:\n", + " cor, beta1amg, beta2amg = getCorr(sub, cond, maskerAmg)\n", + " cor, beta1hipp, beta2hipp = getCorr(sub, cond, maskerHipp)\n", + " cor, beta1vmPFC, beta2vmPFC = getCorr(sub, cond, maskervmPFC)\n", + " cor, beta1caudate, beta2caudate = getCorr(sub, cond, maskerCaudate)\n", + " conditions.append(cond)\n", + " beta1Arr_amg.append(beta1amg[0])\n", + " beta2Arr_amg.append(beta2amg[0])\n", + " beta1Arr_hipp.append(beta1hipp[0])\n", + " beta2Arr_hipp.append(beta2hipp[0])\n", + " beta1Arr_vmPFC.append(beta1vmPFC[0])\n", + " beta2Arr_vmPFC.append(beta2vmPFC[0])\n", + " beta1Arr_caudate.append(beta1caudate[0])\n", + " beta2Arr_caudate.append(beta2caudate[0])\n", + " corMat1amg = np.corrcoef(beta1Arr_amg)\n", + " corMat2amg = np.corrcoef(beta2Arr_amg)\n", + " corMat1hipp = np.corrcoef(beta1Arr_hipp)\n", + " corMat2hipp = np.corrcoef(beta2Arr_hipp)\n", + " corMat1vmPFC = np.corrcoef(beta1Arr_vmPFC)\n", + " corMat2vmPFC = np.corrcoef(beta2Arr_vmPFC)\n", + " corMat1caudate = np.corrcoef(beta1Arr_caudate)\n", + " corMat2caudate = np.corrcoef(beta2Arr_caudate)\n", + " cor_OneSes2_amg.append(corMat2amg)\n", + " cor_OneSes1_amg.append(corMat1amg)\n", + " cor_OneSes2_caudate.append(corMat2caudate)\n", + " cor_OneSes1_caudate.append(corMat1caudate)\n", + " cor_OneSes2_hippo.append(corMat2hipp)\n", + " cor_OneSes1_hippo.append(corMat1hipp)\n", + " cor_OneSes2_vmPFC.append(corMat2vmPFC)\n", + " cor_OneSes1_vmPFC.append(corMat1vmPFC)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "def plotRSA(arrGroup, cond_list):\n", + " # separate groups\n", + " groupArr = np.array(arrGroup)\n", + " #print('Running t test')\n", + " group1 = groupArr[group_label==1]\n", + " group2 = groupArr[group_label==0]\n", + " # plot mean matrices\n", + " fig, ax_list = plt.subplots(1, 2, figsize=(16,4.5))\n", + " ax = ax_list[0]\n", + " ax.title.set_text('Ketamine')\n", + " sns.heatmap(np.mean(group1, axis=0), cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax)#,\n", + " #vmin = -1, vmax=1)\n", + " ax = ax_list[1]\n", + " ax.title.set_text('Midazolam')\n", + " sns.heatmap(np.mean(group2, axis=0), cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax)#,\n", + " #vmin = -1, vmax=1)\n", + " plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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BAwfWORuRJLWIkxK1m9ksSZNnobO5fxDyA8AhwFpgZZLTquqSgc1eAVxSVc9Kcj/g8iQnVdXvZtvv2M6MSpImQ1euS5EkaVKMIZsPANZU1RUASU4GDgMGm9ECturf03oZ8AvgjmE7tRmVJI3GM6OSJLXLPLM5yXJg+cCiFf0Z0NfbAbhm4PVapo6QAXg/vVuAXQdsBfzJbLOrr2czKkkaiWdGJUlql/lm8+Ctt2bb5Uxvm/b6D+jNNXAw8GDg35N8vap+NdtOPZwtSRpJsmReD0mSNF5jyOa1wE4Dr3ekdwZ00NHAZ6tnDfAj4GHDduq/CiRJo1mS+T02QpJDk1yeZE2S42ZYv02S05N8L8nqJEcv+PeSJKmrFj6bVwK7Jdm1f0uv59EbkjvoauDJAEkeAOwOXDFspw7TlSSNpCsz9kmSNCkWOpur6o4kx9K7X/VS4ISqWp3kmP7644E3AycmuYjesN6/7M/QPiubUUnSSLoyY58kSZNiHPM5VNWZwJnTlh0/8Pw64Knz2edENKNrL7+q6RLu8u9/f17TJWzgkP9336ZLmOIt136p6RKm+Nv/eXXTJUyzW9MFTHHWKe26r/13992n6RKm+F8v+EXTJYzfwl8HOpYZ+9Qu11xzS9Ml3GWzz17WdAlTPOSPhl5i1YgPvOM7TZcwxcv/8CdNlzDF1Qc9qOkSprj80hubLmGK227brukSpnjV83/WdAnj15E5GrpRpcambY2opO7JkszvkSxPsmrgsXz6Lmf4mNlm7Nse2Ad4f5Ktx/D1JEnqnPlmc1Mm4syoJGl8snTpvLbfiOnjN3bGvrdXVQFrkqyfsa9dp28kSWrAfLO5KZ4ZlSSNZsmS+T3mNpYZ+yRJmhgLn81j4ZlRSdJIFnp4z7hm7JMkaVI0OfR2PmxGJUmjGcMkCeOYsU+SpInRkQmMbEYlSaPpyNFXSZImRkey2WZUkjSSdOToqyRJk6Ir2WwzKkkaTUeOvkqSNDE6ks02o5KkkaTBWfgkSdKGupLNNqOSpNGkG0dfJUmaGB3J5kZa5iQ338337ZzkvCQXJLlrmn9JUoM6ci8zDWc2S9ImpCPZPLYzo0kCpKrWLeBufwz8j6q6Lcky4OIkp/Wn+JckNaEjR19lNkvSxOhINi9oG5xklySXJvkg8F3gdUlWJrkwyd/OsP2yJF9K8t0kFyU5rL98//57tkhyr/6R1j2r6ndVdVv/7f9toeuXJM1fliyZ10OLy2yWpMnTlWwex5nR3YGjgVOBw4EDgACnJfn9qvrawLa/BZ5TVb9Kcl/g3P7R1JVJTgPeAmwJfKKqLgZIshPwBeAhwF945FWSGtaR6eMnnNksSZOkI9k8jiqvqqpzgaf2H+fTOxL7MGC3adsGeGuSC4H/AHYAHtBf9ybgEGA/4J3r31BV11TVXvQC78VJHsAMkixPsirJqh//6PML9uUkSdMsyfweakLrsvmib56wYF9OkjRNR7J5HGdGb+n/DPC2qvqnIdseCdwP2Leqbk9yJbBFf919gGXA5v1ltwy+saquS7IaeDxwyvQdV9UKYAXAE/7onLrb30aSNFRXbqw94VqXzf/7/95sNkvSmHQlm8dZ5dnAS/qTGZBkhyT3n7bNNsD1/bB7ErDzwLoVwOuAk4B39PexY5It+8/vDTwWuHyM30GSNJeOHH0VYDZL0mToSDaPbTbdqvpikocD3+pN3sfNwAuA6wc2Owk4Pckq4ALgMoAkLwLuqKpPJlkKnJPkYGAp8J4kRe/o7rur6qJxfQdJ0kboyNFXmc2SNDE6ks0L2oxW1ZXAngOv3we8b4btlvV/3gAcNMOurgQ+1t/mTuDAgXV7LVjBkqTRdWT6+EllNkvSBOpINo/tzKgkaUJ4uxZJktqlI9lsMypJGk1HhgJJkjQxOpLNNqOSpNE4KZEkSe3SkWy2GZUkjWbJ0qYrkCRJgzqSzTajkqTRdOS6FEmSJkZHstlmVJI0mo7M2CdJ0sToSDbbjEqSRtORSRIkSZoYHclmm1FJ0mg6MhRIkqSJ0ZFsnohm9FV/deDcGy2Sh977p02XMMVbrv1S0yVs4Mj3PLnpEqb4510uaLqEKVZ++TtNlzDFIX+8X9MlTHH5FXc0XcIUJ3zo6qZLmOKLH99u4XfakaFAapcjDrmz6RLustXm1zVdwhQfeEe7fs8DPO0vD2i6hCnOeNClTZcwxdVX/qrpEqbYfsetmi5hiq2Wtasx+sRXtm26hCne/pAx7LQj2TwRzagkaYw6MhRIkqSJ0ZFsthmVJI2mI0dfJUmaGB3JZptRSdJoOnJdiiRJE6Mj2WwzKkkaSXXk6KskSZOiK9lsMypJGk1HrkuRJGlidCSbbUYlSaPpSOBJkjQxOpLNNqOSpJF0ZSiQJEmToivZbDMqSRpNR46+SpI0MTqSzTajkqTRdOToqyRJE6Mj2dz6ljnJLkku7j/fLslXktyc5P1N1yZJojd9/Hwe6jyzWZJariPZ3LV/FfwWeB3w6qYLkST1VDKvhzY5ZrMktcw4sjnJoUkuT7ImyXGzbPPEJBckWZ3kP+fa56IN001yL+DTwI7AUuDNwO7As4AtgXOAl1VVJdkXOAG4FfjG+n1U1S3AN5I8ZLHqliTNoSPXpWhDZrMkbaIWOJuTLAU+ABwCrAVWJjmtqi4Z2GZb4IPAoVV1dZL7z7XfxfwXxKHAdVW1d1XtCZwFvL+q9u+/3hJ4Zn/bjwCvrKqDFrE+SdLdUFkyr4daxWyWpE3QGLL5AGBNVV1RVb8DTgYOm7bNEcBnq+pqgKq6fq6dLua/Ci4CnpLkHUkeX1U3AU9K8u0kFwEHA49Isg2wbVWtP6378bvzYUmWJ1mVZNUXP/fPC/MNJEkbSub3UJs0ls2f+/SJC/IFJEkzmGc2D/5+7j+WT9vjDsA1A6/X9pcNeihw7yRfTXJekhfNVeaiDdOtqu/3h/g8HXhbki8CrwD2q6prkrwR2AIIUAvweSuAFQCnrrxz5P1Jkmbm2c7uajKbv3PZTWazJI3JfLN58PfzLGY6mjz99/hmwL7Ak+mNrPlWknOr6vuz7XTR/gWRZHvg1qr6BPBu4NH9VTckWQYcDlBVvwRuSvK4/vojF6tGSdLd4JnRzjKbJWkTtfDZvBbYaeD1jsB1M2xzVlXdUlU3AF8D9h6208W8z+gjgXclWQfcDrwceDa9IUJXAisHtj0aOCHJrcDZgztJciWwNXCPJM8Gnjp44awkaXHVkqVNl6C7z2yWpE3QGLJ5JbBbkl2Ba4Hn0btGdNDngfcn2Qy4B3Ag8N5hO13MYbpnMy28gFXA38yw7XlM7aLfOLBulzGUJ0m6uxym21lmsyRtohY4m6vqjiTH0suMpcAJVbU6yTH99cdX1aVJzgIuBNYBH66qi4ftdzHPjEqSNkE142UkkiSpKePI5qo6Ezhz2rLjp71+F/Cujd2nzagkaSROYCRJUrt0JZttRiVJo+lI4EmSNDE6ks02o5KkkZQz5EqS1CpdyeZutMySpNaqLJnXY2MkOTTJ5UnWJDlulm2emOSCJKuT/OeCfilJkjpsHNk8Dp4ZlSSNZoGPviZZCnwAOITePctWJjlt8FYhSbYFPggcWlVXJ7n/ghYhSVKXdeTMqM2oJGkkYziiegCwpqquAEhyMnAYMHjfyiOAz1bV1QBVdf1CFyFJUld1ZQKjblQpSWqtIvN6bIQdgGsGXq/tLxv0UODeSb6a5LwkL1qgryNJUueNIZvHYiLOjJ76hRuaLuEuez3qgU2XMMXf/s+rmy5hA/+8ywVNlzDFE/58n6ZLmOLXb/120yVMsfqCnzRdwhTvOurnTZcwxRZb7N10CWM336OvSZYDywcWraiqFYObzPQx015vBuwLPBnYEvhWknOr6vvzKkaNOeHz65ou4S5PeNz2TZcwxcv/sF2/VwHOeNClTZcwxZ7Pf3jTJUzx/dd/o+kSpvjd79rz/xfAM3b/YdMlTHHyzbs2XcLYdeXM6EQ0o5KkMZrndSn9xnPFkE3WAjsNvN4RuG6GbW6oqluAW5J8DdgbsBmVJKkj14x2o2WWJLVWsWRej42wEtgtya5J7gE8Dzht2jafBx6fZLMk9wQOBNp16kaSpIaMIZvHwjOjkqSRLPS9zKrqjiTHAmcDS4ETqmp1kmP664+vqkuTnAVcCKwDPlxVFy9oIZIkdVRX7jNqMypJGsk4rkupqjOBM6ctO37a63cB71rwD5ckqeO8ZlSSNBGanIVPkiRtqCvZbDMqSRpJV46+SpI0KbqSzTajkqSRdOW6FEmSJkVXstlmVJI0kq4MBZIkaVJ0JZttRiVJI+nKUCBJkiZFV7LZZlSSNJKuHH2VJGlSdCWbW98yJ9klycX954ckOS/JRf2fBzddnyRNunVZOq+Hus9slqR260o2d+3M6A3As6rquiR70rsh+g4N1yRJE60rQ4E0NmazJLVMV7J50ZrRJPcCPg3sCCwF3gzsDjwL2BI4B3hZVVWSfYETgFuBb6zfR1WdP7DL1cAWSf5bVd22ON9CkjRdV4YCaUNmsyRtmrqSzYvZMh8KXFdVe1fVnsBZwPurav/+6y2BZ/a3/Qjwyqo6aMj+/hg4f7awS7I8yaokq75/3scX8GtIkgZVMq+HWqWxbL7k2ycu3LeQJE3RlWxezGb0IuApSd6R5PFVdRPwpCTfTnIRcDDwiCTbANtW1X/237dBJ5nkEcA7gJfN9mFVtaKq9quq/R667wsX/ttIkgCoyrweapXGsnmPA49a8C8jSerpSjYv2jDdqvp+f4jP04G3Jfki8Apgv6q6JskbgS2AADXbfpLsCHwOeFFV/XD8lUuShqn2z4WnWZjNkrRp6ko2L1qVSbYHbq2qTwDvBh7dX3VDkmXA4QBV9UvgpiSP668/cmAf2wJfAP6qqr65WLVLkmZXZF4PtYfZLEmbpq5k82LOpvtI4F1J1gG3Ay8Hnk1viNCVwMqBbY8GTkhyK71Z+dY7FngI8Lokr+sve2pVXT/m2iVJs7DB7DSzWZI2QV3J5sUcpns2U8MLYBXwNzNsex6w98CiN/aXvwV4y5hKlCTdDV0JPG3IbJakTVNXsrlr9xmVJLVMVwJPkqRJ0ZVsthmVJI3EGXIlSWqXrmSzzagkaSRdOfoqSdKk6Eo224xKkkbSlcCTJGlSdCWbbUYlSSPpSuBJkjQpupLNNqOSpJF05boUSZImRVey2WZUkjSSdR05+ipJ0qToSjZPRDO65rzLmi7hLr+8/qamS5hmt6YL2MDKL3+n6RKm+PVbv910CVM887UHNl3CFO981keaLmGK/3X8A5suYYoPvbRd//3AQQu+x64MBVK7rF3z46ZLuMvnWpbNVx/0oKZL2MDVV/6q6RKm+P7rv9F0CVP80Zse13QJU7z38JOaLmGKX/z8IU2XMMVxz1nTdAnT7L7ge+xKNk9EMypJGp+uDAWSJGlSdCWbbUYlSSPpytFXSZImRVey2WZUkjSSrhx9lSRpUnQlm5c0XYAkqduKzOshSZLGaxzZnOTQJJcnWZPkuCHb7Z/kziSHz7VPz4xKkkbSlaOvkiRNioXO5iRLgQ8AhwBrgZVJTquqS2bY7h3A2RuzX5tRSdJI7rQZlSSpVcaQzQcAa6rqCoAkJwOHAZdM2+7Pgc8A+2/MTm1GJUkjceitJEntMoZs3gG4ZuD1WmDK/QaT7AA8BzgYm1FJ0mJwmK4kSe0y32xOshxYPrBoRVWtGNxkpo+Z9vofgL+sqjuTjft8m1FJ0kg8MypJUrvMN5v7jeeKIZusBXYaeL0jcN20bfYDTu43ovcFnp7kjqo6dbad2oxKkkaybvpxUUmS1KgxZPNKYLckuwLXAs8DjhjcoKp2Xf88yYnAGcMaUejArV2S7JLk4v7zA5Jc0H98L8lzmq5Pkiadt3aZPGazJLXbQmdzVd0BHEtvltxLgU9X1eokxyQ55u7W2bUzoxcD+1XVHUkeCHwvyen9PxxJUgO8ZnTimc2S1DLjyOaqOhM4c9qy42fZ9qiN2eeiNaNJ7gV8mt744qXAm4HdgWcBWwLnAC+rqkqyL3ACcCvwjfX7qKpbB3a5BRteNCtJWmTlb+LOMpsladPUlWxezGG6hwLXVdXeVbUncAQzoJ8AAB8zSURBVBbw/qrav/96S+CZ/W0/Aryyqg6avpMkByZZDVwEHDPbkdcky5OsSrLqJ1edPpYvJEmCdWReD7VKY9l89WWfHssXkiR1J5sXsxm9CHhKknckeXxV3QQ8Kcm3k1xE7340j0iyDbBtVf1n/30fH9xJVX27qh5B7941f5Vki5k+rKpWVNV+VbXf7+38rPF9K0macFWZ10Ot0lg2P+hhzx3ft5KkCdeVbF60YbpV9f3+EJ+nA29L8kXgFfSuM7kmyRvpDe8JGzHEp6ouTXILsCewanyVS5KG6cpQIG3IbJakTVNXsnnRzowm2R64tao+AbwbeHR/1Q1JlgGHA1TVL4Gbkjyuv/7IgX3smmSz/vOd6V3XcuXifANJ0kycTbe7zGZJ2jR1JZsXczbdRwLvSrIOuB14OfBsekOErqR375r1jgZOSHIrvemD13sccFyS24F1wJ9V1Q2LULskaRbeZ7TTzGZJ2gR1JZsXc5ju2UwNL+gN4fmbGbY9D9h7YNEb+8s/zrTrVCRJzfI60O4ymyVp09SVbO7afUYlSS3TletSJEmaFF3JZptRSdJIvF2LJEnt0pVsthmVJI2kK0dfJUmaFF3J5sW8z6gkaRM0jnuZJTk0yeVJ1iQ5bsh2+ye5M8nhC/aFJEnqOO8zKkmaCAs9Y1+SpcAHgEOAtcDKJKdV1SUzbPcONpyAR5KkidaV2XQ9MypJGknV/B4b4QBgTVVdUVW/A04GDpthuz8HPgNcv2BfRpKkTcAYsnksPDMqSRrJGG6WvQNwzcDrtcCBgxsk2QF4DnAwsP9CFyBJUpeNIZvHYiKa0ff//R5Nl3CXE8/asukSpjjrlAuaLmEDh/zxfk2XMMXqC37SdAlTvPNZH2m6hClec/rRTZcwxade85WmS5jiyHe16//5sz+68Pu8c938tk+yHFg+sGhFVa0Y3GSGt00/bvsPwF9W1Z1JNwJXU735NfdvuoS7fOWS7ZouYYrLL72x6RI2sP2OWzVdwhS/+908f/GM2XsPP6npEqZ41SlHNl3CFGc8+ttNlzDFka9q17/tvnH67gu+z/lmc1MmohmVJI3PfIf39BvPFUM2WQvsNPB6R+C6advsB5zcb0TvCzw9yR1Vder8qpEkadPTldl0bUYlSSNZt/Cz8K0EdkuyK3At8DzgiMENqmrX9c+TnAicYSMqSVLPGLJ5LGxGJUkjWeijr1V1R5Jj6c2SuxQ4oapWJzmmv/74hf1ESZI2LZ4ZlSRNhHEEXlWdCZw5bdmMTWhVHbXwFUiS1F02o5KkidCVe5lJkjQpupLNNqOSpJFUR65LkSRpUnQlm21GJUkj6cpQIEmSJkVXstlmVJI0kq4MBZIkaVJ0JZttRiVJI+nK0VdJkiZFV7LZZlSSNJKuBJ4kSZOiK9m8ZNjKJNsm+bPFKmYuSY5NsiZJJblv0/VIknpDgebz0GjMZknSXLqSzUObUWBbYIPAS7J0POXM6ZvAU4CrGvp8SdI0VfN7aGRmsyRpqK5k81zDdN8OPDjJBcDtwM3Aj4F9gD2SnArsBGwBvK+qVgAkubmqlvWfHw48s6qOSnIi8BvgYcDOwNHAi4GDgG+vv3F5kg8B+wNbAqdU1RsAqur8/voF+fKSpNGtW9d0BRPHbJYkDdWVbJ7rzOhxwA+rah/gL4ADgL+uqj36619SVfsC+wGvTLLdRnzmvYGDgVcBpwPvBR4BPDLJPv1t/rqq9gP2Ap6QZK/5fCmAJMuTrEqy6jMnf2y+b5ckbaSuHH3dhJjNkqShupLN853A6DtV9aOB169M8pz+852A3YCfz7GP06uqklwE/LSqLgJIshrYBbgAeG6S5f36HgjsAVw4n0L7R4JXAFzwg5/5zx9JGhMbzMZ1MpvP/8EN/pcjSWPSlWyebzN6y/onSZ5I7xqRg6rq1iRfpTckCGDw62/BVLf1f64beL7+9WZJdgVeDexfVTf2hw9N34ckqSWclKhxZrMkaYquZPNcw3R/DWw1y7ptgBv7Yfcw4DED636a5OFJlgDPmfnts9qaXrDelOQBwNPm+X5J0iKqqnk9NDKzWZI0VFeyeWgzWlU/B76Z5GLgXdNWn0XvaOmFwJuBcwfWHQecAXyZ3qQKG62qvgecD6wGTqA3Sx8ASV6ZZC2wI3Bhkg/PZ9+SpIXXletSNhVmsyRpLl3J5jmH6VbVEbMsv41ZjoxW1SnAKTMsP2rg+ZXAnrOsO4oZVNU/Av84V82SpMXTlRn7NiVmsyRpmK5k83yvGZUkaQrPdkqS1C5dyWabUUnSSLoySYIkSZOiK9lsMypJGsm6O+ebeBlLHZIkqacr2WwzKkkaSVeOvkqSNCm6ks02o5KkkXTluhRJkiZFV7J5rvuMSpI01Lp1Na+HJEkar3Fkc5JDk1yeZE2S42ZYf2SSC/uPc5LsPdc+PTMqSRpJV46+SpI0KRY6m5MsBT4AHAKsBVYmOa2qLhnY7EfAE6rqxiRPA1YABw7b70Q0o+8+8famS7jL61/ym6ZLmOK7++7TdAkbuPyKO5ouYYp3HfXzpkuY4n8d/8CmS5jiU6/5StMlTPH8dz6p6RKm+Nwbv9l0CWNnM6q741NfulfTJdzlBU/+WdMlTHHbbds1XcIGtlrWrsF0z9j9h02XMMUvfv6QpkuY4oxHf7vpEqZ45muH9iOLbov3ntd0CWM3hmw+AFhTVVcAJDkZOAy4qxmtqnMGtj8X2HGunU5EMypJGp91dqOSJLXKfLM5yXJg+cCiFVW1YuD1DsA1A6/XMvys50uBf5vrc21GJUkjqXVNVyBJkgbNN5v7jeeKIZvMdO+XGTveJE+i14w+bq7PtRmVJI2kPDMqSVKrjCGb1wI7DbzeEbhu+kZJ9gI+DDytqua81s1mVJI0knWeGZUkqVXGkM0rgd2S7ApcCzwPOGJwgyQPAj4LvLCqvr8xO7UZlSSNxDOjkiS1y0Jnc1XdkeRY4GxgKXBCVa1Ockx//fHA64HtgA8mAbijqvYbtl+bUUnSSLx1qCRJ7TKObK6qM4Ezpy07fuD5nwJ/Op992oxKkkZSdqOSJLVKV7LZZlSSNBJH6UqS1C5dyWabUUnSSNZ15OirJEmToivZbDMqSRqJExhJktQuXcnmJcNWJtk2yZ8tVjFzSXJSksuTXJzkhCSbN12TJE26Wje/h0ZjNkuS5tKVbB7ajALbAhsEXpKl4ylnTicBDwMeCWzJPGdrkiQtvHVV83poZGazJGmormTzXMN03w48OMkFwO3AzcCPgX2APZKcCuwEbAG8r6pWACS5uaqW9Z8fDjyzqo5KciLwG3qhtTNwNPBi4CDg21V1VP89HwL2pxdqp1TVG+Cu6YTpb/MdYMdR/wAkSaPpylCgTYjZLEkaqivZPNeZ0eOAH1bVPsBfAAcAf11Ve/TXv6Sq9gX2A16ZZLuN+Mx7AwcDrwJOB94LPAJ4ZJJ9+tv8df8GqXsBT0iy1+AO+kOAXgicNduHJFmeZFWSVT84/xMbUZYk6e5Yt67m9dDINols/t7X/2Ujv64kab66ks1zNaPTfaeqfjTw+pVJvgecS+8o7G4bsY/Tq9eqXwT8tKouqqp1wGpgl/42z03yXeB8emG4x7R9fBD4WlV9fbYPqaoVVbVfVe2326NesDHfTZJ0N1TN76EF18ls3vvxL92Y7yZJuhu6ks3znU33lvVPkjwReApwUFXdmuSr9IYEAQx+pS2Y6rb+z3UDz9e/3izJrsCrgf2r6sb+8KG79pHkDcD9gJfNs3ZJ0hjceaezEjXMbJYkTdGVbJ7rzOivga1mWbcNcGM/7B4GPGZg3U+TPDzJEuA586xpa3rBelOSBwBPW78iyZ8CfwA8v3/EVpLUsFpX83poZGazJGmormTz0DOjVfXzJN9McjG9yQ1+OrD6LOCYJBcCl9MbDrTeccAZwDXAxcCyjS2oqr6X5Hx6Q4OuAL45sPp44CrgW0kAPltVb9rYfUuSFp4N5uIymyVJc+lKNs85TLeqjphl+W0MHBmdtu4U4JQZlh818PxKYM9Z1h3FDKpqvsOKJUlj1pG826SYzZKkYbqSzQaIJGkkXTn6KknSpOhKNtuMSpJG0pV7mUmSNCm6ks02o5KkkXjvUEmS2qUr2WwzKkkaSVeOvkqSNCm6ks1z3dpFkqShxjF9fJJDk1yeZE2S42ZYf2SSC/uPc5LsveBfTJKkjtokbu0iSdJcFjrEkiwFPgAcAqwFViY5raouGdjsR8ATqurGJE8DVgAHLmghkiR1lBMYSZImwrqFHwp0ALCmqq4ASHIycBhwVzNaVecMbH8usONCFyFJUleNIZvHYiKa0Wt/cE3TJQx4IH/30Xs0XcRdnnYoPPS+v2i6jCkuv2Jrvnn2xU2XcZf/uf9SPn7RnnNvuGiu4kMv/UnTRdzlf39qZ3629vqmy5jic2/8ZtMlTPGcNz626RL+y19fvuC7nO/R1yTLgeUDi1ZU1YqB1zsAg7+41zL8rOdLgX+bVxFq3HXX3Nh0CQM2430np+ki7vKQ3eFZj/5Z02VM8dXvP4C1197WdBn/ZXc4+bxdm65iwK857jk/bbqIu7z9cw/goq99r+ky7vJM4D/ee17TZUzxlFft23QJ/+XY5rO5KRPRjLZJmxpRaF8jCrSqEQVa1ojSqkYUsBGdQ6sa0TGZ7yQJ/cZzxZBNZuoKZvyQJE+i14w+bl5FSAPa1IhC+xpRoF2NKG1rRGlVIwq0qhEFG9EmdGUCI5tRSdJIxjB9/Fpgp4HXOwLXTd8oyV7Ah4GnVdXPF7oISZK6ylu7SJImwhiGAq0EdkuyK3At8DzgiMENkjwI+Czwwqr6/kIXIElSlzlMV5I0ERZ6KFBV3ZHkWOBsYClwQlWtTnJMf/3xwOuB7YAPJgG4o6r2W9BCJEnqKIfpSpImQq1bt/D7rDoTOHPasuMHnv8p8KcL/sGSJG0CxpHN42AzKkkaSVeuS5EkaVJ0JZttRiVJI+nKUCBJkiZFV7LZZlSSNJKuTJIgSdKk6Eo224xKkkbSlcCTJGlSdCWbbUYlSSNZV92YJEGSpEnRlWxeMmxlkm2T/NliFTOXJP+S5HtJLkxySpJlTdckSZNu3R3r5vXQaMxmSdJcupLNQ5tRYFtgg8BLsnQ85czpVVW1d1XtBVwNHNtQHZKkvqqa10MjM5slSUN1JZvnGqb7duDBSS4AbgduBn4M7APskeRUYCdgC+B9VbUCIMnNVbWs//xw4JlVdVSSE4HfAA8DdgaOBl4MHAR8u6qO6r/nQ8D+wJbAKVX1BoCq+lV/ffrr/FeNJDVsXUfuZbYJMZslSUN1JZvnakaPA/asqn2SPBH4Qv/1j/rrX1JVv0iyJbAyyWeq6udz7PPewMHAHwKnA4+ld+PylUn2qaoLgL/u73cp8KUke1XVhQBJPgI8HbgE+D/z/saSpAXVlUkSNiFmsyRpqK5k81zDdKf7zkDYAbwyyfeAc+kdhd1tI/ZxevXOBV8E/LSqLqqqdcBqYJf+Ns9N8l3gfOARwB7r31xVRwPbA5cCfzLbhyRZnmRVklXXXXHqRn9BSdL8VK2b10MLrpPZ/IPzP7HRX1CSND9dyeb5NqO3rH/SPxr7FOCgqtqbXjht0V892IpvwVS39X+uG3i+/vVmSXYFXg08uX/9yRem76Oq7gT+P+CPZyu0qlZU1X5Vtd/2//3ZG/ftJEnzVutqXg8tuE5m826PesHGfTtJ0rx1JZvnakZ/DWw1y7ptgBur6tYkDwMeM7Dup0kenmQJ8Jx51rQ1vWC9KckDgKdB71qUJA9Z/xx4FnDZPPctSVpgXQm8TYjZLEkaqivZPPSa0ar6eZJvJrmY3uQGPx1YfRZwTJILgcvpDQda7zjgDOAa4GJgo6d5r6rvJTmf3tCgK4Bv9lcF+GiSrfvPvwe8fGP3K0kaj67cy2xTYTZLkubSlWyeawIjquqIWZbfRv/I6AzrTgFOmWH5UQPPrwT2nGXdUczssXPVK0laXJ7tXHxmsyRpmHFkc5JDgfcBS4EPV9Xbp61Pf/3TgVuBo6rqu8P2OWczKknSMNWR6eMlSZoUC53N/ZnUPwAcAqylN9v6aVV1ycBmT6M3ad5uwIHAh/o/Z2UzKkkaiWdGJUlqlzFk8wHAmqq6AiDJycBh9G7ptd5hwMf6s7Ofm2TbJA+sqh/PttP5zqYrSdIUXZk+XpKkSTHfbB689Vb/sXzaLnegN+fAemv7y+a7zRSeGZUkjWSdZ0YlSWqV+WZzVa0AVgzZJDO97W5sM4XNqCRpJF4zKklSu4whm9cCOw283hG47m5sM4XDdCVJI+nKvcwkSZoUY8jmlcBuSXZNcg/gecBp07Y5DXhR/x7UjwFuGna9KHhmVJI0Iq8DlSSpXRY6m6vqjiTHAmfTu7XLCVW1Oskx/fXHA2fSu63LGnq3djl6rv3ajEqSRuLZTkmS2mUc2VxVZ9JrOAeXHT/wvIBXzGef6b1HGyPJ8v7Fva1gPcNZz3DWM5z1SN3Qtv83rGc46xnOeoaznk2P14zOz/QpjptmPcNZz3DWM5z1SN3Qtv83rGc46xnOeoaznk2MzagkSZIkadHZjEqSJEmSFp3N6Py0bUy49QxnPcNZz3DWI3VD2/7fsJ7hrGc46xnOejYxTmAkSZIkSVp0nhmVJEmSJC06m1FJkiRJ0qKzGZUkSZIkLTqbUUmSJEnSorMZvRuSHNLQ526d5MEzLN+roXp+L8nv9Z/fL8kfJXlEE7UMk+RhDX725jMsu29DtSxJsqT//B5JHp3kPk3UMkySRZ+ZLsnSJC9L8uYkj5227m8aqOeeSV6T5C+SbJHkqCSnJXlnkmWLXY/UBWbzXZ9rNs/92WbzPDSRy/3PNZsngM3o3fMvi/2BSZ4LXAZ8JsnqJPsPrD6xgXpeBnwLODfJy4EzgGcCn03y0sWuZw5fXOwPTPKkJGuB65J8MckuDdfzbODHwLVJDgO+DrwbuDDJsxqo5z6zPLYDnr7Y9QD/BDwB+Dnwj0n+fmDdHzVQz4nAA4BdgS8A+9H7+wrwoQbqkbrAbDabhzKbh9bStlwGs3kibNZ0AW2V5LTZVgHbLWYtfa8F9q2qHyc5APh4ktdW1Wf7NS22Y4FHAFsCVwEPqaqfJLk38BUW+R8FSf5xtlXAtotZS987gT+oqtVJDgf+PckLq+pcmvn7egOwN72/r+8B+1fV5Ul2Bj4DnL7I9fyM3n83g38W1X99/0WuBeCAqtoLIMn7gQ8m+SzwfJr5+3poVT03Sej9Q+UpVVVJvk7v70+aSGbznMzm4czm2bUtl8Fsngg2o7N7PPAC4OZpywMcsPjlsLSqfgxQVd9J8iTgjCQ70vtlsdhur6pbgVuT/LCqftKv7cYkTdRzNPB/gNtmWPf8Ra4F4B5VtRqgqk5Jcim9I9PH0czfF+v/jpJcXVWX95ddtX540CK7AnhyVV09fUWSaxqo5x7rn1TVHcDyJK8Hvgw0NvSmH3JnVv+G0P3X3hxak8xsHs5sHs5snl3bchnM5olgMzq7c4Fbq+o/p69IcnkD9fw6yYOr6ocA/aOwTwROpXcUdLGtS7J5Vd0OPGP9wiRb0Mzw75XAxVV1zvQVSd64+OVwe5LfG/iHwOokT6Y3ZGqDa4sWQ5IlVbUOeMnAsqUM/LJfRP8A3BvYIPToHblebKuSHFpVZ61fUFVvSnIdzQy9WZVkWVXdXFWDf18PBn7dQD1SW5jNw5nNw5nNs2tbLoPZPBHSb+rVckn2Bm6pqjXTlm8OPLeqTlrkeh4EXNc/UjW4fAfg4VX1H4tcz32A3/aPCDcuyVOAn1XV96Yt3xZ4RVX93SLXsz9wUVX9dtryXYDHVdUnFrMe3X1JUv7illrBbJ6zHrN5eD1m8ybCbL77bEbnkGSPqrpk2rInVtVXrad99ah7kuwJ7AFssX5ZVX3MetpZj9QGbcse69GmpI2507aa2lZPl9mMziHJxcDH6Q1R2KL/c7+qOsh62lNPkosYcr3H+gvgF4v1bJwkbwCeSO8X+pnA04BvVNXh1tO+eqS2aEv2WM+cdbQqe6xnbm3MnbbV1LZ6us5rRud2IPAO4BxgK+Ak4LFD32E9TdTzzP7PV/R/frz/80igieFB1rNxDqc3k+D5VXV0kgcAH7ae1tYjtUVbssd6hmtb9ljP3NqYO22rqW31dJrN6NxuB35Db9rtLYAf9S80t54W1VNVVwEkeWxVDQbucUm+CbzJetpTz4DfVNW6JHck2Rq4HvjvDdViPVJ3tCJ7rGe4tmWP9WyUNuZO22pqWz2d1sTMal2zkt4v9P2BxwHPT3KK9bS2nnsledz6F0n+B3Av62ltPav6E0f8M3Ae8F3gO9bT2nqktmhb9ljPcG3LHuuZXRtzp201ta2eTvOa0Tkk2a+qVk1b9sKq+vhs77GeRuvZFzgB2Ka/6JfAS6rqu9bTvnoG9WcP3LqqLmy4FMB6pDZrYfZYz/B6WpU91rNx2pg7baupbfV0kc3oRkpyf6bOmDXTfZgWjfUM1x82kaq6qck61rOeobXsBezCwGUDVfVZ62lnPVKbtDB7rGeINmUPWM+QOlqXO22rqW31dJnXjM4hybOAvwe2pzcmfGfgUpq5mbX1bFxNz+h//hZJgN5Nkq2nffUkOQHYC1gNrL+eqYBGfqFbj9QNbcse69momlqTPdYztI7W5U7bampbPV1nMzq3twCPAf6jqh6V5EnA862nnfUkOR64J/AkejObHU6D4/itZ06Pqao9Gvz86axH6oZWZY/1DNe27LGeodqYO22rqW31dJoTGM3t9qr6ObAkyZKq+gqwj/W0tp7/UVUvAm6sqr8FDgJ2sp7W1vOtJG36hW49Uje0LXusZ7i2ZY/1zK6NudO2mtpWT6d5ZnRuv0yyDPgacFKS64E7rKe19fy2//PWJNsDvwB2tZ7W1vNRer/UfwLcBgSoJm70bT1Sp7Qte6xnuLZlj/XMro2507aa2lZPp9mMzu0wer8kXkXvJsTb0Nw9Ga1nbqf3p9t+F72ptove1NvW0856TgBeCFzEf1130STrkbqhbdljPcO1LXusZ3ZtzJ221dS2ejrNZnQOVXXLwMuPNlZIn/XM6TLgzqr6TH8IxaOBU62ntfVcXVWnNfj501mP1AFtyx7rmVPbssd6ZtfG3GlbTW2rp9O8tcsskvya3pGpuxb1X68/Fb+19bSnnoG6LqyqvdK7efRbgfcAr62qA62nlfV8ENgWOJ3eUBeguenRrUdqt7Zlj/VsdF1tyx7rmb2W1uVO22pqWz1d55nRWVTVVk3XMMh6Ntqd/Z/PAI6vqs8neaP1tLaeLen9In/qwLImp0e3HqnF2pY91rPR2pY91jO7NuZO22pqWz2d5pnRjdA/UrVbVX0kyX2BrarqR9bTvnqSnAFcCzwF2Bf4DfCdqtrbetpXjyTdXW3KHuuZs5ZWZY/1SO1hMzqHJG8A9gN2r6qH9mc5+9eqeqz1tLKeewKHAhdV1Q/+//bu31WuKgyj8PqCYEQlSRmQCII/ChUtBDvBWkQre9FCGyvRSrAS/wQrSyvBIoUYGwWJWGlEsQ1IYqWiKCGFn8XkwgnoTHf2u8+sp7p3plnFwMu+98w5VXUeeKy7P7MnsudDbr+kDIDufnlAjj3SJAK3x579PWnbY8//t8TtTlpTWs/svEz3sBeBJ9nd3YzuvlZVIy+DsWeP7v6bxWUS3X0duG5PZg9wcfHzaXafp2uDWsAeaRZR22PPfmnbY89eibuT1pTWMzUPo4fd7O6uqgaoqrvtie7RRLr74+XvVfUR8PmgHHukeaRtjz3ahMTdSWtK65ndqdEByaqqgItV9QFwtqpeZfdhG/LsJ3t0BB4ELoyOWLBHCpO2PfZo4xJ3J60prWcq/md0j1t/VXwBeAv4A3gYeKe7L9mT16P5LB5DcPL4gV/YfZ7sCeyREqRtjz3aksTdSWtK65mdh9HDLgO/d/ebo0NusUebkfYYAnukaaRtjz3ahMTdSWtK65mdd9M9oKp+BB4CrgJ/nbze3Y/bk9ej+VTVOXaXuJw+ea27v7Qns0dKkLY99mhLEncnrSmtZ2YeRg+oqvv/6/Xuvrp2C9ijbamqV4A3gPuAb4Gngcvd/aw9eT1SirTtsUdbkbg7aU1pPbPzMCppmKr6HngK+Lq7n6iqR4B3u/sle/J6JEnblrg7aU1pPbPzbrqSRrrR3TcAqurO7v6J3c027MnskSRtW+LupDWl9UzNGxhJGunnqjoLfAJcqqrfGPvgaHskSccscXfSmtJ6puZlupIiVNUzwBng0+6+aU92jyRp2xJ3J60prWdGHkYlDVFVp4Ar3f3o6BawR5J03BJ3J60prWcL/M6opCG6+x/gu6q6MLoF7JEkHbfE3UlrSuvZAr8zKmmk88APVfUNtz8L73l7InskSduWuDtpTWk9U/MwKmmke4DnFr8X8P6gFrBHknTcEncnrSmtZ2oeRiWNdEd3f7F8oaruGhWDPZKk45a4O2lNaT1T8zAqaXVV9RrwOvBAVV1ZvHUv8JU9WT2SpG1L3J20prSerfBuupJWV1VngHPAe8Dbi7f+7O5f7cnqkSRtW+LupDWl9WyFh1FJkiRJ0up8tIskSZIkaXUeRiVJkiRJq/MwKkmSJElanYdRSZIkSdLqPIxKkiRJklb3L7bDZ0ffsYNeAAAAAElFTkSuQmCC\n", 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gKuCcJCdV1UUDq70auKiqnpnkfsClSY6vqtum2+7IvhmVJI2HrpyXIknSuBhBN+8LXF5VPwFIcgLwbGBwMFrAPfvXtF4J/Bdwx0wbdXe2JGk4IzgvJclBSS5NcnmSN02xfKskJyc5v3+9y8MW/HNJktRVC9/N2wBXDjy+qv/coKOBRwDXAGuAv5hudvWNMef+iSRJ2tRCX1h74FCgg4FdgBcm2WXSahsOBdoDeCK9a2FuvrCfTJKkbppvNw9eB7p/O3zyJqd4m8mX6HoqvbkGHkTvWtZH92dbn5aH6UqShpIs+H7NkRwKJEnSuJhvNw9eB3oaVwHbDTzelt43oIMOA95XVQVcnuSnwM7A2dNt1G9GJUnDWZZ53eaw93UkhwJJkjQ25tnNc3AOsFOSHftHIr0AOGnSOj8DngSQ5AHAw4GfzLRRvxmVJA1lvjP2zWHv63wOBToAeAjw70lOr6pfzyuMJElL0ELPpltVdyR5Db3rVS8Hjq2qtUmO6C8/BngXcFySNfS6/I39Gdqn5WBUkjSUEczYN5JDgSRJGhejmOm+qk4FTp303DED968BnjKfbY7FYHT1937adISN7vzU2qYjbOJRL9m16QgTvOWvv910hAne/4IfNh1hgtueslfTESb4p6PPaTrCBN961GObjjDBO55/0ewrLar7LfwmF/6c0Y2HAgFX0zsU6EWT1tlwKNDpcz0USO1y/jlXNR1ho7udcHHTESbY9QWPaDrCJt7wislH4zXryNdd3XSECW4+aPIca806/bRLmo4wwTfuv3PTESb44Lsf2nSE0Vv4bh6JsRiManptG4hK6p6F3vs6qkOBJEkaF125BriDUUnSULJ8+YJvcxSHAkmSNC5G0c2j4GBUkjScBZ4kQZIkDakj3exgVJI0lK4cCiRJ0rjoSjc7GJUkDacjkyRIkjQ2OtLNDkYlScPpyN5XSZLGRke62cGoJGko6cjeV0mSxkVXutnBqCRpOB3Z+ypJ0tjoSDc7GJUkDSUdmbFPkqRx0ZVudjAqSRpOurH3VZKksdGRbm5kyJzkprv4uu2T/CDJeUnWJjliobNJkuZp2bL53dRKdrMkLSEd6eaRfTOaJECqav0CbvZa4A+r6ndJVgIXJjmpqq5ZwPeQJM1HR/a+ym6WpLHRkW5e0GFwkh2SXJzko8APgbcmOSfJBUneMcX6K5N8I8kPk6xJ8uz+8/v0X7MiyT36e1p3q6rbqup3/Zf/3kLnlyTNX5Ytm9dNi8tulqTx05VuHsU3ow8HDgO+BBwC7AsEOCnJH1XVdwbWvRV4blX9Osl9gbP6e1PPSXIS8G5gC+AzVXUhQJLtgK8ADwVe755XSWpYR6aPH3N2sySNk4508yhSXlFVZwFP6d/Opbcndmdgp0nrBvi7JBcAXwe2AR7QX/ZO4MnA3sDfb3hBVV1ZVbvTK7yXJnkAU0hyeJLVSVb/9MITFuzDSZImWZb53dSE1nXzjy/47IJ9OEnSJB3p5lF8M3pz/2eA91bVx2dY98XA/YC9qur2JOuAFf1l9wZWApv1n7t58IVVdU2StcDjgRMnb7iqVgGrAP74tZfXXf40kqQZdeXC2mOudd38/NddYTdL0oh0pZtHmfI04GX9yQxIsk2S+09aZyvg+n7Z7Q9sP7BsFfBW4HjgyP42tk2yRf/+vYDHApeO8DNIkmbTkb2vAuxmSRoPHenmkc2mW1VfS/II4Mze5H3cBPwJcP3AascDJydZDZwHXAKQ5CXAHVX12STLgTOSHAAsBz6YpOjt3f1AVa0Z1WeQJM1BR/a+ym6WpLHRkW5e0MFoVa0Ddht4fBRw1BTrrez//AWw3xSbWgd8qr/OncCjB5btvmCBJUnD68j08ePKbpakMdSRbh7ZN6OSpDHh5VokSWqXjnSzg1FJ0nA6ciiQJEljoyPd7GBUkjQcJyWSJKldOtLNDkYlScNZtrzpBJIkaVBHutnBqCRpOB05L0WSpLHRkW52MCpJGk5HZuyTJGlsdKSbHYxKkobTkUkSJEkaGx3pZgejkqThdORQIEmSxkZHunksBqNH/sVmTUfYaMX6y5qOMMFb/vrbTUfYxPPe+4SmI0zwoe0vaDrCBFdfcV3TESZ41ov3aTrCBNf+sl2Hpbzj6w9sOsIE//g3I9hoRw4FUru89EUPajrCRg/Z6uqmI0zwhlec1HSETRz+iWc1HWGCo3c6u+kIE6y7+JKmI0yw6z47Nh1hghW/166e+OAnb206wgTHv3cEG+1IN4/FYFSSNEIdORRIkqSx0ZFudjAqSRpOR/a+SpI0NjrSzQ5GJUnD6ch5KZIkjY2OdLODUUnSUKoje18lSRoXXelmB6OSpOF05LwUSZLGRke62cGoJGk4HSk8SZLGRke62cGoJGkoXTkUSJKkcdGVbnYwKkkaTkf2vkqSNDY60s0ORiVJw+nI3ldJksZGR7q59UPmJDskubB//z5JvpnkpiRHN51NkkRv+vj53NR5drMktVxHurlr34zeCrwV2K1/kyQ1rCvnpWhk7GZJapmudPOiDUaT3AP4PLAtsBx4F/Bw4JnAFsAZwCurqpLsBRwL3AJ8d8M2qupm4LtJHrpYuSVJs+jIeSnalN0sSUvUCLo5yUHAUfT64hNV9b4p1nki8CFgM+AXVfWEmba5mP+COAi4pqr2qKrdgK8CR1fVPv3HWwDP6K/7SeC1VbXfIuaTJN0FlWXzuqlV7GZJWoIWupuTLAc+AhwM7AK8MMkuk9bZGvgo8Kyq2hX4X7NtdzH/VbAGODDJkUkeX1U3Avsn+X6SNcABwK5JtgK2rqpv91/36bvyZkkOT7I6yeoTTvjswnwCSdKmkvnd1CaNdfO/ffETC/MJJEmbWvhu3he4vKp+UlW3AScAz560zouAL1bVzwCq6vrZNrpoh+lW1WX9Q3yeBrw3ydeAVwN7V9WVSd4OrAAC1AK83ypgFcCPfnzF0NuTJE3Nbzu7q8luPvWHt9vNkjQi8+3mJIcDhw88tar/O3uDbYArBx5fBTx60mYeBmyW5FvAPYGjqupTM73vov0LIsmDgFuq6jPAB4BH9Rf9IslK4BCAqvoVcGOSx/WXv3ixMkqS7oIRfDOa5KAklya5PMmbplnniUnOS7I2ybenWkczs5slaYmaZzdX1aqq2nvgtmryFqd4l8k7Fe8G7AU8HXgq8NYkD5sp5mLOpvtI4P1J1gO3A68CnkPvEKF1wDkD6x4GHJvkFuC0wY0kWQdsCWye5DnAU6rqopGnlyRNqZYtX9DtDZyX8mR6e17PSXLS4O/6gfNSDqqqnyW5/4KGGB92syQtQQvdzfT6eLuBx9sC10yxzi/6E9vdnOQ7wB7AZdNtdDEP0z2NSeUFrAbeMsW6P6AXfIO3DyzbYQTxJEl31cIfprvxvBSAJBvOSxkc3Mz7vBRtym6WpCVq4bv5HGCnJDsCVwMvoNfFg74MHJ3kbsDm9A7j/YeZNuqJPpKkoRSZ121wEpv+7fBJm5zqvJRtJq3zMOBeSb6V5AdJXjLKzyhJUpfMt5tn3V7VHcBr6O3AvBj4fFWtTXJEkiP661xMb1b2C4Cz6V3+5cKZtruYh+lKkpag+U6SMDiJzTTmc17Kk+hdfuTMJGdV1bSHAkmSNC5GMblgVZ0KnDrpuWMmPX4/8P65btPBqCRpOAtfeCM5L0WSpLHRkZnuu5FSktRalczrNgcbz0tJsjm981JOmrTOl4HHJ7lbkrvTOy/l4gX9YJIkddQIunkk/GZUkjSUhT4UqKruSLLhvJTlwLEbzkvpLz+mqi5OsuG8lPXM4bwUSZLGRVeuAe5gVJI0nBHsUR3FeSmSJI2NBr/tnA8Ho5KkoXRl76skSeOiK93sYFSSNJS5TAkvSZIWT1e6eSwGox859T5NR9jocftuN/tKi+j9L/hh0xE28aHtL2g6wgSPPWL3piNM8J2PnNd0hAnOOv3K2VdaRJ94zuqmI0xw3B/8cdMRRq4re1/VLqedfmvTETbaaadtm44wwZGvu7rpCJs4eqezm44wwcFv3LfpCBN84S2nNx1hgnWXXd90hAle/qR2DYwuu3TLpiOMXFe6eSwGo5KkEerIeSmSJI2NjnSzg1FJ0lDKq4RJktQqXelmB6OSpKE0eX0ySZK0qa50s4NRSdJQunJeiiRJ46Ir3exgVJI0lK7M2CdJ0rjoSjc7GJUkDaUre18lSRoXXelmB6OSpKF05bwUSZLGRVe62cGoJGkoXTkUSJKkcdGVbnYwKkkaSlcOBZIkaVx0pZsdjEqShtKVva+SJI2LrnRz64fMSXZIcmH//pOT/CDJmv7PA5rOJ0njbn2Wz+um7rObJandutLNXftm9BfAM6vqmiS7AacB2zScSZLGWlcOBdLI2M2S1DJd6eZFG4wmuQfweWBbYDnwLuDhwDOBLYAzgFdWVSXZCzgWuAX47oZtVNW5A5tcC6xI8ntV9bvF+RSSpMm6ciiQNmU3S9LS1JVuXswh80HANVW1R1XtBnwVOLqq9uk/3gJ4Rn/dTwKvrar9Ztje/wTOna7skhyeZHWS1Wu+d+wCfgxJ0qBK5nVTqzTWzRee8ckF/BiSpEFd6ebFHIyuAQ5McmSSx1fVjcD+Sb6fZA1wALBrkq2Aravq2/3XfXryhpLsChwJvHK6N6uqVVW1d1Xt/cjHvmzhP40kCYCqzOumVmmsm3f7w8MW/tNIkoDudPOiHaZbVZf1D/F5GvDeJF8DXg3sXVVXJnk7sAIIUNNtJ8m2wL8CL6mqH48+uSRpJtX+ufA0DbtZkpamrnTzoqVM8iDglqr6DPAB4FH9Rb9IshI4BKCqfgXcmORx/eUvHtjG1sBXgL+uqu8tVnZJ0vSKzOum9rCbJWlp6ko3L+Zsuo8E3p9kPXA78CrgOfQOEVoHnDOw7mHAsUluoTcr3wavAR4KvDXJW/vPPaWqrh9xdknSNBxgdprdLElLUFe6eTEP0z2NieUFsBp4yxTr/gDYY+Cpt/effzfw7hFFlCTdBV0pPG3Kbpakpakr3dy164xKklqmK4UnSdK46Eo3OxiVJA3FGXIlSWqXrnSzg1FJ0lC6svdVkqRx0ZVudjAqSRpKVwpPkqRx0ZVudjAqSRpKVwpPkqRx0ZVudjAqSRpKV85LkSRpXHSlmx2MSpKGsr4je18lSRoXXenmsRiMXn7Bz5qOsNEN/3nvpiNMcNtT9mo6wiauvuK6piNM8J2PnNd0hAn+6NV7Nh1hgvcetKrpCBP8+T0e13SECT70zH9vOsIkT17wLXblUCC1y4VnXtx0hI0uX3P3piNMcPNBuzQdYRPrLr6k6QgTfOEtpzcdYYL/+e7HNx1hgiOf8U9NR5jgVW/evOkIE3zsPU0nmGzrBd9iV7p5LAajkqTR6cqhQJIkjYuudLODUUnSULqy91WSpHHRlW52MCpJGkpX9r5KkjQuutLNDkYlSUPpyt5XSZLGRVe62cGoJGkoXdn7KknSuOhKNy9rOoAkqdvurMzrJkmSRmsU3ZzkoCSXJrk8yZtmWG+fJHcmOWS2bfrNqCRpKF05FEiSpHGx0N2cZDnwEXrXiLsKOCfJSVV10RTrHQmcNpft+s2oJGkoVZnXTZIkjdYIunlf4PKq+klV3QacADx7ivX+HPgCcP1cNupgVJI0lCLzukmSpNGabzcnOTzJ6oHb4ZM2uQ1w5cDjq/rPbZRkG+C5wDFzzelhupKkoayvphNIkqRB8+3mqloFrJphlan2Jk9+lw8Bb6yqO5O57Xxu/TejSXZIcmH//r5Jzuvfzk/y3KbzSdK485vR8WM3S1K7jaCbrwK2G3i8LXDNpHX2Bk5Isg44BPhokufMtNGufTN6IbB3Vd2R5IHA+UlOrqo7mg4mSePK80DHnt0sSS0zgm4+B9gpyY7A1cALgBdNfM/accP9JMcBp1TVl2ba6KINRpPcA/g8vVH0cuBdwMOBZwJbAGcAr6yqSrIXcCxwC/DdDduoqlsGNrmCTb8aliQtshrBb+IkBwFH0euLT1TV+6ZZbx/gLOD5VXXiwidZ2uxmSVqaFrqb+zscX0NvltzlwLFVtTbJEf3lcz5PdNBiHqZ7EHBNVe1RVbsBXwWOrqp9+o+3AJ7RX/eTwGurar/JGzFJMnoAAB35SURBVEny6CRrgTXAEdPteR08Cfdnl3x+JB9IkgTrybxusxmYPv5gYBfghUl2mWa9OU8fryk11s1X//hfR/KBJEkL380AVXVqVT2sqh5SVe/pP3fMVAPRqjp0LjuJF3MwugY4MMmRSR5fVTcC+yf5fpI1wAHArkm2Arauqm/3X/fpwY1U1feraldgH+Cvk6yY6s2qalVV7V1Vez945+eN7lNJ0pjryvTxmlJj3bzNQzy1VJJGpSuXXVu0wWhVXQbsRa/43pvkb4GPAodU1SOBf6R3eE+YwyE+VXUxcDOw28hCS5JmVTW/W1PTx2tTdrMkLU3z7eamLNpgNMmDgFuq6jPAB4BH9Rf9IslKejMuUVW/Am5M8rj+8hcPbGPHJHfr39+e3nkt6xbnE0iSpjLfGfsGvx3r3yZPJT+v6eNH86nGg90sSUtTV2a6X8zZdB8JvD/JeuB24FXAc+jtjV1Hb4amDQ4Djk1yCxPPBXoc8KYktwPrgT+rql8sQnZJ0jRGcJ3R+UwfD3Bf4GlJ7pht1j5twm6WpCWoK9cAX7TBaFWdxqaTTKwG3jLFuj8A9hh46u395z/NpPNUJEnN6sr08dqU3SxJS1NXLrvWteuMSpJapivTx0uSNC6aPA90PhyMSpKGMtcp4eejqk4FTp303JSD0Ko6dMEDSJLUYaPo5lFwMCpJGkpX9r5KkjQuutLNDkYlSUPpynkpkiSNi650s4NRSdJQujJjnyRJ46Ir3exgVJI0lK4cCiRJ0rjoSjc7GJUkDaXJi2VLkqRNdaWbU10ZNg9h3eWXteZDfvTr282+0iL6wbfWNB1hE8968T5NR5jgrNOvbDrCBFde/NOmI0zw1189vOkIExz/V99oOsIE1627pukIE3zjhH0XvJ3+5az5HQz0vx6zrBsNqZFae/m1renmY7+2ZdMRJrj03CuajrCJXffZcfaVFtG6y65vOsIE1/64Xf9WeOMpL286wgSfe8M3m44wwboLftR0hAm+e/ITxrab/WZUkjSUMdinKUlSp3Slmx2MSpKGsr4jM/ZJkjQuutLNDkYlSUPpyt5XSZLGRVe62cGoJGkoXSk8SZLGRVe62cGoJGkoXbmWmSRJ46Ir3exgVJI0lOrIeSmSJI2LrnSzg1FJ0lC6ciiQJEnjoivd7GBUkjSUrhwKJEnSuOhKNzsYlSQNpSt7XyVJGhdd6WYHo5KkoXSl8CRJGhdd6eZlMy1MsnWSP1usMLNJ8poklyepJPdtOo8kqXco0HxuGo7dLEmaTVe6ecbBKLA1sEnhJVk+mjiz+h5wIHBFQ+8vSZqkan43Dc1uliTNqCvdPNthuu8DHpLkPOB24CbgWmBPYJckXwK2A1YAR1XVKoAkN1XVyv79Q4BnVNWhSY4DfgvsDGwPHAa8FNgP+H5VHdp/zceAfYAtgBOr6m0AVXVuf/mCfHhJ0vDWr286wdixmyVJM+pKN8/2zeibgB9X1Z7A64F9gTdX1S795S+rqr2AvYHXJrnPHN7zXsABwF8CJwP/AOwKPDLJnv113lxVewO7A09Isvt8PhRAksOTrE6y+rMn/J/5vlySNEdd2fu6hCyJbv6XEz4z35dLkuaoK9083wmMzq6qnw48fm2S5/bvbwfsBPxylm2cXFWVZA1wXVWtAUiyFtgBOA94XpLD+/keCOwCXDCfoP09wasA1l1+mf/8kaQRcYDZuE5289rLr/W/HEkaka5083wHozdvuJPkifTOEdmvqm5J8i16hwQBDH78FUz0u/7P9QP3Nzy+W5IdgdcB+1TVDf3DhyZvQ5LUEk5K1Di7WZI0QVe6ebbDdH8D3HOaZVsBN/TLbmfgMQPLrkvyiCTLgOdO/fJpbUmvWG9M8gDg4Hm+XpK0iKpqXjcNzW6WJM2oK90842C0qn4JfC/JhcD7Jy3+Kr29pRcA7wLOGlj2JuAU4D/oTaowZ1V1PnAusBY4lt4sfQAkeW2Sq4BtgQuSfGI+25YkLbyunJeyVNjNkqTZdKWbZz1Mt6peNM3zv2OaPaNVdSJw4hTPHzpwfx2w2zTLDmUKVfVh4MOzZZYkLZ6uzNi3lNjNkqSZdKWb53vOqCRJE/htpyRJ7dKVbnYwKkkaSlcmSZAkaVx0pZsdjEqShrL+zvk2XkaSQ5Ik9XSlmx2MSpKG0pW9r5IkjYuudLODUUnSULpyXookSeOiK93sYFSSNJT1Xdn9KknSmOhKNzsYlSQNpSt7XyVJGhdd6eaxGIx+4KQHNB1ho3ceuLrpCBN861GPbTrCJq79ZbsmN/nEc9r1d/bn93hc0xEmOH7XbzQdYYIXf/BJTUeY4N+OPLvpCCPXlcJTu3zspLs3HWGjQ59+W9MRJvjG/XduOsImVvxeu7r55U9qV55XvXnzpiNM8Lk3fLPpCBO88O/3bzrCBG378xmFUXRzkoOAo4DlwCeq6n2Tlr8YeGP/4U3Aq6rq/Jm2ORaDUUnS6Kx3NCpJUqssdDcnWQ58BHgycBVwTpKTquqigdV+Cjyhqm5IcjCwCnj0TNt1MCpJGkqtbzqBJEkaNIJu3he4vKp+ApDkBODZwMbBaFWdMbD+WcC2s2102QKHlCSNmaqa102SJI3WfLs5yeFJVg/cDp+0yW2AKwceX9V/bjovB/5ttpx+MypJGsp6vxmVJKlV5tvNVbWK3mG105nqRO0p9zAn2Z/eYHTWiU4cjEqShuK3nZIktcsIuvkqYLuBx9sC10xeKcnuwCeAg6vql7Nt1MGoJGkoHbmUmSRJY2ME3XwOsFOSHYGrgRcALxpcIcmDgS8Cf1pVl81low5GJUlDKUejkiS1ykJ3c1XdkeQ1wGn0Lu1ybFWtTXJEf/kxwN8C9wE+mgTgjqrae6btOhiVJA3Fo3QlSWqXUXRzVZ0KnDrpuWMG7r8CeMV8tulsupKkoaxfX/O6zUWSg5JcmuTyJG+aYvmLk1zQv52RZI8F/2CSJHXUKLp5FPxmVJI0lIWeJGFUF9aWJGlcdGVywRm/GU2ydZI/W6wws0lyfH9P+YVJjk2yWdOZJGnc1fr53eZg44W1q+o2YMOFtf/7PavOqKob+g/ndGHtpcJuliTNZgTdPBKzHaa7NbBJ4fX3WjfheGBn4JHAFszzmGRJ0sJbXzWvW1MX1l5C7GZJ0ozm281Nme0w3fcBD0lyHnA7cBNwLbAnsEuSL9G73swK4Kj+xVJJclNVrezfPwR4RlUdmuQ44Lf0Smt74DDgpcB+wPer6tD+az4G7EOv1E6sqrfBxpNm6a9zNmO0J1yS2mq+hwI1dWHtJcRuliTNaEkcpgu8CfhxVe0JvJ7eoVNvrqpd+stfVlV7AXsDr01ynzm8572AA4C/BE4G/gHYFXhkkj3767y5Pw3w7sAT+hdP3ah/CNCfAl+d7k0G97yvPfO4OcSSJN0VI5gkYb4X1n72XC6svYTYzZKkGXVlAqP5zqZ7dlX9dODxa5OcT+98ne2AneawjZOrN1RfA1xXVWuqaj2wFtihv87zkvwQOJdeGe4yaRsfBb5TVadP9yZVtaqq9q6qvXfd79A5xJIk3RVV87vNwcYLayfZnN6FtU8aXOGuXFh7CbObJUkTjKCbR2K+s+nevOFOkicCBwL7VdUtSb5F75AgmHg41Qom+l3/5/qB+xse3y3JjsDrgH36syQeN7iNJG8D7ge8cp7ZJUkjcOedCzvzwagurL2E2c2SpAkWuptHZbbB6G+Ae06zbCvghn7Z7Qw8ZmDZdUkeAVwKPLe/nbnakl6x3pjkAcDBwLcAkrwCeCrwpP4eW0lSw2oEh/eM4sLaS4jdLEma0Si6eRRmHIxW1S+TfC/JhfQmN7huYPFXgSOSXECv2M4aWPYm4BR6syFeCKyca6CqOj/JufQODfoJ8L2BxccAVwBn9veEf7Gq3jnXbUuSFl5XCm+psJslSbPpSjfPephuVb1omud/R2/P6FTLTgROnOL5QwfurwN2m2bZoUyhquZ7WLEkacQ60ndLit0sSZpJV7rZApEkDaUre18lSRoXXelmB6OSpKF05VpmkiSNi650s4NRSdJQmrw+mSRJ2lRXutnBqCRpKF3Z+ypJ0rjoSjc7GJUkDaUr56VIkjQuutLNDkYlSUPpSuFJkjQuutLNDkYlSUNZ35FDgSRJGhdd6eaxGIxed+V/NR1hgtd/eeemI2z09KfCvltf1HSMCb78y90479xfNh3jvz0Rjrvxj5tOMeB6PvTM85sOsdERn38E1627pukYE/zbkWc3HWGCg9+4b9MR/tv/d+mCb7Ire1/VLusuvrrpCP/t6Q/k9W+9rOkUGx30vH148u43NB1jgtMvvTdnn9Ge3/UH7wJH/euWTccY8HM+9p7fbzrERu88FtZd8KOmY0zwuTd8s+kIE7zw7/dvOsJ/e8/4dvNYDEbbpE0DUWjfQBRo10CUtg1EadVAFHAgOotWDURHpCuTJEjTadNAFGjdQBRo1UAU2jYQpVUDUXAgOptWDURHpCvd7GBUkjSUrkwfL0nSuOhKNzsYlSQNpSuHAkmSNC660s0ORiVJQ+nKoUCSJI2LrnSzg1FJ0lBq/fqmI0iSpAFd6WYHo5KkoXTlvBRJksZFV7rZwagkaShdORRIkqRx0ZVudjAqSRpKVyZJkCRpXHSlmx2MSpKG0pXCkyRpXHSlmx2MSpKGsr66MUmCJEnjoivdvGymhUm2TvJnixVmNkn+Kcn5SS5IcmKSlU1nkqRxt/6O9fO6aTh2syRpNl3p5hkHo8DWwCaFl2T5aOLM6i+rao+q2h34GfCahnJIkvqqal43Dc1uliTNqCvdPNthuu8DHpLkPOB24CbgWmBPYJckXwK2A1YAR1XVKoAkN1XVyv79Q4BnVNWhSY4DfgvsDGwPHAa8FNgP+H5VHdp/zceAfYAtgBOr6m0AVfXr/vL0l/mvGklq2PqOXMtsCbGbJUkz6ko3zzYYfROwW1XtmeSJwFf6j3/aX/6yqvqvJFsA5yT5QlX9cpZt3gs4AHgWcDLwWOAV/dfvWVXnAW/ub3c58I0ku1fVBQBJPgk8DbgI+Kt5f2JJ0oLqyiQJS4jdLEmaUVe6ebbDdCc7e6DsAF6b5HzgLHp7YXeawzZOrt53wWuA66pqTVWtB9YCO/TXeV6SHwLnArsCu2x4cVUdBjwIuBh4/nRvkuTwJKuTrP7Jms/N+QNKkuanav28blpwnezmn13y+Tl/QEnS/HSlm+c7GL15w53+3tgDgf2qag965bSiv3hwKL6CiX7X/7l+4P6Gx3dLsiPwOuBJ/fNPvjJ5G1V1J/B/gP85XdCqWlVVe1fV3v/jkS+c26eTJM1bra953bTgOtnND975eXP7dJKkeetKN882GP0NcM9plm0F3FBVtyTZGXjMwLLrkjwiyTLgufPMtCW9Yr0xyQOAg6F3LkqSh264DzwTuGSe25YkLbCuFN4SYjdLkmbUlW6e8ZzRqvplku8luZDe5AbXDSz+KnBEkguAS+kdDrTBm4BTgCuBC4E5T/NeVecnOZfeoUE/Ab7XXxTgn5Ns2b9/PvCquW5XkjQaXbmW2VJhN0uSZtOVbp5tAiOq6kXTPP87+ntGp1h2InDiFM8fOnB/HbDbNMsOZWqPnS2vJGlx+W3n4rObJUkz6Uo3zzoYlSRpJtWR6eMlSRoXXenm+U5gJEnSBF05L0WSpHExim5OclCSS5NcnuRNUyxPkg/3l1+Q5FGzbdNvRiVJQ/FyLZIktctCd3P/GtMfAZ4MXEXvOtQnVdVFA6sdTO9yYjsBjwY+1v85LQejkqShrPfbTkmSWmUE3bwvcHlV/QQgyQnAs4HBweizgU/1r1t9VpKtkzywqq6dbqMORiVJQ+nKeSmSJI2LEXTzNvRmY9/gKjb91nOqdbYBHIxKkkbD80AlSWqX+XZzksOBwweeWlVVqwZXmeptJm9mDutM4GBUkjQUzxmVJKld5tvN/YHnqhlWuQrYbuDxtsA1d2GdCZxNV5I0FGfTlSSpXUbQzecAOyXZMcnmwAuAkyatcxLwkv6suo8BbpzpfFGA9M4v1VwkOXzS19WNMs/MzDMz88zMPFI3tO3/DfPMzDwzM8/MzNOsJE8DPgQsB46tqvckOQKgqo5JEuBo4CDgFuCwqlo94zYdjM5dktVVtXfTOTYwz8zMMzPzzMw8Uje07f8N88zMPDMzz8zMs/R4mK4kSZIkadE5GJUkSZIkLToHo/PTtmPCzTMz88zMPDMzj9QNbft/wzwzM8/MzDMz8ywxnjMqSZIkSVp0fjMqSZIkSVp0DkYlSZIkSYvOwagkSZIkadE5GJUkSZIkLToHo3dBkic39L5bJnnIFM/v3lCe30/y+/3790vyx0l2bSLLTJLs3OB7bzbFc/dtKMuyJMv69zdP8qgk924iy0ySLPrMdEmWJ3llkncleeykZW9pIM/dk7whyeuTrEhyaJKTkvx9kpWLnUfqArt54/vazbO/t908D030cv997eYx4GD0rvmnxX7DJM8DLgG+kGRtkn0GFh/XQJ5XAmcCZyV5FXAK8Azgi0levth5ZvG1xX7DJPsnuQq4JsnXkuzQcJ7nANcCVyd5NnA68AHggiTPbCDPvae53Qd42mLnAT4OPAH4JfDhJP97YNkfN5DnOOABwI7AV4C96f19BfhYA3mkLrCb7eYZ2c0zZmlbL4PdPBbu1nSAtkpy0nSLgPssZpa+vwH2qqprk+wLfDrJ31TVF/uZFttrgF2BLYArgIdW1c+T3Av4Jov8j4IkH55uEbD1Ymbp+3vgqVW1NskhwL8n+dOqOotm/r7eBuxB7+/rfGCfqro0yfbAF4CTFznPf9L772bwz6L6j++/yFkA9q2q3QGSHA18NMkXgRfSzN/Xw6rqeUlC7x8qB1ZVJTmd3t+fNJbs5lnZzTOzm6fXtl4Gu3ksOBid3uOBPwFumvR8gH0XPw7Lq+pagKo6O8n+wClJtqX3y2Kx3V5VtwC3JPlxVf28n+2GJE3kOQz4K+B3Uyx74SJnAdi8qtYCVNWJSS6mt2f6TTTz98WGv6MkP6uqS/vPXbHh8KBF9hPgSVX1s8kLklzZQJ7NN9ypqjuAw5P8LfAfQGOH3vRL7tTqXxC6/9iLQ2uc2c0zs5tnZjdPr229DHbzWHAwOr2zgFuq6tuTFyS5tIE8v0nykKr6MUB/L+wTgS/R2wu62NYn2ayqbgeevuHJJCto5vDvc4ALq+qMyQuSvH3x43B7kt8f+IfA2iRPonfI1CbnFi2GJMuqaj3wsoHnljPwy34RfQi4F7BJ6dHbc73YVic5qKq+uuGJqnpnkmto5tCb1UlWVtVNVTX49/UQ4DcN5JHawm6emd08M7t5em3rZbCbx0L6g3q1XJI9gJur6vJJz28GPK+qjl/kPA8GrunvqRp8fhvgEVX19UXOc2/g1v4e4cYlORD4z6o6f9LzWwOvrqr3LHKefYA1VXXrpOd3AB5XVZ9ZzDy665Kk/MUttYLdPGseu3nmPHbzEmE333UORmeRZJequmjSc0+sqm+Zp3151D1JdgN2AVZseK6qPmWeduaR2qBt3WMeLSVt7J22ZWpbni5zMDqLJBcCn6Z3iMKK/s+9q2o/87QnT5I1zHC+x4YT4BeLeeYmyduAJ9L7hX4qcDDw3ao6xDztyyO1RVu6xzyz5mhV95hndm3snbZlaluervOc0dk9GjgSOAO4J3A88NgZX2GeJvI8o//z1f2fn+7/fDHQxOFB5pmbQ+jNJHhuVR2W5AHAJ8zT2jxSW7Sle8wzs7Z1j3lm18beaVumtuXpNAejs7sd+C29abdXAD/tn2hunhblqaorAJI8tqoGC/dNSb4HvNM87ckz4LdVtT7JHUm2BK4H/kdDWcwjdUcrusc8M2tb95hnTtrYO23L1LY8ndbEzGpdcw69X+j7AI8DXpjkRPO0Ns89kjxuw4MkfwjcwzytzbO6P3HEPwI/AH4InG2e1uaR2qJt3WOembWte8wzvTb2TtsytS1Pp3nO6CyS7F1Vqyc996dV9enpXmOeRvPsBRwLbNV/6lfAy6rqh+ZpX55B/dkDt6yqCxqOAphHarMWdo95Zs7Tqu4xz9y0sXfalqltebrIwegcJbk/E2fMmuo6TIvGPDPrHzaRqrqxyRwbmGfGLLsDOzBw2kBVfdE87cwjtUkLu8c8M2hT94B5ZsjRut5pW6a25ekyzxmdRZJnAv8beBC9Y8K3By6mmYtZm2dumZ7ef/8VSYDeRZLN0748SY4FdgfWAhvOZyqgkV/o5pG6oW3dY545ZWpN95hnxhyt6522ZWpbnq5zMDq7dwOPAb5eVX+QZH/gheZpZ54kxwB3B/anN7PZITR4HL95ZvWYqtqlwfefzDxSN7Sqe8wzs7Z1j3lm1MbeaVumtuXpNCcwmt3tVfVLYFmSZVX1TWBP87Q2zx9W1UuAG6rqHcB+wHbmaW2eM5O06Re6eaRuaFv3mGdmbese80yvjb3Ttkxty9NpfjM6u18lWQl8Bzg+yfXAHeZpbZ5b+z9vSfIg4L+AHc3T2jz/TO+X+s+B3wEBqokLfZtH6pS2dY95Zta27jHP9NrYO23L1LY8neZgdHbPpvdL4i/pXYR4K5q7JqN5Zndyf7rt99ObarvoTb1tnnbmORb4U2AN/33eRZPMI3VD27rHPDNrW/eYZ3pt7J22ZWpbnk5zMDqLqrp54OE/NxakzzyzugS4s6q+0D+E4lHAl8zT2jw/q6qTGnz/ycwjdUDbusc8s2pb95hnem3snbZlalueTvPSLtNI8ht6e6Y2PtV/vOGr+C3N0548A7kuqKrd07t49N8BHwT+pqoebZ5W5vkosDVwMr1DXYDmpkc3j9Rubese88w5V9u6xzzTZ2ld77QtU9vydJ3fjE6jqu7ZdIZB5pmzO/s/nw4cU1VfTvJ287Q2zxb0fpE/ZeC5JqdHN4/UYm3rHvPMWdu6xzzTa2PvtC1T2/J0mt+MzkF/T9VOVfXJJPcF7llVPzVP+/IkOQW4GjgQ2Av4LXB2Ve1hnvblkaS7qk3dY55Zs7Sqe8wjtYeD0VkkeRuwN/DwqnpYf5azf6mqx5qnlXnuDhwErKmqHyV5IPDIqvqaeVqZ55NMPKQMgKp6WQNxzCN1RAu7xzwz52lb95hn+iyt6522ZWpbnq7zMN3ZPRf4A3qzm1FV1yRp8jAY88ygqm5h4DCJqroWuNY87cwDnDJwfwW9/56uaSgLmEfqilZ1j3lm1rbuMc+M2tg7bcvUtjyd5mB0drdVVSUpgCT3ME+r86hDquoLg4+TfA74ekNxzCN1R9u6xzxaEtrYO23L1LY8Xbes6QBtliTAKUk+Dmyd5P+h9x9bI9d+Mo/GwE7Ag5sOMcA8Usu0rXvMoyWujb3Ttkxty9MpfjM6g/5execAbwR+DTwc+Nuq+nfztC+PumfgMgQbLj/wc3r/PZmnhXmkNmhb95hHS0kbe6dtmdqWp+scjM7uTOBXVfX6poP0mUdLRtsuQ2AeqTPa1j3m0ZLQxt5pW6a25ek6Z9OdRZKLgIcBVwA3b3i+qnY3T/vyqHuS3IveIS4rNjxXVd8xTzvzSG3Qtu4xj5aSNvZO2zK1LU+XORidRZLtp3q+qq5Y7CxgHi0tSV4B/AWwLXAe8BjgzKo6wDztyyO1Rdu6xzxaKtrYO23L1LY8XedgVFJjkqwB9gHOqqo9k+wMvKOqnm+e9uWRJC1tbeydtmVqW56uczZdSU26tapuBUjye1V1Cb3JNszTzjySpKWtjb3Ttkxty9NpTmAkqUlXJdka+BLw70luoNkLR5tHkjTO2tg7bcvUtjyd5mG6klohyROArYCvVtVt5ml3HknS0tbG3mlbprbl6SIHo5IakWQZcEFV7dZ0FjCPJGm8tbF32papbXmWAs8ZldSIqloPnJ/kwU1nAfNIksZbG3unbZnalmcp8JxRSU16ILA2ydlMvBbes8zTyjySpKXt/7Z3x7YJg1EURu+TaJCCUFZgHhZJJmCDKGNRZAEGoWGAP60n+P1szulsN1/3dBvoeHe6NXXr2TRjFFjTR5Lr4rmS/K7UkugB4L11vDvdmrr1bJoxCqzpMMa4L19U1XGtmOgB4L11vDvdmrr1bJoxCkxXVV9JvpNcquqx+HRK8qenVw8A+9bx7nRr6tazF35NF5iuqs5JPpP8JLktPr3GGE89vXoA2LeOd6dbU7eevTBGAQAAmM5fuwAAADCdMQoAAMB0xigAAADTGaMAAABMZ4wCAAAw3T90+Xt7TagEIwAAAABJRU5ErkJggg==\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "array_list = [cor_OneSes1_amg, cor_OneSes1_caudate, cor_OneSes1_hippo, cor_OneSes1_vmPFC,\n", + " cor_OneSes2_amg, cor_OneSes2_caudate, cor_OneSes2_hippo, cor_OneSes2_vmPFC]\n", + "for ar in array_list:\n", + " \n", + " plotRSA(ar, cond_list)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [], + "source": [ + "def plotRSAttest(arrGroup, cond_list, thr):\n", + " # separate groups\n", + " groupArr = np.array(arrGroup)\n", + " #print('Running t test')\n", + " group1 = groupArr[group_label==1]\n", + " group2 = groupArr[group_label==0]\n", + " # t test between groups\n", + " t,p = scipy.stats.ttest_ind(group1, group2)\n", + " tArr = np.array(t)\n", + " fdr = fdr_corr(p, thr)\n", + " tArr[~fdr]=0 # set p value to cut\n", + "\n", + " sns.heatmap(tArr, cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list,annot=True)#,\n", + " #vmin = -1, vmax=1)\n", + " return t" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "t = plotRSAttest(cor_OneSes2_amg, cond_list, .01)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [], + "source": [ + "## build permutation test instead of FDR?\n", + "# for each iteration:\n", + "# shuffle groups\n", + "# run t-test\n", + "# end of itreration - compare actual t score of each cell with t-test distribution\n", + "# every t-score with chances lower than .05 in random distribution will be considered ok\n", + "import random\n", + "\n", + "def permutation(groupArr, group_label, numIter, thr):\n", + " # take groupArr, shuffle group labels and run t test\n", + " # returns a mask of things that crossed significance and a t matrix\n", + " # run the real t test first\n", + " groupArr = np.array(groupArr)\n", + " #print('Running t test')\n", + " group1 = groupArr[group_label==1]\n", + " group2 = groupArr[group_label==0]\n", + " t,p = scipy.stats.ttest_ind(group1, group2)\n", + " permAr = []\n", + " for i in range(numIter):\n", + " \n", + " #print (f'Iteration number {i}')\n", + " group_label_ran = np.array(group_label)\n", + " \n", + " # shuffle groups\n", + " random.shuffle(group_label_ran)\n", + " # stratify to groups\n", + " group1 = groupArr[group_label_ran==1]\n", + " group2 = groupArr[group_label_ran==0]\n", + " tPerm, pPerm = scipy.stats.ttest_ind(group1, group2)\n", + " permAr.append(tPerm)\n", + " permAr = np.array(permAr)\n", + " x = np.empty([9,9])\n", + " for i in range(x.shape[0]):\n", + " for j in range(x.shape[1]):\n", + " check = np.sum(permAr[:,i,j][permAr[:,i,j]>t[i,j]])/ len(permAr)\n", + " if check<=thr:\n", + " x[i,j] = 1\n", + " else:\n", + " x[i,j] = 2\n", + " x = np.array(x, dtype=int) \n", + " return x , t" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [], + "source": [ + "x, t = permutation(cor_OneSes1_caudate, group_label, 1000, .05)\n", + "halfx = np.tril(x)\n", + "t[halfx==2]=0 # using 2 as zero, so I can mask a only lower half" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.heatmap(t, cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list,annot=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "celltoolbar": "Slideshow", + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/.ipynb_checkpoints/XGBoost-Betas-checkpoint.ipynb b/task_based_analysis/.ipynb_checkpoints/XGBoost-Betas-checkpoint.ipynb new file mode 100644 index 0000000..0764b61 --- /dev/null +++ b/task_based_analysis/.ipynb_checkpoints/XGBoost-Betas-checkpoint.ipynb @@ -0,0 +1,926 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "# Using machine learning XGboost classifier to look for different pattern between Ketamin and Midazolam groups\n", + "- Running on the Beta of trauma1_0 instead of contrast between trauma and sad (more similar to MVPA)" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [], + "source": [ + "# import relevant packages\n", + "import glob\n", + "import numpy as np\n", + "import scipy\n", + "import nilearn\n", + "import nilearn.plotting\n", + "import nilearn.input_data\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "from xgboost import XGBClassifier\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import accuracy_score" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## No apperant contribution to before/after treatment in general. \n", + "- Lets look at group differences in ROIs $\\rightarrow$\n", + " * Amygdala\n", + " * vmPFC\n", + " * Hippocampus\n", + " * Striatum\n", + "- We compare pattern of ROI activation in the trauma > relax contrast on the 2nd day" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Amygdala as mask\n", + "mask_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=21\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "\n", + "\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " smoothing_fwhm=None, verbose=5).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# compare between groups\n", + "import pandas as pd\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "medication_cond\n", + "\n", + "condition_label = np.array(medication_cond.med_cond)\n", + "condition_label = list(map(int, condition_label))\n", + "condition_label" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "21" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Find relevant beta number\n", + "ses = '1' # set session number\n", + "beta_name = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses%s/modelfit/_subject_id_*/level1design/run0.fsf'%(ses))\n", + "len(beta_name)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# function to find ev number (lookin in run.fsf file)\n", + "def findEV(txtFile, condition):\n", + " # takes the txtFile and the specific condition\n", + " with open(txtFile) as f:\n", + " datafile = f.readlines()\n", + " lines = []\n", + " for line in datafile:\n", + " if condition in line:\n", + " # found = True # Not necessary\n", + " #print(line)\n", + " lines.append(line)\n", + "\n", + " return lines[0].split('evtitle')[1].split(')')[0]\n", + "\n", + "def getBetas(condition):\n", + " betaTemplate = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses{ses}/modelfit/_subject_id_{subject_id}/modelestimate/mapflow/_modelestimate0/results/pe{betaNum}.nii.gz'\n", + " beta_files = []\n", + " for beta in beta_name:\n", + " # get subject number\n", + " sub = beta.split('id_')[1].split('/')[0]\n", + " # get beta number\n", + " number = findEV(beta, condition)\n", + " # find beta file\n", + " betaFile = betaTemplate.format(ses=ses, subject_id = sub, betaNum = number)\n", + " # add it to list\n", + " beta_files.append(betaFile)\n", + " return beta_files.sort()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'condition' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0msub\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbeta\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'id_'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'/'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0;31m# get beta number\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mnumber\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfindEV\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbeta\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcondition\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;31m# find beta file\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mbetaFile\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbetaTemplate\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mses\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mses\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msubject_id\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msub\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbetaNum\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnumber\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'condition' is not defined" + ] + } + ], + "source": [ + "# get beta files\n", + "\n", + "betaTemplate = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses{ses}/modelfit/_subject_id_{subject_id}/modelestimate/mapflow/_modelestimate0/results/pe{betaNum}.nii.gz'\n", + "beta_files = []\n", + "for beta in beta_name:\n", + " # get subject number\n", + " sub = beta.split('id_')[1].split('/')[0]\n", + " # get beta number\n", + " number = findEV(beta, condition)\n", + " # find beta file\n", + " betaFile = betaTemplate.format(ses=ses, subject_id = sub, betaNum = number)\n", + " # add it to list\n", + " beta_files.append(betaFile)\n", + "beta_files.sort()\n", + "#beta_files" + ] + }, + { + "cell_type": "code", + "execution_count": 220, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_008/modelestimate/mapflow/_modelestimate0/results/pe27.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1223/modelestimate/mapflow/_modelestimate0/results/pe11.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1253/modelestimate/mapflow/_modelestimate0/results/pe27.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1263/modelestimate/mapflow/_modelestimate0/results/pe17.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1293/modelestimate/mapflow/_modelestimate0/results/pe27.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1307/modelestimate/mapflow/_modelestimate0/results/pe27.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1315/modelestimate/mapflow/_modelestimate0/results/pe17.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1322/modelestimate/mapflow/_modelestimate0/results/pe17.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running 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"[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1356/modelestimate/mapflow/_modelestimate0/results/pe17.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running 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data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1387/modelestimate/mapflow/_modelestimate0/results/pe27.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1390/modelestimate/mapflow/_modelestimate0/results/pe27.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1403/modelestimate/mapflow/_modelestimate0/results/pe27.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1464/modelestimate/mapflow/_modelestimate0/results/pe27.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1468/modelestimate/mapflow/_modelestimate0/results/pe17.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1480/modelestimate/mapflow/_modelestimate0/results/pe17.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1499/modelestimate/mapflow/_modelestimate0/results/pe27.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "data": { + "text/plain": [ + "(21, 3846)" + ] + }, + "execution_count": 220, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "allGroups = []\n", + "for func in beta_files:\n", + " print(f'Running {func}')\n", + " beta = masker.transform(func)\n", + " allGroups.append(beta)\n", + "\n", + "allArr = np.array(allGroups)\n", + "allArr_reshape= np.array(allArr).reshape(allArr.shape[0], allArr.shape[2])\n", + "allArr_reshape.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 221, + "metadata": {}, + "outputs": [], + "source": [ + "X = allArr_reshape" + ] + }, + { + "cell_type": "code", + "execution_count": 222, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "#from sklearn.model_selection import StratifiedKFold\n", + "from sklearn.svm import LinearSVC\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.model_selection import StratifiedKFold\n", + "from sklearn import svm\n", + "model = XGBClassifier(n_jobs=5, \n", + " verbose = 9, random_state=None)\n", + "\n", + "## Here we use stratified K-fold with shuffling to generate different shuffling of leave one subject out\n", + "cv = StratifiedKFold(n_splits=10, shuffle=True) # running for each subject\n" + ] + }, + { + "cell_type": "code", + "execution_count": 223, + "metadata": {}, + "outputs": [], + "source": [ + "scores = cross_val_score(model,\n", + " X,\n", + " y=condition_label,\n", + " cv=cv,\n", + " groups=condition_label,\n", + " scoring= \"roc_auc\",\n", + " n_jobs=1, # set number of CPUs\n", + " #verbose = 5 # set some details of the activity \n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 224, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0., 1., 1., 1., 0., 0., 1., 0., 0., 1.])" + ] + }, + "execution_count": 224, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "scores" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## Use shuffle split to randomize and run the XGboost N times\n", + "- This will create a distribution of estimation level \n", + "- We can then better estimate how really its more accurate than chance\n" + ] + }, + { + "cell_type": "code", + "execution_count": 227, + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running 1 iteration\n", + " Running 2 iteration\n", + " Running 3 iteration\n", + " Running 4 iteration\n", + " Running 5 iteration\n", + " Running 6 iteration\n", + " Running 7 iteration\n", + " Running 8 iteration\n", + " Running 9 iteration\n", + " Running 10 iteration\n", + " Running 11 iteration\n", + " Running 12 iteration\n", + " Running 13 iteration\n", + " Running 14 iteration\n", + " Running 15 iteration\n", + " Running 16 iteration\n", + " Running 17 iteration\n", + " Running 18 iteration\n", + " Running 19 iteration\n", + " Running 20 iteration\n", + " Running 21 iteration\n", + " Running 22 iteration\n" + ] + }, + { + "ename": "KeyboardInterrupt", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0mgroups\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcondition_label\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mscoring\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0;34m\"accuracy\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m \u001b[0mn_jobs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;31m# set number of CPUs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 13\u001b[0m \u001b[0;31m#verbose = 5 # set some details of the activity\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 14\u001b[0m )\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36minner_f\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 71\u001b[0m FutureWarning)\n\u001b[1;32m 72\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0marg\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0marg\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparameters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 73\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 74\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0minner_f\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 75\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/sklearn/model_selection/_validation.py\u001b[0m in \u001b[0;36mcross_val_score\u001b[0;34m(estimator, X, y, groups, scoring, cv, n_jobs, verbose, fit_params, pre_dispatch, error_score)\u001b[0m\n\u001b[1;32m 404\u001b[0m \u001b[0mfit_params\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfit_params\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 405\u001b[0m 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return_train_score, return_estimator, error_score)\u001b[0m\n\u001b[1;32m 246\u001b[0m \u001b[0mreturn_times\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreturn_estimator\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mreturn_estimator\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 247\u001b[0m error_score=error_score)\n\u001b[0;32m--> 248\u001b[0;31m for train, test in cv.split(X, y, groups))\n\u001b[0m\u001b[1;32m 249\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 250\u001b[0m \u001b[0mzipped_scores\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mscores\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/joblib/parallel.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, iterable)\u001b[0m\n\u001b[1;32m 1040\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1041\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_backend\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mretrieval_context\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1042\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mretrieve\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1043\u001b[0m \u001b[0;31m# Make sure that we get a last message telling us we are done\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1044\u001b[0m \u001b[0melapsed_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_start_time\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/joblib/parallel.py\u001b[0m in \u001b[0;36mretrieve\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 919\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 920\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_backend\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'supports_timeout'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 921\u001b[0;31m 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"\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/joblib/_parallel_backends.py\u001b[0m in \u001b[0;36mwrap_future_result\u001b[0;34m(future, timeout)\u001b[0m\n\u001b[1;32m 540\u001b[0m AsyncResults.get from multiprocessing.\"\"\"\n\u001b[1;32m 541\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 542\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfuture\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 543\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mCfTimeoutError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 544\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mTimeoutError\u001b[0m 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\u001b[0;32min\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mCANCELLED\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mCANCELLED_AND_NOTIFIED\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/threading.py\u001b[0m in \u001b[0;36mwait\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 294\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;31m# restore state no matter what (e.g., KeyboardInterrupt)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 295\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mtimeout\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 296\u001b[0;31m \u001b[0mwaiter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0macquire\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 297\u001b[0m \u001b[0mgotit\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 298\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " + ] + } + ], + "source": [ + "n_iter = 1000\n", + "rand_score = []\n", + "for i in range(n_iter):\n", + " print(f' Running {i+1} iteration')\n", + " mean_scores = []\n", + " scores = cross_val_score(model,\n", + " X,\n", + " y=condition_label,\n", + " cv=cv,\n", + " groups=condition_label,\n", + " scoring= \"accuracy\",\n", + " n_jobs=10, # set number of CPUs\n", + " #verbose = 5 # set some details of the activity \n", + " )\n", + " mean_scores.append(scores.mean())\n", + " rand_score.append(mean_scores)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "### Plotting area under ROC curve ditribution and printing average and standard deviation of the distribution" + ] + }, + { + "cell_type": "code", + "execution_count": 228, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Area under curve: 0.59 (+/- 0.19)\n", + "90% CI is [0.43333333 0.73333333]\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 228, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "rand_score = np.array(rand_score)\n", + "print(\"Area under curve: %0.2f (+/- %0.2f)\" % (np.mean(rand_score), np.std(rand_score) * 2))\n", + "print(f'90% CI is {np.quantile(rand_score, [0.05, 0.95])}')\n", + "sns.distplot(rand_score)" + ] + }, + { + "cell_type": "code", + "execution_count": 232, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=8)]: Using backend LokyBackend with 8 concurrent workers.\n", + "[Parallel(n_jobs=8)]: Done 2 tasks | elapsed: 5.4s\n", + "[Parallel(n_jobs=8)]: Done 56 tasks | elapsed: 40.6s\n", + "[Parallel(n_jobs=8)]: Done 146 tasks | elapsed: 1.8min\n", + "[Parallel(n_jobs=8)]: Done 272 tasks | elapsed: 3.2min\n", + "[Parallel(n_jobs=8)]: Done 434 tasks | elapsed: 5.1min\n", + "[Parallel(n_jobs=8)]: Done 632 tasks | elapsed: 7.3min\n", + "[Parallel(n_jobs=8)]: Done 866 tasks | elapsed: 10.1min\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Classification score 0.6 (pvalue : 0.40559440559440557)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=8)]: Done 1000 out of 1000 | elapsed: 11.6min finished\n" + ] + } + ], + "source": [ + "## use sklearn permutation test\n", + "from sklearn.model_selection import permutation_test_score\n", + "score, permutation_scores, pvalue = permutation_test_score(\n", + " model, X, condition_label, scoring=\"roc_auc\", cv=cv, n_permutations=1000, n_jobs=8, verbose=5)\n", + "\n", + "print(\"Classification score %s (pvalue : %s)\" % (score, pvalue))" + ] + }, + { + "cell_type": "code", + "execution_count": 231, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(21, 3846)" + ] + }, + "execution_count": 231, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "X.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 219, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=4\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None, standardize=False, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Lets look at the hippocampus" + ] + }, + { + "cell_type": "code", + "execution_count": 210, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=11\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None, standardize=False, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Striatum" + ] + }, + { + "cell_type": "code", + "execution_count": 204, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/binConjunc_PvNxDECxRECxMONxPRI_striatum.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=0.001\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None, standardize=False, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# An unrelated region (Primary motor cortex?) V1?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "celltoolbar": "Slideshow", + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/.ipynb_checkpoints/XGBoost-checkpoint.ipynb b/task_based_analysis/.ipynb_checkpoints/XGBoost-checkpoint.ipynb new file mode 100644 index 0000000..819fffe --- /dev/null +++ b/task_based_analysis/.ipynb_checkpoints/XGBoost-checkpoint.ipynb @@ -0,0 +1,7141 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "# Using machine learning XGboost classifier to look for different pattern between Ketamin and Midazolam groups" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [], + "source": [ + "# import relevant packages\n", + "import glob\n", + "import numpy as np\n", + "import scipy\n", + "import nilearn\n", + "import nilearn.plotting\n", + "import nilearn.input_data\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "from xgboost import XGBClassifier\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import accuracy_score" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## No apperant contribution to before/after treatment in general. \n", + "- Lets look at group differences in ROIs $\\rightarrow$\n", + " * Amygdala\n", + " * vmPFC\n", + " * Hippocampus\n", + " * Striatum\n", + "- We compare pattern of ROI activation in the trauma > relax contrast on the 2nd day" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Amygdala as mask\n", + "mask_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=20\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "\n", + "\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=4, standardize=False, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [], + "source": [ + "# compare between groups\n", + "import pandas as pd\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "\n", + "\n", + "ketamine_list = list(medication_cond['scr_id'][medication_cond['med_cond']==1])\n", + "ket_list = []\n", + "for subject in ketamine_list:\n", + " \n", + " sub = subject.split('KPE')[1]\n", + " ket_list.append(sub)\n", + "\n", + "\n", + "midazolam_list = list(medication_cond['scr_id'][medication_cond['med_cond']==0])\n", + "mid_list = []\n", + "for subject in midazolam_list:\n", + " \n", + " sub = subject.split('KPE')[1]\n", + " mid_list.append(sub)\n", + "#mid_list.remove('1480')" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['008',\n", + " '1223',\n", + " '1293',\n", + " '1307',\n", + " '1315',\n", + " '1322',\n", + " '1339',\n", + " '1343',\n", + " '1387',\n", + " '1464',\n", + " '1499']" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ket_list\n", + "## only for 3rd session\n", + "#ket_list.remove('1315')" + ] + }, + { + "cell_type": "code", + "execution_count": 133, + "metadata": {}, + "outputs": [], + "source": [ + "# only for 3rd session\n", + "#mid_list.remove('1253')\n", + "#mid_list.remove('1480')" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [], + "source": [ + "ses = '2'\n", + "ket_func = ['/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses%s/modelfit/_subject_id_%s/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz'% (ses,sub) for sub in ket_list]\n", + "mid_func = ['/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses%s/modelfit/_subject_id_%s/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz' % (ses, sub) for sub in mid_list]" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [], + "source": [ + "#ketamine_list.remove('KPE1315')\n", + "#mid_list.remove('1480')" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_008/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1223/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1293/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1307/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1315/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1322/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1339/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1343/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1387/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1464/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1499/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1253/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1263/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1351/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1356/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1364/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running 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None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1403/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1468/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1480/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "data": { + "text/plain": [ + "(21, 932)" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ketamine = []\n", + "for func in ket_func:\n", + " print(f'Running {func}')\n", + " beta = masker.fit_transform(func)\n", + " ketamine.append(beta)\n", + "\n", + "midazolam = []\n", + "for func in mid_func:\n", + " print(f'Running {func}')\n", + " beta = masker.fit_transform(func)\n", + " midazolam.append(beta)\n", + "\n", + "ketArr = np.array(ketamine)\n", + "ketArr_reshape= np.array(ketArr).reshape(ketArr.shape[0], ketArr.shape[2])\n", + "ketArr_reshape.shape\n", + "\n", + "\n", + "midArr = np.array(midazolam)\n", + "midArr_reshape= np.array(midArr).reshape(midArr.shape[0], midArr.shape[2])\n", + "midArr_reshape.shape\n", + "\n", + "\n", + "## Create condition labels (1 = plus, 0 = minus)\n", + "label1 = [1] * ketArr.shape[0]\n", + "label2 = [0] * midArr.shape[0]\n", + "condition_label = np.concatenate([label1, label2])\n", + "condition_label\n", + "\n", + "X = np.concatenate([ketArr, midArr])\n", + "X = X.reshape(X.shape[0], midArr_reshape.shape[1])\n", + "X.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "#from sklearn.model_selection import StratifiedKFold\n", + "from sklearn.svm import LinearSVC\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.model_selection import StratifiedKFold\n", + "from sklearn import svm\n", + "model = XGBClassifier(n_jobs=5, \n", + " verbose = 9, random_state=None)\n", + "\n", + "## Here we use stratified K-fold with shuffling to generate different shuffling of leave one subject out\n", + "cv = StratifiedKFold(n_splits=10, shuffle=True) # running for each subject\n" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "scores = cross_val_score(model,\n", + " X,\n", + " y=condition_label,\n", + " cv=cv,\n", + " groups=condition_label,\n", + " scoring= \"roc_auc\",\n", + " n_jobs=1, # set number of CPUs\n", + " #verbose = 5 # set some details of the activity \n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.5, 1. , 1. , 1. , 0. , 1. , 0. , 1. , 1. , 1. ])" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "scores" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## Use shuffle split to randomize and run the XGboost N times\n", + "- This will create a distribution of estimation level \n", + "- We can then better estimate how really its more accurate than chance\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "name": "stdout", + 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y=condition_label,\n", + " cv=cv,\n", + " groups=condition_label,\n", + " scoring= \"accuracy\",\n", + " n_jobs=1, # set number of CPUs\n", + " #verbose = 5 # set some details of the activity \n", + " )\n", + " mean_scores.append(scores.mean())\n", + " rand_score.append(mean_scores)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "### Plotting area under ROC curve ditribution and printing average and standard deviation of the distribution" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Area under curve: 0.70 (+/- 0.13)\n", + "90% CI is [0.59166667 0.76666667]\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "rand_score = np.array(rand_score)\n", + "print(\"Area under curve: %0.2f (+/- %0.2f)\" % (np.mean(rand_score), np.std(rand_score) * 2))\n", + "print(f'90% CI is {np.quantile(rand_score, [0.05, 0.95])}')\n", + "sns.distplot(rand_score)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=5)]: Using backend LokyBackend with 5 concurrent workers.\n", + "[Parallel(n_jobs=5)]: Done 8 tasks | elapsed: 3.1s\n", + "[Parallel(n_jobs=5)]: Done 62 tasks | elapsed: 15.8s\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Classification score 0.775 (pvalue : 0.0891089108910891)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=5)]: Done 100 out of 100 | elapsed: 23.7s finished\n" + ] + } + ], + "source": [ + "## use sklearn permutation test\n", + "from sklearn.model_selection import permutation_test_score\n", + "score, permutation_scores, pvalue = permutation_test_score(\n", + " model, X, condition_label, scoring=\"roc_auc\", cv=cv, n_permutations=100, n_jobs=5, verbose=5)\n", + "\n", + "print(\"Classification score %s (pvalue : %s)\" % (score, pvalue))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## Now we will do similar thing - just shuffling the condition label (Y) so we basically randomizing the lables\n", + "This should generate a chance level prediction" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [], + "source": [ + "## Lets do permutation tests - shuffling the condition label\n", + "import random\n", + "condPerm = np.array(condition_label)\n", + "permScor = []\n", + "#cv = KFold(n_splits=10)\n", + "for i in range(n_iter):\n", + " print (f'Running the {i+1} iteration')\n", + " random.shuffle(condPerm)\n", + " print(condPerm)\n", + " \n", + " mean_scores = []\n", + " cv_scores = cross_val_score(model,\n", + " X,\n", + " y=condPerm,\n", + " cv=cv,\n", + " groups=condPerm,\n", + " scoring=\"f1\",#\"roc_auc\",\n", + " n_jobs=11, # set number of CPUs\n", + " #verbose = 5 # set some details of the activity \n", + " )\n", + " mean_scores.append(cv_scores.mean())\n", + " permScor.append(mean_scores)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "# now lets see the mean score\n", + "score = np.array(permScor)\n", + "\n", + "#import matplotlib.pyplot as plt\n", + "plt.hist(score)\n", + "print(f' Mean of permutation score is {np.mean(score)}')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [], + "source": [ + "#plot permutation histogram and real one\n", + "plt.hist(score, color=\"blue\")\n", + "plt.hist(rand_score, color=\"red\")\n", + "# chances of getting our score\n", + "print(f' Chances of mean permutation score to be random is {len(score[score>=np.mean(rand_score)])/len(score)}')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [], + "source": [ + "\n", + "sns.distplot(score, hist=True, rug=True)\n", + "sns.distplot(rand_score, hist=True, rug=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [], + "source": [ + "weights = np.ones_like(score) / len(score)\n", + "weights_real = np.ones_like(rand_score) / len(rand_score)\n", + "plt.hist(score, weights=weights)\n", + "plt.hist(rand_score, weights=weights_real)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## Lets plot each group's array to see the pattern of activation" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "-351.12814" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "## check maximum and minimum values\n", + "np.min(midArr_reshape)" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "#plt.figure(figsize=(30,10))\n", + "sns.heatmap(ketArr_reshape, cmap=\"coolwarm\", vmax=200, vmin = -200)#,linewidth=0.1)\n", + "plt.show()\n", + "#plt.imshow(ketArr_reshape, axis=0), cmap = \"hot\")" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#plt.figure(figsize=(30,10))\n", + "sns.heatmap(midArr_reshape, cmap=\"coolwarm\",vmax=200, vmin = -200)#,linewidth=0.1)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "### plot average pattern for each group\n", + "- Ketamin\n" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(50,8))\n", + "sns.heatmap([np.mean(ketArr_reshape, axis=0)],cmap=\"coolwarm\",vmax=200, vmin = -200 )" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "- Midazolam" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(50,8))\n", + "sns.heatmap([np.mean(midArr_reshape, axis=0)],cmap=\"coolwarm\",vmax=200, vmin = -200 )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [], + "source": [ + "deltaKetminusMid = np.mean(ketArr_reshape, axis=0) - np.mean(midArr_reshape, axis=0)\n", + "np.mean(deltaKetminusMid)" + ] + }, + { + "cell_type": "code", + "execution_count": 171, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 171, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# t test\n", + "tTestArr = scipy.stats.ttest_ind(ketArr_reshape, midArr_reshape, equal_var=True, nan_policy='propagate')\n", + "plt.figure(figsize=(40,10))\n", + "sns.heatmap([tTestArr[0]], cmap=\"coolwarm\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## show the t-test difference between the groups" + ] + }, + { + "cell_type": "code", + "execution_count": 173, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 173, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# turn back to brain?\n", + "img = masker.inverse_transform(tTestArr[0])\n", + "nilearn.plotting.plot_stat_map(img, display_mode='y', threshold=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## Plot amygdala pattern in each group" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "img_ket = masker.inverse_transform(np.mean(ketArr_reshape, axis=0))\n", + "nilearn.plotting.plot_stat_map(img_ket, threshold=1.5, display_mode='yz', draw_cross=False, \n", + " cut_coords=[-2,-18],colorbar=True, vmax=99) \n", + "nilearn.plotting.plot_glass_brain(img_ket, vmin = -200, vmax = 200, colorbar=True, plot_abs=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "img_mid = masker.inverse_transform(np.mean(midArr_reshape, axis=0))\n", + "nilearn.plotting.plot_stat_map(img_mid, threshold=1.5, display_mode='yz', draw_cross=False, \n", + " cut_coords=[-2,-18],colorbar=True, vmax=99)" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# another trial of interactive plottive \n", + "view = nilearn.plotting.view_img(img, threshold=2, title=\"Ketamine - Midazolam Amygdala\")\n", + "view" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nilearn.plotting.plot_roi(img)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## Now we do similar thing but with vmPFC \n", + "As it might be involved in regular (no reconsolidated) extinction learning" + ] + }, + { + "cell_type": "code", + "execution_count": 161, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=5\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=4, standardize=False, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "code", + "execution_count": 162, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_008/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1223/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1293/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1307/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running 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+ "n_iter = 1000\n", + "rand_score = []\n", + "for i in range(n_iter):\n", + " print(f' Running {i+1} iteration')\n", + " mean_scores = []\n", + " scores = cross_val_score(model,\n", + " X,\n", + " y=condition_label,\n", + " cv=cv,\n", + " groups=condition_label,\n", + " scoring= \"accuracy\",#\"roc_auc\",\n", + " n_jobs=1, # set number of CPUs\n", + " \n", + " )\n", + " mean_scores.append(scores.mean())\n", + " rand_score.append(mean_scores)" + ] + }, + { + "cell_type": "code", + "execution_count": 164, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Area under curve: 0.94 (+/- 0.02)\n", + "90% CI is [0.92857143 0.95238095]\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 164, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "rand_score = np.array(rand_score)\n", + "print(\"Area under curve: %0.2f (+/- %0.2f)\" % (np.mean(rand_score), np.std(rand_score) * 2))\n", + "print(f'90% CI is {np.quantile(rand_score, [0.05, 0.95])}')\n", + "sns.distplot(rand_score)" + ] + }, + { + "cell_type": "code", + "execution_count": 165, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.\n", + "[Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.3s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.6s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 3 out of 3 | elapsed: 0.9s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 4 out of 4 | elapsed: 1.2s remaining: 0.0s\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Classification score 0.9285714285714286 (pvalue : 0.013972055888223553)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=1)]: Done 500 out of 500 | elapsed: 2.6min finished\n" + ] + } + ], + "source": [ + "## use sklearn permutation test\n", + "from sklearn.model_selection import permutation_test_score\n", + "score, permutation_scores, pvalue = permutation_test_score(\n", + " model, X, condition_label, scoring=\"accuracy\", cv=cv, n_permutations=500, n_jobs=1, verbose=5)\n", + "\n", + "print(\"Classification score %s (pvalue : %s)\" % (score, pvalue))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Same method does somehow discriminate between midazolam and ketamine group\n", + "\n", + "\n", + "### Let's look at the pattern of activation" + ] + }, + { + "cell_type": "code", + "execution_count": 168, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 168, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "img_ket = masker.inverse_transform(np.mean(ketArr_reshape, axis=0))\n", + "nilearn.plotting.plot_stat_map(img_ket, threshold=1, display_mode='ortho', draw_cross=False, \n", + " cut_coords=[0,42,-7], colorbar=True, vmax=100)" + ] + }, + { + "cell_type": "code", + "execution_count": 175, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 175, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "img_mid = masker.inverse_transform(np.mean(midArr_reshape, axis=0))\n", + "nilearn.plotting.plot_stat_map(img_mid, threshold=1.5, display_mode='ortho', draw_cross=False, \n", + " cut_coords=[0,42,-7], colorbar=True, vmax=100)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Seems like midazolam presents higher activation in some regions of the vmPFC.\n", + "\n", + "This supports the idea of ketamine as promoting reconsolidation, while midazolam patients recovery is more associated with the typical, yet transient extinction." + ] + }, + { + "cell_type": "code", + "execution_count": 176, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 176, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# t test\n", + "tTestArr = scipy.stats.ttest_ind(ketArr_reshape, midArr_reshape, equal_var=True, nan_policy='propagate')\n", + "plt.figure(figsize=(40,10))\n", + "sns.heatmap([tTestArr[0]], cmap=\"coolwarm\")" + ] + }, + { + "cell_type": "code", + "execution_count": 180, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 180, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# turn back to brain?\n", + "img = masker.inverse_transform(tTestArr[0])\n", + "nilearn.plotting.plot_stat_map(img, display_mode='ortho',cut_coords=[0,42,-7], threshold=1.5)" + ] + }, + { + "cell_type": "code", + "execution_count": 181, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 181, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "nilearn.plotting.view_img(img, threshold=2, title=\"Ketamine - Midazolam VMpfc\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Lets look at the hippocampus" + ] + }, + { + "cell_type": "code", + "execution_count": 149, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=13\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=4, standardize=False, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "code", + "execution_count": 150, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_008/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1223/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1293/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1307/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1322/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1339/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1343/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1387/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running 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None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1263/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1351/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1356/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + 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0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1403/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "data": { + "text/plain": [ + "(7, 1265)" + ] + }, + "execution_count": 150, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "## run all analysis in one cell\n", + "ketamine = []\n", + "for func in ket_func:\n", + " print(f'Running {func}')\n", + " beta = masker.fit_transform(func)\n", + " ketamine.append(beta)\n", + "midazolam = []\n", + "for func in mid_func:\n", + " print(f'Running {func}')\n", + " beta = masker.fit_transform(func)\n", + " midazolam.append(beta)\n", + "ketArr = np.array(ketamine)\n", + "ketArr_reshape= np.array(ketArr).reshape(ketArr.shape[0], ketArr.shape[2])\n", + "ketArr_reshape.shape\n", + "midArr = np.array(midazolam)\n", + "midArr_reshape= np.array(midArr).reshape(midArr.shape[0], midArr.shape[2])\n", + "midArr_reshape.shape\n" + ] + }, + { + "cell_type": "code", + "execution_count": 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iteration\n", + " Running 988 iteration\n", + " Running 989 iteration\n", + " Running 990 iteration\n", + " Running 991 iteration\n", + " Running 992 iteration\n", + " Running 993 iteration\n", + " Running 994 iteration\n", + " Running 995 iteration\n", + " Running 996 iteration\n", + " Running 997 iteration\n", + " Running 998 iteration\n", + " Running 999 iteration\n", + " Running 1000 iteration\n" + ] + } + ], + "source": [ + "## Create condition labels (1 = plus, 0 = minus)\n", + "label1 = [1] * ketArr.shape[0]\n", + "label2 = [0] * midArr.shape[0]\n", + "condition_label = np.concatenate([label1, label2])\n", + "condition_label\n", + "\n", + "X = np.concatenate([ketArr, midArr])\n", + "X = X.reshape(X.shape[0], midArr_reshape.shape[1])\n", + "X.shape\n", + "\n", + "n_iter = 1000\n", + "rand_score = []\n", + "for i in range(n_iter):\n", + " print(f' Running {i+1} iteration')\n", + " mean_scores = []\n", + " scores = cross_val_score(model,\n", + " X,\n", + " y=condition_label,\n", + " cv=cv,\n", + " groups=condition_label,\n", + " scoring= \"accuracy\",\n", + " n_jobs=1, # set number of CPUs\n", + " #verbose = 5 # set some details of the activity \n", + " )\n", + " mean_scores.append(scores.mean())\n", + " rand_score.append(mean_scores)" + ] + }, + { + "cell_type": "code", + "execution_count": 153, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Area under curve: 0.64 (+/- 0.15)\n", + "90% CI is [0.52380952 0.76190476]\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 153, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "rand_score = np.array(rand_score)\n", + "print(\"Area under curve: %0.2f (+/- %0.2f)\" % (np.mean(rand_score), np.std(rand_score) * 2))\n", + "print(f'90% CI is {np.quantile(rand_score, [0.05, 0.95])}')\n", + "sns.distplot(rand_score)" + ] + }, + { + "cell_type": "code", + "execution_count": 155, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.\n", + "[Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.2s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.4s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 3 out of 3 | elapsed: 0.6s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 4 out of 4 | elapsed: 0.7s remaining: 0.0s\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Classification score 0.619047619047619 (pvalue : 0.3069306930693069)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=1)]: Done 100 out of 100 | elapsed: 19.3s finished\n" + ] + } + ], + "source": [ + "score, permutation_scores, pvalue = permutation_test_score(\n", + " model, X, condition_label, scoring=\"accuracy\", cv=cv, n_permutations=100, n_jobs=1, verbose=5)\n", + "\n", + "print(\"Classification score %s (pvalue : %s)\" % (score, pvalue))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "img_ket = masker.inverse_transform(np.mean(ketArr_reshape, axis=0))\n", + "nilearn.plotting.plot_stat_map(img_ket, threshold=1, display_mode='ortho', draw_cross=False, \n", + " cut_coords=[-27,-20,-14], colorbar=True, vmax=40)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "img_mid = masker.inverse_transform(np.mean(midArr_reshape, axis=0))\n", + "nilearn.plotting.plot_stat_map(img_mid, threshold=1, display_mode='ortho', draw_cross=False, \n", + " cut_coords=[-27,-20,-14], colorbar=True, vmax=40)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#plt.figure(figsize=(30,10))\n", + "sns.heatmap(ketArr_reshape, cmap=\"coolwarm\", vmax=200, vmin = -200)\n", + "plt.title(\"Ketamine Pattern\")\n", + "plt.show()\n", + "#plt.figure(figsize=(30,10))\n", + "sns.heatmap(midArr_reshape, cmap=\"coolwarm\", vmax=200, vmin = -200)\n", + "plt.title(\"Midazolam Pattern\")\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "tTestArr = scipy.stats.ttest_ind(ketArr_reshape, midArr_reshape, equal_var=True, nan_policy='propagate')\n", + "plt.figure(figsize=(40,10))\n", + "sns.heatmap([tTestArr[0]], cmap=\"coolwarm\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# turn back to brain?\n", + "img = masker.inverse_transform(tTestArr[0]) # turn the t array back to brain image\n", + "nilearn.plotting.plot_stat_map(img, display_mode='x', threshold=1.3) # stat plot everything beyond threshold\n", + "#nilearn.plotting.plot_img(img, threshold=.001, display_mode='z') # just plot the ROI image\n", + "# one interactive plot - so we can play with locations\n", + "#view = plotting.view_img(img, threshold=2, title=\"Ketamine - Midazolam Hippocampus\")\n", + "#view\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Striatum" + ] + }, + { + "cell_type": "code", + "execution_count": 188, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/binConjunc_PvNxDECxRECxMONxPRI_striatum.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=0.001\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=4, standardize=False, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "code", + "execution_count": 189, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_008/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1223/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1293/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1307/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1322/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1339/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1343/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1387/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running 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minus)\n", + "label1 = [1] * ketArr.shape[0]\n", + "label2 = [0] * midArr.shape[0]\n", + "condition_label = np.concatenate([label1, label2])\n", + "condition_label\n", + "\n", + "X = np.concatenate([ketArr, midArr])\n", + "X = X.reshape(X.shape[0], midArr_reshape.shape[1])\n", + "X.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 158, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running 1 iteration\n", + " Running 2 iteration\n", + " Running 3 iteration\n", + " Running 4 iteration\n", + " Running 5 iteration\n", + " Running 6 iteration\n", + " Running 7 iteration\n", + " Running 8 iteration\n", + " Running 9 iteration\n", + " Running 10 iteration\n", + " Running 11 iteration\n", + " Running 12 iteration\n", + " Running 13 iteration\n", + " Running 14 iteration\n", + " Running 15 iteration\n", + " Running 16 iteration\n", + " Running 17 iteration\n", + " Running 18 iteration\n", + " Running 19 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groups=condition_label,\n", + " scoring= \"accuracy\",\n", + " n_jobs=1, # set number of CPUs\n", + " #verbose = 5 # set some details of the activity \n", + " )\n", + " mean_scores.append(scores.mean())\n", + " rand_score.append(mean_scores)" + ] + }, + { + "cell_type": "code", + "execution_count": 159, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Area under curve: 0.62 (+/- 0.18)\n", + "90% CI is [0.47619048 0.76190476]\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 159, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "rand_score = np.array(rand_score)\n", + "print(\"Area under curve: %0.2f (+/- %0.2f)\" % (np.mean(rand_score), np.std(rand_score) * 2))\n", + "print(f'90% CI is {np.quantile(rand_score, [0.05, 0.95])}')\n", + "sns.distplot(rand_score)" + ] + }, + { + "cell_type": "code", + "execution_count": 160, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.\n", + "[Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.1s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.2s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 3 out of 3 | elapsed: 0.3s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 4 out of 4 | elapsed: 0.4s remaining: 0.0s\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Classification score 0.6428571428571429 (pvalue : 0.2714570858283433)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=1)]: Done 500 out of 500 | elapsed: 47.0s finished\n" + ] + } + ], + "source": [ + "score, permutation_scores, pvalue = permutation_test_score(\n", + " model, X, condition_label, scoring=\"accuracy\", cv=cv, n_permutations=500, n_jobs=1, verbose=5)\n", + "\n", + "print(\"Classification score %s (pvalue : %s)\" % (score, pvalue))" + ] + }, + { + "cell_type": "code", + "execution_count": 190, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 190, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "img_ket = masker.inverse_transform(np.mean(ketArr_reshape, axis=0))\n", + "nilearn.plotting.plot_stat_map(img_ket, threshold=1, display_mode='ortho', draw_cross=False, \n", + " cut_coords=[-2,10,-4], colorbar=True, vmax=40)" + ] + }, + { + "cell_type": "code", + "execution_count": 191, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 191, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "img_mid= masker.inverse_transform(np.mean(midArr_reshape, axis=0))\n", + "nilearn.plotting.plot_stat_map(img_mid, threshold=1, display_mode='ortho', draw_cross=False, \n", + " cut_coords=[-2,10,-4], colorbar=True, vmax=40)" + ] + }, + { + "cell_type": "code", + "execution_count": 192, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 192, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "tTestArr = scipy.stats.ttest_ind(ketArr_reshape, midArr_reshape, equal_var=True, nan_policy='propagate')\n", + "plt.figure(figsize=(40,10))\n", + "sns.heatmap([tTestArr[0]], cmap=\"coolwarm\")" + ] + }, + { + "cell_type": "code", + "execution_count": 193, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 193, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "img = masker.inverse_transform(tTestArr[0]) # turn the t array back to brain image\n", + "nilearn.plotting.plot_stat_map(img, display_mode='x', threshold=1.3) # stat plot everything beyond threshold" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## We need to run permutation test to see if the values we get are actually different than something we might randomly get" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# organize labels of group and vector for each\n", + "\n", + "# start shuffle the group and see how many times we get such a difference" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Using the t-tests and FDR to see what survives" + ] + }, + { + "cell_type": "code", + "execution_count": 182, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ttest_indResult(statistic=array([ 0.41356513, -0.18528277, -2.0933478 , ..., -0.79962456,\n", + " -0.91735995, -1.1412845 ], dtype=float32), pvalue=array([0.6850448 , 0.85548933, 0.05372314, ..., 0.43640887, 0.3734689 ,\n", + " 0.27164508]))" + ] + }, + "execution_count": 182, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# First simple t test like we did befor\n", + "tTestArr = scipy.stats.ttest_ind(ketArr_reshape, midArr_reshape, equal_var=True, nan_policy='propagate')\n", + "tTestArr" + ] + }, + { + "cell_type": "code", + "execution_count": 184, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of significant voxels is 1\n" + ] + } + ], + "source": [ + "# use fdr correction for multiple comparisons\n", + "from statsmodels.stats import multitest\n", + "# we need to reshape the test p-values array to create 1D array\n", + "alpha = .1 # set p value\n", + "fdr_mat = multitest.multipletests(tTestArr[1], alpha=alpha, method='fdr_bh', is_sorted=False, returnsorted=False)\n", + "print(f'Number of significant voxels is {np.sum(fdr_mat[0])}')" + ] + }, + { + "cell_type": "code", + "execution_count": 185, + "metadata": {}, + "outputs": [], + "source": [ + "# threshold the t array \n", + "corr_mat_thrFDR = np.array(tTestArr[0])\n", + "corr_mat_thrFDR[fdr_mat[0]==False] = 0\n", + "# now we can turn it back to brain image and plot \n", + "fdr_img = masker.inverse_transform(corr_mat_thrFDR)\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 187, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 187, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nilearn.plotting.plot_stat_map(fdr_img, display_mode='x')" + ] + } + ], + "metadata": { + "celltoolbar": "Slideshow", + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/.ipynb_checkpoints/average_Comp_ROIs-checkpoint.ipynb b/task_based_analysis/.ipynb_checkpoints/average_Comp_ROIs-checkpoint.ipynb new file mode 100644 index 0000000..944d410 --- /dev/null +++ b/task_based_analysis/.ipynb_checkpoints/average_Comp_ROIs-checkpoint.ipynb @@ -0,0 +1,6071 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Comparing Ketamine and Midazolam after treatment in ROIs\n", + "- focus on end of treatment\n", + "- Amygdala\n", + "- vmPFC\n", + "- Hippocampus" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "# import relevant packages\n", + "import glob\n", + "import numpy as np\n", + "import scipy\n", + "import nilearn\n", + "import nilearn.image\n", + "import nilearn.plotting\n", + "import nilearn.input_data\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import pandas as pd\n", + "import pymc3 as pm\n", + "import arviz as az\n", + "import dask\n", + "import statsmodels.api as sm\n", + "import statsmodels.formula.api as smf" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1253/ses-1/func/sub-1253_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.1025577043674729\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1356/ses-1/func/sub-1356_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.17494762097491226\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1339/ses-1/func/sub-1339_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.2077268245048889\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1561/ses-1/func/sub-1561_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.11021738126863087\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-008/ses-1/func/sub-008_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.14191055547093234\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1480/ses-1/func/sub-1480_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.1738407010630942\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1322/ses-1/func/sub-1322_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.23673324713916447\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1343/ses-1/func/sub-1343_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.1488731626509649\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1387/ses-1/func/sub-1387_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.23898132487648083\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1263/ses-1/func/sub-1263_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.18431874512925736\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1499/ses-1/func/sub-1499_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.1677553626829104\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1468/ses-1/func/sub-1468_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.21405186170523605\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1403/ses-1/func/sub-1403_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.22577934756631762\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1351/ses-1/func/sub-1351_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.3276853469824854\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1390/ses-1/func/sub-1390_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.16501041661232188\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1293/ses-1/func/sub-1293_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.17582867045780554\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1578/ses-1/func/sub-1578_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.17796583895372753\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1573/ses-1/func/sub-1573_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.46715496864420697\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1307/ses-1/func/sub-1307_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.39881746948757496\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1464/ses-1/func/sub-1464_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.2263467090601724\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1369/ses-1/func/sub-1369_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.4420321038141352\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1364/ses-1/func/sub-1364_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.1891590580069025\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1223/ses-1/func/sub-1223_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.21993026206772767\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1419/ses-1/func/sub-1419_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.14028772150679011\n", + "/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-1315/ses-1/func/sub-1315_ses-1_task-Memory_desc-confounds_regressors.tsv\n", + "0.20839440234500298\n" + ] + } + ], + "source": [ + "## Check mean FD for each subject\n", + "# session 1 - \n", + "regFiles = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-*/ses-1/func/sub-*_ses-1_task-Memory_desc-confounds_regressors.tsv')\n", + "#df.columns.values.tolist()\n", + "for file in regFiles:\n", + " df = pd.read_csv(file, sep=\"\\t\")\n", + " print(file)\n", + " print(df['framewise_displacement'].mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_008/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1223/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1253/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1263/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1293/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1307/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1315/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1322/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1339/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1343/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1351/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1356/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1364/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1369/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1387/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1390/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1403/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1419/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1464/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1468/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1480/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1499/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1561/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1573/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1578/modelestimate/results/cope7.nii.gz']" + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Set session\n", + "ses = 1\n", + "## Grab group\n", + "# compare between groups\n", + "\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "\n", + "func_files = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses%s/modelfit/_subject_id_*/modelestimate/results/cope7.nii.gz' %(ses))\n", + "#func_files = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/allScript_ses%s/modelfit_ses_%s/_subject_id_*/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz' %(ses, ses))\n", + "\n", + "func_files.sort()\n", + "func_files" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Amygdala as mask\n", + "mask_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=25\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "\n", + "\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " smoothing_fwhm=None, standardize=True,\n", + " detrend=False, verbose=9)" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading 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"shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "## using dask to pararelize fit transform\n", + "t_arr = []\n", + "mean_act = []\n", + "scr_id = []\n", + "#delayed_get_data = dask.delayed(masker.fit_transform)\n", + "for func in func_files:\n", + " # get subject number\n", + " scr_id.append('KPE' + func.split('id_')[1].split('/')[0])\n", + " # get average activation\n", + " t_map = dask.delayed(masker.fit_transform)(func)\n", + " t_arr.append(dask.delayed(np.mean)(t_map))\n", + " \n", + "average = dask.compute(t_arr)\n", + " #mean_act.append(t_map)\n", + " \n", + " #h = np.mean(t_map)" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [], + "source": [ + "df_ses3 = []\n", + "df_ses3 = pd.DataFrame({'scr_id': scr_id, 'amg3': average[0]})\n", + "df_ses3 = pd.merge(medication_cond, df_ses3)\n", + "df_ses3 = df_ses3.rename(columns={'med_cond': 'group'})\n", + "#df['group'] = medication_cond['med_cond']\n", + "df_ses3 = df_ses3.replace(to_replace={'group': {0.0:'midazolam', 1.0:'ketamine'}})" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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scr_idgroupamg1
0KPE008ketamine28.970097
1KPE1223ketamine13.012181
2KPE1253midazolam0.108282
3KPE1263midazolam-21.872662
4KPE1293ketamine-7.580429
5KPE1307ketamine-38.789413
6KPE1315ketamine-21.045033
7KPE1322ketamine40.718792
8KPE1339ketamine-2.454142
9KPE1343ketamine-90.909035
10KPE1351midazolam-28.428524
11KPE1356midazolam-17.781033
12KPE1364midazolam-13.385894
13KPE1369midazolam110.843590
14KPE1387ketamine-16.330170
15KPE1390midazolam-12.436435
16KPE1403midazolam24.746063
17KPE1419ketamine-16.783064
18KPE1464ketamine26.202894
19KPE1468midazolam-2.376417
20KPE1480midazolam80.050438
21KPE1499ketamine48.258152
22KPE1561midazolam15.476287
23KPE1573ketamine17.051298
24KPE1578midazolam33.940796
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" + ], + "text/plain": [ + " scr_id group amg1\n", + "0 KPE008 ketamine 28.970097\n", + "1 KPE1223 ketamine 13.012181\n", + "2 KPE1253 midazolam 0.108282\n", + "3 KPE1263 midazolam -21.872662\n", + "4 KPE1293 ketamine -7.580429\n", + "5 KPE1307 ketamine -38.789413\n", + "6 KPE1315 ketamine -21.045033\n", + "7 KPE1322 ketamine 40.718792\n", + "8 KPE1339 ketamine -2.454142\n", + "9 KPE1343 ketamine -90.909035\n", + "10 KPE1351 midazolam -28.428524\n", + "11 KPE1356 midazolam -17.781033\n", + "12 KPE1364 midazolam -13.385894\n", + "13 KPE1369 midazolam 110.843590\n", + "14 KPE1387 ketamine -16.330170\n", + "15 KPE1390 midazolam -12.436435\n", + "16 KPE1403 midazolam 24.746063\n", + "17 KPE1419 ketamine -16.783064\n", + "18 KPE1464 ketamine 26.202894\n", + "19 KPE1468 midazolam -2.376417\n", + "20 KPE1480 midazolam 80.050438\n", + "21 KPE1499 ketamine 48.258152\n", + "22 KPE1561 midazolam 15.476287\n", + "23 KPE1573 ketamine 17.051298\n", + "24 KPE1578 midazolam 33.940796" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_ses1" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [], + "source": [ + "df_ses1 = pd.merge(df, df_ses1)\n", + "df_ses1['amg_change'] = df_ses1.meanAct - df_ses1.amg1" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# this is in case we need to show the lowering of amygdala reactivation before and after treatment\n", + "sns.boxplot(y='amg1', x= 'group', data = df_ses1)\n", + "sns.stripplot(y='amg1', x= 'group', data = df_ses1)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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scr_idgroupmeanActgroupIdxvmPFChippostriatumAcamg3
0KPE008ketamine3.1901201-0.072546-5.5291552.483448-6.452068
1KPE1223ketamine12.91250219.66234818.528749-10.181743-25.161104
2KPE1263midazolam12.12987208.88953821.97941029.35497958.742424
3KPE1293ketamine-20.2331181-7.122487-19.774799-12.404725-17.078924
4KPE1307ketamine-52.2213101-29.786623-28.613234-9.516820-11.628900
5KPE1322ketamine13.528724133.13494111.50446113.141923-50.048515
6KPE1339ketamine-3.3691651-1.105649-3.718665-32.740704-0.137346
7KPE1343ketamine-65.0852201-11.860424-50.98640128.125856-51.072002
8KPE1351midazolam-18.5520020-25.503946-44.4484714.393234-1.437943
9KPE1356midazolam30.8837200-14.83609713.315349-1.926483-1.711294
10KPE1364midazolam56.474892016.96603445.53267345.82691263.315742
11KPE1369midazolam26.3963910-45.5105096.881987-45.61096613.279358
12KPE1387ketamine-13.5788521-11.315875-3.810227-4.811108-9.722885
13KPE1390midazolam7.84772801.090048-3.209616-25.851357-6.360809
14KPE1403midazolam2.05465807.03655725.67226611.806690-17.095680
15KPE1419ketamine-22.49930415.8007159.04819222.4217112.970581
16KPE1464ketamine-31.1857321-23.971344-56.4882518.19493119.177311
17KPE1499ketamine-53.8379101-47.302711-29.856201-18.45126230.116594
18KPE1561midazolam23.159636010.8377893.59905016.30591613.836721
\n", + "
" + ], + "text/plain": [ + " scr_id group meanAct groupIdx vmPFC hippo striatumAc \\\n", + "0 KPE008 ketamine 3.190120 1 -0.072546 -5.529155 2.483448 \n", + "1 KPE1223 ketamine 12.912502 1 9.662348 18.528749 -10.181743 \n", + "2 KPE1263 midazolam 12.129872 0 8.889538 21.979410 29.354979 \n", + "3 KPE1293 ketamine -20.233118 1 -7.122487 -19.774799 -12.404725 \n", + "4 KPE1307 ketamine -52.221310 1 -29.786623 -28.613234 -9.516820 \n", + "5 KPE1322 ketamine 13.528724 1 33.134941 11.504461 13.141923 \n", + "6 KPE1339 ketamine -3.369165 1 -1.105649 -3.718665 -32.740704 \n", + "7 KPE1343 ketamine -65.085220 1 -11.860424 -50.986401 28.125856 \n", + "8 KPE1351 midazolam -18.552002 0 -25.503946 -44.448471 4.393234 \n", + "9 KPE1356 midazolam 30.883720 0 -14.836097 13.315349 -1.926483 \n", + "10 KPE1364 midazolam 56.474892 0 16.966034 45.532673 45.826912 \n", + "11 KPE1369 midazolam 26.396391 0 -45.510509 6.881987 -45.610966 \n", + "12 KPE1387 ketamine -13.578852 1 -11.315875 -3.810227 -4.811108 \n", + "13 KPE1390 midazolam 7.847728 0 1.090048 -3.209616 -25.851357 \n", + "14 KPE1403 midazolam 2.054658 0 7.036557 25.672266 11.806690 \n", + "15 KPE1419 ketamine -22.499304 1 5.800715 9.048192 22.421711 \n", + "16 KPE1464 ketamine -31.185732 1 -23.971344 -56.488251 8.194931 \n", + "17 KPE1499 ketamine -53.837910 1 -47.302711 -29.856201 -18.451262 \n", + "18 KPE1561 midazolam 23.159636 0 10.837789 3.599050 16.305916 \n", + "\n", + " amg3 \n", + "0 -6.452068 \n", + "1 -25.161104 \n", + "2 58.742424 \n", + "3 -17.078924 \n", + "4 -11.628900 \n", + "5 -50.048515 \n", + "6 -0.137346 \n", + "7 -51.072002 \n", + "8 -1.437943 \n", + "9 -1.711294 \n", + "10 63.315742 \n", + "11 13.279358 \n", + "12 -9.722885 \n", + "13 -6.360809 \n", + "14 -17.095680 \n", + "15 2.970581 \n", + "16 19.177311 \n", + "17 30.116594 \n", + "18 13.836721 " + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_ses3 = pd.merge(df, df_ses3)\n", + "df_ses3" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ttest_indResult(statistic=-2.0672394809544707, pvalue=0.05428628326311834)" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot\n", + "sns.barplot(x='group',y='meanAct', data=df, ci=95)\n", + "#sns.boxplot(x='group',y='meanAct', data=df)\n", + "scipy.stats.ttest_ind(df.meanAct[df['group']=='ketamine'], df['meanAct'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# test changes betwen sessions\n", + "df2ses = pd.merge(df, df_ses1)\n", + "df2ses['amg2_1'] = df2ses.meanAct - df2ses.meanAct_ses1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'df2ses' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbarplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'group'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'amg2_1'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdf2ses\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mci\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m68\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0;31m#sns.boxplot(x='group',y='meanAct', data=df)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m scipy.stats.ttest_ind(df2ses.amg2_1[df2ses['group']=='ketamine'], \n\u001b[1;32m 4\u001b[0m df2ses['amg2_1'][df2ses['group']=='midazolam'])\n", + "\u001b[0;31mNameError\u001b[0m: name 'df2ses' is not defined" + ] + } + ], + "source": [ + "sns.barplot(x='group',y='amg2_1', data=df2ses, ci=68)\n", + "#sns.boxplot(x='group',y='meanAct', data=df)\n", + "scipy.stats.ttest_ind(df2ses.amg2_1[df2ses['group']=='ketamine'], \n", + " df2ses['amg2_1'][df2ses['group']=='midazolam'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Use PyMC3 for bayesian based analysis " + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [], + "source": [ + "import pymc3 as pm\n", + "# first code new variable for group index (1=ketamine, 0= midazolam)\n", + "group = {'ketamine': 1,'midazolam': 0} \n", + "df['groupIdx'] =[group[item] for item in df.group] " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Full model\n", + "with pm.Model() as model_1:\n", + " # Data\n", + " group = pm.Data('group', df.groupIdx)\n", + " amg = pm.Data('amg', df.meanAct)\n", + " #ketamine = pm.Data('ketamine', df.meanAct[df['group']=='ketamine'].values)\n", + " #midazolam = pm.Data('midazolam', df.meanAct[df['group']=='midazolam'].values)\n", + " \n", + " # Priors\n", + " alpha = pm.Normal('alpha', mu=0, sd=50)\n", + " beta = pm.Normal('beta', mu=0, sd=50)\n", + " sigma = pm.Uniform('sigma', lower=0, upper=50)\n", + " \n", + " # Regression\n", + " mu = alpha + beta * group\n", + " diff_group = pm.Normal('diff_group', mu=mu, sd=sigma, observed=amg)\n", + " \n", + " # Prior sampling, trace definition and posterior sampling\n", + " prior = pm.sample_prior_predictive()\n", + " posterior_1 = pm.sample(draws=2000, tune=2000) # this is the trace sampling\n", + " posterior_pred_1 = pm.sample_posterior_predictive(posterior_1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#az.summary(posterior_1, credible_interval=.95).round(2) # adding round to make shorted floats\n", + "pm.summary(posterior_1)#, alpha=.05).round(2)# also possible" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (4 chains in 4 jobs)\n", + "NUTS: [sd, groupIdx, Intercept]\n", + "Sampling 4 chains, 0 divergences: 100%|██████████| 20000/20000 [00:04<00:00, 4844.57draws/s]\n" + ] + } + ], + "source": [ + "# play with glm module of pymc3\n", + "from pymc3.glm import GLM\n", + "\n", + "with pm.Model() as model_glm:\n", + " GLM.from_formula('meanAct ~ groupIdx', df)\n", + " trace = pm.sample(draws=2000, tune=3000)" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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meansdhpd_2.5%hpd_97.5%mcse_meanmcse_sdess_meaness_sdess_bulkess_tailr_hat
Intercept14.647.69-0.1030.080.130.093752.03719.03778.04351.01.0
groupIdx-31.6410.41-52.65-11.240.170.123857.03823.03860.04294.01.0
sd25.184.0418.1133.060.070.053477.03379.03573.03428.01.0
\n", + "
" + ], + "text/plain": [ + " mean sd hpd_2.5% hpd_97.5% mcse_mean mcse_sd ess_mean \\\n", + "Intercept 14.64 7.69 -0.10 30.08 0.13 0.09 3752.0 \n", + "groupIdx -31.64 10.41 -52.65 -11.24 0.17 0.12 3857.0 \n", + "sd 25.18 4.04 18.11 33.06 0.07 0.05 3477.0 \n", + "\n", + " ess_sd ess_bulk ess_tail r_hat \n", + "Intercept 3719.0 3778.0 4351.0 1.0 \n", + "groupIdx 3823.0 3860.0 4294.0 1.0 \n", + "sd 3379.0 3573.0 3428.0 1.0 " + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pm.summary(trace, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.distplot(trace.groupIdx)\n", + "sum(trace['groupIdx']>0) / len(trace['groupIdx'])" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# set variables\n", + "y = 'meanAct'\n", + "dfPlot = df\n", + "ci = np.quantile(trace.groupIdx, [.025,.975])\n", + "fig, (ax1, ax2) = plt.subplots(1,2, figsize=(3, 5),gridspec_kw={'width_ratios': [1, .2],\n", + " 'wspace':.1})\n", + "g1 = sns.stripplot(y= y, x='group', data=dfPlot, size = 8, ax=ax1)\n", + "sns.boxplot(y= y, x='group', data=dfPlot, ax=ax1,\n", + " boxprops=dict(alpha=.3))\n", + "g2 = sns.distplot(trace['groupIdx'], ax = ax2, vertical=True)\n", + "ax2.vlines(x=0.001,ymin=ci[0], ymax=ci[1], color='black', \n", + " linewidth = 2, linestyle = \"-\")\n", + "\n", + "#g3.set_ylim(-.7, .7)\n", + "#ax1.set_ylim(-.7,.7)\n", + "ax2.set_ylim(g1.get_ylim()) # use first graph's limits to get the relevant for this one\n", + "ax2.yaxis.tick_right()\n", + "ax2.set_xticks([])\n", + "ax2.set_ylabel(\"Difference between groups\", fontsize=14) \n", + "ax2.yaxis.set_label_position(\"right\")\n", + "ax1.set_ylabel(\"Amg reactivity to traumatic script\", fontsize=12)\n", + "ax1.set_xlabel(\"Group\", fontsize=14)\n", + "fig.savefig('amygdalaReactivity.png', dpi=300, bbox_inches='tight')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# run GLM but define priors first\n", + "# with pm.Model() as model_glm:\n", + " \n", + " \n", + "# GLM.from_formula('meanAct ~ groupIdx',data = df, \n", + "# priors = {'Intercept': pm.Normal.dist(mu=0, sd=50),\n", + "# 'Sigma': pm.Uniform('sigma', lower=0, upper=50)\n", + "# })\n", + "# trace = pm.sample(draws=2000, tune=2500)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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yprPTpsV0KlBfbPoC48tCp8mtaW+reIVWMtIpSk0jGv5OqyZpyI3lNKfpJ/UcWCUtNUGLnhttqyZH0XZYjlEM0XKcmox30o7jOFWMlXkuPHDRwY6ifgqKpdJ1u1Z5SKIDSw7OHnjg3Mh6N9/8fwEArVtnbLY//nG7rLrnPmbNuiTShoEDV0a23bXrMwCAJUu6JbaJy+msgaLf6zm0jjnJPm/l088XR00n/fDDmdR0egPzYjVr1gxAkGqPSQU4hcSLx/XXrVsHIDpNwnVZuYXKhTcxHQwY8sB1n3vuOQCBc9PRkLwhn7zyyisAAvUMBLMW6sRE9CG1wor0habTYao+NTmCJhhReH9Z6T5VqZMkRzNVslZYGdEXkp4rrmeFAFlKOi1Uh1hOcqrANZ1oeDaLbasOKUUdJxeOmk7acRynWKEXMe3JSQOZtCpVGgedlms9bfs68Hv66WsAAN26LYlsl4Mp2psffLADAGD8+P8FAOjcOWMavPvu1Vnv7hEjMrbounU5EMu06amnOgMAevZ8MbJPrSqnbVbTCCnLxh9e3rJxJw1o1aM8XEAqH9TYTnrWrFkAAmV86qmnAogXLuAJp8qlgqYtmt9rCA2nV8IXtUmTJpHfuA1VTRzt88JTcfPGePzxxwEEiTdGjx5d/hNwFMJiGdu3bwcQqGcgnmZQHz61s6bZpjXNIF8i6pCiSRKskCxLbap9WKckVcmHj5nb5r6thCpW6BRRda/HyE9rlkDt8ERtzVZYmzW9q+eutLQ0q7JZl9kVtVPdqbGdtOM4TnWBuaY1djmM5bRoZRhTT2Z1TtTsZhaau33x4qsj3//gBxlzHce1tEXz97BN+vbb34m0iV7ew4b9AQDQo8cvIm3SQWhaLLeKL54TzdmtzpQ6CLbMWuH/c/Zj5MiRiW2pLGpcJ00VSs9q2n8tG58a/XnRGjbM1DWlktZE7UmKSZNEUFGrQlH3ft5A3KY6QcyePRuAe4GnwZkHvvCSUiqqglbVmJZgQ7dnpcgkapvWe0TRe0QTkrA9/F1fIuH72bIV67bS6hDrva4vMsvbW6dd9TlIKgoC2C9i3b+2q06dOrGXtCtqp7pT4zppx3Gc6gYHVxxgUiyEB3M6qOGymm2LqL2Wgxtum+Y4Ve1aJc2qK37ddcsjf9eqxfZFj23duoxN+ic/eT9re9ZB7YIFVyQetxU/roNmzUrHuvA8R1aVLYoxijkrHDA8cOW2GIabb2pMJ021yZJvPOla1k0L1Ks9jMpZE96nJ5EPRv3qVcuHgA+RVYCAClq9wHnjPftsJpkAb8A+ffqUfVKOMliwnecz/PJR5WqpOlWR6nyTq6LWOGzeC0m+DOG/VfVaf2ucdRJWGs700oJl2+nVtq32d32R6uyFemdzexp5YXUS2lkkKWm1j7uidqorNaaTdhzHqa5woEF1RntneHBpZcfiIF49oC2HOwoWHUSpQytRBR8MupKPxXKCLC0txR13nA4AuP/+dZF1rORCmh/eahPPBc2SHLDzfOqAkNujcFKHYDX9hJ0ed+/eDSD/8dGk2nbSLIChSllH0KpWVVGrQqHNkMvxIloqg5SUlJi2Oc30xG1yeR6D3qjqoMC/6UX+zDOZQP9u3brZJ+oogCqJ55UPWvgFZ4VoqI3XeiFpbLBOi1nK3Mq2peEwls+EKkPLAzupUIiqdCvERtW6zi5pG7Rt6nGuXuB67vX+JvpCTCt9mVTWUTsmzVLmitqpblTbTtpxHKemQBOXVf84vIwOLNWr20pKo06LaXXDtSKXChqg7OxepaWZz5YtM/sbNOj47LbSVDiPTWcUrFBEDsZ0JkKrWKnyVqXNgT73p74CQKDS08I0K4tq10kzd3a7du0AxBU0LwrttkRH2FyPN66GKyTlQg5/r44FYSVtFW5Xda4Kx7oBtZyb7nvx4kzpuE2bNgE4+uKqec2tJA5hrGukv+s0GLEy1hF90RHLm1v3q7MpSfb1pO3rdsL/T/OjsLy7Ne2hKu60xBJ6Hfg7nzlV4noOdH9EvbpJrVq1YvcA0ZezK2qnulDtOmnHcZyaAouEcOBBxcaBJ+2fQDzOmYMdHfTooIoezDQDaY5vDnYoAri+DlipOrmcxk/HbdFRx78DBw5k1xk//uxImwm3zePmvlVMpYUwWnW5tf46j5UJkNS7ntthHXogsHvTTJlvqk0n/cQTTwAAWrduDSAe/8yLwxuRJ52xs6qc1D7GG1m3RywnjCSsGFzNXqaxrqri+bt6hasS0jzjtNcPGTIk5zZXRxgTb3kfhxWk5WmsdlGrUpMqakvxct/qVJKk+sJYNmZdrjz3oR6DnidrJsfKP85j4/2o9nHdnypu3S5fhFYMe1pIkVJaWmqqb8sO/uSTTwIArr322sRtOk5VU206acdxnJoGBw8cBHIAQkUZtoVy8MJSuCeeeCKAuFe2OrtqimMKEg6OOKChrZX75u+6HLc/adL5AIBRo/4PgGBwds89XwIAjB37ZuRYa9WqZQ6wuE0qaM2HzQEef+e+eEyaQYyf6gRpxWHzPLMojzqShgfpSSl480nRd9K0HbVq1QpAUO9Z45i1ri//3rZtG4BgikKnTaywBY3JtD5JaWlpzPmA+9RMYlS+Oq3ENlkp7TgFpnGpTZs2jbSF+5kxYwYAYPDgwahJLFq0KPI3Hzwr/hYo244JxGcpuLw69FiJ/om+FPip3tuWbVxt3nqfaQy+fp9UBYuo7dny9k5T2GyjzvSoslYPecsGbSlprTyXlrnsk08+SbVfq5e85iC45ppr4DjFRNF30o7jODUNDqC1KA8HIlSMFBlhKFSs+tE6gKMwscrvUkzoQNQyBemgbOLEr0SWZ8ndW289BQDwox8Fgz3uW802O3fujLSBaOgjFa+GC6p447ESLleW4294/zSXsmjPJZdckl02KcQznxRtJ/3YY48BANq2bQsgXp1KsykpvCic2klSV4B90dRFn6pBqxOFR/3qYEE0BIKffLh0morr85M3Jh8m3iQ6taPHwu1OnToVADBixAhUZ5YtWwYgUE4aX66OLWG7sPVySMs4xutMRa0vLrV/qx1XazGrqtRKUFYFKCtWWa91WfWkLeWs58LyHFcFrM+gzvxYmcGs2Sv1F9Fzp0pfQ4/279+f/T/XtWpo6zRm2EHLcYqJou2kHcdxaiq0J1NJWylVOTAH4oMXRcuiaipaTWGrZjQNH9SiLTqYsoSLFZpXu3btWLyziiEdWHJ5K0kVB2rqcU3HYlXIOtBTh1Cuz88LL7wQQKDUgcAngNfhxRczta/ppFzZYX1F10lPmTIFAHDaaacBCE62TtHwBtH82DoFRJWp9jW9oVWx8OJrsLtVPDz8m36qrVQfIr1RqZw5uuf3PBZ96PSG5rE0btwYQFBLu7qjZfw0OQO/T3LsoBK2pqiSUhiG/1a7rIa5EM2AZ5UF1P1Y8dVpKR5JWb+r7TctH73VtjRPeJ5jPUf6krfaatm+VQVb65eUlMSynemxWjMpvFfo79C9e/fEfThOoSm6TtpxHKemMn/+fABBKKkObLRsLQeigB2XrGqQ21TbqXqQqwAhOmjTNulgS02IOsgKh87poFNNJBoLrt7uKpI0dbIOijlo5vccjKlntg40KQ65v7CS5m/qEMyBOU21/fr1Q2VQdJ20Tv/oqF5jhvVG0ekKLq92YV4MtedaNuu0xO+1atXKKjnNZqZTWVb+b7ZVy6xpW9W2rTemKqRmzZoBqL4qYenSpQDitlC1O+rLiM4oQDzdnyoqq1IUr7OeY8LleW1Useu10JeUFb+tHtaWv0FZ8ddpVa6s2GzdltrJrQxllmLn9VBbtWbY03ZbCl5t3dxO/fr1Y222CiVY0Rx85lasWAEAuPzyy+E4VUnRddKO4zg1lc9//vMAggG2Oj/qgCc8gNGBhg441ZxmhaypTdoysVgmIEu4WM6P4cG1fmcl/dHCNVZyGqL1pDULGwf0ltkyLYUzB9/h47KcQmmzriyKppOeN28egEBJW3Wf1YFAPUZ5cTgFQXgz8OTT61vtmKo2LJui/l2nTp2YsrMKh1s3u84WcDvHH398pO1qkyWaxICKhsdKRV3dMpLxmutxW4UE+OILvwD4fytshehMiU4xEq34pNmz1BubqNOPvoytetS6X6smdHh/qkBJmm1YVboqXrUdW23i8jrjo+fW8jrXhBL6YtXp1+OOOy4WD63OT1acuS4XnoVxnKqkaDppx3Gcmsq0adMAAO3btwcQz7+tznZJOaqtEDkr7aoqbGtQZSXmsdBBmhUWqCabkpIS04xpiSFroGl5kKuJxCqfahWfUVNL0nXQwaceE8OFZ82aBQAYOHBg4jHkSpV20gzoB4A2bdoACIzyqkyITvmo0uF0B9enMifq1EB0ysaqgmRd7KRatnrDqIJIUuNA3NZKZaiKhH+zrXSesBw9OGVDRV3sMAuUZYvWWRW1TXMGAQhSHqqPgpWDW5WW2mOtiluW6rNszrqcviT0hcqXuOU7EZ5d4bPET84u6X2kql+LO9BOq9Xb9MWq6SPTPOQ1JMiK27aus0ZuhF+kev6IFTNOuK9w6JPjVCWupB3HcfIMTVaW2UQTE3GglBQTrcpVVV9aClwKmbRyp5Z5w3Ky1HboMe7fvz8WAqn2ayt0zhpU6eA67ZhU/SYV4wl/n2S6VJHEbalPAP0PKkqVdtItWrTI/p8xvZr8nVBB6AnSqkOamJ43uRZM1+kWy2PViiUlSb9btjxrHS5vZRDTqlhqj9dzYFXXoiJnrm/6AfTt2zfx2KoayxatD7rOqug9AgTXXwvYJ4WJALazDLHsqHqfWLZPdWCxnFGsam2aW1zLEYaP33oxWlOGRAsqMN0jixAwCkFnbvQc6kvcSlih5zCtYlnSM2l5hOs5sBS2zlgsWbIEANC1a9fYvhynELiSdhzHyTO0U6pdWM1pVlhheFnWNtbUx1Yoptpr1atb1aiVCEoFjZoddBCmMeCNGjWKDUJ1cMp1rMpemjfcGiyzjTpI5rFx+5qJTD/1eiRtwypEo87LR0qVdNJz5swBAJx++unZ73ij0X6mTgmWjU/tvFZ6OS27ZmVVUjWq6pV/h0vIcX29wLpvK46Zx8KLSju6KmQem94MOi2lU0ea/YroC6JYeOaZZyJ/p3nNa6KCJK9ltd+rg47aKtMyfFnhKfrCI3o/sT3NmzcHEPgJaHU3a3vldfYJY0UXEH6vMxjsaFq2bAkgSIO4ceNGAIHS1hkQdWRSu3qScw5gO/VYcd8HDhwwveotnwJr5kTt845TVbiSdhzHyRP08KUgsWKY1Z6bNAjTZWki1EGQFeesea41JphCSZUx17Mc/FR8cCCsWcI+/vjj7DGoY7BVKIbHxgGiJp3RfejgjIPeJE/z8PY4GKMJh39rHDsQD+O04s35O1Ndjxw5EkdClXTStInyBABxW5wqX42xVC9dzUSmtmmmdbPsZbxxqQ70JlDFzt/DN5WlrixPXZ2S4TlgW9kmfmpgPW80/q03qt5MqiL4kD/++OMgvXv3RlXD9mlmNUvx8ZryweJ5Cvs16NScpiMkliOK5XVtvRysXPC85/nSZuIDK26bpLVDPaDD/7dertaUo943OmPD3+lTQgeZrVu3AgDWr18PILge+iyrP4mVVlLfBZYfSThG3JphSMvwprNf+p5xnKrClbTjOE6eoOlKBz5WetqyvJU1tJDq0hqMW8KCAw+aFikK1CSkA1groZMmUVJ1Gral07xjpZwlaubUzGFssypgLS2sMxfWp9arVtNZ2MSmglLT3qoZk+f5SKmSTlodHYB4ti31vlUnBP6utYP1b+th0ApVtKfxkxeLy6mqSIrRtEq8WY4FXC4pfV54OR3l83fNU67btWJ2LeVe1dCTVms4W6X5LH+CpIxaGnOuWa2sRAzWvvQlYtnJuX3eP6zuRrtuWfWgw+3Q+1VfRklxweooZDnf6LHzxcaXC8OH+NxqAg7+fcoppwAIlPXatWsBAJs3b47sTzPnWWUDrSQdJCkUyZp5s+zv2pFZdb4Zs3/NNdfAcQqJK2nHcZw8oal71aNaB/8aChg2g2iBHSsRjw5ANdkRt8nBF2HCH3WqK6s+dHh7aqb65z//GTt2TducVlQQJAEAACAASURBVEaVcMDJwakO5Lk8j5FiTZNb6TGoFzlNgBrOmeTdrUJRzUvcR9iseyQUtJOeOXMmAKBdu3YAkr2LdXpBVaXWl+bvWmuYI2KrKhHheho/qxdHR/3Wwwak5wvWB1C3rbY/zRTFaS7LKUKPTadhVDWk2UPzzdNPPw0g/tDrtbc8r9WmqUovaV2141txy5Z/gSpqRWdVTj75ZACBHdfy9Le8jHWmR30ytApX+P9adk+nCNVZhi9rhvpw27zv6InOFxp/12f0rLPOAhBM+a5ZsyayH50pUUWtLzsrVCh8bdXLXhXxpEkZu/nIkSdGzqOVTlJnIRyn0LiSdhzHqWRYxOakk04CEHTyOlDWeFwtdxsedHGwrgM49VS2HFQ58OQgiusz/auKByusUAfJ+rdloz148KBp504rKKPiigM9OtXyfPHYqG4pvnjurMQ4qqx53tV5FYjXuNZkSmqy4jYffvhhAMDw4cNRHgraSfPgylIh6nWpNWlV/ek2rZJj6m1L9EbUWFz9W1Wules5aR9q/9KLqg+D2pr1gWZbVA1oTLf+zu95o4fPCWc7Bg0aZB5PZaPnUBW0Kml90Cz/hfADb+WR1hJ2GiWgL0D1oubfs2dnXnTDhzeNfM/7jwrasq8rfPm8//77AIJY5F/+8peR5S677LLIMYedVKh0+ak5vDndSXVO5cx98xg1hzeXp0KmMxD3o+kS2VFRia9evRpAkLlMOyiiz4k65OgzV7t27Vh+b8J7ntdHY7X1vUDUF8BxCo0racdxnEpGPXqp6PiptlT1clan0PA2aY7gtiwlrbZldZrkoMtK9GSZ6XRwpKY/a0BTUlISG9zqgE6dXzU2XM+XxmRzoBcurhNeTwd8OhBk+/T8h2c0iDpgWjMYPLYj9fIuaCettsbwyNmqqGPlA9aLRcWi3+eaeN2aZkmyOYe3H0ZvVitnt9q7rCTy4Tq5Scegylk/VUnrFFBSRaW0TFuVycKFCwEEys56GaSl/tPpPJ2NCf/fypuuismaydFpS953Q4ceF/ldw2X0AbW8uLn/d999FwCwYMEClAWvJe+FsO2Utubt27cDCPIT0KbMNjFWWx1+uL7mCqDS5r65HGcL+KnXlcr97LPPBgCsW7cu8qlTjpqbXjOUJTlb6ayVVev6kUcy+RCGDGkc+T7tGXOcQuNK2nEcp5Jg3WgOVNTMpgNnFQPqLEoTARD3WFZvbR20qmOd2mGtkqWWUMo1Fa2aBMNCSj3G0+zdVsgcocJVwaHiTkN31VFQzy0HsElKWgfsVilivbbc1tSpUwEAI0aMQC4UtJNWRRhWE2nZj9T2zBOl9ktiOQgoVvYijbVNK21WWlpq5he3HCusSkfWqN6q4MUblApHXwT6QtCHLqwSNGQkn+gUl+UPwPNkPQxW+Eb4gdZ4YvX6tapTWT4RWo2K5956SRDdvyp5qtI0Bd2pUycAcU/2JN8IHjszgrGtmjGMSteadVJFzXOitbqpsBk3zTh8to0vPEZ58Bjo/U2083nwwU0AgDFjTop8H37BW34vOtsyenTzyLFaDkqqxIu9cpxT83Al7TiOU0nQpGANdjlQ4cCJgzIVKWpHBoJBlCo4y6GOphgNH1MhRNu0ps7VwbxVTEaPjW3mLAC3e8IJJ8QSWem2rfS6VulingNV7Va5XhVSmm+cy2vp1/Dgl+fLEkPWdeF5ocNlrhSkk2Y4Qvv27QGUnXFML5IGjGsZsFxjfK2pGivemSdWp4SsfMgHDx40Pcz1WDQW27KLW4pa26xeuLp9DeRXBV6WZ3o+mDRpEgCgVatWAOzi8upXYM1U8AFV7/Xwy0mvTZqCspxfqAqpBnfu3Akg8Lq++OKLI23TakrWjA+h/fj8888HAPzpT38CAHTs2DFyrLoe2xN+qVseznyWmBGM9w9t05zq03s9KVd2+Hce45YtWyLL8Vywk9FICiru4cNfBwCMGpVpxwMPrI/sN23q8/Dhw6YfiN5bVtIMq0KYVVrScfKNK2nHcZxKggMRrZCkA2cdxFGd6QCVYW1AoEw52LKcW9VESPOGhijqIIziKc3hlaip0Mqaxu8bNmwYa6Nuy0rfTNQUpo6THKSqmUJt/uoZr+WC1bs7PDjjuhzsWl7eRNV8edMwF6ST1hJoPPCkmFGtPqMGfvXy5rbTwgIsJc3vNRRAp584yr///nMi2w+jilDtYtaoPs1ZwqpepHHT+lBYZfHKymvONj/22GMAgH79+sWOs6JYdlS146Y5qqgqVptpUnk5vTaWUtJZBnpE8yFmtbRly5ZF2vT73/8eAHDllVcCCB5o2oP12hDOgtDTmctdeumlkWPkC5fPEDsFLbaQdH64Tz6H3BZjsHn+aaPmsfIYLGWtiprPrmYsY+eQlPc+/LtlG9flk0omWlO/eo9pB6OfOlOm7yHHKRSupB3HcSrI3LlzAQCnnnoqgLizY5qphoMBDoiSErZQVdOmqSFqFCyqlNUmqmYQa3s64CFWuVQVRDoYb9iwoZln3DIBWvtUj2kVHhxgqv1YU9GqNz0HceoYykE0EJh1NFzTCl9VPwOej1yFUEE6aV4sy+4MxEMV9IZRW5B1QiwFbcVLa+YpK6Xb9OlfBxB4st55598BAOvXZ1TDhAkb8dOfNousq23nvseM+QsAYNGiLpFjSbObK/ow6DSKPoxUODrFE1YHXKaiSeHLQr2xdQrLiom3Hmw+iDzPSVNqqpitqlbqnU0FzYebWbKef/75Mo9Rr/22bdsibeVLgL9v2rQpsn1eG7602V5NU6hTjGXNPujLhC8mraVOJasKWHPBa1pKvV7q/a2JPKy8AHffvTqyHYX3x/jxH8SOz5p10vOkMye5KudZszKOXsOGJTbNcSodV9KO4zgVRG3RRAfgqm6TqiwBwYAorOA46OS+6EmuHs7q5KqxvjqYVfu5hiOqWc7KaKaDafWMbtiwYcwLW0133Ldlm1bbNY9JB35qUlFvb7ZNFbwWMeL+OLgG4t7yakJJy9hGcrVNF6ST1ovOGy886lV7k0578OTxYvAk60XONWOWPiQa8G/l+h479k3ZUnBBrNhs3ea0aRcCiGdWSsNSFlaNaz0XeiPyenD6BgjUTj7jpS0bvOVXoA8o262Vy3QKK3xeVTFrTC8/yYknZqok8TzQbrtixYqcjpH2cU0Uwf1SMWv9c43LfuONNyLb/cY3vgEgntJRq3qFsbKt6TPDc0Dly1kELfqgSlrvS+1MeC71RWo9q1aN7ZKS5CyC/EzyyNd9aAQAz78yc2bGa/+GG6LnddWq/0pc3nHyhStpx3GcCqIlcXVaXQcylslAVWl44MHBtGbDstIKq+Ooightk5XkSB0DSZLjadL2whnHVJWrGLLs3KpKrXTRahZVOzy3pwNGtUmrc2XYRJsWxmeZVPU8JeUDT6JwiZodx3EcxykXBVHSOl2p34fREaWGjdBWoNPdaYUy0hzKLC9MjqAYghWsF2334cOH8Z//+f8AAA89dF6kzTqiZdvVRhHeVhgrmQfRkbJO+6nzDPebNF1pZfjJBzpdadmjdHqbU5TqTGWl4Az/X5PjUJ2wDZya5fFv2LABQJAZ6sILM6YKjoK53Zdffjmy71deeQVAEEJlFebQJCTqFMckJjo9q17Aag4KH4OlXnhemZCF54L3G71+9Z6gkuP55rFxPwzh4rmk7U2VmsbXLlnSDQDwwQcZh7Drr/8FAGDUqMx26GynSjD8OWECU4e2BABMnrwNYYYOzRwTzyMdwcjAgY0in/y9X7/8OVI6Tln4dLfjOE4FsQo6qP2d9npNJWnlGA+LDs0fn1TtLfy3+nhYdQo4AGTbrHSgGh1ieczngpVNUae9dRDKT22bOr3xU6evieaR5++W4EmKSNJjSSsaotPjudaWL0gnTZXAkXCSU5JeeA2j0UwwadVU0tDl1bHHOrG6fhK33vr2Z23MrDtz5jcibddZgPK2Vb9XZztN6mE9VLwBw3ac8jxoR4o+SOrMpTYwDWdSu5I6GCXZ3LTajaWgeQ43b94MILhG9KTl70yhye1873vfAwAsX748cqy/+93vyjwX3/rWtwAE6lRLrvL+5zlgUhSmC/3qV78a2V5S/WGdudE0nlTSdEajgraSw6jTpc4OcH31eLbCobg+U6L+4x//AAD061c/cTm1jW7YkLmPH3xwU3aGa8KEjYnrTp2acdizSoU++uieyPJW6KbjFApX0o7jOJWEKj8VG1q9TyMtVBGGB+ZpufxJWp5xS5hw+bTKajpoK0/NAXUIU3WvKU/VlGXlz1DTSRpWulGrhnl4eR0kWkJR07XqoDbXthakk9ZGqo02CcsmrXF2Slo6UP3eKkJAkhJ+RAmmNAKlEVWuVDQ8D1YuXG1j2vc6ncJzxGPQSjEaF6mKKNzmXGckjgRV8Dq1xPZYSU+I5YVKwueXLyKqRf5GRcx9MjSK55IKm8tTfarC5XaojH/729+mnYbIchdddBGAwH5LFaopdHkcHTp0iLSLXqjhUDJ+xxks7SiooBkSqYl9NHRSS6JSaXM57pvLcftalIRwfaYPXb8+U1BDr4EmGqJKDjoJfPZZgtLSZAVsZfwiVtKjshIwOU4hcCXtOI5TQaxQIR3wUHRoHn0daKpCBOz0nPo3B5JaREIHvYQDP8bHc3k1V1iOv6qsLbNEuL1WDgRF7eGaXZBoIhedJVAssWcN0sKiJc0EmmveeH4/efJkAMCoUaMS21qQTlqnDJJGpXpBeTNTSaj6S0v3SdJUaVAEPmPj08Ie1naCixf8XqtWcuGMPn0yZQwffvhrke/pBZtrvFxa4Q2tQcsXAB9aLVKidWXD3+WzfKUm8NAXmGYRImkpPUmSlzvVH9dp3rw5gOA4d+zYASCwp+pMjiY70fhK3jfqoJIrTBxy0kknRbarZTc1i5N6aoeTc7DN6n3NZfVe1yQweh9xe3xRWt75Ot1KpawdE9N6Dhv2+ch6c+dm9vOjH2WukaYBjXdW/Iy/A6zoDgur3vDYsWPLXM9x8oUracdxnAqiKiqpQEZ4Oa31rgPOJK9iDlqt1KOWOaIs81Z438wvz0E9B7JalIIDRatCIdEBUmlpablVtzp40jTDY6TQ0SIhqqRVUWtCGKtISJJq1rZayllnUzT9qpVpUSlIJ82bRXPBhket/D8PRJW02oZ1usM6QSRXz2grBpO2LqYBPXiQyyG7nA7Sua0HH8zYDzmdxItGW12a40W8LVFFaTkq8Nzx/KsNUdOIhv+fT2/WMWPGAAgqB+nNasWPkzSbvqafBeK2Y+6TLyZ6b7PSEF8COjVltZGeyZwi7NIlUzxl6dKlZR7LVVddBQBo06ZN4vYIX5RcTmc8tJgFEChYPRa99/WYWGiDtmGeO74wNQRIOxh1AtLf9X6fPn1H5Pu77mof+VtnzyzHpMwy+KwNyYU2iPVMKTfe2CDxe8cpFK6kHcdxKog6Zap6JTooKCsZTXh5IG6e0sG5Jv3RbWi9bzV76ICPYYgqlGiS4YBUzZgaUhl2ulQxZokCJg/SMEAOXrkdKmKrapmV518LdFjXRVVwElYVP6uWgArMNBNMQTppjuS1iEC4cVr4XT2iebGojjTjEqdg+GndyErcuB91KFB1EHcW4Ge8mAOX5fFrfK91o+oNp8pZM29p5Rc+8FoYQRV1UthCWvhGZaLhKLpvy+/AOj863Rc+BnppE2a10vtGY371emtIiF5brZ7zzW9+E0A8I9mVV14JIFDG3A/VL68Jlb++KK37OmwTp1c328hPqm3eB1rNiPcXva15v3J9q/Ssvpz1+vB+Z/EK7u+OO04HEJSo5DHxb6LqV7P/hb27Sa6zVNb7oRB5AxynLMrspC+55JJK2cmWLVsABA97UnydTm2pJ6KVgJ1oZ5trchM+pKtWMclBdFo7LTZx375MGsL33nsktC9+ZpYZObJBpC1atcpK7mDt0/KIVHsY0ZeoVj9KGmDwBT5p0iTkC47U9dpZx0HSzABJ94hm9+HxWRXErHPPT96fOpXL7altMTwNDQB/+9vfAMSVkw5Q1Au1PI5POpixpqWJblvVoGaBSjPLWN6vmzdHp73/8z8z52Dduo8T/1a4WTY3/AwGu0w216T9HubYY1sA6Ja6HGDbolVd6f2h50rff2GzisbZqvlCB+Eatsd70XpeaN/lQJP3LJ0qVRycffbZAOIe62p64X63bduWtXNbVQiplDmItoqAqIpnuJ8euzWQt0w3Klz4fPKchI+P6LW24qJ1VkD3bVEQJd2iRQsAwcVOQjswPWlpHY125mnx0bnGIuv3Zdlqg1F58roffJDxim3fPpoT2XL7V0VunROiLwr9VKeKpIQJ+ls+0RSIVqebpoas8xXumDXLmm5Ll7Nq51p1bq2auuz8aetWVUnUXpsWzWCR9Ls1CNKXtm7DSiNZXvuuPtunnJI5Vxs2ZDoP7YytzjnYXpk/J5J75xwMsEtKXEk7VU+ZnfTKlSsrdWe//vWvAQSjkvAokaMxOlNxGb68OFLi6Izfc6RD7z6rqLhVZJ0vlquvXhz521JlgRrJfP71rxmledZZw2IveHL//ecAAP7rv1YBAB5//HIAwVQmX+Q6nc2pfR4rl+PImOeEWCFMmnaR201K6MJ9r16dmWrs0aMH8sXEiRMBAC1btoy0Q6frLU9QDTtiaBDPF8OagKCDoKMYzwHPabt27SJ/q32O50XD3OhkpZmjODXMY2A9ao7gzzzzTACBIuC15LFxep5mH+1gtdNOigulXY/b5DZ4H/zzn/+MtFnvXy36YdkBLRunDpa4Hs/VAw+sx5GgA5G//W0aAKB9+6HZmbDDh6MDi8DB0zJbJZ/PXLFqnWtCFg3Rs0LE9D0FxGc0tM0armcNbq0ZPb33NQkN72GaZPi3Oj1ax3bo0CHTvMDnYs2aNQCC54GDWz4PNEvpddJEOpbHNH/XzGKqvImek6RltI/hMVqFgaxSoRYFdRxjI/liCisdvhA0axZfdnzh8EWsCdd54Pxdbcrq0axtSLN7kuBFFh/O63QgP9W+zgGIZiBjW3kMfJnye7W360vSynnNc8tzxQciKVOX7juf3HTTTQCAhQsXAgjOh84Q6AOttk8eD+EDHX4INKyE15+dNl8KmniALyjuk+dQixLwe96ntAfz2vPeZ1UtPrjcH887BxbcrqVS9SXEa85BAxDYlPnbGWecASCY2eI50al47oNt5nlmm6zZCL2fGO8c1B3OHKP6caRnt7N+t19yo0dnrvNDD22OtDGtc+a++Pdjj2XO0c03pzTRcfKEe3c7juNUEFWxOrOhs1xWGduy/EVydXZTk6AuxwGeVfhITS6a/YwKmp8ciFL1su3cLrfTtGnTWOgiB4Jr164FEE8lS5WuZVN1Fk1TDKv5SK+HFRZonavwoNhSwJoelwNv9SzPNbEOKWgnzVE+HRSSUq3xQLV+rtrP1KantXB5MVUNaHA8byzWsuV+unRZ/NnfdBKIntik66TOIfowqDOCTrloAgNVNPybN7/OFujFtzKS6TR4OEsVleDIkSPjB5gnqOR0KksfPL03VM1q9SY+JECgrvly5DXhtDePWyuJ8V7VtvF+0qxcvMa6PK8Zt695s/XlbSlla8aH/h582QHBtCTvE74sNB++JmzgeVfnGs1zwE99Vqk+4+Ua05Rz1Fs7Dd7ep5ySOY7bbmsda/PIkdHc62q+Ugc9tpnnasCAAbk1xnHyhCtpx3GcCqIDIHXu1IElBzyqYssqcGPF8qpy5cBSt6mhdppJTJ0liRYK4mCY0Rnr1q2LrK/5s8Pt1/PAgSS3RfFFfx2apbhvbltNgxycqT+EOhZrjm/LSVL9ipI8sPV6qHe7VjRT0ZRrqeKCdtK9e/cGALz44osAojZpK6QlLQG95hG2qlrpdrRylCqdY45hMvSok1IwEo86pJSWlqJOHXrkRutIDxv2h8gx8ri7dFkEAJg37zIA8dkALqezAZaNVkMD9FxqqIROzwDApk2bUGiGDRsGILBN84HUHNw6m8JrxgdZ7el8WQFx1cjrT/8ArRilaQg546IPv3pKa9UqzYutDmZ8wGkn5otToxX05cF2cBaCISth+/Ibb7yBMHzx6YwEz7fGrfN+++Mf/xjZzte//nUA8RdmWr57yx5sK2j9Itk+T2/we+/9n+yStElbz4rOTGiHYhVmcJxC40racRyngmhiGLWNEitWnYNFnXZPUtRWPgUO8Dg4VUGiA1Q1d6my4+BdTYxqrmP6WM2epuVTV69enV2XAzwqabbBcpxUT3FV95qwiagZVaMl1Hk3l5h/vSaWh77uQ5e3ijkpVdJJf+c73wEA/PKXv8x+pzWPecA8ENqzqRS0Rq56e+vUjdqguF1eVK12xDCpnj1fjKwXKKCorTrT3mictN6QTzzxPQBA585PRs5H9+7PAwB++tNzI8vrzcC2qt2N9lQ++Dw3Ojug01BUnvQ4BgJVWxUw3GvJkiUAguNXr3nae3l8PB8MKaKa5XJAcG60XJxm8uK51Axl+nKwyvepEraqu/E+poMMP/XaW7H0bCenGvmye/3112HBKcWtW7cCCCo7PfzwwwCC2QK+yPiy5998XqnArVzgtWpFnXHiLzx89rs60JStnC0PbVJSUoJbbjkZQDyszIq9185Qo0Qcp6pxJe04jlNBNE2xxjRbCXesJE5J3t2qiC0nOB3IadieKmbLoTXNfMbtvvrqq8ZZyUDz0y9+8Qtzmf/4j/+I7FtNMlp2VStvaWEmNZeq2YkDfLXXpyVOCqPnX/N9q2MvP9Xbe/jw4cZZyVClnXSnTp2y/58/fz6AYNqHJ4CKo3///jltc8aMGQDiyc158VRd8qLzxDGsQG2GP//5dwEEimXQoFcABJ6lY8e2yk7VqH1x2rQLAQSB+tOnZ2x6VHrf//6zAAL7p8Y9UynSg3fgwIE5nQsqJD1mbrdv3745bafQdO3aNaflli9fDiCYZeEDqUligOAc6nQiP2nX5jnWqlb6kGt4iiZgsbJvqa1apzn1hWqFkGhSn7IKABDOGowYMSLyvb4knnwyM9NDdc+CCqefnsmxzZSmWgqR52DMmIwCnzr1w8gxBC+6qKImuYakjB3bKvL3uHHc70mpiSbU1q+dIa/nbbfdllNbHCffuJJ2HMepIAyp46BJHVhVqVmhpprlLckWapnydB3L4VS9sDX8T+OkrQxa/J1iK2y+zJWOHTsCiA+e1FFYVTzt3WqGIpqVkMupt7iVO90yMyW1MW1gqNvgMaj93KJoOuk+ffpUynYGDx6c03IvvPACgLhLvtomx43LpG9U1UDWr898/8AD6zFpUvPINvngssAILxZDGK69dhkAYPz4/wUA+J//yXinVlYqzrRplOrO976XsfFzxkAf2PCDq1WuLGca2mGpqPmC05SlmjZUc23rFJcWAlBnHyvlI+HyfJG2bt0aANCqVUZV0oZK1QsATzzxBIDAG5v3XRqadpazCkydevLJGbsvZ4bYVp4bnus774x6xOsLl+dkwoSNObXr1ltPARCkE9UpyMOHD8c6IGLFmWuOAffqdoqNoumkHcdxqiscEFNNarrheGKXqIe1VRI3rNJUjauijjvwJReJsfKUaxirhguqOlWnx27dMgmhnnnmGQBBFcV33nkHQKZsK4+T69BBkzMKHBiq7dlSzJqzm+jg27L5p8UuJ9miVQlbWctUcWsYsKYztjhqO+nvfjdjY6ai1uxgnA6hoqaauPXWtwAA996bKdM2bFiQ7UhtvlrAQD2G77vvywAKU8yiJjJ79mwAcbWr03JA3EdBX0RaxISezvqC0pKUOrNiKTSGqfzmN78BAFx00UWR/RN90K3ydzptyt953wJAr169AAT3oapLC85qUYlzJqh79+4AAkehMWPGRNZjWVOeM7aFPhGcNVAnKiupA23Pat+nBzfXGzcumJ7VbWmMveWAxPNJj3fHKRaO2k7acRynsqGtlIN9DXu0VK8qtqSSsRxYaDyyqkIO2DR2mANHq3StDlQ1bbE609LpkeYNDlyvvfbaSHs4MKZDJxAfuHEZDqJ0X1YIpLaRqMlLU+HqbISVbS0pp7cOxDXJkg4qVVHzU6sYWhz1nTRjhHli6ZkdzoYGBJ7XU6ZkQgVosww7WfD/vNE4naEB9FQ2zBLFm9opH3w4XnvtNQCZ6TQg2dNZbY1chi8Yda7hQ23VfdYXoeZZ5ydjk5977rnIdjTqQF8a1u/6glA7b3g6kBW/2HFoSI3FQw89BCCwz98sJaBGjRqVuN7o0aMTv6fPAKMfNJf9nXeeEVn+Jz95H4Adi64vzvAzyGW1ih6fVz6Td955Z2JbHafYOOo7acdxnMqC6kiLCOlgSu3GasPW8EsgGHAQeiqrktUBnsZVW4ly1OasDn5pph6Nt+b+eayNGzc2i7QQa+aBqLLW9azUs0G65+SMbqqKiYZchtchlpOolX2OgiDXENijvpNWb/Bp0zIF5Kl+ecJpo6RyUpvjwYMHY44BmiWNypmx1hqv6pQNc3vrw0D48Gg+diD+ciTchiYgsJIYqCMKHzjabZnNi74OFnSc0Qxl+jKx0iLqi0HbF94Wz0uao8qvfvUrAECHDh0ABPcvcxgcaQSGFWVAnwJ9qdOLW68vsV6C+/fvz85g8JnzZ8yp7hz1nbTjOE5lccMNNwAIBjxWnWhNAMOBJZejySysnvl/TcTCdblNDvj0ezV3WNnOtGRuWnlPNRFx4Mr2cv3du3fHYrO1jKo1SNbBqaZ9VaddS2lrqCTh/mnWJFpzG4jPAvD4tJa4opW7csU7aSEtd/XixZk60zoFtGPHjpjTAx9Yp3Kg9/u8efMAxB80TRARRl+CWhBBp7A037lOj+mLiNXDXnrppZyOhfZZdYDRv610krk4uOjL1spUR6XMpBTcB7PvcX2GF7Fmda6Z7yzSajVzVovXTl/g6pCzoGcDNgAAFPBJREFUffv2nPMkOE51wTtpx3GcSoaKTB0Q1TNbneg4eEyK/1UzD5fVEqNW7WQrBliVsdpnLfMSf9fwQJoGeQz8vlGjRjE7OZfhIJQDMn5v2cvZdsux0jo2nW1QOzFNQmpOCg9+6QNgiQSrqhXPF81IueKddDmhl6iGCOzfvz97A3jWovyiDiz6PdUt7b5APIaa10hfcDpFSHR6TR1gmI2LWdCYV1yhBzqdfqyXi04xWp9EQ0mA4EVnpR+cMmUKgMD/gueNEQ5a8pDnUx2Y8oXOak2cOBFAPPJCOy3HqUl4J+04jlPJMHkNBzqq5HQwqGGbGnsLxAelRAWDqnVV2OpsSKyUqjqA1HbQxspj4qd6nYftujpjwBkFHr+aNjio1thrVdqW2UpnFdScZMU0sz3hQbuawNQUZsW881jLW9jIO+lyonY4psCryjrMRxuaMOLSSy8FELcTh6cK1UFFXw78VK9qTQBB1MOY65966qkAgCuuuAJA3EbNlzaXtwrIW59WiImuDwRTrpadli8eZtP79a9/DQA444xM3DJftnzZ88Waa5Wyyuamm25K/J7PoBWn7TjVGe+kHcdxKplBgwYBCAZpVJVqo+bAkmpUaw2HVSvX4QDPygymNmJV0pb3tqpUtpXLa3lfdXJkCmW1J4dDUrkPblO9vNU7W81MbBM/VWnrYFq9utMGxVxe7crh2Qe2XQexVN16Pvl5pGYi76SdagcV0/Tp0wHEQ0z4MGzbti27Dqfa+JDypanpG/m7eohr2kB9qWi9adqcCYvaM3+7Jm1I8s7OBZ2CDNtl+dJM45ZbbinXPh3HKRzeSTuO4+QJJrfhoE1D6tQWzUGWxjCHv1NFzQGjOjNqNjNV71qdid9zeapcVb3qea6FVCwP69q1a5tpd7ktngceg1bmUvWq6Xz1U5MEqa1bC7Dw+qgXeFiha6y2xn7rcmwjnY7Li3fSTrVlyJAhAIAZM2YACB4WLXsHBMqZL0tNWWhVr7IqNKkStuKXL7jgAgBBMQLuX724dT9WSUNi1c5mpi3Anl5jLu2aXm/ccWoC3kk7juPkCXry0jbNwaEWAuGnldQGiKekVS9jje1VT3KtD61x1vzbirfWgS1Vr1bjIqqk69SpE/OA5j5pk+eglaqUswX828qiZpmJ9Jxp26yQzLQMZUBwnq2yt1p3+kgT7Xgn7VR7ePMzQ5VmBQNsBxKrtrEqaVXKVjpCfeFxfc39nlSKMKkdlne3FjngS54V1gA74iCpkL3jOMWJd9KO4zh5hsV1NJZYvbitdLRAMCCjsuWnDuA40LOW12QwVh5rHSjq9pg5iwNWmnKseO6SkpKYvdpS8bRzq4Lm35ZyVsfOtFhmzRKmGc2SkgSp3Tstw1h44HwkeCft1Bg0NCTsoc2YYT78ilU8nliVl3TakjZhTYLA+GgroURawfikqcPw33wR5OKc4pWhHKf64J204zhOnqGT489+9jMAQMuWLQHEy3Ra9mYgXjnLqhilqW4t1akVuLSqkxah4YCRy7ONHJiqaUfVa/hYaIPmoJL7bNKkCYB4LLi2kceoZiaN9dZMY0QdM3XWgMeuhZSAuBe3Dqg5YKfjZkULLXkn7dQYbr75ZgDAQw89BCD6YDJNI72sVVHrQ2p5b1tFDhiTzBcWl+NLgi8dhS8dfRnoS0WXZ3tZm3zz5s0AgiQajuPUDLyTdhzHKRA9e/YEACxbtgxAEFus5ThJUpy0KjdVhVSlGk6oA02NBeZAUm2smkecCpwDXariLVu2AAgGrjTxhBU+1SUHzdw2l2WopLZNB800bfFTj0nT/Vqe55qvXGPJtfxwGJ4nzVLGY2Sp14rinbRT46Cinjx5cvY7PmTr1q0DAJx88skA4kUArBchH0BNOqEJC9QhRcNXrCIGOkWmVbk0uQOVM7OqabF6x3FqBt5JO47jFJj169cDCMwvVkassD1ZB3ZWtSsO+NROq/Zbogl41INabdWWqmV2NSpqmoA4oF27dm12EMo20QbNMqjct3qIqzmI+9RMYWrjpzLWsEOdLdDCOlZoJRBX1xqzzeOvLNNTcjolx3Ecx3GqHFfSTo1l1KhR2f8z0QlH93//+98BxB3JdCSvI3grDlPtgRzh09M1XI82CZ1uZ0iVZqCiYxrtgGzXkWYzcqoGJpp58sknAdiZxsJKWqsrqU2aphGqQio7VY1qn+XfqpzVTp5UmSu8fd7zjJ+m2uXve/fuze6Dtng+H/r8qec54TFpyVkrVlk93TXPuWZ64/75qfHT4ePSCmY0OfXo0SOxLUeKK2nHcRzHKVJcSTtHBVQuuRaXmDp1KoAgixIdzDRbE0fiWs2IaictC5Payrh9bmfDhg0AgDFjxpTZXqd6cu211wIAlixZAiC4X5Jyd2tOaFW2Wu1K46OpDlVFqje42lo13lqdI+lBTbsyUTXcpk2brNrkd1TQmhdcC99oG9U+rnZyHoPa5TWWWWcbNBZd7fFAvFIZj4nXsrJxJe04juM4RYoraeeoItfyjBw5a5ymhmhZ3qYciVMZWesT9eqlF6wr6KMDegTzfqHSTLJJ672n2bcsz2hVwpz9IVxfFbCGD2pcNtUnZ5ssW3h4m7RJq2e67kvtv/zk79ynzhqod7wW3aEa1upX/LSyqwHxcMhwSdx84EracRzHcYoUV9KOUwaazEQr3+gIn9DWxpF+Uj3a8Pb4O23R9EJ3jg7oM7F06VIAgX2XyhKIZw7TvNN6D/IeVU9oqkWNYODvGnusCXhUURPNREZ/inA1qBYtWgCIp8nV54Cqnm3izBKPiUpclbRW7KIS1mRE3K5mLLMK7ISVNFU4Iy369OmTuE5l4UracRzHcYoUV9KOk8Do0aMBALNnzwYQz89LdcAYSX5PmyJzEVNd6EhfbWb8njGm3L9zdEH12bRpUwDROGG9l4hVG1lt0Fr0hYpXY/w1I5mqXGu7fEb4DGzfvj2yXr169bIzBDwunRXQmSpuW/MSqCe79cn1qH41Lprt0OdS7fpcHwhs0GvXrkUhcCXtOI7jOEWKK2nHKQPGQGpcJtUGbVwckbdt2xZAYCtTr25V0Bzp0wbN6kCO4ziAd9KO4zhFA0MEn332WQDBYA+Ih0QRTYijDl5MYqKV3bhtbs+a7takJhrSpQNYbk8rzDVs2DB7DGwT4ba4b/7NbdBRTI9ZneXYVj0WLk+HNR6Lmgh02puE98OUvbmGc1YU76QdpwxY9pL89Kc/BQCMHTs28v2CBQsAAM2aNYt8zxeleokTfs+Sk5VVOcdxnJpBQTvpf/3rXzjzzDNx5pln4rXXXgMA/OMf/8Att9yC119/HYcOHcJXvvIVTJ06FWeeeWYhm+ZUA/bv34/BgwfjmWeewXHHHYexY8fipptuqupmOU6lc8011wAAXn755ex3qqStYhzqhEX1qOFNXN8qk8nlNPRLnbO4vhabUeetY445JruMlpDU+uyqxrkPLqdlMKm0tc3cH88BP3lu6EjGT007SgVNsxYAXHfddSgkBe2kb731Vpx11lmRbEv//ve/0blzZ8ybNw+f+9zn8JOf/ARXXXUV3nvvvUI2zakGjBs3Du+//z7WrVuHrVu34pvf/Ca++MUv4vLLLy9YG1RBE07fcRpN4y01wxhfHvSA3bx5c6W203GcmkGqd/eECRPQtWvXyHfDhw+PlAHMhTfeeAPvvPMO+vbtG/n+/PPPR79+/dCkSRPUrVsXo0ePxt///vfsy8upGaxZswZNmjTBf//3fwPIdEpNmzbFypUrc97GggUL8OMf/xiNGzfGWWedhf79+2P+/Pn5abDjFAGrV6/O/tu1axd27dqFjz/+GB9//DEOHDiAAwcOoLS0FKWlpTh8+DAOHz4c+7t27dqoXbs2GjRogAYNGqB+/fqoX78+Dh06hEOHDmW3u3v3buzevTv7986dO7Fz587s95988kkkFKlOnTqoU6cOjjnmmMi/WrVqoVatWtl2lJSUoKSkJLt8nTp1st+xDfzH7+vWrYu6deuiXr16qFevXvZ7HjOPjcvxb/7Of4Rt4nb4N9vM/fAf2bt3L/bu3YsNGzZk/xWa1E66R48eWLFiRTa7ysGDB7Fo0SL07NkTQ4YMwQknnJD478tf/nJ2G4cOHcLQoUMxbdq0WIyf8vvf/x7NmzfPxpk6NYPTTjsNDzzwAK6//nrs27cPffv2RZ8+fXDJJZfkdB/t2LEDmzdvxjnnnJPd5jnnnINVq1ZV1SFFOPbYY3HsscdmH36iL0zCFx4f/MGDB3tNaMdxYqROd7do0QIXX3wxnn76afTv3x8rVqxA06ZN0aFDB3To0AHTp09P3cnUqVNxwQUXoEOHDvjrX/9qLrdx40YMHToUEydOLN9RVCHnnntuVTeh2tC/f38sX74cF1xwAUpKSrBs2TIAwPTp01PvI6YFZKIE/p8hUs7RS01+Bvv375/9/5NPPgkAaNeuHYDA7qpFKRTac7XkJJUmny21RdNEo2GHaldWO68W/OD3derUMduohTbCSVzCaKlYTVmqyVHUfq+lKtUGredk69atAIB+/foltqcQ5GST7t27N2bMmIH+/ftj4cKF6NmzZ8472Lx5M6ZOnYq//OUvZS734Ycf4rLLLsOQIUPyVpczH0yePLmqm1Ct6N+/Pzp37ozZs2fHQknKgo4hu3btyj7Au3btymZNqmr0RWm9jAjDOKrTvV6s+DPo1GRy6qS7dOmCwYMH45133sELL7yQDUMZNGgQFi5cmLhO69atsWrVKvzpT3/Cli1b8MUvfhEAsvaU5s2bY9OmTahduzZ27NiByy67DJ07d8btt99eSYfmFBt79uzBqFGj0K9fP4wbNw5du3ZFkyZNcrqPGjdujBYtWuDtt9/Gt7/9bQDA22+/jS996UuFPATHqTI4oFu8eDEA4NRTTwUQpPekmrSKwlhe4Vpog59WelAt40oPbKpT9dQOK2lN6qMqX49BU5lStWuKVB0UW2lG2UYtTcnf2XYq6G7duqGqyamTPvbYY9GtWzdcd911OP/883HKKacAAGbOnImZM2eWue4VV1wRyXG6aNEiPPHEE3j++edRu3Zt7Nq1C506dcKFF16I+++//8iPxCl6Ro4ciQ4dOmDOnDkYMGAABg0ahMWLF+d0HwFAr169cM899+C8887Dtm3b8Oijj2LevHkFaHk6Oj1nhcOw+s6mTZsK2DrHcaorOYdg9e7dG3PmzMHcuXPLtYN69eqhefPm2b+PP/541K1bN/vdc889hz//+c9YtWpVxFP33XffzQ4GnOrP888/jxUrVmR9EiZOnIhzzz0XP//5z3H99dfntI277roLgwcPRuvWrVG/fn3ceuutBQ2/cpxi4Ac/+AGAjOABAkVNlUmVqkqYqpTLUVHTlKQKmbHBWsaRKpfLqRLncpYSB+IFMzSGm+uyjURtzhqLrWl3uT2Nd+b22WYqaJqhGKdeDJQc1vxnBuvXr0f79u2xdetWNGrUKN/tcpxqxeuvvw4AaNy4MYDghacZxxgPfdlllxW6iU4No7ydtE4Za2U3nfJlh6YOYtrB8pNTyUw0smbNGgDA+PHjAQCTJk3KZuRjW6yOXjtprQtNcu2kOYNVHTvpnJR0aWkpJk6ciB/+8IfeQTuO4xQB3bt3B4CsP0ebNm0A2CUtVQlb3t5q32UHRo9ntW1zu+ykWcpR82on6UF2uuxEtewl28i2cR+6TT1WVeBqb+d22GkzLW8xOnKmdtJ79+7FF77wBbRu3RorVqwoRJscp9rxta99Laflzj777Dy3xHGcmkRqJ92gQYPsCMpxHMcpLnr06AEAWefL008/HQBwwgknAIhPLRP1nNYKUpxiprKm6tRpcC7PfoK5C6hyw+pVvaz5uXfvXgCBImbbiXqO67bVK5zL85jVkZMq/4MPPgBQtXHQaaRmHHMcx3Ecp2rwUpWO4zhFxuLFi3HnnXdi48aNaNWqFcaPH48uXbqUuY6WOX3hhRcAACeddBKAuKMY7cBUpaq41ZOaapQpoj/66CMAcTuxel5T3e7bty+rmPkblTHbROc0Qlu0emdbbVPHM/Ua37FjBwBkCzgNHDgQxY4racdxnCJi06ZN6NGjByZOnIhdu3ZhwoQJuO6667Kex87RhStpx3GcCrBo0aKITfPAgQP46le/Wq4Kb2E2btyIE044AVdccQUA4Morr0SDBg2wZs0anHjiiTlv57vf/S4A4Gc/+xmAIFSLETpaVjWcGQwIVChVqX5PVUxYrpUqmQqbKnnfvn1Z9U2bM9fRmtT8W722rfhqokqaCpwDHJ6Tiy++GNUFV9KO4zgVoHv37tizZw/27NmDzZs3o23btrj22mtx//33m9Xd1DEqzHnnnYezzjoLy5Ytw6FDh7B06VLUq1cvUlmwOtG6dWu0bt26qptRbck5mYnjOI5jU1pais6dO6NVq1aYMWNGhbb12GOPYeTIkfjkk09wzDHH4Omnn8aVV15ZKe1csmQJAKBVq1YAgspyVMCqYqlKaQ+mKmU89NVXX524n1mzZsW+Y57xli1bAgCaNGkCIG4P16pWVvYybSPt7FTs69atAwAMGDAgsY3VAVfSjuM4lcDtt9+O3bt3Y+rUqTmvs379ejRs2DD7DwB+85vfYOzYsVi5ciU+/fRTvPLKK7jxxhvx1ltv5avpThHjStpxHKeCPPXUU7jtttvw5z//OZv6cvz48dmUmElY+ScefPBB/OEPf8Bzzz2X/a5Lly646KKLMGbMmMptOAJlTXs37cRUtVSp9OqmkmZ8dnmYMmUKAKBt27aRfdKrm4raSvNJNN6aXttUzr169Sp324oVV9KO4zgV4M0338Tw4cOxdOnSbAcNAD/60Y+ytuqkfxZf+cpX8Oqrr2aV85tvvolXX3212tqknYrhStpxHKcCjBs3Dvfcc0+kXOnXv/51vPTSS0e8zWnTpmHy5MnYtm0bmjVrhqFDh+Lmm2+ujOYWFXPmzAEANG3aFEBgs1YbNZU046qpnD/88EMA1SPe+UjxTtpxHMepEryTTsc7acdxHMcpUtwm7TiO4zhFinfSjuM4jlOkeCftOI7jOEWKd9KO4ziOU6R4J+04juM4RYp30o7jOI5TpHgn7TiO4zhFinfSjuM4jlOkeCftOI7jOEWKd9KO4ziOU6T8f5US6DbyjgclAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# now lets do the same with vmPFC\n", + "mask_file = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=5\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None,\n", + " standardize=True, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + 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"shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + 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"[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "mean_act_vmpfc = []\n", + "scr_id = []\n", + "for func in func_files:\n", + " # get subject number\n", + " scr_id.append('KPE' + func.split('id_')[1].split('/')[0])\n", + " # get average activation\n", + " t_map = masker.fit_transform(func)\n", + " \n", + " average = np.mean(np.array(t_map))\n", + " mean_act_vmpfc.append(average)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ttest_indResult(statistic=-0.6388758996578112, pvalue=0.529499641388856)" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#df_vmpfc = pd.DataFrame({'scr_id': scr_id, 'meanAct': mean_act})\n", + "df['vmPFC'] = mean_act_vmpfc\n", + "#sns.boxplot(x='group',y='vmPFC', data=df)\n", + "sns.barplot(x='group',y='vmPFC', data=df, ci=68)\n", + "scipy.stats.ttest_ind(df.vmPFC[df['group']=='ketamine'], df['vmPFC'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "len(mean_act_vmpfc)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "with pm.Model() as model_glm:\n", + " GLM.from_formula('vmPFC ~ groupIdx', df)\n", + " trace_vmpfc = pm.sample(draws=4000, tune=3000)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pm.summary(trace_vmpfc, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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jEsWonTPA6+frbqYc5dAwx8X3DOd8uT7nEj8j5sz1eH/4HHjfVHOk98FeBGrvs8+C91uXN9SUSzRcyJh0IpFIJBI9ilQVSSQSiR6BGSHZslSxviiL2wzanhEzXbNOCogwD4geEnqNCGZEs6a/ztsZeZqibG4i8kQxVynq8WDv0a9+9ava/bJ3Ohl4eVyR13e4MSIvaQfUJ02aJKld0KFO3IMXzycgckcbkXskWp6IkmI4RroT69yPUbvBqC9rNNamY4zAyeMJZreiJ7Z1geuU3/zbuHHjJFU3/s033yxJ+shHPtLRWHoBdqNKVaMMu3Spg0yRED/AmIzjB2LUcrJMxpPiBEc+XJi8w4cF750oya+8j6J5RO1mfzJpyYjKD5kY6XPDMVL4h9rO/t0NYJwXkSVaiUQy6UQikegZOE48fvx4Sa1ZxTSG2OfbBnWUpc96d8aiDRqKBju1GTREGT8uwYoBxpybcjpIWKI6Z7a0pJwoOxTynDLrvDxHNuBPPPHEtuMbCQzrS9ptJpv6nlL4X2pP5/fJivqARj1QjSYG3cRO6YaJJmgdmuQ9Ox1Lp8dABs2yg+eee05S5QZzE5O60jAKFFBEw8mARx11VAdHNjYwg/ZxStWcjLrfUPqS54HM2okn7CTE7VGUgiVbkUAE3XpENDfqPDuG5y4TfnyMZNIsZ4nKIPnw5xiZaMSERd7LPva5c+dKkmbNmlV7rInE6oBk0olEItEjmDZtmiTplltukVTf4IGhEhtbZNJsQsEufTYcbXBGRCRi1ES0/kCEqIlJR5UwTX+PlMjYXc7HTq+E4WMpjWWvM1oY1pc0GRoZHS3ustm8J4zbKj7xxBOSqkQKTrCoTMSIhEJ80qOLHSUmmE1E3+v2wYJ9Ihpjt0ItHoPZnj+feeaZluXtQmMctZyYdA8xqWSLLbaQNPo9VTvBJZdcIqk9ni61u7k4j6JOPnQN+rvdkv7kgy8SemA8l3FaSiwyv6CpaUvJpP1/zwc22Ii8CCw75LyOYszRp7dH2UnG9+3t8Hi9/dESjUgkehHJpBOJRKLH4BBVSWRotNu4sjFqkkTWGCnBeXmySy8fJfNGRMcguy2ZdRRbjggL49pRPwKPmbFoGobcvr+z1pwhmLLdpg3z0cKwvKQXLVokqWLB7Bnq7OIoRlX+31m4dik4VZ5i71EmdRQPbopBewKSjVIAwL+zeUD5Nx8LmywwJsf4KCdw5OIxWNjvc/bss8+2jI1tGNkGsTxXZEe80c12zMp7ARdccIEkacKECZKqOVRK+9kzwjIUg/OFc5QPEZ87ZyL7JmcDAca+KSTDLHDGxMmYvX7kbSm9NtHDliyebtFO28My5yTqLxw1D2HSj4/ZzxEL6nh/3//+9yVJjz/+uCRpxowZteNLJFYlJJNOJBKJHgN7ckvtYQMbbDS+bbSz4xMzq82k2evcxhLDHjZAvb1SqbDc7kAdCyMWHik8Rp0F2a2K/QgiAmSDMerL7vPNEFHJpF2OOVoY0kt64cKFkqQtt9xSUnUCzCp8wGQxnGxSuxi/reknn3xSUnvjAza0j5pYMCM1atzBNnseO4UAzOw9nvLieayeYD4Wtv6jaEBTXWpU4uDlfL6ffvppSdUkcj20J6TXi2KU5T44FrJ6H8s555wjSTrllFM0VjCrp8RnGZ/lzcacgqZkGbrX6EajB6aMh9dthyw2Snjhg7ApX6H8nVnbFJloiiFHdc5cn/FyMnXGvKPs8Cg27mNyroE9Ja6rnjJlSu25SCRWBSSTTiQSiR5FSQIY6mDYirW+NhijjlPMDrdhSMPR26VKF2PaTVnfA4EGGXXEGXbiuWBIMWL/NADNvMn+TXyo6lZue7QwpJf0JptsIqmdqTEjNWKKdRPQJ9sTZ6ONNpJUMVe7gSj/FsWgIyZoeKxsZWY2Wsacy/HZmi/dUT4Gsiq6Zsiko3rRiM0ZPr+Mh5px+LpwwjKrtmScrFVlhj7LD3wexgJXX321pIpJs+1k+XDwzWmG28SkDf5OUQR6j3iOm2qH6dmJ3HvdtjMtx8aHqccWMVZ+kiFH9fnRw4t5DhwfzykZNu8LrmdGLSWrTqx6SCadSCQSPQYb7jb+pHajymD4yoZ11EnN3018nKDHJEbD26M0btQv3MuTsdftgyERL2tSQDU1GoxMrPR6Zv0lESz3Q4JCQ9HffSzldTD7Hi0M6iX9ve99T5K07bbbSqoYpA+IbDXKwC4vHi+8TyaTG5iRHGVzRwwomoDMJvd3Twa6V+raPHqsXoYqVZEYPAvujaiUITp2M3WPKYqrkwWW54Qi+Z6c9ig4q52lDqMZH7Si2MSJEyVVNzDdfyXrZCw9SizhOY0YNh8yhs+xz19Ukx7FlpsYc6ftTMtlOb94fqKKiU7r9Tlmb4/z1eCDluOJvAv0ivm623MkSeedd54k6eSTT64dcyKxsiGZdCKRSPQIHMJx4mwZQmDZJzOZyaTZpYmCPt4OpWtpFNFwj0SqbND700SnZKE+LrJwhgrN8ln/HIWJPLbnn3++5VzRixCVHxpenqStZOTexpw5cySNfCOYQb2kfaJZMB6xDqonsaF2uUwUh2WAv64LVR2a5OY8KezK8YTi5PEn4+ml6ylq8UblJ+/Ly1OEIDoGflKDmQ3QmfTAJIy6/XGMnqT+Tg9HE9saCTgGzY5TkfdEavdGUG1roHpjqf0cRqpb1AiI6qDpVjMizXgeU5M8YrlPuvKa7ploH9FyPAe+l6lYFjHjKBeDWeZRe8ISfhb1oiJeIjEYJJNOJBKJMYKNCbf1ddkkQzdSxS5d6vnUU09JqoxVZmkzW5tgkmhkIJqQkGyRBFBUyeMsj8FNfgwarSRL7FbF5MVI0MleAsakm9oHM4HY+zMxLWHiNtLo6iXtCbXrrrtKaj/BVEuiu4SlAmWddJPKVqRmxPhXFCeLCuyjOJcnPrWYOylkj24SMoJOG50bUWyaGcvMMPZEpluLMUGpmuR0rZlx+ibzNqjxffHFF0uSjjvuuK6OrRO4Lt/64azbHaitHcdJJTV6WsgSjUhFjt2r2DmK7rYoSWcgScVyXFHNfN22Oo2Hcx+dIqq35vXhuDhmMm++qKLKi/IcUrc9db8TKzuSSScSicQYYfPNN5dUGb8lcZFaDSYa1zZmXGoZZWlHhMfbI9Ehe2Xiq8HSOwpD2agqa4wZTmRohCENEjsa2RH5ovFN9s+xMUTo0lJ7NsqMbm/TIb9rr71WknTIIYdoJNDVS9qTgNminDSUaosSGeqYTqQcZkRWesTAI8bBjGi7MziBfay+mGaYdZODMTZb8+xN7PNhZsvygybNbsPLebu+Pow9M9PYx8yEj/L/vlZsg8cxcwx1bqHhglkS66Gb4rjlb1G3M3oVolgymS8lGb1dZo9HNclNnp6odpmoY9Jk0NE90IRumTVdiNwv9fCZkMRj9fJmzv709koXKruI+QU2f/58SdLxxx/f1bEkEmONZNKJRCIxyrAbfquttpJUGb02+hg2kWJpXjZtiRIGWRvMel+Wwtl4omIZP41I8rYkZ5FBTYLDpNaocQ3DSWXXMKmd5fO8UsLaYFJ0WWrr/9uoNHkYKUOwq5e06T0zYxlz9XefiDpptXJ9KdbgjmKFRqRqRkRZtL4YbK5OpuOJNhCriLp8sYyAcc2ofZoRsSuCuuc+Nmaik7mXN5G3TR1sxtejZu2RZvVQ4Lpoa8Qzvlx3HETEYNndzMcX9W+mJ8fz1scdNZ/ngzNSleO1jvpGE3Xzv9Na7GifTfPSaNKaZzY3y1yYmMSXja+NnyOGH8jlg9nzlS8W77MXtOYTiW6QTDqRSCRGGYwfMwGRKmJSO+mJBHeihMGopzJ7KNvQIZmgaBANX4Z2vHxd05coAZIduGhAMiGTjJwJrTTweE5oGHr7kTeiPC7GsS1hPdzo6iXNYncjclVE2d51Bx6lxBtNWdlcLrLuI/dKU6cpI2JG5TFE3YJ4jE1jaergZUQZx2bDrDFnrI9ehHIZjtWTnkkkbIc3nODDgR4ZVg8YdWOJ9M9ZRhI9TLrtU95pzDn63ql3pW65yNsxWDWzpvWavFncP6sRDLYr5IOZLRpLJs3rRf3ykcyZSCRGAsmkE4lEYpRBBS0a/XVkhUmP/L1JhpXLM+YcybtGJbX+TsOdjLw0qiNpaI8lStQkWWjK+qY3oE5HvPzO0BkNw/KcRq1YTYqGW0inq5d0pCzki8QTyu/McC0PvFN1o4iREFFzcV5kI2r/ZsUt3iAsNyiXoRuECmTRROEYuM/oRo4YU8TsI81mqZpw1B2n24hjYhu8uXPnSpJmzZqlwcKT3XXRZGB8aJBhl0yapS0GHxrdtqGLtLajedpUhWBENfQRM4/me/lbU8VEtHy0Ty7XlDXOygm+JJgERE8S8yP8UCxfQpyv9DKZhV9++eWSpGOOOaZ2rIlEryCZdCKRSIwSLrzwQklVcxgjMrTrDCuSJBsmlDBm6SeNfxtJkagMjXvGxLme/04iNJDhy3V4/ExSpuFGA6/TREuCBinJSIlIvMdjdL7BcKGrlzQtZjIXMjsy7040gTuN2TXF6KLtOqP0vvvua/ndbC3qjW2VI1vozz33XMv2pHZ9bzNoxjd93iyb98wzz0iq+nNvuummkuLYfzQRm2KDkT51XW4AY9A8H/YW+He6tqLcgm7ga8HzRvYYJc6U3pImFyBZWvRgI2ON5l1T/X7ETiPmHa1n1DHppnskmkdNx8hj6rSun65Il66wnt/wg5Is2DkK/r28B9lO0fBcYL/60ezelkgMBsmkE4lEYpRgg4QSqEyEJcGR2o0gG9A2Umz0OJzA7GobPU1sMTL2Gd9lYp/HY7EZE5kyJMjkYxI/Iwr5cflOxX9Yd91J7+ty/dKoj4xRCjsNF7p6SVPCjZ2BmuooeaLLSdCpe6JTJh1Z955A9957r6SqtdkDDzwgSXr3u98tSdpss80ktcv12VKviy8zVsYJ6Unrfbsv92677dYyZnd5KuvIB8JgO1HVnUuyfk9O/868At+Y3e57ILiW1R4F1rpGymzMni/nV+Rd8Dn2A83XLspS7zQnwmi6oaPtdsqom7Zbgp6YpqoBoulYOs1MpxgHdRWY4+I5xznoe7nU0+eLiC8yJkl5m+eee64kacaMGfUHn0iMEZJJJxKJxAjj/PPPl1QZgzYmzOgoS0sVMam9xNIkwPW5/m5D0waIDRTHrhljphRwlDhIkublvV1/MnZdhp1Mivw3Gsc03Iwo2dYg8WPyrAmUjXIb8jbwmEgcZXCX8HHyeL1tizBNnTq1bd1u0NVLOhpMk6A7URdL5IVnBjI/o7pmI5pgXt/B/R/+8Ict6916662SpKOPPlqStM0227Qsb8H1gcD49yOPPCJJ+s53vlO7vCeoazl5Lpr2E6loRctHNeB1fyPjiEQEus2KHghm0PYo+Hh8PiOGFvUhltrdhz4ee0p8femqiuQLiW5rjJuYeFMMuxs0sfQmRC7EThXIuJ0oP4DPE5bReH3PA7Jjqd2VyxaHlHT03yknmUj0CpJJJxKJxAjBbnSLqDAJ0iyWjM+suOxZbAPSBoWNITbyYSiODU0M/91Ng8wqSZBoXEUGqztHecyPP/64pIo9S9KECRNaxmj2zYS/qKFNxKBtfHnf/p2eCZbD2pPh0IlLbr0cE0rLMXpdlv15HZOMobbv7eolHQX3mzr7GLRyy4QCHygl6hjX9Rg8YX3yIiYdJWS4RVwE9y7+kz/5E0mVbrQF8X0RSzbhY3j44YdbPh2LjuCxMLOcbDaSyjPTMLPwZCF7oPhAXeJIVAPLfXFMkZD9YGD3nW96SvoxCzjKMi7Hzq5nPtfeB7t6RWpvROTRibwWkfeD6DSruxM01TlH+2yKMTctb0SxcD6A6aKMSo18/euOg4lCdBtTy4DzObO9E72GZNKJRCIxQnBZpckE3eyRLK0ZYMngyKRttDSpaDHxzrBhWrb6lCojnnK73i6lVtnCmOGpshWul7Xx5OM2g/XxU4GMx0S277FErWMNZnn7nNhYN+jJKNcz62degeF1mqSuO8WgYtIRO4jYQ1T0XrYH8/99gVl3G7mHHCOm/jSL3dkBypPl2GOPlSQ99thjktoTD7y/+++/X4i2KqgAACAASURBVFLlWnK5Q8kmXnjhBUnSPffc0zIGT6A//uM/blnHjNGZ5FET9qZyAp871137JiNrZFchJnqU++wUUY3tYJTGFixYIKnKsPf58I3EmuwoLs7YtFTdOL4ZfU08j6K5HGl3R8dtdJqlHS3flHnd9L1ElCvSlMfRbQZ7xNAjvfOo7p9eGs57droqx8nkKi9LN7PnCoU//H24pR0TicEimXQikUgMM6644gpJFYmIElnZrpYExga2VBEEM9RI+YvGKg0XJk+yBbH3zQQ9j3HSpEmSKqLCMjey3JJU0CAzkTBpcmz4qaeeatkmvQFR7J5GGVvs0oAnKWP/aPbcLo+X4UI2lvI+fQ2vueYaSdJhhx3Wts2B0NVL2i4JKkFxkFEmNmOipZvAjJU1r3R/eALx72TSEYPxRXAihy+CZfqYQOBJ4otmJuZJVN4gTorwpy19M2bfZJ5QZIosO+iU0fgc+BzyXFK2biAWSHcSQWYX1c4PBtRi5rjpCaA7jiypnBN+CNi1R28Fj6+J/XXLlJs8FNwe3XR8mEfoRLu76bPT/I4mzQKuF9WqN8XKvZ6vp+/BOqUy1lZ7m3QN+3ffg2xVWLpoE4mxRDLpRCKRGGbYKKRhTBd+ZOjUsWSzThsWJEc08qPyVYPGkf9uEuHfbfjYiPaxOWvbssYeF4+5PDYau96Gj80Ex9+XLl3asjzPAb0EjAPzfDP8SVAW2N9LQ5AkgaEVJkB63/Y8dIuuXtK2Lp9++umWwfqikhGSETG7u7RW6dag9c1G594XL0IExviY1ckJxuQMw8du1bDyYpulOVvbVrndSUzcIGuKMoWb+vSyDIHuJ8MTjuegZE6dMkR2AaMkYDdw/G/rrbeW1O41oeeBCSpRAoc9F1J1DZghXyf7Vx5fxJyjeDivZZNufcQeo3FE871u+50sU4cmDYImD0838fISnQpU0LVZem+YCe756HuBTSVYtsREpERirJFMOpFIJIYJboHp8FnUeIbMjoaPfy8NTyqKGTYwqKrFBEsqjjHTnMSIEsEe00MPPSSpqq+mAhqFgkojjX20HVY0o/YYzTrN2lmDbHhMNCxZNx0JPfHcGUzi9bFK7dKzUZiXDYy8zauuukqSdMQRR6gTdPWSdiyILgCfQCYKMFGBMWl/Su0nkTWR3qdjyVEctwlkPJHSGWNankyufS5rvI0lS5ZIqjpqMXZGkKnUZSUPBGa90g1mFuGsc5YG1MWRI4UtnifGgam73A2sMOYb0/v0uOmRoMuLmfy8UaW4Jje6BvQy8JPeoMhrEZVj8BqT5UY18U2oWz46hqYM9kjdj9tliU7kpWhyv0bHEMXI2bFNqp4bvl9dLsMXFPcdJVslEmONnImJRCIxTLChaRJhI42JigxNsamIDZHS6LVRaoZqQ4JMjWE1G+tsL9vU+YlhMRMmh5G23377lvVsCJk0mKSUddgeq/dtpuxYtLfhxFwmAtJ4ZYKll/dYvbzH7HNjI5vExrC3gsSyHHsUjqGRS4+GiWan6OglbVkzq21FsnNRKzTGL32hLJtWHkikCGREbIB/J6Li9iheRjbgm82Tqa5e1pPSF77T7NYIUUwwUsFiwoKvkxmpb1aqpZXbZwu3aEyRm8jrz507V1Jn9dKeB9Qup1xhpEgVieDXJaxEam1kUvykd8IPEX/6Jvb58IPJD22WuTDJpIlJN9U4c/x1y3ZaLcCHDx+QBu9ryk9yf+zlzMxq7r9T1M1feuKY+c9cF15nX89LLrlEkjRt2rSuxpRIDBeSSScSicQwwUZa1OLVYFKojQmHTWhMSBW7o/604X15HRsmNo5mzbpTknTffX2hgE9+8l8kSX/1V9u0bIeEyeubAfqTvbF9zA41sO90OXYvawOd8s420G0ERzF9IxKv4hgYEyfpoHwwRbZKMOYcfTJ0auP0wgsvlCSdcMIJbdsu0dFL2heF7cRofUa1oMy4rMug5MTgyfRF8yT23yNVs6jelX/ncpFylMGEgvLiMaGDcU6DY4qYQ/Q7M9MZHyWLoJwg65FLmEFQb5zuoohdNTHxEvbQuJ+298G4oI/L2/Rc8HlgZn7dcUV1yFEje3/3vu2NWLZsmSTpiSeekFSd67//+79v2d9BBx0kqV3mkRoDUca/EcWmeTwD1ac3MeeIYdMTxLg6zyWZNB+c1Jj39fZzgNUHTUpmdb9HrsdI0MNjpIRlt/khicRIIZl0IpFIDBHuF73ddtvV/p2kg0m2FHhiCLH8jdnXBkNwJAlVGMJhir7tObPayztEY8PG3/k7Fbf8uw18Z4GXTNoKbI5nM2TiY3Ks2ueJksckA17u61/vS+ydO/c9ktqNYnoHvB4NRJ9LluCW61BsKUoOjRi3j7EJHb2kWQfNmCYtZVq8nly0zEsrNdLepk4vywWY3GBEyQ9kC7S4jWh5Sr2VLJnuJiPKpu20/3Z0Pg1OdLubPMHMWBwnZXy0PAZ2ISMDjGrhDe+zk+SIKAHGn0y+IaN2fJjZvnX5AvT6+JN13mZUjoObtfucPvvssy1//6d/+qfaY/ODL4pt88aNHrAEk374vZx7TR6ayPMVZfiTUXPsURyduSs+16wM8EuAGfGR54n7LdelSzjSXo88PnUvyURiLJBMOpFIJIYIG8JkWQbZLw1RG7cMVdWF66JwgI0hr3vssbdKag8/VHHYvjGcffYzLb9/9aubtIzNx+axUESI27WB7qZFJamwsc+sahI8tho1sbDxS1noM898sGX9j3+8z3h+85sdnmslFVdccWDL8lQHY85AWZJHNs7QH5M/uQ1/lmJLA6GjlzR3zgxVDp7WPS+mfy8P3AcaxbOo38sTw8B+U2Z0FH9rkuvzmD15ytT8pnropm1H60UsP0r5Z+IIx8dC/5ItkEmz5t3nn8L1vNnoGamD2Q73TU8LH2x0CUaxypIpkg2yNaCZsl11ZtDsFOZtRwzaYDY4r6WvAQX9OW+jeyqq4y6POcocb2Lp0bFE9w5dt50ydcaoo7gxj2cgtThm19MlS5EQPjdYH91tRUYiMdxIJp1IJBJDBBNK6aqPDHQaov5k/FmqjOrIKLVBUokAtcagSbYoBuN9ffGLfZLH8+a9r+X3KMmSx+RSVIs6OUQkVW15afzQeKZByZAXScOb3vREy/YqQ9FJja37OeKIGyRJV155YMt4eCx13bAYB48aSkW13ayfbsKgXtK0hKMYEVkYU/ZLq5V1i9SC9gFRyYklDEQTe4hYbZN+cZ1WtZMiCMZvI2YTsXuOiVm1bONmNwpZQqQIVTIelm1ELeGirmORFnYdKJloRtXUhCB6sA3EeiL2F+UkNFUNNIGs0vOaMW8K+UfdrjhOXtuBlMY6/R6tH1Up8EHGsdPjwxeQH7j0uHEONnkXynPFuUNVRHbV8/VgqQ3rpROJsUIy6UQikRgiIt1sMmqy0oFin+XvUruWNo0VSqGaQbdvy0aviUirEebts+abTJrbJRmx3G+pOMbyTxIHhjcZHvKYTI6aPBaVgflbfPbt96ijbpTUHqMmGy7jx0wmJDmNWjRH7WebkAGXRCKRSCR6FB29yiMXEBN9Ip87XdR1blbWvdkN5X3ZkuE2I4lMoklW0aDb09YOy0UorlIeA9toRgILHFP0nW4/uhPp7mapnF15di8y+at0XfO8MMGJFjDlFqPkojqQGUTNLbhtj4lW+UBzIEoA9DYY4/K5cyJZ2VZVkvbee29J0u233z7g/mhlMw5oRkA1Kc6VKAFyIHTr3uZyTclrRpN8KGNyTNqKxEqM6N4dSMzE8PPE9wDDadEzjPKiicRYId3diUQiMUjsueeekqrSIBoq3WbYE6UB0lSxYsPi/vt/HW1NkvTSS49IkpYsmfP79b29vs9Jk/ryT447bmHLMTTlaURSneV4I4LSqWKkjayoXeRDD7Ua09WuByZlBx44v6Nj4fF0gqZ+AOutt55+/OMfh+t39JJ2rMMKKTyhbF9oMDOOSUelxd3Ug5OMjqU/ZFNRklU04SIJQrJZTw7HfUomzc4qg22oEdXZGZ6QTJZj6YrXZ5mRrwNrFsu/EeyEE5XVMSmoDvPmzZMkvfe9723ZJ69hJCvJhhpkbgMJgnBe+DsFexxHczYqj9ufu+++e8vxej4wPsh2omywYWbHhEgeC1nrQB6iiJlG0rcRa48SyCKPTiSxy+dEJJcbJfN1AsYwo/PEckR6OCgPmkiMFZJJJxKJxCBhBvSDH/xAkrTRRhtJqow8VrY0GSA0mMrlSDhseNgQ/O///u+W37/whf+q3ceSJX0d6nbYYaakdgP7k5/sS/jaaaedJFXiJOwRYNC4HqjyIArhMaRFo9bb+OUvfylJevDBB1v2fd55fWVn7353q1RqNQZ/trLYtdbqM4oXLfpzSXGnvRL0EDTpg/iTlQY25P/93/9d8+bN06mnnlo79o5e0q67s+qLrX26WdiBxPE1ylZ6+ZK12aL1Ot4W3UeOTZP5NgmJsI9plCEZuV0i/dVy+Sa5zybmwPWj7fhckc1GEpMUL4k680jtcojM6IzkWZmvUNZGNiE6t8wqZUw6EgCpy6aM4p4UfOFynH98aET79HbtBvX54Dn3McyYcYck6fLLP9yyP4PslV4W5gqUY4u+R/kD0cOH87cp/4DNP6JYdJQdazSJAdW5hFmO6Pkc5ZzwnmFzl0RirJBMOpFIJIaIKN5IbYiod0CkDVC3jyhe2y2iEKPH+MADD0iqjHtqqpPwRKVGAyEqOePvTz/9tKSq+5zJnEOwX//6REmx9yDCt7/d14EvMkjriFIUSo3q/SOVwE5DKV012PDGzZaiujnDg41ijHWarraArVpDJR//nfHJSDqzSYKziUEz/umbzjWA5WTyhIk0WaMkEu6zqb0ms7k9dsaafZ7JKnxuPfYyru7/+9pxgvGaRxKPA2XF2q3zs5/9rGVb0QMs6i5DpsbzWcbsyfx53aM4qRE1m4iYtH/3w8Tn3F6pT33qX1vG7Gs6Zcrfthzj9753QMs4ohwMelfKZTs9JiM6xgg87z6XngOeE5EUp+9xVhB0w6AJzxm7ndnVKKoKocco8tAlEqOFZNKJRCIxRNCYJUGJdMjZKnEgoyAKQ9ggYahw9uy+mPJnP/vzlrEYDJmce+4HJFWs9eGH+9o+3nPPPZKkd77znS37i7KWB1JSjJT9+Hd/mjn/4he/aBmzSZLPG9n7mWf+L0nSGWf8R8vvHpvPDc/3QEmnBHvOk0FT75/7iL4THb2kzRDN0IwmdsW4JuX+Sqvf67hdHRV8GKciK40aKESxu6aaz7o2eOXvEyf2uVcmTJjQ/zdb7Z1mG7OuPCrb4LE1eRV4Dn2MrIs2q3DctPyNDx1+pzvIYzKbN3McCJzUvGHZcIGJKR4rm3qwEYdUsTk+SJhXYS9R0wMniu/ynvCD08k3vpe+8Y1dWo7l85//z5bteb+TJ98kSfo//+cjLfvlvKVXRWp/WESImDTHwhdOlDvg6+LEGMp/cq74vimrDMrl6ZVhZnZ5v/He8bLcRzS/GYNuOneJxEgjmXQikUgMEeyR7e9Rdz6G0wwa7APFQg0bIjYAo25yxrbbtvZxv+yyfSW1hwhtHC1btkxSJbwzadIkSZUhzmRLSp+WIAmiQejzt3TpUkkVm7dB56Yd3rePzefbxq/H5O9R/wQbbVEIpS7hlCSU7UUZ8oqMXH/OmjVLA6GjlzSbAPhAmQnMZhcMpPt3MqTyAHzyo8xmZoQS7AhD9bPohDGuyYtK5sj4Wd2YeVNRnYvL82aiB8LfmZ0dKTxFXW6YW1AyleihwszrSOO2G3dR9DAhU+P5Y5MKMiu6HMv/R1nbvHn5wDKi2LPBa+lzbIU6l+h4nlvRjMdoeDvWGLYgxYIF+7as53F5bpRjZAKL4d/LJjFSe1OVqIFJlBvg+eRj97lnm1efA1eNUN2PteY+t86tsJei7h6MVOiixjlRuUyZr5FIjAWSSScSicQQQZd+JNwSMWnWBdclxdEwJnGw8eJt+e8XX7xPy/pHH71AUsWgaeR7fRtRNpKefPJJSZURtuuuu0pq74jHTm0lo27qjvfII31qaPfdd5+kyqBzWNGhPJbiMoGYCZZRJjvFm5okaKX2EBlJKRMuSTq6VZ3r6CVN69QTiTFmD5YnLqpRLS8YlcTIEKipy0/fJP/1X331qL7YZleOSdlqNxibJDuIbq66UoEmlwm/87wwnmkmQXfKX/3VPS1jfcMb/Nm3nYUL/xR/r+/AU3cMPP7IZRNlv9N7MhB887vFZxSDjtiNv7Mva90YyObojeBx8cFjkElHiS+RBrQZtR82/rRb7tOfvvv34/W91Tovvb8jj+zrh3vPPc9Iqs5lOW56GHxe/GDyvcBqCyrRcU7QjRnpINAbQQVC74fqgb6XPf/N9KlNzyqTcixG5K3ivcDniD+feeYZJRJjiWTSiUQiMUSwxWJUdtq0/kDhoii0wjAEjSSGdmhAcgw2KFlGaCPLBqENTjY78nYYpy8RJR1a9MfbMmNmqJVGNZv1MBxFVl8nTV0uPxDRYjgtYtCRuFVk7Ebo6CUdnRCm/PuiRBeHjK6Mn9mq9kTgZDV7mjr1/9b+nTj99LskVYzkjDMmSZK23357SRWDaWKZRsQwS0SMmQyZ0nc+rz5fDz30kCTp8ccflySddVbfZzSxq+vTN2azLC/vXqk8Ft8AJfuI6oUjdxHLMcx6fP7OPvtsSdLMmTNFuNTDySCeT9EDjt4Tg5KLjHWX/6e2MzXhqSgWxaQjRu3tUw3ODzazQ2/fyT7O/v7f/7tPXMF11Hy4RA+VY45Z3LL/8tguuGDPlr95TH5QOU7u+9bL+VqSCUeuRcaifR3osfE59nXj84Mdq3hPcr/lcyaq7Y6SdqLsfucKnHzyyUokxhLJpBOJRGKIYFemSNo3Mh4i5jaQtC0/aSgzUZdKYWXpZfk7w0UMbdkoeuyxxyS1Ex7v1zFsG6hSVbrKJkQ2ijwmhljZwpiMmsmRLMVlKNYGIoW6onBJiUhZjctGng6OrQkdvaTJFljvGLEQHkQn8Vyu4wNxUTul6Lh+/4GB4c2e/ZAk6StfaZW4Yyw8ykglg67LmGUck7E6ig+QnT/11FOSqolq5vLNb/YlaHzpS79o2X573N7MYkXLMUa6z2Q05fFEsXgeW1PyRB2DNsxSbr31VkntbrUoVu9zH3Vdqsu87rSxQYQozyLKdve8YrzXn35w+e/OmfAD7+yz/x9J1UPpM5/595blo9yA8v4xI5027baWsZ1zzv8rqXqY8/6mJ4IPQrpPPb+9PTJhuixZv8/1WLsc1aTXJSYRTfrk1Jx3DPrggw8Ot5lIjCYGfEnvueeekla2XqmPSqo6vbBX6mc/2/dioiVHNybHFb2k6l4E0bLcJl8YI9Ur9aCDLu3oWHg8nSBSHSp7pTbBVnQkC8lt80XV9LIuf2sq0YmOP5KgbIphkZ1E8Sq+7HkMDzzQWiZlvPRSH5v5+c//v7bx+7/Vde/7Pm3axS37jpI0iSYGx5c9kzHZEcrgetF4IlnYgdC0DPdlQ+Tb3/62dtllF82ZM6dxH1J7drfBpEaDBlB0TuqSHykLzOsRhYdo9NpQbBLoiRqiOFzl8Nz48eMltXd58nepimP7GtpAu//++yVV559Grg24SCGMoZFIVzsqueXykUekXCea/9Fz1mB9dRM6YtK8iGQ2UbwnehnVDT66mbhPNyTnC4svquph2L9XSe0vfbLfyFiIzkH5gmvqxBV95wPCf3/4YcdeX6ldL0KTwhnHMZBQP7fVqa5zNy9738SMdUaTPRr3QKpgnb6IujVSomsSvXw5b/idMf/ma+5j7R9RMTb/7fWWv0Weruj8NWVMR3OjqbtVU6Z8NJ5o3J2sGx2bH+Ibb7xx27YSibHEgC9p90q95ZZbJFUJJnRH0u3tTybnROxFil/8trzcK9U3/he/eG/L+r7pliyZJ0l617tO+f12Wv/uXqku+3GMhC9KWl6Gl6trJOHz05QxyBiRt2Fr0st97WsPtKwfMXXux+fQ7u5rrqnvlTpQzSK3ZeuPSUG0sv27G0nstdde4T6MCy64QJK08847S6pcviz18zn3JxuH8HyWIh3+jSVYRsQCI/ZoRH+nrC3LipiB63E5gdLlUf77SSf9naT2F5I9RjvtdJoIe5Gq8FSru5tMOpLKpMXP8jW6jP3p5exN8f3h60qhF38nO/I4fG5YB1znCYqEgPg7pXGnTZumweC00/rO/2233dYyDoop0dvDZFyjTqbU/6e4DBP6fN9Hsru8Vxkbje4N78eGjO9Dq4M5Rk2U5MWs2ypmLNWkkcQSOSYjMqQYGXoGn70G50lkWNZtkzH8yLhlSSlFhCJ0xKTtjvTDsNMMYF9U31y+WXmCStDS9TZ8g0f9XenSe+MbB3aZWm6OGa6RZje34xi5X0ZSdX6intd8yXrCuSWcH1Z2G0VMMYLHPHfue1u2E2Ug1730Oemjtmt8yBBNJSclTjzxREnStddeK6ndRcjjZriFEoz+XtfdiyGEKBeC+27yCnHu++HvucA2f3Y1elzsP+25YYNl/vw/liSdcMKPasdbdz38X9fPU2GsTjWv3JY/PS89FyxywdIbumPZlc3XldKZ0QvV54CKhsygL58JPjaf1+nTpyuRWJmR2d2JRCIxTCBrjWLPkXFHr0RpgLD5Db01/nRZn0FjiMmNkdY0PSrs4exjc2zan94fjTKpPT7ubZlB28viYzUJojctGisN+qj8j0m1NAiZUFwXEoxysei14fL04jSho5f00UcfLUm64Ya++lsfYNQxirTeiLLApeoklen6UnsXIX8///w9JEl/8Rd///sl613KjsN9+9t9ik7MoLYbnTrFZL9EXXZ3lDjAi+hPeyhcD+0J62OcM+c9kqRPfOKfW9Yj2GrON69/p2qSmZBZXnmMvg5kdGTMZOF0i/M6doJDDjlEknTjjTe2jDNKCIv2PdC18dyli9BoygLmw5c3nJf3POLfqYvtY2CNMT1GZtSXXPIhSdK0aT9QHUrvFtk/s7Gp993kivV89d/Z9Y3uVrvsqRBGHQUyaIY1fC78EvCcPOmkk2rPQSKxKiGZdCKRSAwTbFBEbXwpo8tQQyStKrUbhjS2bFSx8QjzSPw7xYNoaJIJ2rBkfN1hNXsJvD+TjpIEmBn7fDjM6JCI900vAWvAPVavxzg6yRrbopLl2yBklvhACZyR+llTQi4FuprQ1UuaiQtkI1E3JiaoMOYkVVa6L2KU5FSm80vShRfuKUn6i7/4qaTqBF166Z/Ujt3szHE2KkF5wkUn3OOwclnJ1jzpm7JfDR+rz6P3zYlkxagZM+6QVMWco9IjejJ8jGSYdSLz3oZvApZp8Hwwo304NI8PPLBVIW3RokUtx0MG6PH7xqZofrku14kSA3mt6MbkNY6kEMkGWSvMsiQmTXl7niueI+6CteuuZ7WMYyBE9yN1D1gLHsXTfS7NmL0c69197FFLPyaQWRoy1b4SiWTSiUQiMWxg8ifjvlH8txPdaxKFKPzDkAvrqlmNw0Q+hiEYw2bmuvdrY80dq+oShL2M99XU2MiGHqWAGYphGIuZ7wwzUVqWRjGN8RLcR1QvzZApjeKPf/zjbduuQ1cvabIRH3iUrc1yF7KOMgWdHZ84gXwCvByTGRyjPuaYPqEGXzRa6zxxPga6S6JaXZbYlIgELaL4dlRDa5CZX375h1u254nrcxL1qeZE9Hn3eiUbZoIF3W8sueKYzRxPOOEEDReoHudry9Z8URlL+X/qU3MOk9FGqlv+neux1zrXY5cleqXoQeKN7/X893e+sy9WfdFFe0tqzQVwLsPs2Tu1jIUP9agqgw0a7OEx02W+Aj1pPFbPO+c72DuQjDmRiJFMOpFIJIYJxx13nCTphz/8oaQ44TBS6KPWdJkBTGOURn+k8cCwmEGjKmoERAbP7TCsEWlblyCD9jap0GeDnOSAMWuGWmg0NwnqMMzEmudyvShOTeISKZN10sa3RFcv6WOPPVaS9Ld/+7eSqhNF1w0tck6qugnIeGMUK2THHYMCByx+N2u0O8pWvUVNzMq4v0jEok5XOIr5RXXSzlh3Yb/j8iyp8MQzzAZZE0pPRTQhySpLV5Kvqd1SHrtvwKg9G+t8hxMep6+RM52Z/OFPZrdLsZiFwZKL6JNMmdeWAh/+3Q8RfzIBhsyacWEKi/DGp2tTks4774OS2r0g3gZZO18CnCfUSfC8K7UCpPY5Ynbv5XwPWgAkkUjESCadSCQSwwwbXTT+iUghrU4wKqoBNsgCafBF2chMPI2YOBus0ECkSlpd7TLHQoPa+2ASo79zbFEZMGPcNKoZ1opKLUkAyr/xO4kdx+6/R4JcEQb1kna9og+UqfmRADzrWMuLxwlDVhhdDMp0ennHzSj7Z9bqE8W4Lxl7lNBQpzccaXKTWRs+P1Qx43boHmG5AF0yZF8cX1Pzd6m6hi5xYI0tReI9po997GNt2xoqfBxUuqLHhuy49CQwi9rnwvOAUpZkyHyosBcy5y+vARNdqKhHnQA2p2efdZb2sFKg3BdjzHzg0WPjY2OrQy/n6+Df7RXwuYyEOSIJzEQiESOZdCKRSAwzbDRRnYuIegbUteGMGpGQOFBGlb0WjKamM2xpy9JZZkpTEKpuvIznUuiGyaGRJGxTg5yocx7HESWI8lyV1yEiPyRBVCtjX4NOMaiXtBXIrrvuutpBGWRdkXRbuQ2DbgpOODIV6jeb7TsWbaUxM5UoI72pW07UJav8W1NXsIhxm4k8+mhfu02yVTIcZijz3FDJiZOIGuLlPsmemtoL2nMxEqDAf5QMQs9NCS/Dc8eHQVQnHbmymG8RSQFyPboMqfdubXmfVz8A7dlgT2bP85JJR13FeL5YX87zR48PvQv+uxk1+1HzIVXnuUkkEvVIJp1IJBLDDId9br/9dkmxpjdL1CqepAAAFQ5JREFUHGlY1yGSro0yxqmeFSEy4kmQHNoio2bZYN3+GBOmJ4FNW/w7QzZRljzJVVTzzfFEZYR1iaaU+LWRSkOfSaT++6mnntp2XgbCkF7SZny8OGa1jE1FfWnLZXhyPSGimLEnCieONbn93dt1PI11p5E7qm6sUj2j5oWOEgrILPw7O305Ru14Om8GaidHwghRR6o6lxpjqHRPUZHMymKTJ0+u3cdwwN4Pnq/o02Mua9nJQJu2FXk/+PBgcg09D8zD8Hb40KG3wPNq5syZtefknHPOadmuM6bLeC/dnJFbjp4uKowxL4FlQj5Wn1s+GP088Dwe6AWUSCRakUw6kUgkRgguqyTritqsRomyUpy5zPBC1Lkp6rXcVCpKGWEnGHq/zGS30VZHgKh65mVoUJp0sayVoZIonk4SZYORhJKhm0ietwwBcV8UtmJmvsdsQ7pbDOklTdr+3e9+V1JliZNJm30xlV9qd42YNTJjl2n+ZnIzZsyQJH3nO9+RJJ1yyikt65133nmSpG222UZSFetzEJ8ujCh+PFBP58jlEmV5Uyls0qRJLcd28MEHh/uSpHnz5kmqJAh9k7Afc9QQnZnNUnV+eTNxspsVjUQ2N+FrefPNN0tqz2onkzPKWnoel+vAOZ8ir0PU6S3KP2C8lm5NJs4wu7upw5PPiXXNXbXgGnKpPVs76mTGvA4qurF2PhLeYLs/3ueUXkwkEs1IJp1IJBIjBIcEHZpi+VnU9Yo1zlJ7SIWtP2100ThrCuVFTJqs0kYv1b0oTsW/l8Qmqoc2bCwzKZYJn2SrPIamLG2WIzKhk+Mpa5u5jyiURlLq8GW3GNaX9HCyqjlz5kiqrHlOlG6D79YHdiyP8Vhng2+22Wa160flCuUEjJaJYtG+aNa59tjoBYjAczB37lxJ7ZnCZImekJ3sp9sxjSTYYo962H5YsdNUuSzjqPbYUGGN17DO/ViHqESErko+jIzBZsl7fl9wwQX9vzFbmxnofND5O2PKLiOiRKNBVy5r55m4NGvWrEEdYyKxOiKZdCKRSIwQLH161VVXSaoMHZaQmlEzNloampFcq40hitLYKIo6cEVZ4gaTHL0/G2HeD4+JqCMyHhvLTL1PbjMiRyRbEUGKsr19TllmaPjYy2ZQHivFlKLMdIc1O+16RfTsS3qkdH0jRjh//nxJlVuKDD6awHTXDLSsJ5IZ9FFHHdXR2DrFSDCUXmDQhh9G1ltn+zlqVJdJJowVkzXSRRc1kY96gzctR0+Qj8X7d4KR9fEHixNPPLH//45XMzs7aqkX1YjzXLAemjX1BhOQmF+SSCSa0bMv6UQikVhVcMQRR0iSFi9e3PI7JX2Z5FfGpP3/KB4bCS0NJMBUt360XRuyDtU4ydFGMnW4KaJUHicNwigmTEEshp3IoCPBLHoTODYyd5b8ltLM3Ce9IYxJP/bYYxoK8iX9exx//PGSpCuvvFKStO2220qqLp4R1Q/XgZPemej333+/JGmfffYZlrGvLnj88cclSZtuuqmkdqU1igcMlIlvsMyE9cyUD4yYND0q9LT4hn3wwQclVbFnb59d3YYDVtlzvJ365RGDZl1/FKtmVjcz172cj61bOcREIpEv6UQikRg1ONTFTGzWTzNUUIIGYNTFqlOGbbCGmGpfTLZ02MOMmvulkJRUkR4aigYNQdaNc+xRiCbK8o4YN2V+qRpWhnwoZMTjdezeIayhhgzzJQ0ceeSRkqTrr79ekrTFFltIqi+JkOqL3Jmk4MQBq6CVccNE57D6lvuZ00UVxUZLRN2tIlF8otvfvT8/yOwqHKhj13DB2gFXX321pPbzQy10g4pgdEFGXdp4TH5oPfnkk5Ji9bREIhEjX9KJRCIxSpg6daok6dprr5VUsVJjICbNWDGNKxtJNprMQiMxmyguTLZJURoqj1EQKurVXI6JIREbjGySQ0EsIxLm4d8Z66c2OssDI1ngcvtRXNzn3Qb5YYcdpuFAvqQDWITAF9VKTsx0LS8e3U1URTOjSAwNjus61sqbpq5OOooZR9rkkd48FdjoSoxKPqiLTbU0e1uGE1ak4/nwi8Fj8Jz2WCJWzz7w/qSohpfzw7uXKgQSiZUN+ZJOJBKJUcYhhxwiSbr11lslxa1hS4OJoRquYyOJsVFK2Rpk5ky8ZGYzpW69vMtWHW93wqL/XhIZdruyUI5LXtlStqnkMfI8kFkzZGNQecwYSKUtMsB9vp3gOlzIl3QAWv9W3qLkXhmj9oV1QoWVxBLDC+taW8vb2d5kxa5FltofSF6Wqlx8OPDBxGSRpraBFOh3FzZv166xadOmdXEGOoMV6S677DJJVSIL2T47cDERiZ/0FFnHfcqUKcN+DInE6o58SScSicQYwezTRuBASY/M5qZIkkFmx6RIMkFvh3FbGmU0YDlmM2qTlLpkSu9jww03bFnHY2Db1E4z1aMGOIy3Rw1yokY5PDfl2BjeccjquOOOazvuoWBgIeJEIpFIJBJjhmTSHYLu74suukhSq0VnKzATZUYHH/nIRyRJP/3pTyVVCVFUAJLaFY2ofMQyoqb6Srb/jMRO2CfY23NMzvG7kYTd0N/85jclVYzIzWR8TBQj4bnxp8MIQ5UwTVTXxhKuFJwp48gMsbEHs+c0E/zK+6D8nbXA3GfUq9m/Ry1HN998c0kV0y7XZ2gl6onNuDg7cxHM1maGu7fj/TY9D1iaWe7X27THwAx68uTJtWMbKpJJJxKJRCLRo0gmPUhMnz59rIeQ+D3uu+8+SdL2228vqT37VYoFPKi3y0xXJopFFjqTsKKkK8Pfyz61I43TTz+95fvFF18sSZowYYKkqmTKkqXZUnL0cOihh0qqtL3rGKPnHvtKkwmzM1QEzu0onktvkOH7i7KwjjOz7roE47msh2ZbXXuevJy/My7v7TK2TUUxxv7JxA2ei7oxus3xSCGZdCKRSCQSPYpk0omVHlZxuuKKKyRJW2+9taRWa5nNIqJYNDNoqSoUfUZMOoIt/lJwZbQx3FmoiaGD2d4loi5YnkNkiWTClG1lFje9TN4e5zR1tTn3y9LH8nepit+adTuPhJngEfP1cpRp5tgYW+72fqY3ojx31OYeaY9TMulEIpFIJHoUyaQTqwyOOuooSVVDiYkTJ/b/jdnaUfwuynBl1mlT7Dlqk+n1zH4sxJJISJVX6MYbb5TU6mkxayS741zlHCaTZiUCY9OsGWaWNr1PbF1qDW/nW5SxbLNsb9Pr+js/KVDErlRm2OyWxdwSLsex8Zww1l1myL/44ouSRkaAqA7JpBOJRCKR6FEkk06scjj88MMlSZdcckn/b5MmTZIkve1tb5PUHktm7Ir1m0YkBxrpIjPzlZ2K3Bo1kSjh+nlnSkuVhK3nqOeQY6Ssn/ZynHOeu74X2H6XXiE2o6ECmdkx9QnY2arcN1m6Y9NRv2nfr4wts56Zx06PGVvGUpGM58LH6JpoqXq+jBaSSScSiUQi0aNIJp1YZVEXM3If34022khS3J6RtaF1OsQlzFYcr3KtsbNZ3ewikUgkukG+pBOrFdwicMWKFfqHf/iHMR5NIlGP448/XlLV6U2q2jmypWSUGEaBELqa6e5myVaUHOnt0LXsz4HKC9lXne5tJoSxfzslTe2OZs90hp8oxEJJVTbgoBTuSAuWDIR8SSdWS7z5zW/WHnvsoYULF0qqVLeim9zgw8FtGh1DTN32RCIxnBiTl/Tf/M3faPbs2VqyZInWWmstHXDAATrrrLP6LbtXXnlFJ598shYtWqS1115bp59+uj7xiU+MxVATPYymebTjjjtq6dKl/cu//PLL+vCHP6ybbrpprIacSHSFhx9+uP//TiIz6zQLjQRxIklbg4lmBkM9FOYxG45aZXo9h37KvztBzPeo9035TjJsJn65zMvMm4mfUamkzxVLuwx7I1hG5tK4scCYvKRffPFFff7zn9cHP/hBvfLKK5o8ebL+8i//Uueff74k6Utf+pLuu+8+LV26VE888YT22msv7bDDDtpvv/3GYriJHkXTPPrP//zP/mV/97vfaeutt9Zhhx3Wso2jjz66dttnn322pPYevDNmzBj240gkEokIjS/pb33rW7rzzjv7E24kaebMmVpzzTU1Z86cQe20bOm19tpra/r06friF7/Y/9vll1+uSy+9VBtssIE22GADTZ8+XZdddlm+pFdi3H///dp99931gx/8QH/4h3+oZcuWaaeddtKiRYu05557DmqbTfOoxE9+8hM99dRT/THpRGJlQGkUWvbWhqPZKEuzotaSFPRhu1WzVsamKfBhUD6UMW+2n5SkcePGSaoYbdSKkvFuNrbhtj2WqOTR2zGTf/vb396yH2/XDNqfjz/+uMYajS/po48+Wl/60pf0wgsvaP3119drr72mq666SosXL9aMGTP0ve99r3a9LbfcUj//+c87GsRPfvIT7bjjjpL6YnzLli3Tzjvv3P/3nXfeWddff31H20r0Jrbeemt94xvf0Ec/+lH967/+q6ZOnaopU6Zozz33HJF5RCxYsECHHnqo1llnnY62NXPmzI6WSyQSiZFE40t6k0020Qc/+EFdc801mj59um699VZttNFG2m233bTbbrvp3HPPHdIAbrvtNi1YsED/+I//KKkqGi+L+Ndbb73+WEQTdtlllyGNJzFymD59um666Sa95z3v0RprrNEvfXjuuecO+zwq8Zvf/EaLFi3q39+qhJzvqw8se7to0SJJ0hZbbCGpvZ0jQzQG47DOwvZyXj9iwpGQCDOjI2EQqT2G7JhxJEZCWU6PndvxMVCqlEybjTjoVXAM2o1OeqElcUdiJscee2x/FuzChQv1sY99rOMd3HHHHVp33XW17rrrtrGcO++8U5MnT9aiRYu03XbbSarKDFxf6v/btdOEOXPmDNoNnxh5TJ8+XUuWLNHMmTNrO/1E6HYelbjuuus0btw47bHHHkMef68h53sisWpjjd9FnQAKvPzyy9pkk010xx136L3vfa/uuecebbnlljrppJP6X97ExIkTWxJ3iLvuukv77ruvLr74Yh1wwAEtf9t00021YMECfehDH5IkfeELX9Avf/lLXXnlld0cW6LHsHz5cu28887aa6+9tHjxYv3Hf/yHxo0bN2LzyPjQhz6k973vffrKV74yLMeRSPQCrrnmGklVIxnHWc2IzR4ZSz700EMlSRdeeKGkilE7HmwW6zit1zfLJSNnRrSFfFyeWAoFbbLJJpIqMsbGNoxvsy46ipOTtfO1xuxvMmt7cB999FFJ0kEHHaReQUdMeq211tKhhx6qyZMn64/+6I+05ZZbSpLOP/98LV++vPbfQA/WJUuWaL/99tPZZ59d+2A95phj9NWvflXPP/+87r33Xl100UWaMmXK4I4w0TOYNWuWdtttN82fP19/+qd/qpNOOknSyM0jqe+m+9GPfqRjjz12RI4pkUgkRhIdMWlJ+ulPf6oPfOADuuSSS4ZcMzZ16lQtWLCgP9NOamVMZZ30W9/6Vn3605/OOumVHDfccINmzJjRz56XL1+uXXbZRV/+8pf10Y9+dFDbbJpHkjR79mzdcsstuuOOO4Z8DIlEL8JeqK222kpSxahZa2zW6TLESy+9VFK7Ihkzncly2RqTy7/wwguSKnbq9aWKSUfNPbwNx4h9b5t5s2UsmTTHxoz2qK2ms7h7iUEbHb+kH374Yb3zne/UE0880T8JEolEIjG2yJf0qv2S7kjM5PXXX9dZZ52lI488Ml/QiUQi0UOwIM8FF1wgSdpmm20kSRtuuKGk9hg1s7kZs/YL0vFbv8iczMv2kdQQZ710uX2ql/nlypcn66bZupL65Iy/U3/cx+S2mo6XP/bYY5LUVTL0aKPxJf3SSy9pwoQJmjhxom699dbRGFMikUgkEgl18JJeZ511WhpeJxKJRKL3cOKJJ7Z8v+666yRJG2+8saTKZWy2yWxudrli7bG1uF1LTJdy6daWKpZctnk1ozVjNsx8vQ2zfGeUk2mzrpp1z9yf32HuZnXfffdJWjka4nSU3Z1IJBKJRGL0ka0qE4lEooewYsUKTZ48Wf/yL/+ipUuX6kc/+lGtvv2KFSu00047afny5f31vSX+/M//XFIVq3ZimVkr66MNMmmDiWJsVmO4yxyZtlSxcMPJbex+xXppr8f+0VEM2vAxOvbsxLB99923duy9iGTSiUQi0WN4//vfr4ULF/a7quvwrW99S+94xztGcVSJsUDHJViJRCKRaMdVV12l4447rv/7q6++qve973368Y9/PORtb7755lq4cGEbk37wwQe1//7766yzztL06dNrmXSEd73rXZKk8847T5K0wQYbSGrvK+14rvsmOLt7//337+oYzjnnnP7/M+PcpVjrr7++pKrkqoxjl2Oh+plj02bMjj27DOyRRx6R1Bsa3INFMulEIpEYAo444oh+hbxly5Zpq6220lFHHaWvf/3rWn/99cN/Q8HMmTN15pln9ruHu8HEiRP7pUQTvY+MSScSicQw4PXXX9fkyZO155579mdaf+Yznxn2/Xz/+9/Xa6+9pj/7sz8bFFtnKa1FTcaPHy+pvcey2enhhx8+qPHWZVBbN9yMmR24WB9NIRXWPZs5L126VJKGrIrZS8iXdCKRSAwDPve5z+nXv/615s2b1/E6Dz/8sHbYYYf+703lri+99JJOP/103XLLLYMeZ2LlQsakE4lEYoi48sor9ZnPfEb//M//3M9IzzzzTJ155pnhOp3oTzAmfffdd2v33Xfvj+2uWLFCL774osaPH68777xTkyZNGvKxjAUuu+wySVV83LFqxsldD23FMPd9njFjxmgMc0yQTDqRSCSGgLvuukszZ87Ubbfd1v+ClqQzzjhDZ5xxxqC2+corr/SXH61YsUIvv/yy3vKWt+jd7353fzKUJP3sZz/TKaecon/7t39r2Xdi1UG+pBOJRGIIuOGGG/T888/r/e9/f/9vH/jAB7R48eJBb3P77bfvj6+6pvfBBx/UpEmTWsqyxo0bpze84Q0DlmqtDMhWxDHS3Z1IJBKJRI8iS7ASiUQikehR5Es6kUgkEokeRb6kE4lEIpHoUeRLOpFIJBKJHkW+pBOJRCKR6FHkSzqRSCQSiR5FvqQTiUQikehR5Es6kUgkEokeRb6kE4lEIpHoUeRLOpFIJBKJHkW+pBOJRCKR6FH8/zVvvTPW80ujAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Hippocampus\n", + "mask_file = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=15\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None,\n", + " standardize=True, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "mean_act_hippo = []\n", + "scr_id = []\n", + "for func in func_files:\n", + " # get subject number\n", + " scr_id.append('KPE' + func.split('id_')[1].split('/')[0])\n", + " # get average activation\n", + " t_map = masker.fit_transform(func)\n", + " \n", + " average = np.mean(np.array(t_map))\n", + " mean_act_hippo.append(average)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "Length of values (20) does not match length of index (24)", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'hippo'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmean_act_hippo\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0msns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbarplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'group'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'hippo'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mci\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m68\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mscipy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mttest_ind\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhippo\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'group'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m'ketamine'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'hippo'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'group'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m'midazolam'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__setitem__\u001b[0;34m(self, key, value)\u001b[0m\n\u001b[1;32m 3035\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3036\u001b[0m \u001b[0;31m# set column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3037\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_set_item\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3038\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3039\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_setitem_slice\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mslice\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_set_item\u001b[0;34m(self, key, value)\u001b[0m\n\u001b[1;32m 3111\u001b[0m \"\"\"\n\u001b[1;32m 3112\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_ensure_valid_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3113\u001b[0;31m \u001b[0mvalue\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sanitize_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3114\u001b[0m \u001b[0mNDFrame\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_set_item\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3115\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_sanitize_column\u001b[0;34m(self, key, value, broadcast)\u001b[0m\n\u001b[1;32m 3756\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3757\u001b[0m \u001b[0;31m# turn me into an ndarray\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3758\u001b[0;31m \u001b[0mvalue\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msanitize_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m 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\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mValueError\u001b[0m: Length of values (20) does not match length of index (24)" + ] + } + ], + "source": [ + "df['hippo'] = mean_act_hippo\n", + "sns.barplot(x='group',y='hippo', data=df, ci=68)\n", + "scipy.stats.ttest_ind(df.hippo[df['group']=='ketamine'], df['hippo'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df['hippo_21'] = df.hippo - df.hippo1\n", + "sns.barplot(x='group',y='hippo_21', data=df, ci=68)\n", + "scipy.stats.ttest_ind(df.hippo_21[df['group']=='ketamine'], df['hippo_21'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (4 chains in 4 jobs)\n", + "NUTS: [sd, groupIdx, Intercept]\n", + "Sampling 4 chains, 0 divergences: 100%|██████████| 28000/28000 [00:05<00:00, 5140.47draws/s]\n", + "The acceptance probability does not match the target. It is 0.6948570225703795, but should be close to 0.8. Try to increase the number of tuning steps.\n" + ] + }, + { + "data": { + "text/html": [ + "
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meansdhpd_2.5%hpd_97.5%mcse_meanmcse_sdess_meaness_sdess_bulkess_tailr_hat
Intercept7.007.31-6.5722.430.120.093506.03355.03513.03728.01.0
groupIdx-19.3610.02-38.640.960.170.123538.03489.03548.04080.01.0
sd23.963.7617.5231.760.060.043817.03817.03658.03645.01.0
\n", + "
" + ], + "text/plain": [ + " mean sd hpd_2.5% hpd_97.5% mcse_mean mcse_sd ess_mean \\\n", + "Intercept 7.00 7.31 -6.57 22.43 0.12 0.09 3506.0 \n", + "groupIdx -19.36 10.02 -38.64 0.96 0.17 0.12 3538.0 \n", + "sd 23.96 3.76 17.52 31.76 0.06 0.04 3817.0 \n", + "\n", + " ess_sd ess_bulk ess_tail r_hat \n", + "Intercept 3355.0 3513.0 3728.0 1.0 \n", + "groupIdx 3489.0 3548.0 4080.0 1.0 \n", + "sd 3817.0 3658.0 3645.0 1.0 " + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "with pm.Model() as model_glm:\n", + " GLM.from_formula('hippo ~ groupIdx', df)\n", + " trace_hippo = pm.sample(draws=2000, tune=5000)\n", + "pm.summary(trace_hippo, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.set_style(\"whitegrid\")\n", + "\n", + "grid = plt.GridSpec(2, 20, wspace=.1, hspace=0.0) # building a grid to put the graphs in\n", + "plt.subplot(grid[:, :10])\n", + "#fig.add_subplot(grid[0,0])\n", + "g1= sns.stripplot(x='group',y='hippo',hue = 'group', data=df, s=8)\n", + "#g1 = sns.boxplot(x='group',y='meanAct',hue = 'group', data=df)\n", + "g1.set_ylim(-80,80)\n", + "g1.legend_.remove()\n", + "\n", + "plt.subplot(grid[:, 10])\n", + "g3 = sns.boxplot(trace_hippo.groupIdx, orient='v')\n", + "g3.set_ylim(-80,80)\n", + "g3.set_yticks([])\n", + "\n", + "plt.subplot(grid[:, 11:13])\n", + "g2 = sns.distplot(trace_hippo.groupIdx, vertical=True, color=\"Green\")\n", + "g2.set_ylim(-80,80)\n", + "#g2.set_yticks([])\n", + "g2.yaxis.tick_right()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Caudate" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/caudate_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None, standardize=False, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "mean_act_st = []\n", + "scr_id = []\n", + "for func in func_files:\n", + " # get subject number\n", + " scr_id.append('KPE' + func.split('id_')[1].split('/')[0])\n", + " # get average activation\n", + " t_map = masker.fit_transform(func)\n", + " \n", + " average = np.mean(np.array(t_map))\n", + " mean_act_st.append(average)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ttest_indResult(statistic=0.18593831440195263, pvalue=0.8541968951546848)" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df['striatumAc'] = mean_act_st\n", + "sns.barplot(x='group',y='striatumAc', data=df, ci=68)\n", + "scipy.stats.ttest_ind(df.striatumAc[df['group']=='ketamine'], df['striatumAc'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "with pm.Model() as model_glm:\n", + " GLM.from_formula('striatumAc ~ groupIdx', df)\n", + " trace_striat = pm.sample()\n", + "pm.summary(trace_striat, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Correlation between PCL scores and average activation" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['scr_id',\n", + " 'redcap_event_name',\n", + " 'contact',\n", + " 'vet_status',\n", + " 'va_consent',\n", + " 'va_consent_date',\n", + " 'yale_consent',\n", + " 'yale_consent_date',\n", + " 'eligibillity',\n", + " 'mri_clearance',\n", + " 'mri_safety_notes',\n", + " 'enroll_status',\n", + " 'enrolled',\n", + " 'ic_note',\n", + " 'el_note',\n", + " 'comp_note',\n", + " 'screen_date',\n", + " 'scid_complete',\n", + " 'scid_date',\n", + " 'clinician',\n", + " 'scid_return_date',\n", + " 'visit1_date',\n", + " 'mri1_date',\n", + " 'mri2_date',\n", + " 'followupmri1_date',\n", + " 'followupmri2_date',\n", + " 'status',\n", + " 'other_describe',\n", + " 'masterlist_complete',\n", + " 'scid_bid_lifetime',\n", + " 'scid_bid_rc',\n", + " 'scid_bid_episode',\n", + " 'scid_bid_seasonp',\n", + " 'scid_bid_remission',\n", + " 'scid_bid_pm',\n", + " 'scid_bid_current',\n", + " 'scid_bid_md',\n", + " 'scid_bid_currentsev',\n", + " 'scid_bid2_lifetime',\n", + " 'scid_bid2_rc',\n", + " 'scid_bid2_sp',\n", + " 'scid_bid2_rm',\n", + " 'scid_bid2_pm',\n", + " 'scid_bid2_current',\n", + " 'scid_bid2_current_md',\n", + " 'scid_bid2_currentsev',\n", + " 'scid_obid_lifetime',\n", + " 'scid_obid_lifetime2',\n", + " 'scid_obid_pm',\n", + " 'scid_mdd_lifetime',\n", + " 'scid_mdd_episode',\n", + " 'scid_mdd_season',\n", + " 'scid_mdd_remission',\n", + " 'scid_mdd_pm',\n", + " 'scid_mdd_currentepi',\n", + " 'scid_mdd_currentsev',\n", + " 'scid_dysd_lifetime',\n", + " 'scid_dysd_onset',\n", + " 'scid_dysd_atypicfeat',\n", + " 'scid_ddnos_lifetime',\n", + " 'scid_ddnos_pm',\n", + " 'scid_ddnos_tp',\n", + " 'scid_moodgmc_lifetime',\n", + " 'scid_moodgmc_pm',\n", + " 'scid_moodgmc_specify',\n", + " 'scid_moodgmc',\n", + " 'scid_subindmood_lifetime',\n", + " 'scid_subindmood_pm',\n", + " 'scid_subindmood_specify',\n", + " 'scid_subindmood_feat',\n", + " 'scid_ppsy_lifetime',\n", + " 'scid_ppsy_pm',\n", + " 'scid_substance_version',\n", + " 'scid_alcohol_lifetime',\n", + " 'scid5_alcohol_lifetime',\n", + " 'scid_alcohol_pm',\n", + " 'scid5_alcohol_pm',\n", + " 'scid_sedative_lifetime',\n", + " 'scid5_sedative_lifetime',\n", + " 'scid_sedative_pm',\n", + " 'scid5_sedative_pm',\n", + " 'scid_cannabis_lifetime',\n", + " 'scid5_cannabis_lifetime',\n", + " 'scid_cannabis_pm',\n", + " 'scid5_cannabis_pm',\n", + " 'scid_stimulants_lifetime',\n", + " 'scid5_stimulants_lifetime',\n", + " 'scid_stimulants_pm',\n", + " 'scid5_stimulants_pm',\n", + " 'scid_opioid_lifetime',\n", + " 'scid5_opioid_lifetime',\n", + " 'scid_opioid_pm',\n", + " 'scid5_opioid_pm',\n", + " 'scid_cocaine_lifetime',\n", + " 'scid5_cocaine_lifetime',\n", + " 'scid_cocaine_pm',\n", + " 'scid5_cocaine_pm',\n", + " 'scid_halpcp_lifetime',\n", + " 'scid5_halpcp_lifetime',\n", + " 'scid_halpcp_pm',\n", + " 'scid5_halpcp_pm',\n", + " 'scid_poly_lifetime',\n", + " 'scid5_poly_lifetime',\n", + " 'scid_poly_pm',\n", + " 'scid5_poly_pm',\n", + " 'scid_other_lifetime',\n", + " 'scid5_other_lifetime',\n", + " 'scid_other_pm',\n", + " 'scid5_other_pm',\n", + " 'scid_pd_lifetime',\n", + " 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'pef_pulse_sit',\n", + " 'pef_bp_sit_sys',\n", + " 'pef_bp_sit_dias',\n", + " 'pef_pulse_stand',\n", + " 'pef_bp_stand_sys',\n", + " 'pef_bp_stand_dias',\n", + " 'pef_resp',\n", + " 'pef_heart_ventrate',\n", + " 'pef_heart_pr_int',\n", + " 'pef_heart_qrs',\n", + " 'pef_heart_qt',\n", + " 'pef_heart_qtc',\n", + " 'pef_3a_medhx',\n", + " 'pef_3b_meds',\n", + " 'pef_physician',\n", + " 'pef_physical_examination_form_vitals_supplement_fo_complete',\n", + " 'scr_consent',\n", + " 'eligibility_rv',\n", + " 'eligibility_pp',\n", + " 'eligibility_rwp',\n", + " 'eligibility_rcf',\n", + " 'eligibility_ldm',\n", + " 'eligibility_rlz',\n", + " 'eligibility_k13c',\n", + " 'eligibility_g13c',\n", + " 'eligibility_dm',\n", + " 'eligibility_petmglur5',\n", + " 'eligibility_mglur5',\n", + " 'eligibility_mdd',\n", + " 'eligibility_pba',\n", + " 'eligibility_mp',\n", + " 'eligibility_biomarkers',\n", + " 'eligibility_mddetoh',\n", + " 'eligibility_feeding',\n", + " 'eligibility_rapa',\n", + " 'rv_refdate',\n", + " 'rv_consentdate',\n", + " 'rv_complete',\n", + " 'pp_refdate',\n", + " 'pp_consentdate',\n", + " 'pp_complete',\n", + " 'rwp_refdate',\n", + " 'rwp_consentdate',\n", + " 'rwp_complete',\n", + " 'rcf_refdate',\n", + " 'rcf_consentdate',\n", + " 'rcf_complete',\n", + " 'ldm_refdate',\n", + " 'ldm_consentdate',\n", + " 'ldm_complete',\n", + " 'rlz_refdate',\n", + " 'rlz_consentdate',\n", + " 'rlz_complete',\n", + " 'k13c_refdate',\n", + " 'k13c_consentdate',\n", + " 'k13c_complete',\n", + " 'g13c_refdate',\n", + " 'g13c_consentdate',\n", + " 'g13c_complete',\n", + " 'dm_refdate',\n", + " 'dm_consentdate',\n", + " 'dm_complete',\n", + " 'petmglur5_refdate',\n", + " 'petmglur5_consentdate',\n", + " 'petmglur5_complete',\n", + " 'mglur5_refdate',\n", + " 'mglur5_consentdate',\n", + " 'mglur5_complete',\n", + " 'mdd_refdate',\n", + " 'mdd_consentdate',\n", + " 'mdd_completion',\n", + " 'pba_refdate',\n", + " 'pba_consentdate',\n", + " 'pba_complete',\n", + " 'mp_refdate',\n", + " 'mp_consentdate',\n", + " 'mp_complete',\n", + " 'biomarkers_refdate',\n", + " 'biomarkers_consentdate',\n", + " 'biomarkers_complete',\n", + " 'mddetoh_refdate',\n", + " 'mddetoh_consentdate',\n", + " 'mddetoh_complete',\n", + " 'feeding_refdate',\n", + " 'feeding_consentdate',\n", + " 'feeding_complete',\n", + " 'rapa_refdate',\n", + " 'rapa_consentdate',\n", + " 'rapa_complete',\n", + " 'referral_tracking_complete',\n", + " 'appt_date',\n", + " 'appt_age',\n", + " 'staix1_1',\n", + " 'staix1_2',\n", + " 'staix1_3',\n", + " 'staix1_4',\n", + " 'staix1_5',\n", + " 'staix1_6',\n", + " 'staix1_7',\n", + " 'staix1_8',\n", + " 'staix1_9',\n", + " 'staix1_10',\n", + " 'staix1_11',\n", + " 'staix1_12',\n", + " 'staix1_13',\n", + " 'staix1_14',\n", + " 'staix1_15',\n", + " 'staix1_16',\n", + " 'staix1_17',\n", + " 'staix1_18',\n", + " 'staix1_19',\n", + " 'staix1_20',\n", + " 'stai_form_x1_complete',\n", + " 'staix2_1',\n", + " 'staix2_2',\n", + " 'staix2_3',\n", + " 'staix2_4',\n", + " 'staix2_5',\n", + " 'staix2_6',\n", + " 'staix2_7',\n", + " 'staix2_8',\n", + " 'staix2_9',\n", + " 'staix2_10',\n", + " 'staix2_11',\n", + " 'staix2_12',\n", + " 'staix2_13',\n", + " 'staix2_14',\n", + " 'staix2_15',\n", + " 'staix2_16',\n", + " 'staix2_17',\n", + " 'staix2_18',\n", + " 'staix2_19',\n", + " 'staix2_20',\n", + " 'staix2_complete',\n", + " 'bdi_1_sadness',\n", + " 'bdi_2_pessimism',\n", + " 'bdi_3_pastfailure',\n", + " 'bdi_4_lossofpleasure',\n", + " 'bdi_5_guiltyfeelings',\n", + " 'bdi_6_punishmentfeelings',\n", + " 'bdi_7_selfdislike',\n", + " 'bdi_8_selfcriticalness',\n", + " 'bdi_9_suicidalthoughts',\n", + " 'bdi_10_crying',\n", + " 'bdi_11_agitation',\n", + " 'bdi_12_lossofinterest',\n", + " 'bdi_13_indecisiveness',\n", + " 'bdi_14_worthlessness',\n", + " 'bdi_15_lossofenergy',\n", + " 'bdi_16_sleepingpattern',\n", + " 'bdi_17_irritability',\n", + " 'bdi_18_changesinappetite',\n", + " 'bdi_19_concentrationdiff',\n", + " 'bdi_20_tirednessfatigue',\n", + " 'bdi_21_interestinsex',\n", + " 'bdi_total',\n", + " 'bdiii_complete',\n", + " 'pcl5_1',\n", + " 'pcl5_2',\n", + " 'pcl5_3',\n", + " 'pcl5_4',\n", + " 'pcl5_5',\n", + " 'pcl5_6',\n", + " 'pcl5_7',\n", + " 'pcl5_8',\n", + " 'pcl5_9',\n", + " 'pcl5_10',\n", + " 'pcl5_11',\n", + " 'pcl5_12',\n", + " 'pcl5_13',\n", + " 'pcl5_14',\n", + " 'pcl5_15',\n", + " 'pcl5_16',\n", + " 'pcl5_17',\n", + " 'pcl5_18',\n", + " 'pcl5_19',\n", + " 'pcl5_20',\n", + " 'pcl5_total',\n", + " 'pcl5_complete',\n", + " 'scr_psqi_id',\n", + " 'psqi_date',\n", + " 'psqi_1',\n", + " 'psqi_2',\n", + " 'psqi_3',\n", + " 'psqi_4',\n", + " 'psqi_5a',\n", + " 'psqi_5b',\n", + " 'psqi_5c',\n", + " 'psqi_5d',\n", + " 'psqi_5e',\n", + " 'psqi_5f',\n", + " 'psqi_5g',\n", + " 'psqi_5h',\n", + " 'psqi_5i',\n", + " 'psqi_5j',\n", + " 'psqi_5j_desc',\n", + " 'psqi_6',\n", + " 'psqi_7',\n", + " 'psqi_8',\n", + " 'psqi_9',\n", + " 'psqi_10',\n", + " 'psqi_10a',\n", + " 'psqi_10b',\n", + " 'psqi_10c',\n", + " 'psqi_10d',\n", + " 'psqi_10e',\n", + " 'psqi_10e_desc',\n", + " 'psqi_pittsburgh_sleep_quality_index_complete',\n", + " 'scr_qidssr_id',\n", + " 'qidssr_date',\n", + " 'qidssr_1',\n", + " 'qidssr_2',\n", + " 'qidssr_3',\n", + " 'qidssr_4',\n", + " 'qidssr_score1',\n", + " 'qidssr_5',\n", + " 'qidssr_6',\n", + " 'qidssr_7',\n", + " 'qidssr_8',\n", + " 'qidssr_9',\n", + " 'qidssr_score2',\n", + " 'qidssr_10',\n", + " 'qidssr_11',\n", + " 'qidssr_12',\n", + " 'qidssr_13',\n", + " 'qidssr_14',\n", + " 'qidssr_15',\n", + " 'qidssr_16',\n", + " 'qidssr_score3',\n", + " 'qidssr_totalscore',\n", + " 'qidssr_quick_inventory_of_depressive_symptomatolog_complete',\n", + " 'scr_lec_id_5',\n", + " 'scr_lec_date_5',\n", + " 'lec5_1___1',\n", + " 'lec5_1___2',\n", + " 'lec5_1___3',\n", + " 'lec5_1___4',\n", + " 'lec5_1___5',\n", + " 'lec5_1___7777',\n", + " 'lec5_1___9999',\n", + " 'lec5_2___1',\n", + " 'lec5_2___2',\n", + " 'lec5_2___3',\n", + " 'lec5_2___4',\n", + " 'lec5_2___5',\n", + " 'lec5_2___7777',\n", + " 'lec5_2___9999',\n", + " 'lec5_3___1',\n", + " 'lec5_3___2',\n", + " 'lec5_3___3',\n", + " 'lec5_3___4',\n", + " 'lec5_3___5',\n", + " 'lec5_3___7777',\n", + " 'lec5_3___9999',\n", + " 'lec5_4___1',\n", + " 'lec5_4___2',\n", + " 'lec5_4___3',\n", + " 'lec5_4___4',\n", + " 'lec5_4___5',\n", + " 'lec5_4___7777',\n", + " 'lec5_4___9999',\n", + " 'lec5_5___1',\n", + " 'lec5_5___2',\n", + " 'lec5_5___3',\n", + " 'lec5_5___4',\n", + " 'lec5_5___5',\n", + " 'lec5_5___7777',\n", + " 'lec5_5___9999',\n", + " 'lec5_6___1',\n", + " 'lec5_6___2',\n", + " 'lec5_6___3',\n", + " 'lec5_6___4',\n", + " 'lec5_6___5',\n", + " 'lec5_6___7777',\n", + " 'lec5_6___9999',\n", + " 'lec5_7___1',\n", + " 'lec5_7___2',\n", + " 'lec5_7___3',\n", + " 'lec5_7___4',\n", + " 'lec5_7___5',\n", + " 'lec5_7___7777',\n", + " 'lec5_7___9999',\n", + " 'lec5_8___1',\n", + " 'lec5_8___2',\n", + " 'lec5_8___3',\n", + " 'lec5_8___4',\n", + " 'lec5_8___5',\n", + " 'lec5_8___7777',\n", + " 'lec5_8___9999',\n", + " 'lec5_9___1',\n", + " 'lec5_9___2',\n", + " 'lec5_9___3',\n", + " 'lec5_9___4',\n", + " 'lec5_9___5',\n", + " 'lec5_9___7777',\n", + " 'lec5_9___9999',\n", + " 'lec5_10___1',\n", + " 'lec5_10___2',\n", + " 'lec5_10___3',\n", + " 'lec5_10___4',\n", + " 'lec5_10___5',\n", + " 'lec5_10___7777',\n", + " 'lec5_10___9999',\n", + " 'lec5_11___1',\n", + " 'lec5_11___2',\n", + " 'lec5_11___3',\n", + " 'lec5_11___4',\n", + " 'lec5_11___5',\n", + " 'lec5_11___7777',\n", + " 'lec5_11___9999',\n", + " 'lec5_12___1',\n", + " 'lec5_12___2',\n", + " 'lec5_12___3',\n", + " 'lec5_12___4',\n", + " 'lec5_12___5',\n", + " 'lec5_12___7777',\n", + " 'lec5_12___9999',\n", + " 'lec5_13___1',\n", + " 'lec5_13___2',\n", + " 'lec5_13___3',\n", + " 'lec5_13___4',\n", + " 'lec5_13___5',\n", + " 'lec5_13___7777',\n", + " 'lec5_13___9999',\n", + " 'lec5_14___1',\n", + " 'lec5_14___2',\n", + " 'lec5_14___3',\n", + " 'lec5_14___4',\n", + " 'lec5_14___5',\n", + " 'lec5_14___7777',\n", + " 'lec5_14___9999',\n", + " 'lec5_15___1',\n", + " 'lec5_15___2',\n", + " 'lec5_15___3',\n", + " 'lec5_15___4',\n", + " 'lec5_15___5',\n", + " 'lec5_15___7777',\n", + " 'lec5_15___9999',\n", + " 'lec5_16___1',\n", + " 'lec5_16___2',\n", + " 'lec5_16___3',\n", + " 'lec5_16___4',\n", + " 'lec5_16___5',\n", + " 'lec5_16___7777',\n", + " 'lec5_16___9999',\n", + " 'lec5_17___1',\n", + " 'lec5_17___2',\n", + " 'lec5_17___3',\n", + " 'lec5_17___4',\n", + " 'lec5_17___5',\n", + " 'lec5_17___7777',\n", + " 'lec5_17___9999',\n", + " 'lec_notes_5',\n", + " 'lec5_complete',\n", + " 'ftnd_previoussmoking',\n", + " 'ftnd_startage',\n", + " 'ftnd_packnumber',\n", + " 'ftnd_quittingage',\n", + " 'ftnd_timefirstcigarette',\n", + " 'ftnd_refraindifficulty',\n", + " 'ftnd_giveupcigarette',\n", + " 'ftnd_cigqty',\n", + " 'ftnd_smokingfrequency',\n", + " 'ftnd_smokewhenill',\n", + " 'ftnd_complete',\n", + " 'scr_bch_id',\n", + " 'bch_date',\n", + " 'bch_1',\n", + " 'bch_2',\n", + " 'bch_3',\n", + " 'bch_4a',\n", + " 'bch_4b',\n", + " 'bch_5',\n", + " 'bch_6',\n", + " 'bch_7a',\n", + " 'bch_7b',\n", + " 'bch_8',\n", + " 'bch_9a',\n", + " 'bch_9b',\n", + " 'bch_baseline_consumption_history_complete',\n", + " 'scr_ces_id',\n", + " 'ces_vet',\n", + " 'ces_combat',\n", + " 'ces_date',\n", + " 'ces_1',\n", + " 'ces_2',\n", + " 'ces_3',\n", + " 'ces_4',\n", + " 'ces_5',\n", + " 'ces_6',\n", + " ...]" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "## read pcl scores\n", + "pclDf = pd.read_csv('/home/or/Documents/kpe_analyses/KPEIHR0009_DATA_2020-08-13_1339.csv')\n", + "# take only KPE patients\n", + "pclDf = pclDf[pclDf['scr_id'].str.startswith('KPE')]\n", + "list(pclDf.columns)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "dfP = pd.DataFrame({'subject': pclDf['scr_id']})\n", + "dfP_PCL = pclDf[['scr_id','redcap_event_name','pcl5_1', 'pcl5_2', 'pcl5_3', 'pcl5_4', 'pcl5_5', 'pcl5_6', 'pcl5_7',\n", + " 'pcl5_8', 'pcl5_9', 'pcl5_10', 'pcl5_11', 'pcl5_12', 'pcl5_13', 'pcl5_14', 'pcl5_15', 'pcl5_16', 'pcl5_17',\n", + " 'pcl5_18', 'pcl5_19', 'pcl5_20']]\n", + "# remove NAs\n", + "dfP_PCL = dfP_PCL.dropna()\n", + "# set list of columns for analysis\n", + "colList = list(dfP_PCL)\n", + "colList.remove('scr_id')\n", + "colList.remove('redcap_event_name')\n", + "# set total pcl scores \n", + "dfP_PCL['pclTotal'] = dfP_PCL[colList].sum(axis=1)\n", + "sns.distplot(dfP_PCL.pclTotal)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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redcap_event_name30Days90DaysScreeningVisit1Visit7
scr_id
KPE 1237NaNNaN60.0NaNNaN
KPE 141920.0NaN23.036.041.0
KPE 1560NaNNaN77.0NaNNaN
KPE 157321.053.039.048.016.0
KPE 1574NaNNaN37.0NaNNaN
..................
KPE1611NaNNaN28.0NaNNaN
KPE1612NaNNaN47.0NaNNaN
KPE1613NaNNaN57.0NaNNaN
KPE1615NaNNaN51.0NaNNaN
KPE1616NaNNaN23.0NaNNaN
\n", + "

87 rows × 5 columns

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" + ], + "text/plain": [ + "redcap_event_name 30Days 90Days Screening Visit1 Visit7\n", + "scr_id \n", + "KPE 1237 NaN NaN 60.0 NaN NaN\n", + "KPE 1419 20.0 NaN 23.0 36.0 41.0\n", + "KPE 1560 NaN NaN 77.0 NaN NaN\n", + "KPE 1573 21.0 53.0 39.0 48.0 16.0\n", + "KPE 1574 NaN NaN 37.0 NaN NaN\n", + "... ... ... ... ... ...\n", + "KPE1611 NaN NaN 28.0 NaN NaN\n", + "KPE1612 NaN NaN 47.0 NaN NaN\n", + "KPE1613 NaN NaN 57.0 NaN NaN\n", + "KPE1615 NaN NaN 51.0 NaN NaN\n", + "KPE1616 NaN NaN 23.0 NaN NaN\n", + "\n", + "[87 rows x 5 columns]" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# reshape it to wide\n", + "df2=dfP_PCL.pivot(index = 'scr_id',columns='redcap_event_name', values='pclTotal')\n", + "list(df2)\n", + "df2 = df2.rename(columns={\"30_day_follow_up_s_arm_1\": \"30Days\", \"90_day_follow_up_s_arm_1\": \"90Days\",\n", + " \"screening_selfrepo_arm_1\": \"Screening\", \"visit_1_arm_1\": \"Visit1\", \n", + " \"visit_7_week_follo_arm_1\": \"Visit7\"})\n", + "#df2['scr_id'] = dfP_PCL['scr_id']\n", + "df2" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Nan\n", + "68.0\n", + "Nan\n", + "32.0\n", + "Nan\n", + "38.0\n", + "Nan\n", + "35.0\n" + ] + }, + { + "data": { + "text/html": [ + "
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scr_idgroupmeanActgroupIdxvmPFChippostriatumAc30Days90DaysScreeningVisit1Visit7days30_1days30_sVisit7_1
0KPE008ketamine3.1901201-0.072546-5.5291552.48344856.049.0NaN58.061.0-2.0NaN3.0
1KPE1223ketamine12.91250219.66234818.528749-10.18174342.049.039.041.050.01.03.09.0
2KPE1253midazolam-17.4411030-7.129313-1.235472-26.71046833.0NaN58.063.058.0-30.0-25.0-5.0
3KPE1263midazolam12.12987208.88953821.97941029.35497937.034.021.054.056.0-17.016.02.0
4KPE1293ketamine-20.2331181-7.122487-19.774799-12.4047258.03.033.036.06.0-28.0-25.0-30.0
5KPE1307ketamine-52.2213101-29.786623-28.613234-9.51682045.020.0NaN49.041.0-4.0NaN-8.0
6KPE1315ketamine5.8963841-1.910045-2.230514-5.855117NaNNaN40.038.08.0NaNNaN-30.0
7KPE1322ketamine13.528724133.13494111.50446113.14192338.027.0NaN56.022.0-18.0NaN-34.0
8KPE1339ketamine-3.3691651-1.105649-3.718665-32.74070446.067.068.068.065.0-22.0-22.0-3.0
9KPE1343ketamine-65.0852201-11.860424-50.98640128.12585620.019.032.038.020.0-18.0-12.0-18.0
10KPE1351midazolam-18.5520020-25.503946-44.4484714.39323433.025.0NaN43.026.0-10.0NaN-17.0
11KPE1356midazolam30.8837200-14.83609713.315349-1.92648352.0NaN61.063.056.0-11.0-9.0-7.0
12KPE1364midazolam56.474892016.96603445.53267345.82691249.052.048.051.042.0-2.01.0-9.0
13KPE1369midazolam26.3963910-45.5105096.881987-45.61096648.049.055.052.031.0-4.0-7.0-21.0
14KPE1387ketamine-13.5788521-11.315875-3.810227-4.81110848.039.032.032.046.016.016.014.0
15KPE1390midazolam7.84772801.090048-3.209616-25.8513576.025.038.038.021.0-32.0-32.0-17.0
16KPE1403midazolam2.05465807.03655725.67226611.8066904.08.017.012.03.0-8.0-13.0-9.0
17KPE1464ketamine-31.1857321-23.971344-56.4882518.19493121.031.035.035.014.0-14.0-14.0-21.0
18KPE1468midazolam27.22140100.56069622.786213-65.921585NaN9.028.029.029.0NaNNaN0.0
19KPE1480midazolam12.215979025.966124-12.630979-19.501911NaN27.031.030.034.0NaNNaN4.0
20KPE1499ketamine-53.8379101-47.302711-29.856201-18.45126241.0NaN44.064.0NaN-23.0-3.0NaN
21KPE1561midazolam23.159636010.8377893.59905016.30591618.013.057.048.018.0-30.0-39.0-30.0
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" + ], + "text/plain": [ + " scr_id group meanAct groupIdx vmPFC hippo striatumAc \\\n", + "0 KPE008 ketamine 3.190120 1 -0.072546 -5.529155 2.483448 \n", + "1 KPE1223 ketamine 12.912502 1 9.662348 18.528749 -10.181743 \n", + "2 KPE1253 midazolam -17.441103 0 -7.129313 -1.235472 -26.710468 \n", + "3 KPE1263 midazolam 12.129872 0 8.889538 21.979410 29.354979 \n", + "4 KPE1293 ketamine -20.233118 1 -7.122487 -19.774799 -12.404725 \n", + "5 KPE1307 ketamine -52.221310 1 -29.786623 -28.613234 -9.516820 \n", + "6 KPE1315 ketamine 5.896384 1 -1.910045 -2.230514 -5.855117 \n", + "7 KPE1322 ketamine 13.528724 1 33.134941 11.504461 13.141923 \n", + "8 KPE1339 ketamine -3.369165 1 -1.105649 -3.718665 -32.740704 \n", + "9 KPE1343 ketamine -65.085220 1 -11.860424 -50.986401 28.125856 \n", + "10 KPE1351 midazolam -18.552002 0 -25.503946 -44.448471 4.393234 \n", + "11 KPE1356 midazolam 30.883720 0 -14.836097 13.315349 -1.926483 \n", + "12 KPE1364 midazolam 56.474892 0 16.966034 45.532673 45.826912 \n", + "13 KPE1369 midazolam 26.396391 0 -45.510509 6.881987 -45.610966 \n", + "14 KPE1387 ketamine -13.578852 1 -11.315875 -3.810227 -4.811108 \n", + "15 KPE1390 midazolam 7.847728 0 1.090048 -3.209616 -25.851357 \n", + "16 KPE1403 midazolam 2.054658 0 7.036557 25.672266 11.806690 \n", + "17 KPE1464 ketamine -31.185732 1 -23.971344 -56.488251 8.194931 \n", + "18 KPE1468 midazolam 27.221401 0 0.560696 22.786213 -65.921585 \n", + "19 KPE1480 midazolam 12.215979 0 25.966124 -12.630979 -19.501911 \n", + "20 KPE1499 ketamine -53.837910 1 -47.302711 -29.856201 -18.451262 \n", + "21 KPE1561 midazolam 23.159636 0 10.837789 3.599050 16.305916 \n", + "\n", + " 30Days 90Days Screening Visit1 Visit7 days30_1 days30_s Visit7_1 \n", + "0 56.0 49.0 NaN 58.0 61.0 -2.0 NaN 3.0 \n", + "1 42.0 49.0 39.0 41.0 50.0 1.0 3.0 9.0 \n", + "2 33.0 NaN 58.0 63.0 58.0 -30.0 -25.0 -5.0 \n", + "3 37.0 34.0 21.0 54.0 56.0 -17.0 16.0 2.0 \n", + "4 8.0 3.0 33.0 36.0 6.0 -28.0 -25.0 -30.0 \n", + "5 45.0 20.0 NaN 49.0 41.0 -4.0 NaN -8.0 \n", + "6 NaN NaN 40.0 38.0 8.0 NaN NaN -30.0 \n", + "7 38.0 27.0 NaN 56.0 22.0 -18.0 NaN -34.0 \n", + "8 46.0 67.0 68.0 68.0 65.0 -22.0 -22.0 -3.0 \n", + "9 20.0 19.0 32.0 38.0 20.0 -18.0 -12.0 -18.0 \n", + "10 33.0 25.0 NaN 43.0 26.0 -10.0 NaN -17.0 \n", + "11 52.0 NaN 61.0 63.0 56.0 -11.0 -9.0 -7.0 \n", + "12 49.0 52.0 48.0 51.0 42.0 -2.0 1.0 -9.0 \n", + "13 48.0 49.0 55.0 52.0 31.0 -4.0 -7.0 -21.0 \n", + "14 48.0 39.0 32.0 32.0 46.0 16.0 16.0 14.0 \n", + "15 6.0 25.0 38.0 38.0 21.0 -32.0 -32.0 -17.0 \n", + "16 4.0 8.0 17.0 12.0 3.0 -8.0 -13.0 -9.0 \n", + "17 21.0 31.0 35.0 35.0 14.0 -14.0 -14.0 -21.0 \n", + "18 NaN 9.0 28.0 29.0 29.0 NaN NaN 0.0 \n", + "19 NaN 27.0 31.0 30.0 34.0 NaN NaN 4.0 \n", + "20 41.0 NaN 44.0 64.0 NaN -23.0 -3.0 NaN \n", + "21 18.0 13.0 57.0 48.0 18.0 -30.0 -39.0 -30.0 " + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# merging two data frames toghether\n", + "dfTest = pd.merge(df, df2, on = 'scr_id')\n", + "# change visit1 missing values with screening values\n", + "for i in dfTest.iterrows():\n", + " if np.isnan(i[1].Visit1):\n", + " print(\"Nan\")\n", + " print(i[1].Screening)\n", + " dfTest.at[i[0], 'Visit1']= i[1].Screening\n", + "\n", + "# create difference pcl score\n", + "dfTest['days30_1'] = dfTest['30Days'] - dfTest.Visit1\n", + "dfTest['days30_s'] = dfTest['30Days'] - dfTest.Screening\n", + "dfTest['Visit7_1'] = dfTest['Visit7'] - dfTest.Visit1\n", + "dfTest" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(0.16719689115364295, 0.4688204670021354)" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.lmplot(x='Visit7', y='meanAct',hue='group', data=dfTest)\n", + "xMask = np.isnan(dfTest['Visit7'])\n", + "yMask = np.isnan(dfTest['meanAct'])\n", + "nas = np.logical_or(xMask, yMask)\n", + "scipy.stats.pearsonr(dfTest['Visit7'][~nas],dfTest['meanAct'][~nas])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Test difference in amygdala activation between 1st and2nd session and see if it correlates to symtpoms\n", + "dfTest['amg_ses2_ses1'] = dfTest.meanAct - df_ses1.meanAct_ses1" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "ename": "KeyError", + "evalue": "\"['amg_ses2_ses1'] not in index\"", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlmplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'amg_ses2_ses1'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Visit7_1'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mhue\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'group'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdfTest\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mxMask\u001b[0m \u001b[0;34m=\u001b[0m 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x_partial, y_partial, truncate, x_jitter, y_jitter, scatter_kws, line_kws, size)\u001b[0m\n\u001b[1;32m 549\u001b[0m \u001b[0mneed_cols\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcol\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrow\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0munits\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx_partial\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_partial\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 550\u001b[0m \u001b[0mcols\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0ma\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0ma\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mneed_cols\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0ma\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m 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\u001b[0mis_iterator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2904\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2905\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_listlike_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mraise_missing\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2906\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2907\u001b[0m \u001b[0;31m# take() does not accept boolean indexers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_get_listlike_indexer\u001b[0;34m(self, key, axis, raise_missing)\u001b[0m\n\u001b[1;32m 1252\u001b[0m \u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnew_indexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reindex_non_unique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1253\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1254\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_read_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mraise_missing\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mraise_missing\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1255\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1256\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_validate_read_indexer\u001b[0;34m(self, key, indexer, axis, raise_missing)\u001b[0m\n\u001b[1;32m 1302\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mraise_missing\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1303\u001b[0m \u001b[0mnot_found\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1304\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"{not_found} not in index\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1305\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1306\u001b[0m \u001b[0;31m# we skip the warning on Categorical\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mKeyError\u001b[0m: \"['amg_ses2_ses1'] not in index\"" + ] + } + ], + "source": [ + "sns.lmplot(x='amg_ses2_ses1', y='Visit7_1',hue='group', data=dfTest)\n", + "xMask = np.isnan(dfTest['Visit7_1'])\n", + "yMask = np.isnan(dfTest['amg_ses2_ses1'])\n", + "nas = np.logical_or(xMask, yMask)\n", + "scipy.stats.pearsonr(dfTest['Visit7_1'][~nas],dfTest['amg_ses2_ses1'][~nas])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "### So - change in Hippocampus reactivation to trauma script (vs. relax) is correlated to changes symptoms at end of treatment\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "dfTest" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# lets test correlation per group (although this is a very ver\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "dfTest.corr()\n", + "#sns.heatmap(dfTest)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.figure(figsize=(20,10))\n", + "sns.heatmap(dfTest[dfTest.group==0].corr(), annot=True, cmap=\"coolwarm\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "X = dfTest[['meanAct','hippo', 'group']]\n", + "y = dfTest['days30_1']\n", + "\n", + "X = sm.add_constant(X)\n", + "est = sm.OLS(y, X, missing='drop').fit()\n", + "est.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "smOLS = smf.ols(formula='days30_1 ~ group * meanAct', data=dfTest).fit()\n", + "\n", + "smOLS.summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Check correlation with SCR" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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scr_idpeakTrauma1T_R1T_R2T_R3peakTrauma1_ses2T_R1_ses2T_R2_ses2T_R3_ses2TR1_2vs1Trauma_2vs1
0KPE0080.0084090.0014380.0010530.0012520.0292880.000477-0.001506-0.001410-0.0009610.020879
1KPE12230.7800290.7179680.3842210.1007180.5839720.2592390.4581510.007750-0.458729-0.196057
2KPE12530.2651860.2410930.0038400.0036280.0355200.000500-0.136277-0.029247-0.240594-0.229666
3KPE12630.086110-0.0043090.0133070.0204220.2159770.0022320.0035470.0036620.0065410.129867
4KPE12930.1266890.110741-0.071293-0.0149220.2666110.082697-0.064094-0.000251-0.0280440.139922
5KPE13070.0042070.0029100.0000290.0001450.0015690.0002220.0004910.000080-0.002688-0.002638
6KPE13150.1382200.126930-0.1235480.0141240.036497-0.0071580.068810-0.036000-0.134087-0.101723
7KPE13220.001624-0.0007760.0021790.0006280.001706-0.000454-0.0021710.0006960.0003230.000082
8KPE13390.4076560.299639-1.047222-0.0544000.0596000.060571-0.000934-0.017752-0.239068-0.348056
9KPE13430.280073-0.3577240.2122290.0847770.0112590.013012-0.129134-0.1013470.370736-0.268814
10KPE13510.0012340.0002890.0009490.0000560.0013060.000073-0.000262-0.000178-0.0002160.000071
11KPE13560.0526880.1362330.0368900.1052372.1105621.1310810.127063-1.5126810.9948492.057874
12KPE13640.9152330.426590-0.5168200.5661762.0489610.7818411.7864411.3698940.3552511.133728
13KPE13690.001491-0.0003690.0001480.0002890.0076370.006719-0.0010520.0037520.0070880.006146
14KPE13870.0879180.0772120.024198-0.0044630.005663-0.0079240.0089430.004053-0.085136-0.082256
15KPE13900.2988180.0182930.0263660.0866840.4990080.3720150.033121-0.2040800.3537210.200190
16KPE1403-0.001133-0.012253-0.004849-0.0050900.3607190.327673-0.007846-0.0025750.3399260.361852
17KPE14640.9467520.773722-0.055203-0.0071440.5718200.290042-0.471218-1.376700-0.483680-0.374932
18KPE14680.0025840.0011630.0005990.0005260.000673-0.002864-0.0008470.001938-0.004027-0.001911
19KPE14800.5279920.548514-0.0261750.1688360.080483-0.129895-0.005818-2.657530-0.678408-0.447508
20KPE14990.0658990.043608-0.002630-0.0020660.000996-0.0000950.0002290.001317-0.043703-0.064903
\n", + "
" + ], + "text/plain": [ + " scr_id peakTrauma1 T_R1 T_R2 T_R3 peakTrauma1_ses2 \\\n", + "0 KPE008 0.008409 0.001438 0.001053 0.001252 0.029288 \n", + "1 KPE1223 0.780029 0.717968 0.384221 0.100718 0.583972 \n", + "2 KPE1253 0.265186 0.241093 0.003840 0.003628 0.035520 \n", + "3 KPE1263 0.086110 -0.004309 0.013307 0.020422 0.215977 \n", + "4 KPE1293 0.126689 0.110741 -0.071293 -0.014922 0.266611 \n", + "5 KPE1307 0.004207 0.002910 0.000029 0.000145 0.001569 \n", + "6 KPE1315 0.138220 0.126930 -0.123548 0.014124 0.036497 \n", + "7 KPE1322 0.001624 -0.000776 0.002179 0.000628 0.001706 \n", + "8 KPE1339 0.407656 0.299639 -1.047222 -0.054400 0.059600 \n", + "9 KPE1343 0.280073 -0.357724 0.212229 0.084777 0.011259 \n", + "10 KPE1351 0.001234 0.000289 0.000949 0.000056 0.001306 \n", + "11 KPE1356 0.052688 0.136233 0.036890 0.105237 2.110562 \n", + "12 KPE1364 0.915233 0.426590 -0.516820 0.566176 2.048961 \n", + "13 KPE1369 0.001491 -0.000369 0.000148 0.000289 0.007637 \n", + "14 KPE1387 0.087918 0.077212 0.024198 -0.004463 0.005663 \n", + "15 KPE1390 0.298818 0.018293 0.026366 0.086684 0.499008 \n", + "16 KPE1403 -0.001133 -0.012253 -0.004849 -0.005090 0.360719 \n", + "17 KPE1464 0.946752 0.773722 -0.055203 -0.007144 0.571820 \n", + "18 KPE1468 0.002584 0.001163 0.000599 0.000526 0.000673 \n", + "19 KPE1480 0.527992 0.548514 -0.026175 0.168836 0.080483 \n", + "20 KPE1499 0.065899 0.043608 -0.002630 -0.002066 0.000996 \n", + "\n", + " T_R1_ses2 T_R2_ses2 T_R3_ses2 TR1_2vs1 Trauma_2vs1 \n", + "0 0.000477 -0.001506 -0.001410 -0.000961 0.020879 \n", + "1 0.259239 0.458151 0.007750 -0.458729 -0.196057 \n", + "2 0.000500 -0.136277 -0.029247 -0.240594 -0.229666 \n", + "3 0.002232 0.003547 0.003662 0.006541 0.129867 \n", + "4 0.082697 -0.064094 -0.000251 -0.028044 0.139922 \n", + "5 0.000222 0.000491 0.000080 -0.002688 -0.002638 \n", + "6 -0.007158 0.068810 -0.036000 -0.134087 -0.101723 \n", + "7 -0.000454 -0.002171 0.000696 0.000323 0.000082 \n", + "8 0.060571 -0.000934 -0.017752 -0.239068 -0.348056 \n", + "9 0.013012 -0.129134 -0.101347 0.370736 -0.268814 \n", + "10 0.000073 -0.000262 -0.000178 -0.000216 0.000071 \n", + "11 1.131081 0.127063 -1.512681 0.994849 2.057874 \n", + "12 0.781841 1.786441 1.369894 0.355251 1.133728 \n", + "13 0.006719 -0.001052 0.003752 0.007088 0.006146 \n", + "14 -0.007924 0.008943 0.004053 -0.085136 -0.082256 \n", + "15 0.372015 0.033121 -0.204080 0.353721 0.200190 \n", + "16 0.327673 -0.007846 -0.002575 0.339926 0.361852 \n", + "17 0.290042 -0.471218 -1.376700 -0.483680 -0.374932 \n", + "18 -0.002864 -0.000847 0.001938 -0.004027 -0.001911 \n", + "19 -0.129895 -0.005818 -2.657530 -0.678408 -0.447508 \n", + "20 -0.000095 0.000229 0.001317 -0.043703 -0.064903 " + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "scr = pd.read_csv('/home/or/kpe_task_analysis/scr_deltas.csv')\n", + "scr1 = scr.drop(columns = ['med_cond', 'groupIdx'])\n", + "scr1" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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scr_idgroupmeanActgroupIdxpeakTrauma1T_R1T_R2T_R3peakTrauma1_ses2T_R1_ses2T_R2_ses2T_R3_ses2TR1_2vs1Trauma_2vs1
0KPE008ketamine3.19012010.0084090.0014380.0010530.0012520.0292880.000477-0.001506-0.001410-0.0009610.020879
1KPE1223ketamine12.91250210.7800290.7179680.3842210.1007180.5839720.2592390.4581510.007750-0.458729-0.196057
2KPE1253midazolam-17.44110300.2651860.2410930.0038400.0036280.0355200.000500-0.136277-0.029247-0.240594-0.229666
3KPE1263midazolam12.12987200.086110-0.0043090.0133070.0204220.2159770.0022320.0035470.0036620.0065410.129867
4KPE1293ketamine-20.23311810.1266890.110741-0.071293-0.0149220.2666110.082697-0.064094-0.000251-0.0280440.139922
5KPE1307ketamine-52.22131010.0042070.0029100.0000290.0001450.0015690.0002220.0004910.000080-0.002688-0.002638
6KPE1315ketamine5.89638410.1382200.126930-0.1235480.0141240.036497-0.0071580.068810-0.036000-0.134087-0.101723
7KPE1322ketamine13.52872410.001624-0.0007760.0021790.0006280.001706-0.000454-0.0021710.0006960.0003230.000082
8KPE1339ketamine-3.36916510.4076560.299639-1.047222-0.0544000.0596000.060571-0.000934-0.017752-0.239068-0.348056
9KPE1343ketamine-65.08522010.280073-0.3577240.2122290.0847770.0112590.013012-0.129134-0.1013470.370736-0.268814
10KPE1351midazolam-18.55200200.0012340.0002890.0009490.0000560.0013060.000073-0.000262-0.000178-0.0002160.000071
11KPE1356midazolam30.88372000.0526880.1362330.0368900.1052372.1105621.1310810.127063-1.5126810.9948492.057874
12KPE1364midazolam56.47489200.9152330.426590-0.5168200.5661762.0489610.7818411.7864411.3698940.3552511.133728
13KPE1369midazolam26.39639100.001491-0.0003690.0001480.0002890.0076370.006719-0.0010520.0037520.0070880.006146
14KPE1387ketamine-13.57885210.0879180.0772120.024198-0.0044630.005663-0.0079240.0089430.004053-0.085136-0.082256
15KPE1390midazolam7.84772800.2988180.0182930.0263660.0866840.4990080.3720150.033121-0.2040800.3537210.200190
16KPE1403midazolam2.0546580-0.001133-0.012253-0.004849-0.0050900.3607190.327673-0.007846-0.0025750.3399260.361852
17KPE1464ketamine-31.18573210.9467520.773722-0.055203-0.0071440.5718200.290042-0.471218-1.376700-0.483680-0.374932
18KPE1468midazolam27.22140100.0025840.0011630.0005990.0005260.000673-0.002864-0.0008470.001938-0.004027-0.001911
19KPE1480midazolam12.21597900.5279920.548514-0.0261750.1688360.080483-0.129895-0.005818-2.657530-0.678408-0.447508
20KPE1499ketamine-53.83791010.0658990.043608-0.002630-0.0020660.000996-0.0000950.0002290.001317-0.043703-0.064903
\n", + "
" + ], + "text/plain": [ + " scr_id group meanAct groupIdx peakTrauma1 T_R1 T_R2 \\\n", + "0 KPE008 ketamine 3.190120 1 0.008409 0.001438 0.001053 \n", + "1 KPE1223 ketamine 12.912502 1 0.780029 0.717968 0.384221 \n", + "2 KPE1253 midazolam -17.441103 0 0.265186 0.241093 0.003840 \n", + "3 KPE1263 midazolam 12.129872 0 0.086110 -0.004309 0.013307 \n", + "4 KPE1293 ketamine -20.233118 1 0.126689 0.110741 -0.071293 \n", + "5 KPE1307 ketamine -52.221310 1 0.004207 0.002910 0.000029 \n", + "6 KPE1315 ketamine 5.896384 1 0.138220 0.126930 -0.123548 \n", + "7 KPE1322 ketamine 13.528724 1 0.001624 -0.000776 0.002179 \n", + "8 KPE1339 ketamine -3.369165 1 0.407656 0.299639 -1.047222 \n", + "9 KPE1343 ketamine -65.085220 1 0.280073 -0.357724 0.212229 \n", + "10 KPE1351 midazolam -18.552002 0 0.001234 0.000289 0.000949 \n", + "11 KPE1356 midazolam 30.883720 0 0.052688 0.136233 0.036890 \n", + "12 KPE1364 midazolam 56.474892 0 0.915233 0.426590 -0.516820 \n", + "13 KPE1369 midazolam 26.396391 0 0.001491 -0.000369 0.000148 \n", + "14 KPE1387 ketamine -13.578852 1 0.087918 0.077212 0.024198 \n", + "15 KPE1390 midazolam 7.847728 0 0.298818 0.018293 0.026366 \n", + "16 KPE1403 midazolam 2.054658 0 -0.001133 -0.012253 -0.004849 \n", + "17 KPE1464 ketamine -31.185732 1 0.946752 0.773722 -0.055203 \n", + "18 KPE1468 midazolam 27.221401 0 0.002584 0.001163 0.000599 \n", + "19 KPE1480 midazolam 12.215979 0 0.527992 0.548514 -0.026175 \n", + "20 KPE1499 ketamine -53.837910 1 0.065899 0.043608 -0.002630 \n", + "\n", + " T_R3 peakTrauma1_ses2 T_R1_ses2 T_R2_ses2 T_R3_ses2 TR1_2vs1 \\\n", + "0 0.001252 0.029288 0.000477 -0.001506 -0.001410 -0.000961 \n", + "1 0.100718 0.583972 0.259239 0.458151 0.007750 -0.458729 \n", + "2 0.003628 0.035520 0.000500 -0.136277 -0.029247 -0.240594 \n", + "3 0.020422 0.215977 0.002232 0.003547 0.003662 0.006541 \n", + "4 -0.014922 0.266611 0.082697 -0.064094 -0.000251 -0.028044 \n", + "5 0.000145 0.001569 0.000222 0.000491 0.000080 -0.002688 \n", + "6 0.014124 0.036497 -0.007158 0.068810 -0.036000 -0.134087 \n", + "7 0.000628 0.001706 -0.000454 -0.002171 0.000696 0.000323 \n", + "8 -0.054400 0.059600 0.060571 -0.000934 -0.017752 -0.239068 \n", + "9 0.084777 0.011259 0.013012 -0.129134 -0.101347 0.370736 \n", + "10 0.000056 0.001306 0.000073 -0.000262 -0.000178 -0.000216 \n", + "11 0.105237 2.110562 1.131081 0.127063 -1.512681 0.994849 \n", + "12 0.566176 2.048961 0.781841 1.786441 1.369894 0.355251 \n", + "13 0.000289 0.007637 0.006719 -0.001052 0.003752 0.007088 \n", + "14 -0.004463 0.005663 -0.007924 0.008943 0.004053 -0.085136 \n", + "15 0.086684 0.499008 0.372015 0.033121 -0.204080 0.353721 \n", + "16 -0.005090 0.360719 0.327673 -0.007846 -0.002575 0.339926 \n", + "17 -0.007144 0.571820 0.290042 -0.471218 -1.376700 -0.483680 \n", + "18 0.000526 0.000673 -0.002864 -0.000847 0.001938 -0.004027 \n", + "19 0.168836 0.080483 -0.129895 -0.005818 -2.657530 -0.678408 \n", + "20 -0.002066 0.000996 -0.000095 0.000229 0.001317 -0.043703 \n", + "\n", + " Trauma_2vs1 \n", + "0 0.020879 \n", + "1 -0.196057 \n", + "2 -0.229666 \n", + "3 0.129867 \n", + "4 0.139922 \n", + "5 -0.002638 \n", + "6 -0.101723 \n", + "7 0.000082 \n", + "8 -0.348056 \n", + "9 -0.268814 \n", + "10 0.000071 \n", + "11 2.057874 \n", + "12 1.133728 \n", + "13 0.006146 \n", + "14 -0.082256 \n", + "15 0.200190 \n", + "16 0.361852 \n", + "17 -0.374932 \n", + "18 -0.001911 \n", + "19 -0.447508 \n", + "20 -0.064903 " + ] + }, + "execution_count": 62, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dfMerge = pd.merge(df, scr1)\n", + "dfMerge" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.lmplot(x = 'Trauma_2vs1', y= 'meanAct',hue = 'group', data=dfMerge)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "smOLS = smf.ols(formula='Trauma_2vs1 ~ group * meanAct', data=dfMerge).fit()\n", + "\n", + "smOLS.summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Check changes in amg activation and SCR / PCL" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'df_ses1' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdfMerge\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'amg_2_1'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdfMerge\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmeanAct\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mdf_ses1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmeanAct_ses1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;31mNameError\u001b[0m: name 'df_ses1' is not defined" + ] + } + ], + "source": [ + "dfMerge['amg_2_1'] = dfMerge.meanAct - df_ses1.meanAct_ses1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.lmplot(x='Trauma_2vs1', y = 'amg_2_1', hue='group', data=dfMerge)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "smOLS = smf.ols(formula='Trauma_2vs1 ~ group * amg_2_1', data=dfMerge).fit()\n", + "\n", + "smOLS.summary()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/.ipynb_checkpoints/average_Comp_ROIs_DiFuMo-checkpoint.ipynb b/task_based_analysis/.ipynb_checkpoints/average_Comp_ROIs_DiFuMo-checkpoint.ipynb new file mode 100644 index 0000000..6bd9d52 --- /dev/null +++ b/task_based_analysis/.ipynb_checkpoints/average_Comp_ROIs_DiFuMo-checkpoint.ipynb @@ -0,0 +1,2299 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Comparing Ketamine and Midazolam after treatment in ROIs\n", + "- focus on end of treatment\n", + "- Amygdala\n", + "- vmPFC\n", + "- Hippocampus" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# import relevant packages\n", + "import glob\n", + "import numpy as np\n", + "import scipy\n", + "import nilearn\n", + "import nilearn.image\n", + "import nilearn.plotting\n", + "import nilearn.input_data\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import pandas as pd\n", + "import pymc3 as pm\n", + "import arviz as az\n", + "import dask\n", + "import statsmodels.api as sm\n", + "import statsmodels.formula.api as smf" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_008/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1223/modelestimate/results/cope7.nii.gz',\n", 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'/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1339/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1343/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1351/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1356/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1364/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1369/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1387/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1390/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1403/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1419/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1464/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1468/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1480/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1499/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1561/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1573/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1578/modelestimate/results/cope7.nii.gz']" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Set session\n", + "ses = 1\n", + "## Grab group\n", + "# compare between groups\n", + "\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "scr_id = medication_cond.scr_id\n", + "func_files = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses%s/modelfit/_subject_id_*/modelestimate/results/cope7.nii.gz' %(ses))\n", + "#func_files = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/allScript_ses%s/modelfit_ses_%s/_subject_id_*/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz' %(ses, ses))\n", + "\n", + "func_files.sort()\n", + "func_files" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 KPE008\n", + "1 KPE1223\n", + "2 KPE1253\n", + "3 KPE1263\n", + "4 KPE1293\n", + "5 KPE1307\n", + "6 KPE1315\n", + "7 KPE1322\n", + "8 KPE1339\n", + "9 KPE1343\n", + "10 KPE1351\n", + "11 KPE1356\n", + "12 KPE1364\n", + "13 KPE1369\n", + "14 KPE1387\n", + "15 KPE1390\n", + "16 KPE1403\n", + "17 KPE1419\n", + "18 KPE1464\n", + "19 KPE1468\n", + "20 KPE1480\n", + "21 KPE1499\n", + "22 KPE1561\n", + "23 KPE1573\n", + "24 KPE1578\n", + "Name: scr_id, dtype: object" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "scr_id" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/plotting/displays.py:99: UserWarning: No contour levels were found within the data range.\n", + " **kwargs)\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "maps_img = '/media/Data/work/DiFuMo_atlas/256/maps.nii.gz'\n", + "labels = pd.read_csv('/media/Data/work/DiFuMo_atlas/256/labels_256_dictionary.csv')\n", + "#coords = nilearn.plotting.find_parcellation_cut_coords(labels_img=maps_img)\n", + "#coords = nilearn.plotting.find_probabilistic_atlas_cut_coords(maps_img)\n", + "# plot atlas (only if we want)\n", + "nilearn.plotting.plot_prob_atlas(maps_img, draw_cross=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMapsMasker.fit] loading regions from /media/Data/work/DiFuMo_atlas/256/maps.nii.gz\n" + ] + } + ], + "source": [ + "masker = nilearn.input_data.NiftiMapsMasker(maps_img=maps_img, \n", + " verbose=2, standardize=True).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Resampling maps\n", + "[NiftiMapsMasker.transform_single_imgs] Loading data from [/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_008/modelestimate/results/cope7.nii.gz, /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimagin\n", + "[NiftiMapsMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "t_maps1 = masker.transform(func_files)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(24, 256)" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "t_maps2.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "# extract relevant ROIs (vmpfc, hippo, amygdala)\n", + "labels_list = list(labels.Difumo_names)\n", + "amg = labels_list.index('Amygdala')\n", + "hippo_post = labels_list.index('Hippocampus posterior')\n", + "hippo_ant = labels_list.index('Hippocampus anterior')\n", + "vmPFC_ant = labels_list.index('Ventromedial prefrontal cortex anterior')\n", + "vmPFC = labels_list.index('Ventromedial prefrontal cortex')\n", + "index_list = np.array([amg, hippo_post, hippo_ant, vmPFC_ant, vmPFC])" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(25, 5)" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ses1_ROIs = t_maps1[: ,index_list]\n", + "ses1_ROIs.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(24, 5)" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ses2_ROIs = t_maps2[: ,index_list]\n", + "ses2_ROIs.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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scr_idgroupamghippoposthippoAntvmPFC_antvmPFC
0KPE008ketamine-0.465222-0.6887740.5386160.3373280.128000
1KPE1223ketamine0.8566790.5219090.6139980.7743750.589104
2KPE1253midazolam1.023002-0.386011-0.834792-1.1725101.470069
3KPE1263midazolam0.603694-0.5065580.7636010.7461350.560564
4KPE1293ketamine-0.553164-0.309508-0.3972730.297633-0.358259
5KPE1307ketamine-2.318977-0.597950-0.118689-0.990741-1.934913
6KPE1315ketamine0.1948920.001936-0.1152150.2535060.504973
7KPE1322ketamine0.2993611.2671630.4924071.5401141.670747
8KPE1339ketamine-0.516204-0.0038740.5185290.939097-0.079983
9KPE1343ketamine-2.330085-0.823191-1.347205-0.5243860.089253
10KPE1351midazolam-0.763579-0.965045-2.526727-1.078393-0.504770
11KPE1356midazolam1.3543951.352217-0.1055370.108860-1.305680
12KPE1364midazolam1.6132862.6619802.2642930.5482051.331228
13KPE1369midazolam0.865586-0.6417400.360260-2.478017-0.350239
14KPE1387ketamine-0.381962-0.1857510.033346-0.316837-0.620232
15KPE1390midazolam0.392622-0.536858-0.1362770.1161900.767498
16KPE1403midazolam0.5527691.0974040.7765530.2078381.031879
17KPE1419ketamine0.123481-0.3213270.3033590.106221-0.418346
18KPE1464ketamine-1.576694-0.691025-2.1825030.854975-2.496906
19KPE1468midazolam0.764399-0.3322941.141317-0.9329770.284373
20KPE1480midazolam0.293831-0.661676-0.6528751.6646560.426620
21KPE1499ketamine-0.6034001.900897-0.288752-1.550560-1.120646
22KPE1561midazolam0.4553220.6323900.1381341.269623-0.250904
23KPE1573ketamine0.115967-1.7843140.761430-0.7203310.586571
\n", + "
" + ], + "text/plain": [ + " scr_id group amg hippopost hippoAnt vmPFC_ant vmPFC\n", + "0 KPE008 ketamine -0.465222 -0.688774 0.538616 0.337328 0.128000\n", + "1 KPE1223 ketamine 0.856679 0.521909 0.613998 0.774375 0.589104\n", + "2 KPE1253 midazolam 1.023002 -0.386011 -0.834792 -1.172510 1.470069\n", + "3 KPE1263 midazolam 0.603694 -0.506558 0.763601 0.746135 0.560564\n", + "4 KPE1293 ketamine -0.553164 -0.309508 -0.397273 0.297633 -0.358259\n", + "5 KPE1307 ketamine -2.318977 -0.597950 -0.118689 -0.990741 -1.934913\n", + "6 KPE1315 ketamine 0.194892 0.001936 -0.115215 0.253506 0.504973\n", + "7 KPE1322 ketamine 0.299361 1.267163 0.492407 1.540114 1.670747\n", + "8 KPE1339 ketamine -0.516204 -0.003874 0.518529 0.939097 -0.079983\n", + "9 KPE1343 ketamine -2.330085 -0.823191 -1.347205 -0.524386 0.089253\n", + "10 KPE1351 midazolam -0.763579 -0.965045 -2.526727 -1.078393 -0.504770\n", + "11 KPE1356 midazolam 1.354395 1.352217 -0.105537 0.108860 -1.305680\n", + "12 KPE1364 midazolam 1.613286 2.661980 2.264293 0.548205 1.331228\n", + "13 KPE1369 midazolam 0.865586 -0.641740 0.360260 -2.478017 -0.350239\n", + "14 KPE1387 ketamine -0.381962 -0.185751 0.033346 -0.316837 -0.620232\n", + "15 KPE1390 midazolam 0.392622 -0.536858 -0.136277 0.116190 0.767498\n", + "16 KPE1403 midazolam 0.552769 1.097404 0.776553 0.207838 1.031879\n", + "17 KPE1419 ketamine 0.123481 -0.321327 0.303359 0.106221 -0.418346\n", + "18 KPE1464 ketamine -1.576694 -0.691025 -2.182503 0.854975 -2.496906\n", + "19 KPE1468 midazolam 0.764399 -0.332294 1.141317 -0.932977 0.284373\n", + "20 KPE1480 midazolam 0.293831 -0.661676 -0.652875 1.664656 0.426620\n", + "21 KPE1499 ketamine -0.603400 1.900897 -0.288752 -1.550560 -1.120646\n", + "22 KPE1561 midazolam 0.455322 0.632390 0.138134 1.269623 -0.250904\n", + "23 KPE1573 ketamine 0.115967 -1.784314 0.761430 -0.720331 0.586571" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.DataFrame({'scr_id': scr_id[0:24], 'amg': ses2_ROIs[:,0], 'hippopost': ses2_ROIs[:,1], \n", + " 'hippoAnt': ses2_ROIs[:,2], 'vmPFC_ant': ses2_ROIs[:,3], 'vmPFC': ses2_ROIs[:,4]})\n", + "df = pd.merge(medication_cond, df)\n", + "df = df.rename(columns={'med_cond': 'group'})\n", + "df = df.replace(to_replace={'group': {0.0:'midazolam', 1.0:'ketamine'}})\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ttest_indResult(statistic=-1.4180515886707268, pvalue=0.17018571435391172)" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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scr_idgroupamg1hippopost1hippoAnt1vmPFC_ant1vmPFC1
0KPE008ketamine0.9007020.1308181.4155080.1312550.722584
1KPE1223ketamine-0.0003830.077618-0.7728210.5757790.384614
2KPE1253midazolam-0.0228060.185740-0.7948910.294901-0.295044
3KPE1263midazolam-0.821198-1.733423-1.369823-0.584887-0.734617
4KPE1293ketamine-0.5796050.0407200.967307-0.0508510.375149
5KPE1307ketamine-2.235922-0.6462150.460168-1.842212-1.463576
6KPE1315ketamine0.015740-0.469739-0.366420-0.984387-0.386665
7KPE1322ketamine0.6697432.3488031.2455762.6984681.399117
8KPE1339ketamine0.629622-0.045620-1.649392-0.590417-0.581334
9KPE1343ketamine-1.827200-2.167584-0.802191-1.813836-2.091250
10KPE1351midazolam-0.5931470.678353-1.1192290.2164840.486913
11KPE1356midazolam-0.444151-0.4055000.074420-0.316062-0.147327
12KPE1364midazolam-0.488994-0.2173000.325527-0.566040-0.248948
13KPE1369midazolam2.6730960.4533280.535578-0.0671620.916625
14KPE1387ketamine-0.763182-0.395722-1.506574-1.378497-1.390060
15KPE1390midazolam0.221027-0.142072-0.075633-0.1484710.111280
16KPE1403midazolam0.1792130.7197930.4305280.6391861.137717
17KPE1419ketamine0.0042170.725436-0.153304-0.331571-0.721480
18KPE1464ketamine0.7048081.0417851.838457-0.3095790.472867
19KPE1468midazolam-0.611402-1.494585-1.0889211.140707-1.455404
20KPE1480midazolam0.2101711.3609781.9556710.5698260.721975
21KPE1499ketamine1.6135560.3658080.0977911.4125021.903666
22KPE1561midazolam-0.279547-1.245863-0.467781-0.641542-1.016617
23KPE1573ketamine1.272405-0.525214-0.1388690.9475411.372057
24KPE1578midazolam-0.4267631.3596570.9593180.9988640.527759
\n", + "
" + ], + "text/plain": [ + " scr_id group amg1 hippopost1 hippoAnt1 vmPFC_ant1 vmPFC1\n", + "0 KPE008 ketamine 0.900702 0.130818 1.415508 0.131255 0.722584\n", + "1 KPE1223 ketamine -0.000383 0.077618 -0.772821 0.575779 0.384614\n", + "2 KPE1253 midazolam -0.022806 0.185740 -0.794891 0.294901 -0.295044\n", + "3 KPE1263 midazolam -0.821198 -1.733423 -1.369823 -0.584887 -0.734617\n", + "4 KPE1293 ketamine -0.579605 0.040720 0.967307 -0.050851 0.375149\n", + "5 KPE1307 ketamine -2.235922 -0.646215 0.460168 -1.842212 -1.463576\n", + "6 KPE1315 ketamine 0.015740 -0.469739 -0.366420 -0.984387 -0.386665\n", + "7 KPE1322 ketamine 0.669743 2.348803 1.245576 2.698468 1.399117\n", + "8 KPE1339 ketamine 0.629622 -0.045620 -1.649392 -0.590417 -0.581334\n", + "9 KPE1343 ketamine -1.827200 -2.167584 -0.802191 -1.813836 -2.091250\n", + "10 KPE1351 midazolam -0.593147 0.678353 -1.119229 0.216484 0.486913\n", + "11 KPE1356 midazolam -0.444151 -0.405500 0.074420 -0.316062 -0.147327\n", + "12 KPE1364 midazolam -0.488994 -0.217300 0.325527 -0.566040 -0.248948\n", + "13 KPE1369 midazolam 2.673096 0.453328 0.535578 -0.067162 0.916625\n", + "14 KPE1387 ketamine -0.763182 -0.395722 -1.506574 -1.378497 -1.390060\n", + "15 KPE1390 midazolam 0.221027 -0.142072 -0.075633 -0.148471 0.111280\n", + "16 KPE1403 midazolam 0.179213 0.719793 0.430528 0.639186 1.137717\n", + "17 KPE1419 ketamine 0.004217 0.725436 -0.153304 -0.331571 -0.721480\n", + "18 KPE1464 ketamine 0.704808 1.041785 1.838457 -0.309579 0.472867\n", + "19 KPE1468 midazolam -0.611402 -1.494585 -1.088921 1.140707 -1.455404\n", + "20 KPE1480 midazolam 0.210171 1.360978 1.955671 0.569826 0.721975\n", + "21 KPE1499 ketamine 1.613556 0.365808 0.097791 1.412502 1.903666\n", + "22 KPE1561 midazolam -0.279547 -1.245863 -0.467781 -0.641542 -1.016617\n", + "23 KPE1573 ketamine 1.272405 -0.525214 -0.138869 0.947541 1.372057\n", + "24 KPE1578 midazolam -0.426763 1.359657 0.959318 0.998864 0.527759" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df1 = pd.DataFrame({'scr_id': scr_id, 'amg1': ses1_ROIs[:,0], 'hippopost1': ses1_ROIs[:,1], \n", + " 'hippoAnt1': ses1_ROIs[:,2], 'vmPFC_ant1': ses1_ROIs[:,3],\n", + " 'vmPFC1': ses1_ROIs[:,4]})\n", + "df1 = pd.merge(medication_cond, df1)\n", + "df1 = df1.rename(columns={'med_cond': 'group'})\n", + "df1 = df1.replace(to_replace={'group': {0.0:'midazolam', 1.0:'ketamine'}})\n", + "df1" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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scr_idgroupamghippoposthippoAntvmPFC_antvmPFChippAvgamg1hippopost1hippoAnt1vmPFC_ant1vmPFC1amg2_1hippost2_1hippAnt2_1
0KPE008ketamine-0.465222-0.6887740.5386160.3373280.128000-0.0750790.9007020.1308181.4155080.1312550.722584-1.365924-0.819593-0.876891
1KPE1223ketamine0.8566790.5219090.6139980.7743750.5891040.567954-0.0003830.077618-0.7728210.5757790.3846140.8570620.4442921.386819
2KPE1253midazolam1.023002-0.386011-0.834792-1.1725101.470069-0.610401-0.0228060.185740-0.7948910.294901-0.2950441.045808-0.571751-0.039900
3KPE1263midazolam0.603694-0.5065580.7636010.7461350.5605640.128521-0.821198-1.733423-1.369823-0.584887-0.7346171.4248921.2268652.133425
4KPE1293ketamine-0.553164-0.309508-0.3972730.297633-0.358259-0.353390-0.5796050.0407200.967307-0.0508510.3751490.026441-0.350228-1.364580
5KPE1307ketamine-2.318977-0.597950-0.118689-0.990741-1.934913-0.358319-2.235922-0.6462150.460168-1.842212-1.463576-0.0830550.048266-0.578857
6KPE1315ketamine0.1948920.001936-0.1152150.2535060.504973-0.0566400.015740-0.469739-0.366420-0.984387-0.3866650.1791520.4716750.251204
7KPE1322ketamine0.2993611.2671630.4924071.5401141.6707470.8797850.6697432.3488031.2455762.6984681.399117-0.370382-1.081640-0.753169
8KPE1339ketamine-0.516204-0.0038740.5185290.939097-0.0799830.2573280.629622-0.045620-1.649392-0.590417-0.581334-1.1458260.0417472.167922
9KPE1343ketamine-2.330085-0.823191-1.347205-0.5243860.089253-1.085198-1.827200-2.167584-0.802191-1.813836-2.091250-0.5028841.344393-0.545014
10KPE1351midazolam-0.763579-0.965045-2.526727-1.078393-0.504770-1.745886-0.5931470.678353-1.1192290.2164840.486913-0.170433-1.643398-1.407498
11KPE1356midazolam1.3543951.352217-0.1055370.108860-1.3056800.623340-0.444151-0.4055000.074420-0.316062-0.1473271.7985461.757717-0.179956
12KPE1364midazolam1.6132862.6619802.2642930.5482051.3312282.463137-0.488994-0.2173000.325527-0.566040-0.2489482.1022812.8792791.938767
13KPE1369midazolam0.865586-0.6417400.360260-2.478017-0.350239-0.1407402.6730960.4533280.535578-0.0671620.916625-1.807510-1.095068-0.175318
14KPE1387ketamine-0.381962-0.1857510.033346-0.316837-0.620232-0.076203-0.763182-0.395722-1.506574-1.378497-1.3900600.3812200.2099701.539920
15KPE1390midazolam0.392622-0.536858-0.1362770.1161900.767498-0.3365670.221027-0.142072-0.075633-0.1484710.1112800.171595-0.394786-0.060644
16KPE1403midazolam0.5527691.0974040.7765530.2078381.0318790.9369780.1792130.7197930.4305280.6391861.1377170.3735560.3776110.346025
17KPE1419ketamine0.123481-0.3213270.3033590.106221-0.418346-0.0089840.0042170.725436-0.153304-0.331571-0.7214800.119264-1.0467640.456663
18KPE1464ketamine-1.576694-0.691025-2.1825030.854975-2.496906-1.4367640.7048081.0417851.838457-0.3095790.472867-2.281502-1.732810-4.020960
19KPE1468midazolam0.764399-0.3322941.141317-0.9329770.2843730.404512-0.611402-1.494585-1.0889211.140707-1.4554041.3758011.1622912.230237
20KPE1480midazolam0.293831-0.661676-0.6528751.6646560.426620-0.6572760.2101711.3609781.9556710.5698260.7219750.083661-2.022653-2.608546
21KPE1499ketamine-0.6034001.900897-0.288752-1.550560-1.1206460.8060731.6135560.3658080.0977911.4125021.903666-2.2169551.535089-0.386543
22KPE1561midazolam0.4553220.6323900.1381341.269623-0.2509040.385262-0.279547-1.245863-0.467781-0.641542-1.0166170.7348691.8782530.605914
23KPE1573ketamine0.115967-1.7843140.761430-0.7203310.586571-0.5114421.272405-0.525214-0.1388690.9475411.372057-1.156439-1.2591010.900299
\n", + "
" + ], + "text/plain": [ + " scr_id group amg hippopost hippoAnt vmPFC_ant vmPFC \\\n", + "0 KPE008 ketamine -0.465222 -0.688774 0.538616 0.337328 0.128000 \n", + "1 KPE1223 ketamine 0.856679 0.521909 0.613998 0.774375 0.589104 \n", + "2 KPE1253 midazolam 1.023002 -0.386011 -0.834792 -1.172510 1.470069 \n", + "3 KPE1263 midazolam 0.603694 -0.506558 0.763601 0.746135 0.560564 \n", + "4 KPE1293 ketamine -0.553164 -0.309508 -0.397273 0.297633 -0.358259 \n", + "5 KPE1307 ketamine -2.318977 -0.597950 -0.118689 -0.990741 -1.934913 \n", + "6 KPE1315 ketamine 0.194892 0.001936 -0.115215 0.253506 0.504973 \n", + "7 KPE1322 ketamine 0.299361 1.267163 0.492407 1.540114 1.670747 \n", + "8 KPE1339 ketamine -0.516204 -0.003874 0.518529 0.939097 -0.079983 \n", + "9 KPE1343 ketamine -2.330085 -0.823191 -1.347205 -0.524386 0.089253 \n", + "10 KPE1351 midazolam -0.763579 -0.965045 -2.526727 -1.078393 -0.504770 \n", + "11 KPE1356 midazolam 1.354395 1.352217 -0.105537 0.108860 -1.305680 \n", + "12 KPE1364 midazolam 1.613286 2.661980 2.264293 0.548205 1.331228 \n", + "13 KPE1369 midazolam 0.865586 -0.641740 0.360260 -2.478017 -0.350239 \n", + "14 KPE1387 ketamine -0.381962 -0.185751 0.033346 -0.316837 -0.620232 \n", + "15 KPE1390 midazolam 0.392622 -0.536858 -0.136277 0.116190 0.767498 \n", + "16 KPE1403 midazolam 0.552769 1.097404 0.776553 0.207838 1.031879 \n", + "17 KPE1419 ketamine 0.123481 -0.321327 0.303359 0.106221 -0.418346 \n", + "18 KPE1464 ketamine -1.576694 -0.691025 -2.182503 0.854975 -2.496906 \n", + "19 KPE1468 midazolam 0.764399 -0.332294 1.141317 -0.932977 0.284373 \n", + "20 KPE1480 midazolam 0.293831 -0.661676 -0.652875 1.664656 0.426620 \n", + "21 KPE1499 ketamine -0.603400 1.900897 -0.288752 -1.550560 -1.120646 \n", + "22 KPE1561 midazolam 0.455322 0.632390 0.138134 1.269623 -0.250904 \n", + "23 KPE1573 ketamine 0.115967 -1.784314 0.761430 -0.720331 0.586571 \n", + "\n", + " hippAvg amg1 hippopost1 hippoAnt1 vmPFC_ant1 vmPFC1 amg2_1 \\\n", + "0 -0.075079 0.900702 0.130818 1.415508 0.131255 0.722584 -1.365924 \n", + "1 0.567954 -0.000383 0.077618 -0.772821 0.575779 0.384614 0.857062 \n", + "2 -0.610401 -0.022806 0.185740 -0.794891 0.294901 -0.295044 1.045808 \n", + "3 0.128521 -0.821198 -1.733423 -1.369823 -0.584887 -0.734617 1.424892 \n", + "4 -0.353390 -0.579605 0.040720 0.967307 -0.050851 0.375149 0.026441 \n", + "5 -0.358319 -2.235922 -0.646215 0.460168 -1.842212 -1.463576 -0.083055 \n", + "6 -0.056640 0.015740 -0.469739 -0.366420 -0.984387 -0.386665 0.179152 \n", + "7 0.879785 0.669743 2.348803 1.245576 2.698468 1.399117 -0.370382 \n", + "8 0.257328 0.629622 -0.045620 -1.649392 -0.590417 -0.581334 -1.145826 \n", + "9 -1.085198 -1.827200 -2.167584 -0.802191 -1.813836 -2.091250 -0.502884 \n", + "10 -1.745886 -0.593147 0.678353 -1.119229 0.216484 0.486913 -0.170433 \n", + "11 0.623340 -0.444151 -0.405500 0.074420 -0.316062 -0.147327 1.798546 \n", + "12 2.463137 -0.488994 -0.217300 0.325527 -0.566040 -0.248948 2.102281 \n", + "13 -0.140740 2.673096 0.453328 0.535578 -0.067162 0.916625 -1.807510 \n", + "14 -0.076203 -0.763182 -0.395722 -1.506574 -1.378497 -1.390060 0.381220 \n", + "15 -0.336567 0.221027 -0.142072 -0.075633 -0.148471 0.111280 0.171595 \n", + "16 0.936978 0.179213 0.719793 0.430528 0.639186 1.137717 0.373556 \n", + "17 -0.008984 0.004217 0.725436 -0.153304 -0.331571 -0.721480 0.119264 \n", + "18 -1.436764 0.704808 1.041785 1.838457 -0.309579 0.472867 -2.281502 \n", + "19 0.404512 -0.611402 -1.494585 -1.088921 1.140707 -1.455404 1.375801 \n", + "20 -0.657276 0.210171 1.360978 1.955671 0.569826 0.721975 0.083661 \n", + "21 0.806073 1.613556 0.365808 0.097791 1.412502 1.903666 -2.216955 \n", + "22 0.385262 -0.279547 -1.245863 -0.467781 -0.641542 -1.016617 0.734869 \n", + "23 -0.511442 1.272405 -0.525214 -0.138869 0.947541 1.372057 -1.156439 \n", + "\n", + " hippost2_1 hippAnt2_1 \n", + "0 -0.819593 -0.876891 \n", + "1 0.444292 1.386819 \n", + "2 -0.571751 -0.039900 \n", + "3 1.226865 2.133425 \n", + "4 -0.350228 -1.364580 \n", + "5 0.048266 -0.578857 \n", + "6 0.471675 0.251204 \n", + "7 -1.081640 -0.753169 \n", + "8 0.041747 2.167922 \n", + "9 1.344393 -0.545014 \n", + "10 -1.643398 -1.407498 \n", + "11 1.757717 -0.179956 \n", + "12 2.879279 1.938767 \n", + "13 -1.095068 -0.175318 \n", + "14 0.209970 1.539920 \n", + "15 -0.394786 -0.060644 \n", + "16 0.377611 0.346025 \n", + "17 -1.046764 0.456663 \n", + "18 -1.732810 -4.020960 \n", + "19 1.162291 2.230237 \n", + "20 -2.022653 -2.608546 \n", + "21 1.535089 -0.386543 \n", + "22 1.878253 0.605914 \n", + "23 -1.259101 0.900299 " + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "col = df.loc[: , [\"hippoAnt\",\"hippopost\"]]\n", + "df['hippAvg'] = col.mean(axis=1)\n", + "\n", + "dfTot = pd.merge(df, df1)\n", + "dfTot['amg2_1'] = dfTot.amg - dfTot.amg1\n", + "dfTot['hippost2_1'] = dfTot.hippopost - dfTot.hippopost1\n", + "dfTot['hippAnt2_1'] = dfTot.hippoAnt - dfTot.hippoAnt1\n", + "dfTot" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'dfTot' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mboxplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'group'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'amg1'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdfTot\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msaturation\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m.4\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m scipy.stats.ttest_ind(dfTot.amg2_1[dfTot['group']=='ketamine'],\n\u001b[1;32m 3\u001b[0m dfTot['amg2_1'][dfTot['group']=='midazolam'])\n", + "\u001b[0;31mNameError\u001b[0m: name 'dfTot' is not defined" + ] + } + ], + "source": [ + "sns.boxplot(x='group',y='amg1', data=dfTot, saturation=.4)\n", + "scipy.stats.ttest_ind(dfTot.amg2_1[dfTot['group']=='ketamine'],\n", + " dfTot['amg2_1'][dfTot['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ttest_indResult(statistic=-2.8974675362889157, pvalue=0.008353808055991145)" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(x='group',y='amg2_1', data=dfTot, saturation=.4)\n", + "scipy.stats.ttest_ind(dfTot.amg2_1[dfTot['group']=='ketamine'],\n", + " dfTot['amg2_1'][dfTot['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df.groupby(['group']).count()" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ttest_indResult(statistic=-3.502808955912397, pvalue=0.002010504076813303)" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot\n", + "sns.boxplot(x='group',y='amg', data=df, saturation=.4)\n", + "sns.stripplot(x='group',y='amg', data=df)\n", + "#sns.boxplot(x='group',y='meanAct', data=df)\n", + "scipy.stats.ttest_ind(df.amg[df['group']=='ketamine'], df['amg'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ttest_indResult(statistic=0.3937659771165316, pvalue=0.6975443224592655)" + ] + }, + "execution_count": 58, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(x='group',y='vmPFC_ant', data=df, saturation=.4)\n", + "sns.stripplot(x='group',y='vmPFC_ant', data=df)\n", + "#sns.boxplot(x='group',y='meanAct', data=df)\n", + "scipy.stats.ttest_ind(df.vmPFC_ant[df['group']=='ketamine'], df['vmPFC_ant'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Use PyMC3 for bayesian based analysis " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pymc3 as pm\n", + "# first code new variable for group index (1=ketamine, 2= midazolam)\n", + "group = {'ketamine': 1,'midazolam': 2} \n", + "df['groupIdx'] =[group[item] for item in df.group] " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#az.summary(posterior_1, credible_interval=.95).round(2) # adding round to make shorted floats\n", + "pm.summary(posterior_1)#, alpha=.05).round(2)# also possible" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# play with glm module of pymc3\n", + "from pymc3.glm import GLM\n", + "\n", + "with pm.Model() as model_glm:\n", + " GLM.from_formula('amg ~ groupIdx', df)\n", + " trace = pm.sample(draws=4000, tune=3000)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pm.summary(trace, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.distplot(trace.groupIdx)\n", + "sum(trace['groupIdx']>0) / len(trace['groupIdx'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Presenting differences between the groups using scatter plot for each group + \n", + "## The resulting Bayesian analyses plots (density of differences and boxplot)\n", + "\n", + "sns.set_style(\"whitegrid\")\n", + "plt.figure(figsize=(5,5))\n", + "grid = plt.GridSpec(2, 20, wspace=.1, hspace=0.0) # building a grid to put the graphs in\n", + "plt.subplot(grid[:, :10])\n", + "#fig.add_subplot(grid[0,0])\n", + "g1= sns.stripplot(x='group',y='meanAct',hue = 'group', data=df, s=8)\n", + "#g1 = sns.boxplot(x='group',y='meanAct',hue = 'group', data=df)\n", + "g1.set_ylim(-80,80)\n", + "g1.legend_.remove()\n", + "\n", + "plt.subplot(grid[:, 10])\n", + "g3 = sns.boxplot(trace.groupIdx, orient='v')\n", + "g3.set_ylim(-80,80)\n", + "g3.set_yticks([])\n", + "\n", + "plt.subplot(grid[:, 11:13])\n", + "g2 = sns.distplot(trace.groupIdx, vertical=True, color=\"Green\")\n", + "g2.set_ylim(-80,80)\n", + "#g2.set_yticks([])\n", + "g2.yaxis.tick_right()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#df_vmpfc = pd.DataFrame({'scr_id': scr_id, 'meanAct': mean_act})\n", + "#df['vmPFC'] = mean_act_vmpfc\n", + "#sns.boxplot(x='group',y='vmPFC', data=df)\n", + "sns.barplot(x='group',y='vmPFC', data=df, ci=68)\n", + "scipy.stats.ttest_ind(df.vmPFC[df['group']=='ketamine'], df['vmPFC'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "len(mean_act_vmpfc)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "with pm.Model() as model_glm:\n", + " GLM.from_formula('vmPFC ~ groupIdx', df)\n", + " trace_vmpfc = pm.sample(draws=4000, tune=3000)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pm.summary(trace_vmpfc, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Hippocampus\n", + "mask_file = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=15\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None, standardize=False, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mean_act_hippo = []\n", + "scr_id = []\n", + "for func in func_files:\n", + " # get subject number\n", + " scr_id.append('KPE' + func.split('id_')[1].split('/')[0])\n", + " # get average activation\n", + " t_map = masker.fit_transform(func)\n", + " \n", + " average = np.mean(np.array(t_map))\n", + " mean_act_hippo.append(average)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df['hippo'] = mean_act_hippo\n", + "sns.barplot(x='group',y='hippo', data=df, ci=68)\n", + "scipy.stats.ttest_ind(df.hippo[df['group']=='ketamine'], df['hippo'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "with pm.Model() as model_glm:\n", + " GLM.from_formula('hippo ~ groupIdx', df)\n", + " trace_hippo = pm.sample(draws=2000, tune=5000)\n", + "pm.summary(trace_hippo, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.set_style(\"whitegrid\")\n", + "\n", + "grid = plt.GridSpec(2, 20, wspace=.1, hspace=0.0) # building a grid to put the graphs in\n", + "plt.subplot(grid[:, :10])\n", + "#fig.add_subplot(grid[0,0])\n", + "g1= sns.stripplot(x='group',y='hippo',hue = 'group', data=df, s=8)\n", + "#g1 = sns.boxplot(x='group',y='meanAct',hue = 'group', data=df)\n", + "g1.set_ylim(-80,80)\n", + "g1.legend_.remove()\n", + "\n", + "plt.subplot(grid[:, 10])\n", + "g3 = sns.boxplot(trace_hippo.groupIdx, orient='v')\n", + "g3.set_ylim(-80,80)\n", + "g3.set_yticks([])\n", + "\n", + "plt.subplot(grid[:, 11:13])\n", + "g2 = sns.distplot(trace_hippo.groupIdx, vertical=True, color=\"Green\")\n", + "g2.set_ylim(-80,80)\n", + "#g2.set_yticks([])\n", + "g2.yaxis.tick_right()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Caudate" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mask_file = '/media/Data/work/caudate_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None, standardize=False, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "mean_act_st = []\n", + "scr_id = []\n", + "for func in func_files:\n", + " # get subject number\n", + " scr_id.append('KPE' + func.split('id_')[1].split('/')[0])\n", + " # get average activation\n", + " t_map = masker.fit_transform(func)\n", + " \n", + " average = np.mean(np.array(t_map))\n", + " mean_act_st.append(average)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df['striatumAc'] = mean_act_st\n", + "sns.barplot(x='group',y='striatumAc', data=df, ci=68)\n", + "scipy.stats.ttest_ind(df.striatumAc[df['group']=='ketamine'], df['striatumAc'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "with pm.Model() as model_glm:\n", + " GLM.from_formula('striatumAc ~ groupIdx', df)\n", + " trace_striat = pm.sample()\n", + "pm.summary(trace_striat, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Correlation between PCL scores and average activation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## read pcl scores\n", + "pclDf = pd.read_csv('/home/or/Documents/kpe_analyses/KPEIHR0009_DATA_2019-10-07_1121.csv')\n", + "# take only KPE patients\n", + "pclDf = pclDf[pclDf['scr_id'].str.startswith('KPE')]\n", + "list(pclDf.columns)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "dfP = pd.DataFrame({'subject': pclDf['scr_id']})\n", + "dfP_PCL = pclDf[['scr_id','redcap_event_name','pcl5_1', 'pcl5_2', 'pcl5_3', 'pcl5_4', 'pcl5_5', 'pcl5_6', 'pcl5_7',\n", + " 'pcl5_8', 'pcl5_9', 'pcl5_10', 'pcl5_11', 'pcl5_12', 'pcl5_13', 'pcl5_14', 'pcl5_15', 'pcl5_16', 'pcl5_17',\n", + " 'pcl5_18', 'pcl5_19', 'pcl5_20']]\n", + "# remove NAs\n", + "dfP_PCL = dfP_PCL.dropna()\n", + "# set list of columns for analysis\n", + "colList = list(dfP_PCL)\n", + "colList.remove('scr_id')\n", + "colList.remove('redcap_event_name')\n", + "# set total pcl scores \n", + "dfP_PCL['pclTotal'] = dfP_PCL[colList].sum(axis=1)\n", + "sns.distplot(dfP_PCL.pclTotal)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# reshape it to wide\n", + "df2=dfP_PCL.pivot(index = 'scr_id',columns='redcap_event_name', values='pclTotal')\n", + "list(df2)\n", + "df2 = df2.rename(columns={\"30_day_follow_up_s_arm_1\": \"30Days\", \"90_day_follow_up_s_arm_1\": \"90Days\",\n", + " \"screening_selfrepo_arm_1\": \"Screening\", \"visit_1_arm_1\": \"Visit1\", \n", + " \"visit_7_week_follo_arm_1\": \"Visit7\"})\n", + "#df2['scr_id'] = dfP_PCL['scr_id']\n", + "df2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# merging two data frames toghether\n", + "dfTest = pd.merge(df, df2, on = 'scr_id')\n", + "# change visit1 missing values with screening values\n", + "for i in dfTest.iterrows():\n", + " if np.isnan(i[1].Visit1):\n", + " print(\"Nan\")\n", + " print(i[1].Screening)\n", + " dfTest.at[i[0], 'Visit1']= i[1].Screening\n", + "\n", + "# create difference pcl score\n", + "dfTest['days30_1'] = dfTest['30Days'] - dfTest.Visit1\n", + "dfTest['days30_s'] = dfTest['30Days'] - dfTest.Screening\n", + "dfTest['Visit7_1'] = dfTest['Visit7'] - dfTest.Visit1\n", + "dfTest" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.lmplot(x='Visit7', y='meanAct',hue='group', data=dfTest)\n", + "xMask = np.isnan(dfTest['Visit7'])\n", + "yMask = np.isnan(dfTest['meanAct'])\n", + "nas = np.logical_or(xMask, yMask)\n", + "scipy.stats.pearsonr(dfTest['Visit7'][~nas],dfTest['meanAct'][~nas])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Test difference in amygdala activation between 1st and2nd session and see if it correlates to symtpoms\n", + "dfTest['amg_ses2_ses1'] = dfTest.meanAct - df_ses1.meanAct_ses1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.lmplot(x='amg_ses2_ses1', y='Visit7_1',hue='group', data=dfTest)\n", + "xMask = np.isnan(dfTest['Visit7_1'])\n", + "yMask = np.isnan(dfTest['amg_ses2_ses1'])\n", + "nas = np.logical_or(xMask, yMask)\n", + "scipy.stats.pearsonr(dfTest['Visit7_1'][~nas],dfTest['amg_ses2_ses1'][~nas])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "### So - change in Hippocampus reactivation to trauma script (vs. relax) is correlated to changes symptoms at end of treatment\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "dfTest" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# lets test correlation per group (although this is a very ver\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "dfTest.corr()\n", + "#sns.heatmap(dfTest)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.figure(figsize=(20,10))\n", + "sns.heatmap(dfTest[dfTest.group==0].corr(), annot=True, cmap=\"coolwarm\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "X = dfTest[['meanAct','hippo', 'group']]\n", + "y = dfTest['days30_1']\n", + "\n", + "X = sm.add_constant(X)\n", + "est = sm.OLS(y, X, missing='drop').fit()\n", + "est.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "smOLS = smf.ols(formula='days30_1 ~ group * meanAct', data=dfTest).fit()\n", + "\n", + "smOLS.summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Check correlation with SCR" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "scr = pd.read_csv('/home/or/kpe_task_analysis/scr_deltas.csv')\n", + "scr1 = scr.drop(columns = ['med_cond', 'groupIdx'])\n", + "scr1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "dfMerge = pd.merge(df, scr1)\n", + "dfMerge" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.lmplot(x = 'Trauma_2vs1', y= 'meanAct',hue = 'group', data=dfMerge)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "smOLS = smf.ols(formula='Trauma_2vs1 ~ group * meanAct', data=dfMerge).fit()\n", + "\n", + "smOLS.summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Check changes in amg activation and SCR / PCL" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "dfMerge['amg_2_1'] = dfMerge.meanAct - df_ses1.meanAct_ses1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.lmplot(x='Trauma_2vs1', y = 'amg_2_1', hue='group', data=dfMerge)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/.ipynb_checkpoints/consort_graphviz-checkpoint.ipynb b/task_based_analysis/.ipynb_checkpoints/consort_graphviz-checkpoint.ipynb new file mode 100644 index 0000000..f8e4a2d --- /dev/null +++ b/task_based_analysis/.ipynb_checkpoints/consort_graphviz-checkpoint.ipynb @@ -0,0 +1,184 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from graphviz import Digraph" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "dot = Digraph(comment='KPE CONSORT', node_attr={'shape': 'rectangle', 'color':'lightblue', 'style':'filled'})" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "dot.node('A', 'Total Screened\\n N=119')\n", + "dot.node('B', 'Total Eligible\\n N=30')\n", + "dot.node('C','Total Randomized\\n N=25\\n Ketamine=13 Midazolam=12')\n", + "dot.node('D', 'Participated in 1st visit\\n N=25')\n", + "dot.node('E', 'Participated in 2nd visit')\n", + 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"nbformat_minor": 4 +} diff --git a/task_based_analysis/.ipynb_checkpoints/extractingKPE_taskdata-checkpoint.py b/task_based_analysis/.ipynb_checkpoints/extractingKPE_taskdata-checkpoint.py new file mode 100755 index 0000000..8aa04ed --- /dev/null +++ b/task_based_analysis/.ipynb_checkpoints/extractingKPE_taskdata-checkpoint.py @@ -0,0 +1,265 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +# %% +""" +Created on Wed Mar 6 16:02:52 2019 + +@author: Or Duek +Extracting KPE physio data from biopac using bioread package +https://github.com/uwmadison-chm/bioread + +This script eventually create a csv file for each session for each subject - with condition (Trauma, Relax, Sad), onset and duration. +It takes the scanSheet excel file to get the order of scripts per session. +To run the script you should call all functions and then run a loop (at bottom of file) with subject numbers +""" + +import bioread +import os +import pandas as pd +# loading file +#a= bioread.read('/media/Drobo/Levy_Lab/Projects/PTSD_KPE/physio_data/raw/kpe1387/scan_1/kpe1387.1_scripts_2018-09-10T08_39_24.acq') + +# choose scripts channel +#b = a.channels[7].raw_data +# %% +# create loop that will look for changes between zero and back to zero as on and off set time points. +def lookZero(b, offSet): # take Channel data and if we need to adjust timings + time_onset = [] + time_offset = [] +# this function takes a raw data from bioread channel and return two arrays of on and off sets. + look_for_zero = b[0] != 0 + for i, v in enumerate(b[1:]): + if look_for_zero and v == 0: + look_for_zero = False + time_offset.append(i/1000 - offSet) + elif not look_for_zero and v != 0: + look_for_zero = True + time_onset.append(i/1000 - offSet) + return (time_onset, time_offset) + +# %% Function to extract actual data from subjects +def kpeTaskDat(filename): + # takes filename and returns data frame of onsets and duration. Needs to attach condition and subject number + import pandas as pd + a = bioread.read(filename) + ## Take the first ready screen + readyScreen = a.named_channels["Ready Screen"].raw_data + readyOn = lookZero(readyScreen,0)[0] + # set difference between first appereance and TRs. + # Setting to first Ready screen at 6 seconds + diff = readyOn[0] - 6 + # Choose Script channel by its name + b = a.named_channels["Script"].raw_data + scriptTime = lookZero(b, diff) + duration = [] + #condition = [] + for i in range(len(scriptTime[0])): # run through the set 1 + duration.append(scriptTime[1][i] - scriptTime[0][i]) # create duration + events= pd.DataFrame({'onset':scriptTime[0], 'duration':duration}) + return events + +def orderSize(folder): + # this simple function will return the highest file size, in order to get the largest acknowledgment file + # The folder containing files. + directory = folder + # Get all files. + list = os.listdir(directory) + + # Loop and add files to list. + pairs = [] + for file in list: + # Use join to get full file path. + location = os.path.join(directory, file) + # Get size and add to list of tuples. + size = os.path.getsize(location) + pairs.append((size, file)) + # Sort list of tuples by the first element, size. + pairs.sort(key=lambda s: s[0], reverse = True) + # Display pairs. + return pairs[0][1] # return only file name +# %% This part takes the scan sheet and create a data frame with condition and sessions. +totalScanData = pd.read_excel('/media/Data/Lab_Projects/KPE_PTSD_Project/other/kpe_scan_table.xls', sheet_name = 'kpe_scan_table') +# short loop to fill in subject numebrs and sessions +totalScanData["subject_id"] = totalScanData["subject_id"].fillna('noSub') # filling all NaNs with noSub. +# create a session column + +for index,rows in totalScanData.iterrows(): + print(index) + print (rows.subject_id) + if rows.subject_id != 'noSub': + subject = rows.subject_id + + else: + totalScanData["subject_id"][index] = subject + +trialOrder = pd.DataFrame({'subject_id': totalScanData["subject_id"], "scriptOrder":totalScanData["Script Order"], "session":totalScanData["scan_num"]}) + # read subject id and pick the right line from the data frame +# %% +def getCondition(subNum): + + # use scanSheet (from top lines), subjectNumber and session to return a list of condition by order of appereance + subjectId = "kpe" + str(subNum) + subjectData = trialOrder[trialOrder.subject_id==subjectId] + subjectData = subjectData.dropna(subset=['scriptOrder', 'session']) # removing NaN rows (with no session or scriptOrder) + # rnu through all session of subject and create conditions with onset and duration. + conditionDat = pd.DataFrame(columns=['session', 'condition']) + for s , r in subjectData.iterrows(): # s is index and r is the actual row + print (r.scriptOrder) + # condition = [] + session = int(r.session) + print(session) + breakTrial = subjectData["scriptOrder"][s].split() # now its the first line but should be with subject id accordinaly. + for n in breakTrial: + print (n) + if 'Sad;' in n: + conditionDat = conditionDat.append({'session':session,'condition':'sad'}, ignore_index = True) + print ("Out of loop") + break + elif 'Trauma;' in n: + conditionDat = conditionDat.append({'session':session,'condition':'trauma'}, ignore_index = True) + break + elif 'Relaxing;' in n: + conditionDat = conditionDat.append({'session':session,'condition':'relax'}, ignore_index = True) + break + elif 'Sad' in n: + #condition.append('sad') + conditionDat = conditionDat.append({'session':session,'condition':'sad'}, ignore_index = True) + elif 'Relax' in n: + #condition.append('relax') + conditionDat = conditionDat.append({'session':session,'condition':'relax'}, ignore_index = True) + elif 'Trauma' in n: + #condition.append('trauma') + conditionDat = conditionDat.append({'session':session,'condition':'trauma'}, ignore_index = True) + else: + pass + #conditionDat = conditionDat.append({'session':session,'condition':condition}, ignore_index = True) + #conditionList.append(conditionDat) + return conditionDat + #conditionTotal.append(conditionDat) + #events= pd.DataFrame({'onset':scriptTime[0], 'duration':duration, 'condition':condition}) + # now we should create a data frame + + +# %% +# this function takes subject and session number and returns the specific acq file +def getFile(subNum, session): + data_dir = '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/' + folder = data_dir + "kpe" + str(subNum) + "/" + "Scan_" + str(session) + "/" + try: + fullFile = orderSize(folder) + return folder + fullFile + except: + print (f"The following folder + file doesn't exist: {folder}") + return 99 + + +# %% +# now we can iterate through subjects and sessions and create subject data for each +# for now - lets create tsv files for each subject per each session +#subList = ['008','1223','1253','1263','1293','1307','1315','1322','1339','1343','1351','1356','1364','1369','1387','1390','1403','1464'] +subList = ['008']#['1561','1573','1578','1419'] +sessionList = [1,2,3,4] + +for sub in subList: + subNum = sub + print(subNum) + # get condition list for all sessions + conditionList = getCondition(subNum) + # set session + for i in sessionList: + session = i + print (session) + # call file + file = getFile(subNum, session) + if file == 99: + # if no scan then passloop + continue + print (file) + # get script order + conditionSession = conditionList[conditionList.session==session] + onsetsDat = kpeTaskDat(file) + # combine the two + onsetsDat['trial_type'] = conditionSession['condition'].tolist() + # save as tsv file in specifi location BIDS compatible name (i.e. sub-subNum_ses_session_task_.tsv) + # save filename in folder + onsetsDat.to_csv(r'/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/'+'sub-' + str(subNum)+ '_' + 'ses-' +str(session)+'.csv', index = False, sep = '\t') + + + +# %% Addind trialType number (trauma1/2/3, sad1/2/3 etc.) + +# first read csv file +import glob +#file_list = glob.glob('/media/Data/PTSD_KPE/condition_files/sub-*_ses-*.csv') +file_list = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/sub-008_ses-*.csv') +for file in file_list: + events = pd.read_csv(file, sep=r'\t') + # for every line add number + subNum = file.split('sub-')[1].split('_')[0] + session = file.split('ses-')[1].split('.')[0] + # set index for each script + t_i = 1 + s_i = 1 + r_i = 1 + trial_typeN = [] + for line in events.iterrows(): + print(line) + if line[1]['trial_type'].find('trauma')!= -1: + # it is trauma + trial_typeN.append('trauma' + str(t_i)) + t_i = t_i +1 + elif line[1]['trial_type'].find('sad')!= -1: + trial_typeN.append('sad' + str(s_i)) + s_i = s_i +1 + elif line[1]['trial_type'].find('relax')!= -1: + trial_typeN.append('relax' + str(r_i)) + r_i = r_i +1 + events["trial_type_N"] = trial_typeN + # save refined csv file + events.to_csv(r'/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/'+'sub-' + str(subNum)+ '_' + 'ses-' +str(session)+'.csv', index = False, sep = '\t') + +# %% Create 30sec window for each script +#file_list = glob.glob('/media/Data/PTSD_KPE/condition_files/withNumbers/sub-*_ses-*.csv') +file_list = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/sub-*_ses-4.csv') +for file in file_list: + events = pd.read_csv(file, sep=r'\t') + + # for every line add number + subNum = file.split('sub-')[1].split('_')[0] + session = file.split('ses-')[1].split('.')[0] + # set index for each script and index (n) for each window + duration = [] + onset = [] + trial_typeN_60 = [] + for line in events.iterrows(): + #print(line) + newDuration = 60#round(line[1][1] / 4) + startOnset = line[1][0] + # print(startOnset) + for i in range(2): + print(line[1][3]) + trial_typeN_60.append(line[1][3] + '_' + str(i)) + duration.append(newDuration) + onset.append(startOnset) + startOnset = startOnset + newDuration + df = pd.DataFrame({'onset':onset, 'duration': duration, 'trial_type_60': trial_typeN_60}) + + + # save refined csv file + df.to_csv(r'/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/'+'sub-' + str(subNum)+ '_' + 'ses-' +str(session)+ '_60sec_window' + '.csv', index = False, sep = '\t') + +# %% +for line in events.iterrows(): + #print(line) + newDuration = 60#round(line[1][1] / 4) + startOnset = line[1][0] + # print(startOnset) + for i in range(1): + print(line[1])#[3]) + trial_typeN_60.append(line[1][3] + '_' + str(i)) + duration.append(newDuration) + onset.append(startOnset) + startOnset = startOnset + newDuration + +# %% +pd.read_csv('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/sub-008_ses-1_60sec_window.csv', sep='\t') diff --git a/task_based_analysis/.ipynb_checkpoints/fmri_fsl_cluster-checkpoint.py b/task_based_analysis/.ipynb_checkpoints/fmri_fsl_cluster-checkpoint.py new file mode 100644 index 0000000..b3e6765 --- /dev/null +++ b/task_based_analysis/.ipynb_checkpoints/fmri_fsl_cluster-checkpoint.py @@ -0,0 +1,220 @@ +#!/usr/bin/env python +# %% +# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*- +# vi: set ft=python sts=4 ts=4 sw=4 et: +""" +Created on Wed Dec 4 14:29:06 2019 + +@author: Or Duek +1st level analysis using FSL output +In this one we smooth using SUSAN, which takes longer. +""" + +from __future__ import print_function +from __future__ import division +from builtins import str +from builtins import range + +import os # system functions + +import nipype.interfaces.io as nio # Data i/o +import nipype.interfaces.fsl as fsl # fsl +import nipype.interfaces.utility as util # utility +import nipype.pipeline.engine as pe # pypeline engine +import nipype.algorithms.modelgen as model # model generation +#import nipype.algorithms.rapidart as ra # artifact detection +from nipype.workflows.fmri.fsl.preprocess import create_susan_smooth +from nipype.interfaces.utility import Function +""" +Preliminaries +------------- + +Setup any package specific configuration. The output file format for FSL +routines is being set to compressed NIFTI. +""" + +fsl.FSLCommand.set_default_output_type('NIFTI_GZ') + + +data_dir = '/home/oad4/scratch60/kpe' +output_dir = '/home/oad4/scratch60/work/fsl_analysis_ses4' +removeTR = 4 +fwhm = 4 +tr = 1 +session = '4' # choose session + +# %% Methods +def _bids2nipypeinfo(in_file, events_file, regressors_file, removeTR = 4, + regressors_names=None, + motion_columns=None, + decimals=3, amplitude=1.0): + from pathlib import Path + import numpy as np + import pandas as pd + from nipype.interfaces.base.support import Bunch + + # Process the events file + events = pd.read_csv(events_file, sep=r'\s+') + + bunch_fields = ['onsets', 'durations', 'amplitudes'] + + if not motion_columns: + from itertools import product + motion_columns = ['_'.join(v) for v in product(('trans', 'rot'), 'xyz')] + + out_motion = Path('motion.par').resolve() + + regress_data = pd.read_csv(regressors_file, sep=r'\s+') + np.savetxt(out_motion, regress_data[motion_columns].values[removeTR:,], '%g') + if regressors_names is None: + regressors_names = sorted(set(regress_data.columns) - set(motion_columns)) + + if regressors_names: + bunch_fields += ['regressor_names'] + bunch_fields += ['regressors'] + + runinfo = Bunch( + scans=in_file, + conditions=list(set(events.trial_type_30.values)), + **{k: [] for k in bunch_fields}) + + for condition in runinfo.conditions: + event = events[events.trial_type_30.str.match(condition)] + + runinfo.onsets.append(np.round(event.onset.values-removeTR, 3).tolist()) # added -removeTR to align to the onsets after removing X number of TRs from the scan + runinfo.durations.append(np.round(event.duration.values, 3).tolist()) + if 'amplitudes' in events.columns: + runinfo.amplitudes.append(np.round(event.amplitudes.values, 3).tolist()) + else: + runinfo.amplitudes.append([amplitude] * len(event)) + + if 'regressor_names' in bunch_fields: + runinfo.regressor_names = regressors_names + runinfo.regressors = regress_data[regressors_names].fillna(0.0).values[removeTR:,].T.tolist() # adding removeTR to cut the first rows + + return [runinfo], str(out_motion) +# %% +subject_list = ['008','1223','1253','1263','1293','1307','1315','1322','1339','1343','1351','1356','1364', +'1369','1387','1390','1403','1464','1468','1480','1499', '1561'] +# Map field names to individual subject runs. + + + +infosource = pe.Node(util.IdentityInterface(fields=['subject_id' + ], + ), + name="infosource") +infosource.iterables = [('subject_id', subject_list)] + +# SelectFiles - to grab the data (alternativ to DataGrabber) +templates = {'func': data_dir + '/fmriprep/sub-{subject_id}/ses-' + session + '/func/sub-{subject_id}_ses-' + session + '_task-Memory_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz', + 'mask': data_dir + '/fmriprep/sub-{subject_id}/ses-' + session + '/func/sub-{subject_id}_ses-' + session + '_task-Memory_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', + 'regressors': data_dir + '/fmriprep/sub-{subject_id}/ses-' + session + '/func/sub-{subject_id}_ses-' + session + '_task-Memory_desc-confounds_regressors.tsv', + 'events': data_dir + '/condition_files/withNumbers/sub-{subject_id}_ses-' + session + '_30sec_window' + '.csv'} +selectfiles = pe.Node(nio.SelectFiles(templates, + ), + name="selectfiles") +# %% + +# Extract motion parameters from regressors file +runinfo = pe.Node(util.Function( + input_names=['in_file', 'events_file', 'regressors_file', 'regressors_names', 'removeTR'], + function=_bids2nipypeinfo, output_names=['info', 'realign_file']), + name='runinfo') +runinfo.inputs.removeTR = removeTR + +# Set the column names to be used from the confounds file +runinfo.inputs.regressors_names = ['dvars', 'framewise_displacement'] + \ + ['a_comp_cor_%02d' % i for i in range(6)] + ['cosine%02d' % i for i in range(4)] +# %% + + + + +skip = pe.Node(interface=fsl.ExtractROI(), name = 'skip') +skip.inputs.t_min = removeTR +skip.inputs.t_size = -1 + +# %% + +susan = pe.Node(interface=fsl.SUSAN(), name = 'susan') #create_susan_smooth() +susan.inputs.fwhm = fwhm +susan.inputs.brightness_threshold = 1000.0 + + +# %% +modelfit = pe.Workflow(name='modelfit', base_dir= output_dir) +""" +Use :class:`nipype.algorithms.modelgen.SpecifyModel` to generate design information. +""" + +modelspec = pe.Node(interface=model.SpecifyModel(), + name="modelspec") + +modelspec.inputs.input_units = 'secs' +modelspec.inputs.time_repetition = tr +modelspec.inputs.high_pass_filter_cutoff= 120 +""" +Use :class:`nipype.interfaces.fsl.Level1Design` to generate a run specific fsf +file for analysis +""" + +## Building contrasts +level1design = pe.Node(interface=fsl.Level1Design(), name="level1design") +cont1 = ['Trauma1_0>Sad1_0', 'T', ['trauma1_0', 'sad1_0'], [1, -1]] +cont2 = ['Trauma1_0>Relax1_0', 'T', ['trauma1_0', 'relax1_0'], [1, -1]] +cont3 = ['Sad1_0>Relax1_0', 'T', ['sad1_0', 'relax1_0'], [1, -1]] +cont4 = ['trauma1_0 > trauma2_0', 'T', ['trauma1_0', 'trauma2_0'], [1, -1]] +cont5 = ['Trauma1_0>Trauma1_2_3', 'T', ['trauma1_0', 'trauma1_2','trauma1_3'], [1, -0.5, -0.5]] +cont6 = ['Trauma1 > Trauma2', 'T', ['trauma1_0', 'trauma1_1', 'trauma1_2', 'trauma1_3', 'trauma2_0', 'trauma2_1', 'trauma2_2', 'trauma2_3'], [0.25, 0.25, 0.25, 0.25, -0.25, -0.25, -0.25, -0.25 ]] +contrasts = [cont1, cont2, cont3, cont4, cont5, cont6] + + +level1design.inputs.interscan_interval = tr +level1design.inputs.bases = {'dgamma': {'derivs': False}} +level1design.inputs.contrasts = contrasts +level1design.inputs.model_serial_correlations = True +""" +Use :class:`nipype.interfaces.fsl.FEATModel` to generate a run specific mat +file for use by FILMGLS +""" + +modelgen = pe.MapNode( + interface=fsl.FEATModel(), + name='modelgen', + iterfield=['fsf_file', 'ev_files']) +""" +Use :class:`nipype.interfaces.fsl.FILMGLS` to estimate a model specified by a +mat file and a functional run +""" +mask = pe.Node(interface= fsl.maths.ApplyMask(), name = 'mask') + + +modelestimate = pe.MapNode( + interface=fsl.FILMGLS(smooth_autocorr=True, mask_size=5, threshold=1000), + name='modelestimate', + iterfield=['design_file', 'in_file', 'tcon_file']) + + +# %% +modelfit.connect([ + (infosource, selectfiles, [('subject_id', 'subject_id')]), + (selectfiles, runinfo, [('events','events_file'),('regressors','regressors_file')]), + (selectfiles, skip,[('func','in_file')]), + (skip,susan,[('roi_file','in_file')]), + + (susan, runinfo, [('smoothed_file', 'in_file')]), + (susan, modelspec, [('smoothed_file', 'functional_runs')]), + (runinfo, modelspec, [('info', 'subject_info'), ('realign_file', 'realignment_parameters')]), + (modelspec, level1design, [('session_info', 'session_info')]), + (level1design, modelgen, [('fsf_files', 'fsf_file'), ('ev_files', + 'ev_files')]), + # (susan, changeTosrting, [('outputnode.smoothed_files', 'arr')]), + (susan, mask, [('smoothed.file', 'in_file')]), + (selectfiles, mask, [('mask', 'mask_file')]), + (mask, modelestimate, [('out_file','in_file')]), + (modelgen, modelestimate, [('design_file', 'design_file'),('con_file', 'tcon_file'),('fcon_file','fcon_file')]), + +]) +# %% +modelfit.run('MultiProc', plugin_args={'n_procs': 6}) diff --git a/task_based_analysis/.ipynb_checkpoints/secondLevel_fsl-checkpoint.py b/task_based_analysis/.ipynb_checkpoints/secondLevel_fsl-checkpoint.py new file mode 100644 index 0000000..fe2d565 --- /dev/null +++ b/task_based_analysis/.ipynb_checkpoints/secondLevel_fsl-checkpoint.py @@ -0,0 +1,118 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +# %% +""" +Created on Wed Dec 4 14:29:06 2019 + +@author: Or Duek +2nd level analysis using FSL output +""" + +# %% +# %% Load packages +# %% Set variables +# set number of contrasts (cope) +cope_list = ['1','2','3', '4', '5'] +# setting working directory (same as first level) +work_dir = '/media/Data/work/' +# set input directory (where original files are) +mask_dir = '/media/Data/KPE_BIDS/' + +# %% Now run second level +workflow2nd = pe.Workflow(name="2nd_level", base_dir=work_dir) + +copeInput = pe.Node(niu.IdentityInterface( + fields = ['cope']), + name = 'copeInput') + +copeInput.iterables= [('cope', cope_list)] + + +#inputnode = pe.Node(niu.IdentityInterface( +# fields=['group_mask', 'in_copes', 'in_varcopes']), +# name='inputnode') + +#num_copes = 3 + +# SelectFiles - to grab the data (alternativ to DataGrabber) +templates = {'in_copes': work_dir + 'modelfit/_subject_id_*/modelestimate/mapflow/_modelestimate0/results/cope{cope}.nii.gz', + 'mask': mask_dir + 'derivatives/fmriprep/sub-*/ses-1/func/sub-*_ses-1_task-Memory_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', + 'in_varcopes': work_dir + 'modelfit/_subject_id_*/modelestimate/mapflow/_modelestimate0/results/varcope{cope}.nii.gz', + } +selectCopes = pe.Node(nio.SelectFiles(templates, + base_directory=work_dir), + name="selectCopes") + +# %% + +copemerge = pe.Node(interface=fsl.Merge(dimension='t'), + name="copemerge") + +varcopemerge = pe.Node(interface=fsl.Merge(dimension='t'), + name="varcopemerge") + +maskemerge = pe.Node(interface=fsl.Merge(dimension='a'), + name="maskemerge") +#copeImages = glob.glob('/media/Data/work/firstLevelKPE/_subject_id_*/feat_fit/run0.feat/stats/cope1.nii.gz') +#copemerge.inputs.in_files = copeImages + + + +# Configure FSL 2nd level analysis +l2_model = pe.Node(fsl.L2Model(), name='l2_model') + +flameo_ols = pe.Node(fsl.FLAMEO(run_mode='ols'), name='flameo_ols') +def _len(inlist): + print (len(inlist)) + return len(inlist) +### use randomize +rand = pe.Node(fsl.Randomise(), + name = "randomize") + + +rand.inputs.mask = '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1369/ses-1/func/sub-1369_ses-1_task-Memory_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz' # group mask file (was created earlier) +rand.inputs.one_sample_group_mean = True +rand.inputs.tfce = True +rand.inputs.vox_p_values = True +rand.inputs.num_perm = 1000 +# Thresholding - FDR ################################################ +# Calculate pvalues with ztop +fdr_ztop = pe.Node(fsl.ImageMaths(op_string='-ztop', suffix='_pval'), + name='fdr_ztop') +# Find FDR threshold: fdr -i zstat1_pval -m -q 0.05 +# fdr_th = +# Apply threshold: +# fslmaths zstat1_pval -mul -1 -add 1 -thr -mas \ +# zstat1_thresh_vox_fdr_pstat1 + +# Thresholding - FWE ################################################ +# smoothest -r %s -d %i -m %s +# ptoz 0.05 -g %f +# fslmaths %s -thr %s zstat1_thresh + +# Thresholding - Cluster ############################################ +# cluster -i %s -c %s -t 3.2 -p 0.05 -d %s --volume=%s \ +# --othresh=thresh_cluster_fwe_zstat1 --connectivity=26 --mm + +workflow2nd.connect([ + (copeInput, selectCopes, [('cope', 'cope')]), + (selectCopes, copemerge, [('in_copes','in_files')]), + (selectCopes, varcopemerge, [('in_varcopes','in_files')]), + (selectCopes, maskemerge, [('mask','in_files')]), + (selectCopes, l2_model, [(('in_copes', _len), 'num_copes')]), + (copemerge, flameo_ols, [('merged_file', 'cope_file')]), + (varcopemerge, flameo_ols, [('merged_file', 'var_cope_file')]), + (maskemerge, flameo_ols, [('merged_file', 'mask_file')]), + (l2_model, flameo_ols, [('design_mat', 'design_file'), + ('design_con', 't_con_file'), + ('design_grp', 'cov_split_file')]), + (copemerge, rand, [('merged_file','in_file')]), + #(maskemerge, rand, [('merged_file','mask')]), + (l2_model, rand, [('design_con','tcon'), ('design_mat','design_mat')]), + (maskemerge, fdr_ztop, [('merged_file','mask_file')]), + (flameo_ols, fdr_ztop, [('zstats','in_file')]), +]) +# %% +workflow2nd.run('MultiProc', plugin_args={'n_procs': 3}) + + diff --git a/task_based_analysis/.ipynb_checkpoints/spm_2nd_level-checkpoint.ipynb b/task_based_analysis/.ipynb_checkpoints/spm_2nd_level-checkpoint.ipynb new file mode 100644 index 0000000..e343a87 --- /dev/null +++ b/task_based_analysis/.ipynb_checkpoints/spm_2nd_level-checkpoint.ipynb @@ -0,0 +1,592 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/sklearn/externals/joblib/__init__.py:15: DeprecationWarning: sklearn.externals.joblib is deprecated in 0.21 and will be removed in 0.23. Please import this functionality directly from joblib, which can be installed with: pip install joblib. If this warning is raised when loading pickled models, you may need to re-serialize those models with scikit-learn 0.21+.\n", + " warnings.warn(msg, category=DeprecationWarning)\n" + ] + } + ], + "source": [ + "from nilearn.plotting import plot_glass_brain\n", + "import nilearn.plotting\n", + "import glob\n", + "import nibabel as nib\n", + "from nilearn.image import mean_img\n", + "import nilearn.plotting as plotting\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['/media/Data/work/KPE_SPM/spm_l2analysisWorking/_contrast_id_con_0001/level2thresh/spmT_0001_thr.nii',\n", + " '/media/Data/work/KPE_SPM/spm_l2analysisWorking/_contrast_id_con_0003/level2thresh/spmT_0001_thr.nii',\n", + " '/media/Data/work/KPE_SPM/spm_l2analysisWorking/_contrast_id_con_0006/level2thresh/spmT_0001_thr.nii',\n", + " '/media/Data/work/KPE_SPM/spm_l2analysisWorking/_contrast_id_con_0004/level2thresh/spmT_0001_thr.nii',\n", + " '/media/Data/work/KPE_SPM/spm_l2analysisWorking/_contrast_id_con_0005/level2thresh/spmT_0001_thr.nii',\n", + " '/media/Data/work/KPE_SPM/spm_l2analysisWorking/_contrast_id_con_0002/level2thresh/spmT_0001_thr.nii']" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "stat_files = glob.glob('/media/Data/work/KPE_SPM/spm_l2analysisWorking/_contrast_id_con_000*/level2thresh/spmT_0001_thr.nii')\n", + "stat_files" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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wwQewsrLC2bNnDSZz+iYip0+fRqVKlfDKK68AAJo1awYHBwdUrVpV6ehfeukl2NvbK51Bq1atcOTIEURHR2PIkCHw8PDA6NGjsXPnToN7XLt2La5cuYKBAwcqfjX6tGnTBr6+vti/fz/c3d2ViUvjxo3RqlUrA1MWZ2dnHDp0CGfPnsWwYcOQnZ1tsp4rV66M6tWrG0xOrKysDD7m8tdff2HUqFGYOHFigf1MnJyckJGRgdjYWNXxbdu2qSY7o0aNwv79+zVNulxdXZWXeJcuXbBixQps2bIF/fr1w3vvvYc//vjDYMC5cOFCpKamYujQoVi9ejU8PDxUanQg98WzatUqLFmyBKNGjULDhg2xefNmbNu2DWfOnMHgwYMRFhaGHTt2GLUTLiwvvPACKlWqhH/++Uc5Vr9+fdy4cQMfffQRXF1dsXr1asyePRszZswwOH/16tW4cuUK3njjDfj6+uKnn35Cu3btlN8bNWqEs2fPYuzYsRgwYAB27dqF9evXq+qcs2bNGgwbNkw1aKxUqRKGDBmiDPK+/PJLvPnmm/jmm2/Qq1cvTJkyBQkJCZrtacyYMfjqq6+wePFi9OnTBxMmTMDt27eVa5BJGk1q7Ozs0LJlS5w7dw7nzp0zmOz88ccfyn7NmjXh6+uLihUrYvTo0fj444/RrVs3+Pj4qPzEAGDRokVISkrCsGHDDMwnqb5Onz6N27dvo3///gYmn/oMHz4cr7/+OsaNG4cZM2agf//+qjxtbW1x9OhR2NraYtSoUZg3bx6WLFmChg0bGuRVkHcoAOzduxcTJkzAjz/+CFdXV3h4eKgECXPmzMHMmTOxatUqDBw4EGfPnsXWrVsNnnvDhg2xcOFCfPvttxg1ahQcHBxUgwWa3M+dO1d59+qbxRqrT3P6jX379iEnJwdvvfUWBg4ciGXLlilmqx999BH+/fdfxSytQ4cOhTY/3rt3L55//nm8//77+PTTTzF58mSDAYApVq5cidmzZ+O3335D//798dlnn6n+G2PHjsXy5cuxb98+DBgwADt27MD3339v8H+tWLEiNm7ciJUrV2LIkCHIyMiAt7e32e+Tli1bGjVL+vfffxXfjKZNm6J8+fIG6f79919YWVnhP//5j9l56WNlZQU7OzuMHj0avXv3VpkmAbnv4nLlysHX11ez/Dt37sQ777yD7777DgMGDIC/vz/27dun+DRs374d7du3NxhfDB8+HAcPHlT6BHPGPObg4uKCqKgoxawnv3EGAHz22WeoV68e3nrrLSxcuBDjx4/H5MmTDfLdtm0bDhw4AFdXVxw4cMCse2/SpAl27tyJkydPYsCAAXjzzTdx4MABAx8qc8rAn8XixYvRuXNnTJ06FX369MFXX31lMJCvWLEitmzZghUrVmDYsGGIj49XCaOIkSNHon379nj33XexYMECfPbZZ1i8eDHmzp2Lb775Bh9++CG6deumGlAXBcbaa1ZWFu7cuaO0V9oaa/s1atRQ3o/m5FUUmHp3LliwAMnJyRg6dCi2bNkCDw8PDB06VJUHvTPWrFmDvn374sKFC5rXq1y5MtavX4+ff/4ZQ4YMQXZ2Nry9vWFjY/P4N1NYM7aLFy+KqVOnKvvr168XWVlZokmTJsoxLy8vIYQQY8aMUY7169dPCCFEy5YtBQDRtGlTkZOTY2ACs3HjRnHhwgUB5JoFhYWFiZ9++kmV5tixYyozIVOqNQsLC2FlZSX+/fdf8c033+R7P1pmbPR58OCBQXnoY2lpKerVq2egYjfHjM3S0lJUqFBBJCYmqurNwsJCREREiDfeeEM5FhYWJj777DMBQLz77rvi4sWL4o8//hDjx48XAMTHH38sIiIilPTbtm0TN2/eVJmPDRs2TAghRIcOHQSQa2YmhBCLFy82qgqcOHGiaN++vYiNjTWqYp40aZK4cuWKgbpTCCFCQ0M1zUTIZKBq1arCyspKODo6iu3bt4usrCzF/IfSGKNbt25mqTMdHR3F5cuXlfPu3Lkjvv/+e1G7dm1VuqCgILFo0SJhZWUlbG1thZubm4iPj1eZFZDpUM2aNUVmZqZwdnYW1tbWIjY2VgwaNMiomeXzzz8vsrOzRc2aNQUA8dlnn4mLFy9qlpfq7+jRo6rjq1atEqGhoYqa2sPDQwghRNeuXZU0EyZMEEIIVVtv1aqVEEKIvn37mlVfpkw5LCwsxMmTJ8WNGzdEuXLlNPOxsrISX375pbhz545yjNra7NmzlWPlypUTkZGRYv78+fnmtWLFCpWZCy9nlSpVRHJysnjnnXeUNO+++65IT08X1atXFwDE/v37xaJFi8y+92XLlomdO3fmW19BQUGKCULfvn1FZGSkACCGDh2q3HvFihVFZmam8t8FIObPny/i4uJElSpVlGNkkjNy5EhVW9i9e7fR6y5cuFA0bdpU3Lt3T+zcuVNYW1sbtCP9d2NQUJC4ffu2yixxyZIl4uHDh8r+Rx99JDIyMkS9evUMysVNtPg7NL9P7969hRBCDBgwwOjv1apVE8nJyWLWrFmq4wcPHhSBgYHKPvU7+qYbgwYNEkII0aJFCwGYNsUwVp+8jfN+o0aNGkIIIZ5//nnN8wpjxsbbHPWX7du3V9I0bNhQZGVlmW1K06JFCyGEEB9//LHm/YWGhop169apjv/4448iPj5eMTuhd0z37t2VNC+99JIQQog+ffqYVZZjx44Jb29vg+ObN28WZ8+eFQCEi4uLEEKozD6B3LGCEEL06tXL7Lzo8+qrryrv/MzMTDFu3DiD8xYtWqQybePPokePHgbvWADi999/F7/99psAct9NUVFRYsaMGcrv9erVEzk5OWLIkCHKfZga8wCGZmz806pVK5GammowpsjPjO33339XHfP29hbnzp0zuOdPPvlElc6cex8yZIiIjo7O9/mbUwZjz+LatWti0qRJmvlS2xw1apRyrFKlSiImJkbVlwQFBRm4IPz5558iKytLZRLm5eUlwsPDjV6rsGZsN2/eFEuWLDE47ufnJ3755RcBQIwePVoIIYSdnZ0qzeuvvy6EEKJ58+Zm56X/KS4zto0bN6qOX758WWzbts3guQwcONDktebOnSuEUI+Z27ZtK4RQm6WGhISonunmzZsN2o+xdlcozU6dOnXw8ssvG0iqgoODcffuXWX/9u3bAICTJ08aHKtfvz6A3Agjjx49gre3t0pSf+LECbRp0waWlpZo0KAB6tWrZ+DouXv3bpNlbdmyJXbv3o3w8HA8evQI2dnZaNmypSIdyu9+8kNfVQcAffv2xdmzZxEfH4+cnByEhYUBgOo6Wrz66qs4duwYoqOjkZOTg7S0NFSpUkV1bvv27WFvb68yETlz5gy6dOkCAOjatStOnz6N06dPq46dOXNGlYe3t7fKfGzXrl3IysoyMEXQqotOnTrBx8cHq1atwieffGLwu5YJ29GjR1G/fn18+eWX+dZFQkICsrOzERISgh49euC9994zcIzr0qULnJ2dVR8yTTJFaGgo2rZti9dffx2LFi1CbGwsPv30U1y9elVpk8Rnn32G7OxspKam4sCBAzh9+rTRSDLR0dE4efIkRo4cib59+8LCwgKHDx82en03NzdcuHBBkcQFBATg5ZdfxuLFi9GlSxcDKT7h7e2t2t+9ezfq168PR0dH5VhGRobKpMOc/9/jMn/+fHTs2BFjxoxRaetsbGzg6emJW7duISMjA9nZ2fjuu+/QpEkTA83JsWPHlO/Z2dm4deuW6r7s7e2xdOlSBAcHIysrC9nZ2Rg/fny+/62kpCRFEkm888472Ldvn6KZCwgIwDvvvIPp06cbmNYaIyAgAK6urvD09ES7du0MoiABudod0uC4uLgo6vXz58+jSZMmqF27Ntq3bw9ra2uVZqd9+/Y4duyYSivi7++PoKAgs/+bLVq0wOnTp3HmzBmMGDECWVlZJu/p1KlTKrPEf/75Bw4ODko7bNeuHS5duoQHDx6oysW1rQV9h/bo0QMxMTGaZnjPP/88KlWqpIpGBeQ5pNeqVUs5FhwcrLRrugcAqjaUH8bKbKrfiI2Nxf3797FixQoMHz5cVZ6ipH379ggPD1dJQ+/fv2/2+w7Ik85u2LDB6O+Ojo6oX7++0bq2s7NT/TcyMzNVmo+C1jUAo6Y1FhYWBsf5PvW5+sfNzevatWtwdnZGz549sXz5cixfvtxAQ2gq+E/Pnj3x8OFDnD171mCs4uzsDADIycnB7t27MWLECOW8YcOGISUlRcnbnDGPKezt7bFr1y5cvXrVqHZXC/13LZD7/Iw9O14P5tz7tWvXYGdnhw0bNqBXr16oWLFiocvAn0VAQACmT5+OCRMmoHnz5pr3p99PpqSkwMfHB+3bt1el8fX1VY2Bbt++jeDgYJVJ2O3bt1GrVi3N/riwlETbL07MeZaPHj3SHA9x0tLSVGOYwrxftCjUZMfV1RV3797FzZs3Vcfj4+NV+5mZmQbH6RhFT6hZsybKlSuHxMREZGdnK5+NGzfC2toadevWVSJ6RUZGqvLn+5zKlSvj2LFjaNCgAT799FN07twZzs7OCAgIUEVv0LofLWxsbFCjRg1EREQAyDXR2rdvH0JDQzFmzBh06NBBieRiKkpEgwYNcOzYMVhYWGD8+PFwcXGBs7MzIiIiVOe6ubnh9OnTig0lkGvKRgOhLl26wM/PD35+fspkp3PnzqqGU7duXaXMxKNHjxATE2OgaubpiN69e6NcuXLYtGmTwW8VK1bEa6+9ZrTDWLZsGRYsWIBZs2YZ+GTo06VLF7Rt2xaNGjVC7dq1sXnzZoM0ly9fxqVLl1Qf/XoxxaNHj3Dy5ElMnz4d7dq1Q+/evVG9enV89tlnqnSbN2+Gs7MzXnjhBVSpUgUDBw7UbHPbt2/H8OHDMXr0aMV21hj8JX7ixAm8++676Nq1K3x9fREdHY0ff/zRoKPQavv6pnhJSUmqF52x/x8NgM2KXmKCCRMmYPr06XB3dzdQTXt5eWHatGlYtWoVXF1d4ezsjLlz5xq9trH3hn6aDRs2YMSIEVi4cCF69+4NZ2dnrF271uQ9rF27Fl26dEGTJk3QpEkTdO3aVeXHM2/ePPz444/46KOPcPXqVYSEhBidwBPr1q3DV199heHDh+PChQuIiIjAnDlzVIOTP/74Ay1btkT16tXRsWNHZUITGhqK0NBQuLi4wMXFBenp6aoBq7H/JpD7PzT3v+ni4oJ69ephzZo1Bn5VWhire0tLS8WGvk6dOkYjDfFjBX2H1qhRI98Q1dSu+b3SfrVq1fK9B8D8Ns6vYU6/IXR+jeHh4Vi3bh3Cw8Nx+vRptGnTxqxrmkudOnWMvnNM9X361KhRA8nJyZrmhabqWr/9JSYmqt4xBX2fxMXFGfWFsLe3V55jXFyccoynAaBKZyovIjU1FZcuXcKJEyfw6aefYvPmzfDy8lJ+b9KkCVq2bJlvJMGaNWuibt26qnFKdnY2Zs+ejQYNGijptm/fjpdfflkZlI8YMQL79u1Denq6ko+pMU9+2NjYYO/evbCxscHAgQPNEmoQpt61BG8L5tz7zZs3MWjQIDRp0gSHDh1CdHQ0fvnlF5VpqjllMPYsJk2ahD179mDWrFm4efMmbt68qZpQArn9H9UxERkZaVCfxq5v6j1YFJRU2y9OzGlPcXFxZrfRhIQEg/yAohmvFCr0dFGGP46NjUVWVhY6depk1GE9MjJSccLXd9Y1ts/p2LEjGjRogF69euHGjRvKce4PUdD76d69O6ytrRWp7RtvvIGoqCjVn8+YTbsx+vbti4oVK2LQoEFKuFErKyuDAY6bm5vBwN/Pzw81atRAr1690LhxY/j5+SErKwv169dHr169UKdOHdVk5+HDhwZ1ZmlpiRo1ahj4oWhJB+bNm4eePXvCx8cHXbp0UWnyXn/9daSmpmo6i82YMQO1a9fGsmXLEBUVZdRX6PLly088fLGPjw+uXLliYOsaERFhtgR19+7diq2wlt21vb09OnbsaDCg3rRpEzZt2oSaNWti8ODBWLJkCRITE1VaMK22X1JrmgwePBjLli3D559/buBIDORKM5ctW6Za+6UwMfltbGzg5uaGSZMmqdakMUf66efnh1u3bsHd3R0WFun5sB0AACAASURBVBYICwtTSaIyMjLg4eEBDw8PNGvWDB9++CGWLl2KGzdu4OjRowb5CSHwww8/4IcffoCjoyPefPNNfPvttwgLC1PKRpObzp07o3379soED4Dit9OqVStcvHhRNSE29t8EgNq1axu0Qa3/5vr161G1alXs2bMHPXv2hL+/v8k6MkV4eDhatGhhcJxrMgr6Do2Jicl3UEft2sHBQfVuIvt7/r56HHh9mttv3LhxQ/FD7dKlC7y8vHDw4EE4OjoWmXQ1PDzcaLtwcHDI1xdLn5iYGFSuXBlVqlQxOuHRr2t9iqOuAwMDFWGcPi1btsSePXsAAHfu3EFmZiZatmyJ06dPq9Lk5OQoE2pz8tLir7/+wnvvvYdy5cohOzsbbm5uuHLlCkJDQzXPiY2NRWhoKP7v//4v37x9fX3x8OFDjBgxAps2bcKrr76q8v8wZ8yjhaWlJbZu3YrWrVvDxcWlQJPegsDbr7n3fujQIRw6dAhVq1aFm5sbfvjhByxbtswgsEh+GHsWCQkJmDx5MiZPnowXXngBn3/+OX755RdcvXoV//77LwCgSpUqqFChgmrC4+DgUGrW/QoMDDQYY1hbW6NJkyaK/xj54bRs2RL3799X0rVs2RIxMTGKRYg5eZUWnqSmKT8KrNmxtrZGz549i2yyc/LkScVxkEvrL126hKysLISEhODhw4cGC7QNHjw437zJaTIjI0M51rFjR5XzYEHvx87ODl5eXrh16xaOHz+uXIfPXN98802Dc43Nem1tbRUzCWL48OEq9WndunXxyiuvGJTx2rVriIuLw8yZMxEYGIjo6GhlkcyZM2ciKSkJAQEBSvo///wTb7zxhmqgOHjwYFhbW6vM3fIjKysLQ4cOxY0bN3D8+HHUq1dP+c3NzQ1HjhzJN8ra+++/jyNHjmDz5s147bXXzLpmUWLM3MTGxgaOjo6aEnNzSExMhJeXF3bt2qW0C07fvn0RERGheib6REdHY9WqVQbRpIDcCbU+gwcPxoMHD/LtnIuLbt264ZdffsHy5cvx/fffG01ja2ur+t9ZWlrmG1BACxsbG5QrV06VV+XKlTFw4ECzzl+3bh3c3d3x9ttvY9OmTZpt8/bt25g2bRrS09MN6t4YoaGh8PLywu3bt1Xpr169isTERIwbNw62traqCce5c+fQqVMndOjQQWXCBuT+N/v06YPKlSsrx5ydndG4cWOz/5sA8OGHH+LAgQM4fPgwnn/+ebPP08Lf3x/Ozs6q/3m7du1U62cVpk84ceIEatSooTkBvn79OlJSUgwi9wwfPhw3btxQrbNgioJKB83pN/TJzs7GqVOnsHjxYtSrV0+RuGpJzQuCv78/6tSpozLFadCggRKYxhzIjFUr2ldoaCjCwsKM1nVCQgKuXbtWiJIb5/Dhw6hbt64qSlbbtm3RtGlTxdQlMzMTp06dMijPiBEjcO7cOSQmJpqdlxadOnVCSEiI0u+aM1k/ceIE6tSpg+TkZKNjFUIIgZ07d2LEiBEYPnw4EhMTceTIEeV3c8Y8Wvz000/o27cvBgwYoKlFLYp2xzH33onExERs27YN3t7eZr1P9TH1LK5du4bp06fDysrKYMCv309WqlQJvXr1ytch/kly+PBhtGvXTiUIHzhwIGxsbJT2ERQUhBs3bqjavoWFBYYNG6Zq0+bkVRQUpWalpCmwZqdr166wtLQssgWrbt68iRUrVmD79u1YsGABLl68iAoVKqB169b4z3/+gw8++ACPHj3CggULsGjRIkRHR8PPzw9DhgxRhXg1xvnz55GUlITVq1djwYIFcHR0hKenp2qAmN/9lCtXTjFHq1KlCtq2bYsJEyagYsWK6Nu3rzJw8vHxwdSpU7FkyRLs378fLi4ueOuttwzyCwwMVCYEycnJuHHjhvLiW79+PdauXYvWrVtj2rRpijoTyDURuXXrFm7duqXKTwiBs2fPon///qrZvJ+fHyZNmoRjx46pzFnmzZuHy5cvY8+ePfj555/h6OgILy8vHDlyBOfPn8+3LvVJT0/HgAEDcPz4cRw/fhxdu3ZFdHQ0XF1d8cUXX+R7bk5ODoYNG4bjx49jz549eO211zQH/1q0a9fOQKoZGRmJoKAgk+cePXoUgYGB2L9/P0JCQlCnTh1MmjQJ1apVe+zV7D08PPL93diCi56enqhevbpiwvbyyy+jW7duBvXYunVrrFixArt27ULXrl3x/vvvY/LkyU9cakJS08DAQPz666+qhfeioqIUTZ+Pjw8mTpyI27dvIzY2FhMnTixURJXExERcuHABs2bNQmJiIh49eoQvvvgCCQkJBtEKjbFx40bMmzcP1tbWBj4Lu3fvxqVLl3D58mWkpaUpUnp9abI+K1asUMKpJiQkoHv37mjevLkqYtWjR49w4cIF9OvXT8mXOHfuHBYtWgRLS0uDxUQXL16MCRMm4OjRo/Dy8kLlypXx3//+F1evXjVY+DA/hBB4++23sXPnThw7dgxdu3ZV+bMUlPXr1+Prr7/GgQMHMHv2bNja2mL27NmIjIxU3n+F6RN8fHxw5MgRbN26FXPmzMFff/2FunXromvXrvjwww8RFxeHH374AV9//TWys7Nx8eJFDB48GG5ubgWeNGdlZeHu3bsYPnw4rl+/jvT0dFy9elUzvTn9xgsvvIBFixbh119/xd27d1GtWjXMmDEDAQEByrs7MDAQffr0Qe/evRETE4OgoKACa0kOHTqEgIAA7NixAzNmzEB6ejrmzJlTIIn+zZs3sXLlSnz//fdwcHDA6dOnYW9vj6FDh2LUqFEQQsDT0xMrV65ETEwMfHx80K1bN0yYMAFfffWVatL3uJw/fx5HjhzBpk2bMG3aNGUhUD8/P5w4cUJJN3fuXPj6+mLJkiXYs2cPXF1d4erqqgqra05eDRs2xPr167F161bcvXsXlStXxhtvvIFRo0bhww8/BJBrft2tWzfMmTMn37L7+Pjg6NGj8PHxgZeXF/7++29UrVoVbdq0QYUKFfDVV18paX/99Vd8/PHHmDp1Kry9vVUTGHPGPMb48ssvMX78eHz33Xd49OiR6t37zz//KFo7Y+OMgph5F/bex40bh44dO+LIkSN48OABmjdvjmHDhhk1eddC61n4+fnB29sb169fhxACH3zwAZKTk1UTmdTUVHz77beoXLkyHjx4gGnTpqF8+fJYunTpY917UbFz507MnDkTu3fvxjfffAM7OzssWbIEW7duVb2jPT09sWXLFgQHB+Ps2bNwd3dH8+bNVcstmJtXq1at8NxzzymTFWdnZyQnJyMqKkqzn9OnoO9Oc7G0tERGRgZmzZpV5FHvNBEmAItqsHjxYqMRUNavXy/8/f1Vx4xFctKKmDZ58mRx/fp1kZ6eLiIjI4Wvr68qGhkAMWfOHBEZGSkSExPFli1bxKhRo4QQ+Udj69Onj7h27ZpITU0VV65cEf369VNFOdG6H4oiIYQQOTk5Ii4uTvj7+4t58+YZRO4CIKZPny7u378vkpOThY+Pj2jWrJkQQr2A1iuvvCLOnTsnkpOThRB5EcTGjBkjbt++LVJTU8W5c+dE+/btVYsE7t6922jkDQDi888/N4hCMnz4cCGEMIg4B+RGVTl//rxIS0sTERER4scff1Q9H4qQpb9IJn34/djb24vLly+LS5cuiRdffFFkZ2crka5MPe9q1aqJ69evi4cPH4omTZqYtYBbftHYVq9ebVZ0kZEjR4o9e/aI+/fvi/T0dBESEiL27t0r2rVrp0pnziKNptLoR2OzsLAQUVFRYtCgQQZpjh8/LiIjI0VaWpoIDAxURfKh+hs9erTYunWrSExMFJGRkcLT09OgvfLogVrPkj/H/D78ueT3DPQjTzk4OIjdu3eLhIQEER4eLry8vMTYsWNVeWmVj0chatq0qThx4oRITk4W9+7dE9OnTze43/zaj5+fn2oxQvpMmzZN+Pv7i/j4eJGYmCjOnz+vihpj7N7PnDkjYmJiREpKirhy5Yp47733DPL19PQUQgixbNky1fHy5cuL9PR0IYRQovHpf9q0aSNOnDghUlJSRFxcnPjll1+Eg4ODyf+SsbZYvnx5cfToUREcHCwcHR01o7Hx9musHl988UVx9uxZkZ6eLgIDA8WgQYPEjRs3lHeS1jvU1KdChQpi4cKFIiQkRKSnp4u7d++KefPmKb9bWloKT09Pcf/+fZGRkSH+/vtvMXr0aFUexvodY/faq1cvceXKFZGWlqb8J/OrT1P9Rq1atcSmTZvEnTt3RFpamnj48KHYunWraNCggZJH48aNhY+Pj4iPjxdCmBcJyVj9N2jQQBw+fFikpqaK4OBgMW7cuAJHhLK0tFSiIWZkZIiQkBCD6GsTJ04Ut27dEhkZGeLOnTtiypQpJt8xBX2fALkLE69bt07ExcWJhIQE8csvvxhdMHPQoEHi2rVrIj09Xfz7779ixIgRBc6ratWqYvPmzSIoKEh5TidOnBD9+vVT0gwcOFBER0cbLBJu7FmUL19eeHp6KvX08OFDcfjwYeHq6mpQtnv37gkhhOjdu7fRejA15uHvwVOnTmm+e/WjkWqNM4w9p4K8R03de4cOHcSBAwdEWFiYSEtLE3fv3hX//e9/VQuemiqD1rNYsGCBuHr1qkhMTBRxcXHi5MmTonPnzgZ5dO7cWVy+fFmkp6eLgIAAVWQvwPg7z9yxK30eZ0Hf+vXrC29vb5GUlCSio6PF8uXLha2trUG6sWPHilu3bon09HRx6dIl0aNHj0LlpT+O1acg5S/Iu5PXpdY7w8rKSgghxMyZM5Vjc+fOVUUC1U9HEYaBwkdjK/Bk58aNG2Ls2LGFetCl8VPa78fa2lokJiaKnj17lnhZ8vt8+eWX4syZMyVejtL66dixo0hPTy/watyPs1Kx/OROqlNTU41OSuSncB8nJyeRmZmphPUu7e9Q+ZGf/D4rV64UW7ZsKfFyyE/hn4WppULk59n+CCGEhW5CowkPsSyRSJ4cjRo1QnBwMPr3719kfnLPApUrV8Zzzz2HyZMno2fPnnBycjLboVui5osvvsCDBw9w7949NGzYEF9++aWyYKq5C4hKJBJJceHh4YFJkyYVWwh4SdlGCFG4aGwSSWnEwsIi3yhd5objfZbga97oU5brq23btvD19UVwcDDefvttOdF5DIQQ8PDwQL169ZS1nKZNm5bvRCe/dvXo0aNSE6HnSVMc/7f88hRC5Bswpqh5Wt8nEkl+lNWxR2l6dxQ7BTVjkx/5Ka0fLftUQt+uWX7y978RouCrLcuP/AB5ppda6Pt2PUuf4vq/5UdhfQtK0/3Jj/yU9k9ZHXuUlnfHk7hPacYmeWqoW7euKkQupyii0jxNVK9eXTOcLoBCRY+SSKytrfHiiy9q/h4dHY179+49wRKVDorr/9a2bVvN35KSksxe6PVxke8TybNKWR17lJZ3R3EjhICc7EgkEolEIpFIJJKnDiFEwRcVlUgkEolEIpFIJJKygJzsSCQSiUQikUgkkqcSk5Od2rVrP4lySCQSiUQikUgkEkmRQHMYkz47ZYkVK1YAAGxtbQHkhfujW6xevToAKI5kdnZ2AIBy5cqp0mVkZAAAIiIiAAAPHjwAAIwZM8bssqxduxYA4ODgACCvwqls5AvFr/Xw4UNV2Sk0YGZmJgBgwoQJZpdBIpGUTTZv3gwg7/1RoUIFAEDFihUBAFWrVgWQ906j90l6ejoAIDs7W7VPzrG0b29vDwBo0KABgLz3EoUaTUlJAQDExcUBgBK6m/KldFlZWap0ISEhyj1QWeladA/ly5cHkLsWEgDUqFEDAFCnTh3V7/x9nJqaarRsFAKb1wkRHx+vqgM6n86LiooCAHzwwQeQGOLs3AwXL36fz+9zcfHixSdYIolEIikYxbrOzpQpUwAAP/zwQ7Hkv3LlSgB5A4KmTZsCgBLvnDo36tRo4kCdKXW+tCWsra0B5HW2tN24cSMAwN3dXbNMq1atApA3uaEOvEqVKqpr8TmmjY2Nqmw0eKEBAU3Idu/eDSCvo3///fc1yyIpXoq7fUskEknJIwCkl3QhJBKJpNAU62RHDgIlTzMBAQElXQTJU8aGDRsAAM2aNQOQpx3hkOaXNCwkLCGBDmlcCBKWkAaHtlywQ5ob2ppS/HOBEAlrAKBSpUqqY1RW0tDQOVQ2EuxUq1bN6LXofF4muheqKxIokbCLtOJ0T3Q9ug6Vb/ny5QCASZMm5XvPzx6PICc7EomkLFOskx0nJyesWbMGPXv2LJL8li5dCiBPa0KaHDKToA6fOkPq/HhHTp0fdZ6kRaGOn/ZpQFGzZk0AeaYcpOGh6wFAQkICgDxTCjLNoI6YOmA6h5eBBic0WKF86N6oQ6YykQmet7c3ACAyMhIAMH78eMOKMwMnJydERETAysoKlStXRt++fbF8+XJlACKRSB6f1157DQDg6+tbouWQSCQSieRZoVgnO5Kyxf79+9GzZ0+Eh4ejT58+mD9/Pr799tuSLpZE8szQsGFDAHnCDi5sIGEHX/+MhCS0JSEKCXjItJeELiQsoeMkEKLzuL8j7ZOQhoQztCVtDWlNgDzfGa6donMoT/LJIV8aund+T1RW2pLgiARKZCpMdUP3TpAwi+qAmzU7OjpCYoxHADJKuhASiURSaMrEZIec/UmTQx01DQRoS50f7+SosyXtC5k3kJkFdYLU+VGHTflR50xmDzExMQCAxMRE5Rp0Dml09LU+gOHghDsQU4dP+VCZaatvHqJ/z9TB0wBh+/btAICRI0eisNSpUwd9+vSRZloSiUTyzCN9diQSSdmmTEx2JE+W0NBQHD58GD169CjpokgkzwQUeIQ0OzxyGQ9cQhoXbnpL+yQ0IQEOHSdBEQlRuMku1+DwaG5kyst9hig9XU//O90LlUHLL4gf55odbqbM7400PCQ4onvjfkq8DukeSIBEQWbGjRsHCSB9diQSSVmnVE92tmzZAiAvPCp11KSR4eFYqdOjzo4GCNTJkZkE/U4dOdee0ECB8uP50HXJdAMwNNkwZR7CzUz44EVL28RNMKguuCZo7969APJCwZrjdPt///d/sLCwQHJyMnr06IHZs2ebPEcikUgkEolEIimtlOrJjuTJsmfPHvTs2RO///47Ro8ejejoaCVAgkQiKXqWLVsGAGjdujWAPCEH15gQXOPDhSEECUG4VoQENty3h1+PNDlkqkv7JJyhcvDrkubHGNxnhvsDUZm4gIjfO12TR1cjARPdAw/nz7VWVFYyU+aBbSSENGOTSCRlm1I12fnf//4HIG9tmrp16wLI80uhjpo6Meo8qZOjTo/MFKgTo46fL4zHt9QZUn6ElmOsfjq+jg79xqOt8TJyJ1lKz9NxPyKt9FwzxH2FzKFbt2545513MG3aNOzZs6fA50skEonkaUGasUkkkrJNsU92srKyFHMxIHdQzqWBktLHlClT4OTkhICAALRp06akiyORPJVQYBEuoCEtA+2TNoJMcEnwQ4IceqfSlpu3kvCF+6tw6Dpkost9cSg/HoDFmCaKhEhcg0JlIMEQ3Qv3S+LQcUpHAh2CR6qj37n/Ed9S+aTvjhZysiORSMo2xT7rcHV1Ve3PnDkT8+bNUx0jUw7q+KlD5QvfETycKtfs8IhmfMBAHblWSFPub0NoOQEDhk64lJb75nCTDW5ewn136BrUwVN6Ok750fl8UEMdOq0N5O7uDnOoVasW3n77bcydOxe7du0y6xyJRCKRSCQSiaQ0UayTneDg4OLMXlKEGHtWP//885MviETyDEACnlq1agHIC55CwhFuosuDp5A2ggQ4FBafm9FyoQtfSJnSaa3fwyOdcaEO14roa3boNyoz/UbX4pHdtAQ2lDcJgrS0VPweSdBDdUvX45omgrRhtKU6/+GHHwDkarufTaTPjkQiKduUqD3Z6tWrAeR1nNT5aDnN0pY6O64Noc6Pd1ak4dE6n2tLCO4vo6UJ0v+NpyGNDu+w6ZpkMsHTcRMPLS0XLyNB+dF1qFw0gaF8xo4dC4lEIpFIjCPN2CQSSdlGOs9IJBLJE4YWSKbAJiScIIEP17SQrw4PaELCE6550dJ6EPx3LgAik2J+Xcqfl5drbYyVlaC0XKjFTYC5EIv2uXkxP05lTkpKUu1zTQ4P5sJ9hkiARGsfPbsIABklXQiJRCIpNE98spOSkoJDhw4ByIu2Rp0RhTmlLe+MeGdFGhvqmPlic1w7wher45HNtMwmOJTOmCMtX+iOR3bj6WiwQ/tURq6VonshTA1e+CKBBB/M7Nq1C25ubgb5SySSoifl998BAI10W3qjxZ08WUIlkkgkEonk6aZYJzuvvfYaAMDX1xcAsHTpUgBAvXr1ivOykgJy8OBBREdHAwDGjx9fwqWRSJ49atSoAcDQnJVv+e98UWK+5T46fMsFOiSkofW1SBDFhTbkD8PD9+ub0/KoaVzoRJDAh2uAtALEaAmhCF5nXEPEy6W1HADdc82aNQEAK1euBPAsviOlGZtEIinbPBHNDq2f06RJEwB5nQd1NtT5kRYjJiYGABAfH686Tp0WpSdzCD4A4J0WaXB4mFbu6EpaED5Q4JHUeOdpDN5hajnXcsdjHq2Na514WQjKn/s3UeQ5ggZVNJih65Dv0Pr16wEA7777rua9SQrP8uXLVftU//R8P/zwwydeJknxE0ymUbp98ryjf6cNP0EiKTXIyY5EIinbSJ8diUQiKWFIoMMFNxytQCemTHG5kIXQ0gDxqGv0O2l6tPxn9DU7dE3Kg0xnubCJLxLN89YyG+Z+TTw/vvAyDyLDA8/QluCCoPr16+PZREZjk0gkZZsnMtlp3LgxAKB27doA8jp27ovD18khDQ9fSI937PR7QkICAMNwrdT50VZrQMAHGJQvD5FqzKeH+8pw/yGtwQZ3hjUW6U0/X+5sy9PxBfS4/xNpt3h0N67dWrNmDQAZra2g/PTTTwDyBkhU39T2nJycABgOLum5bdmyBUBemyMoP9rSeRRWNy4uTkkrtUOlD264m6Db1rhzB4D25EYiKXmkZkcikZRtpGZHIpFISgjSoGiZzGr52mgFWSG0fHhM/c41QVQuKg9FOOOTcWNCGvrONSk8HD4Pm88FAfy41j1pRZTj2imuCeLCL4IvTl29enUAeUsmfPDBB5BIJBJJ6adYJztRUVEA8nx0qNOgLdfkaK1jQxob3vlQeur0SJuRnJwMIE+qTp0ej5TGnWsJkrJTPqRN4VoV/c6RBgPcn4gGIXQvXINDaJlqcPMR8sGh63HnWh52ldJzbRo3HaFy0+CLfHooqMTkyZMhMSQ0NBRLly5VFnUkUxdqe1SfVN/0PKkNUfug+qe2TlpNwsHBAUDec+ELNZIGDwC2bt0KAIiMjATwLC+GWHoon/v3g6XOSaf67dslVxiJpECYMmPT9l2VSCSS0oDU7EgkEskThia5XBjCNSlc08KFJnxrKhqbqd8Jfl2CNDokWOLmtfp+L5Q3CVy4AIDnbSrkvxb8nriPEAkauD8UF1BxrRnfUvnr1KlToPKVfUyZsdk+qYJIJBJJoSiWyQ75HfDQngTvlHgHziNUcTMDrpXg5hA8Uhk3W9By2iVpO2lFSLPDF9Cjjl3/OvSd0miFSeVOsLyM/Dy6NvlmUNm4My4fWJCkX8vhmA+yePkoXzs7O6PlfVb5+eefAeRqysLDw1GuXDnY2dkpAysydeEaHf6cSCNDz4NH4eNtjvKnML28rVP+gGHboTLTccpTauueAM/pJhG5CjmU02l2wnULVTbWab8lktKLnOxIJJKyjdTsSCQSSQlBGhIyM+XBV7jGhQto8gt/rw8XunDNEcHz5cFeyIySziOhCk2g9fMrqKku95nREk7xe9IK+sKFbdwfisrMhWNcS0aCCRIokOBBIpFIJGWDIp3sLFu2DADQokULAHmdE3UmZAJBx6mDJyk4NyfgEc5oYMAXhaP0JPWmTpObS2g5+9J1qeOmyFa8vFoL+Rn7jeB+QTz6mtZgg2sASMtEmhuuEeD3QHVFzrpcs8PPp+txjRGZbqxatQoAMG7cODyLbN68GQDQoEEDALkamPLlyyMnJweVKlUyiHJH9Uf1Tm2Wa3C4iQ39Tv8N3gap3VB+/D8C5D0z0jLxEMB07q+//gogr81Ih+tigOIG1MrdWMTmbtvpHlewrj2B+WhJJIUhJycHzs7OqF+/Pg4cOKD6berUqTh16hSA3H4kMjJSWcsufwSAjKIvrEQikTwhpGZHIpFIShiu4eEmvVpwrQgXzPB0XDvCBTdcGEPQPml2aBJPAiYqt37+ZAJLAgAeNp2XkfsR8TJzTQ8XHGiF7+b3xH1x+HVJ40PPhJsmk7CgNC7AvHTpUrRq1UoVsIRYsmSJ8n3ZsmW4fPmymbnK0NMSiaRsU6STHXLcpM6NOhHyceHmBdRZUcfJ4VJuHk1Ny+RDK2obRyuKG19Xh2uGjK2Zw51euWkE7zB5yFit0LC846Ut1yBROvLtoTqgAQZ3iOZR2Ph1eRhXOv6///0PAPDJJ5/gWWD79u0AgHr1cldKofrIysqCpaUlhBCwtbVV2jD3H+ODRl7fPAIhpafnQ5o9er50Pl+AUb8tGht4AnltlAao9DuZ5Wzbtg1AXiS4SZMmaVWLxBTldc/jOd0+LbQTptt2y9046Xx4MEi3YOWt3M3fuoV4mqRSAokkf0JDQ3Hw4EHMnDkTixcvzjfttm3bMHv2bDNzlouKSiSSso3U7EgkEkkphQtBtDQ2WmvIaMFNhUnAw0PVk0mkVmQyHqpeHy1NCr83msBT8BU+KddaDJrggiXClPkylYcLqKgOSHBEAgcO1UFpYcqUKViwYIFSj1rcu3cPQUFB6NGjxxMqmUQikZQsRTrZIQkxDwVKmh0tR1FCyxmXpNg8HZeicz8I/QhV+uUheAQzkp5zvxYe+YpL1fV/o45RiR+XnQAAIABJREFUy9mWoMEEaQp4GblpBe+QuXMt12px3xG+vo6WzxDBNVCmzGmeNsifpXbt2gDyNGT6JjMWFhawtLSEjY2N5sCOttQuSDPHfaNI48Y1O7RP59EAjLcvag/6efHFFGkQRANUfi1eZlo8kTSeU6dO1awviRqhexwW9OqiuQApsV10W9L4UDpdcLbWx3O3kboBdWXdc5dIjHHgwAE4ODigbdu28PX1zTft9u3bMXTo0AK806UZm0QiKdtIzY5EIpGUcvgaNNxvhUdX4ya+PB/uB0OT8dDQUFU+jo6OAIAaNWoAMBQ8aWlt8rs2Nx9+8OABACAsLNfGjxahJs2JqfV4uK8NwSfxWvnQeST0oi1N8qmcXGtGAqvSwNmzZ7Fv3z4cOnQI6enpSExMxFtvvaUsA6HP9u3b8eOPPxbsAhraM4lEIikLFMlkhyJVkRTcWBhSwHTnp+WgquXPwn/nfg9a1yN4Obn2g5tB8LVR9CFtFaWhfWP+PUCehJ5MNfhggXesvKMmbRn3reFaKfqdpPmUjq9lpHUd+p3Oo7p9WqOzUVumQR5pdKj+jDlBW1hYGGgZuXaFzISofVA9UxvkGjjaUr3TeRQpkA/A9NsPaVi53w9tqWxcq8QHrlxbRdEWP/74Y4M6kKhRNDo0Hqblquh4I922uW7rxDLQHXfQ7Qbo3hNNjTieSyTz58/H/PnzAQC+vr5YtGiR0YnOjRs3EBcXh44dO5qf+SMAxi35JBKJpEwgNTsSiURSxtHSdnBhi5ZAiQtrYmNzY2ST6SNN/ikIjVYQDH148AweHv/evXuqLV2borhpLQbN8+dLE2itx8MFPFzIxuECI4IvdfDTTz8BAD766COj+ZQks2bNgrOzMwYOHAggNzDByJEjzV6fSSKRSJ4GimSyQ9JnrWhl3B/BlPOslp8KXxOGd/DmanS4+QJ1giTF14qgRefxTlP/O5e08w6ZNDJkIkH7VEc8P65tIo0Q1+iQyYeWVoo0E7TVctol+ACARxerVasWniaWL18OAGjSpAkAQwdsum96XtnZ2ao64pEC+RpPfMBG+dAAjdLT8+NR9Ki90OCTTG0oXzIzMlYWrqHh2ictHzgt3zWqKxmtLR9Ig0N/60ps30m3fZFUP210W926J8/9ozr80q7cbXLRllLyFPLaa6/htddeAwDMmTNH9Zunp2fBMxQAskymkkgkklKL1OxIJBLJUwLXVmhpMeg4D7NPJpA0GSctTGBgIAAgOjoaAFC/fm6o7GrVqgEwFKIAecIhugadS5qcyMhIVTqasFMZuHBL6x61/Ja0zKO1AuFwAQX3yaHz9QUe+uV9apGTHYlEUsZ5rMnODz/8AABo2rQpAEM/Beo0ePhSSse1D9yRlI6b0vCYG+KUd/w8pCiPUGZKo6QP18RwiT4/l0dv42Wk86iuqONNZetu8KhuPEwr1QX3ueGmHby8vBz8vsjU5GmBQufyeqL7NtYWhRCKv45W26aBHj13vq4SH4jx6Hw0sOLtgzQ83DdM/zsP7UvwtqGlAeLPnspOZV26dCkAYPLkyZAAZ/UG0e102/IURK0i27alMGzk81ZHt92bu8nSaXZ0ih652o6kxJCTHYlEUsaRmh2JRCIpI/DJMU1kaWvKH0UrghlN4mmyTVoWmvBGReXGxL51K3fV0/DwcAB5Gp4GDRoAUGtDyO+HIrw9fPgQQN5Ena5FgW3q1q0LIG9STYICrXD5pnxu8lsE2tjvPHobr1suHOPh4yUSiURSOnmsyQ45aJL6n0uItSKF8WhQ3EeGfqdOhkdN41oU0hxx3yEtZ13q2KkzJb8Jgmty+No2lF6/k+WaEa2IVjy9VhkJOp/qmsrAtWh8bSEuted+U3RP/Fnx8mtF6KL8Nm3aBAB4++23URbZuHEjgLz65b5JfE0l/YGRfvQ/np4GRjSwo+emZZLD2xz3FeKaPjpObVj/P0Ttn65JafjAluBl12oLPEwx1zI+63TSex8E656BE1UR+ezQOjvoptuSr064bnsjd3MFqm2wbrdB0RRVIjEfARmNTSKRlGmkZkfyTOKvG4zyAKwRp08/+cJIJGZCk2G+SC1f8NjcfLhWhAuoCBI8xcfn2tXt2bNH9ft7770HIE9LAwA3b94EAOzalRtd4ZVXXgGQF3yDa3RIaMWvyQPJcKEX19hw82MusNEKxkLXI+EAmZDSlspBWwoWQ+mfWqQZm0QiKeM81mSHr0HCJcNcA8MjgnH/Ei1HUTqfm2pwbYZWyFFCK9wmDRy45JtveedrDN4hktSca7FMRY7TqhOKgsZ9QbTWd9Hq4HmkPMpfS4tmSuP0tKC17hBvczk5ObC0tIQQAtbW1gbPlQZC1GZoUEoDJ4Kvt8PbjZYPET9f35SG0vL/Czd94lpCvjW2hg+Q55ROa/5IDInSbZ3IZ4cem6JUO6rb6jQ5yA0AgNM6VdDvusO5VmNyrCkpOeRkRyKRlHEKPNnx1xs0N9Ft06U0XFLKidO1W5Idt6P4ChRBWzcYbd6lCwDg72vXnljZJE8PK1asAAC0Lab8tTQ7PPw+oeXDwwOU0Jab09Ikmgfw4Ny/f191PpCn0SH++usvAMCgQYMA5AlujEVyM1Z2bgKqtQ4PD+pB8MVz6Xea9FN4dzLP5AIKruHh5s8SiUQiKZ0UiRmblt8HoeUHYqoz45JmLbQinmlFvKLrkzMtD7/KO0keaYs6PX3fBx61i0vqKS2P1sWl5nywwTUsXJulpb3S0mJpDQC4hoZrjjhc8/C0Y8wHijQ7NjY2Bk7K9Lx5FDeqVz645PDzaGDFo/cZ++9o+bRRu6XBHNcC0nlcG8n/X6QZIs0uRWWcMmWK0Xt5Fok7qtPcvNsnd0u+OzQ+Pp/rvI9M3ZZUQcxXh6KxqYMgSyRPEKnZkUgkZZwCT3Ya6bb6xjT3XFwAADkXLxZBkSSSoqcaaXJItVOPbXVY6Dr1ai+8AADIvHu3uIv2VOA6dSpuTp0Ke90+je2dNCJlPa2QHwqZ+hUXPGgEN3/V8kvhgiCtcP+Eliky5/jx4wCAIUOGmCw7X5uHX1sripopwQ4XNHGhFK2Hw9PzYCIkDCDBBO3ziHV0HzTpL+vBWjSRAQokEkkZp0gDFJgKBaqVzpR5glanZ64mh+BaE9Jm8JCi3K+CQxJv/fVLuE+Oln8PHzxoaa20FgEkuPaMn6d17zyqGNfKETQI0ooiRpjSupV1zAlra2tra+Crw01c+HpH3H+Nr6dE7YNMa8gxnPLl4XD1nx89K2qTXINJvjZaoX15BEFuIsUj8+Wn3Vu7dq0yiHwWNT8pD3K3lQJ0BxJ1W/LJodeDToOjhF0Ly91kJuRuZdw7SYkhNTsSiaSMU+DJDrk4WOjbVeh64juPXx6JpGippZskkkaH2q012xK6dNTOQ4utYGWTtKZNUQ6APYCayKvOalSPVHE6x/wBY8cCALYuWfLEyliSkJS/uIUAXFhhSiih5bOjlY+WcEXLPJbgYc2NwTU6HG5OyU0+taKxcZNgvk6OlpkyN8/kPjqUPwnH+DPmC0RLJBKJpHRRpJod3unwTot3brxj5KYYpsKoamkxTEVlI0iiTeYN3AGV8uVrrRi7H/pOUnS6B+pAeV52dnaqvPjgQ8sMheB1xY/z9Vv0tVCAoXSeOyTze+VaNH4/y5cvBwBMmjQJTxM8Opq+f4ulpSUsLCxga2trEJrXmMYFyBsokR8NDfxIO8K1KZQPtU3S7FA6Y2tVcY0o9w/TMmnS0qgSpjS2+VGtWjUs0U14pk6dWuh8yhrht28DAKo3a5Z7gCbdpNmhVxxJzsl3R6cRCtbtNtIt0Pk4z0AiKRRSsyORSMo4hZ/s6M1DyE7fytk590tAgEHyghCki9Lzn/h4EyklEhOQgJ1rcvggM0t9vLxOZWHTsmXul3v3iquEpZr7NWoAAF7S7VuQjxP3gaKXAKl6dH9dh39yt93eeQcA4L14cbGUs7TAw3xraVoKCk26afLLJ8Fa6+xolYNPbPliuDzABp1vysS3MPCy8DD6BJ+cawl8tBZC1tIkaS3QrCUI4qaoVCd8naCnBjnZkUgkZZxiWVRUK7oTwTUnWhoaSqfls8PNErgZA8GloVySTZ0XmSlQ52XKLEE/Xy3nWd6RkuaHO/rySHFaIWNNlUXLb4kPDLTqkOqayq2l0eF1aO5ihmUV7gdToUIFWFlZQQgBKysrReNCW/Ld0VpPidefVtQ+gtJR+6Etb19AXnsmbROVhXxneFvj/y+t/1FRUEM3eXrWSAkJAQCkDx2au3/4TwBApZosoc4kOE63rREdDcA88zCJpFiQAQokEkkZx+zJTgqtU0KSWz0hFg3jaumcaRMKWIj7DRsCANrp9hvpBgDBOg2PTWKikbMkEjPgmpxKbMvnaLSv02A46RQ6Nxs3BgDYPHhg1mXtevVS7af6+pp1XmmjDf3fn9Ntm+u2PJod1Rt50gfrtjqJsJPupRDv7o4Ad3e0ecrMsX766ScAQPPmuRVEk14uJNDSLmhBkcB4hDBuckuTXq5d4GasWpNurlWh9HwtmsOHD+dbXnMmylw7pKVl4pHmuACHysTTa/n08PP59apXrw4gry5J2EV1whfD5r46dN7atWsBAO+//77JupBIJBJJ8VMsmh2+AjtfM4Q6G3Ollbzz0opUpmVCYsrfhbY0UKCBBTfp4Ofra6LoGtw3hptG8LVLtLROWpocrXvXyodrbrTKyU0/uN8Gd97l+T7tmh2CBlj0HMl3h9AazNLglzuAc3MhgrSM9F8iXx+q7/wc4Hle9MzIn4g/Y36eVpsqSjZt2vT0hegtAEkPHwIA/qlbF4DB2raK686zqQeTlCqkGZtEIinjmD3ZqUQ2+vZsCyh2+qTZuaKTbuLVV43mFerkBADopOvZm+hcfZQeX2fvbxdtbukkEkZ93YCfayK5pofPGahdM1+U/9zK3d5slLvSlE14eL6X54tAZvbtCwBI8/HJ97zSQrTO3KwGLaxF/03S5NB/lpx5qN5I8eWv29KoXXd+Pd3vKe7uOOvujk5PiYaHJqNkQkiTUZrcUrhv2ufCBi1idYEJSADDQ49zs1MuROGRyEytaUNCC25WSRolLXr27AlAex0efcickguReOhzU0sMEFpR2KjMXFDDfW+o7vi+lukvN3Pm5tpP3ULLcrIjkUjKOMWi2SFMRRQzF1Pr5XApuZb/jKnQpdRZkT8ErXHC18rhIU3186YycE0J13xolUFLqs7vVeteCCoHlZ0PkrQGDNw5mN8Hh46bM8h5mkhOTkZOTo5BVDRTAx0agPHnQvVNW246Q5oe7hPEB3D63ykPXjZuusSjtZkKL1yUrFy5EuPHj39i1yttNI7KnQ3y/3013fONl0FaJCWNnOxIJJIyjvmTHZLoGvN10Dkvltcdq6d7MWadP280KzL/V6TC5AdA4nDdGh0kFHYwu5ASiQ5dG1LaKe1nsuNg+zyqGPNJ+c/F3O1NCiXcsaPRyyf+8QcAI8EuiiGaVXFgz7/QljQ89J9tVV33Rfdnrnsldxufq5GAbpeit9k/UGfztMADj9A+PXfSZpCwgTQ91apVA2AYVILS0zZR57dIQg6t65mKxsYnVVqR0LgAiQt8OLV0/pUUxj8/uJkwTcZN+epwuICJC4RIMEBCK5rMc00OaeVoOQBuIkr3zgUMXABE5eEBeSQSiURSsjyRt3JRhWHV0nZwXyBuymHKL4ZLsrmUnZt0GDNF4R0zlYEGI6Ycd0050/J8+b1oSeN5R00DDK21ibhZDDftoEEVd5B+1jQ7RE5ODlJSUpQBE2lgeD1SfdE+DcBo0MudpHmoYfqdBnAk8edR4gDDCHk0iOPO7Vr+WU9Ss2PO4FgikZQgjyCjsUkkkjKN+ZMd7tuQZeS7TnpbT+drQ8OvpEaNoI8i1SXVDUnR6Rq3dYW7c8fs4hkjSjdwrBkT81j5SMoeYTr/MXvdlrvqWJBvCddckCanItuSRlPXeOs/yG2u6RcuIPM//wHMjNJW5qD7r8W2ilNSHd22pfq8eqdyt/Wh2pbXVRM9l2ajR8N/9Gi0K+O+O3yyTxNNrRDi3BS2oCa+PPoaTbZNLQSrJTQhuIaH7ouu079/fwB5k2x7+9w/jpPOD1NfszRkyBAAeRP6kydPqtJwvyU+6dYKLKO1pfNIQEOCGe7vRIIGuice7p3KR8dJUETnc98iEkjQ/Tx1mh1pxiaRSMo4pfqtrNXp8ePc0dXUwEHLtENrUTvqLPnCevohVPnghQYJfGE6U1Jz7ljMw59SR0xSeVO+O7yOuMMy7fO1V3gIWhpAaJmcPHUdfAGhgRANsKg+qO3wARLVW0JC7qiftC6UntoeHedhbum5cC0kYNgGqEw0MKVr0LPUcm5/kqxdu1aG6pVISiNysiORSMo45o9QtVae1z+mG29Z6KS+FqnqpLRVFDq6NUwsyJ9Cl/5v3fZx16OmJT/u6CJLNYmW4d2eFeqzAfuaNWsA5PlIkLlY5R49AAD1dG2xvi7qmoEfGTVanb94JnLHAE/rOID0VA7kH8/NWJSbTtdtK6i39OfVuTZRvdHWXuf7dO9xC1rCrF69GgDQqlUrAIYTRi70ICEBme/RcS5soN+5uSk3H6XJMF2Htqb8XEyZzdIEmMpB5aby8kAs9L/SF3o01K2fRoKSoboFVem/R3nT73ySrlU2Dhf00CSeJvcE19Rw7RVf7JpvuXCAr/dD5ZDR2CQSiaR0UarF8VqrzxPcV8fUGjWEVuQy7ujKzSD4QENfo0QSdzpHK4qZVqQ4fpw0BQ905lHU0dapk2s2RB201kJ6WiYhWk6/tE/3wTt+0iTQca7JKe2aHT4IJMfvykWUP5nG0KDQlA8T1Ss3peH5aIUE5oNj/TZNbYcGwlyzw+uCzuWLPT5JyAxLIpFIJBKJpCgxf4Rqz/ZTjKTRSX8zmUYnQxeVjQZm8bqBccrLLwMAKukULmG69JUDAswuVn44srCuEgkn6cQJAMB9nTQ2UjcR+P/2zj3KqvI+/8/MwCAOlDsiIBBFVEyRnwhqVJz+kmU0iYqGFcUbyMUAghDXz1UbU5qLtYlJXCZt0FiapFUBU2KgWGW1qKO2NkqMaMAaMQoKRC5ykYvjXH9/nPc5Z5/nnHfODMwMc+D5rMXanH32fve79+yZ932/z/dSfvbZADKvPd9lChQHwj+MHo2PfvQj9GqPzrYjg7ZvR11dHQ4MTAUxVQwLX3BL2TT9RFh3KKRfoxJG1ZexUCF8r5xZ2sRivCb8rvaQr8/soDE9ffv2BZBJAqEJPTR2R1PR07igSSO0WK+mDedCVovMcvGsxodYEgrNaBYzHLF93m/M8JOM2WGyDl5L+1gog5z+3eazibktx+rhaFwUr8t+qIuuGox4nD5DrT3E86lcLVmyBAAwadIkFDVWdowxRU6Ti53KysrMh9fky6RHAeNMw2KH05L/DVvW0dDBixen9kG7cvktt6S+jyg7OlDHMpY1d5FTSBHigM4tB9GkW4VOajRGI9aXQlnUtAAfXT90YG5uvZ1CKljMVaRQxi62f++99+Y9/0izfft2ALn91hoz6Qxl4Xu+o3xKfNXrAWwAgA0bMGfOnBw3H1VcYpPK2DZWC0fb0esmYRstLdaY7Dt/N8teCv95M2wfC9s/+yj85+mwDYuffeEjvdz4yx0SE/BB8rCau+/GggUL0kob74ZvY0Xyb1EbMXr0aNx///1tfh1jiopGOBubMaaoab6yo7OPZCIdLnLCPs5rGiqajrqpD8oO7XRlkQxBxrQ3JWPHAsi8m7owqK+rA955J3p+zf/8T6qd8LnTeee1ST/bmvrzz0ddXR2O/92a1A7mQaCXXtfwS985tZhMK740etMizL8XXDWGB1Mq9gU+L/4loM3/k+eeAwB0ufjiFt9DW0KrPxedVA00Lb4mBmGGMhpONAZGz1dDi9ZvomtizFihGctixNLr6/nqHsv7SbojcqGvyon2VZUaXrOQC7Beh/DZMD07FRgexz7yZ6dxSaoE6T1zy/vh+fozogpW9FjZMcYUOU0udqqqqjIfJoYBhe4rOxIHbkxtaoI7GoObJ4TCi7SWcrDRjF8cNDj40P0hFujJwYbxDX8MKarZ/qBBg7La1QmEBudycNPq9uzfhyF1NdWBLVu2ZJ2X7DOvzYFOB1K9tsIJwHvvvQcAeOmllEn92WdTqXwZ5Dt+/Pis68ZigTgZYlFCTgA4IKuVX7PKaTFBPtNkXRcg84yuuuqqvPd1pOC7179/qjStptLV1MD8nhMivoOckCWLPN5+++2or6/HPffck46H4bbuz/8cQGayPuCJJ1L75V3jO6yxUowT02xsOsllYDjfAyB3osw+9QmJOvhuMBMcA7YJ2+L2wIEDGH5OyNjwxXDQ52TbN0yiXw+T7TfC/h2ypUK8OrVhMpKt992Hbdu24dM33gggN8M1/+wMSv5NMsYYY4wpQPOVHYo0nHXsyXzVKIuc5DqoNdkQJnacAPXasiV+sDFHkH6FDykq3v7tBuzduxdjrj0ntSOnPlFY5PCPAP8+8I/BJvksp3e+5BKG8+SFi8a1YaE2uoPE8HBhyUUsk0MosfT5RBfB/KyxMTTccJFOo4O6y8aMKrHMZjGXxthnwgX1rl27svoP5KZh13NiLrWxeKOYC2osVodb/kzUQMN+aAIa7lfXYHVVVsOPtn/UZGWzsmOMKXLaNIWWyv1ak0UVHQ6OWvdD3RzItm3bAABvvpkKJDjhhBMAZKz4qqZoqlDu11gGDWzl8bSAc0BnkTwAuPTSSwFkBlath6L3rgO3TjZ4TSo6ZNmyZQCA0047DUBu9jcN7uX1OPCqoqOZ6HTioO4shSY9HRXNfhZzXVEXGN6/ZlfTySoVn3QqXrm+1rahcsTPfKfULYmf1R2K7xkVu6Q6o++axg/xmmyb19YAcM1OWMgFyhhzFOLFjjGmyGn+Yud4+Zz440exp0a2rcXBkN1mZPhMK++GkDELDz3Uylc05tDo+pnPAMgoFvxdeCPUHDk1LNCLlbfeTm1HvBh28JeSdYmYdY0KDxMSbAxbKjzh70da2cnend7ydC7lOoqiQ7hg5OIzX1p6INdwQ6OBKjNaP4eLZC5UtTYNz49lNtPMYjHVQtUVTdwRM2Zw8c1Fd1LZYlYyZqrTc4jG7sSScsRQFUuLQquLLg0TMcUnpsKpsqO1jfTZ6+eixQkKjDFFTpsqOxx06Psfc8HQAT9f7ZCmoDU+VrOEcNBTdUPdLfQ4Tjxo7U8qOmTVqlUAgOuuuy7rntk229TMWBqEqwP7/w1FL/WaGzduBACceOKJWfcem7TwmbM/WlcnVkeHPxvN+sVtR7f6z58/HwDw2GOp9GGcmGiBQFWsqJRohrKkKlJaWorGxkZ06dIlPSktBN8h/hzYH/aD7y4nYqoycsvz+DuSfNc1DomxOTxX3Ws0OD4W/6XvqjHGGGNMR6f5ix3On5owVvGQpnOwNZ8/BivmWeFzCZPbhAuNDNbj2rlzAQAfrl7dSlc25tBQAZS/CxQ+dgT3Q7z/ft7zNwRXzJM2bcr7/ZGm+rXXsHfvXgwLCTLKvxC+0ICbDWHLGB0J6KsJ0g3/nHCrIYFUdC7oYIoO4UJSDTSaxUzdJXke92sSFS5mqeTQKKHqAo0cWmRYUfVE1ZCY0hOLLVI3V27Zz2Sfkskz8hFz6VXDTay0gG65mGfyDhqruKUKRYVHE+LQkBMz8OjPWtU8TfNf9NiNzRhT5LRL2Xu1XmvBvZbWxYlBq7tmsirkssEBmoOdBgtzYvLv//7vBfvAFKx04aBCoAqIZqTTSQ+fWSzI9dFHHwUAnHHGGQAySkFs8qLt6ve6VRWOaD0aPe/BBx8EAMycOTNvv48UsXo6OklUVxiNO+O2sbEx3UZFRUWLlS0qPDpZJToBU5WREynNOAhk4oG4j+9gMpNcPvjOqtuPukK5SK8xHYvq6mqMHz8en3zyCerq6jBx4kR861vfyjrm+eefx/z58/H6669j6dKl6cyeBfFixxhT5LR8saOmWGSs2Xm+Oiz497WELt908N+T/T0zX2U7rRnT/pTr5/DL0J9bvrRn/3n2geH7E8N2S1h4lId05x2Nl194AXv27MGXvnF5asdl4QsqPAy22ZO9paLDx0AdQBWd5+6/H/PmzWvdTrcBWvSXxgE1ZhB1k9SFZExV0MQUMeNJcjGej+bW24mhiU1U2UmqGZpJThPVxOroFMoMR2Jul9xPA5Am99DCz5pmXlU2ooYkGsnUeMbraUr3tqRLly545pln0K1bN9TW1uLCCy/EZZddhvMS9b2GDBmCX/ziF/jBD37Qssa92DHGFDltquxovIMqOjELcWygLgTb1axqmm0qlnFMBy+exxoyzeGpp54CANxwww0A4q4P/KzFCGnhpwsGY3JivB/coZiBjteLuato0Cz7oVnkNKubTlA05S6ftU7uOgo6gVL1gv3m89eJFJ8bJ2wlJSUoKytDY2PjISk7zYXtarFKopNOIDeAWlUpKjvc8lwNetfAbBKbZLYmvF9jTGFKSkrSi7ba2lrU1tbmjK/Dhg0D0HHjK40xpq1o/sx0j3xOBOaUSColPfRQOTW4hNWEiX9tsBYzHGDV3/0dgEzRxP/TStc15lDhu08xsoJzdsqPFXKApiML7/ig8JJvZHHaFiy425M1oUjo2B+GHaEMTzrrGo3bouhwtyo6bzz6aLtaxA8XVVhUoVHXXU0YQuMCFSIuwjXDF/ersqNZ3DQRSqHaNEpMXdEsbjQS8GelhiIgt26NKjN6LZ2E62JaFZRY37nls9It+8PFvSYp4bPU9vRZxJ4Rz2ftofaivr4eY8aMwdtvv41bb70V5557bus07GxsxpgixyYeY4wxpsgpKyvD2rVrsXnzZrz88stYt25d6zRMN7bYP2OM6eA0X9lhNqV8gTnh/wfCH76VtDWNAAAgAElEQVRe69cDAMqmTgWQW/gyZtFTVy9+fzAoPOT9F14AAPzmn/4JAPDZz342dTOSNUfb0UxC/EzrqQaJM4ic25ZA1ze15GpKZ8KkCrQK0iXhlFNOAYB0MCmLipItW7YAyCQqoMql1keNIVAXJfZHMwtpIgNSyL++o8H7orVZLe2aPUursPN4Jg7o1q0bSkpK0KlTJ3Tv3j3dTs1vfwsAOHhOSuLoxd+TfrIdFrasS8Pj+HsWlJ9hQRna3qcPAKDLzp0AcpWDZBas2M+aP2O+50yOQHc2um3yZ802eQ3uT75bW5cvR11dHYaH97MXZVcqVpwMBUXr+KBcSSgPNi1fjpqaGnRGblIMY0zz6dmzJyorK7Fq1Sp8+tOfPvwGHbNjjClyOmaAhTHGFAFMDc0FpC7+k7FUQK4xQBetdLXiwlMLcGqNMF3sqgGnuTWSYq5Y6sqlRU+5UGa/8vWVW03tHEONVBon2FwXPE2eoG513PJeYqmjY25sWvtKr5cssNrW7NixA507d0bPnj3x8ccfY/Xq1fjLv/zLdru+McZ0ZFoes6Op1xL/57DeI0wAYsHURAexmM82j+NgwwnG5ZenMkGdEGqTqKqhgdo6YHPw5ZYTBKos9EfXCccXvvCFrH4BmYGU57DII63pVAR0gNT0vlpHg+eNGzcOQCZhwdatW7PuidfXhAKaaIDoM9dJUSE/9Zgfvj6rjoJO0nTCpbEROlHjNqlG1tfXo1OnTujatWv655UuQBvaHRTrEIUYVUpVCRqZ2vQPHxnD021HqmANFcB8ippO1lTF04xffO+55WRN06JzYs1ncvDgQaz4+c/R2NiICUHN7UXFShStEobjBIXn3ccfT71LtbU5k0ZjTPP405/+hMmTJ6O+vh4NDQ34yle+gi996UtYsGABzjnnHFxxxRVYs2YNrrrqKuzevRsrV67E3/zN32B98MJokgZY2THGFDVWdowxpoUsXLgQAHDqqalysVzsanZCLgxVPeCCUg086jLIhagaH9g+Exuo66K6aWp7qn6o2kHU5ZcLYF6Xxp0XgmtxkksuuSTrGbDPsbTcumBXA4y6Oetx7Duvp4oOVah87pjJ4/m91ofTrIR8JkkX0uR9tGdmylGjRuHVV1/N2f/tb387/f+xY8di8+bNLW/cCQqMMUVOy5WdJoro8JDGEOPCwYMxLzElJVbNOxbbM2LECACpugFAbnpnHt83WMFVoWG7mpJXU03zc58QL8F00hrbA+TWVmAmHl6T8RG8d50A8B54nKbR5jUZwzN06NCs61IBik0Y9HPsuNjxhM+W/deJxaxZs9AR0Z99THXk/WqMlboNlZWVZT0zTfNcG2KpGgeltJ0SKhzpIBXZ8veK6ckOyP4QxsIyNu+EQrf50sjG4qs0fqxHj1RgkKqJvBfNYsXiuhrjk/x9XfKTn6C+vh6fv+02AMCIHcjuuLB3794cxfWWW27Jf7Axpv1xzI4xpsixsmOMMS2kW7duGDV5MoCMZ+9Ha9akjQEag6PxG1x8q/KicSrqekgXXi1sSaWF7dD4QeMKrxNL50x08azqBY0zWpcrH2pgUFfSWOIaGh7UFbdQvSeNI6IrMRfpWlRUXXLZHp8Z+xcrDKsKEX9Gmijnxz/+MQDgtmAAMMYY0740f7FDC63U1AGAmuB/X/riiwAySg4HAQ6QWhgxlsFLJwDqXkC0/VhlbF5X40nYHtUYDpK7Q/a33qGKPbccDPPFpcQyXVElotsKJyvJAnBAZiDnfk4iOGDrsyBsT7/XehukUHa12GQm5u6isUodFY2NUtcYjWHSiYuqjNXV1WhoaEBjYyN27dqVPo8/f06YmFxtUFBwDgTlJi3cvJbdT/50+Wum2dxKQpa2suHDAQC7Xnkl5171HjXboWZZ473GguR5PH+P+K5+8MEHAIDp06fn9AFz5wIA1oa+jHw7tbtclOEpU6bknmuM6ThY2THGFDlWdowxpgWsKSnBGchk16ayUzt2bPqYkpdfBpCr0Kh6QD516aVZn9c//jiAzIJTjSi6COcCVdPux7ax5C+xjGPqSszP//Vf/4UYzzzzDADgq1/9KoDcuCb2WRWeWGyOosqKulnyOlS51DDE79WFlYv/WLIWGn5oBFA1jj/bdOmEg/RNLVK82DHGFDnNXuxsD+pN/zzfUfShdV8HXFVcYq4RHBw4+HFg5wCrwb20LOt5Olhp1inC/lLJ2REyXPE4xvywPQ7OPC+pSHGA05gb9o0DMI9j28wgx75qRix1AdEUr2xf6/boQM2+a2YudW/hcYw54mfNuqYThqbcWToC7J/WD1IlR4OR9Z1Lqh289507d6aP58+Xz6dbqIvDLGrpEJZt2wAAn8iESF1wel10EQBgZJCISkKWs2Ghnc5jxgAA/vD00+l71cx+qlLx3eC7pDE7ejzfAVWI+Az/KdS7mjZtGpTR4ZgtoU/MTkeB57/D/gs6aH0mY455nKDAGFPkWNkxxphWhotezTzGzzSKcMG47fnnAQDdx48HAAy++uqs9oL3Yk4qc9Zw7ffOOwCQs+iOqSSq5CTTiAO5qkcsTqU58Fj2SVObs20qMKqC5UvCka8v7DOfNdtjOzyO11XVSmOCaGDSMgHqfq0urJrAhv0wxhhzZGj2Yqd/+MN+gFbjxHdMMMVBRdOn6h9/TV9KKzYHEaodWg+EqMqg8SUaP8PPHJQ4aPG6jKvhgM+6PVrJne3nc6+IDZzsg2amiw3ofCbsiw60qkTE6ucQtsctoQrGGKFYQLS6cChq7e+ozJs3DwCwZMkSALk/L0WVNJ2YJbOxdenSJSezn2atOz4oOSdFat/w56AxUR+FOLjaz3wGAFBOn6mQ3WxQcC8ZdM1nAQC7U0JSOsnbB089le4730VOBvmz69SpE0rHjMHHSJf1Sf9O737zzZxJnU7YVVXMxyBRbnqGZ1dR8ExjzBGlkBubTabGmA6O/0wZY8whoJ49yflgj7AQpMGEi14uFGntz0n48ZvfAAC6nHcegExcEDOXV1DiCYwM7sUbTj4ZADAguE2qosMt3TB3huMY56KJTdQ9laqM1vGZOHFi1vdJ44u63BK2TXdgrUmkiWUKxfSwT4zJUfdnTa6iCTg0DkkNTRrTQwNFzP2Tn3ke+1+0eLFjjClyWvxnamPYJrWW3aGgXFcZCDkocRDgH38OMlQb6NbAQUvjKjS7FAczdQ9guxxEOchpkTdejyoLFR7WHaEFXONSeF8c2JMxO6oQaHYv9lVrlqibC/vGvvN7LXDHPrDPql6xHcbe8NmoSwfvkc9Ug2xVVSM8n88uX4a6jgjfDc0yp/FcmhFQA8rLysqy3GU0tofPRRUzjWPTCV2vXr0A5MaJUWnpzx9HiN1J+zWlhB/02hi2b4T7vewyAED4iG0rV+akxu3cuTOGh+/L+4brBFHz4OmnA0hlfYsVnjwUVa88/O6MbvGZxph2pdBip2sT3xljTAfANhljjGkBVHSYY6tWtkCuG6saXLioVSUlbRAK7Rwv28wFUhsuTs8MCs9bIRHGCXv2ZB3ORf77778PANi0KeXoqK6JXKzzeN7Hpz71KQAZow2NLFRh1OUXyBgU2KYaEOg+zP00uNAIxmfGaw4KBXqp4BCN0dF6PtzSuKVp8tW9WdP7q4KjSUz0e03g0dFdfI0x5minxYudMxsb8XhIizpgwAAAQFfJ3sQBPpbpS90XNOVnLFZG42H69OmT9VkHNy24x/5ooT8OnqqOkFi62KZQiz4HUMYjMQMclRd1zdCigPpsqASoCqX1cvgseK+amY790mBcKhN8hkkVIHkdVTQ6OnwXNKWvBpDzs74TfAc//vhjNDY2or6+Hh999FFORkFVJXVSqa45yfiZ5PecANb+6U8AgAMnnhj2hxsaFrZDZRuUHx53Vqjns/Hyy1PthcPYDN2l0jP4sKWQVDpmDErDeZ0AVD//fI57kDHmKMTZ2IwxRY6VHWOMaQEXNDZi2bJlAFKKRz1SRokK5Ma2qPsiF7dURIgmAqkPi9uDYXHLxWm5uhNJUM+IkJnio3A9Gjk2btwIAFi3bh2AjDGERhVel4YoGj2o6AwcmFo9a2FZXcznS8eviguP3bo1lU99+/btWX2lAYKGls2bNwPIGCpGjkyl0aC6pM+WfVdFh67DRMsDaCFm9l8VG92qwqPu2LFsckWD6+wYY4qcQ1rscEBUpSWmNnAQ01olPJ+Dical6AAcK7DXu3fvrOtwUOTgRncJDoLsL8/T+BW1wmusgqZjBXJrC6lCwHN4bSo8rKvCyQfvTd1gtJig1u/RZ6jBu4TX0cx5eh7bL1Sfh99TqerofO1rXwMALF68GEBurJIqLaroJN+x+vp6NDQ0oLq6OidjWVOTQCDzPui7GlN4ODn+JLzL+8PE8YSzU+oqLgsNnxq2w8I2zO/Kg2WWk+HGoNyUULrR0KwwuemJ/BwIKZL3Augd9q258UaMdb0cY44uvNgxxhQ5VnaMMaaFUKXQDF1cpKo7aVqxCYtcqha6qNbF7gfheozZ6cdFKndkh5+gJnzP61E9Wbt2LQBg9erVWcd/7nOfy+ovDUInnXQSAODMM88EkHH11exuhOcnF/W64KdLKI1Mp512GoCMy6zW+OEzfvbZZ7OuNX36dADAqFGjAMQNPNxPhUbdLrV/ep6WPtB7V8MWDUdqLCt6ZccYY4qcQ1rs3HjjjQCAZ555BkBmYFUruKbypFVcM2DFBhcep8pOLFZAA2I19SkHPVrJVZ3QLFWaulS3yYFdA5CJukpobI5a7tkXTgDSKWlFkeGEgNdlOzpp4jPVZ6NpVzlQU+ngz4T9idWbobJ02223oZhQtVEnJKpw5Zu8NjY2oqSkBJ06dcqZ7OpESN2U+FnfaVWA+Hz5fuh27xspF50eA4MGMz2ceFbYsnAOfe5DOFxJdvx6RtkRCy5jeiq4P7TTGOr5bJXTtoT71ro6xpgixcqOMabIsbJjjDEthIvk5OL14GmnpYUW1sXZEbbl69cDyBgpNDGJqgFcPA8K8Sw1/fsDSLgdhsnngbDo3BG2fcLiuDYs5pl1TRUdoovr4cNTScgZF0PjR0zRIZogJV/bagA4McQjnXVWamVO9YkGBT2fLFq0CACwYMECAMDgwYOzvo/FRWnNo9gz53Fq9NL7irk9K7HCxUWDExQYY4qcw1rsMM6AAajqsqFV5LklmspTK7GzPY2R0fZoFdf9HHwYyKoKlCo5mpGL6P00NbCr5Z4DaMx1gp+ppKiioi4eqhzwmXESxWeWr5ZK8t60aCDb1/gr9pvnsX0eXyyxOjFU4VJ3HA1O5nFdu3ZFaWkpSkpK0L1795wJkh7Pn5cqdTqJ1Otzv/5ctf09W1I/h57XpVIapwvnsAjlMLnxELuTttjSLapCPnNyzSxtQcrhlLffzuxm81dlMsYULVZ2jDFFjpUdY4xpIdOmTQMAvPjii+h8wQXYi4zHIABUhMUiY2w2hNiXutGpMqpUdlQVUPUjXWOGDYfFa01YZNYGY0NvUR9oLOF1lMrKSgCZxfPJJ58MABgxYgSA3DiYWMINVV+SKogeo8fyHhkfREPR66+/DiDXDVlh4hkqRJoWX5PBaOyO1sFRJUddUIkqNXp/NCTxOK3bU3R4sWOMKXIOa7FDFwkqJzEZX2NsNE5E6+povRyNlVFFR7OsaW0aVYQ081ZM4WG7Goej6k3yntSSXygFrcZ6xAKWVenRgnvqXsLJCmH7GkRLtF4Onx3b0eKH3M6YMQPFyNSpU7M+P/LIIwAy74hmFtS4svLy8rSyc9xxx0Ung/rOa80m/jw0058qO9oes7ipIteT3kqcnIR6OwUlF6ZdY50eKjzpYBw5PuwvZ7uqBBljjDHGdACs7BhjzCGwtqQExyOxPhyY+DIoMOUh9fepwf2vPMSlsPaL1mjRRXGOASksMhkLxDUpz+NimEldRoRF/fIe2SdsXLECAPBuSDJzyimnpPoXFt+xzGNEE3bkqymj7sKxNniPQ4emniSNWFR4YnChr2n91eCghqdYLFGhuCRVcNS9mQYgPb7YlR2H7Bhjip3DWuzMnz8fAPAv//IvAAoPNrEaJhwkqF7Qus6BlAqPBgVzYKYVXgv6aZ0cjblRhUlVGFVpVKHKV2dH05CqewrvNRY3RNRVgoHCvFc+C81Ux2eg9XqIxvpoBj1V0zRWhz+jbdu24WjihhtuAAD84he/AJB5Dky5q6mDWWOnpKQEH3/8cc673tyAbr4n+u7mq+uT7JfGgPHn/OELv0FZWRmGjB0LAOjPHz8n4mHeVcPJNyfBnLHTX4rnMWtbuezvKZ9Du8zSlv+ujTHFhr3YjDHFjpUdY4w5BFi/taJv+E9S2RF3vnJKMWHWqMVs1eihqeA/3pFqYEe/VJ43Nsc+qOpAY0i6KGy/7BOGBbfDTqemdsRqyaiCo8aVHaFfTJGeVKJocGFMDd2dY660Gj/Ea8QyyfGaqqiogUGNVrEYIlVsdH8hZUf30yBBg0Wx4sWOMabYaZXFzk033QQAWLlyJYDczFNUajgo8XstIqfKjh6vReI4sKpio/EwWjMlVkyOaof2X11K2L/koKjZzvidpjPVc7U+j7qDxNKj8ni2p3VjOCmJBd/yXmNBuKrOcbLDoOBijdUpxJQpUwBkFB7eL58z09nW1taivr4eJSUl+Oijj3ImibG0tYq+D5zc8n3Rn7e+X6oAcd/6Z55BSUkJ3kj0mSoV1cHy8nLUnnACAGAQs60xd7IqN5ws05+FMTpBIap5O7V9Lewe2+RdG2OMMca0D1Z2jDHmEEjH6HAheHziy1rZBmge4cKTi+FYjRfNMMY6On1CO1pYWY0oz/3kJ6m+3norAGBoWJSWhL7+KWRCGxbq+aj6wfZoRFEDFY9jGYJkeQHNgqYGAyZX0ZgePoPTTz8dQKaI9cMPP5x1r+rayXb1HmJqFe9Bi1CrUUyNY7ECxOqqzC2TyhQrVnaMMcVOqy52tmxJpWziAMw/9gzG5WCnMS86ONC63atXqmZILA2qBoDGat1oYKrGrXBw1fa0Lk+s/k7yGqoiqTrEe9F6N0QnL+rWoi4aGvOhrhNMPcvPqpJp7I7eI9vjhOLaa6/FsQAVHk6w+BypmHXv3h11dXVpZSeWRS8Wm6WxVPzd4DvInwuPV7cnzUiYfG+03hR/dvli6tLTNsbmvBG2nMDHJvSM4dmaffrYSCFIY0xx4gQFxphix8qOMcYcClwIcgGYNH8fzLMPSC8uY3EkNH6owYioO2MsAQYXxyNHpqr/HFy/HgDw21Dv5/jQPyo6auRQwxBVGC7CacDSxCrJ/qpapenw82VwS36mAWfUqFEAgIkTJwIAli1bBgD4j//4DwDA+eefn3V+LOubKi9Uo3gvVHZi2dpirsT6M9GCzcXu8mtlxxhT7LTqYmfmzJkAgIceeghA5o89M3dpHAsHM7p06ICryovGl2jqUi3mxsE0pmJo5ivNcKWKD636tPInU4pyctG7d++se4wV4WNfuNVJjlr+9dnw2enArsoQ4zO4Vas/B3qdeGjc0s0334xjEQZV8+dB15kdO3agpqYGpaWl2LFjR467kdbL0Xdea0Hp+8J3VjMNJmOGgMwELTnJ1EmYqn1J9ZEB7ulYnQ1hywh4wgOp8FDK6Zm1wZrQthUeY4wxxnQErOwYY0wzqayszHx4W75MJvHi2jP4/zSGz/8bdtN4oMaKTqEOD00bn4Rt+bhxqe8jNWvUfVZdedNGjM98JrvPEyYgH7GMZUQLPWu8CxCPQ4rdg95L7Jo0OHART+VEE8yookN4nrorx+5Zs7ORWCFp7S8NYKSqqipvex0VKzvGmGKnTRY7t9xyCwBg8eLFADKDAa3kjMXhoMdBgYMVB04d1GjdVis4P2vQrFrTNXYnNsipOsKMXO+++25W/5KwrX4hNSwL5KnrhrpsaKY3zbKmbixaF4fPjsdpili2y2dLpYDt0NpPlw6mc1Vl4ljliiuuiH63ZMkSbN26FdXV1ennx9pTh8rChQsBAH36pELQ+T7xd4buRDqBTAaG6yRMsxwm3/MSCoih+GVa4eFnSjZUdpLplRPHlYfzzvpfGGOOIrzYMcYUO1Z2jDGmmeS1yn8hWPQPJPbRDTAkcNgdFoWXhN33v5ZK0l0RPp8VtiXnhP+wyCsXnS++DADYuSnVsLpNxhJXkFiMEBfCmuRFCzlzUc0Ma9y/c2eqiuz777+fegQHMg+BC/W+fftmncutxsAUihviZ15ze4g3GjgwtQKngUDTs6ubM++NWdLU/bmQIYnncz8NSTRs8Xw+E2aTK1Ya4AQFxpjipl0WO7RCczCKqQscJGi95mCj32ucA9tnPEMsiDdW9C2m7DC73B/+8AcAmcGMRe+SwbmM46H6Q0v/GWecASATlxQrXKdxRDqZ0TSpfCbsKwdi7tdnQ/hMVJ2icsDzdu/eDQCYNm0ajkUeeeQRAJnncc011+Q9buDAgZg1a1arXXf27Nl59//6178GAAwYMABA5ndIs/sBmT5rJkCtZ9XQ0IAXq/47Kz5s7AXjsi/MObNmZ+MpDMQPsyF53YwxxhhjjihWdowx5nCgq9/xeb4LCg/XjHQKzVF0vhz+84WwpbITlCEMT236npNada7flPo8KBglVAWJFbPlApiqBt1W9XwamqhiqDusFr3l9ZKKkrpa8jMNLTyWbWihYy0KzWuo0UxjgGIxP2pg4vnqzqwlEaiWsf/c8tmoEsT9xa7oELuxGWOKnXZZ7HAQ42DCWBxmMKMioxnJOBhpTE6s3o0OquqWEAveJfxMVYNuCOw/3SWo0iRhn3guXS3eeustAMCZIeUrj4tNRggHbB3I1R1F45Zi6VB5zxpIzHgmbTfpjnIsosrXkiVLAACTJk06Et3BVVddBQBYtGgRAOCkUAyS7yJ/jkDuO6PxYOrGk8xS+MLTz6OhoQHjQyB+CV8Dbqnk0L2K/i2cvfc41Ds0xnREvNgxxhQ7VnaMMeZw0KQNQE7R1c4p2weoOVAMKgmKDUaHLT9zUckU3+JO2HNT/q7ECi8TLuKZcp7utlpUmIYlTR5DlUONK6riJM9Rt2WqSeyLlhZg32kE45ZoHZ6YoqPp81VR0uNiBYHVWKCftSg2n217M3XqVDzxxBPo378/1q1bl/eYqqoqzJ8/H7W1tejbty+ee+65gu16sWOMKXbaZbHDQYGDHgefZAYpIBN/oIXqNPBTVQ+tWVIIVTFUGeJgNmTIkKzjNd1qUp1hG0wzysxzSqF0q4UK4nHg5wRB45m0PT5rrd/D8/kz0Hotx3oWNsZGEY19OlJMnz496/PKlSsBZL9v/H3RzH06qeNEl/Fm/P1paGjA48uWpZWfyZMnA1eG9/KNcBE+Hs3e9tyx/d4Yc6SYMmUK5syZg5tuuinv93v27MHs2bOxatUqDBkyJJ3gwRhjjnas7BhjzOHwg7DAuzthqOAiMEg49PKjeSSdEoIm8y1h+z9hy2xuXFyGYq81obZPlx2pA9Q4EnOP5YKXxhFuaeTQAsua8IRoYVpuNc0/kKv20DWW21isjNbu4T3R7TkWlxQzJNGgo4pSzM2TW1V4tCg1t2yfBiVep70ZP348Nm7cGP1+8eLFuPrqq9NGvP79+zer3UY4G5sxprhpl8WOKiIcGNUCza0Ggqp7A4mlKlV0UCtUZI7HMUMZ2+UgxuOS1n4OoBwQmVGObcfUI6LKjMbaEM3WxgmA1gbiZ3Wx4MCswbWFApuPNebOnQsA+Pu///sj3JOmufzyywEAjz/+eHof3z1VSPmz5s+e7/OUKVMKX2iFFRtjipm33noLtbW1qKysxL59+zBv3ryoCpTEbmzGmGLHyo4xxrQGaxP/p5tfUGgo9NAkwaiOfiH2ppyKDpWccF5NKNL6WthdsX49AKCXGFy4kI3V04kVTGaCCzU88TgujLllchkafNQVOJnGXGv/qKrENrgoV5dbts1rs48x41UsTkmzpNFFVdspFKMTyw7H67Hdm2++GR2Ruro6vPLKK3j66afx8ccf4/zzz8d5552HESNGNHmeFzvGmGKnXRY7OsBy8NBBRdOYxgYdjUVQ9YTEsq2pssPzGLugChPb52Crg3HyHMYlaYwHXTd4j4zt0cmCunSo6lUomJYDeywDHWH/9DwqQM2x+B0LUOHp6Fx99dXp///85z8HkFH99GfMd1Hjf4wxRy+DBw9G3759UVFRgYqKCowfPx6vvfZawcWOMcYUO1Z2jDGmNViWMK6Up4wSu4NJPITaoPHsswEA+37yEwDAa+efDwAYHqQbZmljeZ0/rVkDACgNRg51S1XlRo0hajSh4UiTwTDWRmN3uJ9qDNULqjXccgGdNDDFCiFr7R51a2Yb/F6LPxN+jqlZRBPaaCkDGgFiz1L7yXZ4HO9n27Zt6MhceeWVmDNnDurq6lBTU4OXXnoJX/va1wqeZ2XHGFPstMtiR+NFGNfCOBduCw0yVE3UYl0ozkSVpdj3vC5VD1VZ2B+twQJkBkxODlSF4jNgnETPnj2z7k0H6piCE4ut4fXZPicYGi+lEwd1AdEsZKb46KhuNMaYtmPSpEmoqqrCzp07MXjwYHzrW99K/92fOXMmzjjjDFx66aUYNWoUSktLMX36dHz6058u2K4TFBhjih0rO8YY08r8dzCFv/vwwwCAAQMGAADq/9//A5DIalZVBQBYH4wjXS66KLU/KDrq8kvjSKF4Fa2XoxnFNImFZhqLFWqm+kKDDxUdpjFPFiNW1132henz2QctGcDjCK8dMwjFEs+omkUjmRqtaIRTo5yWRlBlh/Dej7TrLwsfN8Udd9yBO+64o0XtWtkxxhQ77bLY4SC0e/furM8ac8NBiAOqxuzwPE1JqhOAGLyOqiIcTBlHQ7cEDn46qHKwZYxPsg96b4T3pOlYY/V1SGwyw76pUpOslZLveN3qdVlbxUfhOy0AABL9SURBVBhjjDHGmGLHyo4xxrQyFwQjwwXhczI1OBDP9NXp1Vezvlc3Vt0fywym53G/Zl3TOBbNiEb0eI2LoVqTPI/71LDDPnCrhiJVdmLFomP3rgYiLWqtMUKxmkNslwqVFpPmvW7ZwiJJRydWdowxxU67LHauvfZaABmZnYMSB8OYq4a6C2gxOg6CHMRUzdBBS90UeFzMNUSzwungmSy4x77ouRoHRFcKnqvxQoz54fk8Tt1RtGaKuqlotjUO7DGFh4qOKlLGGGOOXbzYMcYUO1Z2jDGmjaELL9HsZ2rgibmvxtxdVW1QQw4NPDFliFC9ULVDDUWatIXGFdbtAYAePXpkfRdTqTSZiyaIifVZjVDqDq0qFw1BGkPE62kdIG2fBiF+z2Qws2fPxtGMExQYY4qddl3sTJo0CQCwfPlyABlFhmi8C1ULDsBEB09mENOsbhzcOLHgQM3jNQhXg3RVAYplSst3DAdets0t+6j1cGI1hWIuFFoDKKYAJdWnZLu8LtvtKEG2xhhjjDHGtBZWdowxpo2ZNm0aAOBHP/pR1n5NqkJjBY0RWk+HqgQNOIoaM9QVV40rbFcVHRpZaHCigYif6RZLJUeNMEBcudH9qtyoK60+I3V7jsXqaPyRGqnYV+2f9kv7x2c0depUHAvYjc0YU+wckcUOB8wPP/wQANCrVy8AmcGIA68Wn+MAz0GKgyIHH56nA3s6zasMdlpUTgdLVZp0AsL+AbmuEbHifhoro64ZOkDHjtcBXwv2cTLCdjl5URcQumKoAmSMMcZ4sWOMKXas7BhjTDuhRgnNJKY1XmgkUdddTdtfKDubqiCazEWVHcan0BhCYwlVDio6MXUluU+TsdBdOJYZrlAJgVhGOO2LGqXUYKTX41aTzRCtx3Os4MWOMabYOSKLHcbuLF26FEBmkOnZsyeA3AGcgyIHp5jSogGq/F6Dc7lVZYfoxELbZ3uMvwFyY2Zi6VR5LZ2EqEKj98BrqxuKBv1yYOd12Q8O4Gx/3759AIA9e/YAAG644QYYY4wxxhhzNGFlxxhj2omBAwcCAD744AMAwKBBgwBkjBM0VtCQQmNFvpgYIGO8UKOHnqfuq2rAUWOKKj10IWaGNSaXidX3yfedZjvTeKTYPRLNjqZqkiaJoVGKyVf4TGMxObpVFYz9ZimFY4UGOBubMaa4OaKLHQ4idJXgZ9bf0ZozGluj6Va1EF4syJdKEQc9tsvBMTlgJ9vh93TxSCo7nFxwH5UUzc7Ga2mqWX4fO1+DdmOxQZpJjvC6dEexomOMMaYQdmMzxhQ7VnaMMaadmThxIgDgySefBAB0794dQK4Co4WTaRzR9PlUQ2jIoZFEXXJjRY/ZrrbTt29fAJliyOyPKkSaOCX5fxp2CI1FGgfEtjWTnG6JKjkaw6PqFLfsj6bzj/WX/dy2bRuORbzYMcYUO0d0sXPdddcBAH72s58BiGcs48BLYilBYwGq6qKhEwpuNQOaxuxwgsHBL6kkqfqj19a4IC0eyIFYn4EqOuqyoWoX21UVin1mrI4VHWOMMYXwYscYU+xY2THGmCPEhg0bAABnnnkmgIyCQxdeLXRMY4Wm2ed5mrhEk73EsrSpQkSlSRWfWC0cohnMkm1QHWIbdNnVc5oq3py8diEDUr44ouR+/axGMra/Y8cOAMA111yTc2/GGGM6Ph1isRMrzvbQQw8ByAy8HNCp9Ki7gaobMZeN2CCpyo66anBw5mCbVJw0ZofKCvfzHE1rqqlmeU29lk4ueA8xBUmLAHJ7yy23wBhjjGkOjXCCAmNMcdOmi52qqqrDOj/fxLy6uhrPPffcYbVrjDEdgXnz5gHIuPIOHz4cQK5RhMYLrb9DY4q66hJNcBLLzsbjqCjFUueru63GxSRVGqpQVIWo7NBopUlaVH3S4s7ququqFdEaQlocmudpxjpVrZg450tf+hKOZezGZowpdjqEstMSjjvuOHz+859v1rGLFi0CAPTu3RtApo4PB3RVgrilCqIDOScanIhwmzyXx3Cg52RCC+hp9jVei+dxoGXMDdvleRzI586d26xnYYwxxrQUL3aMMcVOaeFDWp+qqiqUlpaiW7du6X///M//nP5+165duOqqq1BRUYGhQ4di8eLFR6KbpoNS6P2prKzEcccdl/7utNNOO4K9NaYwU6dOxdSpU/Hee+/hvffew8GDB3Hw4EHU1taitrYWjY2NObEm+WhoaEBDQwPq6upQV1eXPq++vj7rHyktLUVpaSnKyspQVlaGTp06Zf3j9zU1NaipqcGBAwdw4MAB7Nu3D/v27Ut/Zn95/YaGBnzyySf45JNPUF1djerq6nQbJSUlKCkpQZcuXbL+6TX5j/fAdkmsrzye/3g9PhP2i9937twZnTt3Tn/ev38/9u/fj3feeQfvvPNOm/y8jTHGtB9HTNkZOHAgNm/enPe7W2+9FeXl5di2bRvWrl2LL37xizjrrLPSQbzNZfr06Vmf/+Ef/gEAMHToUABAv3798p5H9YXqyq5duwDkxt2o+wSQcTf58MMPs/Yzhau6ZGha08mTJzfjzkxT7w+Q+lnrz98YY0zLsLJjjCl2Ci52vv/97+M3v/kNfvWrX6X3zZ07F2VlZbj//vtbvUMHDhzAr371K6xbtw7dunXDhRdeiCuuuAIPP/wwvvvd77b69Uzb8sc//hFjx47F6tWrcfbZZ2Pr1q0YNWoUli1bhsrKyiPdPWM6FEwJ/8gjjwAAhgwZAiA32xoNL8m6NkBuMWEaZBifonEsmn5f42SoAmn9Hrrd0g2XcTl0FQaAXr16ZV1bY3T02ppJjmgMTqxmEFEFjMdpfJO2T8MT1ZwZM2bAOEGBMab4KbjYueGGG/DNb34Te/bsQc+ePVFXV4fHHnsMTz31FGbPnh11MRsyZAhef/31aLvbt2/HCSecgOOPPx4TJkzA3XffjYqKCrz11lsoKyvDiBEj0seeddZZrZKUYM6cOVmfly1bBiAzQGvMDtUWDoLMCseBnccDmcGfAy1jbzgZoOJDVYgBv0d7vZtTTjkF3/ve93D99dfjlVdewc0334wpU6agsrKyTd4f8ld/9Ve48847cdppp+Fv//ZvvbAyxphDwMqOMabYKbjYOfHEEzF+/Hj867/+K2bMmIFVq1ahb9++GDNmDMaMGYOFCxe2+KKnn3461q5di9NPPx2bNm3C5MmTcfvtt+OnP/0p9u/fjx49emQd36NHj/TiwRQfM2bMwMqVK3HuueeipKQE//Zv/wYAWLhwYau/PwDwve99DyNHjkR5eTmWLl2Kyy+/HGvXrsUpp5zSqvc1evToVm3PGEIjCGPRPvWpTwHINbhQpaCBhlCJ0SQsWmdHVQ4Sy4jG/Wrc0Xo8QEaNSiZyAXIVHFWZYtnTVOEhem9aPJrf85loun66K7/77rsAgClTpuR9JsYYY4qTZsXsTJ48GQ888ABmzJiBRx55BDfeeGOzL/DCCy/gsssuA5CKlVm/fj0GDBiAAQMGAEgN4vfeey+++MUv4qc//Sm6deuWHnzIRx99lB7kW5OJEyfm3f/AAw8AyCg6mpqUg3dS2dEB+I477mjdzhY5M2bMwBVXXIGHHnooZ/LTFC19fwDg3HPPTZ8/efJkLFmyBE8++WSrZ65rCzdOY4zpSFjZMcYUO81a7EyYMAGzZs3CunXr8MQTT+Dee+8FAMycOTPtW65wYnrRRRel0yfHKCkpSS8WRowYgbq6OmzYsAGnnnoqAOC1115rcXIC03HYv38/5s+fj2nTpuGb3/wmvvzlL6N3795t8v4cyvfGdFSYsOQf//EfAWTq8HTr1g1ARqXQosRazFjVE+7neZoCnwoNDRM8jwYeXleLHifjZ7SIM7fsG0sAaBForQ3EvmmhZV5LSweoIqTH8Z737t0LAHjvvfcAAF/96ldhcvFixxhT7DRrsXPcccdh4sSJuO666zBu3Lh00OyDDz6IBx98sMUXraqqwsknn4yTTjoJmzdvxp133okrr7wSQKrw3NVXX40FCxZg0aJFWLt2LVasWIEXX3yxxdc5VGbNmpV3/9KlSwFkJgActIF4gTuTKpw4ZswYLFq0CLfccgtmzpyJX/7yl23y/uzZswcvvfQSLr74YnTq1AmPPfYYnn/+easwxhhzCDhBgTGm2Gl26unJkydj0aJF6Urfh8Pvfvc7XH/99di9ezf69OmDCRMm4J577kl/v3DhQkydOhX9+/dHnz598MADD1jZKVJWrFiBVatW4fe//z0A4L777sPo0aPx6KOP4vrrrz+kNpt6f2pra/GNb3wDb775JsrKynD66adj+fLlrrVjihrNDPb4448DQDopB7dUSzTzmaodVFGo0FA9ZewP41sYd8N2YzE/VG2SqGrEc9hXVYVUfeX57BvjNnmc3iM/q0LEdpgkZufOnQBSHgvGGGOOfpq92BkyZAi6du2KL3/5y4d90dtvvx2333579PvevXtj+fLlh32d1kbdJZIxOxoka1JceeWVadUFSLnfvP3224fVZlPvT79+/bBmzZrDat8YY0wKu7EZY4qdZi12GhoacN999+Haa6/Fn/3Zn7V1n4wxxjTB1VdfDSBTj4cKDNUNxtxQ3aC6ohnKNKZH6+hQ+dF4G0K1hIoQj893TSo6dANWVUj7pvFIvAaP10QxmuWNx1EZ+uCDDwAAN910E0zzKbTYKWmvjhhjzCFScLFz4MABnHDCCRg6dChWrVrVHn3qsMSytxljjDFHI4UWO+VNfGeMMR2BgoudioqKgtmwjDHGtD+sx0OFZ9iwYQByY2qoyGgafc3extgcqiKa5U2VIpYJoEJUXV2d7hu9AKg6aW0gHktFh99rDA+vzTgircfDLftEBWjXrl0AgEmTJuU8N2OMMccOzY7ZMcYYc3hUVVUd6S4Y0yIa0HQ2Nis7xpiOjhc7xhjTjjz77LP49re/jd/97nfo1asXNm7cmPe45557DpWVlbjrrrtw9913N9kmFZ6FCxcCAE4++WQAqWQvQKYujyo6qqqoWkIVRjOrbd++HUBGAWLRZ8bwJNEYHHoKsE0qPxp7w2urosP9qhCx3ffffx+A6+a0Fk5QYIwpdpw6zBhj2pGKigpMnToV3//+96PH1NbWYt68eTj33HPbsWfG5MLFTuyfMcZ0dKzsGGNMC3jssccwbdq09Ofa2lqcf/75zXZRGzduHMaNG4fVq1dHj/nhD3+ISy65JK2gNJfZs2dnfWYsDwtBU+lhPIwqOhrbo8rOhx9+CADYvXs3AGSllQeAX//61+n/U3GhMkNl58CBA1nXjNXJYR/0M9thbM7WrVsBoFXKIhwLrFq1CvPmzUN9fT2mT5+OO++880h3yRhj2hQrO8YY0wKuueYa7N+/H/v378fWrVtx8sknY9KkSfjud7+Lnj17Rv81l02bNuFnP/sZFixY0IZ3YY5F6uvrceutt+Kpp57CG2+8gSVLluCNN95o8hwrO8aYYsfKjjHGHAINDQ247rrrUFlZmY4PaQ0r+W233YbvfOc76Tibw4GxPOSXv/wlAODEE08EgPQiTGvWaHFkqihUdGJQtQGAnTt3AshVj5htjZnfmhuLw8xv7MPmzZsBAHPmzGmyTybDyy+/jOHDh6djuq699lqsWLECI0eOjJ7TiKYTFBhjTEfHix1jjDkE7rrrLuzbtw8//vGPW63NlStXYt++fbjmmmtarU1jyJYtW3DSSSelPw8ePBgvvfRSk+d87vOfTy9c89G3b99W658xxrQFXuwYY0wLWbp0KZYsWYI1a9akY03uuece3HPPPdFzmlOv7Omnn8Zvf/tbDBgwAACwd+9elJWV4fe//z1WrFhx2P3+yle+kvV50aJFAIA+ffoAyGRt4z0x+9oHH3wAAJg8eXKT7auSBADLly8HkFGRqORodjZuVUVq7rVNYRirlYSKW4xjvZi4Mab48WLHGGNawKuvvoq5c+fiP//zP9GvX7/0/q9//ev4+te/XvD8hoYG1NTUoLa2Fo2NjaiurkZpaSnKy8vxne98J8sVbt68eRg4cCD++q//uk3uxRxbDB48OJ2aG0i5Ag4cOPAI9sgYY9oeL3aMMaYFrFixArt378aFF16Y3nfRRRfhqaeeatb5zz//PP7iL/4i/blr1664+OKLUVVVhe7du6dr1vC7ioqKdBa11mb69Olt0m6SCRMmZH1mLSDGCVFZoIo0a9asNu/TscrYsWOxYcMGvPvuuxg0aBCWLl2KxYsXH+luGWNMm1LSmE/XNsYYY9oAL3aOLE8++STmz5+P+vp6TJ06FXfdddeR7pIxxrQpXuwYY4wxxhhjjkpcZ8cYY4wxxhhzVOLFjjHGGGOMMeaoxIsdY4wxxhhjzFGJFzvGGGOMMcaYoxIvdowxxhhjjDFHJV7sGGOMMcYYY45KvNgxxhhjjDHGHJV4sWOMMcYYY4w5KvFixxhjjDHGGHNU4sWOMcYYY4wx5qjEix1jjDHGGGPMUcn/B4Fc/4LQq/p1AAAAAElFTkSuQmCC\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for stat in stat_files:\n", + " plotting.plot_stat_map(stat, title=stat)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['/media/Drobo/work/KPE_SPM_ses2/Sink_ses-2/2ndLevel/_contrast_id_con_0004/spmT_0001_thr.nii',\n", + " '/media/Drobo/work/KPE_SPM_ses2/Sink_ses-2/2ndLevel/_contrast_id_con_0002/spmT_0001_thr.nii',\n", + " '/media/Drobo/work/KPE_SPM_ses2/Sink_ses-2/2ndLevel/_contrast_id_con_0006/spmT_0001_thr.nii',\n", + " '/media/Drobo/work/KPE_SPM_ses2/Sink_ses-2/2ndLevel/_contrast_id_con_0003/spmT_0001_thr.nii',\n", + " '/media/Drobo/work/KPE_SPM_ses2/Sink_ses-2/2ndLevel/_contrast_id_con_0005/spmT_0001_thr.nii',\n", + " '/media/Drobo/work/KPE_SPM_ses2/Sink_ses-2/2ndLevel/_contrast_id_con_0001/spmT_0001_thr.nii']" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "stat_files_ses2 = glob.glob('/media/Drobo/work/KPE_SPM_ses2/Sink_ses-2/2ndLevel/_contrast_id_con_000*/spmT_0001_thr.nii')\n", + "stat_files_ses2" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for stat in stat_files_ses2:\n", + " plotting.plot_stat_map(stat, title=stat)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Now lets look at difference between the groups (Ketamine Vs. Midazolam)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of Ketamine patients is: 11\n", + "Number of Midazolam patients is: 10\n" + ] + } + ], + "source": [ + "# lets see the difference between groups\n", + "import pandas as pd\n", + "allDat = pd.read_excel('/home/or/Documents/kpe_analyses/KPEIHR0009_data_all_scored.xlsx')\n", + "medDat = allDat[['scr_id','med_cond']]\n", + "medDat.at[17, 'med_cond'] = 1 # change subject 1464 medication to 1\n", + "medDat = medDat.append({'scr_id' : 'KPE1468' , 'med_cond' : 0}, ignore_index=True)\n", + "medDat = medDat.append({'scr_id' : 'KPE1480' , 'med_cond' : 0}, ignore_index=True)\n", + "medDat = medDat.append({'scr_id' : 'KPE1499' , 'med_cond' : 1}, ignore_index=True)\n", + "\n", + "groupList = np.array(medDat['med_cond'])\n", + "groupList.shape\n", + "subjectList = medDat['scr_id']\n", + "ketList = []\n", + "midList = []\n", + "for i in medDat.iterrows():\n", + " sub = i[1].scr_id.split('KPE')[1]\n", + " if i[1].med_cond ==1:\n", + " ketList.append(sub)\n", + " elif i[1].med_cond==0:\n", + " midList.append(sub)\n", + " else:\n", + " print('No medication condition')\n", + "\n", + "print (f'Number of Ketamine patients is: {len(ketList)}')\n", + "print (f'Number of Midazolam patients is: {len(midList)}')" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "medDat.to_csv('kpe_sub_condition.csv', index=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['/media/Data/work/KPE_SPM_ses2_group/Sink/2ndLevel/_contrast_id_con_0001/_level2thresh0/spmT_0001_thr.nii',\n", + " '/media/Data/work/KPE_SPM_ses2_group/Sink/2ndLevel/_contrast_id_con_0003/_level2thresh0/spmT_0001_thr.nii',\n", + " '/media/Data/work/KPE_SPM_ses2_group/Sink/2ndLevel/_contrast_id_con_0006/_level2thresh0/spmT_0001_thr.nii',\n", + " '/media/Data/work/KPE_SPM_ses2_group/Sink/2ndLevel/_contrast_id_con_0004/_level2thresh0/spmT_0001_thr.nii',\n", + " '/media/Data/work/KPE_SPM_ses2_group/Sink/2ndLevel/_contrast_id_con_0005/_level2thresh0/spmT_0001_thr.nii',\n", + " '/media/Data/work/KPE_SPM_ses2_group/Sink/2ndLevel/_contrast_id_con_0002/_level2thresh0/spmT_0001_thr.nii']" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "group_diff = glob.glob('/media/Data/work/KPE_SPM_ses2_group/Sink/2ndLevel/_contrast_id_con_000*/_level2thresh0/spmT_0001_thr.nii')\n", + "group_diff" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for stat in group_diff:\n", + " plotting.plot_stat_map(stat, title=stat)" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['/media/Data/work/KPE_SPM_ses2_group/Sink/2ndLevel/_contrast_id_con_0001/_level2thresh1/spmT_0002_thr.nii',\n", + " '/media/Data/work/KPE_SPM_ses2_group/Sink/2ndLevel/_contrast_id_con_0003/_level2thresh1/spmT_0002_thr.nii',\n", + " '/media/Data/work/KPE_SPM_ses2_group/Sink/2ndLevel/_contrast_id_con_0006/_level2thresh1/spmT_0002_thr.nii',\n", + " '/media/Data/work/KPE_SPM_ses2_group/Sink/2ndLevel/_contrast_id_con_0004/_level2thresh1/spmT_0002_thr.nii',\n", + " '/media/Data/work/KPE_SPM_ses2_group/Sink/2ndLevel/_contrast_id_con_0005/_level2thresh1/spmT_0002_thr.nii',\n", + " '/media/Data/work/KPE_SPM_ses2_group/Sink/2ndLevel/_contrast_id_con_0002/_level2thresh1/spmT_0002_thr.nii']" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "midVsKet = glob.glob('/media/Data/work/KPE_SPM_ses2_group/Sink/2ndLevel/_contrast_id_con_000*/_level2thresh1/spmT_0002_thr.nii')\n", + "midVsKet" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for stat in midVsKet:\n", + " plotting.plot_stat_map(stat, title=stat)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['/media/Data/work/KPE_SPM_ses2/spm_l2analysisGroup/_contrast_id_con_0001/level2conestimate/spmT_0001.nii',\n", + " '/media/Data/work/KPE_SPM_ses2/spm_l2analysisGroup/_contrast_id_con_0003/level2conestimate/spmT_0001.nii',\n", + " '/media/Data/work/KPE_SPM_ses2/spm_l2analysisGroup/_contrast_id_con_0006/level2conestimate/spmT_0001.nii',\n", + " '/media/Data/work/KPE_SPM_ses2/spm_l2analysisGroup/_contrast_id_con_0004/level2conestimate/spmT_0001.nii',\n", + " '/media/Data/work/KPE_SPM_ses2/spm_l2analysisGroup/_contrast_id_con_0005/level2conestimate/spmT_0001.nii',\n", + " '/media/Data/work/KPE_SPM_ses2/spm_l2analysisGroup/_contrast_id_con_0002/level2conestimate/spmT_0001.nii']" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "conFiles = glob.glob('/media/Data/work/KPE_SPM_ses2/spm_l2analysisGroup/_contrast_id_con_000*/level2conestimate/spmT_0001.nii')\n", + "conFiles" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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XFxelEDdu3Bg+Pj4IDw/H0KFD4e7ujjFjxmDXrl0G17hu3TpcuXIFAwcOVOy+9HnjjTdw4sQJ7N+/H2PHjlUaWPXq1UPjxo2VdDItWrTAgQMHcPr0aQwfPhzp6ekm89nR0REVKlQwaERZWVkZLOZy6dIljB49GlOmTEG1atXMPg7IKkspKSmIjIxUbd+2bZuqATF69Gjs378fCQkJuYp/8+bNqFWrFiZOnIi+fftiwYIFKFOmjLK/Xbt2OHr0KIKDgzFs2DB8+umn6NevHzZs2KCEWbp0KTp06IBp06ahd+/e+Pzzz02Ol27Xrh3CwsIQHh6u2q7fuK5fvz527dqFY8eOYcCAAXjrrbfg7e1tMJ57xowZqFmzJt566y188803mDhxIhYsWGBwzk2bNmHbtm0YOnQoLCwssGvXLqxbtw6BgYEYNmwYzp49i82bN+eqImaKSpUqoWHDhvj3339V2yIjIzF9+nT06dMHixcvxrhx47BixQqD4xctWoT4+HgMGzYMnp6ecHd3V338atSogdu3b+PDDz9Ev379sGbNGnz11VeYPXu2ZprWrl2Lzp07G3Q8vPvuu/D09ER6ejreeecdfP7551i6dCl69+6NyZMn4969e6rOFH06duyIVatWwdPTE3379sX48ePxv//9T2lAdOrUCWlpaUYbg1qULVsWmzZtwtq1a9GnTx+cO3cOtra2OHr0KBo3bowJEybgvffeQ7169fD333+jfPnyZsetfw5PT0+sWrUKw4cPR3R0tKrxyWh1+hijcuXK+Oeff9CyZUvMnDkTAwYMwLp161SVKS8vL/Tu3RszZ87EyJEjYWlpiePHjxt0jI0YMQLdu3fHxIkTMXv2bPTv31+phF66dAkzZswAkPWub9OmDQYPHqw6ftu2bfD29ka/fv2UBpyp74ap565r164AgK+//lr5ruTFzrtatWo4ePAgIiMjMWzYMPz666/47bffULZsWbPjsLOzw4kTJ/Dmm2/i66+/Rr9+/fD999+jevXqSpg1a9Zg3LhxWLBgAQYPHoyAgAD8+eefBo3v1q1b46OPPsKMGTMwceJENGvWTNW5ZIpGjRrh1q1bqm0BAQFISEhAo0aNlDDp6em4e/euKtzNmzeVMObGpY+VlRVcXV2xaNEiZGRkYNu2bar9puoa5cuXx6lTp/DSSy/hgw8+wIgRI+Dg4IAjR47Azs4OQFZnjmgn4+DggH79+mHHjh0AsiqoR44cQc+ePTFr1iy8+eabCAsLw5EjR3JtF9+2bVvVexMA9u7di8mTJ+Onn35Cv3794O7uruqwnD9/Pr744gusXr0aAwcOxOnTp7F161aDzrbatWtj8eLFWLBgAUaPHo0qVaoYVKpN1RGdnJzg7e2NBw8eYOjQoRg2bBi2bNkCFxcXADnXv4zRpk0bjB07Fh9//DE+++wzjBgxAitWrMCaNWvw448/4u2330b9+vUNymR+6oHm1IMBdT3Q1HUzo0ePRo8ePTBhwgRMnz4dbm5uWLt2rcF1//rrrzh16hQGDx6MR48eYdeuXVi5ciWcnJyUuuLSpUvRunVrzbzLLQ0aNICtra3BM3bz5k1YWVkpnRHGnkMOx8+huXHlF1N1gXyR1+GLFy5cUMnyGzZsoLS0NKpfv76ybeHChUREqrH/ffv2JSKiRo0aEQBq0KABZWRk0LvvvquKf9OmTXTu3DkCsoaDPX36lH7++WdVmEOHDqmGixizX9JfLCwsyMrKim7evGkwHle8Hq3hi7wEBgYapIcXS0tLql69uoHUao5sbWlpSXZ2dhQbG6vKNwsLCwoJCaHBgwcr254+fUozZswgADRu3Di6cOEC/e9//6NJkyYRAPr4448pJCRECb9t2za6c+eOatjg8OHDiYioTZs2BGQPr1q6dKlRaXXKlCnUqlUrioyMpOXLlxuE+eijj+jKlSvKf74nRERPnjzRHFPLQxPLlStHVlZWVLNmTdq+fTulpaXR66+/rgpjjM6dO5slD9esWZP8/PyU4+7fv0/ff/+9yoYAyBqauGTJErKysiJ7e3tyc3Oj6Oho2rlzpyrM4sWLqVKlSpSamkotWrQgGxsbioyMpEGDBuV6eG1cXBz1799fc//JkycNhpB07dqViLKHw127do0++ugjs84HgBo3bkyJiYkG5dLFxYXS0tKoadOmBICGDh1K4eHhOcZFRHTz5k3FThAAff7555SQkEDly5dX3UP9553fCfr2qeXKlaPU1FT64IMPzLoOc4YFbtq0icLDw6lChQqaYaysrGj06NGUlJRENjY2qjK8adMmVVg/Pz/atm1bjnHNnTuX7t+/r5lOCwsLevjwIXl4eGje0xUrVtCuXbvMvvYZM2bQhQsXNMP//PPPFBgYaLDd0tKSrKysyMrKSvWOcHd3JyKigQMHqsJPmjSJ0tLSVDYzNWrUoJSUFJozZ44q78R3sjhki88xevRoZZuDgwNFRETQd999p1kuTS3ffvstxcfHU9WqVY3u7927NxERderUSdnGQ9hWrVqlbPP396d79+6RlZWVsu2HH36goKAg5b/W885l/pNPPskxrca+G6aeu7wOGRLzf+HChRQeHk729vbKtjFjxhARmT3UauLEiZSRkaG8r8WlUaNGBt96CwsLunbtGvn4+Cjbjh8/TtHR0eTi4qJsmzp1KhGR2XaTqampNHXqVIPtAQEBtGDBAgKy3k1RUVEGYf7zn/8QESnPvzlx8TJ79mzl2xISEkKtW7c2OM5Y3Un/XsyfP5/Cw8OVdyaX++joaPrwww8JAL3xxhtERKr4R40aRenp6Yp91Pjx4yklJYUaNmyohLGysqJ79+7RokWLlG38XdfKy3HjxhFRli03b+vVqxcRkaadWfny5Sk+Pt5gqPiff/5Jt27dUl17WlqaKo2DBg0iIqKXXnqJAPPqiM2bNyciIkdHR83r0Kp/idd//PhxioqKonLlyinbduzYoXouAdDkyZOJiFTPjP6Sm3qgOdfIz4t+PdCc6/b396eIiAiV2ceYMWMoIyNDqYfzN0T/fjVu3JiISDUU0MLCgoKCgui///2vwXny+i5q164dEZHBe6NBgwZERIot2KFDh2jPnj0Gx2/ZsoVOnz6dq7j0l9wMXzS3LiC2H8w1WyDK4/DFqlWromnTpga9lQ8fPsSDBw+U//fu3QMAVY8sb+Me8O7duyMzMxN79uxRKR9Hjx7FG2+8AUtLS9SqVQvVq1fH3r17VefbvXu3ybQ2atQIu3fvRnBwMDIzM5Geno5GjRqpWsxa15MT4pCkPn364PTp04iOjkZGRgaePn0KAGa1zFu3bo1Dhw4hPDwcGRkZSEpKgpOTk+rYVq1awcXFRTXk4dSpU+jYsSOArN7vkydP4uTJk6ptp06dUsWxZ88e1bDBP/74A2lpaejQoYMqTVp50b59exw+fBirV6/GJ598YrBfqxf7r7/+Qo0aNTB37twc8yImJgbp6ekICAhAt27dMH78eFy5ckUVpmPHjmjRooVquXjxYo7xMk+ePEHz5s3RvXt3LFmyRFFJrl69aqDKzJgxA+np6UhMTIS3tzdOnjxp1EtTeHg4jh07hlGjRqFPnz6wsLDAwYMHzUqPPpcvX8Z3332HsWPHGgyLsLe3R9u2bfH777+rnpNTp04hNTVVGW51+fJlzJo1C5MnTzbpadDFxQV//PEHrl69qhp2AmQNkQgNDYWfnx8A4Nq1a3B2dsbGjRvRs2dPzR70vXv3qpS53bt3o2zZsnjllVdU4Y4ePar8NvaeiI2NRVhYWIEpZR988AHefvttvP/++wZK59SpU3Hjxg0kJiYiPT0dW7duhZ2dHWrXrq0Kd+jQIdX/f//9FzVr1lT+lylTBh4eHrh79y5SUlKQnp6Ob7/9FvXr19dUc4kIGzduVA1Tee+993D+/HncuHEDQNY97devHzw8PNCyZUtNT5nM5cuX0bRpUyxduhQdO3ZUDcUEst5dZEQ95WcvPT0dISEhqn2ZmZkGZbpVq1a4dOmSMkwPyBrOe/r0aYP3ibns2bNH+Z2QkIDDhw+rhluJ5dIU3bp1g4+Pj+aQ5VatWiE0NFQ15Iufd/Eajh8/joyMDOX/v//+iypVqhjkrxbG3oumvhvmPnf5pVWrVjh8+DCSkpKUbeZ8X/Xp1q0b/Pz8DN7XDJfdnTt3KtuICDt37jTI6/PnzyM6Olr5zypNbt4Hxsq4WPa1woj7zIkLyBpG2qJFCwwYMAAXL16Et7c3GjdurOw3p67Ro0cPHD58GLGxscp7Pi4uDhcvXkSLFi0AZD3jt2/fxsiRI5XjRo4ciRMnTiA0NFSJ5+LFi/D391eNKPn777+VeEzRrFkzrFixAsuWLcOJEyeU7d26dUNERAT2799v9LhXXnkFDg4OqnsNADt27MBLL72EypUrK9sePnyofAOA7HvN71Zz6oj3799HXFwctm7dioEDB+bbA+qFCxcQGxur/L937x5SUlJU9SlOs74SnNd6oDnXCBjWA8297sOHD6tG7uzevRuWlpZo2bKlKpyp7zIR4cGDBwU6gkU/bn3y8xyaE1d+MFUXyA95apT169cPDx48wJ07d1Tb9V+iAJCammqwnbexDF+pUiVYW1sjNjZWqRCkp6dj06ZNsLGxQbVq1VC1alUAUF42jPhfxNHREYcOHUKtWrUwffp0dOjQAS1atMDly5eV8+d0PVqUKVMGFStWVCouLVq0wL59+/DkyRO88847aNOmjSLv6p/HGLVq1cKhQ4dgYWGBSZMmoV27dmjRogVCQkJUx7q5ueHkyZOKDQGQNYSRP2YdO3aEr68vfH19lUZZhw4dVONvq1WrZrSyFRERYTAMTQzH9OrVC9bW1ti8ebPBvrJly6JLly5GPzgrVqzAokWLMG/ePEyePFkzPzp27IjmzZujTp06cHV1xZYtWwzC+Pn54eLFi6pFP19MkZmZiWPHjmHWrFlo2bIlevXqhQoVKijDj5gtW7agRYsWePXVV+Hk5ISBAwdqlrnt27djxIgRGDNmDLy8vJRynhtGjhyJCxcu4IcffsDjx4/h5+eHbt26Acga0mJtbY1ffvlF9ZykpqbC1tZWacR99NFH8PLywrx583Dnzh3cuXNH9eFmypQpg71796JMmTIYOHAg0tLSVPv1h0gAwJ07dzBo0CDUr18fBw4cQHh4OH777TfVcBVA+xkVh4oaeycYe3+Yen7MYcCAAVixYgVmz54NLy8v1b5PP/0U33//Pfbs2YNBgwahZcuW+PDDDwEYPrum0rdw4ULMnDkTq1evRr9+/dCiRQt8/fXXRuPSZ8OGDahTpw66du0KR0dHDB06FOvXr1f2r1+/Hp9//jlGjBiBc+fOISQkBPPnz9dsnB09ehTjxo1Dp06dcOLECYSHh+Onn35SKvRPnz5F5cqVDWxduLPD2DCxqKgogzJi7H0CZL07jLkpNkVcXJyBHWBoaKiq7Ijl0hQVK1bMcThfbq7B2P23tLQ0yEctxPOY890w97nLL1WrVjV4dpOTk80azs+Yk9dxcXGqhh+QlS8ODg6qfNSqS5j7PoiKijIYwgVk2dxy3FFRUXBycjJ4jlxcXJCQkKAMsTcnLv1r4cbYgAEDEBERgTlz5ij7zalrVKpUCaNGjVK959PT09GtWzdVZ92OHTsU204nJyf06dNHZRpSqVIltG3b1iCe8ePHG3T6GaNevXr4888/cfToUYNvozn3mvNDzB8AquHNpu61OXXE6Oho9OrVCzY2Nvj9998RFhYGb29vAzMVczGWpri4OFWlXkxnfuqB5lwjYFgPNPe6tZ7tnL7L/L4vrO8yExUVBQAGzxj/139ejT2HLi4uqjDmxJVfCjNPrE0HMSQ3Y/pNERkZibS0NLRv396o44fQ0FDF2F00NBX/i7Rt2xa1atVCz549cfv2bWW72JuQ2+vp2rUrbGxs8M8//wDIGiccFhamqvyKvexa9OnTB2XLlsWgQYOQmJgIIGtMulghcHNzM2ig+Pr6omLFiujZsyfq1asHX19fpKWloUaNGujZsyeqVq2qapQFBQUZ5JmlpSUqVqxooB5o9Sh88803Sk9ex44dVcpo9+7dkZiYqOSLyOzZs+Hq6ooVK1YgLIEjfmAAACAASURBVCzMqC2bn59frm2x8svhw4dx5coVA/sA/sCaw+7duxVbmLzOkxcYGIhx48bBwsICrVq1goeHB/bt24fatWsjOjoamZmZ8PDwMFopDQwMBJCldkydOhVTp07Fq6++is8++wy//fYbrl69ips3bwLIuudbt25FkyZN0K5dO4MXtoWFBfr06YOJEyeqth84cAAHDhxAuXLl4ObmhmXLlmHFihUq422tZ7S45jNs27Yttm/fjlWrVmHJkiUG+4cPH46dO3fiyy+/VLaJRubmMnz4cKxYsQKLFy9WtplTFh49eoQjR44oNlmWlpYqOxQiwrJly7Bs2TLFXm/BggV4+vQpfv31V6Nxbt68GZs3b0alSpUwZMgQ/PDDD4iNjcXcuXNx8uRJ2NjYoGvXrvjrr7+UYy5fvgwguyzpY+x9EBQUZNRw2dXVVXmfcCNLbLgYa7Q5OTnBzs5O1TCrUqWKUna0ymVORERE5Gg7auydKF5DQSHmobnfDXOeu/wSHBxs1JGDk5OT2XFERESgYcOGmvuDgoLg5OQEe3t7VcPM1dUVCQkJeerI0uLWrVsG7/OaNWvC0dFRsTe5desWrK2t0bBhQ1UjSbRdMScuY2RkZODatWuoX7++ss2cukZkZCT27t2rdOjoIzobmTdvHjp06IB69erByspKpW5GRkbi/PnzRjtBU1JSckxD5cqV8ddff+HRo0cYNWqUQd3MnOcKyHp+9Z8jtmXLzbNlTh0RAM6cOYO+ffvCzs4OPXr0wNKlS7F169Y8OazJC/mpB5p7jcbqgeZct9azXZzzDDP3799HamoqGjVqpBqx0KhRI2RkZCjP5q1btxTBQZ9GjRopna3mxlWSybVSZmNjgx49ehRYo+zYsWOwsrKCs7Ozgfpx8eJFpKWlISAgAEFBQRg0aJDq2CFDhuQYt729PQD1C6ht27aqXoTcXo+zszMWLlyIu3fv4siRI8p5xF7kt956y+BYY61pe3t7ZVglM2LECNWQmGrVqqFZs2YGabx27RqioqLwxRdf4NatWwgPD1cmQ/7iiy8QFxenVLQA4OzZsxg8eLCqZ3DIkCGwsbFRyfI5kZaWhmHDhuH27ds4cuSISrp3c3ODj49Pjl4V//Of/8DHxwdbtmxBly5dzDpnQaI/bIIpU6YMatasqakOmkNsbCwWLlyIP/74QykXeYWIcPbsWXz11VdwcHBAnTp1kJiYiDNnzuCll14y+pwYe7leu3YNs2bNgpWVlapS8fPPP6NPnz4YMGCA0ZdU69atUa5cOc3riI2NxbZt27Bnzx6DBsygQYNUQ3uHDBmCxMREXL9+Pa/ZkWdefvlleHt7w8fHx+hQWyDr+RMrKMaeXXMQ47K0tDTbg+S6deswdOhQfPjhh/Dy8kJMTIzRcE+ePMHChQtx7949sxqP7KFT36PZyZMncenSJXz33Xcqz5255ezZs2jevLnKSUn16tXRrl075X0SGhqK1NRU1RAuBwcHzYqSvnMMBwcH9OzZE+fOnQNgulwa4+jRo+jdu7dmB97Zs2fh6uqq+tjb29vDzc3N7Hcik1s1x9zvBmPsucvtObU4f/48evbsqXwzAdPfV5GjR4+iadOmBt6V9c+RmZlpYBA/bNiwXOe1KQ4ePIjevXuryvfIkSOVCaIB4H//+x9iYmIUtQnIuicDBgxQDdU1Jy5jlClTBs2aNVOG95pb1zh69CiaNGmCGzduGLzn9d/XN2/exLVr1zBy5EiMHDkShw8fVjV2jh49ioYNG+Lx48cG8eT0PnZwcFA6/vr372+gbHLcFStW1Ox0un79OhISElR5C2TVbW7fvm3gVConzKkj6pOcnAxvb2+sX79e9Y4saIVHJD/1QHOuUaseyGhdNwD07NlT5RhqyJAhyMzMxIULF/J6uQVGamoqjh8/blBWRo4ciX/++UcZRnrw4EFUq1ZN5RSoefPmaNCggfK8mhtXSSbXSlmnTp1gaWmZ48soN9y5cwerVq3C9u3bsWjRIly4cAF2dnZo0qQJXnzxRUyYMAGZmZlYtGgRlixZgvDwcPj6+mLo0KGqD70xzpw5g7i4OKxZswaLFi1CzZo14eHhgSdPnph1PdbW1or87OTkhObNm2Py5MkoW7Ys+vTpozQ+Dh8+jGnTpuGHH37A/v370a5dO7z99tsG8d26dUtpuMTHx+P27dvKw7hhwwasW7cOTZo0wcyZMxUZFsga8nD37l0DL1FEhNOnT6N///5YtWqVst3X1xcfffQRDh06pLKB+Oabb+Dn5wcvLy/88ssvqFmzJhYuXAgfH59czQ6fnJyMAQMG4MiRIzhy5Ag6deqE8PBw9OvXTzVUwxgZGRkYPnw4jhw5Ai8vL3Tp0kXVcDSHli1bGnwoQkNDVbYtWvz111+4desW9u/fj4CAAFStWhUfffQRypcvr6k6mIu7u3uejy1Xrhz++usvbN68GXfu3EGZMmUwY8YMBAUFKQrXZ599hqNHjyIzMxO7du1CXFwcateuDTc3N3zxxRe4e/cufH19sWfPHly/fh1EhAkTJiA+Pl6p2M6dOxeTJk3Ct99+i8zMTJUXpX///RdxcXFGh8pOnDgRbdu2hY+PDwIDA/HCCy9g+PDhBsNYnZycsHPnTqxZswZNmjTBvHnzsHLlSlV5LgoqV66sPGfLly9X2SXFxsYqeXr48GF88sknOHv2LO7fv4+33norx97+nDh8+DCmTJmCe/fuITIyElOmTFF5z8wJLy8v/Pzzz2jevLmB3eWqVasUV+gxMTHo2rUrXnjhBU2vjh4eHqhQoYIydLFp06bo3Lmz6tkcM2YMjh07hkuXLmH58uW4fv06rKys8MILL2DkyJFmDQfeuHEjZs+ejYMHD2LevHnIyMiAh4cHwsPDlWeJiLB3715MmzYNjx49QnR0NGbMmGG0opeYmIgFCxbA0dERgYGBmDlzJmxtbfHjjz8CMD6E2xQ//PAD3n33Xfj6+mLBggUICAhA48aN4eDggMWLF+PQoUM4deoUduzYgTlz5iAiIgIzZ86Evb29SvE0Bx6NMWnSJGzfvt1kZ4Q53w1Tz11aWhoePHiAESNG4Pr160hOTsbVq1cNKoemWLZsGaZMmQJvb28sXboU1atXx9y5c5XRG+awefNmTJkyBYcOHYKHhwdu376NevXq4cUXX8TcuXNx69YtbNu2DStXrkS5cuVw7949TJgwAY0aNcpxSHteWLVqFT755BPs3r0bCxcuRP369eHh4YGlS5cqalNKSgr++9//4v/+7/8QFRWFW7duYfr06bC0tFR5XzUnrlGjRqFv377KfapWrRo+/PBDVKtWDUuXLgVgft1p6dKlePvtt3Hs2DGsWLECT58+haurKzp37oxTp06phiju2LEDU6dOhbOzMyZMmKCKZ/Pmzfjggw9w4sQJLFmyBA8ePEDFihXRqlUrBAcHY9myZUbPv3v3brz22mt477330KBBA5UX0rNnzwLIKrs+Pj7YunUr5s+fj0uXLqFatWro1KkTPvjgA0RFRWHZsmX48ssvkZ6ejgsXLmDIkCFwc3PL9VQn5tQR+/Xrh/Hjx8PLywuPHz9GjRo1MGnSJJU9lLH6V27eJabITz3Q3GsU64HmXDcAJCUl4c8//8TixYtRrVo1LF68GHv27FG+g8XN119/jRMnTuCHH36Al5cX+vXrh379+qFPnz5KmDNnzsDHxwebN2/GzJkzkZmZiYULF8LX11dlC2dOXEDWKDUHBwe88cYbAIChQ4cCyOo8evz4MYBs78im7PMLFDIBBO8gS5cuNeoBxdgEiMYm+9XyxjV16lS6fv06JScnU2hoKJ04cULlfRDI8koUGhpKsbGx5OnpSaNHjyainL0v9u7dm65du0aJiYl05coV6tu3Lx0/flzxoqd1PewNjIgoIyODoqKi6Pz58/TNN98YeOoDsiaTfPz4McXHx9Phw4epYcOGRKT26tOsWTP6559/KD4+noiyPQa+8847dO/ePUpMTKR//vmHWrVqpZq8ePfu3fTDDz8Y9dby2WefEZHaa9mIESOIiIzO+N6tWzc6c+YMJSUlUUhICP3000+q+5OTlxjxelxcXMjPz48uXrxIr732GqWnpxt4ttO63+XLl6fr169TUFAQ1a9f36yJoXPyvrhmzRqzvOeMGjWKvLy86PHjx5ScnEwBAQG0d+9eatmypSqcscmjxcVUmNx4X7S1taXVq1fTrVu3KCEhgcLCwmj//v30yiuvqMK1atWKDh48SDExMRQfH083btyg77//XvEUtWjRIrp69SrFxsZSVFQUHTt2jDp06KAcf/z4cc085PJ46dIlA29jbdq0IW9vb3r69CklJSXRgwcP6L///a9qwmkiomnTptGKFSsoMjKSoqOjaeXKlaowuXknmHMPtMot/zfG8ePHleMcHBxo/fr1FBERQREREbRmzRrlvnFc5noQrFKlCu3evZtiYmIoODiYFi5cSO+//77qenN6vrZs2UKPHj1Sea/kPDt16hRFRERQQkICXblyhcaPH6957W5ubnTkyBEKDQ2lpKQkunXrFs2ePdvgfK6urvT999/TnTt3KCkpieLi4ujixYvk4eGhmkA2J0+09erVoz179lBsbCzFxcXR/v37VZ7UOF+8vLwoJiaGHj58SBMmTDDqfTEsLIw6dOhAfn5+lJycTJcvX1Z5LTNWLs1ZateuTdu3b6fIyEhKSEigy5cv08iRI5X9lSpVok2bNlFkZCQlJibSiRMnqEWLFibLorGyPH36dHr48CGlpaWRv7+/ZjheTH03zHnuevbsSVeuXKGkpCSz3zfGvtedO3emK1euUHJyMvn5+VG7du1yPdFthQoVaPXq1RQSEkJJSUl08+ZN+vjjj5X99vb2tHz5cgoODqbk5GQ6f/489erVSxWH/vdZq4ybszRu3JiOHj1KiYmJFBgYSPPnz1d5FeXl888/p4CAAEpMTKSTJ0/SG2+8keu4mjZtSt7e3hQUFETJycnk7+9P27dvp5dfflkJk5u6U7Vq1Wj9+vVKPvn7+9OWLVtU8QHZXuWSkpJU3gJ5KVeuHC1btoweP35MKSkpFBAQQH/88Qe1a9dOCaNf3vi/Fvpx29nZ0eLFiykgIICSk5PpwYMH9M033yj7LS0tycPDQzn3jRs3aMyYMSavPS91xBdffJF27typ+q7/8ssvKg+WWvUv8fqNlT9j70BjZTI/9UBT12isHmjOdbMnaXd3dwoODqb4+HjaunUrOTs7m3y+xLRr5Q+Q/4nsBw0aRNeuXaPk5GS6efOm6h3Ni7OzM61fv56ioqIoJiaGfvvtN6OTnZsTl7+/v9Eyrp/+DRs2KO/xnMqm1vcst+8voqzJ68x+CAHQ7du36f33389TppfEpaRfj42NDcXGxlKPHj2KPS05LXPnzqVTp04Vezrkkr+FXfiKFWtzFmMvcLmYt1hZWdGTJ09o/vz5xZ6W4lhMTUGSn3IpF7mUhKWk1zXkUnKX/NQDc9O5KZfiXYiIcj188aWXXsrtISWakn49aWlp+Z6FvCj47rvv8N133xV3MiT5JDAw0GC6B0nhYWNjg9dffx1jxoxBxYoV8z2E9llFlktJaaek1zUkJZfSUg+U5J88eV+USEoiFhYWOc7hpG9fV9SU5LSVBrTm+QKypjigApp/pKipXr06zp8/j5CQEEyaNEmZ10ZiHjmVi+f1mSqsd01JeQblu1QiKT1YWlpqdqgRUY6O4Z5Lcjt8US5yKamLvh2gMfTHbsu0lZ4lJ/swIsqVzYtcnp0lJxtTorzbNpT2ZcOGDTnmizk2Z+JSkp7Bwrg+uchFLoWzaNluEZHKXksuWc0xC6Kcu7fkkBFJaaFatWoqF/0iBe1tKTeU5LSVdBwdHXMc+hMYGFgi5luRFC0VKlTIcXJYf3//Ap9rrDRQp06dHCeXzot3xpL0DBbG9UkkksLhlVde0fRCnJKSUizT5ZRUiAiyUSaRSCQSiUQikUgkxQQR5X7yaIlEIpFIJBKJRCKRFByyUSaRSCQSiUQikUgkxYjJRpmrq2tRpEMikUgkEolEIpFIniu4rWXSpuxZIFRnFxet+3/sl18AZM0RBGS7+mX7ubFjxxbYuT09PQFAcfvJa3bbm5KSolpPmzatwM4tKT6WLVsGALC2Nm/WCQ7Hrp65nHzwwQdGwy9fvhwA8Mknn+QrnRLJs0iXLl0AACdOnCjWdDwLtGhRERcu9Mlh/21cuHChCFMkkUgkzybP9DxlGzZsAAC4CdtfeOEFAFDmVUlNTQUAJCUlAQA2bdoEAIoHp/fffz/X5+Y4bG1tAUCZ+I8bgtwA5DTweu/evQCAhIQEAFC8h3300Uea5/r0008BZDcEJAWDOfnKk/3y/bW3twcAvPjiiwCyG1mJiYkAgKioKADZ95ePq1Gjhup4LpPcqOf/lStXBgA0bdoUAODr6wsASE5OVtLEXhyjo7O6IWJiYlTXI5FIJOaTCSDZZCiJRCKR5I9nqlGWqmvosDPcXrp1mG79+MABAIBtkaaq8Ll8+XJxJ+GZpDTl6+u9sko7q8E3du8uvsRIJJJniAxkv1kkEolEUlgUaqOsbt26WLt2LXr06FGYpzEbnidKVKnS09MBZKsZrFawwrB27VoA5ilmrJBxHKxsODg4AMhWThjxv6je8fF//PEHgGzlbMKECSbTkhvq1q2LkJAQWFlZwdHREX369MHKlSvh6OhYoOcp7fD9dXZ2BgA0aNAAAGBnZwcgWwkVhyOyksXDErnMsUJWq1Yt1fGs2rKixsfVrVsXQHb50qJu3boGitm6desAZCtpU6dONfOqJRLJ84tUyiQSiaQoKJVK2Q1do8pG95+VLxshHPftpVy8CACwKuyElXL279+PHj16IDg4GL1798Z3332HBQsWFHeyJGbAarDlv/+qhjJKJBJJ/jCllOXcQSSRSCQS8yiVjbLc4uLiAiBbvRDVCl7zflbSeM1qBysNFSpUAJCtlgBAYGAggGwFg1U5thniGc3Fybj5nKJtGStlfBwrVuXLlwcA7NYNTwsODkZgYKByvoKgatWq6N27d6kavldYBAYG4tdff0XFihUBZN9Xvh+skPF9YqcxogLKChgfxw0nvp+spHJ54DLJNolOTk6qNW/n86TozuPk5GSg1ol2jGwr+eOPP6rSnJPdokQieV4xpZTJRplEIpEUBKWyUdZE13BhJwvcSOLGF6+5oivJHU+ePMHBgwfRrVu34k6KxEycAwKKOwmS55A1a9YAyPYmq+8tdOXKlQBkY7/0kwEgJof95YsqIRKJRPJMUyobZVwR4EYXqwaiQsBr3s9qBsNqBatTrBhweF7zebjiwbZmbPejH0elSpUAZCsarIxwXKzSMax0cNy8n9PCSgwrcGK8Dg4OsLOzQ0hICLZs2YJ33nnHIL/M5c0334SFhQXi4+PRrVs3fPXVV3mOq7SyYsUKAFn5GhwcDCsrKzg4OCj5zfnPZYLvC98n0aW9qICKZZH/c1nl+87lgY8TlTRxOgd9ZU4sSwyrb2xjxnAaWAnm6Rk4vDhrhrRFk0ieJwjSpkwikUgKn1LZKJMUDl5eXujRowf+/vtvjBkzBuHh4YrqKHm+6aFzp39ETrsg0YM7I7jh/otuDkj9fVIxK+1kAhkJxZ0IiUQieeYpFY2yVatWAchWC1i1EG1k2HuiqDrwmtUF0caGFQWOh+25eDvHx6oIK2TsxQ6AYnPEYUS1jdMgTh7Na1btRDs3TisrNBwPKy3W1tawtbWFpaUlatasiZ07dwIAgoKCAORtcuHOnTvjvffew8yZM+Hl5ZXr40sj7FWxdu3aALLuk7W1tbLm+8GKlKhY6d8PwPD+cpkSyyYjegRltUpUccXwnB59W0VxH5+T01i2bFlV2rTUOa5U65/bxcVFUdT4miZPngyJRPKMkgkgtbgTIZFIJM8+hd4oS0tLU3mDs7a2ViqJkpLLp59+irp16+Ly5ct44403ijs5kmLmwsaNxZ0ESQmEG/rc2cSdCfr7RKc3klJGJoDE4k6ERCKRPPsUeuuoX79+qv9ffPEFvvnmG7OOXb9+PYAsb4BAtlLGSgD31HOjj+d04h5/0SZGS6VghYyPj4uLU23nyoVos8b7gWyFTPTgKHpTFO11OK18br4W0U5OtDHjeDMyMmBpaQkrKys4OTkp8fJ58jp0qHLlynj33Xfx9ddfK3OkPYvs2rULAFCvXj0A2fcxPT0dtra2SE9PR7ly5QzUUdEmjO8j3y/ezmVEVK+0bM/4P5cXUe1iRDsvfbTs2TiNHCenVfwveoTkaxHLNJdVVmfZ1tKc+fwkEkkpgQCkmQwlkUgkknxSqI2yhw8f5uk4nocMumFSksLH2L3Stw95Vnlt+HAAQPDffxdzSiSS0gO/G3iKCO580FfFxOHiklJKJgBpUiaRSCSFTokeR8iu7qtUqQIg2xaGe+xZDWJbMl7z9tjYWACGNmGsNmkh2g9xeFYMWEljNQPQnqdKtFfjtPGa1QZWYPjcfO2iUsbx8Vp/TjUrKyvlWvn8nGaePmDSpEk5XvvzwtatWwEALXT/2aGJvlJmbW0NCwsLVKpUCaGhoQCAqKgoANn5K95v/s/x8HZRrTWllLGqJYYXEefU04+L4xBtJcVjuYxxHogeQ0VlmeMX507jeft27NgBILtMs8ooHT1IJKUQqZRJJBJJkVCiGmVPdZVEnga58uDBAAB24J3o51f0iZI8k/R96y0A2bPvSIfPBcvISaOyfuge5pUfrii+xEgKHB7aKjqJ0e8cEKcm+fnnnwEAH374YZGlU1IASKVMIpFIioQS0SjjoTADTYTjHnmG1Slecw8/22dxD71oY8aIHhJ5zcoYKwgcLx/P+0UHJoChx0eGFRCOg48V1QtWA/kcojc/Y4obESEzMxPJycnKtYve/jg+T09PAEBkZCSAvHlnLM1s2LABAPCmsJ2VKC5L9vb2yj0sV66ckv+slHH+iXZWoqdPRrTvEr0m6ldm9fdzfOJ+EWP7xTInzoGnf31AtjrLecBxcjjxGsT9opdHfVxdXbF27VoA2Yr281b2JJJSiVTKJBKJpEgoEY2y7kLPqa1u7SKsoxs2zFpzwJs3CzllkmcNt/HjAWTXMbjp5PjqqwCyFbM0AOkALFq2LMLUFT8OzZqp/mf8+2/eImJvbWFZq2EjRgAAHuk27/vxx7zFKykRcAcWIw6rBgw7KnhIr6SUIb0vSiQSSZFQrI0yVm1a5fF40faF1QxWm7hHnhG9JzL8n+PhoTn6qgmQrU4Zs/MxNl+U/n9RURHTxOcUvTiyMsZqhzgnW3x8PNLS0pCRkYGwsDBER2c1WblyxHZCbO/D8fK8amvWrAEATJgwAc8y7EGyYy6Ps7KygqOjo3LfuIyEh4cDgJLfogdDLW+c4txg4n4tWzUtj4qi8qYfp+jpkdMuKllcNrgM6lOmTBlNlU6rbOtXzLWoXLnyc1P2JJJSDUHOUyaRSCRFQIlQyh7+9RcAoG7v3gCy1YuyurVtpax1FV3nbBWdVBZaqxYAIPX+/SJIZcnDoXVrOABgtyUNBg0CAFzUTYQsMYSb6WWFNff7c9lLAFAGQPqZM0ivVQvIq2JUQrBt1gy2ALjZxSYiD/btAwC4tG4N6O1nUpA3EnRSpE1W25UFM1zfv19xlCMpvYgOjHg4tv6Qbh4yrdVhJSklSKVMIpFIioRiaZSx57vatWsDyFa88gr38Iue61gx4+2sXojKmmiQLnpbZPWD7bRyst8R7XhE+x2OS/TWyNfA+0XPdaIykpSUZFCBZjIyMhT7O1bE2G5I9ETJFSa2tRo3bpxGrKWTfbpGR82aNfMVD5dR0VaMvTLyHF0cjlVVcd4y0aOhli2ZqOaaUsr04+GyJaqsxnByclKeE2OIw9T008iITh5yqny7uLgoZZ3ziOeK47yUjiAkkhJEBqSjD4lEIikCSoRSxsScO5f1o1XWgEZudCiNj8q6tc6jW5WHWetQ3eTSCAws3ASWMDhfeEDkld9+Uyq6EuPwKBxuWillzEbYkQhYIcu2LBVAabeGoWvXkJKSgmRkN/j1h9KmXrsGR0dHpCGrQRijU6Gdc3mejNdegw2y85nrctEa4SWlE3FaEFbI9Kc9YAdOHEYcTi4pJUhHHxKJRFIkFGmjjG3IWLVg9YaVKdETYW4Re/VFNYH3iyqEaA8kepHj/VzxMKZy8DlYnWBY4eC4WJUQ4+btnAfsRZHXnEccztiErPb29kqaOG9ZleC1mEd8Pr4nGzduBAC89957BvGXJnbu3AkAqFGjBoDs/Mgroh0W3wdWJMVKKq9ZRRLtE7lhxPu1vDfydo6P4+H7aEwpE9U5LpOiPZuWiqdftozN6cfn4rLNz4VoL2kMOzs7JU6+J+XLlweQnZfr168HAIzXOWWRSCTFiBy+KJFIJEVCiVLKmMeHDwMAHHr2zFrzB4HripXV4avo9odWyjI+Ez3r8eG20c9Wfz2rEKlvvGHQGJRk4dy+PYCsegWQpX4B2WVDaX7wD102RiPL+6J1u3Yo7+VlVoNDn/QGDbJ+6ByClDaqhIbmyQaIB0JyaeRnL+n8+YJIlqSEYM4k9JMnTy6ClEgKHamUSSQSSZFQJI2ydevWAQDq168PINvbG/f6i17bRJuVwoIrnVp2XrydbXK07H/E30C2OiF6xxOVLlG14yE+fDyH4zxjlSE9PV1paFhaWsLCwgI2NjbK+cT5zlihEa9BVEk4nTz0qLRVrLZv3w4AqFKlSoHEl5mZiZSUFIP7JXpZFBUyhv9z/nJ4vi98n3kt2vzxeXhYKt9X8T7qNxp5n2hbxmkRr0X0+ChuFxukHL/4XOTUiLOysjJ4rvi/aH/J8fB74z//+Y9mvBKJpJCRk0dLJBJJkVAilTJG6ZwT3TG6CAF0/ysnqjezLuagcyDA3NZVbCuL4fz9yWvHyAAAIABJREFU85fgIsby33+zGnETJxZ3UkoMzUaPBpDtTZERlTEH4T9DusKTiCz79txqRa6dOgHILqKJ1bMMIG1LqWKWWzjfWSGTdTmJpJQjlTKJRCIpEgq1UbZ8+XIAQOPGjQFkz5klTiIqGouz7UtBwSoD98RrwQqBaB9mbGJUwLhSJtpsiXM48X/Rvo3VAo6H84jVDra/Ee3bRBVDtAsS15zXosrB+/k8derUQWli8+bNAIA2BRxvRkYGEhISNPNVy05RhO+TaOPH95Hvi2hzyPdDS03iMqmvUonKl6hMiXOgiYjKl1YZFj1FinZ3+tjY2Ch5JbpKF23e+Jor6YYj//rrrwDMGzInkeTEZV3Z5U6TurkcllySSU5ORqdOnZCSkoL09HQMGzYMX331ldGwu3btwvDhw3H+/Hm0aNEi54ilUiaRSCRFQolWyhRH3ZWFNbuEY4lLkDt4c6JO+RIv8kWd84xQriDnO6WS4qbP2LFGt3PR4KYylymLskIA3dpC1yOcmpbt1TI3iPOdPatzrgbohtNWj4xUbU+9fdtgWghJ3vn5558BABUqVABgOAyZO5zY0QxPzcA00Nk2Dhw4sPATW0JZuXIlgKzOiLbFnJbCpEyZMjh27FiWF9W0NHTo0AF9+/ZFmzbqrqq4uDgsX74crXVzE5pEKmUSiURSJBRqo4znIWN7KNFORuwhZwrKpozts3Kah0kfU66buZLJ6dVPJ6sPxjzY6YcVVQpRdeDj2BOd6LVPTEN6erpKLdNSyFjN4HnPRK9/4lxtXAlkG61Ro0YZzZPiZsWKFQCAkYUUPxEhNTXVwKaL74u41kK0LWOlTJx8lxs0oodCDicqseIcYfqIZYrXoq2YKScmOYWztLQ0uHZOk2gjKtovcnyiV0gug5zXvObKtb7bdYkkN/zz889KeXvWypGFhYUyT2JaWhrS0tKMvhf+7//+D5999hmWLFliXsTS+6JEIpEUCSVaKVM651jKEg1WwtRr/ht161bWDxPDIKvoFDNuhMXGxuY9sZJixXCCgCwMFDJWWR2EHQIu4VkPR26VLg7PZTH9xo1cxlCyida5r+fse6Ibklw5JKSYUvRssmXLFgDZzpG4YarlUIg7bbjBy1MuBAUFAQC8vb0BZA8JFdWT0siOHTsAAAEBAQCyG/mOjo4IDAyElZUVPD09UUs35x53HnBDhfMkUqf2vvvuu0WX+EIiIyMDzZs3x7179zBlyhQDNczPzw8BAQHo37+/+Y0ywrMr+UskEkkJolAaZWvWrAEANGrUCEB2hYIrDFo2KQUN99SLPfCijQz3nPKcYDwESOzB5/A5zcsk2t1oebTTstsRve+JHiFFmzB9myJra2tFYRFtnrTUES2bNL5nrq6uALLtAz/55BODay5OWI0tLFgJ4ga7aMPF90VLKePKMd8X0a6K75NotyjeB1FNFu0e9Svr4vMlen7ksiPaqYkVfk6LOdMB2NraGnhTZMSyz2uxLPM1itfK6WfVkOfS4+d06tSpJtMnkTwPWFlZ4fLly4iOjsbgwYNx/fp1vPLKKwCynudp06Ypz4/ZSKVMIpFIioQSrZQptsVsJMbyA/faPcxaheo+GKm6HlMkSKvk54VOb76ZtwNFd4yCu8bK4Vm7cmsV9eToUQDZDQ2XnAKXQvjRYxW7dmxsgTvmeZ7Ztm0bAKBq1aoADDtnuBEv5jmHEych5w6kaGGORlaJ+vfvX7AXUATs2rULQPbIBs4b7uhwcnKCtbU1rKys4OLiYqAict5wpwN3fPCE88OHDy+KyyhUXFxc0KVLF/j4+CiNsri4OFy/fh1dunQBAAQHB2PgwIHYt29fzs4+MiFtyiQSiaQIKJRGGVcoRPsb0fuh6LmOKxqiPZa5iLZj4tAeUaUS1SKuSLP9EPfkayll+hUjDstqG4fha+G0iXGJKoToMU9U90QyMzNBRIqiI1biTNn7aM1BxcexjUKNGjWMnr+42LBhAwAgj00ys7G0tETZsmWVMsFDXTmfRBWY/7PjBQ7Pa74/fF/5ONHGT1TixPsvhhc9g+rDcfC9FG06tTxIikqyFnycqAozohosOgLhtZaNqThHHz/H/KytXbsWAPD+++/nmE6J5FkmLCwMNjY2cHFxQVJSEo4cOYLZs2cr+52dnRGuNzVHly5dsGTJEul9USKRSEoIJVopU0ZMRAtrRqdusBrxsGJFAEBZVsyecSxefRXlAeTsYuLZRuzAFf9zGWKFx0HnnM5WmONONEqzKAsgGaAzZ5BeqxZw9WoBpLb0UyEsTLPxJck769evB5DdoSU2lEWHP+JUCuLwZ60OKu4sEKclKU1wY5wb92IHlLW1NSwsLGBhYQErKyvNYbyiw6aKuu+Hp6cnAODtt98u9GspSIKCgjB27FhkZGQgMzMTI0aMQP/+/TFv3jy0aNEi7x44pfdFiUQiKRIKtFbFnvBeffVVANk98lxh4AqEOMRGVNL4OLENZi7s2Y4/umL8ptQpcagQf7TFSoC++2muKIi9/FxJElU3jkO04xHTKKoMOWFnZ6eoCbwW50HTUmRE5YyP43jYG2NJobpuUuaiQpwvjCvFotdNLnscju87r0V1ivNXtF8Uy4V4/7XUXmNhxXvN5xQr5uJzISpZoq2aVhkVh4eJadT3HKofjuH4xco2p5vPw3nNeSkVM8nzzGuvvQY/Pz+D7fPnzzca/sSJE+ZFLJUyiUQiKRJKdFe3Il6wmsH1cAf1f1udrdmLd7PWUYWespIBXbuG+Ph4UNtnefYd47j26QPA0P5ctHliuIGvOF3UHeigW4tOGBMBZCDb8ZiWGmmh64DA7dvmJFsiUcFu/tkrolZjW1TC+L/YyaLVwcTheEqM0jiH3KpVqwAYOtvR6uAC1B0NnDesImoNn+XpSH755RcAwOTJkwvwKkohppSyEl2LkEgkktJDgb5Oy+vcZYsfSa4Q8EdPrECIPeNcochr55zo5U2s6DD8cReH/Ig2L3w8/2eFgYcC6YcRPcjxMaLHOVM2XWLaGbGyxXnK6eJrEA3/xeFOWkoZr8W5rTi+zZs3Ayg+99F8/teK+Lz68/8AhpP0cj5yPnE+JghOZ8QKJd8vsYIp3h8R0dZMX20Sy7vohVQMJ6JVhrksiPGKSpmWImaqwSF6YxXVWi1PpHweHvq3evVqAMDEiRONXp9EIskFprwvliuqhEgkEsmzTYnu41I817FC1k63bqhbs+zBktqjrJXzy1lHxvyb1wGQpQttFw/PLqlnzwIA4nWNGq7gcyOIFQEtBxhcsa/etSuAbOeLXJTSdIspx2Oply6pjpdIzIEVspo1awIwdHbEDU7eLjaARbSGu4qdLdw5w50K7B79vffey8fVFC48LJ6d7YhDtEV10MbGRtVRoDU9iehYRuy84E7GkjodSJEh5ymTSCSSIqFAG2UuuolkRSN1LZsS8WPIFQtWJfKLqAyI6pT4sebzijZwfBxX9Dm8vk2OaN8iNgb0jdD1z8GIaoEI7+eKB59PPx4nJycDL4+iV0jRO6SYR6KNlDjfWXHbllWuXBlAdt5z+vh6xKFIebHNMwZfP3sC5Hi4oijmm2gzJqo+ontuLTswU4qqWIb1w5qak06Mi+FzivaRWuG08piPF/NIDMdlXtwvPmeiJ1FRweP3D1Oahp91HTAAAOCgG0dLOmVC18+EmMuXiz5REgkg5ymTSCSSIqJEK2WKnQ/XtV7Wrfvq1ta8obVunVXhxd1fCjllJYNQnZt6vonJDRsiGUCFwMBiS1NpI0hn7F5HN3eP/vRlVgAskFX8InSOPngwot29e0WWRsmzR506dQCY3wEldlyJQ7/FtdbwV+4U4CkaeK6vkqyY8TBxbpRzh4Y43F3fMYylpSUsLCwUT4yAYaOfO25ExYw7trjji9fPLdL7okQikRQJBdoo44+X6HVRNEYXPdOJ4RTFrCATB0NbMUZUOcTtnE5WysT9QHaaRcVMtJMRPchp2dWIaKkHxihTpoyBuhcfH6/6L+a96GGS0yWmv7gqKKx6sGdPU/O3aXkAZPKqmDGsGIr2Upwuzjf22iimS8u+SmutpUpplRd9RIXalN2iFlqeO8VrE+ct4/eBljdGsYzxdq5kcyWZ93MlnRU4hp8tznNWVUsyVbp1AwA4VNJteCFrZaFTJqpfyVo/L86LJCUQ6X1RIpFIioQSrZQpnXMJwlrnbRGV/81aWz/UbcgawobnRCiqo1uX0bUlm+ju5g3dfDuuYWGGB0mMwgoZi7K2ZQGbZADWQI1KUGwqQsMNj5VIzGXXrl0A8t5gFBuwokImwg1ccRJ7HsbMShkP/y1Jc3QtWrQIgOFUJHwN4sTtnCdsU8ZKmdjpJjpuEp0biR1nvH337t0AgCFDhhTwlZZwpFImkUgkRUKBNMrYVfErr7wCwNDroqiMiZ4ARRsW/ohWKYjEIbtiIipeosc8sYdfVI/Enn59uzFRhdOvIOivxQl3tZQpLZszxtraGqacWqenpxt4qNMa5sSI1yaG5/TzPf/ggw9MpKJgYFsuMf/EfOMKFf/n+2HsngF5V8zEoVNamKosm7L30kLLg2FOYbW2a+UJp52Hd3FZ0moIiN4RxedJtDEzZeMp5jEPuROduWhdFx+3YcMGAMC4ceOMhi9ODOq6Nup1zqVLIil8pFAmkUgkRUOJVspY8KpyQfdjn26tE8iUGo2usoanWauoP7LWNj8VavKKHWUgoc6UDq2yVi8fyVqHFHF6SjMGlWMXAOHIyts62ZsdpFImyQNr1qwBANSvXx9AzsOPjSE6jBEn1BYRO7rE4bXi8Gqxwb1nzx4A2cOew3Sq+/Tp03OV7pz49ddfAWR7OeQ0sHr32WefAchWzPhaxWk/uPGt3xmg34kk2qCJQ5/FTgRxGDvHxXPJbdq0CQAwduzYvF56qUIKZRKJRFI0FEijTLQlE5UlUSHjtajeaNl85RXuMeeefq5g8Fr8SIt2SKKXSFFZ0FcY+BzitYmVIvGDr6VU5dfmidMnqoEM5zGnl9Mvei/kPBErLgXlIdNcuIxxulhtEStY4hAlUaXRUmfyi1Z8WvPBmVJCc6ucabn+149bVMC07OxEN+z8/IoOEURFWcuuztS8gVq2ZbxmRYzduPPzy+kSYUWN9/Nzzg2jCRMmGD2uOCDdlAqhzZoB0OuA0klkcgCypLiRSplEIpEUDSVaKasaFAQAeFitGgCg7i7dDv3JpACk6tYPdZur6xwB5LZiW9q4yz90pnScL7JXM+9w3tlGA0hHVt4+yt7PM9+VL9JUSUo7PLG1aBdlavgr4+TkBMCwE4KdmojznHGnhdhwFR0SiUPJ+XhuAHODmN+lPL8ap0ecPkR/GgWxkc1hoqOzniJWviIiIlThuLG/cOFCAIbTcojTdYhKmb5Nmb29vXIecZg63wMxvSLikOlquu/R84JUyiQSiaRoKJBGGX8kRe+KWj3tHE40wBZtUnLq/c8JUXETFTLeLqoqYiNOy3OfWNnQ/y16kuRr54qBlg2Rqe2iymCOwiPOM6W/TbxHot2fWEESlaei8sLIjgdq166t2s6VRn032PrpE+dfE+0c86uUaXkS1FKfTN1fMZ1a3jnNLTfG0qB1jFimRMWLK71ixVtU/USFWazM8rVpeSYVFXJxOBs/v6yEiUq71vuEYbvEoraHNIeQq1cBAAG6a+Z7w+8NF+OHSSSFjpymTCKRSIqGEq2UMRV1lbI7ul7h6pFxRsNVy6PThNJKHVYEdb3WLJ091O3PndXK801Z4X9CIpABwDIVSA0EbHWCBleOS3oJi9R596sgPXAWK6tXrwYANGzYEAAMVBtxknGxoSmqQmKjXRw6zgqZ6GFQqyOM12wzJnZqcMOYVSW2q6pVqxaA7Ia42FDWhxvH3KgWO4LEIdbi0GRuTLMqaEwZA9QTs1tZWcHS0hLOzs4Gk49zHvJk47xdnLeMETvcOC+2bt36/+29eZRU1bn+/5zqgaEBGZtRaY0zv3hxwCEOYEw0oOIUTCQqCoLIIKg3EW9WbkyWK19vkus8xIgYTaIxmquoUeMcjQM4EYjEgVkQQaQZuhvooer3x9nPqVNP1e5q6OpuhvezFmv3qTrDPkNx9n6fdwAAjB49OuucdyeSiJLPGoZhGC1IQSZlmqXNp8IQzUSoA4R8ClZTsyIySxtbwoEMX9aqbmk/2X+NjYmrMZoxTtfROJsdzbrH/TVl+2QyGQ1wOGjismYrVHWSLe+pxvk01e2quTB1OGPYeL5UT6iY6WBXB26qAmmGvu0lV1xhHJ/SlS/mLF89NZ/yFl/Pp/g2dV+EzwifaXVV0/2qOumrtaaDac2UyWeUrnVc1t+nDpL5DOhxNNtqoeIIDWNPYEPfvph9+eX+FZ56qvU6YxiGsRuzSyhlXzhL6YDq1g033uiswaWffNKqx91hXMBTj3XrIqu00TgdDz8cQFYm8uwYCiel0Wuz2j2Tycqdq6zvV07J6O+Wv3ST2rK1a9uoR7nZ7CZSnWt2b8coqjE6EfUl0CG+5ChEk7Zwv/o5W05sNdbM527NiTgnymwZS9bD1UJUV9W4AY6fcRsaVhhTRkMRJ9Ns2Yfy8rAoCtU5dVHmOdMQQ2Nbu3btIqWsU6dOWe6yPGctucDj+uLweFz2m1kjDcMwDKMQFGRSxpecus7ky6rma3XgQlSVUAs8l2kZ3+zc+zhw0PgjbkfVhdtrhkTfSz0X7Lu+8PWYmp1RC5iqiqCqRL6++GLQVLHT42v2Ra6viozG6xQa1pZi7TsOvNg/qiPqPsXluCsT4Fcum4tPXfKtp/dL188Xm6bPQ1OV1qbUMfOpevp7VEVqe9E++55J38RDt9NkF3wWtP9cZv/vu+8+AMC4ceN26DwMwzAMwzAKxS6hlLUVrZPKovlEQ+ONbdmLXZPSpUsBADX77hsuy/dJhKpZibu2QYGEnSVOaWMJtKKNhbl5PdaFhdRqnbqwl/s8O9KnbWEWy85t2ouWh8YDdaPVpCk6MfYlLcmXKManuPkMXTw+jR40xrCfVLc0WRNbLVURL+jNc2ffaSRjH7TemBrFqJD5arRxO+4nHn+XSCQQBEGUiTHXtSI6eVdDlBrSeBwe1yb3hmEYRiEoqFLmyxSoSpjWN1J3FFWJFH1Z6ud03dsoA12tcaXZIbnMl30XOT8lfnx94at7ks99SBUPDkAY3K7xdbq+DrK4jsa4aTyODrIYv+OrYaXH9d2bQsFYMt4LHTTqvedgULNIsr+qktKliirLjs618imW+eK2iE+pJJpsQPefj1zr5YtzU+UsX2bIfOR7ZlSF5T3SZ53PAn8rXJ/PAJUyLuuzwmvb0s+wUXj2PfFEAOm6WbULFrRdZwzDMAyjgOwSSlmfAqkI241TUXZ2aJte5sbxu4rCtzOxl7PiJ90EYEWXLtiKMMvipwAqXOxYlotfM4/LyWCh71ly3ToEQYAtLvanfYH331wGVFfv1gk3mHVxX6fAahFzrf+liWM086C6VOv6PgOVoklZNPaMcOLavXv3jGWqXcuWLQMAHHrooQCAfv36AUgbneLHWLlyJQBgxYoVGcfipJvrsV4ZJ9uq7uVyme7YsWPODJVNcddVA45mg9T1NX6Ox7XYMsMwDKMQFGRS5iviSXQgoMqYqhgaA5JPteH+NChdMw+qS5AOiPS4mq5aj58rpkYHOVorjZkgVfFRJUyzCDY19kj7xf34EgfoflQ50yyMel6FhsVpDzvsMAD+hAiqsrJlv33KJd2xtBhvvhitfLF8+bIq5kNVW8Y58jprVk8diMZ/c/mO6atLpn1X1XR7J1G+Z03xueBprBjvra7H3zd/W6qQ5VKT4/CZmzJlSqPrGW3P53PnZrktGoZhGMbuwC6hlBmN0/744wEAXZ9+OsNSbew4/davR7szzwQAVDz9dMH3v59Tf9UKX2jauxgzo3WhwqXJSfj71LIhihpTfAW6feVH2HI9dZ/OV5SeE2B9LrnfL774AkB6YnzQQQcByFT0qHwtWbIEQNowRcMIj81JNA0SjFPzGfMUNSgVFRUhlUohCAKkUqlGy0fEz1WTBenxdTueO8/HMAzDMJpDQSZltOJrQDbJFzumSlm+ekeqkOnARoPj1T2FFnXN8sbBgA5kNPBbMxbGv9NlX5yLZl/U2DFVF9Tqr1n4uI265mitKc2EyXvA43Ngo+eoMU66XCiYBptWcF+qbg5a850Hz1cVMq7vi08sKiry1t+Kk2/A58uimE+RU4WVz40mfFAFL9ex82XuzBcPp/trar0v3zPr258el9vxnvGZ4LXhNdEYUd8zQviM8JkyQ4ZhGIZhGG2NKWWGYeRljau3RR2EiRYGuhgjIxMaqLQOmCZy4ee+bItc5oRTJ6DcjvujwUndi7kd19NSEQr7VeliKX0lNKiCffbZZxn9ifdB+0plSt3M1Xigk3M1lqkrNdvS0lI0NDSgqKgI9fX1WftRl1+t5cbJvrpM+8pocH+33347AGDq1Kk51zMMwzCMxijIpExfWhobplkX9WWomeVUtcgX26Lrc0BEy7pmXdTt1LVHi4lyWeOO4q49qkpw4KFKh7oNaWA/r50OAHT/ubLxxV11NP5GXXA4KNOBiip46galNd8KPRBhsV0djKq6qTF3mgxAB4LxwrJA0zMMknwZP331x3zKp6IDRz7DTKzAZ5if+9TkOOrSRjQuT9HnuzFFLJlMepWzfNkN88VJ+mrs6faaAILPhg6qeR10csDf6C233AIAmD59eqP9NgzDMAzDKDSmlBmG4aXSuZMyO2SJf1UjB74YMDXOcOJIQxKTnPB7GiVY5kPjmWhQ4npaCkITBqnRwzcR1xg4GpeakxSFiVVoYFD3dr02ajCisUwn25xkt2vXDg0NDQiCALW1tVmqJK+tJgyhAUTdYnk8neT7EkUZhmEYxo7QrEnZbbfdBgAYNGgQgGyLtqoxRAcqfOkpvrTNqqjpQIfH96kNquyxH3yp68uXL2efC1K8L6q+afC4qm6qfGlsmSog7EMuRYfB7fE+sh+qxOg14ABF1Q5VGbX+V6GC3O+66y4A6ayLenwOlDQBgbphseW9V3cwooqXT31NpVJIJpNZg1dfrJjSWMxXLlQp07hIvX/5Mgvm6jOfDVWeNH7Ql4QizsaNG70JEfTcc6Uuj5MvHo9wO40Z08G3tno+7AevdUtlFDUMwzAMw8iHKWW7INVOvYhw2ReNlmOjq9fEJNxFu2lWw6r+/QGEsWMBshUymiEYU9YFRi58RcCJJqjRovGcjNMIsc49bzTyMPmJGoF8k3etc6ZZFtXApfXUClkuQPdFgwyvgU6e9RzUDVUTtsSzLtbX10dGObY85759+wJI3wNeUzX8+FyWc2V9NAzDMIwdpVmTMo3dUMu3BmD7LPZE1SONDdNYE1Wu8uFTn/RlyoGPuqPweHQRiseoaSFStjwXDijYqpuQKh/so+4nl+ISz7qogz2ti6buUqpeqLrpi8thv3MVdN0R+vTpAyC7WK7eY14PPT6XNcZMY+986guJuyQ1lq5eB6++DKC+OKh8MWjcnr+xpsayxVEFS+PsmnpNGmP9+vXe358mbuDvmQWJ6UbmSznu61++e81BNX+fjBnTDKhaA86UMsMwDMMw2gpTynZBqFL0atNe7FlQIatxbYe26kgL02nVqmjiu3XrVlQfckjG96kFC5BIJBCg5coitAY9hw0DECp/fQB8+uc/F2S/t956KwCgoqICQH6XTlXKOAnnZH/9+vUA0iqPrxyIuliroUzdfHmP1ejBdty4cTt2AXaASZMmAUjHmuk1IDTOqSuxZm+sr6/PUMrUoMNryeQ/3bp1y1hWl28+52ocUNdz9tswDMMwdoSCKGWqrmgsh+9l5gsy15cd0f1ovJMqXupWorEjqnYQDZrn9xrfFLes0zqv7kC+2myqTPlSVPPYdF/atm0b9kIm8evC4zHWi33WuDq9Bho/p2qk716qW9SO0rNnTwDpgZEv7kjjAvV7X/whyVdXLP4McmBXV1cH1aM2bNgAIK2+sF/sNweQPB/NFulThYhmjVRlVX9DjcWs+a6FL2YsrjzlKmmtrm76O9Fz4vpUrDQuks9qvvpnvnPV9TWeU+MRc8WwBkEQ7YexsldeeWXOfuzOnMHJ2M9du2zHVVTDMAzDMJqOKWW7IBvfeAMDBgxAzcCBAIC6N95o4x7tvjS89RY29ukT1ecKli0L/5CSA7sr7T79NMuFdncgK5vkqFEAgH/+7nfN2i/jkmgAUuOBupSqmyq/37RpE4B0tkVONDnZp8sljQGq5vhctFUp43acwOaD8V+agVALewPpyboWrue5UCEjjDW79957AaTLY6jLMq+tJh2Ku8XHDX1qGGMfaVjRmDIel3BSr8+/GiF0O8MwDMPYHpo1KdOXbb6sZ75W0QGExpZoLbCvvvoKQFpV4Pa+WDbNLqfZ3FS14nocuPB7xsQA6Re3Dq58LjC8dpqy2qdkcXD2xRdfRPvtK9ctnn1R43fYZw6UOKDRdNK+QR37pzFcPM6OQpelY489NuNzLTzrUxjZH5+7lj47vpbEVdFcsVZULHk/2Gp8Ep8NXn+6SHHw6lPMVMHj/qgm+RSzOM2dPPlq2WnWVD6reo01sye3U/cxVbZ5jnptfEp7U1VQfUYae2YbGhp2q8lnUzniggsAAOU93QffcO00d40Xhs2YF8P2j/fc02p9MwzDMIw9AVPKdgN4E9f16AEA6OXiUIwdZ1u/fkgivLZdkY4lKxTrXUITxgUyTnCDa3s6Q4OxfXzmrmuXFSsaXY8OjIWuLMVJtypkvmyIXJ/GHHU3VtdsTig1kY9OJHUCreVHaGDi9tvLMccck7FfVezi56iGKq7z/PPPAwCWLFkCAJg4cSKAbJWQxja9tmrci7tY819DQ0OWcYHnTndaTRjD/lI54+dackGvObfbk91fDcMwjB1V47X8AAAgAElEQVSnWZMyrYlFNFZLW91eBy58Sfoy5/FlyAEF1Qvun9tTvWLLAYnWstLj+GJv+BLXgRSQVus4kFAV0XdsHRCoAqKfU9FauXJlllJGUqlU1iCOAxOqEXptuF+9l6o88Vpxu+amgebAh+fHAZMqhb56X6qcqUqTT01RcmVajPPll18CACorKwGkXaC0bhqfFY0x3F50oOhLrhG/b75z86mGvvU0U6cqUJrp06ew6f8H6j6mxYL5TKhSni8bY/zZKC0tzVIXVRXOxZ6W1vzAM88EAPTnB/TAY+Dq/q51s9eyZTt2nAGu/uBGt1z5/vs7tiOj2Tz33HOYNm0aGhoacNlll2HGjBlt3SXDMAwDOzApW+UGQP2bkUbbKAwcN9HaX+HaOqeYrXLL5W4CYeSn3qXm7wegHcJaXb0QU8qGDwcAvPXQQ806Tj/XlrqbyBincjfnWuvuYcJNAo2mwd/CFncfqTx2Xbo05/qc4q574QWsWrUq5zrbgxoDNHaMxhoaS9hqJkGN4+N23I+6YutEmxNRVdrUhbTbDp6n9jvXBF8n73E6deoUTZrZMl7tmmuuyVjm92ro8tVW4/cs/K7u6KrYqVs6UTVT4/B8LtZcf2ekoaEBkydPxgsvvIABAwZgyJAhGDlyJA499NC27pphGMYeT7OUMlUntMYW0fTPanHXmlgaZ6UWcs0MSNVGY8O0kCot8KpO5atbxgFMYy4/qmxp/S4OjrRGW74sgZqNkFBlaApBEETH0cEdBzw6GFSlyjcAai5aMFaVIH0W9DpoSnBfzSvieza3F15/KqNvv/02AOCkk04CkD2A00yjvZt4HF8KdV8q8/gx8mUz9A2ofTXUfIq2r9adTwlnX/m7VXVZ1V1fvTVf/3IRBEHWPYhTXFwc9X/69One/ewu9Pz2twHkSHhCaAtY5FrOVz/fseNxusPpykbfikaLMnfuXOy///7Yb7/9AADf//73MXv2bJuUGYZh7ARs96Ssv3urrg0CMDXDkrfeKmCXjHwc49JWR7m+3Byy1Jm9afA90M3bPnFZwUwx87PWJeKgG1dpRyDYCiAAgk5AGd233JzxYpc57vb/9/926HicUpdTgqN05o5TvjxsLbJs++CUnr8NTjbqKipQijCWrB3Sk4RCoxNEGqx0wsnPNU5JMwr6XElzTcbj6/uKz3Mi3L15p5k1cVfjDZC/XAb3UV5eDgDYf//QV/LXv/51xnp0T/cpXlrioKioKGciHG5PA44amLgfrXumcYC+c9d7vTOyatUq7L333tHygAEDMGfOnDbskWEYhkEs0YdhGMYexkcPPwwAeGX1agDAJVdfDQAopZHAGQWYdTH177D994cfAtj+F8cy15Y1tpLR4jTmZmoYhmG0Lds9KVvrXtrlqRSefvppAEBfcVtSn3u19vrcFtXNSdOv84WiBZL79u2bcztNea9uiT43KE25T/cqJvOgtTnXy0xjRRhfoJnCfO6Kes3ovkgrLM+5STiZgBn+Nm/enJVUQa8JrcZMVEGXTbXca5rzHUWTpvC6abY6dUtUK7fvGfORVYjctTybsjoAKSCqGs3RpFOKy9xFvfy66wAAb591Vka/NCHKepcRMyqKPW8eAGDD4MEAgAo3CC51+1/mOtQlT/IZTX4T/yyf+6Ku70v8QVQF0hgaTYmvxeSpQPB35VN1eA1Vmch3j4MgwH41NaiurkayV3iDfJWjqKDREbmoqGiHXVkNY1dhwIAB+Oyzz6LllStXol+/fo1sYRiGYbQWppQZhmEUGN8EUt0O42nc45/79qPr63pEJ7qMg2W6eboEejNROoXsE2eE2zZ/PoDIUzrLuNTYhD6ZTKLk44+RSqWwDdmxf9wHJwcrXDkDGjI05pDr0yjAyX6uupZ1dXVZBh1dz5cARA0svlhJvfY7cwbPIUOG4NNPP8XSpUvRv39//OlPf8JDzUxaZBiGYRSG7Z6UlcdevnxpaUINTWmvlnX93JdYIF+ij64uVooqi1r8K/uHEULdXFY1TRCiKoNvAMM06DxfJgyJF6GlssQBBJODUNnSmjfEN5hS1Y/LgwcPBj7+GEVFRViCsCjxVmZbDMdZ0NxfDKrfVFmZpcRpcgaNq9D4Cl/q/h2F15DnqcqgDi5VTeF6WsOoqenf+Sz0cwNAnt8mAA2nn466f/wDyzYCvdxFLJOUl4yaOfnkkzP25xuM83ry+YBTzL5wMW18phnzowlVNLterppJOmD2FWFXGkuEEUez6ukg26e+arIYXyH1XApYY5/Hlxe7/wto++dvIaA0VpL5Rcm67P3dfPPNAICrrroKhrE7UVxcjDvuuAOnnXYaGhoaMHbsWAwaNKitu2UYhmHAlDLDMIyCoUWUtU5dvrp5moVUCyNzf+pqrfvT7J80NNFoNGXKFADADTfcACA71osKWb2LIQvE/Zr4ask1do5qXOMyjWu9nOspM5zSkFFZWYmhkydn9Pf9v/wlMg6ocS6ZTKK2tjbr2qrxQY2Leo5aPFqLV+v2hcpM21KMGDECI0aMaOtuGIZhGEKzJmVaI0eLx+YrAu1zwfEVANZaProdiZQ2t1zrFLP2LqidL00d+HDAQ9VrzZo1Gcs9e/YEAOy1VyiXHHjuuQCApU89FcUOUVVbu3YtgLSCw2uhafl98T4ad0e4v3h68aJvfAOpVArFjz+ORCKB+ti5Ue2rr69HAul748vepmUFVBFTtbG5QeIaV6hxSLwnvOc8L1X4tIaRDsTylT3IFSOXTCZR9I1voNPs2djiPqtx+1nrMsZ1XLIEAHCKG/RyIKmtKo2Ex2Mxap4XFUOfOqQDysaUMkV/r7qdz0VO++Br2SfGI2q5BS1hwXvHZ86npOdTyoqKiqL4ScaSBZTK+J+B5IAPYrnZ+duKK+CGYRiGYRitgSllhmEYBYJKlBo/ogQvYjRQN1ROYDWZkK++Xj4XbK2tOMIpTZ+4kg6T3f5Ke7o/XH2yhoVhUBmnvRrTli+JUrzvPjXPp0h1c668paWlGDdtGoDsOmpM0HLEeecBAOY+8kjGJD6ZTCIIAtTV1WUZGXiNeU1oBODnWsdSjYta31LvWa46loZhGIaRj4JMyviS4kCElma+JNWVR2NKdD+Mw9J4Ki2cy5chA8J5HB6/bHmY0i45cGDG8bm+xsJxf8yyyLgfxvn0cLFbZOlTT0V/08rPmjtUSKicaeFsrTfEc2JfqJTwXDSmite6c+fOSKVSCIIg+gdkDxA0U572R9UVng/XV2WN6qEWe95eVMnSWDYOKnl9tN6TPmu+uKV8g9vG+lVbW5t1n9ovWpSzX717985o+cwxsYLPtYnH47PH/ur56fOjda3i+yJ6zr44QL0X2uoz6isKrcXW1YWPfeczzmdM4wm1X3rcOOvcd1TKAon9y6peLPB5B7avMLthGIZhGEYhMKXMMAyjQEyYMAEAcM899wBIuyvTiKLxSTSasGWslzJr1iwAQPfu3TP2p+7ENGbQaHLpo2PDHXByepxrnSKmk9Zql/gkn+uqL4NiLnRf+RLJdOnSBUA4SS/jJJqtswHVObdTOhtHiXMQTuKplMWzS/IacV0aQHjN77rrrvBQ4sZKYwEn7mogURfkiRMnNnp+hmEYhpGLZk3KfOmbNUaLFnOqN77aUhqLpjWrVA3hwIMvQw5IuB2X93JxPwnJOMiBkQ5k+NJmDJlPjck1EKHKx21UMdMaTJqtT2OJOFjTumEcIJSWloaxT0VFCIIgK9ZIEw/wew48qPD4akupsqNxR7ynOwq31yB5Pjtsec988Uc+NVbjk/TZ02yS8YFWQ0MDUqkUqqqqsuKiNG22LwECr3N/F9fI/dDNTeMjuR2VNaq03I/+VnhcPhfxdXyJDdQFzace+pJJ6Hrcnn3gs8qW23OwzXPhb4Uxmvq75G+H15z3Pq6kV7rr0GSFTDNauPXatWsX9ZP9MAzDMAzDaC1MKTMMwygwl19+ecby7bffDiA94dteNWXs2FDxuvfeewFkl9hQY8alHzqFbKjbAeeZ9DamUrYhc7nkn2HrM0Bp8qXGkq/kK17u25aGqe7du2OtszWUS8IWnXPX1NRkGFYaGhqQSCSwZcuWLCMhJ/uqSk5ycXYKVU/2i/eQ+6VhiffIMAzDMHaEZk3K+JLjgEBrYKnlnOvze40Z03pFmsXNlxWNAwXun+oSLfgcYHAgw/2rkseXNS33XF/jdlQhiJ+TKl58gVMpo8sMj8H1NL6GL3rftctV4y2RSER98tUfU2WK32sWQ41NY6v1tpob1M5rzvPTWClNd+1TyFSN9blZaVxUY4PLuPKYb4CpyqIqiTwfup9RAaPKq78l3gcqZlzWZ5i/ibiaFVfNgGzlx1d7TlVTXxwe19e4SP2d+J5FPuNUzjSVOZ8JZjDlteFvpEuXLti6//4AgANcnwJPrFg0elfxi35vbpLSrl27LJXVMAzDMAyjtTClzDAMo4WZOnVqQfYzfvx4AMB9990HID0x5mR+7OfjwhVZPZtKGBUyum9q7QD3eamb3KoLK/EZO6KEQQcckHEYHp6JcRpDXYq7deuGha+8gpUrV+Lkiy7KOC2eDufap115ZcbnyYMOQiqVyjBQ0Bjhi9vzQdWTaqeqk4W6t4ZhGMaeTbMmZYy90hpSmp5ZLeiqiNFSzlgRDjSoMnD/tKxzPVrcNS6H29HyTQs9BxL8nHE9VCuoOlDF4vpqOddYnfi6WmNN42n0nHgOqkzx2mpdLl4r9rFdu3YZrkZaK47KChWtXHF+XYYOxTaEYTf1ALbNn59Vp4yoKnrFFVegOVzkBlv/+Mc/AKTvraor+WLIeD78nM+W9luVL19K70QikREXxn5ojJ7GlqlqxJaKJ4/LTJ5M/61xkdyPqsbcD68HFbd49kAeg88Qz13jCNk3fXZ9A3Jd9tU108F1rt9L/Hhcn/dSf7+q1G3ZsgVYsADt27dHnZsElGSKgwh8YWFcz80WlrlRfCqVyqrtZxiGYRiG0VqYUmYYhrGLwcn7uP++LPzgKPfFf7iW7pnLXfu5a+ltrMW03eS02k1afUqYJhIinQ4+GADQn4lWnBLX3+1vlXM3rf74Y2/RcZ3U06DUu3dvLHz+eXTq1Akr3Hp7HX98Rvf783TcefX6+GMA4cTeZ1zbXkwRMwzDMFqSZk3KrnQuI8888wyA7BpYGiSucUsaF0PLOi3ljC2hJV7VIk1RzP1pFkWqRFpYlQMbrcmligH7TVQhiPddY5W4DvfJjI48R1rlaaVXZYpxNFSQuByPi0smk0ilUti0aVOGYhJHi9nGVYljuY5zXao87DAAwJp//zvan56zLyPfjkKlSO8Fnw3NVhmpo/vuCwDo4tkvx6BFUleM13nj3nsDSI9Re7qYv+LiYgRBgEQigQ4dOmTVc/PFkPH6ap04zaLJ4zPGjMoZa+hpVkdVYLk/HocDWCD9rFCd5bqqmPnOSTNXqurL9TROUfvMe6RZWROJBEoPOghVSN+f/pWV0X609h1/95qBEwBWf/opSktL8RWyM1LG4x9TBx6Ysc9t8+dn1sbbtCm69r6ED4ZhGIZhGC2FKWWGYRi7GFdMnhz+QWWK2RSpiHFeuzCzrRY3T8LJcdXixQCAQMon6ISbE9rezoBTvr/bwaGupYTl+tXfHWDBtm1Z7q2cbGvyInXRJalUCtVz5iAIAtQgNAr0Gjo04/hFn4btt1wM3nN33x2dw8033wwAuOqqq3JfDMMwDMNoAwoyKaMiRcu8qkVc7jlsGACg9v33AWQXVKV6oxkHNSaMFnitoeVTqxg7Ros/Le182ftiV3i8fdwLn2oKg9c3v/VW1rqEKgL7oFZ+npMqKvX19Thk1CgA6XHV1rfeyoq/ideCqqurQxAE2LhxY1bcnipj8WtWcfLJYV96ug/c2KebG0h9fsghaABQ4lyB4tdI4/iay+efh6NJKkZUBDWoPopXdAqZL/seB58cbGqhV9J5eejftXXgQADAOnf8OgDbABQdcwyqqqq8CQ40E6EWnOV90Np6VEh5Xowt6927N4D0M8tYOfab91Nj4agqA9nqmT4LGgOmA2+NY9SMmPr7U2VKa85pAWVVnrmNZj/0xagRjV3V+L6MuL/338/8fvPmaD3eizPOOCOrX4ZhGIZhGK2BKWWGYRi7CLfddhsA4Mp+8gUVsIWZyylXd+ytN94AkJ4Qq8t4lNzFU9JB65S1o0JGpY5iliRSiZQ79zm32zZ/fpYxTMtx8Fg0cKghKF7a4Z1XXkFxcTFOmHBi+KWb9/dzxy0uLs5yyzXFzDAMw9iZKMikjFb9Pn36AEi/ZPnC50AgckI54ggA6ff2toXhSEIt3XxJa4ZCqgK+bI+avY0DEO5H45PUAk/KjzkGADDQLVON6epe9B/F6j/xRa+B8FQbfLWd4hn+4tvH2bhxYzQA4TWJHyfhlMdORx6JJICGhQuj42jWwPhAZslLL2Hr1q3odfrpAIAyd161rq374AMkEgk0bN0aXUu2jAErFEw7/fjjj2ecJ1H1M/Gp809y2fcoY6bCRxGr3Hapjz4CkF0vjNeBn/OHQK+rUgBFABrmzEFVRQXqPvggPK5kKmS/VNXRzKKMHeN6VMA0gynVZrbcD39jqiLlel5UHeXzz76oMqYqnNYb5H40m6PGXmoBYw6mqZQx1q19+/bA6tUoLS1FF7d+fX19VpZG7QevkSp1miiCz7r+f6CxpLwH48aNy7qGhmEYhmEYrYkpZYZhGDspWhvryn9PC79g7NYGaZ01IhXWHI+EM07M1Q1XkzJxIswJK4vdc0JPYwGNFxE8Pv2FRTGrdb7YdFzdtG1bNMln3+hOrm6zmvxIE8vQcFFUVITKf/OEw4Zms+NcbNmc++6LjAbcb6Q+usRVhmEYhtEWFGRSNmHCBADAc889ByA7BqzLN74BIKyDBaRfzNH7O6beANmB37SAM/aDAwa1mKvypbWttFULv2ajW/fOOwCAvYYMAZBWyCIVJodKoYqYnpMOMFRVbNeuHSpffz0jdqsIaSs/BzKpVAr7jRwZHsvti2mhqw8NR2xrFyzIynipakgymcRbL7yQFfNWUlICNDRE15gDGfZj7NixWedeCFasWJE+PkRdQfa9e3fuXABAx6OPBgCsf+01ALHsl198ASBbhVX2cy2f0RKE1zVAqPBWH344AGCN27/2g/C+af+pGnE7Ko28n1R1OAjmM86BKmPt+Bvg/WgsCyafa27D3wMVbY298sWY8VhfuGupcXB8xvis8FnWeoJs2Weeoy/Gjc8aYT94rXzLjNvb3iLBhmEYhmEYbYUpZYZhGDsJt956K4BstYiT+sjy4tx0I8sWFal1mR8zWRAnwmrc0CQq6oarCYuifhAegMpYbeZyShLukGQyGU2e1SWbaN/UeMBziSeA+ujNN7FlyxZsPeUUAOkybVTMjnCuqh/MmhVN+nkt7r77bgBpo4BN6g3DMIzWpKCTMlrkta5QrVMXep10EoD0e3y9y16Ycu4oSkb2NKQHCGz5sqYFnpZ5DkD0Ja6uOz4XHg1+X7VgAQBgucTgpGKZDDUbngat83tVNnwxZ1pYNbqW7tg1NTUZ8U8AUOaC7svcBa77+tcBACvffjtLufOhSppee8Y2tRTTpk1r9HvGnGnmTTz6KAAgWLsWQLbKSqgWlcTiAYG0OxbbEoQxZUUI6+C6WriocM8wYSbyBc8+CyB9HzlgJLzuHNT26hXuUWPG6JrFASuv+1577ZXR8n5SbcqlAGqs1erVqwGklS1eC26rzz1RJYv1vNhHzapIJY7npn3V36XGYVI9ZH/HO9czwzAMwzCM3RVTygzDMNqYO+64A4A/A+HF68aEKzJ2i9YAJwWpQkZDDZM0fulcsJPz5wPInoBzYszj0dBF40FWAiM9AVHIakUhoylnwZNPon///ihG2v2ViWB8MWRqWNEyE+rGXlpaim2DByMIAqy+8040NDSg24lhVsbKl1/Ghg0b0BVpg4caqmhcuOeeewCkkxDtqaxe3QPXXz/a+/2RRz7Vir0xDMPYfSnopIzuID5XGY4jPnOqQtJZ3FWd4cuVAwa+hDUbI9UOrXvEl62qIUTVK82cqEVNNbujFlKNb8t9ap+4rio8msVP+6J9bt++PfZ2ag3jn6IhDE+3LnNx5cqVWaqFXmutGafnzIEP1ZG2QuOd+IxpTS6eh8ZFUR1i2+OoowCkM4PqExO4zwLWcqtwrZPO+rtBcv/zhgMAHv3dnzP2z/5qxj8qZlR3td4Yf0uqhLGlYsb7Flcw9RnTbKNffhn+Evv27Rueo6cGmw6S2Vf2jco41T0O4BOJBE4+Ofz7nXe2ROfAVuuRqUJ2wQUXAAC++c1vwjAMwzAMY0/AlDLDMIw24q677gKQ7fLNiTQnxnjSbcC6X67+2DJngGFSog5OEatwq9HtttxZG6pdnbDVrqREVmbDr30NADCI67v9L5N+Z2VfdOsxhowGOAp7Pz7rLFx22WUIkDZAxJPfJA89FHUABl3gNjjPtS+6lmkkF4XNWncdVrzzTmRAiieYooFhH5dkikaXMjfR/+jZZ6Pja2kIdXdnrNkVV1yhZ72HkEDaBGgYhmG0FAWdlF166aUAgD/84Q8A0lZ/su7++wEAwZo1ALKVKsKXNjPPqXsL4ctYLfyqcOlLVmPHuD7X48udn2+T7JCMicmF9olKjqpsvnPWjJD8vKioCH3dAEPVnEhTY7C9dO/g734XAPDPP/4xSwHjsmamVHclrjdx4kTvubckDz30EIDsuCUqUjow0+QAPI9y58bEfAkcatRJWw2gHuEPpA5AKUd1TEXuyqNFblvu+1GXnA8AePqR0KWH6o/W7KO6pModVWDef71f3B+fZf5GqFIBaTWTx1CVdq2Lu+vZs2fGsfWZVNS1jb8LXuMtW7bgsstOcWuHjnNujoBnnnkpUtbYP2ag/M///M9Gj2sYRlsSIO0QaxiGYbQUppQZhmG0MlRftMi7llAYfuWIjO1STin64L33AMQMS+77WldIftURRwAADuQXA8OmzC3vf5yzKtDrlcFntLm4OX5ZmIsJg94M20oaftgfFpp3yxTypp91FhRO5jVeLggCDKJ7MJWyM0MDFM4Li79jdejqTuWs/GHXfiOc9a8Sl+3Oru2/v/ujwp3PMrc8PHQ3/ucTT2QVdFeXYRrKGPe352VlNKXMMAyjNWiRSdmFF16YsfznP4dxNrT2U/niAETrHBFVa/gS14yFhEqAKmKa5U1TLfsKq2qcmG4XJ65oxddlq7FOqlT5+hyPOXPJFbPqvDGCKCUDJg5QKPIc9YMfAABWvvRSdK2pplCB4bIqZxdddFHWObcmvAdUd/gM6fXUGLmBrr5YNw76/kN27PysStxoktpuDcLrGiC8zpGdmBfTDXKjm8Blp6SdfuaZ8d1HbmSMTWNx3xf+9jcA2Vkh2WoWR63hxevC3xKQLvDLQTDvLe8l48+4D6ptvGaqCGtmUVXzGCPW0NCAe+55PquGW21tLT77LH2PeE6mkBnGrgAjaw3DMIyWxJQywzCMVkZjxpi4hQoZJ+Wv3fd3AMBJI4cCSCtRmgxJ3Z+rnWJW6xSzUo6p6bdLN1waGSpce4hraU2QsXidfM3lH+dQxshpp50W9iEW85XVZ7oD08gx/83MftGqcZRrWYCMiXa0INlm1zIMjNu95nYbloPDJ84YEu8f7wndbbUEyy233AIAmD59es7z3e0IAqDY3BcNwzBamlaZlHGAQYu81lrSmBfNSKgxXbS0q2KmsWC09GuclwbTaw0xXy0xDpg0IDzXPonGr2kmSc0mqAOAuPLG8VPAemRuudgNQAL67LiRUjfXdnUthbRSV1h19ZtvRufElvE+7E+H2KClLWE/qJDxemtc4iBXmy1gObFrXEv3LEphHMS5UW7gvHPK3XJtDdAOQJAAurWPbc+Wg0QOAnnb6zKa6Osoe6PzymJ6hVPPDwesj80M66xRheIzrlk59RmlshmPc9RYSe7rgAPCke/ee++dcSw+i5qtVOMi1Z1L4yX5O9WsippJlO5hhmHsAphQZhiG0SqYUmYYhtHKcAJMIwMNVpx8c5LN5VcefxkA0N9lD+QEmBNkbbn/qG4ZpS0aDzjIpkJFowHXc9kdESZpxCo3j65csAAA8NVXXwEAli5dCgAYLq7nQNpwoIXS1Z0cQNrC9HfXMttkL2nZbxpX+snntFwtcC1j1PqeHLalr4TtC2EzxKl4H7z0UpaRjv2jYkYDGs9jjyGBHOk2DcMwjELTKpMyrf/FAQcHDvqS44CDL0m2WueI7DV4cNi6Zdrhty1enHFczdKoCp1mvPNlhwycGlMh57mKf3z8cRQjpvXAiCpnVB20T9x+27Zt0TikGwciHIDMdy0HLpJ9MXDLZVLJdWVDQ3RNVc1c72rIjRw5EjsD+gxpPbiKgw4CAARMpe0UqSiGjIM2lyghukaMX+fD465h6QYgWI7QSrw/0tea15B+ZBzEusFryg1m338rzJDA+zfAZX2sYGrvCte6ezl81CgAwIMuRboqg1z21eSLx2NqmnONhcxKt+7Qa8vtGKPG71WdUyVNf0/8XGPZDMPYBTClzDAMo1VodFI2bNiwghxk3bowq4EO+jQphrpm+SZRJLIKu2WeTJT4YvTojPV1sKpuVb6EIFnfu+XMFAzp7OiIJcXwFYH2DZy1D/GWU9diut65WeC8cIyMYSt5UOkYlxsyGlRNnZqVHIVwIH3nnXdiZ4DPkC8pC+9FQEv7PNfSwstHyV2raOZe71pO0mrTn89zc/9hiwDw2lJBaC/rp2s3AwA2TZoEIH3/eO/acz/rMrfnPVlz880Z5+VLILM96Da+fevvjX1XQ4EvgU6+3xOfKU7mZs+evd3n0pIMHjw4ihdqaTgh1kk375W6XvN7PqZ6LbldpMC5emSRwLFR2mWupaWHMWY0MrwbNquc8cjnCIwAACAASURBVOGrf4YPPp8QTtT33z9Mb6jPSrxPakDRdVOpFCpdVsVu7vdb6U6UJgjaTiI3YBqgogJkslwqn2OOO6HM77u5HR/jXLo/eP31qJ906eZzT2PEuHHjsEdhSplhGEar0KJK2Zdfhm94zcbmyzCog0KilnvNWMghZ3FRZpuaE76I6447LuN4+QaPvklZ4Aq0Mvdi5hQxPTlMzZ0LIDZJO+qorEyO0T49kzO2HBCkUilsPfJIAEAHpsPmrtgRiiXcJb9nh93dLnIzgGQymXVttZ+saVVeXo62ROulaT23gOfIc+bF1yd8k2t5rTgp4/oc9caFzZrY+hRp28t6Lq6PGpC6QNW6LJDtPvgg7C/37R5Fdr+7K+rbfuhQ5GKNq/HHwXeuSZrv+dZlbX1KmX6ug2pt9XgkCAK0c+5vmw48MOc6hmHsZJhSZhiG0So0Oil79dVXm7XzRx8Nkxd0794dQHogSfdDWiRpddXU+Bzk0cVPrcNcv9xlGOvPrODOqlfrrLzrHnssY386wPcVVFa3ypQbSNJoqO8pLmuGstT990fH1GQkmshBJ0fqsplKpXCgO98yNzEY5tSfV3k32RGal8XKmXJK24u//nVWmQH2k3EUtA5/73vfQ1vyu9/9DgBw8MEHA8hWzP5jaOjCCtYuZop6xsyQd1wr2duim+Xa1EbgZAAI3HWleyOz13H/VNzcfj90SkT9ffcByE5+cdTxxwMASge47dzDwnvCblV4fnsszK6/qTjxiTyQPdFXN0am02cCHj736t6oyWj4TLLVAumEv6eqqioMPP10AMAb11yDCRMm5DzHPQH93al6qf/ncf3Nzi025X6XmhiouzPc8PFkApta95zS67b+3XDy38UlfymnMuaexy3OOBDdS3cc9pPKHX+HfM7jbtpayF0V1zhrP/oIxcXFWB9bn+RyM29/SJgmsoKPP+uRcZnGE5fEEXXuAri6a5H1xClr/C/ycOdmPOell6J7w99Hrn7vEeQrU5bbBmMYhmFsJy2qlHEQqGmeNYshX+hcP3LVcZMvDi41EJuthFBFL2Z+ri91VQh4HJ2s6YCnwSlUG+XlXHL00QDSHjUM+SrnyOi0MAbtvSffjfapA2XNbMdWg+Pr6uqw+J//zHAl2zxhAoIgwAf33hteJzdpq3DjkGhO1jXzunTp0iUa7GmmPN4DTs7amksuuQQA8NxzzwHIMXHg5MjFdkWDLk663Gg05RIILJfVSj7+GECmQaBq3DgEQYD5992XVnVd/GKFc2PkGJCD3TqnhBVLTS9OXHjtS6MNwoZzwgqPykRYA/AuF3s2YEA4u4tnydRBrU+d1Ym/Pnu6H/0dqpsXf0c6Sdu2bRuOG+6C/FzK9bk5JpOGYeyEBIgVasxBdo4XwzAMYwew7IuGYRitjM8VVMsYcMKsRdHVa8Cr4rhJP40PdZ98AgAocsffujw0T3wm7tKBxJr64hCjGDLnnrufHJ4hbLXO6AFkJqVpDDVcxftS+/HHqK+vx9pBgwAA5bRq0AJV5VqGLdJoowl6xG2Z16mhoSHLMKZJdnYmZs+ejZ/85CdIJBIoLi7GLbfcghNOOMG7/siRI7FkyRL861//yr/zfEqZTcoMwzAKQotOylR94TJfcgxy11izYvei7eQGDBpD5osNi168rl3mFul55kssogMNDoTYqkuRKg8N776LIAiwwbkOUSnT2lZHHhdWMF0470NvwgY9Jw7S1L0wfm2pFtENFIsWIZFIYNl+4RDpAJdUotRdl0Uffoj6+np0QFrV0Ix67EdTB1Cthbp/sn9/eypTQaNCpS5UxTcWZ6zXTeqBxTMGlpSUIJVKoXPnzmmV1Q1qV4rrazQoFhe/yEV3yBAAaeGu2t0LLn/wpz8BAJrqJDrJJRK54447AAADBw6MvuO58xqpG6Kivz8+A5ptkTXstJ4gz5ETibhqt6/LVIpvuQ/cj3Fne64MY1fmlFNOwciRI0Nlf/58nH/++fjoo49yrvt///d/kUtmk7CYMsMwjFbBlDLDMIwmstNnpHWuyyXvvw8AKHYKUJSRNpYZNn4csstmpKVBLrSZYJ5Tyob9jgeVjmlGWtdWDR4cGh2uucabkfbuu+9Gc2hurHYu4pOs6upqr9GvqqoKN910E37729/i/PPPb9rOi2DZFw3DMFqBFp2UsR6RutaoKw4t61EWRrdenbP+d/jii/BzyQq3xhUljXI5OGseg9p7rF6dsT7RwqyqkqhLEddvrGhoEASoff99bN68GRtc5rxulEHYLzdAqnVKYOdFi7IGZerWRLhersQO/K6srCxDQeuyYgWSySRWI3NwFz8LjfOL10UD0mrhzgIVqG7dugFI95v95ffsNz/XxAqarEJVnrKysuhedOnSJWtAqINldSfTBC11bpC81d0rHn/DhvAh+d63KCVtH1OmTAEAzJo1K/qsf/8wGwmfV42/8w2KdULAc6FSpteU63H/8VpqicMOyzSw013MpSSf+NjEHThbwzB8PP7447juuuuwdu1a/PWvf825zk9+8hNcc801kZreJEwpMwzDaBVMKTMMw2gihVI5nnjiCQBpF25OlDlYprGBhgFOiLmeFuzmxFndnbl9mVPQ6lyZkE7LlgHIn+nQV+ZAkyEFzk2VHttMaLN63rwsF2JV3VQl9KmB8UQy7f8jrAp/IA/IIvFurjHs2bB9ldlNXRtIkXh2tNJl/nn/17+OzolGBh6fJV7aOhOtj3POOQfnnHMOXnvtNfzkJz/Biy++mPH9vHnzsGjRItx8881Y5u5/k7A6ZYZhGK1Ci07KWGTz7bffBpB+yelAgIoa6eZaGufW9ekDAGi/aBGAtMIW1Qml0c99UMoXsdRfUpcgjaXhssbg8CXNlgOe+EAlni78vRdeQCKRwP/nCpKW/DtchzHmnRctyqrN5hscqXKmg6P6+nqkUqkwC+PmzVnlBHIVao2jrkOakXLq1KnYmVi/fj0AoHfv3gCyB6E6mCQ+FyjeNz6DPO+ysrKojltDQ4M3rbwOLHlfOYhe7dRa0rVr14x+fvbZZ9t7CXIyduzY6O8///nPALKvjT5z7Ds/V+WY18andGvh8YzacXPmoL6+Hu8iraytXBlWzr5IXOgMw9h+7rzzTtzrMu4+88wz6NcvnKGedNJJWLx4MdatW4eePXtG67/11lt47733UFFRESZJWbsWw4YNy29oMKXMMAyjVTClzDAMo5XR5ELqKsoJMpUzKmN0h+WEmRNuVa504k0oENVUVITHXbIkYz8+92k17vA47K8IT1G7devWaPKuRjl12fYpZHqshoYGHEbFiwoZfdg5edA3W5183zVzudQpZXV1dd4Mk76i6G3F5MmTMXnyZADAokWLkEqlEAQB3n//fdTW1qJHjx4Z619xxRW44oorAADLli3DGWec0TTlN1/2RcMwDKMgtMqkjHEzHGhwAOJ72TFkmUHitS4eJ+nUBw5Iunweak+1zkJYKrFbqoyRfOqRxuJwUEGLv7rhxL+LF1dd/OabGdkAi5CjILX0xYcvcDuulG3dujWrgK9mU/SpG6qUVVZWNtqftmL06NEAgDfffDPjc00lTlQ589XsyqX2pFIppFKpjPTYer18SQp4XCp7mzdvBgCsXbs2Yz2qyYXkCxeDyUEw+6ZZE/VaUIFWFZGoSshnS2PMtO4fnyVTyAyjZfjLX/6CBx98ECUlJejQoQMeeeSR6Pc4ePBgzJs3b8d3nq9OmWEYhlEQTCkzDMNoZaJi5G6CzAG0qkJadoCtFrb3GSM48aYwVO4Uj5TL37Pclc2ocXXEfGU/qpyydqhbVkWMQkrQMfOLkmOPBQB88vrrXjdaVefYdy3TkUwmcfBRYVkRuAasBEHljHAS0d/1a6Osp9Ie+x8E0TVQQ5UaKXYmrr32Wlx77bU5v8s1IauoqGhajTLAlDLDMIxWolUmZStWrACQHlDwZceXHF/KfGmvdioIl0vdwEOzNXI/G9asyViO15qKL+tLVjP2aWwNBzpUWdR1KK6O+DI6aqyR1hnTc1fFxRf8ToqLixEEARKJRM6MWjx3zTboG2DwXJucLrmNYND9gAEDAKTPj/De6WCVqDKmFBUVZahiOjDzKZxc5jN64IEHAkgrZEyFTvW4JbjyyisBpDMy+tQ8fSb1GvoUbb0WmmmSbNwYjoQvueSS5pyOYRhticWUGYZhtAqmlBmGYbQyVIGKxOCkrqGc6GoBe6IGIn6vxpdyKkRO6gqcUlaxMGznuYk1J+ZaRoEKWeCUqVKXm4lJlSLlSdIvlrvsRmUnnggAWBRTbTTTI8+ZfdAEMwBQRrsTW1bsYMkFKmScRLDjG+Vz9ndZ2Kzi1yUlWXF67MeFF16Y1Z89Asu+aBiG0Sq0yqRswoQJAICnn34aANDL1RdT1x2NWYmUMnHd4cuyqiqsEOpLE82BicbScL+qWukgQLPXaQ2vuPLAPmjAvLrmcDCmgfr8ngMSzRxJ5YXElblkMokgCFBcXBwVEdX4N4250jpbPO7nnzNH5M7NWWedBQCY41J8awpxzZjpS7ut6m18gJhMJpFKpVBVVZVVw474YvMIU55rds2WiCVTmJFx5syZANL1y3xxcVqTTmMp+XvieowV27RpEwBg2rRpLXAWhmG0KaaUGYZhtAqmlBmGYbQyTADTt29fANmu2RnlBZCeEKsiRmikUeNL8eDB4QrMUkjlSBQmLYVBYw33R0GslF63GkxGJaVr7uUy1/7HN8L+fOiOn1qwwGsUi9PZxZLRJBK4bImRAsZ+UKnjm82dPlh1pU6WnQ1q1csvo127dmiP7FIpWrJlj8NiygzDMFqFVp2UsWYTlTJ12VHVQeOsqDJR/dCBgw5gVHUiqtD5MhOqCw/7y0x6VAiAdP0p3acOrjQbIvEVbeUyrxH7QvViy5YtUR2tzZs3Zw3W2Gdup8oY+0M4WNxVWL48HJ197WtfA5Adr0h86ivRArXJZDK69jU1NVk1vfSZ1TgrreXlU9Jag8suuwwA8MADDwBI//74rPjiFlVxZowY4+NMGTOMPYAELPuiYRhGK2BKmWEYRivDelFPPvkkgLRCpkmGaCRQgxPX12yJmkConjFcIygZORhj5hSQ0iOOAJAuP6JGhqjMl1OmKLSVuD+iMbsqKlze37VOyRr0z7Bd9fWvAwA2IPSQ2/LOO9GmmlgGSIeOlTiljPXFolgzutlxeaRs6I4LV1GjelHYtm/fPqtoOg1fWsZij8OUMsMwjFahVSdl48ePBwDMnj0bQNp1h2gwu8b5qEKm6pGqE77aX3zJa0wN1+dLmWqKxiNpIHj8O1XINHDfp5z4MtwR9klVjbq6uqie1rZt27LOWTPicXtV7jjwYOa+XQVmiXz22WcBpFUgvb6qdup90fhCAFEx1vj6qrLqddRnj/dR47HagjFjxgAAbrnlFgDpwsSaqlxTknMCYRjGHojFlBmGYbQKppQZhmG0ESwXstdeoXTFRD2alVENTlRxtNC9qj3kQxc7NYg11ytc6yQwhoJVugl6lGDoUAahhdCkoKFle4WVHtCNH3D/zHKo9cGcYtbP9Ytj/pohQwCkQ750LkDBS0Pa+ruOlVGyY16kw7qH7WLnlv2W+9xlnfxwzhwkEgmUwF/0/PLLL8cejWVfNAzDaBXaZFLGzHl/+9vfAAA9e/YEkB3/pPWT+NJUtSiuGgF+pUzjtPIVL+X+9HtVTeLr8DtVzjiI0mMT7TNbdUvyZaxMpVJRxkAge5BGhUZVRsYJff/738euzPDhwwEAr7zyCgCge/dwMKZKmT4rfLY0tXg8W2IikcirkPmSFWhds/Ly8madZyGYPn16W3fBMIxdBVPKDMMwWgVTygzDMNqIKVOmAAAefvhhAEBFRQWAbAOVFqEvOfxwAMC2994DkDYWaLH0yI32o48AAJUHHwwA6EbJS5SyOhfjRahEsay4lgVLuRi0r9xxergsiQNd7FbAWLKKzONxB+rMq2XI6jxt4GLl6lx2yWjOQEWOYWCrnUL2KTLa6n+HbSKRiAwrbFlq5bvf/S4MmFJmGIbRSrTppOwjN1A48sgjw86IQqauOloLTOOj8mW+0wx7OuAhGl+ktcdIXBXRGCIOknxKCgddGlCvyoovQyQpKipCEARIpVJIJpNZgf7qBkVliJkjzzzzTOxOnHzyyQCAl19+GUA6KybRuEF9tuIZN4MgQBAEKCoq8t4nVTZ99cyIZrs0DMPYqTGlzDAMo1UwpcwwDKONueCCCwCkkyD17t0bQLY7bdxlGgDaOYNW8OGHAPxF7AnLenXjB06SYvbCWiddqTJFRavSKWOR+6+r4cX+rX4zDFpbjdBAcfSJJwIASjmop43EU/rLJ8jo6tWikEX71zpks13rsiwy6+K/33knNFDV1mYZaFhmw3BY9kXDMIxWoU0nZaxzdMcddwAAvu5cZ6huaJyPuvSoIqZqksZhaYFUrsfvdb+qfhF+zpd4fJ/soyooqqzodtpnEo9tiq+v9a6CIEBxcXFWjTatT8bYshEjRmB35pvf/CYA4OmnnwaQHuRysKrPFj+PD2apQDY0NGStz2dC677x+uqzye3POOOMAp+pYRhGC2Lui4ZhGK2CKWWGYRg7CUyCRGMCSzyQKHGNU8Z8xczVKEQjwt7cEXdLhYnpFGsymkhwWv/aawCAUilLQjdoGh/ixqKioiK89Mwz6NixI4aOGBZ+yMG9a8ucdNfRKVyB60/KLddlrp4Fu8/1A5fNMZIEn3Sty7b4iRPB4kmR2PeVK1cCsBIQWZj7omEYRquwU0zKGOxOnnrqKQDpAUk8zgfIViFUTVKXH82Yx5exqk2a1VFVDm7H+k3MXAgAZWXhsIG1nzQ2TOuXUfHyxR7puagKGM+iGI8/82WuXL8+DHg/55xzGj3e7gaVqfvuuw8AMHDgQADp1OOqvpLa2toMFUyzXfL6clD6xRdfAEhfZ32mDcMwdkmKYEqZYRhGK7BTTMqUxpJP1NXVYeHCha3YG8MwjNaFxgQqZiwbQmgc0LIeDfuH6Q4Tn4ZpBmk86HzIIQCAUlcfLFLKJHiMZibGhqk7NY0XNCrRCLFuXVioLG5kYp/33ntvrHLSW38eL1MARKZ5DAio3G1ETjSEjNkgu74btuzFsrCmPL56990s4xoNXKwVd+mll+Y+mAGxexqGYRgtwE45KWuMkpISbN68GUB29kSfmqRqldYb8ylrmq2R8Vpr1qwBkOnmcs899wBIK2UdOnRAnHyxZCRXnaz4OeaKc0smk0ilUqipqYn6SBWPfZ06dSr2ZMaNG5exfO+99wIA+vTpAyAdx0jlDMiMF+OAjs/e2rVhzu0xY8a0YK8NwzDaliKk87MYhmEYLUebTMpeffVVfPOb34wmMABw5513RgNcupaRLVu2YNKkSbj99ttbtZ/GzsGPfvQjPPzww9i4cSO6deuGCRMm4Mc//jEA4JNPPsEPf/hDvPnmm2hoaMCQIUNw22234aCDDmrjXhtG86Fi9sQTTwDIzsqoLtg08XQ94AAAaUUpGlRrDJlrq50itfL118P9OLdnGoNorGAiHC1u/+qrr2b1/dxzzwUQGs+Wvv46OnTogP4jwzpmUMVOR/3LwqbUKWzVEmPG7qcWLEBRURG2uOWvEBq6ai69FKlUCpX33hsavlKp6FrRcLV06VIAwNixY7P6bqRJAGifdy3DMAyjubSZUtavX78osFph8U4AqK6uRu/evTFq1KjosxNOOCFjfWZvVDRDnipke+0VVhpl7Bong77MelRHLr744qxjXX755QDSihn3qdkYmbGRsUiq4CiciKq7Evc3ZcqU6DyGDh3a6L52VcaNG4ef/vSnKCsrw6pVq3DqqafikEMOwbnnnosNGzZg5MiRuP/++9G5c2f8/Oc/x1lnnRXVwPMxfvz4Rr+//fbbsXnzZvTv3x/HHntsIU/HMAxjl6EI6ZrchmEYRsuRd1L2q1/9Cm+//Tb+8pe/RJ9NnToVRUVFuOWWW1q0cwDw2GOPoby8HCe6ejfGrsXixYsxZMgQvPjiizjiiCPw+eef47DDDsNjjz2GYcOGNWkfqnolEgksWhQWHjr66KNx9NFHR99dddVVuOGGG/DVV1+hR48eBTsPw2hLzj77bADAH/7wBwDZCWuiZD8LFgAAKt12nVyZEeZpKGXwlZOaap1Ctsp9TKMRXcNpVGKrrt1Uzk455ZSM7+PfxWulrXLZEfvTSeJQ1x7gOXG3fo2TyFa/805kVCsqKgLELRwIlbJUKoVUKoVkMhm5Hm/YEJ40/++wZDxNw5QywzCM1iHvpOzCCy/E9ddfjw0bNqBr166or6/HI488gmeffRaTJk3CQw89lHO7ffbZB/Pnz/fud+3atejduzc6duyIs88+GzfccEOUwTDOAw88gIsvvjjLTSdOoV6ujDPSjId0d2lKXBYVs0Kxq8eCfe1rX8P//M//4Ac/+AHee+89XHrppbjkkkswbNiw7Xp+brzxRtxwww2orq7Gvvvui9GjR+fc7rXXXkOfPn2aPSGbOnVqhiHCMAxjTyRfTJknF4thGIaxneSdlPXt2xcnnXQSHn30UYwfPx7PPfccevbsiSOPPBJHHnkk7rrrru0+6MEHH4x58+bh4IMPxvLlyzFmzBhcffXVkesfWbFiBf7+979H6cyN3AwePLitu9Ao48ePx1NPPYVjjjkGQRDgySfD4kF33XVXk5+fGTNm4Nprr8W8efPwxBNPRC6bcVauXInJkyfjpptuKki/d/braux5XHjhhQCAW2+9FQCw3377AUi7S7dvH2oaVKc2zpsHAPjKqUVUwjoefzwA4MvnnweQNkSVOnWL+6HapVkXtWVio3iCIipUXCeRSOCzt95Cu3bt0OuII8LjDXEru1CzqECaS7Bb65aXvv56qNYlk3kTO9XX10dF36uqqqJkR+eff75eTqMJBGhcKbNJmWEYRmFoUkzZmDFjcPfdd2P8+PH4wx/+gIsuuqjJB3j99dcxfPhwAKHLzYcffog+ffpEWe/23Xdf/PKXv8Tpp5+eNSl78MEHccIJJ2Dfffdt8vGaQ744o52V1nAjbS7jx4/HyJEj8dvf/jaqO7e9BEGAww8/HH/729/w05/+NGPy9eWXX+LUU0/FpEmTcMEFFxSkz7vCdTUMw2hJitG4UramtTpiGIaxm9OkSdnZZ5+NK664Av/617/w9NNP45e//CUAYOLEiVGMg8IJ2IknnpiRuCMXQRDkLKL84IMPYsaMGU3porETU1VVhenTp2PcuHG4/vrrcd5556F79+5Nen5yUV9fj8WLF0fLlZWVOPXUUzFy5MgoK6Nh7M5MmzYtY5nJjgYMGAAA6N69OwBEBhBVlda/9BIAoESyK7LtMCSUsOo++CBsRRljoiK2EydOzOojjWyVlWGEG12Ki4uLMd/Fhh1+aaiY4Vtuo2WufSds3nj55UitU3guVORqakJZbd26ddi6dSu2bduGefPmZV0rY/sIAOyYGc0wDMPYHhL5VwldWb773e9i9OjROProo7HPPvsAAH7zm9+gqqoq5z/fgBoI0yevWLECqVQKn332GWbMmIGzzjorY50333wTq1atysi6aOyaTJs2DUceeSRmzpyJ008/PRrANeX5SSaTuOeee1BZWYlUKoW5c+fizjvvjBILbNq0CaeddhqOP/543HjjjW12joZhGLsjjCnz/TMMwzAKQ5DKJVHl4B//+AdOPPFEzJo1C5deemmzDnrTTTfhf//3f1FZWYkePXrg7LPPxi9+8Qt07tw5Wufyyy9HTU0Nfv/73zfrWEbbMnv2bEyaNAkLFixA9+7dUVVVhcGDB+NnP/sZfvCDH+TdPplMYsSIEZg7dy5qa2vRr18/XHLJJbjuuusQBAEeeOABXHLJJejYsWNGMpiFCxdGxgPD2FOZNWsWgHRxdMZ+UX1ShUyL1lONYizaV199BSBdg2x7ePjhhwEA5eXlABDVqeQxk8kkjj3pOADAay/+PYoR0yRPqoytX78eQGYhd2Z2zVU/zdg++h51FC59913v988fdRTebeR7wzAMo2k0uU7ZPvvsgw4dOuC8885r9kGvvvpqXH311Y2uo/Flxq7JWWedlaGCdurUKUpJ3RQSiQSee+457/djxozJGIwZhmEYhSNf9kXDMAyjMDRpUpZMJnHTTTfh+9//Prp06dLSfTIMwzAKwNixY3N+ziQ29E7Q7IlUyKqrqwEUJgmSJuD5zW9+AwBRKZSSkhIse/DhUAlbsSIreyPVOqsv1rpYnTLDMIzWIe+krLq6Gr1798bAgQMbVSwMwzAMw9i9KAKQXYDEMAzDKDR5J2VlZWV5sycahmEYuw7Tp09v6y7kzNho7HyYUmYYhtE6NDmmzDAMwzCMPQuLKTMMw2gdmpQS3zAMw2gZ3n77bXz7299G9+7d0atXL4waNQqrV6+Ovt+wYQPGjBmD8vJylJeX4/rrr2+7zhp7HAFCpcz3zzAMwygMNikzDMNoQyorKzFhwgQsW7YMy5cvR+fOnTPKjlx11VWoqanBsmXLMHfuXPz+97/H/fff34Y9NvYkimF1ygzDMFoDm5QZhmFsB4888gg6deoU/WvXrl1UF2tHGD58OEaNGoUuXbqgY8eOmDJlCt54443o+6eeego/+tGP0LFjR1RUVGDcuHFR/THDIK+++ioGDx6MQYMGYejQoTnXeemll3DEEUdg8ODBOOGEE5pUnsSUMsMwjNbBJmWGYRjbwfe+9z1UVVWhqqoKn3/+Ofbbbz9ccMEFuPHGG9G1a1fvv6by2muvYdCgQRmfpVKpjL//9a9/Fex8dkcGDx6MwYMHt3U3Wo0NGzZg0qRJePLJJ/Hhhx/i0UcfzbneFVdcgT/+8Y+YN28eRo8ejRtuuCHvvpl90ffPMAzDKAyW6MMwDGMHSCaTGD16NIYNG4bLL78cADBjK/MZsQAAA2FJREFUxoxm7XP+/Pn4+c9/jtmzZ0effec738GNN96IBx54AGvWrMGsWbNQU1PTrOPs7rAO257CQw89hHPPPRf77LMPAKC8vDznekEQYNOmTQCAjRs3ol+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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for stat in conFiles:\n", + " plotting.plot_stat_map(stat, title=stat, threshold = 2)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/.ipynb_checkpoints/timeCourse_analysis-checkpoint.ipynb b/task_based_analysis/.ipynb_checkpoints/timeCourse_analysis-checkpoint.ipynb new file mode 100644 index 0000000..4c88983 --- /dev/null +++ b/task_based_analysis/.ipynb_checkpoints/timeCourse_analysis-checkpoint.ipynb @@ -0,0 +1,466 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## This script analyzes the timecourse produced by different scripts" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/sklearn/externals/joblib/__init__.py:15: DeprecationWarning: sklearn.externals.joblib is deprecated in 0.21 and will be removed in 0.23. Please import this functionality directly from joblib, which can be installed with: pip install joblib. If this warning is raised when loading pickled models, you may need to re-serialize those models with scikit-learn 0.21+.\n", + " warnings.warn(msg, category=DeprecationWarning)\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import nilearn\n", + "from nilearn import plotting\n", + "import glob\n", + "import os\n", + "from nilearn.input_data import NiftiMasker\n", + "import matplotlib.pyplot as plt\n", + "import scipy\n", + "work_dir = '/media/Data/work/KPE_ROI/timecourse'" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "# load ketamine timecourses\n", + "vmPFC = np.load('ket_func1_vmPFC.npy')\n", + "amygdala = np.load('ket_func1_amg.npy')\n", + "hippo = np.load('ket_func1_hippo.npy')\n", + "vACC = np.load('ket_func1_vACC.npy')\n", + "dACC = np.load('ket_func1_dACC.npy')" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "## load groups\n", + "import pandas as pd\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "\n", + "ketamine_list = list(medication_cond['scr_id'][medication_cond['med_cond']==1])\n", + "ket_list = []\n", + "for subject in ketamine_list:\n", + " #print(subject)\n", + " sub = subject.split('KPE')[1]\n", + " ket_list.append(sub)\n", + "\n", + "\n", + "midazolam_list = list(medication_cond['scr_id'][medication_cond['med_cond']==0])\n", + "mid_list = []\n", + "for subject in midazolam_list:\n", + " #print(subject)\n", + " sub = subject.split('KPE')[1]\n", + " mid_list.append(sub)\n", + "mid_list.remove('1480')" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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4+GaIh+8pfFnFM1Twy/pvHl/Y4iOR9JJmCh9wErdS4ftgjJkA3g7gawCOA/gMY+xRIrqTiF7d7f1vNoyxwOUnHF2lJpaO8/310nC9SbY7POB/6/gFMCYH5w0LNQ8/OAwmI8MX8LWNb7IxjLF7ANzj+977Qm770l48Zr8oGRaqph1q6WiqEh7w3UvEnFT4QwNjDIWKiV2ZGM6tlfHI/Dqu2ZPZ6sOS9IBalU6wwh+JaTJpO+zwsQr+bVeciKqgagarPN7IIS2d4aFi2jBthtuu2QUi4JvHL2z1IUl6xEYK3/HwZcAfalYLfKxCcMDXVYJpb6Twh+tNsp3hl/R7JxK4ce8YvvW4DPjDAv+8Sg9/G5P1FH77lk5FlmUOHVzhJSMaXvncHXhkfh3nZJ/FUMCvyHlDpZ+RqCqrdIadsMFpHL2JpeMlbaXCHxq8gB/V8OIDkwCAB05lt/KQJD2ibFqIaAoUJaiVaDiTtjLg+8gWm1s6kaZVOjJpO2zw8bgjUQ1TqSgAIFsavl2n2xFnn214CExGNZQMa6hWmsqA72N1A0tHV5UNPXxZljk8cIU3EtO8fQjc9pNc3JQNK3A0MifFhyVWh+fzLAO+j2zRQDKiIhJy5tdUgrFBlY5U+MNDjgf8qIqYriKqKTJH0waGZWNutbjVhxFIxbRDK3SA2sTMYdphLQO+D2dSZrC6BzYYrcAV/hC9QbY7BcHDB5ytZ1Lht85nD8/hlj/7zkDOISobFmIhNfjAcI5IlgHfx2qxirFksH8PuKMVwiwdV+HnK+ZQ+X7bGX/AH03oA+nhf+x7z+CLD85v9WE0cGqlgJJhDWQ9u2PphIfAYdxrKwO+j6V8FRPJaOjPdVUJtXTKhgU+Qn+YLgO3M2JZJgCMxiMDueLy0/efxueOzG31YTTA+1p4V+sgUTHt5go/Mnx7bbd1wF8rGQ3LShZyZexIhwd8rUmVTsWwMZF07CDZbTsc5MsmEhEVqlu6lx5QS6dsWlguDN6Vx4p7TANr6TRJ2ia3aAnKVx8617ertW0d8N/yd/fjA199zPvashkWcxVMp2KhvxMJ8fAtm6Fq2ZgccU4WMuAPB4Wq6X3wAcfSGcSkbcWwsVKobPVhNMBPQrygYZAoG3boaGRAqNLZ5ID/yR+ewl33nerLfW/rgH9quYATF/Le18uFCmyGpgpfDxmPXHUvWafTzslClmYOB/mK5a27A9yk7SAGfNPGSqE6cNM8uaXDCxoGiYrZmsLf7LLMbNEI7QPqlm0b8G2bYa1k1K0jXFh3FNJUE4Wva8GWDr9knXIVvizNHA4KFbMu4I/GdRSrlneCHxTKhgXDYgNXIbY80JaOvUHS1nndN3s2VrZYRSYeXinYDds24K+XDTAGXFgvw3YrahZyzn71ph6+EmzpcAUzneaWzmB98CSdkS+bSEZrKpBPUR2kxC1jzEuKrgyQj29YthcsBzNpa4WORgacTViqQptu6WRLUuH3HJ54MyzmqZALrsLntkwQES14eBovyZx22+8H0eeVtE/ep/DTcR7wByewigJkkHz8VeHkUxlAhV8xmjdeERGSEXVTA37FtFCsWqHj2btl2wZ8PiQNgDf90LN0Rpp5+BTo4fNL1knP0pEKfxhoTNo6l9qDpPDLQkJ0OT84JyKxamgQFX55Aw8f2Py9thtN6+2WbRvwxdK6c2uOlXMhV8Z4MhI6VgHgs3SYZwNxeMAfiWpIRFRZpdNDGGP4wdPLW9JY5PfwB3GeTkVIiA6SpSMq/EHz8C2bwbBY0yodwJmhtJkKn7+vwqb1dktPVhxeDPzOZ47htmt34uVX7ABQP/HwvBvwF9YrniUThu7OzjZsG1Glpg64yopqCtIxXSZte8Rd953Cx757Es8uO/NYXvqcqb6pnyBy5cakLTBgAV9U+AMU8JfrAv5gKPyFXBnHz+W8fpmNFH4yqvW8SsewbDx5IYerdjeuyuTOg7R0uqBq2vj8A3P45vEF73urhdoHllfqLOTKTf17wLF0AMf7F+EqK6qrSMU0WZbZAyyb4X1fegRRTcXt1+0GABSrm6cUTctGxbQb6vCBwbJ0BlXhr9RZOluv8Blj+C+feABv/bv78dN/9T0AQCKysaXTa3v2nofP4fa/+h6W8o35lmyfA/62UPj8SVzK1Z7gbMkAEbA7E69T+M/ZkWp6X1zhm77ELVcwMV1BOq4jVxmcgHCxUqiaYAx47aE9mByJ4svHzm6qNcBb6sWAn4q5Cn+AAr6ongc14A+Cwv/OiSUcObWKt7/sclw2ncRiroLbrtnV9HeSEc2LD71iOV+FzRzRMOnLF0pLpwes8IAvnFGdWlcdM2NxnFsrO122+YpXVhmG5gZ8f2lmRdiPmY5pWBqg5FkYb/m7+/Hy50zhF194yVYfSiDi4DJeTbGZgSPvXsqnhICvKoR0TBuoKixRPQ+SpbNSqGI0oSNXNrdc4TPG8OffeBIzo3G88xUHmubpRPqx17bkipYg8VLbxyEtnY7hSmNRCPirRQOjcR27MjGcWythpVCFZTPs2MDSiYRYOvzFi+kqUjH9okja/vDkMo7NrW31YYTCB9CNRDVvUcVmBg7++KLCB4BMQveuGkUYYw1XfpsB9/ATEXWgyjJXilWMJyOIacqWK/xvP7mIo2ey+M2XXd5ysAec8Qq9nqVTaRLws8UqIpqC+Aa5hU7ZVgF/KVdrPedz73dmYriwVsGFdeeyreWkrRli6WgK0vHufD/GGquARFYL1a6TwmXDQsW0Bzq5nBO2TfGphpuq8L0rjPoP32g8EmjpfPKHp/GSP/6PTTk2EV7yuHs0jpUBurJcyVcxnoggpqtbqvAZY/iLb57AzGgcr7lpT1u/m4yqKFStno6s4Aq/VG18L/OxCkTBe3a7ZVsEfF4eVjIsFNykX7ZoYDShY3cmjqpl47Fz6wCaN10Bgodv+wO+T+GXjI7fJJ89PIcX/NG3Qmfq/9onjuD9X3q0o/vm8CuQQe4I5pfSqajmtcD3YyZL2bBw/zMroY8/4lP4owk9MGn7yPwazrr24GbC33u7MjEsD9A8nZWCo/CjW6zwHz+fw7EzWfz6Sy9rS90DztWdZbOe9hHw56IUaOlUMdqnsQpAjwI+Ed1KRE8Q0VNE9J6An/82ET1GRA8R0beIaF8vHrdVVoSKHJ64zZaqGHMVPgAcO5MF0IrCd868VdNfpVNflmnarOM3+SNn13BhvRJaDnZ+rYxnlwsd3TeHe9CD3CAmWipc4fejY/MLD87jFz7yg7q6caB+n61IOq5jLaAs86yb3Asbn90vPIWfiaNi2ptaydSMlWIVEyOOwt/KOnyedL1qd7rt3+3HPB1P4QdZOiWjb/490IOAT0QqgA8BeBWAKwG8noiu9N3sQQCHGGPXAvgcgD/u9nHbQeyq5T5+tmAg43r4APCQ62VPtWrpNFTpWNAUgqYq3ljVTn18/gYNW6JSrFpdV2OseQH/IrB0+py0Xc5XwFjj3POcb/kJZzQerPDPu+W9YSsw+wW3S3aPxgEMRqUOYwyrBUdURTRlSztteSJ7ssliozBqS1B6F/D5ya8ccGJ2rOYBDvgAbgbwFGPsJGOsCuDTAO4Qb8AY+w/GGN9kfB+A9oy0LhE/AEu5ijPUqWJiLBHBrozzITl+bh1jCb3pMCWgmaVje00cfN5Kp5UcF9yrkLBkUbFqdt1Cv3YRKfxUTPOe2354wbUBX/X3HWbp8BHJfuvkXNZV+Jsc3PhJcNeoI14GoVJnvWTCtJmTtN1ihc8T2eMj7Vsl/ViCUm6i8FeLRt9KMoHeBPwZAGeEr+fc74XxKwD+NegHRPQ2IjpMRIcXFxd7cGgOq8Uq9ow5gX0xX/GC3VhSx0Qy4szHaaFCB6gFfL+l48zlcH6W9hR+Z2+SBTeBHBSMbZuhWLWQq5hdfYh4Y1i+Ynbt+X7yh6dwqkuLKYj6ssz+JW356+S/b/8+W85oQodls7ogkCsb3hWBv4Kr3/AT1Yyn8Le+UoeXQnMPf0sVft6pfElu0GQVRD+WoIR5+IwxrBWNvnaS9yLgB6WTA9/xRPQmAIcA/EnQzxljH2GMHWKMHZqamurBoTks56u4fHoECjkKn5fUZeI6FIW8QL+RnQOInbaNlg6/OuDNOZ1YOpbNsNBE4Zd71FXJT3qWewLplELFxHu/8Ag+e7j3+1TzFRNRTYGuKt7Mk34oRf48++87X7EQ0ZSGRB9Pqom2Dq/yArDps/J5WSa3JwdhgJqnql2Fv5XTMpcLVUwmIx1VvvRjCUqtSqf+OSlWLVQte+AtnTkAs8LXewCc9d+IiF4J4L0AXs0Y21QJslqsYnIkivFkBIv5SkM3227X1mlH4fsDvjhqNRPvPNGzXKh4VR5BHr64ULmbD7YYrLqxdXgzWz/6DnIV01NY/VT4PI/hV6H5itFg5wA1y06cp3M2KwT8Tfbwy6aTP+IVZoPg4fNCCSfgb22VznK+0pGdAwAjbkluLydmlkPq8HmusV+z8IHeBPwfAThARJcQUQTA6wDcLd6AiG4A8GE4wX4h4D76BmMMK4UqJpIRTI5EsZirNnSz8UqdjSp0ADHgN87S4UHJU/gdePh8RDMQnFAtCkpjuYtL9/qA33mwXnSvRvrReZoXBpepCkFXqa8evv8DWKhYDTX4QO19I/7NYvv9plfpuLtZkxEVEU0ZkIBfU/hRbWvr8J3Pf/sJW0BQ+D20dMKqdPo9GhnoQcBnjJkA3g7gawCOA/gMY+xRIrqTiF7t3uxPAIwA+CwRHSWiu0PurueU3AajsWQEU6koFvMV4UzqPLH8UrgVhR/Rwiyd2kLktBvwO1HOYuAIsnRE+6VXCr+bWnwv4Pch+VuomHUlkTFN3WSFb2Ik2qi2vBHJwnN4bisDvmkjqqsgIkwkIwORtOXHMJGMbr3CdwVfJ3hJ2x6+v7kF5xcYXsCP90/h92SWDmPsHgD3+L73PuHfr+zF43QCVzvjiQimRqI4uVjwaqgzrlLb1YbC15Twskyu8GO6Ak2hjmyOC7la4Ag6YQyawvcsnT4o/FzFrCuJjOpKXxqv8qEK3/Qu6UWCJmaeE3Yjb3bALxsWYq7YGE9GBkLhrxaqiOkK4hF1yxX+ct5pAOsE/v7rZZVOTeHXv0/4yPaxDo+1FYa+05aPQR5LRjApKHxNIW8o1t6JBABgxq3kaYauhQR8wdIhIqTjekdB8MJaGQo5J42gN1mvPPz1kuF9CLrx8GsKvz+WTkpQ+FGtP+V9YXtX8xWzoUIHqCVtg5boAI0VXP2GK3zACfiDovC5jbKVCr9YNVEyLEw02WLXDFUhJHq85pAna/1J29VNUPhDH/CXPS9Rx9RIFFXTxpnVEkaFeRUvPTiNu37lZlwz07iQwE/YPPyybz9mOqZ1NDP9wnoFkyNRZOJ64GVknaXTZZUOL1XtKuB7Cr8Plk61fvlITFfqln30Attm3lTMxiqd4IAf0xVEVKVhiQ4fdbsVCp/biRPJyECUZa4WqhhLOoErpqsom72dR9MqXBR1aukAvV2CwhjzrlIbLJ0Cn4UvFX7HrHr1wFFMppwn8sSFnOfDAoCiEF58YKqlsi29maUjNG3tn0ziqYV828d7IVfGjnTM3aUZbumkYhqWAxYotMq6EPDzXczuX8w5z28/FoLkyz4Pvw9DuPLuzH0guA4/FRDwiQiZRP0V3Nm1EvaOO8/nVnn4gPM+H4QBas4cHecEGNUUMLb5/Qn8OABgosMqHQA9XWhUMW3v/daQtC0ZXuK9Xwx9wPfKwxIRTI04Xv3JpULH3Wyhlo5R+9ABwDUzGZxYyLdtQZxfcwN+TPcaeUT48Le944muFf7OdBwK9Ubhlwyr5/XnOZ/C7scQLvEqqrHT1gpU+IBz2c0tnXzFRK5sYu+4Yw32I+CfXi7ikz88Ffiziiko/JEIClVry3fIiolSr6R2C3x8L4fXhcKfTkWxkOvNEhTxCrXR0qn2fX3n0Af81UIVqkJIxTRP4VfNzpsbmq04FBciXz2TgWUzbwpnqyzkKtiRjiIV1ZAP8MVLrsKfHUt07OEblo1C1UImrne9wk3cItbLuTxV00bVtOsUdj9a9MW/XTyZ2G4nbVjAzwjzdHhl1d6JJIDGXEAv+JcH58TFSl8AACAASURBVPDeLzzSECSA+goxHti2OnHL5+gA8I6t13ZcK/Cigk7LMgFgOhXzmiG7RVT1QVU6/Wy6ArZBwF8pVjGWcDpqp4TETadn0jBLpyLM0gHg5QMemW99wUjFdIaiNbN0eNJ2ZiyO5UKlI1+UB7lMXOtqWQtjDIu52uL3XpZmBs2x4V5wLxFPUqLCL7ofxqAqHcCp1OEKn1fo1BR+760LHuiDrLOKWXvvDULAX8pXUKhaXvVb1Gua2zqF342lsyMdxYX1ck9yEPw50FUKqMOv9nWODrANAr6oNMYSEaiKo9A7zYQrCkFVqC7gWzZD1apP2u7KxDA5EvGmcLYCb7ramY5hJKaFJG1NxHUV06koykZno3B50MgkdKRinSv89bKJqmXjsqkR5+se+vj5gDk2/UjairaZqPBrJ5zg98nkSBRzq0VUTMur0OmnpcMDRXDAr11djgZ0AW82R06tAgBu2DsKAMLgu81X+MuFKqKasuGy8mZMp2IoG3agxdouPMiPJSKBjVcZqfC7Y7lQ9epaFYU8X7GbWlddpToVJ+6z5RARrp7JtKXwuU84nY46VkuIh5+IqF6ZWSe2jhfw4zzgdxYceEnmZdOOldHL0sycMCmTE9X6ofAFD1/4AIZtu+K86ppdWC+b+LdHznuWzmwfk7b8ZBQY8A3bm+PET5DFHs5+aZcHTq0ioiq42r3K7eccpI1YzjtjVbrZIMX3XC+sd+/jl8WAX21M2vZzrAKwDQL+qq/LjpfOdeOV6apS96EW1xuKtJu4Pb/mBNAd6RjS7i5N/2VkqWohEVW9v2mpgxK8+oCvd6zwvYDvKfweWjrVRoXdj3pufrJLRbU6BSru0w3ixZdPYt9EAp+87zTOrZUwORLxgm0/hqfxE13QLt2KMKmVK9mg0bubxeFTq7h6Ji00InY/2vo/Hl/A//eFh9v+veVCpauELVDrwL+w3r2Pz1+X0YSOiml7q0xtm0lLpxesFqt1ap5PxOxmjVikIeA3KnzACfjtJG75xEVu6TCGBsum4Hafck+yG4WfjnVn6fCEmBfwe6jwvYDb58Yr/rdPpqJ19x02GpmjKIQ33LwX9z+7gu89tYSdmRgiIXOWmvHsUgF3HzuL751YwpMXcqE+cVNLJ0DhF3o47KsdKqaFh+fWcGj/uPe9XiRtv/3EAj7XwURWvmaxG3iOqheVOvw54IGdn8hzZRM2Q125eD8Y6oBv2wyrRQPjiUaF382lk6YSDFO0dFyF7w/4e5xL2odb9PEv5MqIaApGE7qnbP2J26LP0umkyab3lk7vPfzatqvac+rU4fe+LFMh5/1Qp/BDlp+IvPbQLCKagjMrJezKxEMnqTbjdz//EN75qQfxpo/9ED/559/Bt58M3gPRzNIpm5a38zfuKvytsnQemV9D1bJx494x73u9KMssuKOD290XvJyvdpWwBWp7rnup8LkI5a+rN1ZBKvzOyZVNWDYLVPjdJEcaLR3nRYz6LJ2daSdx+3CLPv6FtTJ2pB2/kStbv/ouVk0kIlrN0ulA4fPAnBYsnU4qEBbzFegqYVc61vHsoDBqlkrtdYpqCqrCZXAvyJWdEcjxSP3VA/9gNkv2jScjuO2aXQCcJL0akNBvhmUzPDy/hp+5YQYfe+shAMDcSjHwtvx4/CdVy2YwLOY1/SV0HvC3RuEfftZJ2N60Twz43St8fgJr1xZaLlS66rIFnJN+MqLWTbLtlJqH77yv+evqn+DbL4Y64Ne27tSeRH551s1lXkRVYAhBJ8zSaTdxe2G9gh0pR03w+vMwhR/TVSQjakeWznrJQFRTENNVpGJaxwvXl3IVTCSjUBQ+O6gPZZm+Tlugt9UeubKJVEx3B3yJVTo84DefL/im5+8FUNsnq6vU8jz8Z5byKFYtvPDySfzEQWfhT1gzXSXE0uH5Aq7wNXdZTC8XdrTDkVOr2D+RqFsmxO2mbhQ+P4G18z4tVk2UDdvr+O2GHelY3WDDTuEBnscfnrjluZl+B/yeTMscVGozuWsv+M/cMINUTPN22XaCrip1e0v5mzCqN54/r53J4LsnllCqWt7ldhgXcmU8d2caAASFX/8BL1RrzUATI9GOJmaulQzPK0x5o5yNDY/Pz2K+4n2w0zGtt1U6FRNENcUK1JRi2dj4uWyVdXdAm5MQFurw3YCZCKnS4dy4dwwfesONeMFlEwCc90arSVtesnvNTAaaqiAT10Pr52uX/obv+41Xl4mIiuIWePiMMRw5tYqfeE79trpeLKDnf087ORxvjk6Xlg7gVOos9kThO88B7wPy52YyXeQWW2G4Fb4wVoEzlozgtYdmw36lJTS1/rK9HFCWyblh7xgsm+Edn3pww72vF9yxCkDNO/bX4osnjomRzkbhigG/m/27izkh4Hc4HfQLD87hg/ccb7CU8mUnOa0otXK6frTo5ysGUjGtoeSTK69EwGsqQkS47dpdnmLzJ/Sb8fD8GuK6isumnLLWZrPs+bH5FX5Q/igR6d2wr3Z4drmI5UIVh/aN132fK/xu1hwWQgbcNaM2k78HAT+1scI/cmoVnz/SPLFc9hR+vaWzLuTV+slQB/zVAp8v3dsnUVeVust2/kYWh6dxXvqcKbz71ufg3qeXcMuffQcf//4zgfeZr5goVC2v5pcHfH8tfqFiecuYJ5LRjjz8tZLhrelLhVxJtMJSvuJ1L6djekcD1D5/ZB4f/s5JfP6B+brvB60X7EW1x1rJqEuic0vH39RVqFqIqAo0tb2PiHP111qO4ZH5NVy5O+09xngyEjr4LKxKJ0jhJ6Nq4AiGfsMbrg7tH6v7vqfwu7DiuKXTjp3Hr/A7HY0s0kq37cfvfRbvv/vRprcpGxYUqi1J8ndQp+P9NV2GOuDXPPzeXiZFVAWmFVSl0/h0EhF+46WX4z/e9VI879JxfPBfHw9U5bzihecYeCAWFb5tM5QMy/OVJ5KRjiZmBls67SlC22ZYyle9+UTpuNbRVcLcqpOk/MO7H/X+DTgnNtG/B7pX+BXTwlv/7n689sP3wnRP2DnX0vGXfJaq5oZ2ThC61lrS1rIZHj27XjeSezwZ8aa7+gmr0glX+FsR8FeQimm43C3T5dQUfvdJ23YU/lIPRiNzWum2zRaryFfMptU8paqzNyPu65dYKxmI6Yr3XPWLoQ74p5YLSEU1xDe4LG8X/4c6LGkrsiMdwx/89JWomDY+df/php/zmnZukSQDkrb+yhFu6bRbYbNeFgN+ZwvXV4tVWDarU/jtWjq2zTCfLeG2a3eBMYZ3ffaYV4GTq5gNCr9bL/i/f+UxHD2TRdmwvXEIvEonqiv1SduqtaGdE4T/6i+Mk4tOwvZqX8APs3TCqnR41Uqjh7/5ls7hZ1dx076xOhsOqO0j7ipp63n47Sj83gm+Vrpt+Wvz9GL4WPSyaSGuq15MEq/c+m3nAEMc8Blj+M6TS3j+ZRNdtVUHoSnBnbb+skw/B3ek8OIDk/jHHzzboAK5wud9ArqqNGy9KniJxFrS1rRZ29Uxa8XgpG07LHonKCfnkI63P4RtIVeBYTG84NIJvP/2q3DfyRV89eFzAIB8udHS4ZZZJ81Xnzsyh0/cdxo/5toNZ1aKYMyZiJmK6Yi5VTr85Ol0NLd/ed2qh89Lda/d41P4ASdw22ZeInitZNT9vPbe21qFny1WcWIhjx/bPx7481gXTXOMsZqH38ZJYzlfQUzvbo4Oh+fWmpVm8quvZnswSlW7XuFX+YnclAG/G55ZKmA+W8JLDk5tfOM2cVTcxmWZQfzSC/fjwnoF97iBjcMDvljONhKtH3vAVQ738CdH2h+vYNsMuYoZ4OG3d9JYchef8GNIxzSUDbutOmlu4ewZi+PnbtqDmK7gwdNZAK6l4/fwOyzLLFZN/P4XH8YLLp3An7zmOgDAmdUiKqYNw2KOpcNrxd37dvodOlP4rXTa1hK2NftjPBkJPIHzYxpL6DAsVldjX5vj5PfwN1fhc/9erL8X8V9BtUPFtMGroNtJ/PI1i70QfNxqbZa4XWtR4cd0xVP4Janwe8N3TywBAF5yYLLn9x3RyPOAAWGWTgsB/6UHp3HJZBJ///1n676/lK9AVaiu0y4Vqx+RzD/oCSFpC9ROFq3gNFnVqnNGIhqIOlH4zhtfrNLh998q81lnrPCesThUhfCcHSk8ft4ZQ5GvmA0efqdDuJbzVZQNGz930x7sGYtDUwinV4reFUk6pnlXD9xnLlStjqzAiNaiwp9zEraqYH/w8sEVn4/P/16uMkUfvxKo8NVNV/iHT61CUwjX7RkN/Hk3YzEKIRNNN2Kl0H2XLWd6A4Vv26wlhV92PfxYQMDnidx+MrQB/ztPLmLfRAL73KUUvaTB0jEt6CrVfXjDUBTCL/74fhw9k8WxM1nv+4s5pyNQvI9UrH4Jilcb7iZtd406b8KzbuBshTVf+ZeiEEYi7Sdc/Vck/M3ajo8/t+oc98yoM1b4ip1pHD+3DsaY562LxPTOLJ2c17WrQlMV7B6N4/RKqW5eT9SrJKktmA6bo9MMXaUN6/CDErZAra3ePy6DH9N0QMDnPxN7QBIRbdM9/CPPruLqmUxof0SsC4UvXtG089pni71TzbzbNiwhm6+a3lVIKx6+J16qUuF3TdW08YOTy3jJgd7bOUDjZbt/n+1G3Hr1TgDAQ3P1AX/SVz7mX4LCVRsf2TvjdnfOr7Ye8LmqFd9cnQxQW1ivIKopXlDm99fOiWNutYjJkYgXJK7YlcJq0cBCruIo/JCkbbvVHnnfbPu94wmcWSnWRjBH9QCFb3bU3NVK0vbkYh4lw2oI+PyKzd89zVXtDvfkGqTwxfdfMqKiaGze0vCKaeHoXBaHQuwcwFH4ndbh11tY7XXaNpuF1C7Num3X3NEIl04mcWG9EprP4lU6RIS4rnqlqutCqXQ/GcqAf+TUKopVCy/ug50DOJZOXR2+Wb/PdiOmRqKIqArmBGUudq1y/OsHSz6FH9NVTKWinlJuBb/CBxyF266l8/D8Gq7Ylfb8UV4/3K7CnxlLeF9f4XYZP3g6C5uhZ2WZ/jENs/6AH6bwOwj4rSRtvQ7bPfUBf5xbOr5KHZ7Y25kJsHR8oxUAJ6nPWHedre3wyPw6qqbdUH8v0o3CF5vI2lH4hYq14WiMdmjWbctfkxvcoXEnF4ObLMvCZrx4xOmXsNy82kWj8InoViJ6goieIqL3BPw8SkT/7P78h0S0vxePG8Z3TyxCU8hrd+81uqr4PHwrsAY/DEUh7BqN1SnzpVxAwPd5+LX5LrVAtGcsjrls8MCtIMRtV5x2Z+Iblo1jc1ncJExE9CydNk4cc6sl7Bmrjbi4YmcKAHD42RUAjZMqO2288k/e5Avgz7sldrxKR7zvQsXsKFi00nh19EwWI1GtLmEL1DrC/aWZDZaOsM0qbLQCgE3rtj1yynm9btoXXKEDdOfhi2Mi2jmJOVeJvSvJbtZty4UOT1qH+fhirIjrKkqG5YmtiyLgE5EK4EMAXgXgSgCvJ6IrfTf7FQCrjLHLAfw5gP/Z7eM24zsnFnHj3jGv5LDXOB6+0HglLJFulZnRuJe0ZIxhMd9o6aSi/qRtvcIHgD1jia4VfiqmIVdpPVAfP7eOsmHXVWTwy9FWS0R5Df6e0VrAH0tGsDMdw2G34iMVpvDbDBz+dYV8M9VjZ9e9x/FfPZQ6nNejt5C0PTaXxTUzmYacTzzi1Gev+gO++/fuDErahjReAdi0eTo/erZxYJqfbpbXiKOeW726Y4w5uyN6aulEsbAevEeazzi6ZiYDXaVQH79s1IoBYrqCkmEFfib7RS8U/s0AnmKMnWSMVQF8GsAdvtvcAeAf3H9/DsArqNfF8S7L+QoemV/HSw72x84BnMaraoPCby84zIzGPYW/VjJgWCxY4Quji4s+Dx9wFP7ZbKnlOeHcLqgP+O0pfF6Cd+O+WkVGuwp/KV9B1bTrFD7g+Ph8umjSp7B1VYGqtN/Aw5OzSUHhA8Bj55zHqbN0DAtVt1yzE0tno2mZZcPC8XPruG42uJplPNk4H4lfdUyMRKCQP+A7z0VEGAHBj7to9F/hM8bwwKnVpuoecD38DhuvOknaVi0bps16GvCnUzFHkQckxPlrMjESwb6JZKjCLwmxIh5RUa5awliFiyPgzwA4I3w9534v8DaMMRPAGoAGv4WI3kZEh4no8OJi8CKIjYjpKv70tdfhtmt3d/T7rRDxWzpmBwF/LI6FXAUV0wqswQccRWrazFNxPGkrJuj2jMVhWKzlbTyPnV3HnrF43VVCu0nbI6dWMTMar5s4GtMV6Cq1PE/nzCovyUzUff+KnWmY7snL7+EDzhrJMKW4XjbwmcNn8K7PHqsbOcE/oPwE4gV8V+GPROvLMrlnHu/A0tnIwz9+bh2GxXD9bCbw5xMjjd22PMjFdRXpeP3MorJhI6Iqdd2t/MpkM7ZenV8vY7lQxfV7g09gnG4UPremiFq3dAq+npVe0KzbVlTpl0+NhCp88cqRWzoXm8IPUup+udnKbcAY+whj7BBj7NDUVGcVNsmohp+7aQ8umex9OSZHVxXYDJ6qdhIx7Vs6AHAuW651rfqrdLxJls4bolhxmoHEDzcPmK3aOkfPZHG9T13yrVetVnU8cGoVN/oqMoiorfEKYtOVyHN3pbx/B1VYRPVgpfix7z2DH/vAN/Huzz2Ezx2Zw30nV7yfFdyKH/688U1f62Xn+dRUpS5py5VxZwq/eeMVL8VtR+GL01hHfQG/Imy74mzmInN+9TS6QbCKhbxuQXz0uyfxZ9940vuaW1Ojcb3lSp+NVlR2ws4mm6/WSgY0hZCIqLhsOolTy8WG8lzGnL0TfPd17CIN+HMAxHnDewCcDbsNEWkAMgBWcJGiqU7g4EquYrZXlgk4Ch9wmo9qCr++ScRbguJ+qIpGY9UBD5ji4LEwFtbLmM+WGgJ+OuZ0cLZSRXE2W8LZtTJuClB0zniF+mFvj59fx788MIfPH5nDl47O4/Ry0T1etwbfb+m4lTpAo4cPhCv8j333JK7YlcaH33wTgHrbI18262wwIsKse6LkJxVR4XN12GlZptHkeTw2t4Yd6WjoPobAgO819jkz87M+he8fuJXYRIXfatNhtMmVmchHv3sSH/jqcXzucM004Ap/LBFpudKH/05PA75bJcXnMInwOnoiwmVTI7BshtMr9ZU6Xr5FVPhVy8t7bUbA78Wz8SMAB4joEgDzAF4H4A2+29wN4K0AfgDgNQD+nW1WkXAf4H5p1XJKrMRSq1bZ4zYbza+WPAU/NRKru403E99VK1zhi/ArhbmVjRX+g666vGFvvToXxyts9HfUWugbPdt0TPMU/gfvOY5/PnwG2WK94r90Molv/PZPYD5bwkQy0nACu3QqCV0lx0MP+LA6z3d9IFvKV3B2rYxfftElXimumEvIB9Rj7x1P4LFz697fHhMUvjcLvxNLR2teh3/sTDa0GxVwKnXCyjJjWqOlUzGthoIBftylTfDwS4Ld1AzxdXtkfg3v+NSD+Nyvv6BudPFnDp/BB756HFFNqTupObXrSsMaymb0Q+HzTufza42fNXE+1eXujuenFvK4fLp2xeqNYNEED3+TFX7XzwZjzCSitwP4GgAVwN8xxh4lojsBHGaM3Q3gYwDuIqKn4Cj713X7uFsJX1bNRySXjcbL6o3YmYmBCJjLllA1HR/WPwubWzpc4Rfc9YYiMV3F5EjUq/hpxtEzWegq4ard6brvpwTrqFmlBeAE/Liu4grBeuHwAWr3Pr2ED3/nJF5xxTRedc0uXD+bga4quO/kMn738w/jy8fOujX4jSpXVxVcPp3C8XProZaOXynyQWRXz2QQ11VoCjUo/IaAP5Fw/3bnQ+at4TPsmjrsqA7fSdoyxhpmuKwVDZxcKuDnbtoT+vvjIxGUDKtu0Q23dOIRFZm4XmffVcxGOzG5qQq/cZZPEFFN8YbT3XdyGc8sFfDQ/Bpe9pxpAM7sq/d8/iG8+MAkbpgdxV/++1PuyUx1trxFnEqqVhP2efdv72VZZkxXMZbQvXJekbWS4ZU6czv55FK9wvdOjgEevq5S27ZwJ/Tk9McYuwfAPb7vvU/4dxnAa3vxWIMAD/jc0gm6rN6IiKZgR6pWiz+Vahzy5F+CEtbuv2cs3pKHf/R0Fs/dlW5Q8VxZtJJwfeD0Kq5zA7ifdEzHfLaE//W1J7AzHcOH3nhj3WPNjiXw999/Fn/5rROwGcOVvhMP54qdKZy4kAssdXUCR/2Hni80uWq30wiW8W3fCprLMzvOA77z/drwNEtI2nZm6TA3v8OtP84xt7Pab6mJ8Nnty4UK9kScYxSnsWb8Ct+wGi2dTfTwWx0cKA6+O+0uan96Ie8F/AdPr8JmwPtvvxI/cPMva0UD02lnXWMiqraV+OWjJXrZeAUAOzNxnA+xdPjcnlRMx1hCxxnfVbdozTn/dywd0Q7qN0PZadtv+AeZJ2UqbTZecWbG4pjPFt0a/MYhT/4lKIWQCY5OwG/u4Vs2w0NzjQlboLZHc6OAX6yaeOzseuhExHRcw8nFAh44ncV/feWBhiCgKIR3vuIATi4V8OxysaFCh/PWH9+Pd9/6nMAPgH8zFeAo/Eunkp5a9+cSCgFjGmbdqwsv4HuD2Wyh/LWDxiuNi4FGx5InbP0dtiJ8/7Jo6zhBXQERYTSh141Idrq869973F7ZDIVfajHgx4ICvtCNemIhD10l7JtIeglgbut4Cr+N5q3aOI3eBvxdmVhTD58zO55o+Ex6QsKrw3euVjdrrAIgA35HRASFb9sM+arZUZMXb75aDOiyBWp2Q83Db7R0AKdSZz5b8paHBHFiIYdC1QoJ+K0NPvvysbMwbRY6o4jX4u+fSOA1IbbFrVftxMEdI+5xBycur58dxdteclngz4Iu6x+ZX6ubS5OOaXUnr1y5sQGHl2am3GYsIvKuHril08m0TF3I7/g5NpfFZVPJplMR+a5TMeCLfR6ZuA7LZl6JbsWwGwoGVIW8pp5+w0++G10N1bqkLS9xL5YunriQxyWTSeiq4g2R4w1oRdfeCsrfhNEPDx9w5+mEWTpiwB9zxneI+Hdfx3UVVcvGarG6Kf49IAN+R3gevs28ccOdvGAzY3Gcy5axsF4ODPi8ssQL+IbZ0IwEiLX44WOSj54OTtgCtWP3J1hFGGP4+L2ncMXOFG6+JLjJhquU37rlYKDlAzgq/7++4iAA4NLJkcDbNMOv8hZzFZxbK9cHfJ+lU6iaXsUTZ2Ys7uwWFfImUU2pq8PvZB5+xFfBJfL0YqGuCimIIIUvlv3WXivn5+WAskzA6TkobMLETE/hb9BpzoNcsWrhjKt8T4oBfyGHA26CczRRr/CLVQvJiOblAVrBP2iwV+zKxLCUr9bZirbN6rbIAcCecUfMiQ2RfDJmrfHKec4urJdlwB9kdMHS8brkAkoIN2JmNA7TZlguVBtq8AEnkRjRFK8pqlgJbvdvpTTz6JksRhM69k802iitePj3P7OC4+fW8Ys/vj/Ua/zpa3fhXT95ELdv0PT2U9fsxFfe8SK88PL2Zx1FfT4u78oNC/iMMbcs0z+XR8X/ft0NeNPz93nf47Xi3ZT0+fM7IutCYi8Mvo5PDPgln8IHaq9V2FiPRFSt61DtFy17+O4xPrtcgGExXDKZxFK+imyxirJh4fRKEQfcKz8v4LsntYJbnRaUsA+jUDGhKVTXgdwLeGmmOBc/SPTNjiVgWKzuasBLvgsKH3Dq+jdjFj4gA35HiB/qbkqqxCqVyZDqmOlUFM8sOUqoUA2eDdJK89VRtxwwKFhHNGcNXLOA//F7n8VoQscd1/ubqGvsm0ji7S8/0LDT1A8R4eqZTEdJqpivRf/h+TUQAVcJAT8jrFusmE6LfVDX7u3X7a7bl8A91VLVAtHGKyuD8N4bvgFqjDkqcKMPdjqmQVOorttWHL+d9gf8kC7vhK5tStK2XQ//xAXnvcyTtU8vFvD0Yh6MQVD4zkmPX3EW3WIFJ3/TuqWTjGo9T4Ty5ivRxw+KAbwoQLR1StX6ngX+//wmTcoEZMDviFrAZ10FfHFwWJDCB4AXXjaJe59eRtW0UTbs0KQt0KjwK6aFf3lgDj/7N9/H4+dzoVYMP/6wgD+fLeFrj57H635sb0eVK73EX6nx0NwaLp1M1iXn0rFaYrOd5J3THGShUHEshE6CBU/a+j18vk7RX3rrh4gw5u625ZRN22vWGXUT7PwKprzlCt8pKd5o+Q+3pJ68kAMAvOwKJw/09GLeOwlwhZ+MqNBVwqoX8M2ah99GWWavE7aAY+kAqCvNDAz47mfyjCDCyr6eBfGztFkBv/fPyDaAWzqmqPA3uFQPYrcY8EMU/osPTuKfD5/BfSeXATQOFAOCa/Etm+HX7jqCbz+xiEsnk/j9256LN79gX8PvcjJxvcHDNywbP3h6GX/73ZMA0PT3Nwt/4u6R+TU8/9L6E1km7nQOlw27ttWqhQ+/Y+nYKBmdLT8BhKY8n9fMA3Qryf2JZCRA4bsefqJR4QeVBIseftW0cedXHsUlkyO4/dpd3pjlXtDqaHB+jE8u5KEphJsvGUdEVfD0ovO1phD2u1dbTmltBGulWtI2GVER01QYFoNlsw1PMJ3uJN4IbumIzVfZUuNAwpmxOIh8Ct/XsyAWBciAP8BoQiVGNwo/GdUwmnACbVjAf9HlkyAC/u3R8wDCqyH2jMVx/FwOpmVDUxX8xTefxLefWMT7fvpK/NILw313jr92fW61iP/0oe9jKV9FMqLit1550Ovq3UrEBp7FfAXn18u4xte5ylX0WsnoSOEXAxrcWiWiBSdteZloK7ke/3iFimF5Noc/wR7UeAU4Cecld0bT4+fX8Yn7TgMA/sdXH8Obnr8Pd95xdVt/VxitTorlx3jiQg4zY3FENRX7JxN4eqEAhYD9k0lEhCsV/rmwbea+HlqtG6CfygAAHhZJREFUG9rYeP1kvsejkTmpmI5kRA22dATRF9VU7EjFvAQ1IOQ7IvUePrB5AV9aOh0Q6ZGlA9RGI/hn4XNGExFcu2cUX3/0AoDwqoNXPncaR89k8TN/cy8++t2T+Kt/fwq/cGi2pWDPj1+0dB4/l8NSvoo777gKR/7gFrzjFQfa/dP6gtjA8+i8M+3Svyqwtm6xvYDPFX43m5LCkra1hekbv0/8AV+s0klGVKhuJ7EzjCtY4SciNUuH7zz+36+7Hi+/Ygc+cd+pjpeR+Cm3uDeAH2OxanklsZdNjeDkYh4nFvI4MF1fsTWW0LFarHqqOBmtLf5u5diDei96xc5MfWkm/9xwu40zOx6vG3niH60QE543WYc/wOhavaWjq9RRzTbgBPxERG2qRl5yYNJTa2GB6O0vP4C/eeONOJst4QNfPY5r92Tw3+64qmUf2hnKVQsy/PFefsV023OC+onXwGPYXh03r+vn8KC6VjLqFpVvBFf4JaNzOyCsDp9XWm3k4QONAV+s0iEi7EhFcWa1BNNmsFlwcjkRrSVtz2ad4PTiA1O44/rdsJkzyqAXlFrc5yxeheybqAX8UytFnFou4MCO+lEdmXgE2aJR64lwyzKB1vbadnOVthE7fc1XYaJvdizhU/g2VIU8S1iMGa28L3qBDPgdoPssnW7aou+4fgZvfN7eprd5sdDo1OxN/FPX7MI3fvsn8K6fPIiPvPlQW4Gad3ByeMAPu/LYKsQhZ88sFTCW0D27gyM2krVTYsnzA4WQBrdWEBP6Iu14+KOJCNbLhrdzoewLqtfvHcUDp1ablkQmI6rXaXs2W0JMVzCW0L3E6ImQBR3t0upocPEYPYU/nYTlnrSCFH62aHijkZOR5gr/T7/+BL7yUG1Ib76fCj9dP15hrWQgoioNz8Oe8QTOr5e9qrKSm4vhsUJaOhcJulL7UK+Xu2uLvu3aXXjvbf6NkPXcsHfUe/NuZDWMJyN4+8sPeMmlVsnEdZQN2/swLeWrSEW1gVL3gDjkzAn4QXsPxNJFb1F5Kx6+u2i71I2H75Vlhij8ViydhA7GasrRnxi9ad845rMlnHI7VoMar+IRDSXDgm0znF0rYfdoHESESyaTUBXCU261TLeUWvTwxauQvePOaybu9D3gu0obTThXnEVhcmnNw29U+P/4g1P48rFawO/1ekORXZkYFnIVr6lqrejEAL/omx2Lg7HaFZbf/tqKKh0Z8DtAFxJz676W6r48nqp4C9l73TnI8Y9XWMxXQnsDthLxQ//MUgH7AwJ+ncKvtGPpOHX4RaOzBeZA/XtDxPPwW7h0H3Obr3hZoliWCQCH3FlG9z695B53UKetc/uSYWE+W/ZyRVFNxb6JBJ680BuFX2k5aduo8C91A76qUMOJezQRQdmwPWsrGVW9/I2/NLNiOgPIlvI1G6xQ2Tix2yk7MjFYNvOugp2r/MbH8tfil3z5lphU+BcHtfHIdsMMjX7x8iumQeTMS+8HmUT9ALWlXPBAt62GWxurxSrOrZVxaUDA5wPR1kom8hUTCrU2FyemO7N0wmYWtUKYh79eMqAqreV6vFkyxSpsm6Fq1s/LuXJ3GnFdxfefWnaPOyBp6wa7QtXE2WwJu4WFKwemR3BioXcKv5W/Sex45aOpR6IadqZj2DeRaEg8825bnnBORGprKBv3IVTd/zsBuGraqFp2T9cbiuzyNV+tlYwGWxEQAr7r41cMu07Vc/GiUO+HvIUhyzI7oPahdqp0+rlOkfMLh2Zxw97RntZQi/hb9pfyFRzc0Tjzfqvhwe2J807AuiRgHo+uOp3D62UDlrvIupUcS1RTUTFsmBbr3tLxefi5sol0rLXjEIeHeVuShKCqqwqum83g/mdW3OMOV/hrRQOLuUpdz8eB6RS+eXzB2cPQQTexSKsevqIQIpqCVFSrC253XL878ITFK17mvYCvgpfe+6el8h2zy3let9+fwWmculr82VGslQxvOUrd7dIx6Cp5Y5JLPmsuoiruPKfNGY0MSIXfEbowIGuzFL6i0IaDt7qhMeBXBy5hC9RU0fFzTklm2MmWl5m2U54X051tVaWAVZKtooc1XpWNlieqjrkTM8WyRH9QPbRv3PtZWFkmUBtBvHu0FpAO7HBW8D273H2lTqtlmYAzYG2vb5bT7/3Uc/FbtxxsuO2YT+E7w9OCFT5fEZqvmCgbVt9GI3NqAd850WSLwTFAVQi7R+Oewi/7roaInCu+zbJzABnwO0L8UG+Gh78ZjAoNPXwo3CAGfP6h5wF//2TwTH2+UL2dag0xcHbeeBVch58rmy2X3tUsHSO0Euem/bWpp0FJW37Cesq1bvwKH6jNtekGvy/djJGo5nXTbgRvYjrrdrTyBShAY1nmYr42yGwxV6klevuU7xpPRBBRFZxzryyaxYDZsQTmBA/f/zryLWabhbR0OkBzry1Xi1XYHY5GHjREhb9ccEsyUwPo4bsf+icu5LArEwtV4lzhRzSlpYSteN9A5wFfDxmPvF4yvNn7G5GIOFNSVwvV0BWCNwpjrgNHK7jBjpdfigH/0qkkFHLm2tyGXS0dUxiVNvY5/+Xrbwi0PoLgJz2+ES4Z0byrJr/CFydXLuUr4GZavywdRSHsyERxfq0My2bINRl+NjuewL89cg627Yz6mBxpXFEqFf6AQ+SMXeXJos3qkusnYinjUs75uwZR4ddqse2muZN0XMN62WxL4YuBq2tLpwuFT0Rep6m3Fs8X1DNx3Ws4C/Lw47rzWFzF7xLKdGO6ir3jCTzVZS2+ZTNULbvlpsND+8e9ROZGeEnbtTKInBNeWB2+qPCX8tVaZVYfE6GzYwn83ycX8U8/PAUgXPQ9/9JxrBYN/K+vPxE4hmLPWHxTcoAcGfA7RFMJS653OAwKX1UIKXdT1KA2XQH19kXzgO9aOgELzEPvW+uFwg8ej9zKaGSRsUTEsXTM+vkrIjftc4bGBTZeuQr/5FIekyORhttcPp1qu1LnwnoZr/7r73m+eqsLzDshrjtXOVXTRkJXQVRb8l32Wzq5ijejaDlf8RrO+tVpCwDvu/1KzI4l8AdfehRAeAx49XW78fqbZ/E3334ap1eKiPueq4//0s34/Q36cHqJDPgdoquKZ30MQ8AHajYIV0xhI5u3EtG+aBrwXQ+/nQacOoXfoTpUFYKqUKCH384azLFEpN7SCbBtXnHFNKKaElg+y69QyoZdZ+dwDuwYwTNLhcBFLWE8cGoVD82t4bGzTv6EJ437MTKbiLy8En8tmiVtr9jlFDQs5SubovCv2JnGF3/zhfjgz16Da2YyuGFv8GJ6IsKdd1yNH79sApbNGq6GYu6JbbOQAb9DdMHSGbaA7yn8AfbwAceLDiMT15GrmFgrGZuq8AHHxxcDqWU7c/nbmZcynoy4lk64in7llTtw7P0/GVgDLjboiTX4nAPTIzAs5nXrtgIvkcxVah3AQPDJqBdwW4eXmPI5NP5O28VcBXvG4kjFNMfS6XNZJkdVCK+/eS++/I4XeU1kQeiqgv/zxptw8/5xXB9yYtgsZNK2QyIq4dz68Cn8bLGKpVwViYjasY/dTyKqAiKAseAafA7PSRSqlteItRGiwu90GB7gfMBFD58PcGtH4Y8mdLdKp7EOXyT0+0IQDlL4vMfiqYUcLp9ubbcw36jGx0T4x/32Gn4iiwvvQ//GM8YYFnMVTKWimBqJYjFf8RLDm9XM1AqZhI7P/PoLtvowpMLvFE1VwFybdlgCPh+gtpSvDKR/DziXyDFNhaaQt+krCPE1ad3SqX0culGHEVWpU/i10cjtKfxssTZLpt2ZRopC3lWKWIPPuWxqBAoBx8+17uM3BnyeUO5PGOGWjtgx699ru14yUbVsTI1EMTESwVLOsXSUDldUDjvyGekQXn6nCR+six3H0jGxXBjMsQqcqK5g73jCS5AGIQbXzazDB1yFLyQWeTNbewo/ApvVmoo6SYzyK7QghR+PqDgwncKxuWzL98ctHX4CK/fRwwdqpZliPsW/13Yh59TCT6djmByJYrlQ9ZafbFb36sVEVwGfiMaJ6BtEdML9/1jAba4noh8Q0aNE9BAR/UI3jzko8GDTzWjkQSMd17FWciydQVX4gHNZv1Epm1gq206nLaergK9R3WiFdmbhc8bdbttzbuNRJz55TeEHXwldPzuKY2eyYIwF/tzPvNsxyv+eVheYd4rfw+ePJQ5P4yfEqZEoJkeiXtJ2kOycQaJbhf8eAN9ijB0A8C33az9FAG9hjF0F4FYAf0FEW5u56AFiwB8WRuMRGBbDmdXiQE7K5LzzFQfwKy+6pOltMh0E/HqF352lUw20dNpT+EBttG4nKrqZpQMA182OYrVo4PTKxonbXNnw1jQ2Wjr99fDF18K/xN6rKEs5AT9bNLBWMobmqrvXdHsavAPAS91//wOAbwP4XfEGjLEnhX+fJaIFAFMAWr+WHEC4pTMMTVccHiSLVWugFf4bNlgYA/gUfoveOa/xj2rKhkuym6GrSt08/HZm4XP4VFSu8Dvxo5NRDRFVwWQy+LW8ftbRXUfPZLFvg5EH3M4BgLx7AquVZfbJw3cVvhi8Y1r9Enuu8KfTjocPAKdXilLhh9DtK7WDMXYOANz/Tze7MRHdDCAC4OmQn7+NiA4T0eHFxcUuD62/DKPCF/+WqQH28FuhG4XfrTqMaL6kban1Wfgc7l+fXysjKmxJaodERMWu0RiUkJPXwR0jiOsqjp7ZWHvVRhyoDVU6rc7SaRc+QE2ciRPVlbqAv5CrIOpO4eQi5fRKse8lmRcrGz4rRPRNADsDfvTedh6IiHYBuAvAWxljgd0ejLGPAPgIABw6dKg1Y3GL4M0SwxTwuaICBrPLth34sm/LZm17+N2Wo+qqEujht6M6+cTM5UK14/fYG5+3zzvZBKGpCq6ZybQW8F2F/5ydqYaA36+kbcYdkZz0lWVmi7W/iZdkEhGm3L4RZ5+tDPhBbPisMMZeGfYzIrpARLsYY+fcgL4Qcrs0gK8C+H3G2H0dH+0AwQeoDVPAF/+WQfbwW4GIkI5pWC0aLas9XuPfrcLXVWrw8JMRFVqTqiI/I1ENmkIwbdbx6IJbrw7SafVcv3cUH7/32Q1n48+vlhBRFeyfTOK+p53FK8126vaCQEtHb7R0ptz3qihSRvo0KfNip1tL524Ab3X//VYAX/LfgIgiAL4A4B8ZY5/t8vEGhmG3dC52hQ/UfPxWG6+ICFFN6UHAr7d0cm3MwhePha867Ode4ev2jKJq2nj8/HrT281lS9g9GkM6pteqdKr9rcPfmY4hoil1VUZRX9J2IVfGtBvwJ4T3rLR0gun2lfojALcQ0QkAt7hfg4gOEdFH3dv8PICXAPhFIjrq/nd9l4+75ehDaOlk6iydi9vDB5zXRlOorYRnTO++w7ih8arU3lgFDvew+1UFA8Br9d/I1plfLWFmLI50TEO+ajrjfk0LukptXbm0w1gygu+9+2W49aralUpMr++0FRV+MlKbmS8DfjBdvVKMsWXG2CsYYwfc/6+43z/MGPtV99+fYIzpjLHrhf+O9uLgt5LIECr8kYjmdSgOQ5VDOqa33YDTK4UvNl61OymTwxO3/RpdAAC7MzFMpaI4enqDgJ8tYWY0jlRMB2NAvupsl+rnyQhwGqrEpHNMq3XaVk0bq0UDUyNO2SkReVemSenhByI7bTuEe/jDVJapKIR0XMfkSHQomslGE3rLdo73O/FI4DCydtC1xqRtu8cBCAG/jyMCiAjX7RnF0SYdt2XDwmKugpnRhPd35MpuwN/kenexSodPq51O16wcL+BLDz8QeRrskGG0dADn7+k24A0Kv/myy7GQq2x8Q4EPvfGGtv12P7pKDQq/2WTPMHilTj89fAC4Ye8ovnn8QuiVyDl3d+vMWNwbKpcvmy0vMO8lMU2FaTOYlu1tuhLHeHMrchiuUPuBfFY6hFs6nXizg8yB6ZRX3nax89xdaTy3zQ1+l7v7XrshqvmTtl0q/D4H1St3O7PkHzu7judfOtHwc16DPzMa9/6uXNlAqWp1NVW0E8S9tt5YhVSjwu90n8GwI5+VDuGdtsOm8D/y5pu2+hAuesQqHcYY1ktdevh9DqpX784AAB4NC/hZZ/TCnrG4tyshVzZRNhtX9vUbcc3hQpOAL8syg5EBv0O0IUzaAgjtypS0jth4VTZsmDbryCbyyjL7nBidSkUxnYri0bNrgT+fXy1BIWBnJuZVyKy7Cn/zA35tzeET59eRiKh1i9G5pSOTtsHIpG2HzI4lsCsTk16hpAFxAYo3OK2bssxN8Mmv2p32Vhf6mcuWsCMdg64q3onLUfj2lir8o3NruGYmUzf3aKe73WtY8lC9Rgb8Dnn9zbP47rtfNhTVLJLeEnFXHDLGkOtgUibHU/ibUAlz1e4MTizkG/bFAm4Nvtv8VFelU7UalnL3G95TsV4ycPzsesPKwFc+dxp/+5ZDOLijtS1e2w0Z8DuEqH8NJ5KLG93dhmbZDGslvt6wm7LMzQj4aVg2wxPnGzdgLeYrXuljXHdmFOXKxpZ4+FH38R48nUXVsnH9nvqAr6kKbrlyhxRiIciIJZH0GF6yW7XsmsLvINcznoyAaHNKDK8SErd+skXDO/kQEVIxDfnK5jRe+eGP98NnnHk+W70U/GJDGtASSY/hc5YMk3lLQ9rZZ8vJxHV89C2HcOPehkVyPWd2PI5UTGtI3No2Q7ZY9QI+4Fyt5MqmU5a5yY1XPJ9x/zMrmE5FsTMdvNxFEoxU+BJJj4m4JbtVy8aKW8bYaRLxFc/d4Xn5/YSIcOWudIPCXy8bsFn96OxUVHctHdtbGrNZcAtptWjg+tlRad20iQz4EkmP4WOGDcvGmdUS4rqKiU0I2t1y1e4MHj+/DsuujYVYdWfP+xX+WslA1bS3oPGq9njXzUo7p11kwJdIeoxn6Vg2zqwUMTsevyiU6FW70ygbNk4u5r3vrRarAJx8AicV07wu162qwweAG2TAbxsZ8CWSHiMG/NMrRcyOJbb4iP7/9u4+tq66juP4+3N7+zDWlq5unds6ZcgCMgTBhYAPSHjQDQkj0T8wJM6IIQYT0RhxZH8Z/8H4bEQMAd0kBIyIshA14CT6F+hQMxEYG6AwHGtx3eja0W7w9Y9zTne73m7t7vXenns/r6S595x71vP75Xfz6W/f8zQzq5Ylt1goLevsTwN/Ukmno3Ui8Gs9w88epyjBe/pPrem+G4ED36zKssAfO/IWu4cOsbw3H4F/xqJO2ooFnt5zNPD3jZQv6YyMZ0+7qnUNP9nfGYs6K77JXTNy4JtVWVsxKd8MDI9xcOxIbgK/2FKgv2fexPNr4egMf8ExJZ1MzUs66Qzf9fuT49Myzaosm+E/P5DUwt+Rk8CH5L46A6+/MbE8NDpOS0GTTistnVnXOvALBXHLmjO5ZOWimu63UTjwzapsIvAHR4B8BX5fdwfbSx6GMjR6mJ55rZMOOtdzhg9w06Vn1HyfjcIlHbMqOxr4yQy/f8G8420+p/R1tTPw+hgRyamZQyPjU64DKJ3h1/qgrVXGgW9WZdnDcV4YHGFhZ1uuHqjd19XOocNvcnAsuUJ4aHR84q6dma720hm+IyRPPFpmVdaaHrR97eAY/Tk5JTOT3SQte7jI/tHDU64SLi3peIafLw58syprK7mLap7q9wB9Xcm9abLnxZad4dfxoK1VxoFvVmWtJYG/vDc/9XuAxRMz/DeICIZGDpep4R+d4df6XjpWGY+WWZVl99KB/M3wF6Uz/MHhMUbH32T8zbcmXXQFLunkmQPfrMomzfBzVsPv7ijSXiwwMDw2cR+dY0s689uKZGdpuqSTLxUFvqReSY9K2pm+Tnvjbkndkl6R9MNK9mk217W2HD1nPS9X2WYk0dedXHy1v8ydMiG5+KmzvUixoEl/3Gzuq3S0NgBbI2IlsDVdns7XgT9WuD+zOS8LwWJBLDk1fw/o6OvqYGB4jH0jU2+rkOlqL3p2n0OVBv46YHP6fjNwbbmNJL0PWAw8UuH+zOa8LPCX9szL5XOP+7raj1vSgeRMHQd+/lT6bVwcEXsA0te+YzeQVAC+DXzlRL9M0o2StknaNjg4WGHTzOqjpSBaCsrdAdtMX1c7e0tKOuWe1tXVUfRFVzl0wksAJf0eeHuZjzbOcB83Ab+JiJdP9BCIiLgTuBNg9erVcdyNzeaw9mIhd6dkZvq6Oxh+4wh7DiQ3Uesp8wD27nmtHDh0uNZNswqdMPAj4orpPpO0V9KSiNgjaQkwUGazi4EPSboJ6ATaJB2MiOPV+81y7baPn8uqpd31bsZJWdSVnIv/3N5hujuKZctSn/vwuyZKPpYfld7kYwuwHrgtfX3o2A0i4vrsvaRPA6sd9tborjlvab2bcNL60sDf8erwtA9Qv3BFby2bZFVSaRHuNuBKSTuBK9NlJK2WdFeljTOz2stur/DK/kNTTsm0fKtohh8R/wUuL7N+G/DZMus3AZsq2aeZ/X9lN1CD8mfoWH75MLuZTdJ7ShvFQnKChWf4jcWBb2aTFApiYWcyy5+uhm/55MA3symyu2a6pNNYHPhmNkV218xyF11ZfjnwzWyKvokZvgO/kTjwzWyK7Fz8BfNd0mkkDnwzmyI7F98z/MZS6ZW2ZtaAPrJqMS/tG2VlX2e9m2JV5MA3sykWdrazYe1Z9W6GVZlLOmZmTcKBb2bWJBz4ZmZNwoFvZtYkHPhmZk3CgW9m1iQc+GZmTcKBb2bWJBQR9W5DWZIGgX9X8CsWAq9VqTn15r7MTe7L3NRIfYHZ9+edEbGo3AdzNvArJWlbRKyudzuqwX2Zm9yXuamR+gLV7Y9LOmZmTcKBb2bWJBo58O+sdwOqyH2Zm9yXuamR+gJV7E/D1vDNzGyyRp7hm5lZCQe+mVmTaLjAl7RG0g5JuyRtqHd7ZkPSckmPSXpG0j8l3Zyu75X0qKSd6euCerd1piS1SPqbpIfT5RWSnkj78nNJuXmGnqQeSQ9IejYdo4vzOjaSvpR+x56SdJ+kjryMjaSfSBqQ9FTJurLjoMQP0jzYLumC+rV8qmn68s30O7Zd0q8k9ZR8dmvalx2SPjrb/TVU4EtqAW4H1gJnA5+UdHZ9WzUrR4AvR8S7gYuAz6ft3wBsjYiVwNZ0OS9uBp4pWf4G8N20L0PADXVp1cn5PvC7iDgLOI+kX7kbG0nLgC8AqyPiHKAFuI78jM0mYM0x66Ybh7XAyvTnRuCOGrVxpjYxtS+PAudExLnAc8CtAGkWXAesSv/Nj9LMm7GGCnzgQmBXRLwQEePA/cC6OrdpxiJiT0T8NX0/TBIoy0j6sDndbDNwbX1aODuS+oGPAXelywIuAx5IN8lTX7qBS4C7ASJiPCL2k9OxIXm86TxJReAUYA85GZuI+BOw75jV043DOuBnkXgc6JG0pDYtPbFyfYmIRyLiSLr4ONCfvl8H3B8RYxHxIrCLJPNmrNECfxnwcsny7nRd7kg6DTgfeAJYHBF7IPmjAPTVr2Wz8j3gFuCtdPltwP6SL3Oexud0YBD4aVqiukvSfHI4NhHxCvAt4CWSoD8APEl+xwamH4e8Z8JngN+m7yvuS6MFvsqsy915p5I6gV8CX4yI1+vdnpMh6WpgICKeLF1dZtO8jE8RuAC4IyLOB0bIQfmmnLS+vQ5YASwF5pOUPo6Vl7E5ntx+5yRtJCnz3putKrPZrPrSaIG/G1hestwP/KdObTkpklpJwv7eiHgwXb03+29o+jpQr/bNwgeAayT9i6S0dhnJjL8nLSNAvsZnN7A7Ip5Ilx8g+QOQx7G5AngxIgYj4jDwIPB+8js2MP045DITJK0Hrgauj6MXS1Xcl0YL/L8AK9OzDdpIDnBsqXObZiytcd8NPBMR3yn5aAuwPn2/Hnio1m2brYi4NSL6I+I0knH4Q0RcDzwGfCLdLBd9AYiIV4GXJZ2ZrroceJocjg1JKeciSaek37msL7kcm9R047AF+FR6ts5FwIGs9DNXSVoDfBW4JiJGSz7aAlwnqV3SCpID0X+e1S+PiIb6Aa4iObL9PLCx3u2ZZds/SPJftO3A39Ofq0hq31uBnelrb73bOst+XQo8nL4/Pf2S7gJ+AbTXu32z6Md7gW3p+PwaWJDXsQG+BjwLPAXcA7TnZWyA+0iOPRwmmfXeMN04kJRBbk/z4B8kZybVvQ8n6Msuklp9lgE/Ltl+Y9qXHcDa2e7Pt1YwM2sSjVbSMTOzaTjwzcyahAPfzKxJOPDNzJqEA9/MrEk48M3MmoQD38ysSfwP5JtOzb6H41EAAAAASUVORK5CYII=\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot each subject - look for irregularities\n", + "for i in range(len(ket_list)):\n", + " plt.plot(dACC[i])\n", + " plt.title(f'Subject # {ket_list[i]}')\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot each subject - look for irregularities\n", + "for i in range(len(mid_list)):\n", + " plt.plot(amygdala_mid[i])\n", + " plt.title(f'Subject # {mid_list[i]}')\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [], + "source": [ + "# all in all, ketamine group seems reasonable. Lets look at midazolam\n", + "vmPFC_mid = np.load('mid_func1_vmPFC.npy')\n", + "amygdala_mid = np.load('mid_func1_amg.npy')\n", + "hippo_mid = np.load('mid_func1_hippo.npy')\n", + "vACC_mid = np.load('mid_func1_vACC.npy')\n", + "dACC_mid = np.load('mid_func1_dACC.npy')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Generating global maximum graphs (session 1-2)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = 'ket_func1_{region}.npy'\n", + "ket_func2 = 'ket_func2_{region}.npy'\n", + "mid_func1 = 'mid_func1_{region}.npy'\n", + "mid_func2 = 'mid_func2_{region}.npy'\n", + "# now lets built it around individual global maximum\n", + "def maxVec(funcArr):\n", + " vec = []\n", + " for mat in funcArr:\n", + " vec.append(np.argmax(mat))\n", + " maxi = []\n", + " for i, x in enumerate(vec):\n", + " maxi.append(funcArr[i][x])\n", + " return maxi" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " T test for ketamine group diff Ttest_relResult(statistic=1.5433996488468762, pvalue=0.15376419602078736)\n", + "T test for midazolam group Ttest_relResult(statistic=0.7009216115690157, pvalue=0.501070531766361)\n" + ] + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reg='rACC'\n", + "ket1_max = maxVec(np.load(ket_func1.format(region=reg)))\n", + "ket2_max = maxVec(np.load(ket_func2.format(region=reg)))\n", + "mid1_max = maxVec(np.load(mid_func1.format(region=reg)))\n", + "mid2_max = maxVec(np.load(mid_func2.format(region=reg)))\n", + "\n", + "plt.figure(figsize = [10,5])\n", + "labels = ['','Ket_ses1', 'Ket_ses2', 'Mid_ses1', 'Mid_ses2']\n", + "x_pos = np.arange(len(labels))\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "plt.xticks(x_pos, labels)\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Calculate cross-correlation between vmPFC and amygdala" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/.ipynb_checkpoints/usingFSLRandomise-checkpoint.py b/task_based_analysis/.ipynb_checkpoints/usingFSLRandomise-checkpoint.py new file mode 100644 index 0000000..7dfe0e1 --- /dev/null +++ b/task_based_analysis/.ipynb_checkpoints/usingFSLRandomise-checkpoint.py @@ -0,0 +1,160 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +# %% +""" +Created on Fri Mar 1 11:10:24 2019 + +@author: Or DUek +analyzing resutls from SPM 1st level analysis using FSL randomize +It uses TFCE for correction which is a recommended approach today +Variation from: + https://github.com/poldrack/fmri-analysis-vm/blob/master/analysis/postFMRIPREPmodelling/First%20and%20Second%20Level%20Modeling%20(SPM).ipynb +""" + +import os +from nilearn.plotting import plot_glass_brain +from nilearn.plotting import plot_stat_map +import nilearn.plotting +import glob + +# %% +# grab all spm T images +spmTimages = glob.glob('/media/Data/work/KPE_SPM/Sink/1stLevel/_subject_id_*/spmT_000*.nii') +print(spmTimages) + +# show all results (all T images per subject) +for con_image in spmTimages: + nilearn.plotting.plot_glass_brain(nilearn.image.smooth_img(con_image, 8), + display_mode='lyrz', colorbar=True, plot_abs=False, threshold=2.3) + + +# grab all contrast images +con_images = glob.glob('/media/Data/work/KPE_SPM/Sink/1stLevel/_subject_id_*/con_0001.nii') +for con_image in con_images: + nilearn.plotting.plot_glass_brain(nilearn.image.smooth_img(con_image, 8), + display_mode='lyrz', colorbar="w", plot_abs=False) + + + +# %% Now we grab al the contrasts per subject +subject_list = ['008','1253','1263','1293','1307','1315','1322','1339','1343','1351','1356','1364','1369','1387','1390','1403','1464','1468','1499'] + +copes = ['/media/Data/work/KPE_SPM/Sink/1stLevel/_subject_id_%s/con_0003.nii' % (sub) for sub in subjectList] +copes = {} +ess = {} +for i in subjectList: + con_images = glob.glob('/media/Data/work/KPE_SPM/Sink/1stLevel/_subject_id_' + i + '/con_0001.nii') + ess_images = glob.glob('/media/Data/work/KPE_SPM/Sink/1stLevel/_subject_id_' + i + '/ess_000*.nii') + copes[i] = list(con_images) + ess[i] = list(ess_images) + print(copes) + +# %% Smoothing the specific contrast we want (v[3] meaning the 4th contrast) +smooth_copes = [] +for k,v in copes.items(): + + smooth_cope = nilearn.image.smooth_img(v[0], 1) + print(v) + smooth_copes.append(smooth_cope) + nilearn.plotting.plot_glass_brain(smooth_cope, + display_mode='lyrz', + colorbar=True, + plot_abs=False) + +# %% plotting the smoothed contrasts +nilearn.plotting.plot_glass_brain(nilearn.image.mean_img(smooth_copes), + display_mode='lyrz', + colorbar=True, + plot_abs=False) + +# %% Grabing brain mask for analysis +brainmasks = glob.glob('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-*/ses-1/func/sub-*_ses-1_task-Memory_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz') +print(brainmasks) +%matplotlib inline +for mask in brainmasks: + nilearn.plotting.plot_roi(mask) + +mean_mask = nilearn.image.mean_img(brainmasks) +nilearn.plotting.plot_stat_map(mean_mask) +group_mask = nilearn.image.math_img("a>=0.95", a=mean_mask) +nilearn.plotting.plot_roi(group_mask) + + +# %% Creating concatenated contrast (across subjects) and group mask +copes_concat = nilearn.image.concat_imgs(smooth_copes, auto_resample=True) +copes_concat.to_filename("/media/Data/work/KPE_SPM/fslRandomize/TraumaVsSad_cope.nii.gz") + +group_mask = nilearn.image.resample_to_img(group_mask, copes_concat, interpolation='nearest') +group_mask.to_filename(os.path.join("/media/Data/work/KPE_SPM/fslRandomize", "group_mask.nii.gz")) + +# %% Running randomization +from nipype.interfaces import fsl +import nipype.pipeline.engine as pe # pypeline engine +randomize = pe.Node(interface = fsl.Randomise(), base_dir = '/media/Data/work/KPE_SPM/fslRandomize', + name = 'randomize') +randomize.inputs.in_file = '/media/Data/work/KPE_SPM/fslRandomize/TraumaVsSad_cope.nii.gz' # choose which file to run permutation test on +randomize.inputs.mask = '/media/Data/work/KPE_SPM/fslRandomize/group_mask.nii.gz' # group mask file (was created earlier) +randomize.inputs.one_sample_group_mean = True +randomize.inputs.tfce = True +randomize.inputs.vox_p_values = True +randomize.inputs.num_perm = 200 +#randomize.inputs.var_smooth = 5 + +randomize.run() +# %% Graph it +fig = nilearn.plotting.plot_stat_map('/media/Data/work/KPE_SPM/fslRandomize/randomize/randomise_tstat1.nii.gz', alpha=0.7 , cut_coords=(0, 45, -7)) +fig.add_contours('/media/Data/work/custom_modelling_spm/randomize/randomise_tfce_corrp_tstat1.nii.gz', levels=[0.99], colors='w') +# %% opposite image run +fig = nilearn.plotting.plot_stat_map('/media/Data/work/custom_modelling_spm/neg/randomize/randomise_tstat1.nii.gz', alpha=0.7 , cut_coords=(0, 45, -7)) +fig.add_contours('/media/Data/work/custom_modelling_spm/neg/randomize/randomise_tfce_corrp_tstat1.nii.gz', levels=[0.95], colors='w') +# %% +from nipype.caching import Memory +datadir = "/media/Data/work/" +mem = Memory(base_dir='/media/Data/work/custom_modelling_spm') +randomise = mem.cache(fsl.Randomise) +randomise_results = randomise(in_file=os.path.join(datadir, "custom_modelling_spm", "GainvsAmb_cope.nii.gz"), + mask=os.path.join(datadir, "custom_modelling_spm", "group_mask.nii.gz"), + one_sample_group_mean=True, + tfce=True, + vox_p_values=True, + num_perm=500) +randomise_results.outputs + +# %% Look at results +fig = nilearn.plotting.plot_stat_map(randomise_results.outputs.tstat_files[0], alpha=0.7)# , cut_coords=(-20, -80, 18)) +fig.add_contours(randomise_results.outputs.t_corrected_p_files[0], levels=[0.95], colors='w') + + +# %% F contrasts +smooth_es = [] +for k,v in ess.items(): + smooth_ess = nilearn.image.smooth_img(v[0], 8) + print(v[0]) + smooth_es.append(smooth_ess) + nilearn.plotting.plot_glass_brain(smooth_ess, + display_mode='lyrz', + colorbar=True, + plot_abs=False) + +# %% plotting the smoothed contrasts +nilearn.plotting.plot_glass_brain(nilearn.image.mean_img(smooth_es), + display_mode='lyrz', + colorbar=True, + plot_abs=False) +# %% +ess_concat = nilearn.image.concat_imgs(smooth_es, auto_resample=True) +ess_concat.to_filename("/media/Data/work/custom_modelling_spm/lossTotal.nii.gz") + +# %% +randomize.inputs.in_file = '/media/Data/work/custom_modelling_spm/lossTotal.nii.gz' +randomize.inputs.f_only = True +fig = nilearn.plotting.plot_stat_map('/media/Data/work/custom_modelling_spm/randomize/randomise_tstat1.nii.gz', alpha=0.7, cut_coords=(-20, -80, 18)) +fig.add_contours('/media/Data/work/custom_modelling_spm/randomize/randomise_tfce_corrp_tstat1.nii.gz', levels=[0.95], colors='w') + +# %% Fliping to see the negative +from nipype.interfaces.fsl import MultiImageMaths +maths = MultiImageMaths() +maths.inputs.in_file = "/media/Data/work/custom_modelling_spm/GainRisk_cope.nii.gz" +maths.inputs.op_string = "-add %s -mul -1" +!fslmaths "/media/Data/work/custom_modelling_spm/negGainRisk_cope.nii.gz" -mul -1 "/media/Data/work/custom_modelling_spm/oppnegGainRisk_cope.nii.gz" + diff --git a/task_based_analysis/Analyse_fsl.ipynb b/task_based_analysis/Analyse_fsl.ipynb index 845c342..d0716bf 100644 --- a/task_based_analysis/Analyse_fsl.ipynb +++ b/task_based_analysis/Analyse_fsl.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "metadata": {}, "outputs": [ { @@ -26,16 +26,16 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 147, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "21" + "22" ] }, - "execution_count": 3, + "execution_count": 147, "metadata": {}, "output_type": "execute_result" } @@ -47,7 +47,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 148, "metadata": {}, "outputs": [], "source": [ @@ -56,20 +56,9 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "20" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "func_files = glob.glob('/media/Data/work/modelfit/_subject_id_*/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz')\n", "len(func_files)" @@ -77,200 +66,85 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for img in func_files:\n", + " print(img)\n", + " plotting.plot_stat_map(img, threshold=2.3, display_mode='x')" + ] + }, + { + "cell_type": "code", + "execution_count": 179, + "metadata": {}, + "outputs": [], + "source": [ + "# visualize results\n", + "t_plot = nib.load('/media/Data/work/fslRandomise/randomize/randomise_tstat1.nii.gz')\n", + "p = nib.load('/media/Data/work/fslRandomise/randomize/randomise_tfce_corrp_tstat1.nii.gz')\n", + "# suggested threshold should be a=0.005 / .001\n", + "\n", + "thr = 0.95\n", + "t_plot_data = t_plot.get_data()\n", + "p_data = p.get_data()\n", + "\n", + "# threshold raw t map by p values\n", + "p_mask = p_data < thr\n", + "t_plot_data[p_mask] = 0" + ] + }, + { + "cell_type": "code", + "execution_count": 180, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "/media/Data/work/modelfit/_subject_id_1322/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_1387/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_1339/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_1464/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_1315/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_1223/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_1499/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_1307/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_1351/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_008/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_1390/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_1263/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_1369/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_1364/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_1293/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_1480/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_1253/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_1343/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - "/media/Data/work/modelfit/_subject_id_1356/modelestimate/mapflow/_modelestimate0/results/zstat4.nii.gz\n", - 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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" + "" ] }, + "execution_count": 180, "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": 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P9sQT8wy43Jdo8ern7xOLuePCfP5cSdKPfpR89JlVdNZZZykIgmDHJmwHgiAIgiAIgiAIgiAIgiAI+oFN6pvytavzIZn442sQ7AJ0ISTcuECS1Nt7ZO37a665RlKrvySrpqIwYUScEXK2qOs4zj2nGIn3EXpUVhyH/5ur+Pje1TKzZ8+WVK08/4UvHMGV85bVkefmdGBCFexIdHXNy/9blrd5edwnD0tbLDFp35b02gfN/0+x8fLLH0p7OVZQU7mirrR11ZKrnYhR90creVa6SsoVfu796spcv757WHIdcEXj6ofSCtnDZs6UJA3GN5ciko3lyEU8GfGFu+6669L32Vfwm9/8poIto6trQf4fUiBewqC87ZEkzZ+flGvNalbeJ0pkj2ePS1fzeTyXFKWoqVDT8bn7WPosB1eWumK8r8pbf555w5Mf4LjFSS6F6orjSK+Xu1K58nL3u9+RP/vVnhtPWGZbSNKXvvQlBVtGV9ccSdKcOYdLqmbL8N6aFcrEwmuvJc9vlLCuwKPOY4uCjzqxk/KV2HI/Y1cCegxVz9TV9nMva7Q9rvouzVbg/vS7KlKdi+LVy4hf333P8YRdsWKFJOnss89WsG3B61iSRo9OMx7w7CVeqWuIA1fve1/E23yO71QXu+crdPKl9+u4p7GU4qvRiVilOoT7hnTfxx+n3UvbjRtTu4fylbilzSN/zj333LbpDIIg2Pb01XZgcJ+vGH98DYIgCIIgCIIgCIIgCIIgUK+ktzoetSXEH1+DYCelq9my7vS8vScpXlGjXH75M5Ja1ULsM7Ld7MuWzq+PwPuIuauMUEeh6MB/0+/XSSWIAvaDH1wuSfrd75I672/+hiNd8ZpGo77//bS8Kgpf0hMrum9fuhAANt5XUr4uWJAUHEce2ZM/P0R1kgpu7txNDTUPao+RI5M6iJh1ZWjJ36/Tyticz/Xw1SP2XYFXUou46so9L4F91Ezc11VOXnbBFX6c99xjj0mS/jhjhiTpgNXpeDTHI+YmlTgqGr8P2+9+97uNe11wwQUKylTKbmCUnLimfk1xvWnTOEmVAkhqjRfeD3UpW1f9ufKTcoG6in3qxJJy1MuLe8+CK7ZL3rDcn+uW2pBJL74oqVI/cb6vwO3ey6XyBNzPn8ufY8iQIY3P7rzzTkmVgvDLX/6ygvZ0daGqSyu3DxmS3jezW1CpNqtNiUVimRkt7nXpq6tzLfoHvFNixWPQ+x0e467oKylfwdsOVyC6T7df1/tHRx6JJzTtYqoH3nrr/bX0lzxo3UuWfPnkJ1O6zjmH+qhS3vpsqGDrcMUVV0iSJkyY0PiMvoPXVcTjRz9Kvb933qZyMH9+fRaM97O9P15qC8DrPGj1HlbtPn5/7vfss6k9O/yYfMKSvKVz0fB6Tf+hLvA2zWdfUC/QBvz4xz+WJK1Zs0aSdN5557V9jiAIgv6nr7YDB/X5ivHH1yAIgiAIgiAIgiAIgiAIAr0jbWqzCvR7IP74GgQ7CV1dySdNJ2ZfkWFNXzKQPjlvH06qtz32WKx2uM8kCoqSasrVSL7SNSPsjFyj6OL6nI/yw9VUpGfGDKqkpCI49lhMpVC8blCd5BE1eHDKEzxjURr89Kc/lVT5J7K98MILPUuCrUjlfYniL0kj5s4dIalSCL3ySlI07bFHUjgMG/Z8Pn5VPm5sQz2BSgrVFDGE6gflqCv9iGX2SwpYVB+oMVzZh1rDVSglBWxp9Xin5InpykTfukqFPOV59124sHbfbruf+yFuzlP2oXxPSt+phWfZ3WCGQaVgg2G2n0bNFy8+SlLlbdfs/egrURNvHEvdOmhQ8s9DDVhSolLXcZ4rnH3leLxXKbGHmQerq/rAla7uI+6zKMBVhN72uFrK49XLk/t9uuKd67sKrRneAXUA7ceyZan+inZD6upCtTk6b5nekN6bzyggL5u/412sXLlSUhWrxDSxVqrbgbbAVddeh5b8h93nuITPpnDFLel2pa2XDbYPPHBgLf0cT1l1/29/HlcEk66nnjpUkjR1KiszV/USbXIoYLcOXefk/9yfVZn41E9o6gdQNN6w/RNtP4uqpkxJM7iee65eltx/nn4u/Wzv2xAnlCO+d8W294X8POKecnfooc+lhA7IXv0v5/Sz5sRSHjz13/bZJ7UpXh64LvFLethny3N2dc3O+RFrOgRBsI3ZpKoO30rEH1+DIAiCIAiCIAiCIAiCIAh6VakSthLxx9cg2MHp6nq5/sHDWfk6oekzBA6NCiKNdDNy7Kv8MhLtaj5GyFGioFpxH8pOqwEzUu4qGFZfdTXTAQfwAEPzFlUSQ+ooYN+obX/2s5X5/PoKy0D6UYuhLLn22mslSWeddZaCrc+sWfdKki6+eJIk6Re/aO8H6WrTFSuSp9j69ZUPI7HkqqeSaoNY43j3IXYfPldLoTJxFXVJwQce665IBN93SmULDjjg0fy/9Hxr186spRt1jKtcSltXTKI227Rpk3o//WlJ0rR8x30blsvpnO/88/+RJF1yySWbfaZdl4l5m+urAUnpo40o+6mv0ruaODFJg+bNS6rBZk8+6kbKAu/BV8YuqZyo+4jb1atX17buQ0l8vnBQ8qli0gTOVq6wdsU38UL6SD/p81kSXj5d8er7nOdx7P6dXj45z893BTs0l2dfRdy9Nr/3ve9Jks4//3ztblSzGVzlnSIGf0bykPfIzAWpim3exbHHVspvSXrwwboC1r1fuRbvhzrd+zfgsVqqo0vK11Kd74pE0ufXc99kj2XS7V61JcVrafaFK26feiqlc+rU5r5jUknecsvTkqS/+7u/a/vMwebpujf/56S8/UjeDsrtdXM3BSUolSpFh3Z0Xd4u5PjULvT2JoWp+8LTJtBfdg9l9okHyovPRnAFuJePUlw1Er4xl5d1+XOauw20d5uf9ePlBTzuee45czbkdMzOR07I1z1MQRAE/co7CuVrEARBEARBEARBEARBEATBVucdtToevkfij69BsMPTk7fZY21jUnvq902+goy6r2MIOq1ozgg5Slb3u0OJwgi0e7ay7ytx+4g4+4zMs4/iw9VKXB+vVq5fDaEPytsN9nmSCtx1FyPkH6g9JyPmrp5CSeOqsh/84AeSpP/yX/6Lgq3H6NEpVn/+8zRc+Oab6X2sWpUUzMQF78kVsKg3pUotxBZcSee4uoiYc5V3s++mVPaW7LTKvH9e2nf6enyleEVtmfLWFbbuC+h+h54vrkREbTJkyBDpgQckSWtPTCZ1+yJIz8Xy/G9+U5L0/fy+vva1r232WXcVKgUO8icUQa/ZkRtr2+XLPyipqleb1dyol8BXhHZVknv3chx1Ku8Zr2RXGREndW1utXD1pBwH3MfVoK5UddVoyWPWPVnBlbLTp6POSnn64ot1xaor4l0d6G2UK2O5X7PXsatr2R8yZEjt2BtvvFGS9Oqrr0raXZTfzD6p+xnfd1/6nJhm6+q85s9ofysn6vT5CSf8VpL0+OMpKnmXxLi/W9p1yg7vx2czAPu0L64ih1LM+BZKXq8lj02/bqkssfVY9Trd4xUee2zvpvwhr9Isodtuu01S5bu7u9TdW0rXqfk/zDSbkbej8pYmgLaxWfn627xl6YW9NnOs1OjmTpjwiiRp6dKD0+E5voh/4pc63xXg1LV8TxvA964A9/65Q/z19IyRJHV351ZiGVJe+ufUEXW/b5/d4LOMvG1y5W1V3mitVuXrL5PT23ty22cIgiB4V4TtQBAEQRAEQRAEQRAEQRAEQT8QtgNBsPtw9dVXS5Jmz04qwgMOSKPBH/kIxXZpdfC6+sgzq96yUjYj2ig9GBlnBJ0RdbYoelDMuqKVkWtXRTHSju8gPoDsA+e5kqWSBrDFFCsNOz30UBppZyQfTyueA4UM90XV6GosRtZRAqCAXbs2mXPFqtbvjh//+MeSpIOyjyRxMnNmeh8335ziylfpdXVcsy+jq9GAY0qqCVcn+WrqxIirlYjVSo2t2nElJSyU/AV93+mspM1SmwHd+YGSIvADH/i/kqTXXz++7fVLvsyebyWfZqlSQx6QiyP9EHTpx5x7riTpmvy+zz777DZPuCuBQyqSJs8R1IEouFO9sueeSTnUrOwGFIOu4HTFsnsWu0IWFZSr4qjLvayNX7q0dp2p+f27D6Urbl2l5z7iXN+VpqXyQboq9RXlD8NE1e5HOXbVo6sE3UewdP/mY6gL3EfZvUfZXnHFFZKk8847T7sa1On33JPUv6ecwvtI73/48ORzTPzR53jttVQ/uRpTavZ4R05CeUie3++8k2KVd4vC1fsLvFv22br3pbf/qMO5vs92cPx896x0NTdb4sjLosdm6b6l81zpSllwb0/3O25+Bq9nbrrpJknSGWec0TYtuy33zEvbnux8zsSTU9LmIyk0dVz++P6mV/k4zQBddW8maFhXyUjlg34S8eXKV9oA2g7eP30YP77kjextDPFSniVAu+flmLqh3rfy3x9ebtn3Phf3nTTpD/kT5MZ19X2VkVJX15z8DCe3e9QgCIItI2wHgiAIgiAIgiAIgiAIgiAI+oFQvgbBrs/3v/99SdKBByZvLldlLFpUrTaMIgR6e8dKqka4fZVdH8F27zTugXICtZR7o/E9n5NGroNHnnusch6qw1ZPJxS80FheXZI0c2YaWb/nnroHFmoOtjyvK0EanrDHJZ0C2r/R96YlbFHEXHvttZKks846S0FnbrjhBknSIYck5ZJ78OLh+/nPJ8XCz372vKRKsYGSGYVGpYxqVV27KoN93rkr6TxGuBcKLfeO5HzUIyVv2U5esCXcZ82vVzq+oS7B87kxFNvejKiTwpb8I895TveFk6Tf5y2LMns/hBSggrvyyislSedmReyuQlcXnq5177kFC9LshIED05b6cPToRZKkNWumSmr1LW5W+ri3K3HrdTLXoG724/06vmI7aipXwvr1XcnKcV63Upe7otrLjftg+v1caTt/fkr/wIEja597ufPzuS55676f4B667fLK6xy2tHNsqVtou3cF/0yUkN3d3ZKqegI/1r33rquDUQGT79Sv1PGStHr1aknN74Q6jHZ+r9q9wBWknO/v1mPW61pXnPL+yqu7q/Y9x7tfOOnyOHGv15Iq29MLJeWuq9/JY/Lcvfab+4k+O4m00c7+5Cc/kST97d/+rXZnmHl2112pTz1kSFpHYcaXpqcD8uSHN9PXeiafN6/5Iqtsu9b2l9p+ozlICs/165dIau3T8D69H07b7f7bHO9KaFe8NvszN9/X4/b3v08zmypFauKpp5JH7dSpybN2+HD6KihWU8wtXJi+93guKcBRxFdKW6e5vqAMPyZJ6u2d0eb4IAiCPhKer0EQBEEQBEEQBEEQBEEQBP3AJoXyNQh2Vebk0d8xef+dO+5I2zw67eoKqVUB4h5hrnwFX9XU/fJc4cGIOlv3+xs0KCkb3VPNVzdFdUj6Wr3WUJbh6cSqyPWR71NOSZ5TCxfWPdhK/oKovdZ+6EOSqnF4dDdDhw6tPR/Xu+aaayTtDh6W747vfve7kqSxY5P8wxXIbKWXauf95/+cPv/Nb1KcuaK6OV59pWv3JXOfPWKNe6PwcRU079rVIO5rzH1dyVdSvpYUrOA+ga7OKilp16wZa+ehGvmLtseXcBUYW/IZBVRzHfHh7AFNfYBXIuWKLT6PKNdmzZolSbr44os3m6adh5Q3V1+dfHYPPTR5a/u7q/Jube17975r9uBzdT6gKCTPV61KMiny3H23/f35FsUr/tbEE+XFVXMo5XinpNPVdqXy4KpFbztcee7+hqXy7apAVxmy9fLt92nGvQddQebv0dsbjt+Zld+od4866ihJVVvuCmy25IXPNPD6TarqYGJPWp23dV/fyZNTbC9delTtc1e+gtdpJb9t0sT7ZVvy4y75Eru63BWHHoMlz1bOL82uIH3u08xzkJ/0q1Chuw9z1Q631vOuOiQtd+T+Z09PjyTpoouOz2netZWE9GnGjx8vqar3eFeP/39PSJI++BfHpP1/yCcenbfNP9JRtvbkLQrXZbat2ygLCSzvlXdCWlx5T1vg/XPeNe/f48PLMnW/9w2IPy/TrMHg/fxKidqdNkfnfnzueE+enNqMF3YHaOoAACAASURBVF6otxVerkeMmJv/R/+fzCXjWo0Y/+//TTMGjz+e3xpp9klv72EtxwY7D5dffrmkVs/qUn+D/tIFF1wgqfICRhnd2zuzP5Mb7EqE52sQBEEQBEEQBEEQBEEQBEE/ELYDQbDrgUoG/Rpaz4Wf/KQk6a2sQHAfV6nV/9KVFowSujKDa7iyw0e8Gen21XRd+cPIOGoK1C+MQrpHmqtkuM6KFWmEe8SIxvrqllvpOvPnJx9A96p1Dyvuj0oL/QeDWBOff752dVcQ4D16/fXXS5LOPPPMxrFdXXdLknp7T9XuyogRIyS1eu0y6sznL754SO37t95KSmNfCdsV3M24mtkVcag3+B7Vh68C7zHhsY06xD1lXSVV8tQsKdXd5w9KStVS2XT/wE5qrU64AtCfQ6rKrytkSnlAuUZ1vLOvBt/V9bIk6Zpr7pIkIbZw9TTb8eOpv0bn89vHSHNdTnx6fK+eMkVStcj2+LylZkRM9friNBuAPPf4QDXF5yhWX82qZm8roOStioKW8gIeT1zXn9m9X/m8Xfy1u577GboC071mPYa9jWs+11ez95kjXqbZZwYIeYRv5DnnnNP2WXZEUPwxG8SVf14Ped/C8xDl9tFHN89+SIrXBQu6JVX+9s0KTak13zvVad5GlLbtVM/tjvNZCe4p68dRhl1N6qpS7z/5cwKfu/LQfZeBts7ro2ZvaX8/rjYsKcf/z/95KD/b5Pzs+2pXZNSoJM90P2Cf/fXwvWn2w4c/nGvkDye/c8SeNVC20iz05O26lfYFB6Z+6KZNKT6oY6nbPR54l8QfW8quK2B5t/R36QtxHmXW47zU53Al+YoVqbUaMSK1m1qVVafDaqd1LJerVqWZat5GvPnmyLbnNZejRx5JaTzuOLz8c6N9Ylad369gB6CrK/cfBuX6hD9ybUi/r268MfkDjx5d99MnBl3lT0wQK3iXS5/JW2b2zM7Hf3zrPUywa9IPC26174EEQRAEQRAEQRAEQRAEQRDswGzatEnHHHOMPvGJT7T9/tZbb9XkyZN15JFH6otf/GLnC2I70OnfFhDK1yDYzozPajAGhVE0MdDyUh7lZvQbdalUjQi7Fxj4iLerl6A0su3qB/fNdL9A1AKoKXw1Xp4BRamPzHPeqlUj2t6vtxf1YH0leu7jyl5fuZ1BVdRiB9vIPiP/gNKA7Y9+9CNJ0he+8AVt9aGwnYhbbrlFkjRkyBBJVRx4/qHsQUnhq4O7f+vYsfMlSStXVr5yJaXni1mZRXlBM/KB556rHU8aiDlXh7uyBTWIq9pKKwW7L5qXGc8LV1F1Umv5c/vx/jy+LVFSf0Gzl5Yryd3b0D2c/X1Tfmfn4z7ewRd3RwHP51tvTc+z775plWdXSbO6c2MJ7Ib8KUUl9ZF7ii7PnrHNM5red//9tXOGzk9lYkBWwA7GTi/75w3PldmTE5Pa6KhlSUXlswBcncQ7cwU48K5RuLqajrKO2o7rcR2u6+WA53JluCspwdsi9+Wm/BFr7tnsnrOulGlW2Lq6031lwdPOM5EXvir5zqCApU6fMGGCpFZ/SV8Jne995oHHW6V4HdV0dt0v1j0qS0pRr9Pa+eA373fycnVaPZsTJZ9un3mDUtDbLJ9RBN5fcZU2se4qLy9D3u/ymG/uM06ZsqSWhp6eY9qeA7TVtJ+7quL1xhtvlCQNG5Z64u3qB6k1dubOfVGSNH16KvPaMLj6kk49nZMsBNU6+o4LJUkLFiTV7B57JEUn7x3PV5+d4/WSzxbgOOKFd0gcUHfTfuHV7jOWOpUD/31BnUC6li1L/eZRo5JqWsu6JUlPPLE2X7/eJyspYL1c+CwH/30jNddXxGtuKB/g/XLksnzv0Qq2A6Py+6GsDMrbJWlG4Ze+RKF5UpL08MPUQ3UPd/D+Mb/dqt9reL6G4nVXZdasWZo0aVKj/mxm8eLF+pd/+Rc99NBDGjx4sFauXNnmCkYoX4MgCIIgCIIgCIIgCIIg2N156aWX9Mtf/rI40H3VVVfpG9/4RmMh0eHDh3e+KJ6vnf5tAaF87ScuvfRSSdJFF120nVMS7KjMyUOvePkx8NeVBH2anBcCXnzaaZKkPbP3a7PPl6tNfCS8pHh15aur6sCPczWhr37Offx7VujmfBRCJd8xP84VH35f9ykjX0gHFe1+TzxR2+d71I6+2iu+d+TPxz6Wnu+LX5ytVj/aXZ+rrrpKkjQxq+x4P8QkPpIoNVyFhvLCfRl5by+/PK14b1czUW72RVCVhSc6IqkJe3Jj+P7lyyVVZQG1bglXa/sIu6fZVSCuQvEyVVJp+b6rTkpK1lLZLSliS+f7/Zs/d8WL+2WWvAy5RqO85uuhKD377LPbpml7M2vWLEnSQQclpevIkUmRhKKX+mLFihWSpDvuSPH+yU8+WbvO/PljJbXOWkCp1k5D9maOI1clNd5Gnt40PK+k/XaOc2oj93lEjVdSiLJ1z1lfzZ4yTtl2z1WuAz5rwWPC1Vs+u8J9hbmO1ynuN+7lwVWJvrJ8c7nx9tH9lkvKL1d8eR41e/vuaFx22WWSpGOOSQpI6nQgL3wmAHnD8dSXrtqsejbN8UF5SO2rxw54/kOnOtQ/9zrO68SSv7Bfd/DgBfl/qZ177bWPSKrioPQcpfNff/2E2v3ZujKRfVfIlhSQ7gk6cOBATZ78ar43beyq2j3Yuu8996Kc33DDDZKkL3/5y5t91p0F6vqxY1Nd7fWG91X8+0oVPzdteprWABioDtR/sXsd5WWJd+NrJrhPOHUocYP6jzqy1FfgvE4e15R5rwc9PaT7iSf2zdd/IX9fP660pc53L1tf04J0Nf9emTYNxWSWUg7Mf2Sh40hRfQNf9jn53icr6H+YDaJlp+RPutPG+/Oq16k+u8C93b1O5PgHHnhWkrR2bVJdX3ttqv8oUxdccMF7ep5gx+CSSy7R//pf/6sxY8tZtGiRJGnmzJnatGmT/vmf/1mn5b+xFMF2YCsSf3wNgiAIgiAIgiAIgiAIgmCn4d///d81fPhwHXvssZozZ07bY/785z9r8eLFmjNnjl566SWdcMIJevrppxu2Om3pB9uB+OPrewSFK6MsjCziG8RKe67cY4QxlLG7H/PySF133sfiposBvrwwbVf+YmISSWhFVtc0j0ozEszoXmmVXfdnKyl8St5mvuI7I82oJRihdu82H7mngnOlBrhyju99BJzRypJPmSteXSlAfnA9vGFIL0oBjjv00BfylY9uuktK087g57e1GDNmjKTWfHV1FPUbaihXhboiyRVGzUon/67h98UHjJSjMsltaHcWPvRm1WIWCmrf7PHjfrXckxFTV1W7zzHwDJ18Cz2mSx6u7VZhb6bk9ep+aaV0lq5X8qJtTnvJW7qklIGGcuueeyRJI09Jaocr83nnnntu27RtL4hvVmEnVtyzmOfGN+q229K7o55zJT15Sz8B7+lm/dNYW7Gcuq6+Dra0eGP93IGPPCKpUp9T15FmjxdUvHuZ0tbrWvfjK6lBuY9/797IbN2D1r3bXDlLHePx7f6EHM/ze93jaqnmcuH+pX5OSfnqSiw+J03Ew6233ipJ+tznPqcdhe7ubklVrDf7g0qtHrts/X14nHidUEW7tHRpWiHePd/76lddwuvCLfXBduXd8OGP5W8m5C0q3g1tzyt50w4ZwtLq3W3P834bykJi2NWpXv+W2oq6CgxPy/qS8+vXJ/U+CnvKnff5UP/D7bffLknq6emRJF188cVt07Cjw7RT8spVzF5vuSKW/Z6ewyRJ3d1Nv9I35LJE34Ss35g/X5c+8LLEe2c7Ywbtabr2Y4/VZxF4e0vZ89k6rsx2xSj3c+W0lx9vB73cEKfel/J0tKuDpVZ/b873GVVe7koK+HRS3vKDay/7fMLJ5XODrQaz5yh3993XI0n66EdzIUGh3GguUgwzi4iYIbZ9NoD/9vV+CjFCPUd55281/GY5L6/FEuw8PPTQQ/rFL36h2bNn680339Trr7+uM844o/FupfQb9vjjj9eAAQM0btw4HX744Vq8eLFmzJhRvjC2A1uR8HwNgiAIgiAIgiAIgiAIgmCn4V/+5V/00ksvqaenRzfffLP+8i//svaHV0n69Kc/rfvuu0+StHr1ai1atEjjx4/f/IU3KY17dfq3BYTytY+gcHV/s0GD0jAaoyso5korX7PPaE1X17x8ByTPeIMxsp7eaG/vzK33MMF2YUEe3UU76UomhD/D0uKbDSUskfHHrEhBCSVVI8Huj+cKHLaoWjwOXf3H8b7Ssfv8uYK2tMJ7qTy42on7As8zYgS6RVYTT+Vmzpx0HVeU8fw+Qs/13ZOKfOA4ynWlFBhmW4mhsK9+9ej8rNdLkr7yFQy8edOL8z1P1s4KKwEffvjhkqp6jrjhfe5nqj0UECUlBfGxOX/T0srXi/P3R9YXMa2qUIM391gecT8yqxVRfHkaUW0Qo4yUe3o8XeBqa1fgeV50wlUepZWIXf1R8qAtnd9OJeZKFVeaUP69XqB8uV8nbpCjRiXZ8nXXXSdJ+spXvlJ8/m3B5ZdfLqlSeVEPuBqqpPjB2xr1aWmVc/L2g6tXNz7zuCOPycs37rorXftjH5MkjVuYVsqm7vKVsUkj8epKNvcBJE59Ze2SXzjXc4Vtw8/W2pqSCpH0uXqerXtPujq1pLh031Vvu5pXqh869EFJ0iuvfLh2LfD37M9UUnK5Ooe6ZkfwzcTr9dhjj5XUqrbz2SzuK1/ya3ef54ULqUf2a+mPeJ1bqpvA30On7zerhOvD9ytXzqilizhZu/ajba9TUiKuXn1C7fuS16zXwf47w2fs+LvxMlFvn72hTHUV9Y333Xiv3JstafPZVjsb3/3udyVVXq9ej1Vergl/d+45TX1b+xW+NitcyXKf2bruEEnSpk2pf+v99ylT8F8+Mm/T+50xo0eS9NRT9boehb3X9SXfeT+OGR/U3e7TXcoD4o/fJrR/qAi5P9dl1gV57X7SnZS8ni4/rk6WUGaVsZbkd+LeolvZ0zGo853vfEdS1efzGGiwVEZ6QVOmpNmHixcnhbmvR+JtspdPP466lO/Zp567/vrrJUlnnnlmH54u2JH5p3/6J02fPl2nn366Pvaxj+nXv/61Jk+erD322EP/+q//2uiXFQnP1yAIgiAIgiAIgiAIgiAIgsTJJ5+sk08+WZL0P//n/2x83tXVpW9/+9v69re/3feLhefrtueKK66QVI0oMjrqag33fPXvGZErj+yXDGleVrBrgGYTrScDKVjboITFcW2YeYz86fjjJUnv/+1vG58RR4w4u5LQVT/EL7gnlK9m6gpZRil9dVNXLQHfo7JCncX9GG2k3PhoZVVOqPnqubRhw/LadVx54ipB97h1xYArc6qRdF5Guxo4pfUrX+nO+wyp55H2gaymOi+nbZp2Nkr1n3sber2Gqob3Tv23Nq+sTRmYmFeg9NFsqdVvkXc36MUXJUlvHHywJGlfqs78qt7OF/fyxT19dVRUH66aRr3rdbjHipcJ934t+fI5nfwJXTXl25Kaq6SA7QuujPe0uAKW+sLrhXdOOklSVRcOO/10SdIDs2dLqpSnX//61/uctq0JqgdigRjw1Zepb1zpDWvWrJFUqUdLq1jzvVTVge7P7XV01wMPSKrKFJAG98dz9VPJG424Z0t6fNZOSWHybn07va52BRrlz1XUbEmfK3VdhUo5J+/HjetpSkV3LU2kwcsI9yx5dfpq86WZJx2VFtsA1iUoKRh9Foorn71O8Bj3vJLKqtlO/tYlOn0PJX9s98kuxS77r756Uu16/n3Jx7uU3pKfeel6Jd9dyjxlhRhvLiuPP658bFKQUV66uuqz9jgXKIfuB8q7ww/7Rz/6kSTpi18cmZ/tZO3I+IwXnx1FnrvS399Za8wsq75cmjsjS3NfcGguUw0FbL0ceDw2zGJH5WsPy+dnf9l99lmSjspthitCSz7zjvt/kydsS4puIG59TQaOJ4aIMfY9j72/4OnhPsccQ2+O381VO1r11emH02fvSZtlE/Op/i6Un3VBTvuRCrYevo6G95MbPfSNvJC6YpX9kj8wn3eKYZ+lBSVVdihggz57vm7BX1Tjj69BEARBEARBEARBEARBEAR9tR34QN8vGX98LXDllVdKqpQwjIJ85jMcwehMeiO/+EUaTfGRafchY/TlhBMYqWN0h9FSRukYOfz4e3+YYLtyd37nh+R9yjBjt3s99JAk6f2sGp3VVO/LI3ArDklnEimMIEqtijNGnl3V54ps9jnP1XDEL6OUrvoDX0nbVYrsu9IHL6hKfVH3EXMFwHPPJV+u1auTEvy445Kn1Mc/ThWWys3DD+O7lXDPPVdt+Oqy5RH+ZSqTvps7d4Qkafr0ddw9bxjZPTrfY3a+x45ftqkH8WlyZWPJA9iVYWvXpmgfcuKJkqQjXeg/LSk5yLIFeds7f36LSsoVd+jAJ5LtGcqXryg/MkuA3D+M6zHyTRlxxR14DJV8yKCkeiqprDr5rLmS1ZWvrs5qVdWo7XXcf7EdJWUWuBpufvbVQ/Hand//2zlLT/x4KguNHNrGylf8/w7OKmr3/ePdEws8n6tEfaYAx5f8yZpjyn1xuab7AKIqWnbccZKk/e+5p5ZW6mx/367sKvmUlvy/O6kM+6rY7oR7JfM8tBU8P/vktav9XH3NdVtnM1T/5xm9LLuq2BVa7l3oZZW85zrMJLjtttskpUUgtjWu2vZ881ku7ifK1j16vQ/RTKlu6eTx2tfPO9FJufdur9epzi7V9aV0ucpy0KBna9+vXz9JUquqy+spLxvN/y/NhnKVpM8E4Z6UAc4fOnRovsJJ+fzX8jMMbvvM2xuv4/3deD74O/EZBHy+fPlBLSrwrq6U5/vvn3srq7vzXVK/lfqAvB027NH8fV43gE5MozOT/OrJc/enLVFS7Hs9BVvq51vyxPZZF9SjPovHfwf4zLSq7s6/gQbkfmOzSJJqPeeRlLzRlyxJ15wwIe1rae6NvLFX/bw8Y23WrFmSpIsvvrjTYwdtmJff5RPXXiupam989lw1m4r2ghdR78G/8MIRklo94F2p77MnfUaO9+E89r2fRJ3KbyGfkRTxsRvQV9uB+ONrEARBEARBEARBEARBEATBFtBX24EtIP74alx66aWSKh8jXwn4nntY7ZkVsFG01tVPjLq4kqIa4WYVS0ijPDfcsDxfryvvp1Vx8Xe78MIL39PzBduel/LI3z4Tk9cQo7joBFzJ475xBy9PMfF4XoF7XI7N5nPYuueSq5zcy869yXykm1HATsqQTt5lqHVJB95kKGBdwevpcR9ACZkjWrqUpx/+cBrVvu++12vPzyilK27cg44t9+H5ly//oCRp5MjHm85OiqxFiybW0vzEEynvjzkm+zVvHJ2PZ3j+FO0s4AvIeyCufJVq6knyy1VSjFIP48K8NpSvkF/rkT1pu2jKlIZSfO+VScngI9aHPvecJOn1HEsrjk5qkf2yNzI1rb/bTkpVro/yDrwsuOK000rbnXwF/fNO1+mkhC0pYt2/dXMrjffVx9PrroY/b/4ejcJruSODvzWCHkCJesEFF2z2flsLn+FCXvlMAuon9/f1uD/llLfyldMT33//W7XjfZXo5nu4IsRnKaD0OOC++2qfl+r4Up3mZXjo0EckSWvWHN82jzr5/pUU16Xr+L5vSZ8r9FDQeBvinq+uQnblenNveuHC/WrHbqlS0Z/F1fDejvp1b7rpJknSGWec0fa6W5Obb75ZkjRmzBhJVX6Rn658djVcX99vO5/Jd6v87HR8X9XWna5Xuq/HQ6nfVJot0EkB26n/tHZtUvgdcMDTkqT990++z+vXn1i7L22VK++bcUUY79e9fPmevpur+312A7+Z7r//QUnSSZ9NaevKE3x6Z7ckZbtwbe6PDx8+XFJVRikH9HFc6eurpkM7v/tSXKxfP7127v77pz7i2LHMrKJOGlY7Thvn5f+klvKNN2bW7rm5trsdfnypzHqdXvJI9lgg74g/n6Xgsyp8xgBwHV8TQsrtJtnU3I/kp8GylJeLFo2u3ev559NvhXHjsgJ2Nd6wvN/0W/ySS07J20X52Q9T0Heys64GnHWWJOm522+XVJ55VfUO64rXZ56pe7OC/7boVMe6YtVnAPjfbtjH/5/Ze+7Bz7pA5513Xtt0BrsAseBWEARBEARBEARBEARBEARBP9BXz9ctIP74ajBy7H5X7o/GqAsje64kLI0kViOTda3PLbe8lv9XHzn0UebLLrtMUihgdybwO3XFEbDP6DBKHt45I3DH5xW0N+fFSLxwLdQs3NtVVSUFRmu8bp5OflklJZCvqO1qPKA8MAopvZm3edSa1WCXJUnlRz+aVI+zZ9dH3H3FS/Ien08v576/cuUMSe3zBZVc5UFEGUffVx9Z7+rCZ3DHW1X1lltukSSNzV6d4ErrkmrG84f8e+ruuyVJp3zq1PQFw+OIS03wMezJ6v9vFlYx93c1fF5SiRDL7l/snlOl1VO3VCXVqaz0dUXtTiouT1eprJXU5P587l/ZrgyWfGFLz+Dv6Oj16yVJD2cVFTofSkbD6fzHP5YkvX8t6odtA8pX6hf36HTcw9VVp/Pnp3KzJtfZ1A2uSm3O65JCmfoERRbXcr9lV4a6d5m/V3//wPVL8dxJZdVJ/Vc6rtRnKvkT8ly0IbR1bL1v5m3agw+mOn/gwIEtqlm/p/cD/XNfrRzmZXUd2ip0bawYgCvhsDvv1LYCxZ/7KJIHXp+2evMlPE5Lqrm+UFKa9lWZV7pOp889xryuBE9HScFcotOsBn+e0nO+9tqRte/9fOKRd8u74902n+Ptn1+L+oN201emJz58BXs+v/tHyYv61E/tWDN9qB95Lp+1QL3BO+a5eP4pU16QJC1enJSQW+KL2lo3dvpFT41B3VZXvILvl+roUnvdqRyVfG/9e/KK+OO3DG3X+twP8OO97+Hp5l0NGfJw/iTHFF3t5mxcltLW00PbXZ/9xvt99NG0/6EPzVV7cn99wKk5zfQrpxWOD5rh1dDHc2/p1nJTj/Xqd1J95tmWznqgvnLPePpV/tvPf58Te9QbxDTPQ5171VVXSZK++tWvtk1PsPPSD8LX+ONrEARBEARBEARBEARBEARBP1i+xh9fAY85HzH2UX/2GZlr9XKtU/Ize/jhNFq8evVqSdJbb9VX2nblzZYqEYPtDzE1eXJSY7p6xleoZSQN5Y6rC10t2kxpZXNXvnIPH4Usqfm2dCV2p5M3GnlSUpy4SgOVxapVKf3DhuVR62WTVQcFez1vuW9Jwcn9hg17QpK0fPkUSa1Kl+aVnPFK/MMf0grEKCMqIypUfLy3rTx/YSvQ1fVQ/l9S9mr636VttsXShkX5P0slSQ8+WF9J3CEf3euL4x/41f2SpINOSisjH0ZWdedtHjZvbvBKfsCUJ5+14HU225ISrq9lgHSgEGQk3BV3JdWW+6K6J2fJmxNKK2n796Xn7LR19VW7tHe6t6eBdzEt+/auWLFCUuWj9XZWI+yZt9Rx1113nSTpK1/5irYmXV0L8vUfkySNGzeudl/y3L2LeR7ejT8f9Yz7s7r3na/A23wNx1f1ZevKT9S7Xtc9klfEPmbZstozcV3e4ZIlh9fSWFKgdlKelFRYpeOdklrL3wFbntfVx5RL1FY+W4ny21yHlXyQKZO0P6hgvGySpwuz/2XD9y5vqc+o7g7J25X5Hfan9+uNN94oSTriiLRqtM+uIh88f0qzZkoKemjXJy71A0pK+tLnWzrroERffYw7KQQ7KQ3b1anN35fS5ZS8+h1XZTW/m5Kqt5RGry9K5ZC44DjqpZuvvSU/0/h8nxlt09zfsFr56NHJA9RnDJBXPoPpQx9iBhN9zNRnmTixR5K0dGmqE5rrjs3NTpOqPFy//sObPW7//e/Jx51SO6+veDo6xSeU4srjrtQXo34E95Wmjin9fiDmWn8XMDUq16Sr8+7qZl1a+k2w996p7+7v09t0ZkC4xzVp+uAHc9940Mz8+UM5TTMVlFmStyhg/W8lrbFM6zigtvXzPDZ91kkplkrtGr8bvD/uf+Ph+NLvcggP2F2PUL4GQRAEQRAEQRAEQRAEQRD0A/1g+Rp/fAX3t+o0ol4a7e00gli6LqPEKCv8ur6yH6O45557bl8eL9gODM2KI1/h2r1liAn3JfWROh+xk6o4ZHQPPxu2PopXimfS4KOEHn/uM+gKrk6rRJdWBfbRy1I6XS38+9/vn5/3WUnVyDrH7b//4LbpJA9RRR13XFayDkjqDA1N25EjeyRJCxak/GSUtF6u03scP35p3m9eelWqlK9U3ymNl132dN7ffh5S+FhpQB7F/6/5C5KM3dKTeaXXdUl5cMIJSUX35JN1FYF7fXpcupJh6a9/LUla9Z/+kyRpcvZ4Jacea0rrhwoqaq+7oaSagpLi03HVxiuvvCJJevHFF1PaVyVlzH159XmYPr2+srErx1yZ60pG/EdHjBghqapPUJX485bUYa5Q8ufmnbDvq7k2n+v3LKmJS+e5ytdVKdSVtIPk/fXXXy9JOvPMM7U1wGf5ttsWS6pmnJQ8WV2Bz3GuynT1jM92oF51ZU/zdyUvY67JcaTFvYw5nzyd9Ic/SKri1+Ouk/oQfLXgkiLO8Xj39s+9J0uqMVdYllTW5EfJ39zbW56j+Vm8LXa1p6fR8wZPV6pP7uBu4CzM7er9/uCggw6S1Npn4N7UOz5bga2rvYFn77T1/zff21X+nRR7pVkKffUDdDr505au7+krzRTy6/RV4dvJX7nkkQk+66NdWrz+Zx/lOPHgvu5et3mauWc1U+vo/IzbRznI2gukp1O9RNskEYu5XzcoP8+6pGs/5JC0vsBrr1X9OK7Z1zguxcm6dX9ZO69TPHeaIdlppkqJvirD/d27v76Xc5+BR4y5D3VrlcVdLAAAIABJREFU/K6y/cojHjWxzzpxvGyU2vbGjLV1OQ8+iwL2NklSb++n215/d2XWrFmSWpdz8FnDvOOq/UXGTOu5sXae4zHnvy1K/RXqLZ8N6jM83O/f+02lPiD3+d73vidJOv/889umP9h5CNuBIAiCIAiCIAiCIAiCIAiCfmCTwnbgPfMYqpC8PzOPkjASN+ULX6gd/9ztt0uqRlNKo/+llaX9+5IC0VUg7q3jiqH+VEgEWwc8+Hh3L0xJHkTE3vSsnOOdlpSu7i3ZrDQgDrjHKx9Oo744ku714IOSyl5N4H54eDGiWGQUEIWYq6WA0WaO9xHv0nmdPGQ9vSXfTdLrK36zz+glKrBp05KaUEcnH7CGrRc17a+6JUmvvvoftfvWvQEZqeW9cHLSNbmX4tq1KY9XrBipHQaW40Zy6styM4y9bHDeJjXA0UcnbWpPT4r1kpLp9NNTfv3kJyk+eF+NOMgK2EU5vlCnTFAV4z4S7Sqpvqo6SmWAfcoAqmj8Sd86JfmuUfPe+qlPaXPMnZu8x0488URJrSPsnn5XBCxfvrx2f2IYJSzedV7PdFKxuOKH+3Nf9yttxu/hytCSkofjqOt4Fsorn/Pe3fO8WZ24NejqmiNJuvfeD9Tuz/OVvNxdJUO63IeV771d93qqGZ+tgPqXuCHPfBaCq4dcTex+tCUlqPdJXPG90vx6161L9Rvl5de5DMP/k/tOz+f9pVkJ4t7l+OyjTEPxzffeJ4JOakfykfLhSlieq/m6roJ3VS956iseezwsy9fbaFv0WUdl/93e11+XVOUldd21114rSTrrrLP0XvnhD38oSfr7v0+V/FNP7V17BvKJZ6EseNlj35WO4MofLxvNn/Vav5sY8nbb6VSXu9rWFele55Xqyk7K2r5633fyzC/haqr9939AkrR+/YmbPQ/8d0Zzf6WTz6Z7JVcK0ATx4v7X3MOV+cRTZSBPp2LbQj1Derze8zq7ivPleZt16us8/fV6SuqseIU/5f7O8HyrP766vpa2kuewK2E9XiirPiPTy8GWrung9ynFks8AoQ52T23vT3i6vT7u6RkuSeruXpmv4HMLWpXZPlutVIZdCVn1N7PydWB+xjw7S5NC8dqOyZdcIqnNr6K8vsOeDyXlO++W+mXu3OSTXvXFUj+gk182W++38nsLeK/u8er98k79IveKhlLZC3Z+wnYgCIIgCIIgCIIgCIIgCIKgH+hVJZrbWuw2f3ydl0czWF0WBcLLrGiY920tRe2Z1U0b77gjbfPosPuMuL+Ij+h1WnG604h6aYXsYMfj0ksvlSRNnTpVUvXOxs6fL6kaEXvttdckVQofRtRcXYkSwUfom49hFG7cvOThiXLVVXw+qu++sx7H3NtHA301e54J9RaqIkYTh+TVn13pwnV9NLKTIoX4d9+xg//6ryVV5RhnqPe9/HItnxoMyOpTTmCYtqEATVXuCSckhdIDD1SjoSefzHvIqtlG9dwjSXrxxeT5yTsib0kzSq+f/vSnkqTPfvazbZ+5P+jqQp2blQNUiLNV36ea4dEaq8q+nLd1z1dwddt99zEaXF9RmDgoKZulKpbcbxEVdqWs4dn6pi4CYnfNmjWSpKVLk3fvsqxOmz07Z0oHpavziU98opZOVzISs64G8TaFPKJs4Tm7enXyyBo2LAXvmDFjJFUqE1eoldqYkgK2+Z24is0VNH6Pko8oaSIvuK57rXI8z0wcXX311ZKkc845R++FH/5web7vIbX7gqdj+PAF+Zv6uvVLlyZvaI9jV1O4Pxj1c7OqzOsyV61xDS8HXr94H6TkTVby/iXPUV6/8MILkqp4u//++7U5vpEVrxPt8+/fdVfb44899lhJVRuA8nXUqKTUROFNfdnX2Uc8L+0lMeeKl2ZPQPfiPfXUdM3f/ObN2ufkEddEVce9Ds91iL9/0sz57PM9Zbed6vzd8vd/jwapW5K077719039Sv5Rn7pHX2mldPD8b6dA8nLiqjNXH3o9UroHz0C5cn9j6mBiy2eOucrJlc/g9ULJT7vUjy/VwX5eq9rLfeRVO68Tze1pSfXreek+7a7qJ2b9t4h7KlJG7r471R+nnjo133/beGbedNNNkqSJE1ON5Mrukoc86V+yJM1YmzCBPk+9DWg3IbXTe+GeKF7f3rj580requBl2WdYcB7tKO/OVeruze773j8v/S7wupfyR7nzNszLj/tNt/pH00Gl417hq9F7feaenq6U5RnGjn0uXzG3ZBvye15Srzu6uubm82a0pGV3Yo79jYVfRZSWnrx9Pedzu5kR0uZ9qpvxGPTfoLxXn23lqu/SbGP3HyY2fZaUtxXe5vP3gIsuumizzxPsuITyNQiCIAiCIAiCIAiCIAiCoB/YMHKk5vVlcfss0uwLu80fXwfYtr6eXrXPX7cX5+1+pvLw1XAZyS8puFzd5OqU0uqXJVztEux4MMrr3li8a189li3qGUaniTVii5h7PfvENV+bezK6R3wxEs492Xc/vdJIto/m+Sgjyi1PK59zvD8DChX2Ucaibuq0kjvpQcnC8ZRjtnjveTlrKF825tHsVdnXiQF17Mka/0npPPHE9U1XGVX7TkpqJ5QSrmBz32hXF9xwww2SpDPPPClfb1U+rz9G1B/L2/zA63JOZVuzxx9PShviidHeSh2Dcjl55o4f/3tJ0sqVKa2uegHihOsSj8QHio1mRaCrKtyP01cr7rTCtHtNofBbtGiRJOknP/mJ3g2f+9znJFWxTBkrqUX66j8I7stMXqHYRUk/cmRSc6Mc9BF/KKmw2s2q6OSp6Piqx34PVAGUd1e6EBdAPFFHvltYiffww5MPs/v/+crIBx+cPOY0/eS0pUJZllRQGzak+sDryeHDF+UDyctUzh55JF3PPbWlqo7mffEeiFPqLFfvk9ek3ZWyJb9vb49QeqN0Ja54Nq572mmnSWpVVnP/f8v7G7MC9vsdFOO/+93vJEkf+chHJEmvvvqqpMoHlfQQz93d3ZIqxberJL2c+yrtvHPOoxxJVdvKs95zT10N7l6vHMe7cc/SkkKce/vK66SdcnDNNddIks4++2xtKZw7b16agTFt2sKc9rQquyt7PH68/wLeR3C879Bcpvh/J+Vbp2uiwn7++eQozGwAZvj85je/kSSdfvrpkqRx48ZJqpTFJcWe+/aVvPFLZcqvU6rbSzPb/Huut3790W1ypXye06x89bSBK858lp3XP9zLPWHHjk3luafnGEmtq4T/6lePS5JOO23beGbSHpf6Xa6U97aL85YvP1SSNHLkM/nKqY+9fv2H+5wWj5PXV6+r7Zd6AH5eaa0F4p+6m/qKOs/fGXU/53seQaN/bb65neIYvK/jeNxy/9KK9T09h0mSurv5nVC1Rc31efMzDRmSzFrXrUvzXL2uYZ88rP4a0GOp5a8G3HO0gorDcrb05Gzi19GGJ56QJA0oeLWW1gPx2Qfef/b+NTHtM4U6+SJ7G+x/6wFik+O9PnW1eMxSDtrRviYMgiAIgiAIgiAIgiAIgiAI3hO7jfLVla3oanw1WoQt+z+QVhf1URb3UWNUjdE2tqwM7CoLYDTFV3Hu5P3UVx/DYPuBQsBHxlzV5e/e1YLuj+Qq1uZ7eFyihPXRQB9JdhVDaZVW4tC9YP26KFsYNSRdrnhxPziezb1f+Z50+ffu57Qxe7uuzPcZXlCKV/s9abPwyNr32pg8HpcswZvyCElVPjW/u7feWp/TOLT27KjaXD3j75W8O/NMfN2yKveUGfmeK/N1hmtr0dt7siTp5ptvliRNmjS49j3KCLbEiavpxo3ryWdMyGmtxxGx7HFA/vnK4z463fwdMUNsu+q6tAp39cx19RSK1wUL0ru+PSv1SvzVX/2VpErdNmLECEnS8OHpvbiavKR649lJf0ntVVpBmOsTR+QHakqUgqtWJeU0SsGDDjpIUqsfOXgb0zxi74o8cAVsSWVQ8kB33yzKjNeNrr76zne+I0m6JK+s21dQBaOY99XqScfBB2cJ+JeSj64Qo7PS8eVJ7fL220/V0nXIIX/IB0zOW3oc6d2gwuJ+lcqmUl26zx11YMkfE7zOdXWexxll8Q9/SGlG+U154zqUYbbEuXsYc79p05Kycv3Xvy5J+lxWYaFkvcu8X1HSel/Jld4v57odVdfBBx8sSRo/PvnuUg5cQeNqbfd643ma7+Xe/qVVuL0OB87jOu5x7h7+rsYhL96L0hulMLG5YkXdgxy87JU8MD3eSv6OriBqvh+x6+e6D7bfw1Xazz77rCTpuuuu20wOSL/4xS8kSd/4xjdq9yspVb2t9v3SrIrS+V4fQqmf1VcloVPyOW/3e8HrbFeEg78Ln8Xks/emTEntznPPTd3sdVEfX3/99ZKkM888c/MP9x4peRh7mfXZHe5zynb9+ultz2unBC/FSynOSvHi+PFezzS8x/MaCNztjw8+KKkqk95ff9+JJ0qS9syzEfje88q9sb0OKPkB99WP3/s6bN2vt1p7oOLNN+t5M3780vxNqksHDUqq+PXrT2n7TKRt0aKJtesAz3zkkT35k2H5vDTzqLe33pfeXTg5xxzlmn4xbdjeOd98NpS316U1CLxNLin06VPxG9X7Af47gFgltvx3u3sDezvo8eHPEbOUg3aE8jUIgiAIgiAIgiAIgiAIgqAf2OWVr2/n0RWUrq58bSxqnrcD77tPUuuovW9LK2OiovAVQ1F9TPnSlyRJ0/Kg8mv5xghq/vzQQ7Xrg4/Y+0hksOPgfkWucvaRP94px7GPws5pHmlzrydXlBGPPuLuqgUfrfMVIFGcePy7QtIVru557N6Kfp6vVImaj7zkeRhNdX9EV7CVRlfhjTfG5es+lD9J11m37vDac7sHZbMqxFUElPXSyrE+slqpILrzNqudEBkOHZ6f5eV8/NbzmEId5d6sJd8lj6tK4ZfS/M47a/O2ruBwLzEfxXZP4WaFpY9Ul1b69eNLKhKOZ2ScsjNz5kxJ1Qg4ijGeFdXi0KFJ4cyIeUlF5elxL06embwoqepKq4z76uTkLfvMvnjqqaTOxBP20EOTd52/c7/+5lab9TS3U4RLre+m5Hfrx5e25AV5t6WgxuDdFj3UByYld0Pxiq0fxT6L1F110TqHJtUbCxakMkueov5qfn7eJ3UOeUmd6H7JvL+SksvrF49ProvHKtenbiXeXeFKeXDvM49LrjN6dHp2lL2ojyl/nE/clpRqtBXUr/h90kYcdljyAUTh7YpNj1Evl1LrjBFvp7zd9PaUd8fnrm53tY773gHfl/oAfcFV1j6LyvPZ+y2+anPJv9kV8xzPdZrz131mOcdntIDnMzGL52tfcTV4J99ap5Ona6fjO3m/drqv+yL6zAJXufs7ar6Px4OXA2LO+36UV/pC06evyFdM7+yRR1K7SDknfjzWeRfv1b+7E1deeaUkaeLEpGD0/oP3t0mn50fJ+3hzdPJDLu13iodS3JJW70fRgnfn7aoTTpAkPXvnnbXjG3XAo49KqvLC2yDqWp+pRB6Rp+QV7Rzbkv+91yUlT+hWNT3tbHN/fEwtjfPn1/trAwd+qHYPV8LSvpE3XgdVfdM8Q00pvjQhZqVK1TsiZrwd99lOmzooYr3d5jpePmlDKOf063lf7lPM9T09JUrrnrzxoRRPvdlnvFMZDwIplK9BEARBEARBEARBEARBEAT9wi6vfGWt8o32ua8/hwLWfT1KPlal4xgdeV/2B/xgvu7oQ/J//mveZqnr4LzY+NFz0/Z3ebSI0beSb1nJJzDY/jRiwEbKXSVV8opxtaDHXPNImiszOZaRZkYDwZWpJc8mRglRQaCOYjv002mlWty8SBF6tGF5y92XsJ+V5SiCGJ10lRLlzZ/PPSFdxbM5xUczrqZ8/fWpteNdmcc+6W6nzPSRcdLsiq5Jk1gtl1qIXCLXklenHkiqVA3iGbwWe/dcfvnlkqS/+Iu/kNS6ejcx6mqRFuXB0KSu0ur6KLarOMFXKEVp5p5lzSucljwFfeuqiZI6yWPGFQ48O2UIf9ADDzywdj/3CCt5IpaUrKVVUUt+biVlrMc6iiLy+MUXX5QkPfNMijuUg1OnTq09n1+vOd9KXoyuRnC/Us8jV8KDv0v323KP4JJqt8QNN9wgSZoyZYqk8rtq8Q1ml6KXiybx7h50c+em8rB8+UuSqvpr+fJUbxBD1KvN9bOvDs+5nreu/iXN3jco+VG6Gg8lN3HAM7nqyBX8pTrW78f3PDvvbsWKpJyjnvT2kX0vr+QdKiwU3fPmzZMkHXFE8ufG69jTDe5fLLV6krpPnLeb7l3u1/R9nynlM0K8ziLtqPjOPffcljQ7t956qyRp8uTJtWt7WVycPauZw3BIbttdWeRl1d+v55F76TafT2x7u+rekKV7oL50hX0J/IRLKm2nk6cr+HVKsyva9dma90uqqE7p6LQGxOYUuq6eLPVDfWZGK/XKkb4ZMU995upK8q7Za7k/4PquSvd1Drx99T6PK7/fjYfju33ffb0O9Qp1K8+E22nWZqo7z9h4I5eL17IHrNe5vDNXqFPn0m6xdTUgee2+/N5eEnvuu1madeMz8/70pxNq1yMGm69N++L106BBj5ArkqT99+dXSlLTvvLKsbXjW397W/xuve75Tsmll14qSRo2LP2OIaY+9jE8cFPwPfBAaveJUeoLz2fvM7oHbKnf7/1XfmMSBxznsye9j+n+xV5PNmbD/PrX6b6FvkL8rSZoRyhfgyAIgiAIgiAIgiAIgiAI+oFdXvn6hu0zOIXb0ADbX3tSMnl73yNpVKzkOePbDxx9tCSpO1vF6Wi7Mfsn2XZx2gzOCRl76qmSWsbU9Oy990pqr7wLdgyuuOIKSdKkSZMktaotPIZKyiJwlWqr32YFI75sGUHmWFehtFtVvvlzjvdVmvHzcg7Mq6MySvlKVtUx4k6xeDKvwO6rGxPX7vnqn7vC1xVEpRXvfXTUR+gZrXTfTF9Znvs0lz9f+RV85HPaNM7pzltqJ2qlLINv6PB70madK2TfOxPOP1+S9P68wrnHqPuZAt8feGD2ImTB2N/WPRLJH1fBHHNMUhUsXnxY7T7usch7ab6GK0RdUdPXFaxdbeHliZH7EVkZ5qugutKrpIQplS3fL/mL+0i/+06WVHnAc40ZkzzQyEdWt+c606en1ZtRPrbD1b0lZaqrM0vqOL+ul1+vG3315C1VH7kaw5Vp0NjfkNSUejLnCRKin3Dkb/M2+ZnybtwXkfwirtesWVO7f7N3rddRXNPVc1zLVYSukPVyUVqxmvu46rjk1+3vsOQ/X1LE8i7xZl2V2wRXZnoMlFY5ZovH8dNPP1277/jx42vHuaqKfGz37N4ml7ywUZNDabVuKJUDL1+kw1eM3xx/93fTJEkLF9ZnSxEXqw8+WFLVNiPm9jSXFJKu/nV1XKkeaz6mFBteh7HPO0J5x+d/lWeYuVc490bd5DM7SvXRu8W9ez2PSh6dpTyDksK1rwrKzXmIlnw2Pfbcd7hKY5pRMXfuwW2/p+x43pP2ambX3fnzU4tpfTeg6N+UVZ57mp+pzzwhdkprMXg/vfSbsBmvM302gB9XopM3rPvJ84wT8qyXvcbnd5QL/ZF55uWDNguiVLf6TChXyLL1mQC+VgLX9z4M/WvKK9fzGTRHHLE8X4l+fqp3N2z4aO06zed6+0Qa1qxJytYDD3zOrln3u+V4/y1SHZ/3N6b+VldX7juImUz9q/DeUaCN+uIXx+ZPWA+i/nvG+/z+W8zXh/DZmF5P0TZ47DZ+w56SfqTsd3eqZ4jJaR/7mCRp+F/n5GX74Idy2RiV+8nEFLHtf4Nhn/uWZqwFQTOhfA2CIAiCIAiCIAiCIAiCIOgHdnnl68zCiOI111wjSTr0nHMkVVo0xrJWHXdc+s8jj9TOKylhu1G2nm0XwkYGcdvLeTvZtikZOuwcS2g2rT0gj/D//Ac/kNQ6ohhsf1AIuEqr5GHnShMfAWxW5Eitqw83X8NXcHXfNh+dLylMfHSfkWhXZvja3qSJ7SHPPitJejUrwViduDcrV0gHeVZ5r75eSwf46DMKM0YlyRsfHQVXyJK33I/RbN4RKkA8Sd1fsVlhW8pT0vaRj/AeOScNsT7xxKjaswP7K1akPPvUpz6lrcWinNbpeX+t+Sy5mtPjZ8iQLAE8MamrhJd1rtfGjeuRJM2bl/LPPUEffDDlJz6NeJSVykBzmshPYox3sjwruUZmlYern135wPWIPZTq3JsR81IZ6aRC6eTv12mlbT/OFb6ufHRPPk8nz+Orzj/33HO168+YMUNS+xXWXSXlqyGXVHCl9rK00rb79PkK1P4ur776aknSOed4w1mHcuxxBp7Ohgzi9qx8RR647jFJ0jPPJFWVrwRO3hKjw4cPl1TlMceh4GtWvrpylfdLneZxzffuMe51WSneuB9pGTIk+dVS97uaz1V5pbj2OsPfHZ+TRyjU8BP39JXUf7xLXzV92bL07hYuTJ0n6g3i31VezTFV8nt0JZbnAb5y4O2Gtx+u4Pa45D6uMOvq6sn37ZbT1TU7/29YPmbf2rXIP3qOiLnH0zYX6idXGrk3sfc5vN/TjMeCK9BdIVzy2HU/QN+nHil537s/oONrLZQUjKXn8vdY8ucurSFRihMoKYdL9Wy7tDqlc0gD7QJpefnl+qrxpWd0ZWkrW29GjyTdeOONkirFOz2JVXlV8sOXLKmlC0oKfo9B8OdszrdO8eJ0Uiz31TO4VPe2LCuQ+23vO/FESdKfHnigdh3qm3XZI53U7D1njqRynHpfhfbR2yRXtBK3tJ88xwc/SC01Om+785ZYWld7zub6gzqAe3l/idkKzzzzgdpxAwZ0q5mykpFOQW5/3sgK1wm5z7Dksfz9DO0OVLMzmAXCu0stzrx59frD63p+2xED3v7wPn2NhtKMmYYKPF+f2U9v59nFw/kR9Ld5mxWvM3NZeSjXH4Pmz5dUxcfq/LehP99+e9pan9c9pi+44AIFgRPK1yAIgiAIgiAIgiAIgiAIgn5gl1e+OrNmzZJUjYJ0glGYkoqx5DHZX6AgvOSSS7bpfYPO+Micr5IK7u/mI2au7mQEEJVg84i9q20Z3S2pbN1HstOqv80q2+a0lDQMPhLuKy274sw98RgtpNwxmuoerO4txfG+iiqUVlslXYzMu8rLfYf4vFlJQ577KuKViq6uYAbS4spFV7T1J65c5DldTfdur+tKavKI2HZ1p7/X5jS5+qd5ZVupUs6hWnbPS+Ce5D9pQzHHrIJKbVZXNpfUwZ5Xpfv2devn8zyl+3jse9lGBYYaE+Xr4sXJeHzkyJGSpIkTJ7a9T/NnrjTxPPCVYkurmft1Of7AAw+UVNWpxAXvhnfv9ZPDCrwzZ85s+72X1b76c6Hcdn9WV+B7m0A+4f3a7KHNsfRNiGfKEtf0eHSPV9KCGpPrujKEd4hK0xXPJSVbp+87xbGrS11p7rN6Nuep2PzcxDfP/8orr0iq4txjypV5UqvS0VV/JR9mj3vvA9B2exy4z26p/Xo3/Uz3tiytIF7KX1fXuYIMxTRxRp1NXqGkbq63/Tmd0uwC78d4PvGsqKBRU/vMmL56bnbKk1KMu0rS46lTf8vPY+tenn4edFKLt0uzt2eld+D3KPm6+zvxZ+H4qt+zZf7dnaAeKPVdfFaYt03eZ/W+TKdy0tfvmq/VKS5KlGYfeHnphK/tUKpvOrXj/vvYPay93+C+utDpuR3Ob+4zkxbqXtJAm8s57kHsql7wPk1Qp6+/Vzx//V3z26DUn/V22/vpHqPok+nnvKwtg76eK999fRKP5ebfMMGOx5133qmLL75YmzZt0jnnnKP/9t/+2za9/273x1fnj3fcIUla/MlPSqoW3sIie2OWqOv++9uev0deaEv/NX+AhJ0LZSm77snbufY5qx4ggc+zefWBNCVZy9MfBPbNC32c/M1vpv/EH1+D7YgPXaxre9TuzbHHvpL/l3Jr6dK0gNM776R9t5XYFlDdZDcT9fUn/YEH5oUOJuQKillgXIAL//4j+T9PvcsU9p2R01JahueqUiemurgnB+Oe+Y+pQbDl5MXvlizK+2mq6pw59Az6f2CkxIqPpDI2/sknOxwZ7Cp89rNHpf8M7d7MUVSE6Y9Fhx2WBlX+8IdJtaPG53qx9MfYINiWXHstdWz7AbL3Cn/iHdQvV985eC33iQavqn/Oz9TSn4lG5IFZH9DbVsyZMzjfPw1E7rln+sMpA2lDhhy1TdPTzMKFaSHTyZPzn/PW5V9FjQVcd8+Iu+++NOC1zz4sCNpqP7MtmZAXzoLGWznEPsAlAvsBvj83WXPwI3dl/vi3X/iCJOntW27ZamkNtg2bNm3SN77xDd19990aM2aMZsyYodNPP12TJ0/ufPJWImwHgiAIgiAIgiAIgiAIgiDY5Xj00Uc1YcIEjR8/XnvttZc+//nP6/bs4but2O2Gvn1adGOhoAcflCStPeEESZWyj5HBN046SZLk436nDs3/Qbk6kr+c5wW7jmfBrqw1+1HenZe3iLMa6q3x+T95kZ2R+cB775MkTfvf+ethSWK/KLkQNEZ3mYg7o4PBe/DeYfELXuYdd9SnUTBtgukJTF9iKhDT84hJpikwysz0hc1NHeJc4pgplaVpbqWFt7bUfgDlJOVkLzveTdXdBsEX6eB7ptaiCiUPuZ5PBSLPfIqbP49P/+u0eBKfz89TsWFmnhJbmcu3Tnc55JCn8zfUBT2SqukxvF/wNPl0t8suu0ySdOGFF+q9QnWDFf6oHJukgecaNy5LJIbmxQJOSUqDxigxs8S4IBXPgLq9AO/fpwLxfln0gPfXOiWxdWr32jyF/BhCgboz73cnsYbmjEpfTMgLcfnCIKSR8kkseRnyqXU+ta/T1EHwKe4+Vb/TdMbSlH4g/aXn5H5Ma8dmgWl4S5emqBg7dqxLYUxRAAAgAElEQVSk9ovK+danbvpCQb54k0/h9Klnnkf+7t0mo0S1+BCqvyPyNpXf+fNX1o5vXVQlxeWcOdThKX3kFcczrZmpjeyXpl+61UzzFHu3VuEeTHujzAzNfRW3TPFpk3xO3hEvjYUjsoURn5famdKiaR6vPs2XurvTlGvOY1og6SDdndoo8AW4mBaPxYPbMLSbluztiH/ui3R5GfN+JXHBuy0tHOVlvXXqa25p6w41+RpMpGTVVyrldC4xWZoaX5qeXTreF5kjjshf+jVu7yK1WiuVpvG7LQFTyclXry9GjEizSrBOIZbIv3HjFqqZV145drPP3GmaOHhdW2or+rrwksdVqQyVpux2Sm8zXsd6O+Ofs/WFcTyW3VIDfPE4t5TaWnh9NvyxJGnbMy8o6fWmz0AqtXHeh92SRc061YFOpwW4SpT6s6/39EiSVnV3S6p+1+b5HS39M7cJ80WOyDOvG0q2K+0WxGo+z38j+XHcj3dBzHl7TD3RfG/SQj3o09rdGssXD/Y8JQ6qsv5s3vakzbJR+bzDtDvhvyndTu1DHyLaiL7Ubi1ceLik6n2w5T2VLDTcLmJeXlDTtYsDV6yo7R+6PM/iOyH/tjspf8GJNJ8X5S0K2N+nzfAb0nb1t66SJA3I7SHPT6yed955kqS78+f8Vp4Wf5vZ7rz88ss6OC/ULEljxozRI488spkztj6hfA2CIAiCIAiCIAiCIAiCYJej3YDZlvpMv1d2O+VrSWHDdlD+6/fa45Jy1ZV9WBs24IvG2i+okRjlycMmx/ekbU8+MO823KCRogmfSMgei4f+v2n7Tx9O2+y5eNgP82F5tKY3+5Isys95WIyy9B+DutN2XRrB++Qn00jf3Ll1tQJKEUbEGFFlxJ/Y43vUUCgMGLFlRLCdkbcvHlRS0XVakKE0Qs/xpGVqXszEVQMcx4i2m6a7GtgXrmPEG3USeVFaCIC88AWzXLVQUp4wOsvnjQU6pk6VJOFgyvJav234OUlHZ6UPeV+ljaHStL9qVfKl4n26wpk8dLUBeYF6amvQENo/8YSkVvXGpElZ2//XWfF6ej6Bx3YP66wy1Ybe2gGuFvHFolCn8X55dlcdSK35pF/+UpK08m/+RpI0vCcfyID6xnqSuSf38AViiB2PGVfcdVL+lcqSj9y74pV9Vw6UFmvxvPUFcVyF5e/Y1ZqoR8gX8tkXYGr3rK4aAVeuuNrbF7IDXzwM9QNpdO85v26DSR9PW9rlv87bhSkqpnwwLTqmjXfnL1CgVuW7OT2+oCGfE8fkpatleA6UOjw35zUv3AeuquVc7k3cusrY78G7IQ9fzApw8o60sgBbSTXlsxj83Tte15YWg/Hy5PUd+z4LolSX++J9XIf8ciVOO7zs+7X9vXr7wTO5Cpn49cXEvF70bVWucs29Dnf17uoiH86dQZqfJXk/K7AOOiipPpcu3b+W1pJ6sqScdwU97R6xTFo5zxdElFrLg9dZ7Psic3zOQlqHHZZUZd6ecNyUKZZPA3J9kPPooIMWSJJWrKi715eUuKU88hj0utyfp5Py1ftpbP9k6qqSX+/mFtoq3cvLse+X4sAXSfQ6vTT7getNnvySJOm227aO8pUZQtOnp2mIrn5+Ph83wRY6dQUsz0X7h5rS6z/oy4JbTmnBtk7xV+qXl8qs14nr58+XJC3KswIaiv2cR6WFef1d+7v0Piv38z6t98f9+b3+LJU72jRvE5sV87RrpcUPfeE16hraXT7nGbyOog576qlDJUlTp/Kbn3ZmsHYHWMR83LhxkloXYa1mkdBBH1Dbpx6YP39k7XjeJW0m+f/KsWnWAkJVavCPZ2vWxo+2/LeV3jwrYvnL6Xc6MTYv2fhrGr9p/iFvr8jbPek03pU2D+SZSP+oWvo8xn2GIr8GDxulYAdhzJgxjf6wJL300ksaNWrbvqBQvgZBEARBEARBEARBEARBsMsxY8aM/7+9N4+Ssjq3/3crEBlkbGaBRhAFwgwKekVi5ItiHKLBEEWZFLiOeOM193pXNDcuk3jzc4izAorBeR4iGMGIAyCK2EoYZJBG5qmhISCC8P7+OGdX1bu7Tlc1XQ0Cz2etXqer6p3f55z3VJ199oMlS5Zg+fLl2L17N5577jmcf/75mVfMIUec8jU00q4qobpeGbaiWzcASatD6mJq8o22vuRgzjdzXdlykX+Doz2eE+RtVZKd4dUCvWkK+0p8haZ+WObiMfHt+sXzZvmlLdF35VPisrRGkfOgnDbN3cTSfm0OKgDU84qo0ogjtarcSx3d5Qgwl+UofcjXLqSIyKTI0PVV5RBSanDUUj2dqFhTz0i9Rhxd5jmrl6J6Rqm/oS6nXnJcnu9v6dcPQLKa1vTCtMhXy1SdDK99afUaZez0Uy2I7Yuj9TxmVazx3vEaqLq4Inz93HMAgC7++pRSc7Ryo/gY6VegHxIV+nN8+YVrcObPj6udmNlUvV7Vr0nPVVWeqfGo6gbG0Odvvw0AqH/22e7Qxf+aGjP1Tua2NRZVtZhJ8Rp6P7S+KghDShr1vlKViXrahRS1JKTO0jaiLLVUSIGjPrRE2wHe3/nec65PcXHa7YfaIVXYaLyU4rn4y2ZOyI41n/k3xvvy/f6uXMjtUMrt6jDrYMivl+ootgGqzFFFd1VRGKUef0gdzDZdZ1BoG6u+2fr84XIbNji/W/pjqsozk/pK1X26Xmh9ovVA4zb0zNK2OhQz3B7vifqia7yn7i/kiR4q1etQ1aT066W3tXoo6syAUHs5darzqTvrrLNQipBn3QJ/3d/vCABo1copf5Yvj3vPZ2ovdNaJ+hsz83joGqVuj9frxBOd7Kiw0Kl02UbrrJ6Qar9t27ax93l9k+tTbeXVaHt8/7kqe/DxupHJ8768CkWNZZ2dEPIEDb3PuNFnlcZJNrMyQvc3VJ8y+RJnen7p87d16yWoDDQu9Rox67n2BUMzS1hHdSYBKavPnEnxGlIXa/809NzRY9X9hlTKvEZ8Lum90RksXJ/LaZutCm9tK/gs4vpE/aa1z8vjULU9t8PnK0m9l6ec4jqCq1en919XJTNRVa8+Z/W7iM7qS1IVRxL6HAnlefj4YypF3b2LItazuNJY+1Ik8Z1xsvPzLxroZjMU8OsXn39dYqshz38h2O09YY/yuQ0a+5wH6OsVj1f6FdpQ+jral//himr3AADq+fw+jCM+e0Iza2z28Q+PKlWq4IEHHsCAAQOwd+9ejBgxAh07djywx3BA92YYhmEYhmEYhmEYhmEYhnGAGDhwIAb6H/APBkfcj68hfzyio/YtvvwSALDSe0ByzPYEbylVk0lU7/PlTF+e6qVyzcT3ist7xetqL5Kr6stGtJ3o8p4rq1NBW+DL1/2O/UsqpWlPMsVv5/eufM2P4lHJ15FK3SU2GlNRNJulKtA4iqvqKVXicARVs5eHFAapmZg186wquDmKyH3Xr++ki5s3x7P9ZvIIy3YkXxVBenzqXaY+tjrCz9FTbkcVQ/o51V0cteb5h64hR9A5Qt9klpOO7+zjvJXryWBmqo59jVeONfjmm9g+Vq/uGjtG9XpVb00eoyoRVW2QC3SUmtezZUuvGGKGT1XoU03lk8jPmxdXQKi6QPcTUr9p9tz6XtHEMfP3U9Zpt8S1vrwuvGfFf3eeTCv9vVRVLdVnHKmmF5x6d5FM6qWQZ6WuH/LMVA88VTcpHFHXDOy8d9mq1nU59UJT78Z0bUJIFaVKHsY8y3+d4AKqWWC9kKJMfWdVaR+qG494pStFgSf5so1v9r6mWoLP0RJ/rmvctS4sbBQ7Du0n6OwFLkc1O9shfSboPU9VtbMt4jKq3AqpklQBSyUGj5Go7x6X42sqYUNZvUkmFWBIpaV+laE2QusNz1tnfmSKe96bevWc917NmjXLWjztNlVxyPul2b5V2awKaLYxGjfql6mzXEJtVAwf5DXcBAA08W9/vcz/w77pM07507q1a8Q3b+4NoHSMh+o40ZhWhXVIfZfK2rXdAZRWkTGW1dNRl1N1lB7jtGnuutWu7epj8+YlvmQPfoc/tjqx9ULtmba9mTzzdXuqdNfvGSH0c8YFS8ZTSAGZTgmbyas89L7uQ2cz6bmpJ3VyhpBb/pNP3Dyir7+Oz4LYX1iHunZ193S5N3lVVTVfs1T1JdWhfPaE4puku37Z1qmQzzvjXttMnXGWabaAKlIZL+wDsS+q34f1XvN9XrNQzKhHrH730bZbz0v796G+Ebfnbf8BtE751OUraN7cTdfasSPeV9BjItyX+sqH9q1tfvLnFBdHeXmT/XYP3g88B4KQD7p+R+N1Dz3TuL72qXQmaMID3898K/Iz3wq8h2vC85XfYfxvJAV+9t6WVs6FlYvX9mXNZ/0/vf/P/1PgS+/aykeF/63lV3deCgCY73/L6WgKV6McmOerYRiGYRiGYRiGYRiGYRhGJXDEKV+Zie6pp54CUHokWeGoTvNC53HIURhmzuSIYHEXZzTSzHsituMoiviPcLhltVeS0fK1wccfu396OzVCQgH7R5ovUoLmPaxaHu/KZs7HCFX8663+tTenvHC1jcYcLNQHTkdaNebUP1BHy9WnCSitoMjsS5XejyiTz5eSyc+Po5da6oi+qjx5rTRbNM+P6i6O3KtqQZWUmlVZFblUbyQUJn4ovYU/n93+FvGqNcpPnmujAv9P75YAgCXTF6c99lCGZy6nflckm+zc5UV9qlq2dNlvcZYfnWfGUIrEmMCViv6l7hyPEc/YkA+kKndCiqJdXvFaz1/oHfRpSlmWsaieljwG1hsqXHiPN27cGDv3+vXrA0jGEN+nEpD3SVXjqn5SNZOqOUJeWHo+vEaq7FNVKN/XOqTbCfkGKoy7Fi1ctBd4P1ZV4KduI6R61HrHa89rSf9d5iBvG/AL1Hqqih3NqhxSC9Oty+d9xy99mTgzmjczFa2P88WLqfqNq4pV4aiqVLYjqnRkm87zUOVQqsKI56Tepqo60nZEs9dr26bPDfVQ3bx5MwAksr2yfqm6mKXOHgqpsDR+VQEeWk7bjEzesiEFLhVs+fmu0Q7NLEndn76nSkxeM15Tfd5xn6qy0rY+1OZzf8cf73wLZ81y15jPvVTy8lxbjAVuBs4F/n2qvZ/39t3vsQ/qZy1gU/p2LaTwCmU2D80EIKpWTd2WqqL0uc/rqddb64S2/VxeVeFcb+1apwtu2vRjv102AOnPOaTKZjnHt509/OyXULZ5kqmtDvkvE20fdXuZjjcdmZSv+lxT5WCmZwHrDu/FrFnu+auzBCrKZZd5yVvPAgBA667+A5+bAVgHAJgxg8rE+LOFMcQ2W2eAhNqlsq6x9s9Dyk+dFad+9Orrre1KJiWsHrt+x+D2Na4ytc2ZFOCaI0L7iTpLgvVevxdoW5KcBeKnuOQ3Su6cD/0lnL0Sn22nx6xKTG1ziLZVJOnVzlmuDaU8vOH1C/kIa19HZ31orOmMLJY6+4TtydKpU91++zv//nYU2F/hS3rB/soV9XyT34vT6iiB5fOxvf8NZQwVy/6J2t5v6N8XxN7u6LezxZ9nPVPAGllgylfDMAzDMAzDMAzDMAzDMIxK4IhTvhL1pCMcdcnkW6KjYE0XOW/WvX5k8Eu/Pkdpdpx8MoC4ZySQVNRRfVLsM/n19UbANWkSS/UC5Q3VvTS2Cg1O/HDOHjdqQ2UtBwGNykdVCeqxF1JjMpbU/43rc1SaSoHUmFVfLVU/EY42MuJCCrbyEsoUy/0xEzLh6Cb9lHSUmeeoakHWO66nihe+VkWRjnKreozHz+2yfqo+OI9vdEh584z4MjXaOQVStHJlbN86Mkx4jdTHSzO6h9R9+wOvd1LB4A2M6B3dy5dU3tOj+gNuge1g3PdPlR0hBVDIA/PohQsBANPbt3frv/sugKQfE5BUsGo2Y40BXlf1wqT3K4+JHrBUunD5NT4LKt+nci7k36d1MJRFXO+jqrpV3aGqE90O76X6LZNMysD+/d15ffWVU26zrqrfW7pt6jEnfLjEo5HHdlxREQCgg1cbq6qIy1MlpQpS7lcVQVdddVXwWAFgjRMQ4lGvWN/JW/CFlDvd8ek9DKnCeP5sN9RrWhU9qq5J5/Woy/AaqKIklDE95Jet2ZvVa431iJ9TEa7PFEX9JjP5X2q9UJ9D9RtUxW+obQldB9ZvliE1WKqinf+zLdi61Umi+VxS5bX6JbPN0JkcmXxxSz9/t/r33fZSvYEJPefzPktdA/DpAxIq88TDLNH5bBg7f56bxq4q/+nbzlK9ibX/ouphIHlduIzOYiC8vryeIY9UHgNjlp/zGHlOfM02buVKl7K6RQuX02HJknax49BZCqE2lpc0U0xq31BnUZBMfrmqIAypTstqw/WcQrOcQl7NOmOE91efCYwHto06G4L3ZsSIERmPNTu80pBej+yr7fC5GUpcedog//6a6QCAr792amiq1rXOZvLlTady1mumfUHt2+m9YL3g+ryGjGOuz2us/V6Nk/z82QCAjRtPjm1X8wxoOxeKay0z+XeHroeuTzRGVO2YrJ++1duTonzl423nFr+vuMo3kwJWvdXV21rzRfCazZzprtmpp7Lt7oUjgbFjxwIAXnzxRQCl+8XqBUtCfueKxrT2e3l/1r3vJKglZ7gvZomr/+++1DwWFCZTAcsHJh+ga329b1rg37jBvy7y5S2u3Ojuf724fbhhlIkpXw3DMAzDMAzDMAzDMAzDMCqBI1b5euWVVwIAnnzySQCllXY60h3y0dPRnJB/ydGfOXnCd375et7blQKzjd5rklujiqHmS3LgHM5psyu+5LczYy+bm+9IpZOX96n/zyny3nwzvTefKo9YqopLM9iqGowjrKlKklCWW26L63brRmVJAQCgfn1ndLN5c5u062eT0TXd+6oO5Mh6Jn8snlPquQGl1TcsqRTna46KNjnrrNj6m6ZPj50PR2NVrUWlAe2CSmm9+EGqlLzAl96yjHV5k/j4qYejjqRXEf9LVcqqirkiUKnXseMG90YfLw+hSsSfxFH+ybCPykCfKRStCgAALZk+fqerAytWNAYQ9qXU+6SqPJ1BwLhN/Z/qD25bfWcJ73UogzhjTO89VVZUyH7jffy4vyZNmEccsXMLqY9CdUbrrG5H6wjPY7H3ZGUo5vtrpbEc8gMk3N4337ihel5HtjvplFC6DVWiqZJLsxazHVCVsmYYZr2m4lAVf1yeKuhMRF7xSnUgXvflG778oggAMH8+FT/xuOR5qO8uY4jHpzGnCu9QnU49v5BCTJWg2saqF7D65WqfRu+v1pNMqkw9N6LHp8ep3om8Fqp85TVXz8iyVMOpx836XFtU1nqc6WKX93WVr2v7Pvggdg24LcYz98F98h6ynVU1KeHyWm94jb76ys1kKi52meDLfAb81RVTvKJnSkL55Usqedhw+AfXrl0lsXPmPtSHVtXAa7t3B5C0S17nyyZ+9oI+Y1PjR/2IuU1tF7S+qFpNPWB5X6hA5nJsR6gYJNzfV1+1je1P21D1O+b9LPFer+wnaL9L+3Khtjnk+RqaMaIZ1nX5TIrYdMeisRl6bmmW91atvgIArFzpZqvw3ur957Xma1Vx5g4f+FW9YT1nC1Lp5mcDJm7aGieFq1Ur3mYzpho0+MYvSMkcK5arUJs3uxkj6ZSvIf/rkOpf20C9f4wjxjeff+vXr499zmutuRbWru0eO0btd+n3X32+hb4Ha73MNgeAehSrR7M+H1XtyPOcP9/dq44d5yd34hWMO3a0BlB65gSPUZ97OpND22YeM59HoXv26qucLtYORxK8vnrP9X2Nfb23JNRvZaltXuJ+zHGJd6b3dLMb+rHe+0l+iXwW2oWsKp835fGcKOXfXbGND1hPAQwja0z5ahiGYRiGYRiGYRiGYRiGUQkcscpXoh5JOioW8oDiaJoqX3WkOpTxnmvF9YhJG5Kaffw/zaRMwOFcpzhDda9D2DoFADDDH8dppoCtRJxcMIrcUNkrr7wCIJwRVEtVp3KUl6O66oeo6oxUdJ9ctmdPr06q0TG+ws6tsfVUXZVppFtVTpmyBKsCNrS8qr+I1h8qZzZtcqaOLX7lUll2bO9X8NVjQ79+AIAvmREzUG+peuSg5x4pq3GQc3XKShzg9iOoVKvzWEOqOH6uyk31dqQKIJcKkeuvp2TVe0WzXfENUQ3fzDEveDHVUg3jyyXKJU6K36qVu75Llx4PoLSfoKp79f7r/U5tbzUrqqqmeD1V0af7yuTDyc+pLqFqimpM9WFTVXZIBRpSgajHqyoVdRYFY/HYL5wcmddMnzWqyCCMP3pgsk6GlMOpxxvyhA4paEJKZ40DVZSG1JDaVq5bR71dlgz25VJXgV94wc0U4TX47rumAEp716n3nbYbIfW6Ku3Vx5V1mgrJ1H0xznifeO1C2Ze1TWMbyvjlPjX+Wa8aNXJ+efXq1Ystpwq2TJm0Q/VNl+dx6rNGVfNaP0IqQVVX87ppuxFSvKaqj3mtqJX9XnykuQ8+L3jOvI+8r6paZltBX0n1dVel14knuofK9Onuc87USst9furFbv/0Uk87Pph4Ul4Z2Lx5IQDgyy+deleVkKqQXNqpEwCgv98MHw2cHKH+z6u6OOlh88LCxKGq77B6O4Zm8oSysGuWeCqReZ25Pc5mYMk6EvItVl9kQkU0J8BQVNxA1Oo8XsYJCWWV1/PVZwHjR/uGes/0WZTOK1fPTT0VQ/kAdB+7d/cDEPZ8VWWaPmf4XM0dPm35Gj89kLN5ashie+L/5OW582cdbNbsc/+5l8q1989BX/exxrWTDRoUAQCWL3dvp7Zz6h0emn0Q8ubVNl37CJpLgdeS90IzxuvsntCMMu2TsgzNZNJSnwEh/0/1utX+Iku2p9p+6kya4uI6seMFgJKSkljJa6mzF1hqHybkWcpjVQVmyMf5SEFn+KlHrvahQm09CfWHGaNs67XPyPJH8+YBAD7xsXTCKacASD4Gi3zJx2OBL5uzfcj3bWav/3Jlj7/G1+R3QXrGckOGkQWmfDUMwzAMwzAMwzAMwzAMw6gEDnvla17e1NjrKOofe60ji+ohpaPAOgKoo2CZRjgTvkdynG19WZM+RSw5TFMTQpEvKXPwRjd+SP60tjAqGSpe8/ImAwCeeSbuT9ihwyr/n/OeQSs3Yp4YeV/j/DLfecdFg46wquKIo9mqIEj9TDO1JuUviO/bG8LRO4pqv5BHGQn57YWyEKvaiqPMem5aP1QNHPLCovL1Iu64qy+9MrOR9/vhCDpHZ6lA4fWqdd55qaslhZ2+bFTkhjlT6/dXDd21pQqGFkLtAp6K6iOpWaHV34oj9qNGjUKuYPuXV+DfYLvi2xm2Jmf48u8Xu7KYmUDpmUkfpURKbUdI8aCj3OqNpz6XrAupy6gaRJWA2uYSVWeqApnb1babqgqqLJd7iQvvX/369WPHqqXuX9XloeWJKgVafOkyc6uiOqRUpNpF1S+qygkpFENq19RzUo83ovVaveZCqipeW83erH69V199dfDY0rJ0g9+fq60+MW9ie6qEU1WLKmBVKbTqBOcLSIF8Y+87xu2qbzfPJ/Wah3xESWjfqmSluomvV692bRfrmKqgNOO1xqvGR0hJqnVe1VPq40nUy5Wfa9sfmk2haihVwof8itPVv0RGd++nzNf67E14f/o2WhWNeo35fOX7PEeqk3V9Nqxbt8avVToS/RBtvNmHbCgllYAlcUV1yJed14tCwpp+/R0+2Pcxn4F42efPnh17P3VbOptHY6L0OcZjK+QrzPrFtpnXn0pBXm8uRyWszjrienrfeYmpHeUlpfI5lBmdMc79hjwyVSnJOqx1Xftl2nbz81R/1fbtV8aWmTfPqf0Zm1SMc10ea0jFrW0lt8Nj1/W7dPkaADBjhlPaZ7rn5cfflWnez76Z20/iyxY7aEVc3sXCt98e7UvmG/D99ba+H6FZ0ml2PKcAANC6tfMbLSx0Md21a+pzkyu7fa1dG48Pve8hj1TtG/IaM655L9gfVv9v3gOurwp+xlcmL1hVf2qbrKV+T9b6Hpqxx3vB5bQvo20/jy81VwCvBeu4ts2MT67D90OzXLSuhtTmufcyPjRgG8h2JNSmaZ9KFavadwzNHlZlsvZ/GSNkuX9Oaezl+eNZ7l9vPf10AEDH37r1nn/gObfeQrfekNcudx8M9BtmHh4fLqt97FveHaMsTPlqGIZhGIZhGIZhGIZhGIZRCRz2ytckbtgyL8/5T0WRk8hxZFj9/NTDLZStNKQmUtUQ1yvxvllUyHBsjYOpHHRNjLJyQSrNPvXlRj9i2GGuK4v4vi9LKWWNyiKK3BDYI488AiBV6eElKH29rNDbbCZkle+7IbP/9/+cMmnOHKew4yi2+pml8wljvHXuTP8smniKe+nOIv/aBcg777iR+I0b41lN6fsXykoeytJLdERcX6sqj36DqhzXkWyO3KuPWEKpTjUPr62Yth57sZNwrrn//th6zGBf4BfnZlj9Vnzu/L+oEOZxVq9eHc29EpLvtUh4obljDSlddeSWI/Dq1UjFWi5h+4cuXiIsaijm8/ylL0/x5VhmCn3Jl3MoJ3HaYGY8VrWAqgRUvcpzL0v5ynvOeqA+myEFjXpJcl+6fmhkXdt+bkfrZyjDtKpYVNWhygCq6DTGVTWiSlkeP+uU+hiGlK4hlU1IhZPKB16BwivfX3wE9drpPvScNFO9zjQJ+elmSxQ1ir0eNGgQAOCFF14AkGxnslVPqgqUdl+NZzovWapuGHPqAamqd6B01l/eV/VU1fsY6qto/WB7ElJaqw+fzrAIKUhVucL9U6VENL41s3ZIQav1QZWuWj+5Hq9xSH2tSncgGX+hfh/baKp8+NxkvFD1w2Pkc1SV1IwLbofxx3vw1lvueM49l20KMlNCb1Vp22XyS6IPWcIZNzVi50D0Gc+u6Ab/Dy3Pa8p90gAXqKUAACAASURBVDqe2gaoojNTv0K3qbGhMZKqsgWS95b1jopYbbN5/VescC6uoZwPVbyvf62L3Fwb9hNWn3wyAKDRjBlpt6tet+q5GVKJaTujfq2hGSVU38WV1fyWEfdMZ8wztvl+yB+frzW2tW/H19zel1+2AQBs2OCUqUOHDkUuiaLTAAB5eYvdGzN9m8/vRDyNRJZzd29btvzMv2ZF8WpV3lwt2UlkV3uF+2DPnrX+jaT6EjXYD3dl06aujn7zjVOshu67PtP1/vNe8TXbm+OOOw4AUFxcDKC0+lh9rvnM4WwL9YHXONR+XGjGG9Hj5v4YQ6G+kj5D9PuBxpzOjEl9j+fKUnNp6Mwq9SzWmWu6fVXRX3HFFTgSuf766wEAEydOBJAyq9C3vdoPDf2mot97dfYBr7fORiKsM/rbjN7f0AyY7bNmAQCK+rjEOz8Z7BIGfPTyy247rkA1TgVh6dsDU7wa2XAE/fhqGIZhGIZhGIZhGIZhGIaRnrVra+F3vzs143I9eryZ9TYP+x9f1eNVufHGGwEA9913n1/ejVpoZkRVl3A0RUdPdLRfR+5JwnbLl/SWxARXNKoqC3JQVn28OOriE33CCW+wwaegjet9jMpkzJgxAIDXX/fGmFW94rXAL6D3LiFSdT6EPS/27qEq5EuM3FMJ6TdARS0AXC/rUATzAZUSLiXj1KmMS/cu41aVN5pNNJNHlSpX0qleUl+rKpTeVaH9cKSfI+fq3zndq3H6TfM7kkzPvNQ1rrsudjysPvXy/T80cHUCJlTt1g0AsOXDD2PHm6rACymVVTWj2aBV8Uq1QlFREQDg2muvRa6h4j/vBPnAN0AlnV2pueRrOHs47KT6w0vtly2LZ8rW0WvCc1UVgiqjNUtv6rZVQUwYE5r9nPB6q6JHVYmqPuH7mZSjqg5XnzO+z/2vXbs29jnPlcoJquHUf1D9zfRacfuMI6JqM1UOLvfexdQyn+KvS6oKTe9nP1F3h9Brovdf/bd4jTUbPJfLdYbsSy65BADwslc1UJ2pvqpE1Z6MvTr/+AeApOKVaLZz9W5MVZWF1EQhZbbeE31NqPZTf9KyMqKX9X6oT6P3jsfLa/LVV18BAFq1cgo8zrJYtcp5ozPuGZ88bvUBJowF9ZhNnZ0AJOtR8+aMZ/dA3bq1NUKo758qtnQfPEZV24RUVtyeqoX5msrFKBocPEYl0bZTUEjvV86aYj/CN4/z5rmHHttBbd9UXVrFZ49e7NWUR8k10muWTtWmMRryitR2RWfSEO5LlYBsC7U+MxZUAavnzmNnv0SVdev+6jJff+djuK6v55qVXpWoPB4qpNVbNjSDTpWLetyqzKbitXt36pXzkJwNtTN2jNoHZGwS7dvx85DaWNsHfs5rx1lElYfvHyz1T7Sq/rwL/Mfs9H3R0ZU72V/gtzFfYTb6zuDG+NuJLOf8zuU/qFLFbefzz+sm2oeOHb0KVzqk27fHn2+MO66nXr+MW32e8ppyO4wnzijjPWX8qfqPpSph6d+rzyseX0h5HvJ2175v6PuBPl9rXHghAKCB/7wdvw/7cgMft+vXQ9Hv7CFvUJ0hFWqT1Wuf14r9rQEDBpQ6hiMRtj3qKR+aWaUztULPIbad2saqD7B+RwvFpv6Wo/2rIn8+/fyXx4v+P58Ag9/j35cT/70pXo3sOex/fDUMwzAMwzAMwzAMwzAMw8hMHhKDejnCfnz10K+EPProowCSKgyWmg1eFREhr6aEiurjj2PL1RAVFQdXV8rI4s5TnPtiQz/ayvFsQtVSP78/U7wePC68kN5afiRsjx/dpciJAgSqD8/3JVXtNeRzDpovEWXsWcl91mjpyp3L/BvP+nKpazA+fD6eyVO9Eznqq95MVFLoaKWO0KvaSRUuOtKtXmfqmacqRF1O/RAXPPggAGCeP6/TfX0u8vsvnuAk5SeOHAkgKXBNKF6phuA98ErQAv9ynag71A8x9T3N6BrKOEtVwrp1Tmc6eHD2KqcKwxhirHl1x9xvXHlfy/jiibji8j4427Sh85/bADMoU8Wmigu974wftqskNT41c696X2oG8lDGXvXHU0UOy9SMuamohyZH4FVhobMnuB9uV5VB6h/JEX5649GPrWVLd1NUtcXlWXK76ouWmvkaSCoTGnrv4gKvHNBnWSpar0OKd/UVVYWaetER3aeqeUeMGFHqmHLBxd4TmrMWeD68RuoryuPi+RDNyqzXntcnnYJeFdsk5O2q10o9gTU+GUd8X/syiiq3Q55s6g/Ic6YydZ5XTFLxxv2fdNJJse3wHjM+eVwNvTKb17x3b/f5O+/Erw/jXdvdRCy2dftDVdf6162b9NQuLq6R9lqojyXLkFdnyOdZFYyq3lFFmdaL8hA96cq8D/wbDCsq+Bamn52i6lI+p1hqO6mKx5CPc2q7q22wqpL0OoYyX+t1Z8ljVTWn7o8qKfY39By4HhWH3D7bara1nK2gquzQ+fGaUe3NOkmFLdub0PeHkOKV94THl1SvJqaqQA3xq1aNe1lyHVX4hfx4U/0106FxxPpf2f2cKCoAkOJvv9N7ILM/3ceX7LpMaefKOVSpFrlihb9eK3gN3XTCwkJ33UJ9mtT3lixx5QknuHUXLGgMIHnt1E+Xccdt6awXtj+Ey/F5StWhznLheoxbnenGUus8FbTa7rEehtSiGr88Tx4fUX9g/d5xAUOWNqqcwua/Bzfykwxfa9w4sc2uvj+j90W/4+gMJr0WoVmsvNZ8vuXau/hQZ+zYsQCAcePGAUg+23QWUCg3Ae+LxqR6vXJ9ltovD30P036Mesry/dqfOS/oxT16AACa+x9n+BUor63/h3kwvvDP/tdNAXv4cRRSvvzmBPvx1TAMwzAMwzAMwzAMwzAMA0cj11ns7cfXAKNHjwYAPP744wBKZzxUbyYdbQllCg6psEIKooQy5r33AADL/YglVSJHambFHzYczfb65Jm+0lIk1cuXHDnjwDrrdit5n6O/Xp1Zww3EIdVhqIkv33cJZbGgFWJwJFxH2tWLjoSye3M5HeFWX0n121MVnqJqKo7Ya30JveZ+eT7zvCcbt9fAH8+WN50h9ka/XI2f/xwA0Iinz4F57x3LxNBUlKRTJHHk9OSTvUS5Z4Er53AE1JkD+SqcGP2n+qUyvF0zERXFX+fd6f/x57+AEnzGLF8zJtv7KRgrvKpkp1ORderkFB6vvuquE+NC/UpV0UPSKcjUN0yXVf9tjRFVMKhnKmOUih8qdFSlwRjmCDzVI4w9Va1RwcfleVysG6GReR6PqmO4PR63+rTxdcinXP3d1LeU+6WKK1Vlo8p2rcfqm6YKP702oc9VuUalzpIlCVf0SuWCCy4AAEyePDl2nJoRma95T6nO5DXTWNR7ka4foMpX3YZ+nskXUpVqjBv6+bFOhmYraB1VdWIoFqgGnD9/PoCwWvn+++8HUDqjN+sL+ziMy759XRv81ltu/V274l7QmqVaYzLx3E1kKef8B2Dr1uWxcwr56jZt6tRO69a5KROq8tRS/eXUO1GPkYovXsMK8Vt5TaUfpgAAunRhPOmUG/f5zJnOz1RV3jxW9dhlO6jnnk7RrW26Xif1lFQf2VB2eG0bVZ0bug+sC1pn2B7ps4NZ5XmfeB/1+abKaSpc+Yyhek7bbKIqPdYFPT7WGb4+9VSed8OUpavGSs1crzNB9LW23eoJrd9hEtnDfd/phhtuwIHFd1pW+GtQ6Ov7r/zH9EQu8OVvvAI2YdutcevOu6Qk7rOqamSgdNv42WdO4azqvdA1U/UxYR3j9tUXW5XPrDd8ptNnm/HIPo4+jznrhttr0aIFgKRSW33IQ/7h6gOtyltVHfK8E+0uw12nelKw7vujzVM+Vw9qblP7Y8OHD/JruF7+k09+E/ucOTyM/eOqq64CAIwfPx5Asi1XBSzp2tXF3GefuTZSfwPp1889fz780MWgzh7i/Q3FoD6vtI5q347rbfGzlXf27g0g+fW8HmeS+O/tn77hSnYzjMOJPJR+HlQM+/HVMAzDMAzDMAzDMAzDMAyjEmwH8iIdWjPS8sgjjwBIjtqook8zcWu2W73Mu087DUBS7MhBlAZ+lEVH/DmSyZFDqkJsdO6HS8JzimNlrdyoM87xb9NnNNWWC0gGg4ysgf6kfsS+fvvkKlS+LuCo/SO+/K1TZnz2mVP2aFxp1vEBA5w64O9/d0pGxrWqJFQZS0JKWI68s/5w5J31RRVDql5i/FNpwhF7zRodUtToKKdu95xzzwWQELxi9RNPxLaj/mZUygBJNcDFf7zIvUEhEVWjHJX34r2IctofIHkD/T8UzGimX+ULN1r9xhuzAYQzmbK9DHmBEVU0py7DkvdSR75VJcTYUlWHqotUfcIR9KKiIgDJGOE9b9rU+dpSdcIY536oFqFSTP1DWRd4nKr2pPKCymiqRKhaYalqLa1zLHkvVKEUUq/z+vL6pf6vWbk1I62qcfXcuJyqEtRLlfX7kksuwcHk+eefBwAMHlzfvyNTCnzlfvdd9zxmW6CqVG2nVP0MhOtCOn9YoLTHqWYhV8Uz+w7cLo811HcJZZjXeNE4XrDASSxXrlwZWy5b5duf//zn2Hr5+e7BR8Uu4XnqrAqN65/+1LfVI70mhZf5r0m/3tmz58fW0X5br15Ugbu6O3Pm2tjyWmdCXuiaIZ5tBEvWeXoQ54K8vNf8vi+Mvf/KK6/4ff3EvZHv+yebZgAA3nxzS+zYCc9ZZzOoapV1OrUd0Vhh7IbU1Kqc0/6HKgg1BlSdyHpHr1f1mNe6wrZc66Yq/tSTVeOI8PjVN5LHRY9NVQTyc76vcaT9uVNP7ex2WCNlquROxrubiTNrVv3YunzObNrkOpGXX345Dgfy8lw8o6r7zpXwD2X/m5MqvHIt0W8r8CXDv8iXmzbEVnzpJefZn9qv0Puv6tjQrAGFdYf3X9s29inUg5VxyzhjfGp/nNvhvdf2iPWA+z/xxBMBJPsg6jmsM+NYPxjn7L8zxnicPfyzgV3losceAwBcMGpU7Ho04mxBXx13r3DltJRl8mfPjp3T119/DQC48sor/bH5WQVdfHv3heuQR5FpFiuTe++9F0Cy38zn+QUXMMFEfPrhe+/FPeX1Oc/Y1VkO6t3L5Rnz/C7COhialaW/2Wz1v9mwB8hmgS1sc/sp7bAlL68bgPcyLtejx1mYM2dOVts05athGIZhGIZhGIZhGIZhGIbZDhw8VGFKvzKqRziCHsqWq/A2UsjMQdit3leEgrPvvEclR/E4EmmK1x8+UdQ17ftJRWwXX/rx3vZ+DK1EVqD1JIfcFrqiuG9ykWIOv9HX7XV+4jw4d+6MZwkmfH3mmVSnuA0NGOBeT5/Oc4mrA1Vpqkoh9WzjqCRH4llvWHJEXhUsqljhKChHL6lSVGWZKutUiaZefe+8/TaA5Mj8Tq8s50h+WaqtvLypftvBRQ4ZImd1mTinJE4JMWmSa4fUK6969bgKiqPOOprM+8hRZ5bqs5TajoaywBPuM5NCL7Q9VUtrFlVV1GpM89ip/qDKg+oRVXnr9hn73B5jm3WDMclS1aRUoYTUqSG/UX2tZbrszVrvVZkW8qFVT0L111KfT2bMPdgks4a7azl9ulM8qv/Y9u3f+dIpeVRVqhnFicZm6rJ6H1IVhKmf816oKk7vDbfD+GLchfwzVfmqShBVH1K1uX79+tjxMA4feughAMDVV19d6pxT0VkS7PvwurDN0TY9lJ06Ya7O52hCxZ+cgrB9e1xVzHX79/fTTap2dOUep6LbudPdR/X45L47dXLpuBctctNTVLGp9YIeoLlUvCbP5cK07190kZup8fLLVMA6X8f333fXolo1d+68zqz7vB+qbA0plFLjJtQm673T2GeMaYZqom2w+mhrv1y9fNX/mPVXZ0OoKkrPVdtHjQvtzzDWVQmsM4JUQa+zObje6af765LvO4Sbkh71b7zxj9i2OLOD3ymY5+JwI4qcYo0KcEzw/fI6Ba4s8Z0eTvepIQpIfkmj8H4TFXpxH1Vtn4HS9yc0SyE0e4WoJ7LOHOre3R3DypXuGPh9lPETev5qW6t1mfWJbTr3/+Mf/zi2vj7nNDcCP+d+VAHMry//9DNMq/jjfv+FFwAk68tR550HIDkxi036Wu8rumfPHnwzdy6A5HfkM8880x+bV0DX8Qronq6ICk3xeiAI9ekee2wcgGRsJGeSuajQ/oiqqol+tw35rmud1NkL+051UxfpCM8Y47cG/jZDlfbAw+GLn5GBo2AJtwzDMAzDMAzDMAzDMAzDMHLNUQCOybhUubAfX/eT6667Lvb6vvvuA5D0J0sqwuKKPcKEuxwrpaiRI3ocW50nWScPfMZQI9dMmvRPAECVKosAJJVIqkgiHOXu29erplb0d2VRykIclqPydaFT1z79tJP5rF/vRp4Zj+eey+H81Gy4QHJcz4335eXVjx2DKjh05F7VUapE1de6vGa+VjWejsxrpnr1+9H9ZcpariP3VLyURRT1z7jMoYae0+uvOyn1vn1u9I/KCvVyJeq9x+vJ14zxULbb1FFtHdHWWAx5uIY8IEMehRojXI4+fPSqYtvOWFQf5VDGavXs1NjXEXpeI17jX//617HlH330UQApqhBRKmrmYPX2DF1Xraup21DluGbKprKGql8+t+jhygy4P3SeeuopAMns5G+/zezh7p7MmdMYQOm453lTHdizZ1zp+vnnrv7w+qXGSiYPXt0X7xPvp/rnsg3k++pLyu2r8lX3o4R8ubWuJ1RNXh2lvpkhqIx99tlnAQCNGzeObZ/bIzqLQcvEVJIp3uNvp1O8Tp+eqqCJ152kUtI/WPfQ59HJ32rXdroXVQvzWs6f3y52zqo4Y3xQ8XowvI3pZ8x27ZNP3Pt5ea690SzR2i7xXBjzmgchna9xaJu8Ttq2q7eq9gvUO1NjUL2n2R6dfTYzbjNtetxof+VK55lKX0JunyrRzX3dtKNjp02LnSvR553WZb7Pa8bjYn9D6zzrMttZKhLVoxPw/sabvNq7fb3EMZ1//pn+P3YSXZscRYNxJKAKcMY/las1arhre/rp3hO0yF879q0TKmIXI1OmOK/X77939yi1367KZaJ9hVCcahxw29rO9O7d2G/ZfaPcubMotjz7Kow3KmBPOcXt/4MP4opuqg/ZJqjKkHG2wX8vPe6442LHRbQesu/BOCZ8vha9+qp7Lf12lqwf3/lcDCt8/HP7N4wciUxQAW38sNA+4QMPPAAgGYOchcDY1O8MWidC3y35mm1n6HN+8+BvMgW+/i/23ZclTz8NIPnsNo4Aci98tR9fDcMwDMMwDMMwDMMwDMMwKsHy1X58zRXXX3997PVf/vIXAMnRG6o1jveeXu044O6NQzb4URXakfVilt3KOVzjIPD4448DSI7kqVeUKpU4wsfR848/dsv17u09qt44K2XrbBmcx+tbb7lI2rXrGF/GFWmTJrltVq8ez7Z77rluJPkf/6gTOxYl5EEVUvOpB6tmWdVRTPVo0/2p0kV9P1W9p4pYzZDJ0VDCUdZslK9HAqqMYKmKYfVAVEWrXn/1q2QcpnqGhRSuIS/MdL6xqfvW5dSvlO9T1UGVr6pPVGmqPoSsc4xx+qbxNVVPIT9irq+KV8KYpXefXnNV1KvXrKpyVHGZer31GHl/VIHF+jJKshQfKlB1wXtPZY4qcHjP2YZTIcdYPOUUH5PN4r7f3brNBwAsXOhiSWMUCGdK17ZN2zj1LlbfS217VT0YUpCHvF5Vyc16wu2xT0R/fPaBsvV+/dWvfgUAmDhxIoDSs4q4PdandeucEo31hsfx5pv0Xl4GIFX5HVchpv5f+r7EZ4QcfbRrp3gtvhUlll4jHhOVk4MHHzy1IfshquhXRXxIbaptdugZyu2lts+Z1P6qpuZrzUytx8TYVc9UPk94bAMGePlKW6+C4xS0pQWuXONU0armZf1OtI0zZ8bOnXWOx8X31dtclbz6LGEWeG6Px8/X9MRWX/Hf//73AIArrvDPzfP9NU/5whgtoHTnyP5W8dxzzwEAGjZ0s77U7xfw2apLmJOB76+JldWru+vJe5Pq563+8aE40H6PesPqc5XxNWiQ/wLZrMCVXvis3sS6f9aLGTPoye/qExWxjEO2rXz+sR5wOW6P56lxrArv0OyEkLdxKHeEKuXVW9Y49Ln22mvTvv/YY48BSPa5+D1aZxfrd0P1pteZQUo0ZQoA4G0fg20GDgSQ7AGwDbZZyEcQpnw1DMMwDMMwDMMwDMMwDMOoBI5CMvFijrAfXyuJ0KiIz7eIIslov8SX/cuZOS8vz6kgo2hgudYzDjwcgeOIHUeTTz2V6lI3Ejd1atwXSpVrc+c29cvPT4wI9+rlMk1Tsbp3b1x1wtF9KjKoFuJIORVdzz7rFFlbt6b3zVTPKvUTpDpQR75Do5CqmlE/H1XE6PZUvacqRh1x12zDqvJR5UxI+XukwftDBZD6JvF+qa8orzPjoVs35g51cffxx05ZwdFoLs86krqPsCrNoeoJRVVH7dqtBgDMmFEtduxUgqmfbWi7qtZSJS7PjT7h9957L4D0me5T1+d5Pvzww2n3x3vw3//932m3Q4Vhs2bNYsv/7Gc/S7t8WVARGvKJzaRiPFSg6mLq1KkASiuUeL5UJFGBxnpBRTjgFTm0Ykwo0NxyxxxT2v80pPoL+WRrfdA6qH6CF1zAOuUOat489zqkFNG2T49PKe216mDc33333QCS9WrcuHGx8+NxMivy7bffDqD0zBA+q/TeXHhh3NMxBBU03G6qV6Nm7fZWhKWUrYWF7pj5nEl4Dx4CapgRI0YAAN59910AwPqeLu13iy+/BAAUdewIIOkGr5nFj/HL8X7wfvMaqaIotd3Uax7yJ9bYZ2xrLGjsh2ZHJNstL3Vl9WM/fI3zsHzzTTc7YeNGd1+1XvO5xP0wFnkeVAaq77H6LKvXPOsEz5f9Mnpl60wdbqdJkybuOtT153GF20/0JIwA2sfQvuZnn7k+SY8eM/0avLjunhUWujzoqUpXIP5s1LZX+5Uar1pq/0mV808/7XR4l13m/Wm9Wnfr1rzY+lrqzDHt22i/nHHJa5XaL0vdTsiHX/vXPA/1o9c+E9H+P+sTr++h4iFvVJzQbKoJEyYASCpi2VYzVjS2NV+BPrc0pj/y2+dz05yDf9h8+umn6N27N55//nn84he/KPX57t27ce2112L69Ok46qijcMcdd+BiPyM9SLa2A+X4+c5+fDUMwzAMwzAMwzAMwzAM45Bh7969+M1vfoMBAwYEl7njjjvQqFEjLF68GPv27UvYSJRJtrYD/8r6UO3H1wPNaQH1VMF+bzHHLsBGpaFZxzkCN2MGR3/dyJ2OErPk8qlKHY4wz53rcjOqF5J6JmlGYo76UcHBkXXNTM3XN954Y5nnSIVc06ZOncuRclWqhnx4VAkTyrKu50+4HBUoLFWhqcrckKpRvZyPVFRBzfujijBF1Xjz5zufQca0+rOqh1/qZ6qKCmUrVXT5du0oRywAANSr923sHDXmsvU1JjqiTs/WyVSFeA9M1sWQL1o6ZR5Q2tPyqaeeAgAMGTIktlwu1aghH67DFY0FXmuqKvi5Kt6SseGUdCihaopzlr7wZQdZPux3p7MMSEhpymNTNV3S4NLRqdMKAMDixQWx7auvJgkpb7l/XoNQrNATlm0IS8JnDz1J6fHK7VINeOWVV6bdfrYcqn7EuYaxy/QDezt3BgD09K8bsWvpw2a3Cxes8fdN1X3qw6r+jEAyhqjoo7ekerOrylqfI9ymxiLRfkIylt1sB6zwz6sVPumC1/WuXLkSQGkFK5V6jFmd4cNroO2F+myHnh28HpoVnsdBNRbbHy5/6aVt3Yb6+g2eASMDVb1CXtJu4JiFCwEk7+G8ee7aqopZ1ZyqmAOScc04VW909avXbTPeQzO3GH/PPPM2gGTbuGwZYp/zGaBxk86PWc8h9fhJ6JmjCnVtA3g9dDvaD9RnHI9H6zPPwzBGjhwZe82ZLepBT7Teso3ld+BDYfaKkZ77778fF198MT799NPgMo8//jgWLVoEwLVD7GeWSba2A+X48fWozIsYhmEYhmEYhmEYhmEYhmEcfFavXo1XX30VY8aMCS5DG5/f/va36N69OwYNGpRIhFwmR8MpXzP9lQNTvh7iRFH/g30IRpZwxE1HrxUdldYMqKleU5qpWl/rKB9LXU5Hspl1l/572aKqpxdffBFA0o9HR/RVbaXHqctTQcBrwWupGdxZqqKWqCeVKoQ5Gmo4VKnB2OVr9TYjel+5niqeyvL+CnlehlRPoSzxSdUR3Qudb1rVqq1j66kKQ701Q9unOooqFFWeDvT758g8r4VuT72qCJenJ61mADdyD+OZ90izVYfa8HnzWgIAaAF79NH0oO4Q214qIcUrS834HPIMZl1Vr/Bkvt66sTKk6A55vipcjv63Cj2L6Z+pPphcn9dS693h5iv8Q4FxwifdCb5kdCSkgf6Nan7CwNbWrr2su3y5e9/fR1WLplPJ6T1Vj0slFJtUvmnbrp6VLJPPpc1++ZBzXz8AwF133QWgtEcl+x+qJOR5UG0VyqStM3p0NpReH/X85HFwO2+95er08cc7Jc9JJ50UOC+DJJTdrfw/vtzRvj0AYM3ixQCSfRSWGoNsxxgTXbrwS3xDJM3/qNB0MyHoca8z1Fiqwpv70P65ercyLoYNGxY+cQBPPPEEgKRXMJXc2n8O9YVYnnTSN36L7jxWruwcW0/hcapynNeOpfb1iPZxQs9dw9CZLffddx+A0rMPWAfpSW8c2owdOxZ33nlnKfV+Kt9//z1WrVqF0047DXfffTfuvvtu3HTTTZg0aVLZG8/W87Uc2I+vhmEYhmEYhmEYhmEYhmH8YHnwwQcTiVtLSkowePBgAE48NnnyZFSpUiWWiLVBgwaoUaMGBIveJQAAIABJREFUfv7znwMABg0alEjYVibZer6WA/vx1TAOEFSGqK+ZqlDV94mjyarqAEp7pJKQh6ZmclSvKa6nmVz3l0GDBgEAXn/9dQBJD1jNtkpCvoOaEZsj5SSk9qJyJKQ00PPmdjds2LAfZ3v4ot5cjCdVb6q6WxUTGldUQuhoZarSQf3/NDY01lW9wddcb+HCJrH1Q/7CJORzRhhbVLyGFIBE/URV9cuY1Vjl+bMd4bVMl9HTqBi8trwnjB1VJBGNNVVJa6ZdbXfSwXUYV/QkI5qBXeNKj62wsBa3DADo2nW1P6ZaseXDfpnpz/Vf/3JGVxs3bkQ61NtV2wBVurIN5/t63kZuqStlKYGH2HlzOXr0UhnIONRnbSo6gyLUppLQLIPQcurlzr5S374uhu6/f1WZ+yP06SaPPvoogKRikOem2etD9V/PQ71hQ9dB+22EzwD2Uxo3bpzVeRnAc3/5CwDgOu/tmOe9/Gp6pTevrfadea/5DGjRYqHfIiW09NROnf2zBkByJgTjV1X/OsuBbSr7Vyy5b8YDS9bBqT7O+gdmKQwfPhyA80YEgNZexc42mm1vSD2WrH/uOBcscOvrTLWFvp6wLWng/XR11h+PW/3JNReEzngzjGyxvB2HL9dccw2uueaaUu8PGzYMP/vZz2I/vALuOXzeeedh+vTpOPPMM/Huu++iQ4cOmXeUredrObAfXw3DMAzDMAzDMAzDMAzDOOTp2rUrCgsLAQB33nknLr/8cowdOxYNGzZMWLGUidkOGMahC0fg/va3vwFIKtxUFaWKOFWLqJIodV0dMeZr9UZTj1PNSkrvslyx3PvDtWvXLrYfVY4QVTvqeagvomZW1ozaXI+KAqqvEj51554LACjw+z/el4XeD2iNfz0woCg43NmyZQuA0kpWVTCpMoH3VVWqqqzI5Nua7jOtLyHFKgn5B+prVWWHjoX7Z0ytW7cOADB69Oi0y1Ntoj5+VLOE/JcJry3VXFSeGbmH95SZUHlPqMDhvVPvV22fuJ76AvP9VO86xt1JJzmV0OefF8SOSVXmP/kJP3HK2C+/bBD7XP2sVYXHbN5E/fayjX+q76jQJZwOxrae104911Qtz2vKa2XKlcqB96uRf+0tXZOer7RhZZMuNujsY2ifgs/cdF6ZIV/hkL+w+hurJ3zI/1uVr/zmpJ702cI2nf7F9N2mYo91M/Ts0L6cvg6hM0r0OrTzx9XjCO2X7A9sT94oKACQnEFw7E9/CgDYs8PVBD6XtQ+qMUUv7bVr2yT2keyPuudHKKcB32ebx/f5fNnhj4VtJeuUxhG3E1K8KvS5pB9mgb8WqiDX7bPOz57tzktVwuwP0lW/xZw5AErPimAfiOcT6gNpX0hzPxiGYSgTJ06MveYPrwDQqlUrfPDBB+XboNkOGIZhGIZhGIZhGIZhGIZhVAJmO2AYhz5r1jgdpfo5hVQT6sOaqpbQzNHcFkeWiY68c/Se22SpKqlcMXbsWABJ9V/btk51taNfP/faL7fClyeuWBE7XqLXhIoX9cfk51ThqPerlg399lk296KGLV710/UIV5ZQLfLuu+8CSKpFeP14fXm9Qz6RqspTZWA6jzytD5opW/ehqqJMStfQMYZiTVXUq1Y5H8Ff/epXabdLNKvq//3f/wFI+vVx+5rRWpW9miHbyD28p+qlyHvPdlZVmqrm1Ay7VDKlg8suWuSyblNVxLadJbc1Y0Z8fSqh69Z12sVMqjoSqg+Z6gm9WFevdt6xbHvvueceAEl1II+LSktVOfGa3XjjjVkdr5EbqNTnHBd+t6DAoxrla160tsE/C4v82/V8POqsE9aFbHyNQ57vqmQl+vwIKWZZd047LbfP7X//938HgESSDj4DWDd1Ro/697Nku6Ge+0TVliElbb8jvF9SEdjXTcxE8Wqo73zsMIbYXoVmac2b52pQ6kwUrqMlCc3sYt2pJnWL2+Zy7H9VNEcB+3VUdHO/jEutX/yeoP1sxiOvZedlywAkFa/a31blL5+net5cXvdbXFwMAJjhlzvN6oFhGJWFKV8NwzAMwzAMwzAMwzAMwzAqAfN8NYxDn1GjRgEAnn32WQBJtWBI3aAqidRM2zpinq23mKrstm51MheOpFdWhmmq/5g9+ET/fnNfnuDL11u5DLLdvQI25IPLUkfSeV7qmaYj7zxPXlH63RWa4jUtK1euBAB06tQJQDIWGU+ayVz9igkVDCFfydR4DXmghtS16kGovoAhb9iQ4lw9Kjdv3gwA+OabbwAAl1xySdrjy8TNN98MAHjyySdj+1OVul5bqq2uvvrq/dqvkZkbfCbsV199FQDQrJnLZK2ZrwnvDe+Zfq7KH1XGAsk6oZ/RV1LVUlyebRhVtVQfcb3yksl/mW0r459+0GwLqMri8fDZcsstt+zX8RiVA/1P3+vYEQCw4swz4wt4j1f6nTfxGcub+NeqQlXPXm0/gbCyVWNM1f4hj1dtu1u02OS3wJ6EU97de+/r/nV/5AL2kxjrbLN1dpLOvgiV2aiEU/djWd8rTki1rO2rlr1702807mWdek+4LD9TRSmfI9o/Su3bA8D69esBAOdcfLZ7gx3UNVS6LgEARFHFfLGp6J40aVLs+NS7nG2/9t8Y90k/XIfWb14jnb0U+n7C/XC7VNJ28sfbaz/O1TAMo1yY7YBhGIZhGIZhGIZhGIZhGEYlcDTMdsAwDhc4qkz1BEd/+/alzyAdSBcAAN580ymMUpWAIS8xVc9qVmFVzKqqVr2ecg2zB7/ofQE/b9rUHffppwMA2i9aBCA58q3eaKqA1SzAHInnSLtmSd20ySlkhgwZAv8PAOA1f92oW+ta0RM9zBg2bBgAYNq0aQCAevXqASit6OP9oHpPFTvq9aVxmZoFXu99yBuZcB/0bFM1hmby1TqkfoL0qqS35dq1awEAV111lV6e/YLemGwH6O/G46dykGpM48Dx85//HAAS2VFVEaTtjPoDEn6u7XKqUpxtE1U/LVu2jG1LFVmEnzNeVBUX8pPUeqSfEz1Wqt/pGcrPOYOD+zdl9qEBFcwdPvkEAEDnSt7XfB/T6i+vMLZZRxhHqfHFmFNv+ZDaOjSLgbRq9U//H13ju7iiht/eTpfluEWLFmmPeX+havipp54CULouhfonqujVfhnhc5Dv8xlGlTmVisb+c/nllwMAPvroIwCl71W3blvTr+j5/PP4rJ/UGA7NtFK1uPY5ND7YJ0hMzaJB85qGfrlGmU+0HPCaPPPMMwCA/Px8t3uZ4aRx/q9TTwUA1F3gvqvoeelrnQmiM9hU+crZRvUHDwaQVLxWs5lphmFUNmY7YBiGYRiGYRiGYRiGYRiGUQlYwi3DOHxQX9W+fb3ar2o7V9JjpMTV+vz8+OgwUNpDjQoRRRVXVBZqdnoqLKjCqmwGDRoEAPjb3/4GAKj74YcASvtxqXKAqHcal6MKjPA1PaM08zy50EbSs+Kss84CkFQEalZf9S5jPPH+bPFKCWr4mnvVFeM3Va1H9UOmzNH6PusGVRN8rRl1te6oeprrX3nllWVek/3lvPPOAwDMmjULQDJWhw4dWin7M8rP119/DQBo29Yp7LRdCnkbJ3yCe/cGkIz3Jv5ep6pYGX/chqqLiLblurz66nF5HiuV23wGNGzoVFSsN+o9HFJ+jx07FsahD9sZnc2gcaf+i6rWZDxxPcZb6rOAzwddVz1PQzGvStAkfN6v8C/dc/7jj11Mr12b3je8ovAc6ReqilZ9nu38yU8AAMf652ZIza7PIM7U4cwTI3cUFxcDSHpld+tGl2PKTF1sffWVy0Ogfe6yUGW3tumhWQelvMNLtvgl6vlyoy9zq3wll156KYCkApazc+gjzuNiXNf262k/PKQAZx+Hy2/76U8BALWmTgVQWvFKRS6sf24YxoHGPF8NwzAMwzAMwzAMwzAMwzAqAVO+GsbhA327Xn/dZeKdNcspR/r0me4WKHGpTefOpYLJfZ4uezDLHSefDCBpT1L9s88AhD2lqCChwkIzqh8ofvaznwEAXnvtNQBAnTpOdUClDEfMiXpqcaScfplUZ9GbzagcioqKAADt27cHUNovlfHF+8T72Myv35Wjif1c3G7wAqY5/u3mhYWlPCzVP1MVsOrlSrUG1UNHn3MOAKD4uecAJGOe6twxY8Zkefa5pU+fPrHS+OFAxRmVQMcddxyAZMyxnSJU/jBWa3tFPz2tGZupijf1SVb1kJbpsskDYb9utunLly8HkKybzZs3B5D09+N2OTOD6qPhw4en3a5xeLB06VIAQPfu3QGUnkHAeNEM6OrbzfY03SwcxpaqZ0NtufoVE+7jvfdc27579wZ/LE6lzTrENp39glyjx0f1pCp1Wc+reWWfqtMJ6/yOHTsAABs2uPM6WM+kI4Hzzz8fADB79mz/DttkFzOLFrUBkIx3ndWjs7FSl9XPtL+u/Vf1Qk3WIa/oLuEvAPSjrRzlK6EC9uWXXwaQVLyyrOJnMLE/N6djRwBA7Y8/BlDa658lZ1Mwzo9+6CEAwPcLFwIIz0wzDMM44Jjnq2EYhmEYhmEYhmEYhmEYRiVgtgOGcfjB7NH0DZsxw9XyqlWpjoirVtOpQTjCTieolvPm+XXjfpZUglB5whF3Va1Q7XSgufDCCwEAEydOBAA0aNAAQFJtwPPkCDrVXPTtsgzbB5YrrrgCAPDiiy8CAFq1ahX7XBWvVEwktKyUTDjbSdSdFXuJKIoSsatKLPWy1IzYLBk7NX3mej5D6/rMuXR2I4Vekd7V/MUMQb3wmEVd22TN3szYLfafU6+UqozSNo5ts8YxCWVWJ6qApZJV1VeXXHJJ6HSNIwiqK1955RUAydjWzOOqfmNc8nOWjPlUX0tVhGubnSkbvPZneAzsB9BLkttnzI8YMaJc1yJbEl6UnkmTJgEAGjduDCB5bajwU69LHif7XTze66+/vlKO1wizatUq/19LX7p7d9JJywAAc+c2jS2v7W5q+xzy/ta+ir4m3BZV5Z9/7trqbt2W+CXoS9suq3OrKBdffDGA5Mw0Ksu3T54MANg4cCCApGZ47xbnUav9dM4+ylbZmpdXCACIoq4VOXzDMIz9x2wHDMMwDMMwDMMwDMMwDMMwKoFKsB3Ii7JJ2WgYRqVDtefxxx8PIOkfpkq+VDRbqipDtAwpTKhWoQrXMq0b+8Pzzz8PIOkjqRmwNf6O69EDQPK5Rq/X+nP4X1Klrd6Cui2iyj4tqT6iCqPuZZcBALrIuTS3R6ORAbbZzZo5Cfexxx4LIBnvVP5QKaSK2FTPV1Wu6jpUQ6lfLON569atseXq1q0bW27FihWx5VkfKksVaBzaTPaqNs4+0Tikuo99C51Fw/aa/RigdNzzNdtyVRNqnQgpBxnT9CA/2P2Xh7yHZcuWTkXJmUQH+7iMzOTlzfD/dZBPnNp07ty4spv1IDVWVdkcUnoTzcmgs3rYB1qzxh3DRRddtD+nljPuvfdeAMDYsWMP6nEYhmFUNnk9ewKz52RcrscpPTFnTublAFO+GoZhGIZhGIZhGIZhGIZh4CgA1dPn/txvTPlqGD8w/vrXvwJIZtRW/6jUKhvKeJ0uAytQWklCD1iqAM3/z8gFquLW7NWMT3rdhTK9A0mVlCrB02XTTv08pPKmimT16tUAgF/+8pdptzPVr9ffHpFGljArdO3atQEk45kllU3pFFD6mdaZkLerZnTnNllf+Dkzp3O7VGMNGTJkP8/WOBKYOnUqAKB+/foASsejqlkZX4y/VC9Mtr2qXCW6bZ0xoQpCqmwZ40uXLgUAXHnllft5tobhyMsrcv9ULXDlHs5S+BQAsGhRPoBkjKZ6bKvilXGufRGWXbo4v9nCQjdjSJXh9AJmn2X48OEVPDvDMAwjG6r17IlGWSham/Q05athGIZhGIZhGIZhGIZhGEbW5AH4UY63aT++GsYPDGaQf/TRRwEksw5TTUWVIFDa85WoIpZKEY7E0yONaim+NoxcMGzYsNhrZsmlfyDjU5Ug6gGYDl03pPpW9ZTuS7PHK1S8Fvr1upoC1sgAs0I/8MADAICGDRsCSPqv1qhRA0DpWExHyA+TCqtQ/HM9Zlhnpmn1SqYK0TDKon///gCAKVOmAEi24aqgZlwxphlvqepWLqPerdqma6yr0pUl973FZ1dnrBtGRYmiAgBAXt6n/h3Xdn/xhfP1ZuzpjAUgqVzlMoSz2FL78AAwd25TAMk2OeSNXKdOnQqckWEYhlFeqgCoWwnbNAzDMAzDMAzDMAzDMAzDOKI5Gtn9+FpSjm3aj6+G8QNl9OjRsdfPPPMMACA/Pz/xHpVUqu4jHDGntyYVrhxh5/LmIWVUJhdeeCEA4L777gMANG7cGEBSEUglUzolt6qlqBpRP0AS8gvc26OHKz/8MLa9TJji1Sgv1157bdr3J02aBACoV68eAODYY49NfEZVlLbhqljVeFf/WL6mDybVgOpDSFWVYWTDOeecAwB4/vnnAQBNmzq1HhWwLNnuqiI2FVXFqgemKlwZ0yzZn6FX/S9+8YuKnp5hpCWKegEA3njjDQDArl1NAADHHHMMgNIq7J491yfW/eQTN/OBfRZVvDL+2R9nXLNtZrxzvYsuuig3J2UYhmFkRR6AY7JYzn58NQzDMAzDMAzDMAzDMAzDKAfZ2g6sz7xIgryoLHM9wzB+0IwbNw5AUkHFrNoXXdTIL+GUro8/7rKpcnR+1KhRB/AoDaNsHnnkEQBJT7OaNWsmPqPCRLNna2ZsospBzaxN9ffXX38NALjqqqtydBaGUT5eeumlxP+NGrk2m204CXXRNAM8la7q560+mKxbNtvByAVUBHJGDhXcVASmemuzbWbM6owHfs73qQCkMnDbtm0AgPXr3decMWPG5Px8DKMsHnvsMQBA69atAST73n360PO1Q8rSzKWwEQBQWBiPfypdN2/eHCtHjBhRGYduGIZhlJNGPXviF3PmZFzuk549MSeL5QBTvhqGYRiGYRiGYRiGYRiGYWTt+VoeDprydePGjbjhhhswefJk5OXlYeDAgXj66acTn0+bNg0333wzvvrqK9SvXx933XUXLrnkkoNxqIZRIYYPH46JEydiyZIlaNu2Lb777jtcffXVmDZtGoqLi9G2bVv84Q9/SHiq5YJkhlanHImi03K2bcMga9euxejRozFnzhysXbsWy5cvR0FBQanliouLceKJJ+LEE0/ERx99VK59MHN8s2bNACT9MqkQpAJWM2arByZVJlRNDR48uFzHYRwZvPDCC7j33ntRWFiIk08+GdOnT499XlhYiJEjR2LhwoVo3749JkyYgK5du1Z4v6+++ioAoEkT5ynIuGYcUw1INAP8jh07ACTVU8wAT9Ug/ZWvvPLKCh+rcehz00034fXXX8e6devQvHlz3HLLLbjiiitKLffkk09i2LBhGDduXJmxQz/vUDsNJL0rtW1WJSDV2lRvW8wa+8PNN9+MZ599FiUlJahXrx5GjRqF//mf/0l8vnfvXtx22214/PHHsX37drRt2xbvvfdeoq3MBvZPrrvueP9OnZRPXVz/4x8u3tkWM643bnSK2JBHuGFkSza/mWTblhuGkaR5z54YnYWi9Y1yKF9LZzc5QFx00UVo0qQJVqxYgQ0bNuCmm25KfLZgwQJceumluOOOO1BSUoLCwkL08MlSDONQ4qOPPsKyZcti733//fdo0aIF3n//fZSUlOD222/HJZdcgqKiooNzkIaxnxx11FE4++yz8fLLL5e53G9+8xu0b9/+AB2VYew/9evXx9ixY/Ff//VfpT7bvXs3LrjgAgwZMgRbtmzB0KFDccEFF1jyKuOQo2bNmnjzzTdRUlKCJ598EjfccANmzpwZW2bLli344x//iI4dOx6kozSM/WfkyJFYtGgRtm3bhpkzZ+KZZ57BK6+8kvj8tttuw8yZMzFr1ixs27YNkyZNStgcGcahQja/mVhbbhj7B5Wvmf7KQ0bl67Jly9CrVy9MmzYN3bt3x5o1a9C5c2e89NJL6NevX7lPAgDeeecdjBo1CsuWLUuoO1K59NJL0aZNG9x+++37tX3DKA+VEeOA+5G1V69eePLJJ9GlS5eE8jUdnTt3xm233YaLL754v/dnGGVRWXEOuFivWrVqWuXrrFmz8B//8R8YNWoUJkyYUG7lqzJhwgQAQOPGjQEkPSw1k7BmfacisLi4GABw/fXXV+g4jB8euYzx8ePH46mnnoopX9955x0MHz4cq1atSiisW7Zsicceewxnn312Ts6BAxkNG7pM2fTMVC9jKl41vjds2AAg6f1688035+S4jB8OldGWn3/++TjjjDPw61//OvHemDFj0LlzZ7zwwgsYMmRIhdVSVAmy308f7uuuu65C2zUOP3Id46tXr8bZZ5+Nyy+/HDfffDO2bNmCFi1a4IsvvkCbNm1yfwKGkQW5iPNsfjPJdVtuGEcKrXv2xO+yULTen0vla5s2bXDnnXfisssuw86dOzF8+HAMGzYM/fr1w9VXX426deum/evcuXNwmx9//DFOPPFEDB06FA0aNECvXr3w/vvvxz4HgE6dOqFp06YYMmRI4guzYeSayohxALjnnnvQt2/fjMutX78eixcvthFJo1KprDgvi7179+Kaa67BAw88UOrHI8PINZUd4/Pnz0fnzp1jsdy5c2fMnz+/sk7JMEqR6zj/9ttv8emnn8b6IJ988gnmzJljSa2Mg0KuYvxPf/oTatWqheOOOw47duzApZdeCgCYN28eqlSpgpdeeglNmjRBu3bt8OCDDx6MUzWOYHIR55l+M7G23DD2n6MAHJPFX3nI2vP1/PPPx/Lly5GXl4dPP/20VEbe8jBq1CiMGzcO48ePxxVXXIGXX34ZY8aMwdKlS5Gfn49q1aqhWbNmeOedd9CsWTMMHToUxxxzTMwT1jByTS5jfOXKlfjJT36Czz77DHXq1EFeXl5a5euePXtwzjnnoE2bNnj00UcregqGkZFcxjkJKV/vueceLF68GA8//DAmTpyI8ePHV1j5GmLSpEkASmfUtqzuRx65iPF0ytfbb78d8+fPx3PPPZd477LLLsMJJ5yA3/3udzk48vj+gaQClgpvZoanf6B6vJqK8MghV2350KFDsX79ekyZMgV5eXnYu3cvTjnlFNx///3o06cP+vXrZ2op46CQixiPogiFhYV47bXXcNNNN+HYY4/FM888g8suuwwjRozAAw88gCVLluCnP/0pnnnmGfTv378SzsQwwlQkzsv6zcTacsOoGO169sT9WSha/6cyPF+vuuoq/POf/8R1111Xrkbhww8/RK1atVCrVq3EqHr16tVRUFCAkSNHomrVqhg8eDBatGiBGTNmJD4fPnw42rVrh1q1auGWW27B5MmTs96nYewPuYzxsWPH4tZbb0WdOnWC6+3btw+XX345qlWrlpiOZxiVTS7jvCzWrFmD++67D3fccUdFDtcwys3+xngmatWqhW3btsXe27ZtG4499tic7cMwsiUXcf6f//mf+Oc//4kXXnghMXD10EMPoXPnzujTp08uD9cwyk0uYjwvLw/dunVD9erVcdtttwFw3zMB4NZbb0X16tXRuXNnDB482L5rGgeFisR5Wb+ZWFtuGBWjMjxfEWXB9u3bo+OPPz4aOXJk1KxZs2jz5s1RFEXR6NGjo5o1a6b969ChQ3B748ePj1q3bh1778c//nH02muvRVEURf/2b/8W/e///m/iszlz5kR169bN5lANY7/IdYzXqVMnatSoUdS4ceOocePGEYAoPz8/evrpp6MoiqJ9+/ZFw4YNi/r16xft3LnzgJyjYeQ6zsmePXsiANHy5csT77366qvRj370o0QdqF27dlS1atWocePG0ffff19Zp2gc4eQqxseNGxedccYZsff+/ve/R82bN4/27duXeK9ly5bRlClTKvWc0vHQQw9FDz30UHTXXXdFd9111wHfv3FwyUWc33rrrVHHjh2jTZs2xd6/4IILorp16yba7qpVq0a1a9eOrrnmmgN2foaR6/7K7bffHp1//vlRFEXR0qVLIwDRihUrEp9fe+210dixYyv3pAxDqGicl/WbibXlxpFAcXFxdOGFF0adOnWKevXqFc2bNy/tciNGjIg6d+4cderUKbr44ouj7du3Z9x2hx49osIoyvjXo0ePrI83qx9fR4wYEQ0aNCiKoii66qqrEv/vL5s3b47q1q0bTZw4Mfr++++jF198MapXr160cePGKIqiaMKECVFBQUG0bNmyaMeOHdGgQYOiIUOGVGifhlEWuY7x9evXR2vXrk38AYhmzZqV+KF19OjR0SmnnJJVxTeMXJHrOI+iKPr222+jf/3rXxGAaNGiRdG3334bRVEU7dq1K1YH7r333ujkk0+O1q5dW+F9GkaIisb4999/H3377bfRww8/HJ1++unRt99+G+3evTuKoij67rvvopYtW0b33ntvtGvXruj++++PWrZsGX333Xc5P49M2I+vRzYVjfM//OEPUdu2baM1a9aU+mzLli2xtrtPnz7RXXfdFW3dujUnx24Y2VCRGN+7d2/0yCOPRMXFxdG+ffui2bNnR02aNIn+8pe/JJY5/fTTo1GjRkW7du2KFixYEDVs2DCaNm1azs/DMMqiom15Wb+ZWFtuHAncdNNN0e9+97soiqJo4cKF0Zlnnpl2uZKSksT/N954Y/THP/4x47Y79egRLY+ijH85/fH1tddei43EbN++PWrTpk301FNPZb2TdHzwwQfRj3/846hmzZpRjx49og8++CD2+a233hrl5+dH+fn50ZAhQ6Li4uIK7c8wQlRWjKcCIFqyZEkURVFUVFQUAYh+9KMfxUYyc7k/w1AqK84BlPpLxxNPPBGddtppFdqXYZRFLmL8iSeeKBXPQ4cOTXw+d+7cqHv37tExxxwTdevWLZo7d26uT8MwyiTNcLUgAAAC7ElEQVQXcQ4gqlatWqwPcscdd6Rd9owzzojGjRuXk2M3jGyoaIzv3bs3GjBgQFSvXr2oZs2a0QknnBDdcccdsVkLq1atigYMGBDVrFkzat26dfTII49UyrkYRohc9cuz/c3E2nLjcGTgwIHRhx9+mHh9/PHHR+vWrQsuv2/fvmjMmDHRn/70p4zb7tqjR7QlijL+lefH16wTbhmGYRiGYRiGYRiGYRiGYRxMbrnlFuzatQt33303PvnkE5x66qmYPXs2evToUWrZ4cOHY/LkyejQoQPeeust1KhRo8xt98wykVa2ywGA/fhqGIZhGIZhGIZhGIZhGMYhwbZt23DDDTfg888/R6dOnbBo0SKMHz8eXbp0Sbv83r17cd1116FXr14YPnx4mds+++yzsWnTpozHkJ+fj7fffjur47UfXw3DMAzDMAzDMAzDMAzD+MHy4IMPYty4cQCAyZMno1mzZgCAKIrQunVrfPnll6hdu3Zw/ffffx9//vOf8be//e2AHG8qRx3wPRqGYRiGYRiGYRiGYRiGYWTJNddcg8LCQhQWFqJGjRrYvXs3AGD8+PHo27dvqR9eoyjC0qVLE/+/+eabOOmkkw74cQNAlYOyV8MwDMMwDMMwDMMwDMMwjHKycOFCXHHFFTj66KPRoUMHTJgwIfHZwIEDMX78eDRp0gRDhw7Ftm3bEEURunTpgocffvigHK/ZDhiGYRiGYRiGYRiGYRiGYVQCZjtgGIZhGIZhGIZhGIZhGIZRCdiPr4ZhGIZhGIZhGIZhGIZhGJWA/fhqGIZhGIZhGIZhGIZhGIZRCdiPr4ZhGIZhGIZhGIZhGIZhGJWA/fhqGIZhGIZhGIZhGIZhGIZRCdiPr4ZhGIZhGIZhGIZhGIZhGJWA/fhqGIZhGIZhGIZhGIZhGIZRCdiPr4ZhGIZhGIZhGIZhGIZhGJWA/fhqGIZhGIZhGIZhGIZhGIZRCdiPr4ZhGIZhGIZhGIZhGIZhGJXA/w8PS7An36ZqjQAAAABJRU5ErkJggg==\n", 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\n", 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\n", 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9900eTyXVIN5lrt5jpJ0RcvfJdMWHq/5cJdXQz63v8Hi/Dufzlbj9Psi/qwSHTZmS7j9vv5FXCi/dD56wjPSHF+z2o1abk/93Uk7n53SxJOnCC5Pq4umnk8+Z+46hvkDhhjLWY5Z36Uo+V6CCq65djeU+gaibSF2hWOKggxbn/yXdyIQJyV/wlVeqvobEtl/Hrw+u5PV8g69Gz/PDI5PnfEzev2Vk/k/P/LzWhwK2K0GR6YpN3jPx7yo5j4t5LS2SpGFz50pqryRFwe3n8fLhKXFFPKKCkpIKT4RzXZy4Ph+/T4fn8etDqTx6GwUlxW/pOaGeRPnKcx/2zW+m+8rnPTUU3l0OM0yk5PWOQu/BB9O7oU4ntvC45F0SQ65w9Zkurmyl7uN79+mGGTNSGZswIbdF3aj9mFGU6miv48lXqX9EmfY629uoI4/suO1gf+6DfOMHTdnwWQvBrgH9TuIdb2AU07TN1F0e98QZdZqE/z0/DDZUzkO8EJf0mXxNCMoRsM15/vjKK5Kk/ocemnbon6+a2wK8YMdHXRoEwW5Nm6QPu/SM8cfXIAiCIAiCIAiCIAiCIAiCTtsODOr0GeOPr0Gwk9HWlpQYP8pKzkGDBlXSSZPW5D2TXG348AWSpBUrvpCPr3qSoeRwRQcj3eyHcsT9Lw89dKkk6eGHq+djZP6YY/LId4/koaYNKX+1WtXPz1WJXP/YY9OI/v33V0f8XfGKIqZPVjFlR9yswZLWZmXIZx99tHI8q7+ivMFTDUXCpZdeqqBrqNXm5f/lFaV7ZaXbOlQaKOFSjKEARD2NAhCVByoNX1ma49zr0lVUzrhx/fL/pkuSFi06tHJeYpK0mVds477T55Sl1tbkx9bS0pr3SLF96KFpe86c0ZX8cpxf35WNrvzzFbnJJ+fjOFeXk758662SpP7f+pakhpZmYz7fgrw9KdQtFRpx3pLTpJpraxta2Q/PXd6nq5Bcnecexl5nUte9PjaVr8HPP185nvJAHe7KVy8f/jl1I+d5+eUUEYcf/kzlOosWpbbH62jKr6sQvdy4UpbjiFvKvXvWuqLdyyX78bypJ5gzQe2D7yIregfNacUf2uoCnuWYMWMkSTNnpjp2/Ph3JUmnnZbq1l/+MsUCHpZr1qR+gvsBUzZ4h17n8a6JLZR6XgeXfI7vu2+lJOnMM1P+6LcMGDAv52tc5Tgvk+4vTv6Xj0+esUPnpFkflA36HQ88kNo0ytj69R2r0H1GEGWBWQu0ld/5zncU7LzcdNNNkhqKV+LRfas95b270pq2g76T1CpJWr48xavPKij5bXsfwfse7WYvcMKqJXPdxf/GG2+s3CfnIf6Jd8pB+HAHQbBr8ZG0eX3z3baC+ONrEARBEARBEARBEARBEATBZjWUD11E/PE1CHYyULy65ylqorlzh0mSxo5Fl5ZWL+3f/0VJDQUsuO8eI9s+8o36iJFqRrAXLEgebq2trZIaI+fkR0qKDx2YN+djOp0UJq5Sar8K8cacj6r/oa88j2IAp7ae6ba1NntQDXruucpx7oOIAhblDSPx1113naSGoiS8YLceVrhmBWmNxDuUPdBJJIXgG28kxakrOnnXKO+IRWKC2H11+HBJ0sFvvy2prJbmvA3VdzYu0wGS2ivkXLFH2Sgp9xr3X+tw/8WL96vshzLSFYjErKu2XK1eUt6Sb1dPkfIcOL+vDD7tpz+VJO39138tCU09NUtD9bYib++pSthaLc86GJKUy/UHNWto/r41f8CTSnH16KPV9+vevv6eeJ/EM+9p4qJFle+X5JWyB+SrrX7gAUmNla05bvaIEZKk0fPnV47nepQrvIA9XlhJm7hhf85D3UnqilRwVRX3R/kG92aGUvnz5+rPd0neb5+nnpIk7ZfrF9SEa9emKWWhhC3jitcrr7xSkjRqVFL5U4eiXGVWwfDhCyVJ/funupd3zzN3ZR7vbvjwNDth1arjJLX3hOU8tBmN/kjC60piku2nn35LknTssa2SpOXLR1eO97LhHq5e59PC+YwbZnH4KvSl2RR8z/Pgft3D82c/+5mkxnM8//zzFew48Dzu1y8pv6mDiUvvy3jfxN+317WUr1/8YpkkacSIFAeUA29LOttnKc0e4PrYfQ/NTdryHOhLc1vTK9/X4MGDJTWUu+SbNoH7J25pa84991wFQRDstLSp0cB3EfHH1yAIgiAIgiAIgiAIgiAIgo8UytddmVptqiSpre3UHZyTYGfkJz/5iaSGvyWqJUakUTi0BzVfOg4F7MqVR0hqr6LzFeLB1UiuNPHVURveZ92q2cjZdNWTq/E4/wsvJH3dqlWrKp+j9EBJw8h+3XoqXyevXay9TdXHdUor1w/NKj98Ln93222SpBtuuEFSKEm2Dlbg7VX9eB3/SbKJBQsOkdR4t8Qa78o9T4lJ0reGJoUhiswZWdF32JtvSmqvxPMVsvF6ffddlIopRktlzmO45CXrUOZKvoOukG2mVnGfZPYn1rlfnpNDmfeVxF119l5WpWz6X/9LUqOssUo8es49l1xb8GCokqn7NrWkdDERmnRDp5yS/CWffLK6Ujrvk/fB+0YlRPlwtRzvrdfs2ZKk5cuXS5I2rEhvCHU/cX1oVsy6J6ursYgj96T1OttnSaDq43v3LIaSmpDzcZ3x45Mqce7cgyrHuw+iqxpd8fpa9iHdNx/PfaHOwi8UVdnNN98sSTr77LMVdExjlkOSfd9/f9pyVTMxgKIUJSj7LVmS9Mju/Uq6bNnRkhrvlFj2mTp8zmyJku+3e+BTBubNG97h/uB1MHgd33fGDEntfZMpw1yf2PMZSe6b7G2jH+9lDI/Rc845p8P7CLYPeB737dtXUvv+qq+pQF1J3JLy/n32De8bT1VXUhMvJS9Z9oeS0tphv5f4IE1k06y8yfm5P+pSPvcZdu7R3Lt3miH3i1/8QlLj903EbxAEOxUfqfEjqIuIP74GQRAEQRAEQRAEQRAEQRCE7cCuSa3GSsEjt7hfsGdyyy23SGo/cnz66aiGNhbSw1LSLftsbuLzpHpCOVHyj3QFrPv4se0j1q7MqMPl88ellandk/WII/KQel01maqlZ55J10MZwHEL816teSRq39/+tnI+96xy5UldbZbPg4ht2De/KUl6L0t5UCLHqsKdwTSSC1ER8baSIm/z5l45rcaWKwApAx6jKNjQDKFaJrbcZ4wU9cjLL6cYQJUE7pdW8knbWnWUU1K6uhrFFYJedly5ShkprcztXrheBusrG2fFK6B0paTz3Kfm/J66h3i/1tvwftlxuiV/QdjPzWl9ckI32yFv5ffk/nq8X+Le62Rf6d2V4tTNqIdWrkx1Kiqsktevq55cWVtSgJMfyheQf87vsxDcL9Ov28hPup+xY1fn7RSJv/1ti6T2szMoD65GHDdvXmU/Lw/eJvAc77nnHkkNRXF4wf4pLTlNtfHvf/+spMaz4h27pyWx0atXagOIIWKV2HXFIO/yteylSV100OLFlfNynKvFPSbcS7NUp5fq8vY+4gn6Te7pWZp5421OySOzVPb9PKTXX3+9JOmCCy7oMP9B18DaDNTpHg/gdTV9D+Kd+PU6EohX+jCo9PFMJU5c1Y83MNcp9f9JfdZMfY2FXK5nDkjO4iPybIsVeZYFx3vfxJXb9Zlr1lfxGW533323pEa9cOGFFyoIgmCHEbYDQRAEQRAEQRAEQRAEQRAE24GwHdi1aLcC+FY65u1p6qI9DZSVjGQzIswI8QsvJBXOEUew3ihaTfR+WVWFYHRD/n5D8hscPDiNUC9demjl/K5GKq1I7SPajKi3HynPWpR1+fqLO47X0vUaktmhle2ePdOIvvtctua9Br36arp6waOWfPsIPJ8jUuPqbA/MqzKjLMEHEAXB5Zdf3uH97Yk0VP14XKJNTWqoBx5IyjViHJ8yYgAfM9QPqIZQoBFjb0+YIKmhuUL9xGCkq5s4P7GKmshXnOb8qLHeGZLug5p6UlZ9NPN67awXLPnq1+9pSY2VvEsqdFeqehnymPb8cF5fVZ7j+dz9B3m+9Dd80HdFLhN7Dtm8uCVv8kDezSkC7018Ua1VXn891Sn+Pth2ZSqpe7PWFcr5e/eBJI5RDeGj7bMX3K/PldHgcVda8Z3zuuK15G3sK9uTf75/8cWk2vrCF9L9v/xymjVEOfY49vj3cuJqMvcfLymDua+YBdFoB6Uzcprq9E996gVJjbrVvSsBj0cUbq66pn3Fr9hjpNo7aF9WeGeu6PO2wVdjL81y8JgqxT736zFGfwtcRe75L6m4UUr6LAVX2rr/8TXXXFO5/iWXXKLg43PHHXdIaq/g9rrdKc1SWb16deU8lBPvp7NN+Sl5C1MOiHNX5pb6GMST19XE47h3U2NHOfXZPl63cz5vU0rexeSTtonvb731VknSt771LQW7N43fE/ymm7zD8hIEdUL5GgRBEARBEARBEARBEARBsB0Iz9edA0aUffVURhLxB2trO1OSVKs9lrdP3qrrhOJ19wQVDao/vJl89VpGnFkh3r3K9tsvGw2uPNCugIYzKVMGDUqr8K5efVTlvIww+0i8qweJb1eMuLKlrgKrGyAOrnzt5QWee26QJOmooxhaYgS/OjLOcS1vpZWwXT3mXmylFefrqsvnn5fUeB4H5Ofryhb337zyyislSZdddpn2VGq1Ofl/k1JyQFY9L0hr4z76aFJBrV+f3hF+gMS6r4qOwszVRaSr8tUGZp8/9uuXPye2iGnOhyoEdRAqE1+Rl7Llild4duBASdKReYXukserq58cYnPFir+o7O9KVf+ctH//FyvnW7Pm6Mp2yRfQU/Z7++CDJTVW6m7J/sleB+yDQjOrbdqyOg0V0De+8Y0t3veuT/Zrn58319E2U9cSOcxK2FT5vFZLfnklb9KSXx4pK8WX6m7KEaoo4p2V5F0VSF3u16c8uKLUVXfuRcz5va4GL9fA+TnOPVjnzKn6jHN9VF/eNpU8mt0D+ZBDUjmeO3dYh/fp5YXz33XXXZIaz3VP8IJFeUbMuS6+pABklXVX4tHvIXXwsuR4Yr5Prnv72OrwXnZKvtqufCWmHFeQ+qwA4D6POy61To8/np4DZZLYKSlrXW3tEOPkn9jlc1TgnJe2lbaPOoN83n777ZIaysVQwm4dd955p6TGc3blM/3h0qwG4s9nHfA+iXc+d8Wq15Wch+OJZ6+L2Y98ejmlj8R5XHkK3tcpzTRzhS3PhW3Oz3Fss5+XW+7j5z//uSRpce4D7sn9792VtrZjtvi9q/mnTNnPjj+1y/MUBNqsUL4GQRAEQRAEQRAEQRAEQRB0OeH5+vF4KY+kTWqiKMVrdXlWKPpI9tChQyvbpIxMM0LXWFF7rCSpVpsqSbrqqjckSVOmTOnwuqF43T256aabJEl9+vSR1H4l6pJHmSsw2H/hwuGSpA8/TCo04g3PNM7Xp09S9zCy7F5QJc9UV6r6CtkNLycUuOm4ZcuGVM7HCLaXF1duNIwT03m6d9+/kh9XZ7la0NV+7uvnqSsJuI57Z6F0IL+c/8Ybb5QknXfeedpTqNVa03/6jUspYv4cAi+/TCwnTSrPGFUH6gpX7/iKt+5JOuHttyW1V7655yQpqipihTLB9fxdUhbGZlU1KhJi4qilS/N9daxULW27WsSVp1BS/LpP4IoVX5Ak9e//m8p1wOsQ8DLM94dkNRl1Q+m6rnQEro86bsS3vy2p4QCcnVKbtrk7P1nRuq41b6N4xY+bWQD9K0fNmZP8+1wN5fAcvU7yeOc9EEfuAXvkkUmF99RTqc6iTVi2bFnleG97XG3kKkKuQ7mg/BA3pfN4XHs54bx+/16Xsz/Pxf0EfXZCyYfR/Qf9Ot5W+f2sPeEESdLAe+6RtHuvLH/bbbdJ6kihSr+26hdN3eszRnj2xLDX1eAKUVcEukekvztvxz2G2Y/Y5/vSKvWuVERJyucnnIBiNc0eOPFEjkxq99mzqz+vvN/iqmpXCnpd4epz7guPUJ/BhIKYMst94L9Of/Scc87p8P6DBGp3nhvPkedPXQi8P6+riUv6k5yH8nHEEdXyIK3OaYonZsB5PHN9yovX7ZQL4oA2gfhyz1nKBXhfZdw4JGCH5DT5+8+fn35nlCErzFQAACAASURBVNZ28Drb63yeh/edfFYEn6OCRMFdq03Lx09WsGtx1VVXSWr/W9fLyvDhwyvH3XtvVW1+yy23SJK+nfuhQdAlhO1AEARBEARBEARBEARBEATBdiAW3No2HssjZSc3Ud/cZyN1gwcnz8qSCqQ0ws4oDF5Qdb+4rI7pn1dTx4OJVWIv3OXVQcGfgtIZ7r03KV4ZQXcVj4+ggyszfHTQVWrEJ95ejHRz/pK3rHsxlVZb9ZWpFyyoejmVRr79eu29X9PzOeqoNBLPSLfv76o+cOUuuOK1tEqyeze7n2Dfvn0lNZQmXO/ee++VJC3JKsKLL764w/ztHuS6DKtRhH6tKUF94zHpfsG+Ii6qDNRQrjZ2n2FXTRMrHO8+hOxHWSilrrbwFblLilbPX2kVe44fMeK1fGRq0d9887DKcSVFHqxefXxlu6S4LZVFyhTn9/O4khBVTWk1eN4Xg8P75rQlp3Py9cftYm0cahqUrjffnLS8xPPIkak8EG88H/cB9Dh01Q/fU354P+5rSZx6HUZ+Zs8ekXKb6/76e8l9EhTgfh5X3LraiPxS7jiP+36TX69LXcVXej5eR5MvLz+cl/vy63nqarTp0/tU8tOsjQU8kV05vzspYFGx0//lHXzxi/RPeuU0xYAr/Lwf4Gpk96bsYR6u/u5cbe0zU9zb0mfuAGXEVdnuw1zyunc/ZWboNFIUwYvzcaMllWdFeH/I6wgo+THTD6E/6efxNsjfC88t1GId87Of/UySNGhQWpPAZ0B6Ww1eR3kd7XHf6GNQrnrklLhK5czbYK7rsyMoH96vdy9ljuNzb/udIUPSc9BJeS0H1nh4tWfleqWZZ+5j7tcp9bn8dzVtGuXiRz/6kSSpre27ef81ebt3h/cR7Hiuu+46SY06lbbG/7ZCHUdslPD+yd133y2p0U+hbITP9Z7B5s2bNXHiRA0dOlQPPfRQ5bvvf//7euKJJySlfvDy5cvr/eUiYTsQBEEQBEEQBEEQBEEQBEGQFsUeM2ZMfaDpT/mP//iP+v+vvvpq/TYPqG+RUL5uGyXFKz4jjGzu+8tfSmo/wukjb4zY+WqN7v367LNp++ij+at6Ghn0lYkZEf1J9pjFWypGaXZxeuSVF7MM7H/+z7QS/DPPpDhyVRGKCuKMOGppYWX5FJfvvju6chlXB7n3mftcEncO5ymtjO6rBbs3VEllB64qdC+qhuKjOrLviteSL6CvUuwqS1fEkH8+dyWDK1NcjcX94OGLAuXmm2+WJJ199tkdPoddmh753R6Wt6fndN08SY3YRRHJM3F1k6seUKYREzzzUoy4KsrfsauV3AuVd8x1Xf3BfbjyrbTCL/lghN33cz+zhjY0pa7wLXlQbi0lpS54mXUv0dLq9L6CM++J/gmDxAOyiGdT/mBX8zXHP+6OO+6QJP3+9+k9E19eJ/lsBFezeR3vPo+8f8qP11UoVkvqIV/R2pW0XN8V2mzT9/A2hP043uOF47w8NlNTcR++IjZxyXGuqqI8uUK3dF6eG+fnfK7wdpUilNRcAwcOrDwPVFjf/e53O7zfnRk8FMeOTWsUoDD7whdW5D0OyCl11wJJ7esQrxP8Xboa2RV67k3PzDCPXW+XfdaF56ukiAVv14H9eR4NtfeinKb+/Suv9M35OKhyvZIy0vNZ8t7378kPqjDqCvZzVbbPDnFFL+e54YYbJEnnn39+u2ezJ4HHa0tLi6RGH8LrQldogteVX/1qOu7pp6uzYIhf3s+sWWmm5GGH4SO+Ph/3ucr5HFf9sZ/3odxjls/xdEb9xflGjcpG/sqzbM7K5WJs/jgJ5PXaayMq5/PZHZ5PV4CD1x9ebtyP3NeuoN/d1nZ23n9q3j5Vwc4B72jIkLQqgM9GoB/h/XfvV/lvNT73fgGxxHmZ1UF/4MILL+zCuwt2Bt555x09/PDD+sd//Ef9+7//+xb3vfPOO/V//+//bX7S8HwNgiAIgiAIgiAIgiAIgmBP5/LLL9e//uu/1gU1JRYuXKi33npLJzZWyiwTtgNdw9VXXy2poXjFg5XRFleyuheVr5jrI/c+gv3ss2lE8+ijl1WO85FTRtZRi+EJy2qUl1566dbdaLBDqNWeSf8ZckxKJ+YvFk+SJB1zTFIJvvBCGmlmVI9RPle+Now10wjv0KEvSpIWLeLEXLeqRuK87vnK+d07taQYKX3u2z6SXYJ8MeLuyvIFC3pX8uf58BFy9wP0VYFLCgVXgnj+Sitfe75cCc/nu5MCtlZ7LP2nx8kpRZzRyh4pxt57L6WukqZu5F0Qi7yj/fdfks/ziqT2nqaucgZXg1AXE1uu8vYYYkSc/Liqxd+pq4j43hV24D598Nprn6t8P3bsO5KkGTP6VvLhMVfypvT7clxtVfKr8/M2U52XvDHrW3m0mBps/C6ieHU8zqirXJHtforg8Uu8EX94k7mi1ZUcri4CV5h6nKIOInWvVVeKujqR+/QV41357W2X19UeP65s/9KXUFWmtvHJJ6tKXldcU7+4ys99Pb2N4PuxY1+XJM2ZM7pyHXBvXc8/50EB29k2cGcE/+IvftHbS0ovM13Su3nwwdSf7d491WX+jEqe7a4M9LrIvTF9VkBptfRSmfOy6XVls3fmM3bwfp8/P92fK3FdNV6qu30Wh9el3mb67wzKYOl3h9cJHts8fy9b/D6aMmXKFp7K7ge+zSi/eb6k/nuQ5w0eT7zPRx6pquq9/8z75nwvvJDi/f3303HHHkufYqUk6aWXhlXyQ1xwPLNvqOtd4erlEcUrCnPideHCz0uSRo7MMzfXJYV1fbbTwpfydQZVjvO+nfuCl5Ty3m/3Nsl/t5Rm4DGDtK3tOwp2DvhbBu0kf+vwMuUzdrwt8LrM+1U+w83r9r/8y/Tb8r77Un+LGU2rVqW/0VDnsUZBSz6u5y7cru9JPPTQQxowYIAmTJigadOmbXHfu+66S1/72teKa8hU2A62Ax3/8gqCIAiCIAiCIAiCIAiCINgJeeaZZ/TAAw+opaVFX//61/X444/rb//2bzvc96677tLf/M3fdO7E2A40+7cV7FHKVzyNUJbideQjhD5yzcgbaUk9VPKUYv+nn+4nqeEv6D6DjKjj4cRIH/ljZJaRxcsuu2wrn0CVXc1/b2cHjyHpqJSwaGkeMNaQnI5MKpsjjmAoJS0bOn16igfib+JEPMWG5jSNgC9dms7vI+9QUgm6J5T77biazVV0zZQiJdVdaT+u7yuEu6KlmeLWcYWBn6+k+nMlreenpAR2tRlKCbxgr732WknSRRdd1PED2YmpK14xeUVsTejVRQepTl2xYqGk9r67rrbwOrRBS+VzXy3d3xGfozh1z1hUQag+Sgo8FIjuhcl5PNZc3eUj8j7y7m2Hxw6rr0+Y8HbeHt7h83JPWPcFfGnAgHS9nM8Ts6ISSgpYH/31OsT96VxRyHOGHqqCUPqe7LPuszim5fxM3snaIvz/PI54zxj6o+Rw9Zt7krp6xz3J3JuU1FfIZj/iyuOBOqj0Hl1VR75ctUTqqkK2XX3k3q0e717uuP7xx6Msrqqk3EvW75PreFvCNpCPSZPe6fA6/jxLPt/eRrrKsF+/1Mf76U9/Kkn667/+a+3s1Goz8/8OyimVOv2TFbZd9ZYvvWOfOeKqbfei9+PdAxZKbUIzX+xmCteSV6XXwdwH79oVpaV+VGmWgfsNe5n38xPb/E7g/DxHVwqSepn2tpnfQ2z/+Mc/liSde+65HeZ7d2P48NTmUpe7qt5V8K7C9zrC11zwupb49fJBesQRtJoH5jS9740bF1fyR5uAcpW6jPjge7bd/5v80LZR7riPVavSdt++03I+Ul9v0aLBlXxwHupsFLjcN+dlf6+z3W+f58Z5SP13i8924jz8Xr7gggsU7Bhuu+02SY3ZxfRLfF0dj0WPDZ8hQ0x5f9h9xn2m3YMP/j5ff58O83NfjqkzmbqVJ33My5+P3sn6p0GVH/7wh/rhD38oSZo2bZr+7d/+ra66/lNef/11rVmzRkcddVTnTrxZoXwNgiAIgiAIgiAIgiAIgiBw/umf/kkPPPBAffvOO+/U17/+9U4Lxuqer83+bQV7hPKV0RcUr67+cLWKq7RKXk7gHj8lVYSPdLrHDaMwjLz6yL6PZHNfjDRu68p9MarTVbAacFaKLMj+dT1zAe+Vv0YWdliWxHZLStiJE3n+99t5GXJBNTWq8i3x4AoL9yr1EWVXzfmIvldMJV9B6KzvZGmF9WbKlWbn9/38/n20tKTO4v5cHejlkdR9El3NSb2xa3qpZdVFr6SorCteCUliWlUvSXyqS7ME2q8YjEIzlQlXWPoq6776OaoPUo8lRtKpW13F4gpY98PzfJeUfB575LPkX+yfz5gxonL/7qFZ8lMknbB0aTpP9jN/oVd6QUdkBayrwUvb4M/RFbKuEO47N62QvDj75i3M8bLswQclSX2yv9yVV14pqTF7A8XrzHz9He0Ne99990lqxIevLE584JdH6s/HV90tpR5P7h3cK79Hzud1uePlztVX3vfxOri0Mr0rnr1v5MrXUr78OjNnVtVYGzdWVY+uqvLjfQVvV6xOmtQv52BMTlvzdVP59llI3geEkiLfPWwHZAX6zuj7XfekF/66I3PavYO9JSnNZpgzp0VSI5Y2bKgqNb1/yrOnDnU1k8eo92N4lu6FX5r5UlKWenvs7bvTTCFb8sFuRul6Xvbcw9OVv15m3dMfhWDJl5rjXOHps0g47uc//7kk6a/+6q86dZ+7Gvg+7r///pIadaP/ziutqeAq+ZJPtM+qca9f//3ZKI/ko1oXchz5dYWoK0W9zuR74gYld6mcrlt3eCXf3jYwC4S6lPO637irDUuzJqg3Vh13nCTpU/mPJ+TPn5v/TqbNDgXsJ88tt9wiqdFfIkZL/Q7etStd/V2zH7FV8v32/gjncbW/q8dX3J9+ez9zxhmSpJYsPu/ihe6DT4DJkydr8uTJkqQf/OAHle/++Z//eetOth08X/eIP74GQRAEQRAEQRAEQRAEQRBsETxfm7EVf1Hdrf/4euutt0pqeC8yOlLyZfNVE331UB/pdHxEkNEaRlV85NRHcUpqLK6Ppw37M2qDKgZvC1Rn7qvnjLRtVvhDczMplLBbCU+uNadJBaZZY/N2S0p65fjh42ynqZFZGXHP0fmDZyVJb76Z3tR++82S1D6OoOQH6aN+7jnlPpoef+CeZK4o6awytaQ4bebl2ukpAhk/ryuCXeFSui9XyvooLEoRRvxRX7If9Q8j/jfeeKMk6bzzztuq+9kxZKNixBcrLF3LfmmImLqIZ7HOPEepaz0WG3S8grCvzu7elr7SL/isAl893tVLrkh1NZbjKijyRZ3vI/2udPQy5SsEu1+f54f9vC07fMkSSdLzg5Mv2+P5vZxoClin5G/s6iz32HKV1fuzZ0uSPshx0NPaLBQRzo5WvAJ1APmk7WXbfRhR/XB//p7d+xVKPtacn3jmOO9LUPew30knpec/bVrPyn24zzblz/MLXI/v3SPW60Jvc5zSbAnwvhVx5F5wrgbk/v1z92NUr6x4zR5uWtAz5//9ynV5TuSH+0Vx622Eqwk5D/XN4Fz+di7/zDyboUeezZAVrOqX6wQEsYtzGd2QPOmJfe8vu08wsejPyJWAHtO8a/C61VXXpdkEXqeWUq8DS56v3h9odh7o7EwgrwNcvU0Z9P29rSjNwDn99PScHnkknZ/YJHWFMpAPFLL4v7e1ndzh/eyqDBmS+jjEd6kO97jwvoPXAV5OvG/i8erv+5VXkgftoYcukCQ9/TS+9R3PVvDZOuB1NbhC2uvMUnniPK54JeW83DfxQ8pzdt9un4G39gtfkNRYcX6V9amoN9xbl/PQZhPn/D4uLcATfHx4xvzmAe9Xu6raZ7S58tVngPlsAK8b/TruH+79G/eIX3jnnZKkFXlBpg+z9/+LP/mJJOk73/nOlh5DsLuB7UAzPtf5U+7Wf3wNgiAIgiAIgiAIgiAIgiDoFJ21HdjT//h63XXXSZKGDRsmqTEC5qMs7nHJtqsofCSZkcXSCDTbrn5ydYt7LZW8gly9xSgP5/fVYRk14jm4F+wz+fpD83bWZ9YFmMHWUatNzf+raolZsVxK6prNm9OqwkcckRUlK8alFBEYqpznkiJl5tRR+bgUf4sWsdR8wkeKfWSbEWb3PHXVX0lJUlKMNO671mEKzRSyJW/kknebs7VKWFd3+XVdZbg0q5Za8/6fnz+/cl32d79Rzuc+jTx/FAA/+tGPJEnf/e53t+o+PglQudRjemWWQ61EmVqVwM6enZ7V+vXpnnkGpVVMeRd8j6qjT58UsyWPU/d+pQ7k/O47Rp3Mca5gJD++0jNKN9QUHsOlVeRLsyk6q+4ued26P5srTUtelF94991KPlwJWfKydbyMuzrLZ4m4B5evUMzzL/kJPpb3O/kTVsLenz2/yD/5njTpnbxHS07piaUy/+tfp7aX+HNPM1dRlVSBJf9Fni9xXfIchcmTU/6eeKJHZX/3SiOl7+CqKVc4Q8OrWZX7a1Ynu392Z8uVl2OelyvEXRFTV7Ssy5+vQ5k7N18ntbHUyf5+vPy58t79If3+WWeg5M27QxiTFa9MStg355mZOKTzc/pImonzmc8sk9S+31xSK3vd6bHk/W5iqLOK0mYzc0oq/lJamtlT8oj1/Urn62x/xsuyp54f/91BmfTfN48/XvUGpc30OtmVx+29bDn/1Hx/p3bqvnZWaHtGjUp1gLdpPkPK226PB1fClnwl3RPZ20z24/PXXktetKUZlZ5v91j2Pgj3xe9J+q2uoC7dr/d/qRs5j/cR/PeGz+LxNnDDfvtJalRDTK5CTcl9H3xwmt3zxhvJJ9/bEu7v2GNT+vjjKf5ZK+Wb3/ymgq6B2XzM9KA99fYYPPa9P+Fl0Pu9pD6jrOSfTVkgVn3Gis/Y4ffA+nvuSdu2Hs9dWQm7Zs0aSdJFF13U4X0GuwmdtR3YCnbLP74GQRAEQRAEQRAEQRAEQRBsFbHgVpWSOoYRMtQ1pZVroTSS7oo49xnzkTxSH4GGkt+Zj3D7yKmPZDJ644pXX92d72+44QZJ0vnnn1+5LrGUXR3rWjYEmPfl/J+5k/jw7bxkdWCvrGRdl57g5s2tktorFaSVKdmQ9/cRlTSw284TmPfrqsCSp6mvFlzyxfER7pIqyeO35IXleLkqqf9KCpTScc0UMiVVVUn15ytq54Uutf8rr0hqvA+O47346C71jtc/HO9+otdcc40k6ZJLLunwPnYM6OAxuklKsTlzkmqqR4+k6PrMZwZKajwz7omYQ6kHpVhAdYN6guN9tVRXhLpahxFsj2EvQ67k4zjUyu4l6yPzpTLXTOXUbBX4UhvA/XMfKCxdWeyKSLaJvZIis7Rid6nMeB3iSmT3FPVZImyjDPRZGrTpy/N+Az6hNojn5rNW6j6Z9dZyYU5T+UApsXz5ckmN8rC1PvHsj8KC5+vqevcW5n0+/3x6XkceuSSfJ5XPktrIVXuu0ne1UykeOqvuc0pKWFcBuhKG+yH+SwpY3sOjjz4h6U89hwdU8sF9e93O+Vwx7GqzkvKV/fv27SupsbL6N77xjS08le1DjRA8PafTc4rHKxN3sj1uPdTXpnsaPPgNSdLixUmZ5upwVxG58pV3VpoJU6qDmtFZT1ePUe9HlCiVAZ9RVFK6eix3Vh1eyndJkVsqK67Sds9Nb9t8dgrfz5yZ7i+LvepranzrW9/q8D529t8P/funfrrfrz/Xkk+3U+qvugLU46XkU8n+Pkui5FPfaKu2nC/OT5vF8ZRXUs9PiVK5876XK369z8T+VEekzMwck99XIz/p+ey/f9LGzphRXcPi6KN5b6kiO/HE1KN/5JF0nmuvvVZSqBa7Avpx9Ju9PYVmsyVLan9v532dnFJ/3L/neiWlrXv9sx/9LC/T9Ot2Lk/3oMvprOfrVrBL//E1CIIgCIIgCIIgCIIgCIKgK9gOwtdd84+vrXn04vi8PTNv/+bqqyVJLS0tkhqjH80UqCUFXmkFYl9x2j2WfOQZpSwqDEZvfFVYz5+f10eT/DhXw/h9/dd//ZekxnPDanS+qqDxwRN2R/nv7ezUavfl/52REh7shqSqOeKI9D6eeGKWpD9VvuaR2x7VzfrISjY58hXhGf0jDkqKDGim6Oisp2tpe2tXDW62emopv717T5MkrVt34hbvwyk9F8evz/MeNGNGZduVIHxOOXRlCWmpnsB/FFXUzkCNSqFfVRmmlanuGjeuVVLDh6zZrAI+P/bY97hCTtOze+aZdDzP3n3HXNXvK2z7ir2uuHS/MV+xu+Rr5qoPj7FS2XGVSqmMlEb8S2Xa2xbyT5tC6n6L3mb5eXierohtpi4v5ZP35bNCXNkMvCeUE84npXh98MEHJTXugzg58shVeY9ROaWSTs970aIkE/Q2nm2PQ56Pq4O8T7HgoIMkScNmzark09+Xq9h47q+9tm/lfrx8NfOZb6bi87rSFdauciz1aUp9Jr+ezzrgeu4J66l7toL7lLqqzBXaXo9wfEnx6vUHccCsrB3i931pTpnaxIwbTBW72ef0T+gQPpdcGNvaqr55rhB09T7vkGdQmv0A3q+Fre2vlJSIpfOVZvyU1FpP5DprMlLQAl4Gms3g8fvw/JR8xr0OcZWWzyLxOqE0S6HkNTpkSFIU4vd43nnnVfK5sypeWZH9wANTYHud4zOUfJZIMy/ikhK6pCQt9Z1KSvDOKrZLXsWuWO/Xr5+k9kr10qwGr8O9LXIfT9pEnquvTQKcb0nepkdwxLp1HeZDok5P8ThhAnPVqMCQ8ner7NetW8oX/e6dc+bZrgEzlkaMSL673o8kFkr9Am9HPWb9OO/P+swhr8O9P+CKWe9X+CwB+g3NlLSUqZtvvlmSdPbZZxeeWLArsh0sX3fNP74GQRAEQRAEQRAEQRAEQRB0JaF8zTBw3z0PaI3Mf5JeMWWKJGmvX/9aUln56uoFVzv46qw+8usjz6XVLTkfvoekrtoqefuUfEx8VAhK/if18511lqSGlRcit9acIoAgyHjOeMEGiVrt3fy/k1PSL8cXA6ws07k+eSqdcEJ6kg8++Fb+YnRKGNrlOF7AyqSkcN8996lpns+OR8hLypHOqvQ6q0wpKUh8u6Qk6NNnQfpPjzMlSb16kd8nJUnvvTehw+v6eZut5O6KDtRQXh+4ksdHbyn37tfoK9XzHinPjLI281DbntRYuHhiTsfnlMpgevYnntUiSdq0KcVyaaTaPRilgTmtBrsrz7zO8hgtKel8BJp3gYcr79brbI8Rp1nZKamloJnquplaq+T/556TxBDKUpSXrhDgeftz4vmURvZ/k/3WaDOOzTFd8qp1VQv5ceUlx5OPkj/5nLzfuO2kpjr99H3y//A6xtM1+3Pr2ZzyBFLB2Lz5zyW1jzfKuitgS0pxnsfirHil7fXZMhxPHcN7dwVmafYO+SjNtvE6r+QdXFKyNMPPB+7F7Co9V5+5YqWkUvP7dw9X99ot+e+TH7+OPzevH7zvuLetmvyJQseP4GKmDqGOdTkdvg223SP1Z4YOTWrsRYsOqJzeFbCuhHVvTWjmLe+fN2vvm9XpL+cySss0cfXqyvlK/XB4Oyvmjs7b07J35vH5POBlsOSz3Mz73j/3utvLqsc+dbvPiKNu8n6mr21R+p1BmWCF8yuuuEKSdPnll2tnZsCANKvHldj+3r2Oa+Zv7e9xdlaU0s0fmv3AvQ/S2boTSjMfm/VvoRQnXqc1U9ZyH7R57mlLXUscNfOAJh998myP1Yeltpg+iyuzV65MdWi/fm/mHLk37TrbTvnp0WPvyv1zH6GA3Xp8XYvSOiQlT3efWeJlzfsLJZ9rL3vEGv2nCROWSpIeeKA6M65UBnymi7cFPqMFyMdNN90kSTrnnHMU7PpsB8vXXfOPr0EQBEEQBEEQBEEQBEEQBF1J2A5keuYBrjYUr/lzLKo22WqQrhh13zxGVRgtAVe4osJg9MVXsXTfNJSuKN9QJflIXklVUVIcljyEXL0BdUWfqqAc7pmfI8E1IH8+L39QXcs90FHZDRcvNGz55tp+LTmdn1SDp52G5CSnDNRiVVQ3331OkrR5c/IEdWWl+1WWFBWdVZA082xtppTt7HElpUfZmy2NqNcVOyvyceuq/kB+nmZ+lQ7f85zx5aM8UV4BZYgrV1E18TmjrtQDDRVoglFe9qce+CR9g2q1/Ozvzs+I4T33IUa+sT7l8ZBDkip50aIklS15SzbuOanFp05NsdtYtTx926zuK8WUj0DzDn21+pJ/mo/Ed9ZHzZWApZF5KHlENfOV81guqcm5X/cW9dkWnm+//33GJA/T6luTjlq6tHJ+98Rsdp/+fP0+iH1WoHYVyvZSvDbIitdeScWmdalX0dqalK2uLHU1D8/f/Z7di7fkRezPsa4PPzrr6371q0o+fLVd8Lbf3zfl0eO25Jnm78nj1ZW33gcq+Wy6Eps+kveV3E/Q69iS0rekbC95yfE+2Y/3iUKV9+YrxJP/Zs8NuB9WGi8pvbcL1OV/k1MKOf2XqTnNE07qM3Hon9SFZWlqz/Dh0yVJS5emGSj+DkopdNbDteSR6udp1u7XfYrztiteHY/VWQPT7I2TqxaSdYFdM1VWs35ISXlbagtc2eozbcDrCGKd1J8/n1MGfYaP+zri1z18+PAt3t+OhjUvDj/8cEnlMl0qy67W9z6FvyfmSNB9nZMVt2NyW+pKzl69fpP3TH2n998/SVLz2TDb+nlJMf5KXouAyU+tOR1q3sbcv88qoo2h7fO1Tfje/bv5fu8jj5TUmEDIcztk5cpKPrn+qlVp/YG+fZ+XJL31VjpyXfaK/fDDVJF95jPVdQz8/ZGfK6+8UpJ02WWXKdgypZlk4HWW90N8phRlgrrFZ8aB95+9bXGPig8bxAAAIABJREFU18ceq9aB9Fs6q0L3/q7/7aUeu7l/wv1dddVVkqRLL71Uwa7LZoXtQBAEQRAEQRAEQRAEQRAEQZcTtgOZ9XnomgFoxjQY0XbPKV9Jl5TRCvdn8xWz3aeNz/174HhfcZdRE9QUpO5vxnn9PK5WYrTow+yNc2h+IK35QbyXvXPqKwrm/KEUXmfPkRFaPuiev0f0NjXn/9SddBXTT4wzcnp6Tu/M6a05RQHbktP6ELKtIE/Asv/09FyffDKNnvHe3CfOV2eFzno1QUmJ0VlFa7P9m50XXNHdGH3MkhKUNxsYe6q6EDe7j5ICpjRKS7niObtPoPv+uPIdxQiqQ8ov13U/otLK2ig1Lr744g7vr0vK46X27KgM8AHc1HH68ssj9aeUVgHn3u65Jz0D7pk6jth2XzqeQTtVxv5J5TD29dcr1/e62MtIZ9Xcjit512T1x4oVKyrbJX88KM1WcNU0KiKUcb6avSuMwcuQK/aISZ99QWx3+/Ok8BxabwQSvXLZe3LQIEnSMdm3jvvwlZ1L90s+eE5ehlzhuLU+eNtKrXZf/l82wFzHPI+FOZ8HV/Z3NdzBB6e1mRcsSKovr7Nd/eOKV4+D0kLzrV/6UvrP88/nfFVVde6zR+rvuXHfHasUSyvWex+qpDgprYxd+pzn5Koontt7770nqVHOqFM5jnhxf/6Sqou61z1auS7vifst+e97347U/bxLs6LI/+eyymx7Uqs9lv5zbfKoPyFXjd/O6S1JaKYnOOCqnNIvWehmsKTpc1eFlxSfJWVnI58dv7P299OxwrWz/RQUr828Zv38deFvnpDDD49j31hZ2b/kW15ai8F5PHto8qvi2FwGSrMGOJ+r0F31TmxTpkozcShjtBVcl5j1mYBsUyauv/56SdIFF1zQ4f3BtPxcJ39CvydoU33WgLetpbUVvO4veacSL8xz4ykjJOc9eN36/vvHVa7TbAYZlGbDlMqfH78q10EtOa6POaqa8Z7T1eFxnM+9Yn2FeVLu0+Oo7os9ISnox9H45XRTtl13pbb71a9b9xeSGvHt75n3U+/zWH68DQmaU/JcLc1EoY5h5hy8/npSK/MueRfETjOPV+8/+G8qX9OAust/Z5RmBHkMlepw7pN8c51g16ZNXT8DfJf842sQBEEQBEEQBEEQBEEQBEFXEspXo3seGeuRnwoj04xF+Oqr7s/hI3OoF0p+bu7946Mz7kPI6Ij7ipT8SlxV4opcXy2S4xiI5wH0yCOW87Mitp2yNYN+oZul6/PzZACyxfbfUxWwtVoe+1ic3ucJaZFXPfHtvAODeSyMzVA3D36sfc4DRdmZD2S0jFVEfcQeiIN9931GkrRq1ZGFfHfOa6y03ex8W6u4LR3nxze8nPCaQguybyUfnVXMNPO+cnWWl1NX6bnKCrWWK1pLPqh+Pv8eVVeJj1P+arVs8PeVU1PKsB4xjP8wsve6IjYpH/1ZUXdRV3IvxCzbqGq8DiXmSXlm1Mk8q6OXLascz35el37cWOS6q7NK6u2335Yk3XLLLVt1XvjzrCwt1f0eYyhXWZl56NDkM40nKs+pmTrMPSZRi/AeaFuoipbnumhArvx75/feP7cp/pw8xkven8SFKw99f2KfeLn22mslSRdddFGH9/nxIcBZGTkpXufNa5HUXgXDfR50UC6b/SZLkg44oFWSlMOknecwaidXZPtqwWj7UUuhnqLpmJX98Hpn5TfvmeeGWo1tzovC0j3VSopUV9n5LBzqOC+HrvJzRXzJN9LLBfmkDeS+UMCuXbu2kg9Xwpa8k302g9dDHtfUA96XKz0XX1fAFfl+HP7inVULbhvJl5vmk4j/sqrbTxyQ/0OHkn5KlsC+/XZfSdJnPpM6NN26pdkPJTUSuNK1pJIvtd+l43v3npP3SLXXunUndnj+zvZPSv7VgFfn+jwLoGevytdNvfZL+XFF4onZq7KZpz+4AtPrXld3E9P+u8XbUv/d47NTvM6mriOmm/FJKV7B6wYv065+A69LXBXnz315bmtb8vFYKh8we7akRhvYbBZBsxldtCl+PuqcUhvt10PxqmwvXu/r5T5ga97sazPTSopuvvfruh89dXa9LuQGc+O3fmX1+r3W0UYniF/gPdJ34nrepwDPrytfm629cF9+P2fuYb+DJemKK66QJA0bNkxS+1gt9cepe554IrU6J5xQ/duGz7Bp5unuM35cVU6Meb7ce59Y9b+5kG/vr3hZdbxfG+zabBg8WDM70zd78MFOn3PLERQEQRAEQRAEQRAEQRAEQRBsE7uk8rUnksw8ZL9vVmqiE1uTR0F8RNeVb/iOzJgxQlJjVMNVCu7n596rPrLnPl+oTtw7Em8aVwH5iB2jRRznI46b5yZlwgLzKdt39GhJEoIGZNMIGhgHZEVrdIWj8/Guu5u5B4/0JbIs7NctkqRl30ybeyWBpj46Lu82M6cuLZZ9juJ1Xask6eWXqyss4/9IPHocN+I5vcm+fV+VJK1alVYsL60SXCoXJQ81p7PKko+rAGmQI7dfXol85WEdnqeU72aKHB8BL/kY+qgno66MtvrKnD5q635D7ivontMc12wEftvImrqX8iZq7RyLdcO/hWjvUmy+8spHOe+pjvKRaO4NlYHXpWx73VdS4QAj1SXf42YxxPZLWUnKXVEUD37jjbSdvVwXL06F8913U+3461//Wh8H8u2+3iXFHc+jtbW1ko9+/fpJkkaOTKqzIUOGVM5bWt3dlQCuQOw2J6nI3s0xvCKvCN2S809b4KqfkkeWK29p01Ay+iwUL0s8H+rAruahhx7K/zsmp9zhikp+vAy3tKTnr7Py/mTv/hZJ0qZNb0pq3Df3S9uN4tjVQtzv4QuT8pa6ZEFuw+nyQOm5ETc+a6KzHsjug79q1SpJ0rKsOEcJ7tfz9//000+rI7761a9KarxXlN2k5Nv9GLkP4hflK0pYUvLjPn6upHHVHhCnKGpZMZvzuqKZ/Usr0LOfK25Lfu7bhYm53cyV3S/zx0/mdCD7ISyrPhIR5CNGzJAkLV58hKT2Xq/Q2f5F6biSJ2z7/kRqL1evPr5yXDPFYOn3gKurSqru95ckn+eNg9PUp5dznXx4Xo3d8+F1sl+vmYcteL/E+yulNtD9h0v9HY9lYt7b9nHjWiVJc+eOqjwnrkPZvummmyRJ5547PJ/3ZO1IuD/3h3Q1XGlWiavsqCPr589+9KOZ6ZbL28AFqU73GVGl35GleCClbaBuoi6mzvE+hKsBfXbRnFzuhzySUqoBZmEclut8KP2e8PNTt7ly2BXUfI7FNGuRDH755XT+/Nyo84H3yXtB2cx1va/lakaPb1d89+2blP5XXnmlJOmyyy6rXH/P/R1cXpOBZ+jtLp8DZejxxz9b2fZZgVDyfHXPdVeze4y5Wn1O7nfwt5FBM1IbR1ktrWXRbIaQx1QQOKF8DYIgCIIgCIIgCIIgCIIg2A7sksrXVjxJc4qAkAF7RrQYmfSR50MOYWyvRZI0YUJ1Pcrp0+tagHRe8xNhlAW1BaMdrl7wkTRGUziebR9x9hFXH2n1USZX0QBqmd7Z0wfLHNRejCOu/vGPK9cp4SN9e5rnzc03J63I2T9skSTNdS9X5HQtOUVNWF85Hu/S6qrB06ej8kquRyilGTUseZ4RByg/mq2EDlurVC0pRkoKlpKiwyl5xRUVs93Vuf0sH6Vy5eXF78+fp5c7V1ExOupeV+457R5j7j/oI/ZsX3311ZKkKVOmbPG+O0cO2rraaZ4kad68Wr7moZIadZP7xPnILvfiCkdXxrmvlqtBXAnqqhygjDTzXvJ3Pml58qxFAQtzsvLznXfeqeSr2cq3J56YfAap43lnJa8n7oP92XZ/Pl+hGsUk6g/SSZOSF+bs2Ul9NXBgars8xjyG+R6VUmPF5bzS9fS0xPHvcj6IQWKV90Rc+Cqz3ia5JzDX5zhUKcQLzxHF43ZjSD4/jeXCSZKkP/7xd5L+xBevJdc1J2XF64F5fxrR3HQSL76SMm33yqyOw8PU60BXku+V38PyrBT/M2sT3M+OPggKaY+rkpqP90ZcUQ6WZJUfceGrCJfq0BIPP/zwFr//xje+IUkaNSqp6gZndaGvrI73MWonFLrkk7jkeRBPnm9XBXpby3vivL7qsecLvB7bZLOxXFFDfdaV1GqpTtf/Seppuh0b7krpxV9P6fEcQBlABF6vwkbmtFqXOyVFqX9P2r//ssr3q1YN3uL+/vny5eMr+SmpjEox+XG962fZdrPj+vRJ/Uf6a51V6EIzb1w/3vsnxBhluPT7wT1EPZYJjLFj38nbaCSBADoop3j0v5TPM6nDfG8vbrzxRknSAQekOYDEi/uPu2q+5J3qv99WHZr6SvW7ylMKN+Y2wf0fSwrvzs48Ix9c32dE+u9U9vfZNnUV/jNpzYjF+f7Jl/ttU9d6+fZZBdSleP+WPGfdm/jzue0h/8yO8pl+7h9K3VyaLQVeB4PPLGQ/2g7aoKCBz94r1fmuKvey5DOMSmWhtJYA/UbOf9RRyZd73rxxlXx4mV2d18OhpvK/HREDPoPG+1MlRa5z1VVXVbYvvfTSDvcL9hxC+RoEQRAEQRAEQRAEQRAEQbAd2CWVry151AEvFkamGNntnkdHGO1gVIbRkdmz04ieq3D++MekpnC1lqt5GN1gxA3vndIIHdd1jx9XuLknk6vKOG5j9k3bK3vi+P7s18IDy750G7PK7e28YvcfTdXE6A6jNM1GZ/YUxSvUlc2vppFiXZv9AlmIGzXU6TlF4Do9+TU++2xaCpu4cnUXI83+HqGZ2qjZqsKlkfTSqKUf5+op8JHvEs0UsqW0zuKkWlyzpqrq21pPOT+upJ5s5iPqfo2uInQfIlc+MMLv+S+tJswo78ehVsuGxCcl1VA9RmelZ7p5c1UNQp3kq3ZDSW3Nca5wJLZdKelqFFL3KvVVxF3R1gzy2ZKVrvPGpRHy1uz56mWT+zjrrLMkNeoA96B0Bas/F18l3n2+S6uo0qahZCQGmHVx001vSZJmzEjy+uHDk7/e/tl/jphspoB1JTMx6Qpg7sPVM97WlhTRriBw5YMrElHboF4677zz1BWcdlpWA34lf4B4K89mOOQQFLfMq8k+0yhdkb2Z8nX06FRHvfXWUEmN++Q9ulqH9+lqIK8zXEld7wvk98Hz8zak5H/tylnUTfRleC/ED/Hu79W91DgfCmzO11nP5DvuuKOy/bWvfU2SNHZsUurjceyeqZRXPGlRwlJO3Aew5McNXl54X+5t6wpY965zX8hSG0j56NI4vzPHOPIe/L3vTsnqHNr3TsyfI/9h9fOhOV2X87wp9Y+HD08KzrVrT5DUPsZKamvo3/93+X90mKrKSW93fSabt9uuXnZ1stNMYdjZGTVjsw9ySfXE5336TM+fHJi3U+WxZs34Tl2nlG/3bvXn4sfzfFw17kpDV1Ly/tr3EykzLpUmkDbY9+5c/clw/vloUrk++UprfkyfntpMb5O9jXJ/SZ4bZ5uf0/5pckO9aRhofRYoefV2dgYaKe+NtoTzen8RD1Pvg1G+aAO4P5+56ddzdaD7dfsaKo7Hpz934pU+F/kkfx6vXh7cX91nrrlvt/dt+B4FLx7G55xzTof3syfhz85navm74JkuzSpxrPLbsuq69LcOUl8Ph+v7zDCmRxL73j9l/71fSo0hXvODc36XLl1auY6v3+PqaO67Gd7vveaaayRJl1xySaeOD3Y/QvkaBEEQBEEQBEEQBEEQBEGwHdglla/gI9+MsDHCyKiJe+T4SC4jwK7O8ZHBksKO0RTOX1I/uFrFlbeuIuFzXz3ySB5AXpEaTcnYt5IKasF++0mSRjEQndVtjEcP/va3JUlLsgLWfRh9ZeQ9Hbw2L710ePULlgs+NSV7fTGlH42t7qa5SUKy997VVUN5n6iiSn4y7mVWUliXFLAltU4zD7GS4rOUDx+9LClRmylg25M0BShFmilWOuvx1lm1ZDMFcsn/z71cqSdQGLgHtCv0XQnQJb6AY7LaBnU2Cr5ZGBYvktTe38zV8aVVPtkeOvStfD4Kwwc5fV2S9NprSZlZUoiiYGPbR5zJl3tJuVesQz5X2wq+3hb4KuQldXoJz4efj3dPTJRU7eDKSPJJfliN/o2s4OX+UAwyO6RUt7vS1N+rt2k+i8O/b6ZGb6ZKc9zzd1t54IEH8v9yZU0biQgPf+66gTetZlbnze1e/ZqU4+em2RCjRs3JH6S66/XX03tARcN90jegzigpLrxPA+7B28yDDXh/1EXEIddFEeJtRzP/a88XipQzzjhDknT//fdvMV/O3XffXdk+99xzJUnjsmLdZxug6uN5US7cs5b6zPPPe/C+mnsck7pS2ZX7HA8lVZ0rYLuEfQspYu5bc4pkr650zSkK2E1t9kWi1K57zPAsG4pXMoI2cEXer09lf54h/sP4JfOs6T9Tp6Ls81kErsJq5qnpNO+fbJk1a5Lysnfv+ZXPO+s521kv/9LnfjzPhzaJz/F7bpaPRp2Y0gcfRJ2WUsoQ7//kkwm45Llaq03L55/cYf67ihphdpIpjAm71vT5xImprp4xI5Vp7695P27RmDHp83yaPs89l77PZXvWxCQlp2kZ1KRsl9bsgJKy3M+Hyp+6jePoa7BNX8bbeF+zgONIqcuYzcDnlEOeF22crzTf2fLjM8p85iiqRveQZXvcuFZJ0lNP7VPJB6nPOPVZV96mUk6oX4L2M7Y81txnmP1ZJoVu08JjUn9pr1dekVSeOeYxzzvkNxHtO3URZcGVuaQlj3ZiBHxmndcJXnZLv4vIv6/jEuy5hPI1CIIgCIIgCIIgCIIgCIJgO7BLSxzdp87VH4xWuN+eK81K3kiu9vLrudKWkTNGYVAfMSriI2yupuA48r/ffkmWtnDh4ZXzQPc8jDQyDywzGjPy9aQue+agtNpozzxEy4Avo08HZgUsI7R8/+R//qcCqVabmv5zbl5d/sL8BYpX/DKzoOGjbP/ylVyqHsmKWGWx1aGHJlXa0qVHSSp7k7kitTSaVvKAIt4ZISbugXhtFt+N51AduS75CTajmVK15LG6ZMnBlfvy0dGSgsTVeSXVVintbP6B8/posHuqUc753Ed3wZVDXaJI/0ZOUeoh3+iRFI9jxrwmqaHU8zx4XebKyJEj30zn6zc5paip1mYPzRUtkqSDD04rcb/5ZpKnuHelzwZwhVlJnVNSKQP71xWk+XNXU6FyQFWF+gF8RNtj0vPjfnJ1f/J8n8QClHydSTkOFQtlmdXpUfy9lL2tDs1eWy0tLZV8eJlwtYerXTwevKz5ysbks1cvPLmI8XdzuiDnd2Ll/D7rxD05txYUl2eeaXUWSlfqckRa9Vaxf2X3+scjc9pix3NbKylgKT3oIE6Mz2DyRHUlpfvtEQf0SVyF5XFVWjUYeG8rVqQML1iQ8lOqW2krKAelNqPUh6I8sX3qqalRnDp1qraFH//4x5KkM888U5I0YcIESdLQoVWPXVfEUi5cBeYesL7Cuyt8fDaT3zfvzz3nXPHi8Uy+v/3tMTl9JufzmC0/kA6o1ZLvsB5J6uW6ghVRD5dGlIug1QWp9bJAIUl+4e+998UOr+tll3sdONB8k+uNTjrvsmWprfHZFm/lmVxz586VJP3qV7+SJJ100kmSGip9lHY8U1+hemv7HSW2dn9X+a9cmWaklcpMZ2f0+O+WZopCP87VWpRRyoyrstv3O2irNuXjqz7h7sHbCDQ8SAm07QxrMRDvXH6xfb4yxd+ECWkO4bx5qa6jTaZuXDM+KWWJYnTMzD4h7vGTb83qfO8rlLxf/T2Wfp96G+11HXU129R5y5eneuHdd1MjRd3nytA/fvnLaTtfb+1jj0kqt0H0Z30mHD71rib0+y4pu8HrZu7P1ZCjRs3NR1TXbPE+pSuDyb/7entbQN/hqqvSTMgpU6Z0mN/dGWaBjhgxovK5zy5wr/P653mbJuYP2Qu+m/2m9fbXvVV55z7rkneI8nXAX/6lJOmIfBxFf2XuF7sS1teWIHZ8xh11gpdl7w97DG7r7Ilg9yOUr0EQBEEQBEEQBEEQBEEQBNuBXVr56r4dPtrA96SMWuBz1sy3DNyHjZE8Rnfcf9CVsGsmT5YknckAIEOnkIeBnnk1pT1eflmStGDBIZX8M8K5pLVVkvTprGJClzDc1Bi98wgsI7hrsxcRai9SQKuj731PkvRYTk/eSoXjbsNxWbp6dd5muO7anGJHh29mNt998pS8XbXG0rp1J1ZO30ylVPJO85TviWtGuI8//sN8pjTy/fOfp/LBSD2KkdU5LkbnuHJFbjPla0ld6Oo4VyV+XCWJ++eB+/W5T6Vfz/0uKd+lFbA7C+f3lTbZdgUB9+Ue066YL626+gyjtHl78p88z7qK+3/nmEYMjRrEhIXkpaUF70q8W6nEGENuzWlWCPaYnNLxtruzPq3Evd9+qGJS4XnhhaSW4N697kW14N6WvkpqCb5HPbHmkUckSaNNreF+4uAqFmh2fVfAsr/7fhMbXmZK/s6uUEQBCPglvpzbFNgv+4J7/r1sodAl3yXvVx/x5/iWlt+mC/RKSsWG2iglGzeeLKmhrAXywXvi/Nu6Smyj7CIDzBlBqbpv9WONzPuvza0khYppIy05RRiLDGplVh3Wy8cQS9MFJk5slSQ9+GDVZ84VF808ln0l+ZLSEtgf5evbb79d+Z7njXcqbQXlz1VKXh5KbQZ9F7yH/+Iv/kKS9Jvf/EbbAqpI6sQjj0xO+CNHJknyLNSQef/9s/IV1RdqsFI5d49lv3/3dnWleql8lxTDjfqkoLjeGg4YUD2VCw3p+HGJo2y/qhWrKCTvv58Up6V22/vfjfY89yyH9Kyed1P6j69ijkrZFa9AP8fbSWYr8LnPnthWZWszL/3OUpqhx3YpnyW/ZVcOknrbVJpR5LNKeH7ErNf1vJ9GYKXP6Uf6fTbYWNm/sb19qNVyn+X/jKtetjWnVM0LZaS6Y/TodPzzz6e6iufWkvei+ByYZ5dQBxCXPC9aGuLRZw008rvl+PS2npT+6uqjUgEeNGOGpEZfwGdmcl3qwNLvZDxsaZPfMy9ZzuezY+jfuk85cD0vn9wHcePnc9988sFxfP/668lTGNUjz418uP8nsxN4b2z775/DD8+dlVyPXXpp2toDha/F34I82w+PPrqyP03J8OnT0/fPpBkd9ZlU+R3zrl1t7DNnwOtQzx911TF0u1JoqIXf6pOSDzc10dKc9s39Ia5HLHpMgrcFPgPM626fHRLsuYTyNQiCIAiCIAiCIAiCIAiC3ZJHH31UBx10kA444AD9y7/8yyd+/V1a+YpKg1EKRhUY9XAVj69u6J6LPirBeX0Esb4q5P5pxW60JazvPW5e8jNcPzqpu45HWfC/czopp2ur6TH5/T+RVx11lYv7nLz/apLKDsojdozA+vMg7ZkVBGu/9CX9KYz+IN5pySnCiNY8moRI6Jg9RQmbBRsXpYFW/TSnqxEBou5DRZgG97QBtd+CnD6bEvenAVcm+HvzUTQfuWWV2sWL05D+0qVpHO9f/zXF9zN5tPH229P1WHmactL/+efTbWQ1UGnl5dKqqyWPspI6q3S+0vclb1X3GPP8eHl2D1h/rtw/I+yo/nzFS1cqlJS/zRQqPnrrvknkh/dcih9AkbG4w29zKc/q7LoahEKNAjaXekacly9PldWAAVnR160lp1ldtcFk/KinUDfN4t2Rq1xYeqS6USPz7IW1SZG7cWNSwvFOXOlK3csz5t2WPi+tIIxqYsiQIfm6Vc/LkuoJ/N2W1FDN/Nw4ztsaL+uUVVfOuo8fx6MwJHaoE2bNSkP/xDj7lVYuJ1+UBXyL3dPS92/MSskp8bUJJcGoynHEG/fN+/b3goJy28mVd7ecLwoNYUyjhxAXG7m6CjDjvpgoKvIBzz9P3Cbl8YQJ7Fhdev6009KDefDB9H7dn9tn97ha3n2+6dO4rx2Uyod7HaN4dZVWaQX0Ul0HfI+yHOXttkIcw/SsrOE+eK1Y8y7OcT5w0SJJDUW495n8/rh/V1G6vz/liXrFla7NPHJ5Xo8/ntYJOPFE4qWlw/vfIv+UU28QUPohFqIfQ3+Ufguvpl4W0omoa3r1eiF/wdMlRulB0rjkQjWyZ/V8XH9hqnuHD08m+jNnpjqBtRLcNxB4VtSFH5h6yj1n/ZmXZhw1m21Qmn3QjJJq3f0GXcXV7Lqujncf72b5KZ3HZ2FQJ/E+Zs5Msf6pT6HtrJ63PENobd7v5C3m7+OTK+fcH6/3cV6lbiVOCXSeOzK5NHukra3q/clp9lmZlJC1wloC0Gv2bEnt+wQl/0dXuJYUsf6+JmYFLm2y+9r/7sD0Q2b/vKI8PvHu4+7eqNRl7nPpdRzly9dUQVHqM9G8zvXr+u8a9iffAwcmv3TaOI7zvoe3SZzXZ8S5z3ppRl0jTnzO6J6Dt+/+txF6yXT39svttKv8gZihX+mzPMFjbtGY5I0+OJcxLzv0A57Jbd/4nPK3Dpqinv3yf3ITtiZ72dK76JfPTwy6atvbCup09iv9Br4U+XSwQ9i8ebO+973v6bHHHtOwYcM0adIknX766Ro7dmzzg7uIUL4GQRAEQRAEQRAEQRAEQbDb8eKLL+qAAw7Qfvvtp+7du+vrX/96fVHeT4pdQvlaq6XVFn3ElJEvUl95mlGWww9PHlKzZg3L56uOPDJijleMe7fWVVXZJ2RSHgAbkAdK2/KoSl2TkxWvBzKqgqqGP6qPyP8ZMTB/8HpKsnLxmBOTN+gTjz4qqf3KetyfKyChpABk/3duuEFSY8Rvv2xes+DKK9P5LrtMUmOcD0FE1ZVv96Xuj/mtpMajSCJ2qitFGChH+OHKDobPNqTRPVepNfPx85FiRglR29Q9mfKo4apVqyrfv/jiix3eH3Fe8o718tNshXmJNwAkAAAgAElEQVRw7zdXoJRUgNBZ38ySQsVVRu6B5goFjvMVrN3rDE+zAQOSgviDD06pnN/z79d1jyr3dfTny3t3fAV4ZzzvpYPn29Z2Zv4qH9srBy0iJWJ3cQruoUOTOmTZMjO13JS3h2Tla49a9TwUEhSDvfL368yAMJcJLcZTM+Xr2GO/UDnBE0+kE1JXeWzwjFHq8Wx9BL3ksch5KRO+4nNppejttXppScVEflzd5WppV6DiAUsdgR/066+nNgc1CbEJHpvug+axyPU4DzG/enWa9tGnz9TK9gcffKpyXu6X98jnqGdc0bm1nHFGUj7W45ZwnMgOOaVORxwFxDPiqTybQSv5IK0EP2tWdeV1nterr6b3OGYM+imed9rvtNM4z945ZbpMuvBTTyU1oNdNHn/LsgoKRff++7+Rv8HRPd3YbbelcuWr/NLHKCnGSwrXkhec91WIjwED0ns47rjj8v091eH14JRTTqmc59d5leRZpqyZl2cd0bNyZzUU3NTpPC9fTdnbElfGuted90XdZ9E9cUse0Ox/003Lyg+jwO1MbZn7tylFmDozp/RHqKP94VDVc1xLThekWOrVa3Z1h26jq8dvQgmZ6/iJtcpmXWhYF3fzRaqjiGlixOukE044QVL79pJn5v2mZqunw9YqXztLqb9U8gP0+2mmzPU2zstgqYyWlK+O9z/9uZb6eT5L5emn0/0sXowf9valre0YSVKN31uvpjp3/nx8JVPc7bVXqgO4f57nqFEpUHv0SL8XKdP7Lq/mf8CAXJePzFPgFqa6Z84cM9A3tnYGVbM45nlTh/vviMPefFOStDj7vHd/+mlJjfdJ34DzUO6ow6gz+Z3pdbzPMKVPRdz4DDQ+575o44n7ks+mr6Xiylv6Dr5CPSm/i3zGK+cpKWnnzWup5HPVqnT+bfWf35UpvXtS1pnpZb/J3HfXf4PxblA7++xArrd3VqaenJuajYekdXHenj+/cj7O/7n8+aJcV72WFbM40/akzctLJfTO3rCTaav+Rzr/xjxrhL/J+Cxqb3t8ptqUrTQInpbzP7lQ9oOPx7vvvqvhw4fXt4cNG6YXXnhhC0d0PaF8DYIgCIIgCIIgCIIgCIJgt6OjAa2uFtI0Y5dQvrri9eqr0/Lzo0ZVfeN8xJVRlgULDqrs5yPBHMeIGCNcKA33Of10SQ3hal01k0dHEMmgP0U8U1cWoDi4J6dnZRnNGNbYy95WWSHb/f9L6Zf/36T2eDd7F72kKugGuO6f/fd/V+4HfDTGR85f//d/lyR9Hx+Sgh/J6A4/3R3Jzy8LPBbPyB/n9zMkWf2qJac46A7KadYx6z9QyPZCwbHllcxdicn7YmQaLzQUr66C47wlxSvw3onzksqt5KHU2dWO3eemmXqwmaK2dB+uUAH3cOqsstY9YBl9XbNmcofHuxLHR4cZJWVk3v2ASr6e4D5JJVUaHNjBZ3U1d4+k5m634jWxihfmrLRS8MCBqD2qSr16JcfxvkL2ptaUrnNvR1/Nm/Mih6I2S7XtCV9K+fnlQ8mv2leGdl8ulJzuzegj6Tx7vveVeZt5vDZTvpb2a5a6d5WruJ3SqqmcDxULXp7UJawoTl3iKjO/j84qHakzeJ7EemtriicUDqhM/Hzs7z6Drq7aaibmACduSU/KKVIIwtMb83ctXZkUHjNmfJjvJ6moSvHFe50zJ8XnuHHUVTx3M4CvS2vTfR93XNrvF79IfoOufKaO5rmRvvBC73z9pKRctCi97yVLktKb9+V1TIlS3DcrD67sJB4pryVQvOLhxnm+8pWvSJIeeeQRSY242Pu00yT5euyN2oXnRV1Mm0qdy/e8v1L5c29iniP55Dhf/bg0G6mk1N8auKd66BDDdFAfIebyU+mf63pi3y1c2wn4NlXTTTxVk9J2y++UDirnYfeV5CNl7PnnaXfTp/4sJ0+enLJV8EZlP5/N0KyuaKY0bOa56u2+U/Jb9rRUh/tsjYEDeaDp98OiRWlqnaunfeZNMxV7qd/ifo6+krh77oK30Z6f7c1VV12V/nN8/h2zMMna/vCH30lqXwb9Pb/0UlLlk2/aRu6r/r6GZMUrbcTC/vm4ZZXjm3m4luK0medryTfa76fui5/3W3vssen7O+6Q1GiTXa3vKv6SHyflkdR9PDkP+SBefH/vn7u/Jvv7fXHfPjPU80G8unLWZy94Hc7+/nuiUS7uk9SYXbY74zPCSu2bq+R5Vz5DxD3siUXenXveD7c2iZZnXvY1xv/YIX+fz0rYFXn/ARtsR6rY+u+hlHTPF/ry36b+yGOpG6bPZhW514Wu+u4sj+UyMKTJfsHHY9iwYVqU/f+ltAYAs8U+KUL5GgRBEARBEARBEARBEATBbsekSZM0f/58vfXWW9q4caPuuusunZ5Flp8Uu4Ty1emsF5IryBhFYWSrpOphP0ZlXECwOH/AeHXtpaRJfSd7wtYHZ7JJarfnUtqb1WYRg/1NUl3UJbXZd0TEQPYfGfpITrP56BozX63rEb74RUmN0SAuV5uaVG+MyvB8LsverkEVlNY1JISIk/KDXpx9Ao/IpefL+esjc/paTv+D95pFfiUFQkmxWVo52pWy0FnZvCtBXW3G6KOr2FzRAJ5PHwV1SoqQ0nbp+GYr0VOOR45Mioe3307+PcQ/+eU+6+U9e1v5ypV878+hVB+5ksSVI4yOsu2rC1NeXR1VWgW6NZ+/pcPnl0f1UDcR21hL+orXVHYHZI/MO/PsA0aGW6qnrav71yVF3fPPpxFo/MJ4FzzLDRuS6v+DD96S1N7rdOLEXIt2S9f/8v/4/9l77zCrqrP9/x4UVAakDV1hAKWIFKWpBMVYiEQMiQUxNCEUQcUYo3nzS/Lm/eVK8qaYqFgjKkETGwgRxUIRLCDCiyCh9zZ0hlEBI+L+/rHWfbb7PrM4M8MM9flcF9fmnLPPLms/q5xZ97ofry8/4Hx3J050U8/qUcnj0P+Mz4JeUuo7xjLldYZUJkV9rc861MeoJ2Ym5aB6Z4V8AzUmeXwqDJnlXdX1+v1MqihVBKpPHK+PsczXqqIirMOse1Sr6Gser9jQd/0av9W2PeRLyc6UGeN3uvheuNCVe4UKrsKo1zDrrqrn4/vm0Csp5Zgxwz2n3bu3J77P4+7alVQAq0qJz2unz8i9evXqxPf5vPV5qhpflbCZfC9VEaP7qzqPYzB6r155pZMg08tVj6t9ELf8XjPvqaaPk1A/o/6E3OpYUdH74FazOPP+GLfazugY9dJLqYxx+0+detohr+NQpFRCzPLux504kI/kBz64X/VGx+f6mKSV+FK/XccjcwSssnBnJrtli1sCtG+fi60mTZz3JVb6tVIpP3Eez0lzp09nv5pUkpFMMcgYqvfDHwKIuyTexkGv7s/kmalq51B/XtStHl+vP5Oylt+rW9d5+GOQWzWAYf5ATznFZfny2xLXrd6amfqiTKs2NKY19vm+5txQBaJ62ZY1I0e2dv9hU+Lb9FatNgAAFixwP7TYRrNNJBwPVq5cGUC6/3rt2n6w0zC5IjNufZD4no63M41fSUj5WtTcCSSlyps5EwDwH9+Xnurvn8djObBc+LzYrvBzHQ/rCjneL/tsVXbr+FcVr5df7jrdyZPdcUOrmRjv6hGtPqHqA8p2g3HK73HM+B+vgFvlr7eW9zHV+x88ODmYzspy+0WRr6/1/XPYfOL4dvJZ64qZ0MoQlpmON/kMeBzNHaB5bM7wf1vh30Q4LuPwLPWzpbZze+e323glrPoiUx+71/+RJJvjPv6eyfVbhi7/5uIHFp894ZYx/8f/rmAd1TblrrvuQnHgsLOleb2WKaeeeioefvhhdOvWDQcPHsTAgQPRsmXLI3sNR/RshmEYhmEYhmEYhmEYhmEYR4ju3buje/fuR+38x+UfX+/0nqSvvPIKgHTVgqqbVFXFWRfO2Kr3K7+fmun1mXj3+9mMz+R85bxvWNV33nHf91lZU/aH3PqZ/1r05OIsDpUBnL5hZmUqBUTsw/nVCpx487M1273SYU9yd+za5WbQORszfPhwHIrJvjy6n+yzL6tmuO0vu7otVVN+O+EWt63jRHOpyTEqX1PP0QdCUWeqGa86864ztfSr01nCb3/72wCA6dOnH/J8qsLTLLv0hOV18LyqoAh5WIUUsMVVuup+mTxnSaNGTPPsZqYbNHAqsA0bnFJHlRnqZZYpG3AmZYuWM9EsrppVWD3r9PrUY40c2rHGNyZ5bZNv57pNY+9fTIHgNp8cfhYVgpSSURHLk6X5Ajq9ANUKqkxVj0TGlrJokVP+tWrF2Gbj6BrLnj1dpRo/3jWOIXWI+nqxDPPznRos5HWaKXN0qA5kyvqeyctVn7meR5V/oRhU+BzUc0tVOZlgeWpbwPLl9bPtYKxqG8Pzqg+gth3qCVbUtiII45jLQtgHs09mnztP3l+1N7ED71efP+PrwgtZnu7+58xxfpxt29JDmZ13UqtJD171nWfbwHJ5//33E7dFBaj6EvJ6dP+OHTsCSFdd0TeU8ZIpHkM+g3yuqpJTVRLPx/vr4v0IeTz18eeW56WSZeNTTwEA9g4aBCAeUpWXbcgfXOuV9oUhb1Zeh2Zt5nPTvpnl8J3vVPLvNPbbdf68yfIqEfu8vzeqyAcuJpYtcxmfmzf30sCHvIJvpt+NA9f1+fJG0n9v1y53HG1rt2xx/Vnduuv8cdh2u0pFT03A1SFtCxizVW5xA6wWfu93fG4Clk3Vqq7OnDbLVdJ1lzjzWtaoioF+POTdqkq54q4sUoWdfi/TSqC0FXvtvRKnt9+Rj8G3TXXqfAIA2Ly5ZeL7xW0rM12vqtdCfR3R86tiNsRif5zDVn1V6eq2bMu5Am38Zf4/bozCNk5zGvB9HX/H1+9NktmE5/rtDnccth2hnAkkpJjOhLY9JNO4nt/T38U6RtPVG6FVLRy38rV6NasSW+9bla9x+SRXSfH72qbyetXXXz1bdYyiv2fUn56tJoe4+b5NT1dKX+637F34g89TESccjGX1v9V+Wsd5fEbaH7L/5nhU2zDu31K9+v1h2NbzZ0r9HHnjaqeEzfdi9RVyP/w5c8Afr56XO9efwgMmd5zrx42MAfb3jOmWt94K4Bs/i4YMQXHoebL/zeUkwjxfDcMwDMMwDMMwDMMwDMMwyoDjUvlK1INFZ6pDni+cVVH1hapFOFvD43M2R8+n2RmpPKXIRnLBoqafuc5SLyxOnFGBQPyszGZJilqfr/1sUC3vRbrSH3/L6NEAgK/8jOHQoUNRFDhrM8OXV9eTbDaG2VLnzHEurlWqLAcANG/u1So7/HSYfy6PebngY8lktMBovy1Y7P9zFoDwjLeqiPias4KcuWW81q/vrkPrAbcdvE8OZw81+ydn7VQRruoi1gPNUB5SkKj/oWa+DClItP5myioc8s6Kj+/mRfPyqvv3XYZtVWCoMoPHuegi5xm3fHnVxHWEvHtDqDIopDYMzR7z/vgcQx5h1OZVKOSz8ePdM7z+eq+82+PVR76yU8TRSb9IBewN/jV91DSdeGqq1z1rxhLRa1Z/YMawltWyZe795s3XJb7/3ntuipsKQVUG8nyqwOXnOtOu1xWqiyG/tZDiVZV+IcVryCNTs8SG6k4mNTnPR9VHTk5O4nWm46p6RFUyrOOqeOX1a0Zy3RLuxzZO6wy9TIvNU5v9f3zb7fvKVKVhm71QXq/6UnZ0nW3z5jww1zv4eK/opbSp+uG0Fp06sZNnp8/OgtoNN0rYscOp81nXVQkSUo+pV2omPvroIwCxYpaex9xqRnk9r8ZxSPVH9HmrWqpGDdc2sx1gH6WKV1VJqqdxkzxXzmu8bx/bwhaiUFEvXfWyUx9E7VtV+UN01RT3U6U5VZ9UvC5cWDlxXSVRvvI7Cxe6cUabNpv8J5T+ufFA8+YckX7qL9r5aGMeS8tJLD/91GdF/9p5t1at6vfzbXy5cpQXwb9OthHAfHe0HVRZu0oXUmgyhlhWzEXMLoZKV+6vCrtKPvcC27RMStOQ8lU94Yvq3RpqgzO1rVp3Un0lQ4VNR6ogeATXlqiCMKS0VGVkyHebaIyrPyPPq219SHHJvkFJKV4bFvpx8dEmlq9buLa2bVt3HfPnu/hhvGiOA5Yj46FmTReXuNK32exD2IT753Tuuc5Rcvt2V2+0vEPq+0y+7ySTVyxRJSjvk32L/q4NtflsA7UN5vs8HvsOHftpG6rthMbrlCn0dnX3x9Ugen6SyXu2WTNKxmsiiftdt22b+wHH30PUZvKxbvJtMuO6Rw/fvuX4PVK+oOI0vvLE+92svs18piT0m5XPhG2Gtpk6DmVZn+lXM6TkyP5vG9sl704uQ4I2zMxl4R95NR8CnZ9323y/SpjDvAYbnB/0wgYNAAA76HvO7ccfAwC+9rFcy7dlXFXMnBJzRo0CADT2HvSyztAwUpjy1TAMwzAMwzAMwzAMwzAMoww4rpSvWVnOiIPZ6HXGWjPP6gwsZzTVn05VCvQh4f6auVZn3lT5+uW0aQCAvCuucOfzqpTIz+7M6uT0ZR3ecN8/4LfbfGZiVV2p3xj5oIVzw+rgEu+lJsqpX6BSgP6GReUqf14qX0MesNv9+7Xow8IJT++LMuVA8njHK7E6y09tz/PqKU67+dm0lIFMAZ1l3Lxafn5XAOkz1qFM5STklaQexbw+zjiHFKHqwcS44OydxnUqe7JcT8inUWctVTkQmvEPecZmUrqGFAB8vXq1MzKtV28OAGDLlosS31OlO+vZRRf5LMM5PQEAzZq5me/8/OTzUKVCpi3bHbYvqgQgbdp85v/nnueSJUm/T/VNIoUpXkmq7SjvFa9UmYgYYD0CcH+KqCie2iGvvQHa2We72F+79tzk+T3q+0WlG99XL6jly+sljnPeeWsLvczXX3dlxdhmGVMZxzJMZT312VA5c83s64xdfUah2A95RqrXq8aEKho1NhXGUHHVV7yes85yqri6dZ2kmb5nmdRdWsdVQciYpApK+9SQqkhXp6QyK+fmAojVbzW98iCTb2CIKHJtdhYrCSUPtAFk/LINp9qsiv/Ceb7edOD73M/FVaoesGrO9VsKY9PcR/l8+UV3QqrDWB58Pqo6KylUup5zjlPosl6EVEWhONCtquq0zwmNadTfvE6dOgDieq+ezTrG436st+wD23zGNhSJ62GcqpqKx2ne3EldFi5snNhflfXqnazKVm0v9POVK1nfKiWOH/JJLArq65wK0oq5bptS6vlYnuW3BU7RWlDQDACQleVk3frMt2/vkLhG1vWwYs/da0gdFYo1vt9xs1Orp8rc9xFsq3kczfGg3pPqQ0wyZZnX19r2hb4fUtaG6tJmn2W57qJFyQPN9uVWz7dBFNalckAkFYjq3Rm6H30/5G3LOGrRwo2HFi1KrhDkebRN5/Ni3aGikHVOaUlT3yWl9DtBM5ezrfYiOix1cVyunKvr2paox2utWv5nMhWv7DPoL8nFGKnnkp04bmg8GFoNFKpPoZVhmRS0rA9sI/n8mDNCVx3pdYcUq6qMZXugylf9XcDrDa0EUwU6xxjsC9Vvnqg3cazA97/X2A5yLHvAKZNr13a5IebMcffJLpxdPc8X/x7ycZw24E5LgHDCEWoLNU+FrmxhGWqbrHVP+/ut/rwfve1+wzHGuK1xjUvAkstkFVS8Xum3Lar7//jG89w1AIBqv3cvc106H0T+fs5fvz5x/epvrCtlqPbW1QAnfb4cIyOmfDUMwzAMwzAMwzAMwzAMwygDjivl6zfMjgCkzyyrwlW9ZDhrQXWJzhiqSoezMaGMfES9b1Izcl4Bq5nxTnvvPQDALJ/Zl15Vp/iZYVXsElWbVJzvPLUWyWwTZ2EqSsbk4qJer1TAUixHIQU2Fz7Lc1Wh7x773HnnnQCAWT6L7rnneq+q8n4ulDOnqazAvH9n1rtrV2sAQBS558uZWMZhzZrb/P5upnTNGrdVxafOImZSWmh8ZFLacjaSCmkqShivjBtVAoSUJOqlHPJ+VSVspvshofsLESsHcgEAdeu6Wcnly79M3J8qX1PTpsx0WeDKqVq1iQCAffu6JY4f2iqsz/SzZDvBWdz4fmv4rYub009PqsVUMYSq7nzZh/BM4zlSKhDO2nuRAiOSWwoBv+ABaIBFNYlkXo4ls2wd3MXos1KFHNtq1hFVy/B9VWGnJLhVchPvfve7jAmV5Dpl4axZrm1XdcfGjRsT563nPSND6iytA6p0JRqz+rm22XqeUCbskAIxVDfYd1FZyBhUNYp+X1dd8PlQqcw6pJmP1UeaykZehypeGZ88flNvnVrTZ5+decEFAIDPH30Uh8UBL0md7XuvbF9XWS9SClZfftf4z3/mNudd6rasF2v+z//nX35Lv/YCrjZxNzB9urvvb3+b0lpXoR55xL2OM2S7tpjlzefEtpr0798fALB1q9OGvPXWW4XertKsmVM3UvmcyedSfSRDqxS0XlMBoio57qdexjx+aHWFKl4ZV1SeqKez1hPNtqyKG97//Pmu3eIYsXNnth9Uc7m+4qOPchLXoWo27bu0b8zk+Rxn1C46vKe4rfQdGPsFWrSyDWfT9mpydYI+I62bmvWeW95bq1aUAroTbd/ufMZVDa8e53xfVVWEdYDPnM+Ux2fZqapZPeyJtqnahoe8aTONt0ioTdXfD3U++SRxfTz/1q2uDalTh6tVfFuUEkVX9fsnx2mqvg4RUkyGvO21DUobh3i0z+7ZkxJR14b74TU+8Ofr3B6lS4G/rwO+vDiOY/yXd9fVti3baPqBa3p63m+b5Nv8OcWmgasoOBbyH3z99dl+655/qG0NjRGKqoAloXEzv8/nV7NmzcR+HPeznusqA1XA8rlecfe33Qn4/BgOHAvSPz1vBgDgvfeoRHWExkwalxw7aF+onsIaj0HvXD5WDlX3tfXH+RAAcMaHbouLmPOjihzPH4BDtp2MIwYCA+7EQ9t+jVXtd7UtYH/Jv6loW6N/y8n2Xqwcl2sbleI82absyClTz3WbNn9NvIRXvrIOkND4O9TWV+/bFwBwuX89ceRIAEBPU8AaAUz5ahiGYRiGYRiGYRiGYRiGUQYcV8rXKOqQeM2ZuNBMoM6+qK8W0WyPnF3R90MqkdDMul4XZ4Woqsh68013fd6fUL08qeZQdVKmWRmdsS8t6GOyjjOyJ/isTkqNVt6bRTHjO2dMF/jtDj8j6pUhfM6cSc7N9Rnmc3z89vNKAD9R29iJkfDxR+6AOiNOFQzjN+S/GPKACsUFZ5CZaZr+f8wozvugyk2VGZoZWtVyup/Wx0y+diHlK1FlwLY2TqFAa69d3r9n40ZX3mefnbyfffK8rrjC+wNV9MohToYeoNShZmL/lJrUE1LyqOJhsi+PayUTfKy8TfpaNm7s1HOffJJUiabgbO+scH3s35/Gan6Wfpb3qvQKwyVsWin+8LFZLif52ifnBsb57Rs853rZ0ZVBkyYupletapW4Hl21oN6jnTq5e5w0yfmSaZmivJdbUJSSUixSHeRXSdDjtorz97qkNy93uz++e8j0iKWKis+yfv36iesKKXkzeaOG+gY+S1Wd8X7ZB6k/MV+HlK8klTXWq8Wo4sjk7amqMNaVyJdHJf+9VA2Y7dLHUknImKaqnuoVnpfnYR2i/xz7xjr+8VXzqr1zfXj1vO02HA4TJzoFdM+evnIvqZbcYaf4o9d0n1f0itd7/dv0IvtZyj/Ob1fxi0728/bb7n537HAB+vjjyeOfcYYrSfWZp6KY5cj31RePSuZM9Ozp/KvZxjMeQxnndczD/Zs0cde5alXSU1XjRsdGmRQkjGutL6p0UQWsqjRDilOiClnGNctbvV3ffJN9mPt+5cpOzaa+hvy+eiDzOjmWUO/j01q7VTJUUvPqh5VgbJW2gqOK8zxPmRdqdna2mb6NrF7d5VTYurV14l5YJ7W/I+k+xBwguRNdcIHrA6ZNc22Qxpi2dZnGNSw7tmUcv9C7nvuxTd/Q3HnYtvYqcVVZMXZU2Zdp5U5ICcvXu/yzreGVrSFFryqWdcXehg2bAAANGrDV8Z2272t1pV6obui4IZPyOP6+y1Ghyki+1r6C3+vYkQHmfBlRJalE7Mxy6BBQKJYY37Zvlradl5Maz1EC7mVyOf46dvJzGndP9Rvf2M90Hr2poc4+tulJx/ycHOdTuXGji4NMbZjGDz8PtYWZ4k/HKJrTRD+nYlzb4q+6uZVe2TNmAAAuusiNpVJKX6oM1/ntEtm+2hUA0KXLZADAhx/WSFwPUb9rblnPGaccK7IdIKqoj5WqfrXJPv9cF/rnR19QX50uvtj1acuXu+c8xX98oW/rU+1fTlMkcWOfKOqOE53Q31D0bxTapurKKO1LNMZ1FTOfuarIUxHA32qsgrP89twJbstF0/zd4vO0rJ7pliqV88pXHe+EftuqxyvXmrCFTa7RNox0TPlqGIZhGIZhGIZhGIZhGIZRBhxXyleF6gKdsdbZFp2pVp8+zbBHVYNm76QSgMfjDJtmYVT1BfdTdYYqEXVWhbNDodkYojOfqvQNKRZKSu4JrnglKd+1A4vdtqGfMT1XdqTaaZ+LG84gN23qvaRadHXbH/n9KM2k1ZT3CdS44nNXRYKq5EjI25XoDDjjg9ebk+NkjlSrUY3GeORrzcQdis+QAlZnuDWDOd+n4oZwFpT1U5W3Kb2NFzSsbOhmsKuscRkuFy50M9uffvpF4r5ib2U/fbrPK3nWUwHhpvh37Wrnt05hoz5EVBSEyoWvr/TfY/nrrG8qm2rKz9RJl1q3dqrMl15aliiXlKLjEHDVwHveb/rSS52CC3v9OWb7HcUf8GuKbJioeLzfvkG1hyubhQtrAwDatKEijk/DyXLPOcepdpYudaoHPnOdSb/ooi3+e+66evRwJ/7nP12Z33ILM3j73ZiVfhWf1Tq/9XPQB/yOO/19Zvs56td87V8AACAASURBVHOc2qtHr2sBAE8//AyA9GzorBOMNa1zqvYJqVVIyPcvk8+g9j2ZlISaRZ7K15CPuKJK2wVe8eo1TMjyxbrXpwY+VWJ/YWOXLZ4KAAoTegQ8ZD8Xf/K9XlVDTd3Hzz4LAGhZ6NUWnVht4y98h1dHHeCZfHxU9PJAfwP7fFi+6KxSsZwHZL2hCijPqaUmTXL3s22bu3O2nYwHeq7y+agHrqp4+Nz0+bNNvOEGtyxj3DhKO5B4v6FvCzmm0fjT+A0pXmPZ5GeFXk/ouCF1lo6JtI/S61I1H+OF9TPkG6rtDeNO1aKqrGE8q2cx+w7Gra6iUDWi+nHycypmKixw6tDdW6luLD6MMSpBU2m7qXjluIPqIMp0qOA74DrOOnVcUC9a5Bp/9e9VZVlIdU9mz3bqbJaZruTh+yGPxpAqm2XNLO68bypeeb2VvSqfvn4s+9DqBfXn1bqQ7hGPxHG2t3UekizuT3yMcHwQ8mbVNkD7gkWLGHtrAQDt2u3y522W+D5h+XKlz+LcXABxF19tsxuAMra1jhHNcq/jOf6+YLnEv0+8tLAFV4ahcBYG3i8xfkC9sGfy+HN1Pz/IaSO+37N9G3fAxcuKFa7Xif2p3Tisdm02+qxAHJRw7OM6j7PP5tjESUE3b+6YuApts2rU+MR/4uKX404dU2Ty7A21uboaRsftjJdUrorJkxOv0cb1mee1S5weS9g1sLPnuNR3rTNnVkoeR9Bxf1pbKcrw0JhM+5bPPrs4cX9ff+2OX7mZ79M4qJntspSceaZrg9v7PACM7+bNG7n9Lub+e/35korXxf56Wp6Av5NZFvq3ldB4V3MG6P76W5axqStmGKuMCbY1S/156r3qttWotqaoXSSo2/1+c171//HjfF1xw7rOGCPa7/M3ILN08PTdT8Bnb5Qupnw1DMMwDMMwDMMwDMMwDMMoA45r5euwYcMAAC+++CKAdB87VbjGGYULz3jN2Q+doVf/ElWlqApFM/LqzLD6/OlMd8gbM6ScDalJOCszdOhQGMWH5ZeawmV40WOTM+Xr/NZnDW7alPNfXvtwlX9Jf0qKrKiYXZVUXISyjXKrXkckFBdEZ8QZj4xPqv2oJOGWihHOYlJZwvrAWUJVy4U8mtRrjMflcTjLyfdTChav0GC9Up+hU1a5Al3t77eKv1+tzyF/zUWL3HlbtXLPb/duakScdIgqKyoDOPvJ58WtqjlDz0Fne/n+hg3udYMGXjFRz0sKajq15k03dfD37d7+wMdRZ2SGz3j5cqdUbdbMq7rfzXXbKv5cVHdTvsPYZ7L2lGzKqTzatGFMekUtp5wrUvXiDtiihVOlzJrlykoVaBO8RdP3v+8krS+95Mrg669d2Tz/vCv73r39da9y1/HKK04NpJ6NjI3+/b1Edr3PfiqZowcOdGqO++93sc2Yp1enzryr4k9V3KG+R/0Diaqu9Hia/Vz7LJ6PdYgqK9YVnl/VMooqFBi756115XugkVd/eBUTW7qLfQZl1vGrfV1529f97/r7VSWi1kl+Ps/7y7Gu7fbnP1yuvfZa/78P3Ka8z0xck4pXv6VPJq2Sfdy/sST5OqUEn+rihp6yO713LOsb71dXyfB5se4zfkN+jIyLWMXjng/L/Yorrki8T8Vr7dq1E9ehim1VP6Vn2qacycnIoqhR4jyqIiShTO+qdNU2MqTA1VU9Wq+0HLUehVaFqJqPz4f1h8dle8WxAeOX96EZuXWsqcrzRX5bS8ZsJYF+1Q0aNHBv0NuyIKniTilf+Uj3sSyyE9uQWknvQVfqqMQxpP5VtXGo7VEFX6hfpfKVz0IVsGzL1V+cbQyPy7rE6+b+qf65lfMvZ5fYYNmyxPe4oCnbjw/zL3GdaHW/n5af3p+qwnQFG+9n3rzqieNoVnq2PVyFwBzsfDpn+uMzhrm//s7QuqHPm+XE1/XqOY9atPFtKcfLMxOXixn+eruWskrs0UfdMoXhw/3qnIu5usHv0N7HOdVxqthMKcHdB7r6IOxxzAomxvkpkl6++tzT648ruBo1PvWvnTp+584uieOEMrCHFKGq8tPM87xf1os9l7sc7llvvOEOVC95t7MoAJ/st1x88a4rpxkznPL84MFkfVUFrK5k5aoj1ituVYGuv4+1L1L/UJbz7n+7+Kh+l48Pn9Ojbt35AIBFi1w72qqVX/bSwg+K/c/BKGLgJGl5aaFvnxAMHz4cADB+vBv4qBd9yKNd0d92mu8m3bfXoW1Ra69OprZ8p28j2Y9+2s7Js1m1q/lxZRWpg2xj+RuP16XKV8Ycj8/fgH1N6WoUk+P6j6+GYRiGYRiGYRiGYRiGYRilwZYt2fj1rztk3K9du0lFPuYJ8cdXzkKE1AYhJaEqWnUmTmfa+T3N3Mz95tZyyjTOxqhHpao21PNK1Vrqkcnz7OziZj5z/XVyVifvH/8AEM8g/uhHNBk1SgKVEinTND/xWfEit01lKKbv5FSvLdjnnwhVhFTIJsVDqYyLlASUK+dmoEPeRoyjTCqjkEKknChB+X5qltDPdPP4zIxNRQnVgPz+Z+JdSgUEr+tz733GOcHtH3yQOK76Y/J6mjRxnlf02lJvVM42hjLDq3KEihEeR73JVKm+Y0dSeavKk5DfkZ5XFSSZPLq0HFJSkTyv1swpfKa9czFmXbd6T0Gqo1asOMNf88bEfi1aeEeaHT6zK1XbFAPXc20dDvgtxR+c6GadWOe366mAdW3Trl3uGX4pikjObE+a5MrgjDOS6h4+gzfecNcbz0xXTRyPz5hl+fzz7r579/bSxfWU47gLfeyxrd+8vLS2mLEdUvCFMhKH1OYaK2yzQyovXk/nznzWSRnbqlXO9y+UQVmvk6gKJ6Rc+Mh7vrIpo2i/q1eXqVKRx+kuil1eh/Z5qoRUFdedd96J0sWrskKiJRU3eYuwVBZdKmALVgAAxo1zGsb8fNcm8r7on60+2NxqOWtbod5nWr7aNjJO2ZZT/UcVEQnFQ+g5rFlDxbdTvKrKSL1edfWOPueQP72O2bRNDK0a0u+xnLSc1V+T5c6xWkjpQkWMervy+VAZzzGo9kX6msdtsMjFDftW+raWhNtuuw0AMMOre1IrJnJkR7bR7E6Yhb4gJfkDkB4LmiOBpKucmGOAqwYaJo6nCtdQ7oNM+6lik9fJFTuMeV2po56SWmfo6a4etzW9ur/ufKeMy7rwwkLLic8UFyYVsuy7uJ96WapnK69Ts9Drihk+F16H+mfX8uOuz/332SYR7scY1L6TqAdnq1Y7/Sc1k9sc/yOVnQVlaXnsu9z156JsYD0YPnyie2OH937t7Xfgqh4+GA7zaeFKRewqN+5v1IhScXYO/gA5ZyVPzJ+PBew8eOA9id0y5ezYtcv9wKhRY0tiv127Lk3sp89H20jtMzS+NG41V0FqXO3zBLCNlttJ/z0z261KmjBhpT+PC4SCb38bQKzApkK8yvTpAOLfE6yPqjzn9bAeMc75er9XOTI9wdmfuN8RjNvFfgzDoewX6/1zHevfGOYVsFWch2urVjP8B967mGHOOFHa+nZ0wYmvgmSbpCt39LdYyIOdbbi2fdrG6Pl03MLvs//WFWpnLHEDtRoyntcVayFfb/09obF3++23hwvJOIHIQvpKhsPjhPjjq2EYhmEYhmEYhmEYhmEYxuGRhTg9aulwQvzxlQrPl19+GUBYpaR+c6rKCPmgqbpCFYM8fu15bkos62zne7jBX1+Oz7auM+2creHsiirqQkqAenPmAAAadurkXrMgfvhDAMDap58OlJRRHOIZdKdu4sR3c/85la9LOCGyjzPefmpYk3pySpaqqVXb8c0ddUacZPJpVGWKZjzXeOasotYD9Qrm5/Sxo6IklZFc/HFUKVLho48AAF9yltHPGm72WXbpNaVZS5cvPy9xfta3ja1bAwByfPxz/9ZdnMIkFgPyObgp+ffeS85asp7x/OopxfPqzLrWR30uvE6tr6Rly3UAYi8p/b62V7NmuZn4nTudMqBHjx5+z1yUFLaV073agGoe9XFbtMiVWatWPvZ/JApYZtCmCoKxTbHHEvl86ToAwIQJruzLlUv6Aat/r6r/iSredMY6pNbieV591bXF113nFK8PPujype7fn+wjeFzNUB1Sm6jCTese1Vd5ee68tfwqCX5vrfc05f3xvN27axdN9Y07zsKFTn2zbds2AOkz+VRzU22u96PlR1Qlc6VvE6b6VR/0dA15hKoqX71ueZ1ULqi3Jj+n0rDUqeLVWWwr9sjAarb3C5xXLbmfD+zXX3flz7Zyn2/71Y+arwkVHFoO6htNQvWC5aKKV67K4XVt2OBGIWy7+XlIbR9aPcHr0LGJXleo7STq+82+gKo7etPq6iKNU1Vqa73n96mECa06UAUMr1tXSeiqKC1v9fvm/tr+qCcttzzvkCFDcLhs2uQ9NxmyVGpR8UcFF9vydX77LkeSTrGmykpVMRE+o1atOOJ1Mb9ypWubtM3kcZo1c8qztWvPTRxXY0pjkbF/wQXsbFyZTpu2J7EfFZ7s46hs5bhFx9vql81nz7abbTQVtWyZq57nxisHveKV1/uBD5kqfryiMRFSj7MO8Xq1DWSbwq1mAOf+Gos6DtQ2OeSNT3Q8Fkunib/Onb6urcqSz6f6rUuCkFvGPonPPuv9GH/s3+CqUS56oSLXW5mmxi68rXq+7S/vtxzz8PvsMijh5HKQJf6DPLb9STNZbav0ecS4erh792WJd0N9AmE86MpOwvhTP07NKaFjKLbRbE9mUfjMsd5sN1acONEVxM6dTkHOOGzid2Mrk0ojsNMdiH0W22xV7DL+GN/6O4SlcKZX6mqbzWavlm/38r0f+sKF7ndCmzYcxKaWd7kNVwbwee/j7zY3hlvhy6npSeT7OXDgQADp+Xa0v+ZrHV/qChT97bpfvFsZw7pKUVcGEV39HPIPT6m5Bf2NrDkXQt8zTlTKIf7tVTqcEH98NQzDMAzDMAzDMAzDMAzDODxOQfpk4+FxQv3xlX5ZOnPH2Qui6g2d4QtlpuUsjSpfNQMx5zk7eK+txT7baORnxjmrouoJVY+ElIk6k1nLn6emn4nc41VOf/3rXwEAP/7xj2GUnMcffwcAMKy3U//Nf8h/wLrICf2U0aWfQucM6fpayf1pIeUjZeZMFw/t2jnfyXnzaifOr2q/kC+fKlL4ulMnTlG7WchFi+oCiGeYGedUWqjPHV+rmoizjpwRD2VqV1891hPWV9YHqvNCSvXqs13WVMZ/ly6+XDmVvp5SBueV+t577jrVW1k9dDXbq2a+5Gtej/pVcsv9L7iAcUDTMzdTP3u2U59RSaPtEMuNs77cj7PMpcny5csBpHsWqtdiSi9wjdv0drZaKZuvJRTlMJOx3rp/PXmyU5ieemrSlzvkX6aqIM3+zmeg/neqjFP1BGP9rbfc8bdscRdKf2deB8+jmZxV6RlSAKpKi4pXZiTf6dUevB76DPLZs6698oprC6jeqlSJmchPT1w3z6NZY1Vhx1jnlnWAdTOUZZ50F8/aEFp32YZQ4ad9pj5X7t+3b99DnqekRL6TnjzZNd7f/e7F/hPKl5yc6c0nkqtoWI67d3+eOB7bLpYj9+N9qaJX22zGS0j5StQjWT3XWN7p9ThJ2GcaidehvofwPHxeG7zvXt4jjyTul+VC1WBubi6AOA7pRc0+QZXjmVSYWk6qVMk0tlJVn2YEZzlrn8HrCSl91ZuX8DnyfbYHpUHfvue7/yS7n7jR5goR9W5MLdUpXK2kHuaq1Pzgg6S/ceyZn+SSSxhDl/j9nHQuNP7WZ8++Kr4Bd94rrjgg77vtwoW1E99jzFKFrupjPmvux7aXscm2/Kxp0wAAe6+4wn1PvPTLzZqVKB9V7mlsaZ/I6+L3NAa5ZYyFsr/zeOwT1H9ccwCoglZX/rEuz5xJKeB+/z1XLrt2fQgAuPnmm5HkKhxJ+vTpAwDo23eue2O0l75Sucpxe1KYGlcDvl9R3if8GaaLM7g/FbMHqKhMtjWKKmG3bbsksX9I6RrKNB/qe1TxzbjQNpff58o31sOPPnDl2fE3vjy9D/pbb60DAHzxRTKnypYtzrt256hRAIAL7rgDQFxsXLVDtE1Wj2ZdjcHtp/77lUXdmKqPXuH6ZRsnfa3mfzcs9r97Jk1yyv09e94HAPTt+63EdVHhHEW1Em+fTIpXhW0oV3awjdKyz9S2q4832z71WGfbw/1V/RxCPeG1LdPfCzo+4Pvdu7v7e+EFd1z7G8vJgnm+GoZhGIZhGIZhGIZhGIZhlAFmO3BIhg4dCgAYO3Zs4v1m110HILa8ogXW3necolFnRTjj17atm+pavDgXQLqKQWck+fkOf9z8yy93r/35qognZihzdsijR9UqFJlV8xPQWS3cNvf73wcAbHv8cRiHD+MqJ2c8AOCGG7zra05Lt03ZBbJyUlrin/xYzpi4WcLZs53KJ84y67YTJ7p44EywqqIUjbsePSr5Tw7Ilm5Hbga7VSunNJk/33kbcbbyggv2JL43ZYq7Mc7+XXQR55b3J/ajedacOW4qWZWiqnLTmXXOnmqmy1B2Vm5fftllM/3yS1ej6fGm6jPWJ/VcprqQ16GZt1WRqrOzPK7Wy1iK6+LhH/9w17do0ToAwODBg3E4TGYm+cOYcaef8ZgxYwDESjT1JkyZuf7LqTieX+nf5i2+67f/8luGEGUNec4HjGWtqg+NCVXiqQJNPZ5U9ZFJEafPil6YXMWgM+gpH2LvD9bce2iqd5T6/XLGnuovxlCNGjUAxGoOqqm4/7333gsAeOKJJwDESjq9LlVJ87zqMarqEcY21eqq8OX3+TqUvVbVaOrXqMoBVWVpHeP3eJ9Ulx0p/vWvpE8c70/bEF4f74+qOKrqtM1WL2CWJ8sjpPBk+evqHcaZjlXU347PkUrTr7p0ARD74lGLVdmrgVTlGPIlbNnSe+H6Tm/1ance+oxuePBBAMCdw4fjULz66qsAgEaNGiXujwpYljvbchIaC2l8avyFlLxEveq4ZTmrL7iqybS+ZPIt5fPnahOq9EqDKGoLAMjiShuuSljnt939VpV8ouxgG6He7pnQFWPpVPZbFzsdO7px9ltvVUx8X58Fy5bPZNmyuonratWK10czW1c327RxbcncuU6BxzafW64wIdo28VmzjvN8fHY54jGpqy9U+crzse3WNkTHTYxN9s06blHPVvWc1xhUv2nGIp836yD94Y93/vEPN2ipXt2tLrnmmgv9J/xl5sfrVeonXmKfj4t9vrWcmpv8WnJYH4992HUdWOf/486/YoX7Baqq/FBbpGMLHYfq2EgVrKFVLBofWq91DMXj6Aqx/+s/HwCw9wZ6KJ9S6P6qZJ3r1YLqPcv74VhMc6KoT6j2AeXffjtxvpBP+ftesV7OK9ZXLnWrsnRc3rfvRPefAu8pu6cljCT0KH/uuecAxG2SElLAamxrrOj+bPvVo11R/2JudWURYQzq+C3d59y10ZUr7/PbyjBOBsrBbAcMwzAMwzAMwzAMwzAMwzBKHbMdKBKpGen+/QEATb0nKv9wXc97bq4R9Y5m7Fu2zOVnDKmn1ING1VoUHDScPz9xHO6v2Uh1hk7Pp56epy5bBgDY29wpMbO9OCrl3FW+dIPlZOf6668HAPzrX061U7Wqm0m/7LImgW+4KfCpU52SgDO427cnZ/c0266qzYh6Paly+s033Yw647B7dypemb0zNaUPALjwwnX+NffL9Vt3nVddRXNaXoc/TnnnfZsS+vqZ4erVnbKESlYqO3SGXesPVVrqPaa+harG4udUD/Jz9ahiObJ81ftNfTF1FjbkL6TqRioaomgYkjRFaXI4ildlwIABhb5PZdq4cesAADf8LNd9wFChb5r3+8LSdf4/3DoZyIcfOnVSuXJJNbOqcYjGBlEvU1UlhbY6E68KVcYAfcg4t8nQbsr/eDHV3gYNAMQJfquuWJG4Hs7E0+eMKg7GJGNQZ9pDnrfqn6iqKq0rofJVFZZmumYss+5qn6iqM1UU6PNSfzlVf6knLsuNqquy8npVunfvfsjPn3/+eQBxned1a3nwtSqAVdHK/dk2spy0rVP1k2ZK18/Z9rB8a9d2PpeRvz8+HRWmU7eh8RdSjqf6iPJOJdakyWQAwPjxXySuPxPX+dVIEyc6dVFDryynuo9jOFX/sZy1j9T6pKsolJBPoqqrVPmiPqfqFadjNVUxqiKXfVdZEPnxYFbWDPefPD8ynO0b7xyv9GN2enBZg2trdu1Klo36b/NZadkTXeUQxxJjzUUjFa8hT3WiMaAq/YUL3bNu08ZHd0V/Pftcp7Vnz9LE8ah8pV8zUc9VVRBy/MA6rCvhMsWces5yqyuCuGU566oUtpmqfNXxC/dTJSXbXvZRw4efAwCIohND8UpuueWWxGsOn7KyuAbSD2r8OBYFLv5fftl9Hsf//wEAbrihjv+erjBLrhiLn6NrZdmm6WoHouNcXe2gqzBYX3RVBbeq5te2Wdv2+vXX+v/xd4JrD7Zv75w4D+NQM9ozznhfXOXD/VlfeP28Ts3RwjaWCvHQaijtA7WP1s95/pTC1R+nKwoninoGPjEUrtz4+9//DiB+9myjQyuodFzKZ8XPdaUJ0d9qurJE+39+X3MKpPkCZxgHsG5897supseMKdzX3DjRMOWrYRiGYRiGYRiGYRiGYRhG6VMOwOkZ9yoWJ+QfX2+//XYAwON+lmWsn335jlfCrvP7fXbppQCA7BkzAIQ9KomqUjRDtM6itPDKVFUXcXZGZywzqWZUhcHzrPz4Y3eBF1wAAMh/6y332vuwGaULVTsxk/22SuLdl15yyo79+50yg/FCpQZhfHCWTjNYk0yZ4fl+164i16vn1X+0jSzgzHZ9ue6KshX/nvK5bnue7Dbb/YdxTUUJZ/qprCDqVcXZUVUT8bUqWDXTN9/neViOVKhwP87As74ta9IkcfeEc5lnvPkmgFiZwoz0Db2f4Y2Uk0mW3AXeT5WlnHscZkNNi/EbvP/VKq8UnM1gchrQmTOpCKNS7wy/TSr7WAdU3RFSRRNVeaj3oyoLiao7eD5VqPFZ1ZRtyijciYKQ7b1uO6xz2wVNnao58qsbtm/fDiBWqqoqTO+PnlHqA8c+bPTo0QDSvV3p5amKVy0XVdeQkOpGFYFEPSxDfoaqxFRVmKrgWac2btwIIPYiPlZQBaZmGmefzjaGPnd8HiG1DvcPlZ+2/aHsvDw/r48Ka7Z9p/qxgSo6VBmt/n461uB25UoXh+eeu8BfmbufggLnUx7yfAvRs6dTFz377LMAgBYtnHE945vqJ/aRWo9Cq0P0fkIK11D9ULVZyJNOny/R+qj1oiy8XkNEUddC358wYQKA+F7iGHatobYtfAYsk8suc/cyf75rwzRmNas6y2KuTz7focMqAOnj35Dqm+dlP882UVX4c+a4/Tp1Yh+yI3EdrDPcn3WF4xYdh8crWpJ1mHVd67DGppaL3i+9Vrk/VWN6X6oIVLU7y5sKRPZB3P/uu+/GoTjGmt4yJ4rcWCYr6wP/jouLF15wavQKFZLjS/Lqq+5z9f7n88zPTz53/Z3HeqUrLfm59gH6u1RVe1pfdAWltoGhtjAeBSUVXqE2le2FejIz/rSesb6E/NBV+cr6zfE3j0uF609+8hMYxxb9/d9YRo0aBSAej7Tw7+94/XUAcaxk8vXW3wGhlV76G1j7d/YdOt5RVbiOb3UFV4z7IRDKx2KcYJS+8PXE/OOrYRiGYRiGYRiGYRiGYRhGsSh9y9cT+4+vw4Y578VHH30UADDRZ5Cu5bPXf+H93L7w6hudgdRZEVVXcRZFfU2IZk3VTLf8XLNU6vlC6oy0jNI+6+pBrwxQzyyjbJgwgZ5bLmtvrCBx6p2Q/5wqJhgPfP6qrNasoDqLd9FFfN7nJC+QUs4DVCvuTXzw1ltOGdGtG+OMrQynerw29ICf/dvj43wdTzAVALBvX07ieqtWdTPprBdUrKhnVaZM9Torqr4+nF2lio71S49TvV07AECuv73mfrvXK1bph/iJby9u69YNhbGYmbz7+Teu9Ft/nLYs77uPP8WrMmnSJADAuHGuzM880zlZxwo/Kjvds9E2h+oHPmvNOhrKjK2KMVVd6My2Klx1BjuU+ZmxMveZZwAA9W+9FUDsktx0s/8PpbAik6bbWwVRN7FN1vOHrkOVc0QzTv/pT39KHIcqKVXLq8I2lM09pBDMrJJxqDKQdZuqFT5/3VLNohmGjxWoOA7557HP5/Pbts0pP1kObPsY76qU1O9rHx/KaM3zs9z5PSqodVWFtrFEz7upjVslcc7y5YWWR7oC1tX//Hx3v/PmORVjSZXL9Ph9wo/RzjvPLa9gfFMdSNWTereFvJSJ1q/Q5yFFfkihrMcLtVN8nvR4vfbaawsrhiOKquhDyjQd18YqIPf5hRfuBADMn5/s//lMQjkR5sxhmSb7dc1Uzb5C/ZJ1RRm33O+dd5IrzQ4eLFxZpyuOGHO8f8acZoXXPkpRD1f1hOVKHMa2rm4Iqa85jqKilVvWvays5PguinILvb6THWZof+UV9xzYhp52mlO1qd+kxq8qjfnc9Pectil8fjwO40PbMP0dqvC4l1zi2sDZs5OKbR176FgrPW73JV5t3Ng+sV/IM1Z/p/A145ZttCq1Q6pBXX1xul+F9ZUfo2k9JJN9fWPr1PM4XHF2onCHz6GQop/7scRntMk/y6p+vM0epvK77wIIe6/qyjddHaExpf24/l4I/Z7QFVo8zttvu5V+cW6HLw5dEMaJgSlfDcMwDMMwDMMwDMMwDMMwyoByiG0WS4mT4o+vw6lUI0OGHHL/xx57DEA8E6lenepRyRk99SlR1Yn6l4R88tTLh+hx9fyqOuLWKFs4w0vlCL3DOHOtfnE6o66qOJ3ZVZVgaDt3rnv+HTqsT15g6nhUG+hy6wAAIABJREFURDilxcyZyet8991kdtz//MftF0Wb/HWsSpxPfTgZb4x31hetF9xPZ8L5vnpBqXJYlcLqvUalChUlymZfHB+98kpiv2oDBwLIrN5qeRLNqFNNpJl0VV2hz4qv1fNT/fNYF7RN1ZnoUFZzbWNDnqSq9NOs5bVq1QIA1PQemZGP3SnNmwMAznPi7pQAdp3fVlu5MnF8HmfnTqcGoxqb52Gsqu9fuqdU4fA89JZlnalTx2VgZjmqAkBVNPo8NRutKg9UYaB9DdsMbulpOSRDX3us8dRTTwGI45IKVpYb74v3zUzp/JwqNMaf+jdqPGtfr+oiop5kofrI+sp4o5+lKj1VlUfF65JmzQAAzZcuTeynylFed8jHvKQM9auS/vKXvwCI6xPLi4pp3ifLjc+pZk1XQ3nf2l7o/aiaLaR4CSnUVZkcal/YDvTq1avIZVFW/POf/wQA1K5dG0C8ciSkJlIFLNuYDz6goi+pEA0p+IiujuDxtaxD42Dup20V+xrGhmbODvkAss0ivF6O43h+rVs6bg+pszhu0f0Ys3r9jBWeTz/n9fJ17Dk6w93AxV0BANGsUpbqnCAwIzufL9vwkGKT8c7nqKsSdHUD0bGRrk7RPpRtG+NTffJ13B23RUmvWM0Jovvr5/FYgWMQF+8cF3PMoj6boTEa39fxunoTc6tKWG5Tit/p0wEA2X5MpTkkSPeTaFx+vJL2jAYMAAA8+OCDAIAqq1cDiPtvxh7roP6+0C1jhnVXf3uriju02jj0m5x1lePAtL8tGUeduXPn4qKLLsKLL76IG264IfHZZ599hi5duqReb9q0CX369MEDDzxw6IMW1XagGE3QSfHHV8MwDMMwDMMwDMMwDMMwTgwOHjyI++67D90CloGVK1fGggULUq/btWuHH/zgB5kPXFTbgc8z70Lsj6+FkEn5NsPP9K3zGXo5O8MtvZx0ppCv1btSZ/5CWTRVzcTX6j3EGcuRI0cW4W6Nw4XPT33+VGWmilZ+rr6MfN5UPnAmnvET8gHkeRcsSMZVVtYp/nvO0+rLL0+Tz5Mz7aquYjxyxplxx/Op+oqf87pVpRWqB7wPXhc/Z31i+fB6NIssy5/va9bVbWPHJq/P+zTy/rd4r1cjhjO9VInwGbNsGYPa5mlsqP81Z6DZdtFvjTPcIcUdCSnQQlnHifoEUvVFxZwq+HJXrAAA7PXHpXY8pLxV71TNyPuHP/wBQFwu2nfQa1S9Xu+///7Ea21TVAHL57Js2TIAwECv6s5EVtZkAMCzz+5OvK+qFT7PO++8s0jHPV5gOdIHU1WBjE/1Mmb9IJ07O2Xyxx+7uOLzUK9XjR9VE6nilagfJJUY9BRlPeT1a9sa8k5rtmRJ4nUoC7Bed8iXXnn44YcBxPHONpv3wQztPH+fPn2KdFyFq5eoamO5s35rPQ31XaraUtWbblU1eqv3tDuW4DVSXRTyNQ75U+s4lLHGOsH+mfD7Oh7STNUdOvCXizvO7NnJPkdXfnXqRI9K96xmzaIPuTsulYRUo4fqIOF96fhE+zZV7rHNCCkded3qpcs+Usc1PJ76G6sSmXWI35840d3v974H4xCw/Nj28Lnqc+FzYFug41DCONI2lfGgnqeqiGY86u84XUWiqj8yaZJrw/buTcZtSPmqqyviviXp+Zqfnxyjsbx4vbo6Rn+PhH6n6P1rG8s41wz1+nvBOHHI9LcKKmPZn3NcwzZQ+/XQShXtn1kndeWX7se2gH9b6d+/f3FuzzhCjBo1Ctdffz3mzp2bcd+VK1di+/btCSVskKLaDtgfXw3DMAzDMAzDMAzDMAzDONHYvHkzJkyYgOnTpxfpj6/PP/88evXqVTThwCmwhFtlyTr/EHKd6AVfOosZ5PnP6ffXwW+7BlQZTz/9NACgbt26AOIZQ52d0RlDzdjHmUDOgKovHPfn55zhHzRoUJHu1ygd+LxU0aFbzvRqZVefGj5fxgtnntULjYQywuuMvs4YhzI0M854XM4ucr8NGzYAiL3JOBNO9WIoS3HIV5LH7dhxh78yd7zly5OZ3LXceFxVaWl5xx62/yl0f1UmGDEsS840q/+cZrVXlRSfAWODZawZePXZhVQbmTJLE/2++pSxTeZ9qS+hElL6qXJOy0XROqL+aLyu8ePHA4jVT1TdqJfoTTfddMjrvuSSSw75uRJF3Yu1/4nG7bffDgCYPNkpgFWBqv5/Gl98rjR/uuAC16bNnVstcR710dS+Qz2L1WuMqj6+1jbu7LPPBpCukiI8T8grOVTPVDWlq3VCUNHN8qOXa25uLoC4z2Gfstx70JaUTKuXnnjiCQBxfVQfRta7TMc5HtHxhCpcdTyg/bZ6vBPGvh5PVzvwtXq5A8mVQTwP9+d1derkB+ao57d7Cr1etu1sk7f5lS5UL1H5yzZX/bh1pY6uouD5qJJXr3tdRcHxuvY1et2sI+rpyjqm77MvuM5nhTcOjcZ3KPM5X+v4UMe3hM9DV46pYpr1hivJuB+Py+fJeGS80uedbX1o1cmTTz4JIF7Nw3rA4+vKPNbL2bNdWxh73ibV/qFyC61O0r5T+xTNPK+/h9VDl9x1112Fvm+cOGRlfeD/d57ftgEARFHXxH7sxzmeYH9+1VX0L2Yf4dreqVM/9cdJjtf5+0XHS/yc463jLYfBycRdd92FP/zhD2n9dIgXXngBz/rV6xkpqudrMbA/vhqGYRiGYRiGYRiGYRiGcczyyCOPpCabCgoKcPPNNwNwCY8nT56MU089FT179kz73sKFC/HVV1+hXbt2RTtRUT1fi4H98RXAXipeL/Vv1HebCpvdNpfJ433y9M1uEiT4LNRfb6z3mqQSliom9QYKZd6luoUzr+oByxlUqnaMIwvLX59PaMvnzhloVcNlOo4qRjV7qXqDadZhvlYvMc2ArRkf1dv1jjvuKLQ86OtHRQnvTxWwev0zZrh60bWru65mzZb4I7KmOUXI+vVnJ46r3nEsP94ny1UzX3JWk4px85JKR5+Rqu8Zy6qmUs9EzYqeySdMVVKqniKqmlBUmUi1k6rSte0NeV2GvGgZU/TcHDZsWKHXo3Wd5cHM46oIZl+hPuDqH22ULqFM6SH1TrrnMNuspOexon6WWn82btwIAMjLc+tv2NcwDmbPnl3ocanQ0HoV8kALKV5DfQ73p2IkpAihMkVXd2h95udUe5W1p9rQoUPL9PjHMowhqnkYa7pihG0Q2xptszQ7PGODbX6mNpkxzPMsW9YgcR2aaZqxsmBB/cTrr79OjgNCHpeZFHNjxowBkO4TzPsMLU9Uz09V9HG8w3JLy+YeOJ6u7GF5UR3O16Z4LR4sNx176GoEPv+QD7SuWtEViRoXfP7cX1V3/J2nClUqq3kdmfzbBw8enHjNVQf16jkVIMdAqtzlfWn90RWWuvpDv090jEd0nK4r90J9kY15Th6iqLO807XQ/bQf//vf/+7/R8Vr+cT2yitd3Z80Kfmbj30h+0bLl3N8MGLECIwYMSLt/QEDBuDaa68t9A+vgLMc6N27d9FPVFTP12JQ+OjIMAzDMAzDMAzDMAzDMAzjOKJt27aJ1y+99FLx/vhK24FM/4qBKV8BeIErmtLclRNsK/3n4v3aIeBxE6Jfv36J1/SZCPkNqs8blXkns1rjWIaK49deew1AuveTKjAJny+fN2eSOTPN9zkzHvJA0hn8kFI25ImqnmL8Hj/n+5wVDKn6iCqwmXmaGcE1a6wqSqZMoarSKWcvv5wV0n2P5cbyZHmpUka9ulQ1qArgkDrtZEYzOaufmcZYJgUrY5gKN1WYqtKVz0pVGUQzTIdU4aqAVU/N0P4kpHrifqwb9GVT6APOWOX1shz4msdhnVdFJD/PpH4xDg+NC43fUEbpWK3jlsu8955TLbFtUT9uVflxvx07nFcsFRnaZmdCFebad2RSvIZUS+o7Tj9C5YEHHgAQj3Go6qKiZNSoUQDitpf1gsrx888/P+M9GiWDz+Cdd94BED9jtvXcsp9mP6tKOL5PJRxjjt/ns1W0jc7kka8x2qjREnyT+fPrJj7XPoV1KBMDBgxIvOaKNfXMDNUJ3g/HG1qObOu5VWUr0b5PVybxOtgXGMWDfef7778PIH1criug1JM15JXMvpptLeNfVf7qH87js8+nwpR9AdtGbovLj370IwDAo48+CgBo3Lhx4nNVYOvYh9fP++F1Mq4J45H7t2q1wX/iymXjxhYA4nJgPQn9ruH7PF7IR98wCFfMcOEMVd+DB7dP7Nejh2t7n3jC/VXHvFxPLLiKhSxYsCDxes2aNcU7oNkOGIZhGIZhGIZhGIZhGIZhlAFlYDtgf3wF0DSDkrW+bA+Xvn37Jl5TBaLZXTnzZ9kdjy22ewVCLYkbziBzRpiKBc4UcyZbPZ1CXqWcGeeMd8gbOKRSUlQRotfNLa9Xj0evseLCjNH0/6NCRlWTGve8TyphTznFKcDz81050puNx9MZdM1Ky5lzZrJWf03z+UmH/mEffvghgLjM+My0jENZ0jVTNgkpTFWhqjGiaqNM3pREj6uK1kwKWD0+Y2rLli0AYuUeof8xMxgTvX6qXbjKgSoSvW9TOx0ZqOikb7UqVvla/S75nD74wGXf5XNVv2+28eqdqmo3xg3jlm0claRXXnklAGDq1KkAgO9+97sA4r4jhMa/1rvzzlsLAFi2rElif/WfpEJX0fagoR/DTPTbO4q5esgoO6jE5LhFxys6LtEVM3zN7+t4RZWEOq7QtlbbZM22DtT02yr+upJZ5Fl3OF4pqaqJK9a4aoEKWPX4JKoK53WoHzrbFB3/6eoM7at4HG0LjJLBtotxrX723IZWhGkOBfUF5/PRONBVPPw+6yHPw7HAxRdv9VfcwW+5VpMK8L3+eIX7G5Lhw4cDiNWADRo4j+WQp7GOx7U81IOV4+pY8V7Fb90v57PPXgUAWLOmIYD0XA06tlPFa2iVhWGEoOrbbwyjZJjy1TAMwzAMwzAMwzAMwzAMowyg52spYn98PQYIZY03jk1U8Uo481urllM9qSeaehzxtfpl6ow5lZ1UlqjvX6YsoZn242tVhmoG98PNQE3P4nHjxgGIM79rxnn10lJFCdFyoMqM5UqVmXoqq3rRsqhmhioMqo01NtVjkqiKpKgxqkq8ULZ5op6vejz1rFWlbOg6QtdFdcfWrU6Vwqz099xzDwDg/vvvBxD7HKtikeXF8lSfQPWkpRrN1NlHBvo/0se7Zk2nttO2KqTMpmqQn2vmdKqdVM3D46pPOONb1VKMm6uvvhpArGbi+Xg89fXTeG7RYhkAYNky58u3dGnjxPn0e/TR7N8/x2/X+f1zE+djPF+GJBP9cXqaAvaIkZU1AwAQRV0BxM+Qik7GlHrOhxSWjHXGIF/reIWviSpiGVPaz4d9iam2ptLOXa8q5DZvpkLw8KBHKMctuopD+5ZQtniOq1geLG+2FdxP+0zt8/iaK4qMkkF/draVfJ7qOczxIz9nnOk4UxW02oZrPOg4n8fj9XTpwnpHpXdVv92ceD+KrirWfVMN+NxzzwGIf6/wPkNjtFBca5/I92fOpFJ4GwDgoov2+O838O+78lWFrSqFd+50SVfsd7JhGEcFsx0wDMMwDMMwDMMwDMMwDMMoA06B2Q4YxrEKfR/r1asHIJ7xVm8oVXaGoCJEZ4TVP1BnpHXGOqR6UnXS2rXO549eaTrTX1pQcUCFjSoF9D66dKEK0bV+M2Y4xY6WiyoIuO3Uaaf/fj2/dTPwkyYdOmO3EbN+vcvenpPjlG6qJqbqWJWAqk5WtQTh97h/yMtVfbH5jNVPjd+j+ko9OXl+PX6oTqo6nHWdWTNvv/32xP5UNzGGGfP8fsOGDRPn18zIfE21uHF0oC8g/fhCqPJVFaq65X5U9aifJuOW9Uzjk32LZmKniknjXZXhWr+WLz8vcXzdqt/fhg3MZH2521Sp74/3AQDg0UfdeVkvPvCqpc7+eId2JzTKAipeCVX7Z511VuJ9xhy36sFONIZIyCsyRGilS0h1vXp1cwDApk2bAADLli1LnI9tp7bJh8uNN7b2/3Nem9OmufGLrs4IjcP4ufZRvF5uL7mESuGz/XaHP5/z+6aC1jg82LdOnz4dQKw4VaUyt3zObKtVEatxoIpY9fLVMRDb1nbtWF/O81uXkf2hh5z3cGkpQPv06QMAGDt2LIB4dYf2ESGlN+NVVz3pqh3y0Ueuj6DSW+9flbMcl/M6DcMwjgpmO2AYhmEYhmEYhmEYhmEYhlEGWMItwzh24Yz0W2+9BSCeEeZMcMiDlKjKSGfIQ76WpLjv83zMoK4Zt4nOUB8uzLr60ksvAUgvF247dfKtXU5Lt/WWV127OhXhxx/nJY6rCpw46yo9sxomPu/RYx0AIIrMSyoTw4YNAxB7YNapUwdAumKTz45KPPU3prqBdYPfZ8yp769mAlbPTMYs1drcUmFKVRcVuyHPTqL+g7wuKnupeKXHK2NZ4XkGDRqUeP/BBx8EEGexJ7wP1sXSVm0ZJePWW28FALz44osAYmUpn6+25SG1m8aVtrlUvNIHWzNoh9R0bDvVRzKkIuRrvR5FvZFZj/PyXJtLNVLfvgvcFwroR+jKQ/0oO2dY5WEcedimU/lHFTWfNWOSbW6m8YVuGYuqkFUf7tBrhX0C22KuJuBr1h0qGEubxx9/B0C8sklXUfB+QyuStC6zb1EP3JTisaFvW/KcL/gVV6z3+99SindlcGxC/3X1y1aP1tCqGz53XU2jq2xCPvSxUpQrtVxb+/rr7tX69WXzc71fv34AgDFjxgCIferZp7AdUAWsejNr/Kt3a2h1kSq/6UV9ww03lMLdGYZhHCbm+WoYhmEYhmEYhmEYhmEYhlEGmPLVMI596J1KT1NVhFBJwm3Ik1Vn0lUVGPJ2zaQoUeWFZilWv0JmaC8tHnroIQDp5UDFQTwz7lu7pBAXsZLVKQNUQcItvaVeeMH5ct5885f4JlFkzoPF5dprrwUATJ06FUCsNlLVsnqk8hnxWRONQao/+D3NGKzemaxj/D59wvha/Yt5HJ5Xz6OqDcZ+fn4+AKBv376HLB8S8modOXJk4jUzaO/evRuAKV6PVXr16gUAeP755wHE6iDNSK5tM+OZbTPVPdqmqrI7tNog5LNJdZIqXdX7Va9P1Vl6Hu6/bZvLWL1q1arEflHUVr5n/tnHG/TvbdmyZeJ99WxVNbbGIttOwjZUYyyTglaPy1hl3WGbzs+5uoF9UZcuXTLdcolgm842m+WhPuaqitdxV+vWu/wR6UFP/+Qqfivmcgf2+u8XL6u9UTSooOZqFPVs5XNUpWfIHzu0qkb303rD8yxa1ABA+qobxltZMWDAAADAP//5TwBxn8LyUI9bQgXw5rauL6BALGvKFADx6g62J1qeHKezXvfv37+U7sgwDKMUMM9XwzAMwzAMwzAMwzAMwzCMMqAMbAeyokwp1w3DKBH0x6RHmHq2ahZh9YalEpUz5Jxh5n5UWOgMtc6wE52Zp5KEM8/M6ko/Qm579+7tr2OyP0734hRDEHpMESoPVOV4+eXn+j049eSyDb/3XtJ7iuXJmXZmEueMvlF6PPzwwwCAtlQ7eNUyY1AVr4xRxjSflWYSpiqCz5B1gcpAVb5qlnmqJ6hmYZ1RL0yqSRgjP/7xj0tSDMZJyrPPPgsg9glkfLOtZpvK+FO1D9tWfq9u3boA0v01Q56xPC798apWdZ6r2meoQlaV5iGlLY9Pj+PVq1cDMGX2icy0adMApGc9Z6y0bevazPnzk209Y4exp6sYGIO6OiLkfanjFB6HdYqrBLjKQfuOq6++uoQlUDSeftplnaePOOuw9k28HlX6duzYxv2nvfd0Xek/KODKHI5z+IFb4RNFXUvl+o3C4WoejkM59gjlXAjFq/pqh7ZEV6Kx7eUYin3F8uXLAQB33XXX4d1oERk/fjyAeHUR+wqWA+u5/s5QxS7HYvy9wfLkfd55551lcwOGYRilQFbb9sC0eRn3a9etPebNy7wfYMpXwzAMwzAMwzAMwzAMwzCMMrEdMOWrYZQx77//PoBYHUglh2ZJpWJCs4tqRnhVknB/VmXuH/KmUkWJbvl9esENHDiw5DdfBP74xz8CiLMt169fH0C6523IA45bqijNM+rI8dRTTwEAmjVrBiCOSfW6ZGyr6oHqDqoq+IxV+UpVlfrqqYqE56UikEpYxgjPy1gZPnx4ie7bMADgb3/7G4C47VLP4DiDtUN9uuvUqQMg9pBVPz1tszXTNtWAVGtphnn1Aed1qUqLx2O927p1KwCgT58+GUrAON7JypoIABg1ahMAoF27dgDitrx9+21+z3P8dj0AYNEip9ZWv2HGEl+r3zZfr2zUCADQYNkyAOmxqT7F3Grdoh/3jh07AABDhgwBAEz2deAa3mcp/9QZNWoUAODcc93KHNY9XmfI4/bbv7vc/edi/0ae385ym2hJqV6mUUSefPJJAEDr1q0BpK8iUK9WHXuoV6y25Yxrxq+OX1lvNN7z8lyAHK22+LnnngMQeyozrkPjcCpeWQ9JVtZiAEAUJb2lDcMwjmWy2rcH5hRB+drJlK+GYRiGYRiGYRiGYRiGYRhFphyAMwrPgVti7I+vhlHGrFzpvLuoDgxlU+VWM2Or16v6XariNeQlq5mudUv4miqosubee+9NvKaasnbt2gBibzeqGDVjvHH0GDRoEADg8ccfBwCcc45TR9EnTLOmq1pCfQOpClH4faIxG9qPdYWxTP80Km4N43CguufBBx8EEKv7iCpQ2eZnZ2cDiFdDqJ8gUV89VbDq8ZVQBm5+j35811xzTSHfNk4Goqhn4jX9jKnojNfbudUEVLyqj7GOP3SVgnrInr10KYB0JWto/ELYprPOcD+udiDd+b3spEKxtLjjjjsAAM888wwAoJFX8rKvoRJ30KDq/hvfcxtv+WqK12OLwYMHAwBefPFFAEBubi6AdI9Ttp06dtE4ZxyrYpvj+ZBCnFvGz9FefVBa5zfFq2EYxyOnAKhayse0P74ahmEYhmEYhmEYhmEYhnHSkwXgtFI+pv3x1TDKmFtvvRUA8PzzzwMAmjRpAiA9668qPtTrVWfWVUkS2oaUryHoI6gqriMF1ZTG8cOwYcMSr1977TUAsQJWY13VHhqzir4fypTNusLXVBayLjFT9k9/+tPi3J5hHBJV41MJyzhkW61KV/W1VuUrCa1iUC9kol6v/D6Pz3pC5athkL59+wKIs50Dzk/444+TGSc4XmEsqRpblYHaRhdV8Rry2KTClMehf3Iae8s2rQXHdyHUMj8ry/VFWOiUjVFUvywuyyghvXr1AgBMmDABANCgQQMAcVtLGI+6aoFxq/WD42q+5v6as4ErvTZt2lR6N2UYhmGUiFNhylfDMAzDMAzDMAzDMAzDMIxSp6i2AwWZd0lhf3w1jCNE7969AQAvvfQSAKBhw4YA0pUd9DRTzyjNZK2eraoeDHm7qoca4feoeK1Xr17JbtQ46bn22msBxBmE69Z1PoFUj2gmYFWsqrJVVdxEPWWJKgtD5zWMskCVsH/6058AxGqnkJqPqAI21OarGiuknFXofdy/f/8i7W+cfFx//fX+f5MBAP/5j4s1baO5qoAxqascCNtoVbqy7dc2XusKj08FIc9bvXr1xPeOdaKogv+fKV6PZb7//e8DSB+vc3ysK9YYrzoeD9UPze3w6aefJrathw93F3LbbaV7Y4ZhGEaRyQJQlHXA9sdXwzAMwzAMwzAMwzAMwzCMYlBU24FtxTymYRhHkJtuugkA8PTTTwOIs6pWrlwZQLoCRL1e+T6zpRL1vySqQOEMvGZdpQKFM/E333xzCe7OMGKYQZg88MADAIAaNZyPYJUqVQDEvmca6yFv10yKQa0rof0N40igHsP001Qlq6qnNO41kzxXQ2TyimX8s42n97FhZCKKugMAxo4dCwBo1KgRgFgByNjkqgLGJOF4Qttk3V5ySQP/Ded5OWfOXgDx+KTLzZe6j3/md/Myk/xfum2140T5ahxfcLw+xbehBW+9BSBWXFPJqv7abKsJ9+PnXH1w4PLLAQDdWG0u81uLZ8MwjKPOKQCqlPIx7Y+vhmEYhmEYhmEYhmEYhmGc9BTV87U42B9fDeMoMVDS4FINlZOTAyBWkGgma/VMy+TzR7VTQYGTiuzatQsAcJXP0pvn9+tgM+1GGXPXXXcd8vNnnnkGQKwqOfPMMwGkq6m0ToQ8NFlH9u/fDyBWYRnG0YSqJ6r6NL61TVflaybFq8Lvs+1nRm3DKCr9+vVLvGY2+Jo1awKIla8hj3l+ritz4hheAgCYPt3t13HAt93b7/qPN9P7so3fOk/Mal9+XbIbMoxicJXELVeu0c++UqVKAOI4V69itvX5+fkAgMu9p3K13v6A/7Txt2EYxrFGORTN87U42B9fDeMYIU5w4f5ING/evKN4NYZhGIZhGIZhGIZhGCcXJ5TydceOHRg5ciQmT56MrKwsdO/eHf/4xz8AuBnC2267DePGjUPFihVx77334u677z5al2oYxeb111/H73//e/z73//G6aefjh49euAvf/lLytd19+7duO222zBt2jQAQLdu3fDYY4+llH4VKlTAmjVrAAC1a9cGkJ5lVdnZpQsAIPvttwHEM+y1evUCAPRQZeuAAQAs565RcrZs2YKhQ4di3rx52LJlC9auXZvyMAaAe+65B//617+wdetW1K9fHz//+c/TFFTf5Favxn7wwQcBxH7IVau6rk8Vf6G6QIXgvn37AMRKP6rADeNQTJ06Fffeey+WL1+O6tWr4/777095/5UGA3zb+/zzzwMAzjrrLACx97EqWhm3zPSenZ1d6HHVI5mqK8b/xo0bAaSvukg/zhR/nKuKcjvGcUimtnn69Om45557sGrVKuTk5OBnP/sZhgwZkvqc2eAfeuiDiMxLAAANSklEQVQhAHEMc9WCxjLbZPWsZ3b3Z57ZCQC4/PIB7gT0vqzAM271W2pQnDc+/v8S3b5xErF79240a9YMzZo1w/vvv596f9q0aRgxYgQ2bNiATp06YcyYMWjYsGGRjpmpDR01ahQA4I477ih8B1tpZpQioTHLihUr8NOf/hSzZs3CwYMH0aFDBzz00ENo1qzZ0b5kwzguKAvP16KtWSsDfvCDH6BOnTpYv349tm/fjnvuuSf12a9//WusXLkS69evxzvvvIM//vGPePPNN4/WpRpGsSkoKMAvfvEL5OXlYenSpdi0aVMi6covfvEL5OfnY82aNVi9ejW2bduGX//610fvgg2jBJQrVw7f+c53UpYZSnZ2NiZNmoSCggL8/e9/x8iRIzFr1qwjfJWGUXSWLFmCW265Bb/97W9RUFCABQsWoF27dkf7sgyjVDlU23zgwAF8//vfx9ChQ1FQUIAXX3wRd999NxYuXHiUr9owis99992HFi1aJN7buXMnfvCDH+A3v/kNdu/ejfbt26OXFyoYxvHEocYse/bswXXXXYfly5dj27Zt6NixI773ve8d5Ss2jOMH2g5k+lccsiI1YBJWr16NDh06YOrUqbjwwguRl5eH1q1bY9y4cejatWuxbwIA3n77bQwZMgSrV69O8+4DgPr16+OZZ57B1VdfDQD45S9/iZUrV+KFF14o0fkM41CURYwrr7zyCv77v/8bixYtAgBcc8016NGjB4YPd75ljzzyCF599VW85TOpHgrOqKuHGo9lGIVRlnH+1VdfoXz58mnKV+W6667DZZddhp/85CfFOv7LL78MAKhWrRqAWFWlyteDB50aip6aO3bsABD7HWfynDWOb0ojxm+55RY0adIEv/nNb8r2Yr8BM8nXqVMHAHDGGWcAiNv2zz//HIBTcAHxagjuz3EU6wO9jal4Xb9+PYB0384QWVmT/fm7l+h+jLKlLNryb7bN27ZtQ506dbB3715UrFgRANChQwfcfffd6N27d4YjJXnssccAxDHK2Lz99ttLdJ3GyUFpxfjs2bNx9913Y8iQIXjqqadSyte//e1vGDNmTGrCYe/evcjJycHHH3+M5s2bl8UtGUYaR3rMsnv3btSoUQM7d+5EjRo1DvPqDePEp2n79hhVBBvI/699+yLbRWZUvjZp0gR/+MMf8MMf/hD79u3DrbfeigEDBqBr164YPnw4qlatWui/1q1bB4/54YcfolmzZujfvz9q1KiBDh06YObMmQDcUum8vDy0adMmtX+bNm2wePHiIt2QYRSXsohx5d1330XLli1Tr0eMGIHXXnsN+fn5yM/Px/jx43HNNdeUxe0ZBoAjE+eHYv/+/Zg7d26iHhhGaVIaMf7hhx8CAFq1aoW6deuiT58+qT96GsaxQGm35do2165dG71798YzzzyDgwcPYvbs2Vi/fj2+9a1vHcnbNE5iSiPGDx48iBEjRuDhhx9Om6hdvHhx4ndmdnY2mjRpYr81jSPKkR6zvPvuu6hTp4794dUwigg9XzP9Kw4Zla/kuuuuw9q1a5GVlYW5c+emlEclYciQIXjyyScxevRo9OvXD+PHj8ewYcOwatUq7N+/Hw0aNMD+/ftTHpdTpkzB4MGDsW7duhKf0zAyUZox/k2mTJmCm266CXPmzEHTpk0BAHl5eejXrx+mT58OALjiiivw+uuvo0KFCoc6lGEcNmUR50VRvvbv3x/btm3DG2+8EfRqzcTjjz8OIM4szPpCb0t6YlIpaOqqk5PDifEKFSqgXr16ePvtt1GvXj30798fp59+esqTvizhqoYqVZzDFP0yGc/0zWzcuDEAt0oIiFWFHM7xhxc9Xvv06VPm124ceUqrLS+sbZ40aRJ+9KMfYdeuXQCcgnXw4MGldu2GURQOJ8b/+te/YsWKFXjssccwZswYjB49OqV8HTRoEGrWrIn//d//Te3fuXNnDB48OOXJbRhHiiMxZtm0aRM6deqEP//5z8VewWAYxzL5+fkYOHAgVq9ejdNPPx1PP/00zj///LT9BgwYgJkzZ6bG2GPGjEHbtm0PeeyW7dvjn0VQtA4qTeUrGTx4MP7973/jjjvuKFaj8N5776FSpUqoVKlSalb9jDPOQG5uLgYNGoTy5cvj5ptvxtlnn40PPvgg9aOaJvz8PxMVGUZZUZoxTj788EPccsstGDduXOoPrwBw4403omnTpvjss8/w6aefokmTJvYD2TgilEWcZ+KnP/0p/v3vf+Oll14q8R9eDaOolDTGATc+ufXWW9G0aVNUqlQJP//5zzF58uQyulLDKDmHE+eksLZ52bJl6NWrF8aOHYsvv/wSixcvxh//+Ee8/vrrpXn5hpGRksZ4Xl4eHnroIfz2t78t9PNKlSolfmcC9lvTOHqU9Zhlx44duPrqqzF8+HD7w6txwvG73/0Obdu2xSeffIKxY8di5MiRwX3/9Kc/YcGCBViwYEHGP7wCccKtTP+KRVQEPvvss6hx48bRoEGDonr16kW7du2KoiiKhg4dGmVnZxf677zzzgseb/To0VGjRo0S751//vnRxIkToyiKorp160Zvv/126rNf/vKXUa9evYpyqYZRIko7xqMoiubPnx/VrFkzevXVV9M+y87OjhYsWJB6/fHHH0fZ2dmle1OGIZRFnEdRFB04cCACEK1duzbts1/96ldRy5Yto507d5b27RhGGocb49/61rei//mf/0m9njdvXlS1atUjfh+Fcf/990f3339/NGnSpGjSpEnR/Pnzo/nz50eLFi2KFi1aFM2ZMyeaM2dONH78+Gj8+PFH+3KNMqQ02vJQ2/zyyy9Hbdu2Tbw3cuTIaMSIEWV7U4bxDQ4nxidMmBCddtppUe3ataPatWtHZ555ZlS+fPmodu3a0VdffRU98cQT0SWXXJI61+effx6dccYZ0dKlS4/KvRonL2U9Ztm9e3fUtm3b6L777jtyN2UYR5Du3btH7733Xup148aNo61bt6bt179//+jll18u1rHbtmsX5UdRxn/t2rUr8jGL9MfXgQMHRjfeeGMURVE0ePDg1P9Lyq5du6KqVatGY8aMib766qvo5ZdfjqpVqxbt2LEjiqIouu+++6JLL7002r17d7R06dKoTp060RtvvHFY5zSMQ1HaMb5o0aKoVq1a0QsvvFDo5127do1uv/32aN++fdG+ffui2267LTEQNIyyoLTjPIqiaP/+/dHnn38eAYiWLVsW7d+/P/XZ7373u+icc86J8vLyDvs8hlEUDjfGn3rqqSg3NzdavXp1tHfv3ujGG2+M+vTpUxaXWmzsj68GOdw4P1TbvGrVqig7OzuaNm1a9PXXX0erVq2KmjRpEv3tb38rlWs3jKJwODH+xRdfRFu2bEn9e+CBB6KOHTtGW7ZsiaIoirZv3x6deeaZ0bhx46L9+/dH9957b9SpU6cyuQ/DOBRlOWYpKCiIOnToYBNnxgnNf/3Xf0U//vGPoyiKojlz5kSnnHJKNG/evLT9+vfvHzVt2jRq1apVdNddd0VffPFFxmMX9Y+qpfrH14kTJyZmYj777LOoSZMm0XPPPVfkkxTGu+++G51//vlRdnZ21K5du+jdd99NffbFF19Et956a1S5cuWoVq1a0f33339Y5zKMQ1EWMT5gwIAoKysrOFO5Zs2a6Nprr42qV68eVatWLerWrVu0YsWKw74XwwhRVm05gLR/3/ysQoUKiXrw29/+9rDOZxghSivGf/WrX0U5OTlRTk5O1KdPn2j37t1lcbklRv/4unDhwmjhwoXRO++8E73zzjvR6NGjo9GjRx/tyzTKiNKI80xt84svvhi1bNkyqlSpUlS/fv3o3nvvjQ4ePFjq92IYhVHa45Vnnnkm6ty5c+K9KVOmRM2aNYtOP/306LLLLit05Y5hlCVlPWYZM2ZMBCCqWLFioq1fv359qd+LYRwtCgoKogEDBkRt2rSJ+vTpE7Vv3z6xupjk5eVFX3/9dfTFF19E/fr1SyjGQ3Tr1i1q165dxn/dunUr8vUWOeGWYRiGYRiGcXR57bXXAKQn3GKirdWrVwNwSWUMwzAMwzAM40ThkUcewZNPPgkAmDx5MurVqwfAJZ5t1KgRPvnkE5x55pnB78+YMQN//vOfU+PpI8mpR/yMhmEYhmEYxmFx8ODBxJYJZOyProZhGIZhGMaJyIgRIzBixAgAwJ49e/Dll1+iQoUKGD16NC699NJC//C6ZcsW1K1bF1EUYeLEiTj//POP9GUDAModlbMahmEYhmEYhmEYhmEYhmEUk6VLl6Jly5Zo3rw53njjDTz44IOpz7p37468vDwAwA9/+EO0atUKrVq1ws6dO/GLX/ziqFyv2Q4YhmEYhmEYhmEYhmEYhmGUAaZ8NQzDMAzDMAzDMAzDMAzDKAPsj6+GYRiGYRiGYRiGYRiGYRhlgP3x1TAMw/h/7dixAAAAAMAgf+tR7CuMAAAAgIF8BQAAAAAYyFcAAAAAgIF8BQAAAAAYyFcAAAAAgIF8BQAAAAAYyFcAAAAAgIF8BQAAAAAYBMiAxz2+pIeWAAAAAElFTkSuQmCC\n", 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Sr6DkfEblwQoVHe3ohOb9+ffnPVUKB3Sn7+P55eD9+36hklJVNiwHOxmSo0kYIWOY+4PfMwLH18htKkn+TCdNvxZmVfX+V6xYIUmaM2eOQgidwagwNkIIoRVhBlD6Ptigo49EacDEVPSDFfrj1Bin1mzE0peEdUcaOc1zeppGbcn4pc+FDW6fOweFrBfD/XM6nFOndITeuXOn9u7dq+7u7rpggXDgdKSxsWTJEkk1p6uTTjpJUu2B80ivlLWRiXN8k3PuulqPwg+Ul6V9MByLaX5d/tj1JOLLcWBYYaLzGX02DDt5d3Csulp1gKvuj85o7sg42i+lhTYMVWTn7vZQVq/mDbGy4XVc06SURInSe1VOluoldrfF96i/Z+QN00WX8n64s7dqY0XEPlULFixo2O4QQvvQkcZGCCG0AzZebbjZIKRxyYGRByvGBpoNPxt8HsVzOo5+DYMZv1QNOP3YqA4Js56WDH86WXPfNkaNjWnmDin5bNiIZa4QXxNf66pTdldXl7q6uurCusOB01HGxoMPPiiplhjHnv2cE/YIzA86q2FyVOmblVJlNXyMNzxVEu/DlHIQMD2xo1auu+66oV6GoPrf3rAolDsm/w6+7r433OFRnubvRj8E5u+gExwd8JhPg9EuJR8ROrdVz8HKhEMF3akyXJGZRKlEUJHwvew2WH429C/xs0DVr1Tm3PK7P//t3/6tpJGtFhtCODg6ytgIIYR2gtEdnMazscsIDY7G6Yhcmr41TKtfCrHmoIiGKvdbzRLKCJZSYUBDZYNtoVHMjKSEfi/MesppwqqiMn78eO3atUsf//jHdc8990jKlPbB0hHGhksEO5eC4/mtYHC+nUlgPGr0zeft+KAx90J1NMlOg6M2jnzpYOWROKMl3Nk4X8Tll1++z2sx2nFUj/103CHxujPDJ6M76IPBaBPeS96/16NvB2Vq30vM1ml8T/Ie9vF8n7DqbPXcqIZQNnYb6SdSCntk3g23xcoGQxLdNvp8lCR8nisVEBcpmzt3rkII7UVHGBshhNBOeMr3+OOPl1Q/7UfjlEqCv6dxTFXABiJH9TbgSqnmaZwzgoNGOHNmVPdhOFVo6CRPp2emD7BhXqqFQhXGcFDJTKLVqc6enh6NGTNGkyZN6p+GDAdHWxsb9lZ3OWbntvCIiHIbR7nMcOgRmG9GVrv0A0f/C6nsnESpj8f2MR0547bwYff6mb/eN8xTYejj4I7JzmYeVXPUz5wS7HxLvy87Wr4EvH/fY3YQ9N99Hj6O2+n7Y1+5MRhNYqXPeTdYLpzZSr0d00vzxeXt7WNhfyOfO6NMGPVF6Z5KDBVIZ+dNtdgQ2o+2NjZCCKEdsQHIKV9Wcy0V3qNCMdRRPnNQUEmhMcxoFhqc/judhKVyzhA6RZdCr91GXxsb5jZeqYRwqtrH5bQiry0zipquri719PTUTQOGA6OtjQ0/qFY0GMnhm9GSHyMImIjGIzrOORs6PPlBlMpOTaUHqRQB4CXn4qnWOEPmLbfcUrw+owk7cf36r/+6pHoJ1p0kC0n59/A9ZAWBHZa3d4fHtNEM52Pn7HvQ6/mzOziqaKTkA8R2SLV7kNEdjIQp4e+t6vhF4nPy332N/Nz52hlfC6/PLK08FzoQMjKISozz6SxatGif5xNCGHna2tgIIYR2wlO/p59+uqT6SqeM1OAghX4GjZK6Vf9eqqVC51sqGyWfDfpu0KiuTity+s3QX6SkznBQyCll7sd/p/9Kyf+FAwr6eHR3d2vcuHH9RvTSpUslSTfffLPC/tOWxoZ/dBYv8k3nz5TrWFei5BzlB5O5MjiSq8pu9NFgZ0Flgnk5OPfPcC1mHLWqs3LlSknSrFmzNJqxgx1roDDdcMmxzZ0ofycmUWLZbEu87pB8b7DolLd3+6iElSTlkpzOEMTqS4j+HL7XmG+mhPdtRcO+HvS9YO0TytT0kfJ+Nm3aNKA9JSmf7SesOhtCaF3a0tgIIYR2xIMEOjLTF4JTtnSq5eh/sEgPJoljqD5h9Asd2zmY8v6rBqANc37HHB/+zOm9krP9YNtTdeEgspRQz4wbN07d3d3q6uoa4K9hJ/5wYLSVseG6IR5RMedBo5umup5vLo/QeDPTW77kld9IjeADQdnTNy0rXTJDZMnz30v6mfh4oz0PBwtS8Xdg5+hICXbqJfnan3mPMeqE9wHvTXbaPH7J8Y+qBB33qu1gsiIqCFQcSpEyzATq7e0DwgJYfH6M72W/HAbzT/Hzzd+Sz6XVrGXLlkmS5s+f33B/IYSRp62MjRBCaGfsiGxDrTRNx+gRGp1UGGzw2eg2JV+M0veEmUvpA8LsnlVlo+Q073P1NiWjl34nPDYHFD62BxIOJ2cSutJ+qkaza6NMmDChvz1RNg6OtjA2PGp3AhzfnB4h2buddSP8gHiEV8oOWapzMVj63OoDyrLIbpP/7lEYc4HwIedoj/4jHE16OdrzcFDpoYNbKQyPDnb0b6ACVUrr7HuIShR9N+hjwQ6wlA6a7WZkSNW5raSe0E+ILwxDxzuGSfLvlLGZv8ZKBCOrDAtu+Zqx4Bb9oZgGO4TQurSFsRFCCO2Mo1DOOussSfV+B4wKYXI5Vi41TA7IadqSkcvtDZ1z3c6SU3Fp+ri6LSvX7mubRpRyh9Dgp0FuI9Z/5344hV09Jysb48eP7z+ep/ec/XXevHn7bHcYSEsbG8uXL5cknXbaaZJqP7bxzWqveY/yOA/uEZJVBd6kjO/3g+00tf5MRaSaZ8Prlhy+2JZGuTqk+nnp0giYnYdHi3ZAG23QT4C/FUfvjFJh+BsrpzIsjh1fKcqF9xplZ6oFVizoJ8HteX8xY2p1H35B+YXke6RUCMt/p4rGc2V9mJK/CacO6JfEZ8btLeUFYXExTx3kJRBC69LSxkYIIXQCpdIJjDZhmD2d0zlNx0yfpeqwNhA5JWVK1Vu9n1KBQcMpu+o50fma03BUdbhPpq3nwMDnzoEFB2wl35BSLpOuri6NGTOmrr1MXheGRksbG0zly5oJxjehFQ4+OL5ZrIzQMYnpaO0LsmXLFkn1D7pHXtUHz39jRlDjESvVmVLlTXZCfqB8rlZS/NnHc6TAqlWrJEkzZ85UJ+NMqtOnT5dU74fDkT9zQzDhEBWRRhKrVJ/kiEpJqWKwlyX1wPcR5XLmhOFLpHpfsWIwM376eWLOD+Pny+v53mX2VWZFLeWYMVTtmB6aDoTMz1HK/Et5/u6775Yk3XrrrQohtAYtbWyEEEInYMPMAyIbcqUQZzqrl/wSSqHyNIbpH8EID0KFhJVXmdejUdr8UqJDfi455JfaSEXD14YDDQ7ceG5UMqp+KtXvuD6nbMPQaEljw6PV3/iN35BU/8Bx/p1ymR84Rqn4AXdkCG9mr+9RJWs6cF6+OnLzvLT3Tecoho7xgWOyHdZnYZSKOxefk0d7dAzr9Boqvu5UFpiRk4qTr7tH6/6N/TLw9bNkavXL+2OHR0nYS0aPMAMpc0ZQlfC9yAyyvB+qHSqVOzrU8YVB5z+GU9L5kHI0O2HmJOH+WZWWdYKYQ4TJmfhM0YfE1zKE0Dq0pLERQgidhA0qT816sMEEaVQ2SlkzmSKexilD7zl6L/lJUF0w3L60rG5XMk5Lxyodm8oC/UeoXDAtQKkOTMlHpK+vT11dXdq7d692795dlzKhlIwu7JuWNDY8/1yq2so5Yz+ITrpSCnEylM9KaWuZY4HrVRUWKwweBfqzOwOOjA0lOe/bfiPuPJhXgc5WdOjyNZw6dao6GSsPzDdSknDZaTO0kH4JvK4ejbMKrPfj39tLZuHky8b3BUfjLKNtHx232+s3CokshQZSLWPnyc6bETlcj1I/nxMqgwzLpP8Mn1sqGqakcDLbawihdchTGUIITcKp1F3llcaqi9JRqbBRzGlARkZw+o4GIEfvXN+UUtbTEbnRQKu6XXXAxgR19POgcchw/pJvBY1mOlvbgPeyVJizNM23d+/e/n87d+7sN3r9W/laxBF5/2hJY4NZNvlg0GvdN59HSsybwTneEowIGWwk6JFblUaOUlL9PDnnxX1O9hlwqt3NmzdLqj30bhtzF9CBy/vv9DAtX7+SExr9CNjxGPpa8Denj4yvKztIjtJLSZlKSgt/L4Ya8iXj9avKhu8dL9lWFvuiU6FfHHyevPR6vGY+Z0Zt0VmRzwa3LymX7A98bfwc0t8mhNA6tKSxEUIIncDRRx8tSZoyZYqkemdbT6t5aYOJyoSNSxuAHL3TIKTTLROgceBVql9CB+pSjgsvq/4M/huTwlHJ4Ge2yUax287QaNaF4TVgBA9VmkblKHp7e9Xb26v33nuvP/Ta23mgx/aGfdNSxsbSpUslSWeccYak+vwaHPn4JvQIyjeFHxDfdL45BnMM8nG8Ph8kdwSNakrw4WTxH7fFnQ5zfuzrxpfKiobb7OOxcyiFtrU799xzjyTpN3/zNyXV+yXQOYxlrv17sbKoO2FGJtFBzvcmOx7mgvHvxIgJqmNUYnx/0D+B7eB9UN2HsapCRYL3GHOM+HsqhKZUL4ZhmP7Mc/U5lhwHS86Q/o3pX0P174EHHpAk3XjjjQohjCwtZWyEEEInYaOUhf5K4cWs+mpD0dOpHlAdd9xxkur9HhjizSJ5g2UOZUFJOqaXMpdykFVtO/1NODVYKgXAKWlfSw46aZSyvozbQeOXUSXVsPNdu3Zp7969euutt/r354HiYJVyQ2NaytgohX/RKapUKdUPBCt50gGICsdgIVmlEK7qg+VoAT7UXvqBogzKtriTKOVdYBhWSYKkZGglYOHCheoEeN7MBEpFh+mbmbeipHqxdk2pSmypUBVlZ/ojuJN2O3x/+D5gDgu3n3lZGiUa8rV5++23JdVeWIYKIZUNdtr0hSLMCUMVx52+XxqlKDGfCxNLef++ZrwWDiMtRaGFEEaOljI2QgihE3AyvVNOOUVSfU0TDi6YPp9Gqb9/4403Bvyd9UJKqeNJKfcFjW4umYm0lEm0em6cyizti5TKTtCJmoNGDj49EPSSWVVpzHZ1damvr089PT064ogj+o9nY5tRLK7ou2DBgobnET6ipYwN3sCsnMn1+HePMn1z8CbhzW784Hl+3iNB37RsD733q9uWigyVjs157tLIlT4E9PlgnQsuWZOl3WEEAz+Xii5xlF0K5TNU0/z70PmNFUoZrsd7yOwrZXJ1v1a6qJSYavspqVtFe+uttyRJGzdulFTLS1Mq/uVr6XMt5YRhBFRJ0aAcTvWG6o5fqL7nndPES/poUMnktQ4hjBwtZWyEEEInYAPIhpINPRti9KnwYMHbcdrN2OhkWQQ66ZYSnpUGI1Qm2C7vn7kqbNA2SgNgo9HGJZUMhn8btq2Ud4PrM5LGRrIjfTyN6AghJzzkVHd3d7fGjRunnp4eHX/88XWlJzjgYCHP0JhMaoYQQgihqbSUsmHZlFYy0xwz9LTkJMmkP8bTK6X0yk6GRKnd+7OlXD0e4+A5X0nnV3pUez6RWeroSOg2eMTBkE+PImjtO0SzU6DXPZ0XWY6c01f0VOf6pRGd4bwtR2c+nvfDMu+c1mGBN+/X7WHIM0dj1SkD/59pxb2tIxrcJoaY8xp6f74H/XdOQTFJGKchfQ5M2sew71KYMvMrMK06i995P0uWLJEkLVq0SCGEkaGljI0QQugEPM1hQ44VbD0o8ZJVimnw2RBjyGxpAFbKy1Iq525KScRKFXYNHVyrbaUjZqmu02BF4UpRg/xMPy4b2f5NHLXkQScHgN3d3Ro7dqy6uro0ceLEut+ATr6pxTM0WuoqMWSOoW9+wAxD9DxK9YPmB9vf+yZj2CK9o/lgmdI8qFROlc598sb1MZwwzEuO8jwvyAeKycSYnpvLToEdF8MmOZfNEFauz3vM9wadGE2p8+a8NF8mVhNY+I3qG1N1e3s6ddIhtnquzC/gdelP4LlsJqDj3DrPseRUSwdN78+du19Mbl/JqZYvXu+H16T0Ah3M+TeEcOjorDdQCCGMIA55nT59uqTaaNoGn6dgPVVLpcLr0cA66qijJNUMQw6kqDSYUl0ZQlWBiojbUyqqZqqGHQuxHWwSrKGWoqeiwfwrNsZ9Dpzi7uvrU3d3t/r6+tTX1+Gn5jUAAB7GSURBVFcXAcYoq9K1DwNpKWPDDxZlLlbv44/M+W2OvCh/eclRK0ehPg7nrDnfL9WnjfbSbWYmQcN6AT5XJgWjDwYz+PmcqNZ06qhuMK97Q/maigEVEP5uHF2XFBV2wtyOqpp9c3iPcf9ur8M9vV+/xOgbVP0/czYwiZefN6pkVlmYQM7PI8OM2fnznmTYtdU7+nTwmvlepk+JFRm3s+RL4vYvXrxYIYSRpaWMjRBCaGdo/DFplw0y5/KxYzjTmNPB2NNn/t7GJ+s1cerLlPwjSn4PHGDRMKQhSsO2ui8ODKiKlIzXEv6eyglDZOkbUvqeDsk7duzQnj171NfXp61bt9ZNy9nI9YDB+7Gqdcstt+yz/aOVljI2OE/uB80PKueimYWP1f54UzJJEeWzUqlresub6ii6NL/sYzC6wW3iw0yfDDqCMWUzi8XRkazk0NXulH4b/r3kv8Dfh05ipeJhrGVRLYBWbQd/x1LlSmZ+ZC0LKh+sCmqqKcRZeJAvGEbGUN2heuYkYJ4CoCTP54z5B1gwjSnm+Xz6mrIIoaEC42vEa8faFyGEkaOljI0QQmhnSpltGZ7vQYCVDSsdHBywNDxDoG3YUVngNGyp9g9H+0yM5SkrZnOmAsL28v9VSonEBqtZxTYy7Jv75YDDxqinNFnXyL/F9u3b+5WNLVu21KUfYEZcTy/6+9CYljI2BvNu59wuCzaVbkbmMPADxHTOxjcn0yLz5q5KhpQTKWfyAWLZerepVNCLvhg8Vx+XnVmj1OqdAO8Vjq75mb8Z85O4U6aPB0fHHtV7v0y9TYXE8OVjWZyqnSlVqqRjoH9nKzXV/9uvgxEyXrIIHNvKFw8jaCiLM6+Hz9X3dink0ZReTjwOf0v635ScF0MII0dLGRshhNBJ0PeCBpa/d3QK05pz4FRyRKcPhaEjM49bUjo4tUynXxqiHBBKZbWlVNtqqNV6mbacDs6lwanTk3Nw6UGlf4OtW7dq9+7d2rt3r954443+a8pAAv+mvvbePjSmpYwNz8FyFMcQJRYhY86K0lxtSV3gnLX3zwgBhkB5Drvadu+Lqor3SZ8N79vfszaBOxM+sKw3QN8Nt4cqTadAnweOrkvz9nTEM5RI6UNj6DPD4/t3GSxhEaNK3AGyqBnbU/JXsHog1e4lRnOV8ld4H8xbY6gc8EXo58Rt4DWh3xId9ghfEtwfM4iWXoydGokVQjvSUsZGCCG0M6UsmMbGKI1jw7B6hj7bYPN+WPG2lIRuqO2k30PJ0KRvSaNQe1bJphM3k8SVwsrZZk59MpEho1PofO3v7aPh9P1efvjhh+rt7VVXV5e6urrq/GQ4pe3fqtMSJw43LXV15s2bJ0las2aNpPqbijcP590ZzeKb3A9GaZ7fD4W384jQx2Vcv0dOlESrx2DbDBUPH6s0v1yaqy9FO7BNbvv8+fMb7r9d8b3y/e9/X1J91kuG27GWCvNoUPJlh8fOlI55VNX4UqDvjqF07HbyPLw9FRU6r1Xb6G2ZOpudtJc+JyoXXJ/nQLXHih9/Az4TfEkYKhmle50vJ6pZ9ocKIYw8LWVshBBCO0MHbxaXtMHnqS4blf47p2o9WLCywelSlmn3lBkTodFoLhmMbientLn0edEQrCo5pUybpfT3dCyuhnNXKQ1C+T0T7tFAp/O8Px9++OHq6elRT0+PpkyZUpcrxdeapSJKzv3hI1rS2NiwYYOk+gyCHE166ZvLDzAlRtZUKaW95aiWCgnXq6oIPqaXHtkyeyKrfNLTnlEUvJHpb0LJ0Ou5k3KOhE7FnbCvOztVKgbsOBi947+Xon54D7KTZVQSq/TSP6iE70FKuMyv4t+56rNBvw76DTFPhttEvxUqHINFdzBniZUF74/XnE6PpQRYzAzKLLxUKK2s3HDDDftsbwjh0NGSxkYIIbQjHAjZoKNvhnM9eIqL03gclDCpHMN8vb79Dmzg0UmYodk0ku3HYIONo/5S8btGPiLMc+F9lIxFRn1wirm0JNwf/V8Mpwmrior9NaxwVNs9mPN2aExLGhtO9/rQQw9Jqs+eaXzzUG5jMaPSKNLfc8RFqdIPYCl1r1Quzcw8ChyFlRLSuHNiZUzj7ahwuI1vvPGGJOnGG29seO6dggtTMZytFA1Sigrh6JoKE0f7VMV8LzKSwr+LVQYrHFQ66LdAqdjru330k/B1kGr3q9vKjKFUEBglwqqs9HkqJVuij4g/W3XxZ+/f19z7Z90avhipsDAaxqGHVkZDCK1DSxobIYTQjtx0002SpCeffFLSQD8Aqb6MgA0qRqHwsw00ThHbqOW0mo3RwQxFw5B5G6xULjhNWarAKtWnv2eCOjracxqOYeQ8JqdA6YjMkgO+NgwU4FRkb2/vAEOdSSSZXK5TS0IMNy1tbHDOdcWKFZLqZTiPaj2i4sio5EjEuWzf7JTFGN/fSNngDew2MPyLjl+l2h6lfAr0yfC8uDu50cbNN98sSVq1apWkclKiUhZKRjawMzWl4lGEmT2ZGZQvBaoLpYJchp2+7/1qe3xOvjeocLgNfIH5s/flz+xU+TwYfmZtFPsPeXt/72yqfn7piMfKx3Ts84vxl7/8pSTp1ltvVQihtWhpYyOEENoRKhcc+NDRm8apfSZsqNkgo9M8fTiYx6NUZNKwHQyxZ7g0o2VKieCkshrC6XA6U9sI5bQa28wBGaekGS3C6TxfE16rnp6efp+NMWPG1CVYtFFdqnsTGtNWxsacOXOGtJ5L/drBiE5S9MZnRAdvIkalsDRx9f8l6ZA1OiiT+oHwvLMdvUarYrG/UEJ150klqOQrwd+0pIKxsmhpyfA65s2ghMzQSKoNg4X5VSujHnPMMQPO1SN/5tFgPgtWWeaLkuvT4a7kPGjFwve41SiybNkySdKUKVMk1RRH+mTRR2PmzJkN9xdCaB3aytgIIYR2wMarDTgOdOiEznl/+iPQUGQ4PiMmmEm0ND1o6NNRSjFPRYMRJ9VEahyA0WD2Z4aLl6JHaMSyLUzd7890smZCPxrPY8eO1dixY9XT06OJEyf2D1b527E9ybOxbzrS2HA0Swn7fkybNk1S7abzzemOwTcpR3qNRpl8qEtZSxlF8Nprr0mSrrrqqqGeXmjAlVde2fDv69atk1S73u4MGT3Eqq3MrkkplU5qTD/NzptKFx3v+LJhXRG2i1E21XvR6zpHhztZVhj2/c4XWemced/Tb6V0r/PFVaLTstyGEGp0pLERQggjCZO+cXq1FD1ibJjR4ZhOvzb8bCzTwZjGNNvBaTiP4tkO1hXhtLANV0//SfVJ5EqRLcxPMVg+DTpp81pRFXLbfW7MqkqVZvz48RozZox6eno0adKkuoyhnBr35wULFiiUGZXGBn0/PPrlSI2likujWKl+rp7ZG72NO4uXX35ZkjR79uyDPp9Q5gtf+IIkafXq1ZLqfSacgdQdlVUByt8lf5+SPM2OlfcS16fPCZUxRs0wV0YjqN4wpNDn7nuSkVNMG81zHkweH0wJCSGMHvL0hxDCMMMICdYyYYKzUj0Pj6q9P0ZW2BC0isBpOu/f0Sw2mnkcllXw3zl1zNB8Vn2tGr+cPuM5UlmwAU1HZSocPjdOfdLZ20v/BpzapKpTzdI6ZswY9fX1qbu7u98YpwJCX5Gwb2JsqDb6/fu//3tJNW9+Pwx0RPLNZy9/qdYZlByz/P2LL74oqVa1NDSXlStXDvhMfwZKr5RGHRXk35wZQOlTwVos/nvJh6dU0diUHAGZybTayTPyhX9nJ+3PDrek0sEpgVLU1mA+HKWEUiGEzifGRgghDDOev1+7dq2k2tRVycGXWTJp4HFUzxwTNoq9Hxt6dO71Z06/uV02wjllbGWGkSKlqWap3ril3wjVEi+ZO4QMFv5NY9uGOSvn+lp5O4dom97eXm3btm1AhE31eP6NvN+wb2JsVPjiF78oSfre974nqVYsyQ+FH7RZs2YV92HfAD90ljvtm3HeeecNc6tDIx555BFJNdnYSgRH4aUslSUHOEa1sLS3Oy6G1/Hlwrwc9NWgCkCfIErBVaiOMELG+BrwRciqrfTlYP0XZvxk8iaqRSGE0UeMjRBCaBI22I466ihJ9VVgS1EjnFbj6J81VGx80sg1NpKZqp6+G5xWtHJCVYDGL6vWVteh6sGpQ58zo0xK03KlarIlxcNLKhQ2spktdc+ePdq7d696e3u1ffv2Op8NH8fXNE7+QyPGRgOuuOKKA972S1/60jC2JBwo7nStTjHHAxULJkPyZysVdMBzR+NOeNOmTZLqi0p56Q6NBa9YSdgdmSXdqVOnSqqF7VGB8XlUO9qSsyGP7X342vgcfUxfC2fqtErHRFR8EdIJ0ufm7UMIo48YGyGE0CTsS+EU7Bxtl0b5npbjFJSNY0ZkMNNnKbSaBmJJPWDFVDvD+/g0ZGmIVv/vY9Cg5hQklQZDhcRt8LVlZA7VI3/vcyqFrVePU53eZPZUG992qA5DI8ZG6EisKJTyYvizOy4v3SFye9ZS8Wd38t7enfLmzZsH7M8d3YFWJH366aclSUcffbSkege/qnzNImClCrYMo/TSqgrDJEsvSoYAUn2xDF2qiRJC6HxibIQQQpNYuHChJOmxxx6TVDPUmBKeU1E05DgF5s82CD0FRqOaDsic4iJMLsckd9zeo32vV90v/TuYJdUGvY9F342SszbT7fszw8H5mSqQj08HZ+fX6O7u1oQJE+qmVH0er7/+Oi9f2AcxNkJHws7WCgMzcTKlMuuFeDt2SCWlg4mMXnrpJUkHrmiY3//935ckPfHEE5KkY489dsDxquoFc7ww1LAUZsl8Ml76Gtn/xdtZGfE1YApu79dydwhh9BJjI4QQmsxbb70lqT47JovdGToO2wj2lJRH1/ZzYNI3Th8y7Hkw3xEvvX8btSwYaMPS61WzafpcvW8W/GPqfq9n6GdiZ2wfgzlE/Heu52lBDiwYAVT1X+nq6tKYMWN05JFH9u+H7T7YAcRoI8ZG6EjoAEf5198zZNAdEEP6WISJJb15HKsHlr2Hi6985SuSpEcffVSSdPzxx0uqyelSfTQKO3O2lamn3bkyDNKdtSNj/L3X93p+IdqRzlMJIYTRS4yNEEJoMh4Fr1q1SlJ9QjQbfnS2tSFoVcCKB6vB+nuGXlPBYK6KUrE85vdge+n4TENWqjfgvaxWV5VqhjKVDYZ3M1OnFQu2jTVX2B4rLlSFbCT39fUNqH/CKJhEoRwYMTZCR0K5uZQm2rBIE30zWDvFHRllbnd07uwdPTLcXHPNNZKk5cuXS5JOOumk/u8GK8ld6vyZIbT0IvOLyEsmlvLnRJ+EEEyMjRBCOES8+eabkmpVWD26Zip3G7U29Gw8W9nwVBYjNWwAej3DSBAbnh7llwpI0pA09AExjZLL0R+lFJFTqgPjczQ0lukMzoGFry2VDk4jespzz5492rNnj7q6uvT+++/X+YzY0A/7R4yN0JG4Q/iHf/gHSfWheaVqq6XaJYb1Q6gK+OXgJVMoDzfXX3+9pIHVbemrYay2uJP1Z4YIsnNmThJGq1D6dzbVEEIwMTZCCOEQsWjRIknSihUrJNUUBRrBVg5K4ct0TLbx6/VZpZUKBX0vHNbMyqzMEEpfD+YHqRq4pWk3OixzSf8SL1lSgPtj9IrhelRv6K+yffv2AbVhfI2SV+PgiLEROppXX31VUq0js/zMzpyOcKWOybCoFKVbqwVvv/32sJ5PiWol4jVr1kiql5eZ3Ii5QeiXUqrWytooluzdGS9evHh4TiqE0DHE2AghhEPMnDlzJEmPP/64pFrtFGa39OdShIUNRxvRNiBtENqItr+BDcpSfg6GRdMYZ+E/1lqpKhucguQxGK3ibUtVXel3YhrVNqleG0e7+JpyCtRUE/t1d3dr9+7d2rZtW3/pgRtuuKHh8cPQiLEROpr58+dLqsnWHq2zgytJqpSx6cRGGZnRKc41cSjZuHGjpHopnEmJWI6cLwNGo1DW9jm+8cYbkmrXOoQQSIyNEEIYIS6//HJJ0lNPPSWpfjqOkRxWOqwwlCI7mHzOsMAgE7F5eydw8/GtBlBloAHaCE45NsrYWd0368DYYK9mJ622iZE03u+kSZManovb7nM21XPq6+vT3r179cEHH+iqq64qnlsYOjE2wqjAsrX9GShPc/Tvzpy+HfSDoNJRqrB6KFmwYIEkacmSJZKkadOmSapJ7T43hg4yq6o/2zmQxcFmzpzZxLMIIXQSMTZCCGGEsXOtR+EMU2a4slUAKgulpQ1Lj/b9mUnqrCaUarewkiupOlJTaeBUZClNvo9ho5g1T+jYTGOZ6ox9Nnwc5ixx+6r+Lb29vdq1a1f/lGQ4eGJshFGF/QvceTrkj6GDjOBg51r67A6S6aVHAodZmqVLl0qqZTV1Z0x1xy8Bd8p2kLvlllua3OIQQqcSYyOEEEYYF6t74IEHJNWHYJeceQ2zbZbS6FMV8HZM2GaFw/VHqpEaUv2UWyOfDabJN56WY7FD1j4pZQr1+l76nG3Yl/J2MOGej0fH6TfffFM7d+7Ucccdl5T7w0iMjTCquOmmmyRJDz74oKRaB0Z5mR0VFQ4mEHLnbBXAqoCP1wqUOk4rHj6XlM4OIQw3MTZCCKFFuPHGGyVJ999/vyTptNNOk1Qzhk0py6bhVJgVDRvLnja06uD9MeMonYmtiFCV8H4b1Ubxd8xqyvov3pdzgHjpY/t7Kxg+N14Db8fcICWfEEa9LFiwQI8++qjC8BJjI4xK5s2bJ0m69957JUknnniipJoPB2VrdmjMnmlJ1h3Ydddd19wTGEYiFYcQmk2MjRBCaDEcvmxj2AqHQ7Y9amc0idUEf7Z/BI1kf/b6rNFCFcJGt5UNft9I2fAx2FYqC/7eCgYr0fp7OzTbsLcSQT8UqzX0R2GafX/va+RrHppDjI0wqmGExfLlyyVJRx11lKRah0fZms5mV1xxRfMbG0IIbUqMjRBCaFFoDLuWikf/VgM8OqfvhWGVVhvJVhsYwcH6IV6fvh7G++Hfq21i3RYrDN6nlQmfE0sG8Htv7wGBfTWYf8MKiv1YPPX51ltvSZLmzp1b1+Yw/MTYCKHC9ddfP+Dz3XffLanWUTKcz51+CCGEMjE2QgihTXAtlYcffljSQB8JqT7qxKN858uwiuAIDGbd9PqMJLGKQB8RTidWa7nQqZq5QWiwW5mwUuG2+lisF2Olwm1nJlD6rdjH47XXXpPUWmHpo4EYGyHsg+ScCCGEgyfGRgghtBkOrXa0ygknnCCplo+DGUO9tFpgtYEKhyM+rC4YKx1ez9u98847A45XLTzodbwvFvKziuLaJVYseCzmELGCwaKJDFO3b4bbaFUojAzdg68SQgghhHDgRNkIIYQ2hdEqjzzyiKSaj4b9IawCMGrEqoNH/87KyYgQ1hfZunWrpJr6cNxxx0kaGAXj1P30C7ECwdweVigMFQ7m5bDPhn0xrGTYR+Ptt9+WlKR1rUKUjRBCCCE0lUOibFx77bX67ne/22/ZSh9Zxj09PfrOd77TXw9A+mi+bceOHfqv//ovnXPOOYeieaFN2Lx5s6ZPn67p06frX//1X/v//vjjj+tP/uRPtGHDBp144om6/fbbdemll45gS0MYGWbPnj3gs5UO+0mw4KBVAisYViasFjDjqPH6c+bMGbRN3/72tyXVFz1kThB/9nr0A2G1VtZIsfKxaNGiQdsUDj2HTNm47bbbtG3btv5/dha6+uqrB/x96dKlOu2003T22WcfqqaFNuFrX/uazjzzzAF/+9WvfqVZs2bpzjvv1Hvvvac77rhDV111VX/CnhBCCCPPoMrGHXfcoX//93/XU0891f+3hQsXqqenR3fdddewN2jFihWaPXt2v5Ub2puXXnpJn/rUp/Tss8/q7LPP1uuvv66zzjpLTz75pM4777wh7+fHP/6xfvazn2n+/Pn9IyVJ2rBhgyZNmqQvfOELkqSLL75Yhx9+uF566SUdffTRw306IbQVVDqWLVsmqebTwbwc1WgSqaZoHEyWTR/DyoNVE/tW2HeD+TKMfTMc3TJr1qwDbksYOQZVNmbNmqX169f33yB79uzRqlWrdM011+jmm2/WpEmTGv4766yzBuxn6dKlmjx5ss4555wBhkuVV199Vf/8z/9c94CE9uUTn/iE/uqv/kpXX321PvjgA1133XW69tprdd555w35/unt7dUf/uEf6t57760zQn/rt35LZ555pp555hn19vZqzZo1Gj9+fN39F0IIYeQYVNk49thj9bu/+7t64oknNG/ePK1fv15TpkzROeeco3POOUdLly4d9CCLFi3SX//1X2vixIn6x3/8R82cOVPTpk3T7/zO7wxY75FHHtG5556rU0899cDPKOw3M2bMaOr+582bp7Vr1+rTn/60urq69Mwzz0j6yAAdyv2zZMkSffrTn9Y555yjn/70pwO+6+np0ezZs3XVVVdp586dGjdunJ544on+bIQhVGn2vd7qzJ8/f0jrOU3/cCS1u+aaayRJ9913n6Sa74XVlJKKzUib0N4MyUF0zpw5uu+++zRv3jytXLmy/+YZKlX/i4suukhXX321/u7v/q6hsfH1r399v/YdDp5mTIeRefPm6ZJLLtGyZcsGpDQejNdff11LlizRT37yk4bfP/vss7rtttv03HPP6eyzz9ZPfvITXXLJJVq3bt2of7GEeg7FvR5CqKerz+blPti5c6eOPfZY/cu//It++7d/Wz//+c910kknacGCBVq5cmXDbU4++WT97//+b8PvbrrpJk2YMEF33nln/99+9KMf6YILLtDGjRv7s9iFzmDbtm365Cc/qc997nNat26dfvrTn2ry5MlDun/WrFmjK664ot+DfceOHdqxY4cmT56sX/3qV/qbv/kb/ehHP9Lq1av7t7300kv1mc98Rl/96lcPyfmFEDoL+5M999xzI9qOTmJIxob00cj0P/7jPzRlyhT94Ac/2K+DPPnkk/q93/s9HXbYYXr22Wf15S9/WWvXrh3gIDh//nzt3LmzP1QrdA5z587V+++/r8cff1zz58/Xu+++218qezA+/PBDbdmypf/zqlWr9N3vfldPP/20pk2bph/+8If68pe/rGeffVYzZszQ888/r/PPP1+PPfaYLrjggmadUgihg4mxMfwMOc/GnDlz9NBDD2n58uX7fZC7775bc+fOVV9fn0499VQ9+OCDAwyNnTt36vHHHy86job25emnn9b69ev7fS3uvPNOzZgxQ9/5znd09dVXD7r9+PHjNW3atP7PEydO1NixY/v/9tnPflbf/OY39Qd/8Ad68803NXXqVH3961+PoRFCCC3EkJWNX/7ylzrjjDO0ceNGHXnkkc1uVwghhDAiRNkYfoaU1Gvv3r268847dcUVV8TQCCGEEMJ+Meg0yvbt23XMMcfo5JNP1vr16w9Fm0IIIYTQQQxqbBx++OH9mdtCCCGEEPaXVH0NIYQQQlOJsRFCCCPArl27dMYZZ+iEE04Y8Pcf/OAHOvvss3XkkUfqtNNO669nEkI7E2MjhBBGgDvuuKOuWODu3bv1pS99STfeeKO2bt2qVatW6Y/+6I/0P//zPyPUyhCGhxgbIYSwH6xatUpHHHFE/7/x48fvVwVjSXr55Ze1cuVK/fEf//GAv2/evFnvvfeerrnmGnV1delTn/qUzjzzTP385z8fxjMI4dATYyOEEPaDmTNnatu2bdq2bZtef/11nXbaabryyiv1l3/5l8Uqxk63bxYuXKjbb79dEyZMGPD3Y445RldeeaUefvhh9fb26sc//rFeffVVfeYznzmUpzjqmTFjRmorDTNDTuoVQgihxt69e3XJJZfoxBNP7K9oOhRWr16tBx54QOvXr9dzzz2nWbNmacOGDf3fr127VjfccIPeeecdSeovghlCOzPkdOUhhBBqfOMb39D777+vJUuWDHmb7du367bbbtP3v//9ht//4he/0MyZM7V69Wr9v//3//Tiiy/qi1/8oo477jhdfPHFw9X0EA45mUYJIYT95Hvf+54ee+wxPfnkkxo7dqwk6fbbbx/gy8F/kvTiiy/qlVde0bnnnqtp06bpsssu0xtvvKFp06bplVde0c9+9jNNnz5dF154obq7uzV9+nRdfPHFWrdu3UiebggHTaZRQghhP3j++ed1wQUX6J/+6Z/2e15/z5492rRpU//nf/u3f9Mtt9yi//7v/9bUqVP1yiuv6JOf/KSeeeYZfe5zn9P//d//6cILL9TXvva1TKWEtibTKCGEsB88/fTT2rJlywCnzXPPPXdI6sOYMWMGVDGePHmyuru7+//2iU98QsuXL9eiRYv06quvauLEibr66qs1d+7c4T+REA4hUTZCCCGE0FTisxFCCCGEphJjI4QQQghNJcZGCCGEEJpKjI0QQgghNJUYGyGEEEJoKjE2QgghhNBUYmyEEEIIoanE2AghhBBCU4mxEUIIIYSmEmMjhBBCCE0lxkYIIYQQmkqMjRBCCCE0lf8P0MofugiUQ6wAAAAASUVORK5CYII=\n", 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" ] }, "metadata": {}, "output_type": "display_data" - }, + } + ], + "source": [ + "plotting.plot_stat_map(p, threshold = 0.95)" + ] + }, + { + "cell_type": "code", + "execution_count": 181, + "metadata": {}, + "outputs": [ { "data": { - "image/png": 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\n", 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" + "" ] }, + "execution_count": 181, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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\n", + "image/png": 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\n", 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\n", 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\n", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -308,9 +182,32 @@ } ], "source": [ - "for img in func_files:\n", - " print(img)\n", - " plotting.plot_stat_map(img, threshold=2.3, display_mode='x')" + "anat_mean = '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1322/anat/sub-1322_space-MNI152NLin2009cAsym_desc-preproc_T1w.nii.gz'\n", + "\n", + "plotting.plot_stat_map(t_plot,\n", + " bg_img = anat_mean)\n", + "\n", + "plotting.plot_stat_map(t_plot,\n", + " bg_img = anat_mean,\n", + " display_mode=\"x\", \n", + " colorbar=True)\n", + "\n", + "plotting.plot_stat_map(t_plot,\n", + " bg_img = anat_mean,\n", + " display_mode=\"y\",\n", + " colorbar=True)\n", + "\n", + "plotting.plot_stat_map(t_plot,\n", + " bg_img = anat_mean,\n", + " display_mode=\"z\",\n", + " colorbar=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## The negative picture (in case there is less activation in the second session)" ] }, { @@ -319,12 +216,11 @@ "metadata": {}, "outputs": [], "source": [ - "# visualize results\n", - "t_plot = nib.load('/media/Data/work/2nd_level/_cope_1/randomize/randomise_tstat1.nii.gz')\n", - "p = nib.load('/media/Data/work/2nd_level/_cope_1/randomize/randomise_tfce_corrp_tstat1.nii.gz')\n", + "t_plot = nib.load('/media/Data/work/fslRandomise/randomizeNeg/randomise_tstat1.nii.gz')\n", + "p = nib.load('/media/Data/work/fslRandomise/randomizeNeg/randomise_tfce_corrp_tstat1.nii.gz')\n", "# suggested threshold should be a=0.005 / .001\n", "\n", - "thr = 0.95\n", + "thr = 0.1#95 # shuold be 0.975\n", "t_plot_data = t_plot.get_data()\n", "p_data = p.get_data()\n", "\n", @@ -341,7 +237,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 11, @@ -350,9 +246,9 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] }, "metadata": {}, @@ -360,7 +256,8 @@ } ], "source": [ - "plotting.plot_stat_map(p, threshold = 0.95,bg_img = anat_mean,)" + "%matplotlib inline\n", + "plotting.plot_stat_map(p, threshold = 0.95)" ] }, { @@ -368,20 +265,10 @@ "execution_count": 14, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/plotting/find_cuts.py:62: UserWarning: Given img is empty. Returning default cut_coords=(0.0, 0.0, 0.0) instead.\n", - " .format(DEFAULT_CUT_COORDS))\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/plotting/displays.py:767: UserWarning: empty mask\n", - " get_mask_bounds(new_img_like(img, not_mask, affine))\n" - ] - }, { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 14, @@ -390,9 +277,9 @@ }, { "data": { - "image/png": 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KkVlOom6aZJaGZN7xJ5MJ+v1+qrEdz4EdcD3Pk54xfJ/XmWXFukutvl6G5YWRDYPBsBCYNdFz0nOdLflEza6uWb1J2Fis3++nohrcp3binJXycN/XY9UkgsfNqhTRkQoSCb2eG8HQJOawhGGeSHUe3PEmya4nie/7Qm6YvqLrKgW6+hhMZemusPMIkWG5YGTDYDAsBGZFNrTDJ8nDeDxGEARIkt1ma+xnoifXfD6PXq+HKIpSRl40tOLTOMtmr3W8brWJXp5V/ZF1vlm6DxKTLDKStZ+r1UloMqPJBo9Ji3Id3aAuhlGm0Wgk15H+G9RzsEQ2qxrHsHwwsmEwGBYW2lODmguWf5J4DIdDEYBqZ9AoitDr9ZDP51Eul+VpnBUsk8lE9uOKRudhlnATmF/uOmtfWiehl89L98wiKoepeOE2+niVSkXGoi3bkySRCAfTUjT/8jxPohilUmlfxMaNFBnRWG4Y2TAYDMcas0L/WqOgXT/51M2naEY5gL228nEcI4oiBEGAMAwRBIFMrr7vw/M86QfC5mK6N8lB4+Wx3Mk9SytBuCmVWe8fxjF0lgZEp2XmEQ99DuVyGWEYppaPx2Nsb2/LdWEZrI5gAHt24lxHp1b0eWbpXQzLBSMbBoPhWCMrDcBJrVgsSiifbeAZ6WD0gs3YJpMJdnZ2kM/nEYYharUaKpWKlGqORqOUvqBarSKXy+HKlSsp/YeOchwmUqAForNSHLPOOautvHbk1N1f9VjmtZrPiijoVAi3r9VqqNVq+4zJaF++traGbrcrJGw4HIrDKAldGIYSSWKkiNEP95oYyVhuWOmrwWBYOJBscPJiiJ/EgukQAAiCQMgI36cTZlY5KsWm1EQEQZDqAsuST66rcRCZmEVOsoSibsmp677Jn4dNR8xKrWixKX+nq6q7DvcznU7h+z7K5bJcfwCIokg0GyQouj8N9+U2jMs6D8NywciGwWBYOPDpXkccAKRstHUZJnt2UNQYhiGKxaJENYC0IJKlmYVCAeVyGUEQiP7AbZuukUU+skiCuw7fy6rO0L9nVbm4KYms/cwTkbpRjSRJUKlUUpbnej1WlJBw1Gq1VCdYkg3ei+l0miKEuoJlnrDVsFwwsmEwGBYOmmjodubj8TjVDyUIAvF/oNiTT+MM7WcRAj3BFotF2YakZh7h0HAjFYxQZEGnE2ZpVNx13e3npU/mQRMNYNcMTY9TC0a1Iyv/1pqO4XAoaRIKdHU3XZ0GckmSRTWWF6bZMBgMCwUSANpkaxtyXS1Rr9cRx7EYdnE7TUoI1wxLRwu4XRiGou3Qjd3mTfCaQLBaRm87S8Tp/s313f4iWVGHWddsFrTRGNNHejtXCxLHMZIkged5Er0godORJr0NU1gUitIPJY7jmYJYdwyGxYaRDYPBcGyRVbbJp2zdQl6nP7SgUqdIgF2zr/F4LE/irVZLJlnqPzgRanD/2htCpx9mEQ5XR6FTCbPSHrOiFrNSMFmpFm1GdhBIgphiYkt59zySJMFgMBCyweV0Z3UrXXitGNFwiZDWbsw673nLDYsFIxsGg+FYIYtguO9zosrn8/J0zOgGJzD6QLg6hyiKpGcKyQefyvP5POr1euo4/J0lssPhEL1eb99Ys+CSDEYQgP025Zp0MIrBiZrpHi6fdQxddnpYcH2SLW37rq9BHMcpIsKUCaM1PC/3mvNc9Xpac2M4GTCyYTAYbjjmNWGbV7KpoxqcuHVJJpfpzqOubiKOY7TbbQRBIKkYToy022aprKtVYKM3moGRQHAyzXpK1+kWvUy/pyfnLHLlXptZ1+hqzMf0vrV7qud5+9aj9iKXy8m9Y7pKl8tybJo4afdWTS4Y9ci6dpY6WT4Y2TAYDMcK8yYaTlhMnzBdoJ0+syZ1/ft4PEa320W/35eneU1SXKdLd1xuNALYe3IHsl1DZ6VAsqoy3CZlen03hZMVRXCrU+ZBpzG0DbkLOqrqc2ZpsSZ6WWPUJIOExiU5WeM1wrFcMLJhMBiOHdwJi8tINDi5u66eTIu41RUkE3pdbebl+760oh8MBvKEz4mXYyEZYQqG+g5Xy5E18bvCUK2tYORDE41ZREeTIfea6e3m2ayTZLn7Yakw01IU1DL1oa8RsGcqxmiHG7nQ5I/nq/enx3yQbsWw2LCEmcFgOFbQT+l60nHz/FlPzkRWJIFhe3diY7UEJ37+rdM2/EnDMN/3U+JU/j5Lw6FJgHtuWpMxa31NXlwi5R5H+1jMGofeh262pgWymoz4vi9EhyXDep+6Ed4swWfW+4ctIZ6HeSk5w/GBkQ2DwbAQ0E/BeoLkRH+Qx0SSJDKZuumQJEkkKsJUgksgtLCTlRsAJNqRpbuYlQrQ5CIr7aPHlyUidS3Ks9IW7kSuIx4kOIwyeJ63zw2UESRecwpjGdHRfiZaP5NFFLNSJFn3Net9w3LA0igGg+FYYdYErcmFm06g3mIe2dBpCz1BU/TJVAif5HW0REdE6BfBZaxm0SQI2NMjaCLg9lVxtR/ue7OqVdzy2SwNidaw6LETjFwEQYBqtbqvOoRkhOvyfKhx4Tlnpbzce6mJiBaEzksZGZYLRjYMBsOxgat3cMsyOSHSlIvL6FJJuJMx4aZP2A2WKRLuR7eqp66DZl6lUgmNRgOdTgfT6RQrKysolUq4ePHivid9YDfMrydcdyyzJmsdweDfehtO9jwXPfGTVNFmne+zuy17w3D/JEyEGxnhtWBUhxGgrGus76UeO4kKj8NlOk11Nf4ghsWCkQ2DwXDDMRqNMnPtB6VB9NM3Iwyu5mFWCD6rYoP700QiiiJ0u13EcQzf9xFFUarEdjAYwPd9iX5Qx1Gv19Hr9fYRCp1+4RO9jspkRSd4rCzRKdd1oyVummkymSAMQ8RxjMlkgnK5jHq9LvuZTCbSOE07g2ptDLvq9vt9cf8k3NRJFrkgNHnjdjoVpn+3qMZywsiGwWA4FnCf8LOqUThZ0f5ap09mRTH0forFohhRARA/DQBCOEhi9HqusLHb7cL3fYRhKGSFvh0sE+VLT7BZuoQsQqHXm9XIzY0GuJGNyWSCfr+P4XAoKZV+v498Pi9Oof1+X47Bc5tMJvvMu1xDMl6Tw9ij6zQX75l7byyVsvwwsmEwGI4F5oXjXdGjrkiZ9eSfBV2KycmSk6BOdWRVvXC/uuyWf+u0AglMHMcIggCNRgMARFyZlTLRE/pB0R1NejQJ4HVhmoJaFFbaRFEkxIPpJ8/zpFRYR2Fcsy6t9eDxfd9Hv9/PJIX6HuifrmZFp1H0/XR/Nyw+jGwYDIZjhSyxIyclRgl0B1GtX5gnuOR6BMlGVhrA3ZeOGvClm7m5QkhO1kw76N4hAPZFObKOq8nVrAlcg5U2Wq+RJAl830+NJ0kSGQ+vp75mSZKkyl4Zjciq9tF26gdhVrrFvcZGOJYTRjYMBsOxgjvBkGToiZuTJAWHWU/Mrh6A++Lf2ojKJRqlUgme5yGf3+294lqgU0zK/fPpnxNzqVRCEAQYj8diba5TKrlc2kmTx3VBm+8oilLruOQD2EuFMLVDokECQsJxUOdZVyvC/brRn3kaGTcVpitjSqXSvn3o++KOyQjHcsDIhsFgOHZwJ2EdOQDSuX7XqGuWQFSnYzjxuWZgwK6LZq1Wk8lVe28A2KeR0OPLEjrqHivuNjwX7s+NXND7I+v9rCiA9tBgFIMRDz02wiVmbqQB2IsAkdyRZOnIUlYaa5bwNese6XHNun+GxYaZehkMhmMPrdng3/w5j1y4oXtOdiQSWRNvtVoVkSiJBqMnJDduaaie5N3UhC4vzXLMnEU86GSaJcLM2oe+PiQo1I645aY8Ds25NPnSY3GjQ57nSSmvq6Fx70UWqXIFoe59zNLJGJYDRjYMBsMNx9VYTLsTE5cRWaF3jazlWRNkqVRCuVxOldTqNIIWlrpkQvdQ0Y6mFIxmER53fFnC0axxu9vqZcViUYShjASRNGk7dn1Mdr7V58Nt+SoUCvB9X1JYlUoldd2zIhZZkYysezVLtzHvvA2LB0ujGAyGYwN3UsnqtZEVjThsXt/dFz0yOJnySR/YjX7EcSwVHFkERzt1BkGQiiLQPEuvy/26vUX40x3fLBKVtUyTHo5Ll+7qihX3mrhVPlkppiAIJNJSrVbR6/VSkR3uy71Ph7l/7ljdCIxh8WFkw2AwHAtkPc0Wi8WUeyiX68lIe0IA2f4cBFMZnFx934fneamoBQAx9qKYUpMFHoOgYRWJBd8Pw1DSGKVSSUzA+LdbCTNrctUkRJuL6XEwxUFX1SAIxCeEwlqKV7U/BiM3ev/6mnF8k8kEW1tb0kPl4sWLcjy9Xz1eV+TJ9cbjsaSatLiW0MtcszYjH4sLIxsGg+FYwhVUAvuFhLN6orjagCx9BiMBeqLM5/OIoghxHANIdz51J3it4SB5IFwxpXYP5TH1uoeJ2mSlUPRPmpJxWRAEmE6niKJoX1M5PZHPip7o47GKhC6j5XIZnueJniVrzPo+6uvlajUA7KvM0dfL1d0YFhNGNgwGw5Fi1iTiig+1LiKXy6UEnBqzKh5cwsIJ1/d9IS4kLzy+rjDREYCsKgxux22iKBKPC21TzrG7ZIHbudEF/j4rPUEMBoPUuLVZl943q1N0Oa2e1IH9PiDcjp1umXLSvU4YBdK+HC6xcHUwWhiqx+gSxazrYFgsmEDUYDDccOjUR9aTdZaOgMv1U+5wONwXxeA+XcGhfr9UKiEMQ5lw9TG1TbkeI5EVcdHlqVyfE6iu+OC+s6zLtVYha4KeRco02eH1oLeG9tTQ49OGY/o9nQrR50nBqU63RFGEKIpS14K+IFmiWne/7nh0CbPWn7gRJcNiwiIbBoPhWIFRB05Mrm02/9Y2426UgL/TaIvRBf7O9Ea1WpX1oijCzs5OasLjflyxpHYu5d/afwNAqn+LrkihfTjXdaMK+uldk5ZZQlE9cXO/JDiFQgHVahWTyQTdbheFQkFEnp7nZUZZslI3eozj8RitVkuIGatZfN9PaUp0pEKLU4fDodwXfc857nw+Lw6nxCzHVcPiwCIbBoPh2EFrKLJ0DMB+jw032sDtdcM27mMwGGBnZ0d0DsPhUAShLnHRT9ZuSkITEU6wmhAxlUGRK9MxmjhkpU3c4x4WTC0RcRwjiqKUniNLQ+GKO91l7vUnySM5IGnRPWOyruMs91F9bd0xZFXPGBYPRjYMBsOxgquL4O/A3gTpPunPSklwcvN9X56mtZsmNR8scXVD9+7+eUxt8uU2UOMxOA6SDz35upMrkWVaxp9ZItesc9dGXrlcDv1+X8gGyRCvpbu9GxlyX1yfqRVWpGRVsWSlm1wjMH2f+VNHc3R6JWuMhsWBkQ2DwTATb3/72/GDH/wAOzs7+NSnPoVarZZ6/xWveAUef/xxdLtdPPXUU/jVX/3VazqOO1lzgtYtyfUElVVF4UY9gL3IBicsagry+bxUa8RxjH6/n1kt4e7b1YTo3zX5YKqCUYDhcIg4jlNP7DpdMes4WfoNfc305JzL7ZbylstlqY5ZWVkBsNcB1r12urSXL5c8uBEGHpM9WHiu3J+O7rjnqlNkLnnR0NEhfT+NaCwujGwYDIZMvPGNb8Qb3vAGvPSlL8Wtt96KMAzxwAMPyPs/8RM/gUceeQTveMc7sLKygnvuuQePP/74NR1LT95ZEQjX3MudrLL0FXoS5ZN4HMdS1lqpVBBFEQaDQcr7QUcRssL8uj+LLmfNSg+4ZGkeiZkXrZmX2uG5kWh4nifluGx3r7UlWdfLJQTuWDUR1BESTTCYWnIjUu7+XCLhnqs2P3OjP1nX0LAYMLJhMCwB7rjjDmxtbeGFL3whAOCWW27B5cuX8fKXv/ya9/mqV70KH/7wh3Hu3Dn0ej28+93vxmtf+1qEYQgAeOc734mHHnoIjz32GCaTCZrNJr73ve89rfNwn6IpctSTsSYDumqBBmCc/GmJ3uv10O/3U1GHXG5X3Fmr1STFwCd/TSZcQsNXkiQYDocyyetJW5eH0tiLk7DneahUKgiCYF81iEZW+gJAiiQAuxNyGIYIwxCVSgXAboqHKZRut4tbb70Vnufh1KlTCMMQ1WoVYRiiWCyKWJVj1xEJ977w2pA8UQ8CQKyog/wAACAASURBVKI2HCN7qGiCoe+X/tslIvxZLBYRhiE8z5N7q89d42rs7w1HAyMbBsMS4Hvf+x7uvfdefPKTn0QYhnj44Yfx0Y9+FP/yL/+C97///dje3s58PfHEEzP36T5F5nI5BEGAu+66CwDwMz/zMwCA//iP/8D58+fxiU98Aqurq0/rPNynYPcJPiv1QOgICAWhevJnB1U+jQ8GAwyHQ5lw+d48nQFfJCgkLTweHTaZ0mDUREcU6PAZhiF838+8BvqctfeGfp+kSk/e+tokSYJOp4PRaIRqtQoAWFtbQ71eF28R7TpKcpAVZXEFrSQ0+p6xnJgeHK5IlBEYvU++r9M2OuqhSZyr3TAsFoxsGAxLgg996EP4zne+g69+9au45ZZb8I53vAMA8Hu/93tYXV3NfN19990z9/foo4/iTW96E86ePYt6vY57770XAFAulwEAz3rWs/CGN7wBr3nNa3DXXXftS7NcDXQ+3xVVuv4TrrZgluaBpGIymaBUKiEIAnni1xUUwN6TNMeix+VqHMbjsZAKYNfrg1bklUpFJu4oiiQ9A6SjAvn8boM2unBqYpGVKnHTDoRbreFej3w+j3a7jW63i+FwiCAI0O120Wq15LrwvGjS5aZWOAbd1I37DsMQQRDIOYRhKBoYppgYldBkhtec+9Hn65IrEjQjGosNIxsGwxLhgx/8IF7wghfggQcewHA4PPR2L3vZy9DpdNDpdPDNb34TAPCRj3wEn/rUp/DP//zP+Na3voUvf/nLAIBz584B2HWsfPjhh/Gd73wHvV4Pf/Znf4Zf+IVfuOax6ydYILsza1ZlhIZezmoJvrgvTnzVahXj8TiVfsl6aaJBrYJuM18oFBAEAXzfFz8LakN02iPrqd0VmmYRj6wIAc9R71N7UXAb+opsbm7iypUr6Pf7GI/HiOMYvV5PxtntdgEA1Wp1n2ZFp1C4nGSLkYx8Pi/7yOfzKUJCkjUej8XMTWtfuB6w58JK6HN0I0yGxYKRDYNhSVCpVPDe974XH/rQh3D//fdLSuPBBx8UIuG+SCy+8pWvoFaroVar4Sd/8icB7E4I999/P5797GfjzJkz+Na3voVz587hRz/6EYDd9MkzUR2g0wsUNOrKEP20zgmYugu36oHj5oQZxzFGoxH6/T7a7TZWV1fh+z5830etVkMQBAB2Uyw6nTIcDjEcDhFFkbhyhmGIcrksQtNut4vRaCTj4fHq9TrW1tZSxIJkhpOpNhlrNBqo1+toNBqoVCop8kDo60OiFIYhSqWSVINw/HoiZjTizJkzuP3223Hx4kXUajXceeedOH36NOr1ughK6ccRhiHG4zGiKEK/30cURUJcSDIYEQF2m9ax+mVzcxMAJBLhRpj4ykqJ8R6656D/x3TKyLBYMLJhMCwJ3ve+9+Hxxx/Hb//2b+Mf/uEf8Nd//dcAgN/5nd8RIuG+SCyysLq6ijvuuAPAbuXJX/7lX+JP/uRP5Mv/4Ycfxm/91m/h2c9+NsIwxL333ou///u/v6oxz4omANhnDsX13adbN+1B0CWTE3EYhvJkzSdvVqboiIA+bqFQSDUdA5BKgTD9UigUUKlUsL6+jnq9LoJFRmlILngsHU0BIPsLgkDa3vMcuS4Fp4wmUBvhenjoVAePT+0IIxe8ProjbZIk6Pf76Pf7ErXQ5mQkYNSgVKtV1Go10Z2EYSjES/eb0URQp5RI8EajkfiC8PqSMLpdX917bFgcmF25wbAEePWrX41XvvKVeMELXgAAeNvb3oZvfOMbeN3rXodHHnnkmva5sbGBL3zhCzhz5gwuX76M973vffjgBz8o7z/88MM4e/YsvvrVrwIAHnvsMbz1rW+9pmO53hp6YtfOn1mpAq7npht0ZID74E9GIqrVKnq9npABXcrK9am74Fg4KVerVVSrVSEN1HxEUZQap5s+IdxJk3oS3/dF38DoB1MXXI/j1OPV4lidiimVShKpqNfrIu70PE96m3ieh263KwSN4llglwjVarV9Za21Wi21jtaAkIDwfT1WVvJQG0LhLgBJR1F4S6M1VxRshGPxkANgLikGg+G64aGHHsJb3vKWfcs5oWpPCD7Fkyjwd7cyhPl/Egw2HtPVDdRjALtP9jrtMJlMcPr0abEpj6IoJWh0jwfsRWGoQQjDEKurq9J7JIqi1PGazaZEVvSTOqEdM/mT++Xx3Cd73XiOyHri154XJFGVSgU33XSTLO/3+2i1WpIWabVaGA6HQjYY2WEUg/slMWAK5sKFC6JP4fhWV1cRx7GkxHhPAIhQl3/rXjGs1OF1ZhSF58C0UJKkW9tzP4bjC4tsGAyGI4MW/+m0ghYWZgk2mcIg6dCpD1fUyP3zKZmVF7Qo1xUrLJXlxM9y2NFohHK5LL4cTMuwEkO3bqcAU5+De74A9kVieN65XA4rKyuI4xiDwUCiBZzIeSw3wqMrX0gUOEHzXHgNptMpgiBAtVqVqBC1GXEcS9RBR4JIEHhNgF3CAexGMPL5POI4hu/7qbSRHqOODgF7qTIdueDYgb2IF4mE/h9wox2G4w0jGwaD4cigQ/06apBVBsq/+XTLapNCoZDSXuimawDE8KrVaqHT6YjQcTAYoNvtolQqoVKpIJfLiXaCLxIFrc/Y3t5GpVJBkiTY2dkRgy5d2soOqDp1wPEBaV8JXX3DyZypHRKOtbU18fYg+XD1EDpVw32Vy+UU4drc3BSSRWK1urqKcrmMW265Bc1mE4PBQMSzJBPExYsXpWNus9lEFEWoVqtS7kois7OzI1Eq6kh4/fS58x4CeyJaXgNXQOpW6rjX1nC8YWTDYDAcGdwSTz6Na28JHYoH9nwndKqFk5RbkQLsahwYlWi32zIhUp9A501gN7XDCTafz8tTurYdr9Vq6PV6sv92uy3iTrpqTiYT+VuXe+rIjZsKITkplUqSgiB0hEOfJydcHRnS12o6nabOodfryfGn0ymGwyEGg4GMf2NjA+12OxWloTlZsViUKpter4disYgoioS8MeKhHVh5nXXfGJ3qApDqhsvlbhmwKxQ2LB6MbBgMhiOHnmxIOPg0rD0wAKTC8LqPilsiy4mY6QNGMDj5TSYT1Ot10UawtHV7exu9Xg+FQkGqS4bDYSqlQ33GcDiUrqpxHKeMquhOyvObJWrU1SOcWHWJL7AnaKWGgpEJ/fTvimeBvWobt3cL/87ldt1QoyiC7/vwPE90HYxMTCYTbG9vYzAYoNFooFwuYzQaSUomiiKUy2VJa+l0GO+prmrR901HqhgBIZnSZEPf26z0k+H4w8iGwWA4UmgdAp+49QTDCRzYSzswzE5tgBYZ6vQFKy8o3KTDJXUJAERfwdTJzs4OCoUC+v2+uG7Sj2M4HKLdbqf8OID0JMqURRzHqYlTp0xIHvSTPydgrROhFoMdarMmX0Y23IgAr8V0OhUDM9/3U8JNz/OQy+UwGAzE84OpjV6vJ+LZdrst17pWq4nQ1o0g8RroCIwmRJrsMHJCLYg+L30u+n9Ek07DYsHIhsFgODJwEtGlpnyyJ1lwy0Y5oXPy0xMRJ1G3aZcWfHLSZwkr0yz5fF7SFdSQJEmCS5cu4eabb0a1WkWn00G325XJnf1XuL8gCKQ5mq5O0SWfJCo69aGjN9RE6Cd7HpPeGgBEMMoqHm29rq8ndSgkdCRm1KFUKhWMx2N0Oh0Ui0XUajVcunQJ7XZbIjo8J6ZdVlZWUnbsJB6lUkmiIfq6ZIli9X3Ry1ytjo58aMMzi2osFoxsGAyGIwMJAJC2qubES1LBp1mtt6AZFS3Cub6OkGT1+OAETkIRBIEQjZWVFTkGn/oBoNVqodvtCjHp9XqyL6Z8fN9Ht9vF6dOnZfLV1RZaW8EIC6ta6DdBQsAJXutYeJ7sSUKCoUmHTjUxkjEej3Hu3DmUy2UkSSLEitd1MBjItW+1Wqlog9aJMNVEwzJeHxIo3/dTaSRdgeISg+l0Kvbm+tqQYOoIB9d3/0cMiwUjGwaD4UgwGo1SjcCAdAhe+0foJ309gTGFoicrIN2LxBVQcgLXv0+nU7HdZopFNxADIKmMdrstx6fzJgBJP2xvb0t6RTt8atMtraWo1WqiT6HWhKWmXM7rxOXaxIuki9eK5ISpIFbuUMzJdvC0P9cppel0ilarJRUiJEu6O66OXmhxJ38nsjQWPGddkeK+r9NOrjeJYXFhZMNgMBwpXK2BLnHVRlpaB8B0iSYqhK5gAPYmNK0hcNM23I5iR12tAuyZe9FwqtVqpQgLSQsnZk1SXK8NRl08zxMDL07ULHXV/hgARNzqeR4mk4mYbLXbbXEB9X1fPEBIrur1ukRQXJ0Hx0uHUf0+hanUvpBghGGIRqMBAFLZogmVJgj63mkS6Hpt6Hukyab+f8jy4zAsFoxsGAyGYwH9tKujEVymyYcOsTMK4QoHdShfPz27IkM36nD27FlEUSSOmjQO6/f7qFQq8mSuoxu+76PT6QBAym7b1YwUCgUMh0PRRhSLRWxtbUmVjLYS131Eer2eVM9UKpWUaJV+Iexsq4+rK3CGw2EqasPx8FyyyJ2e8IMgkH0xMsIIDiMd7vXUpEPvy62acSNSbuRDr2NYTBjZMBgMRwaSCm1MxcmIBMIVjepJmNtwX/qnrmLRkRGtK2CkgILGXC6HH/3oR9Lrg1EKYHcipIhydXVVJvx8Po+LFy8iCALZF7DfA2M0GqHVaiEIApw9exb5fF72x/LTOI7RaDRSaSD+Ph6PsbOzk6qwqdfreO5zn4vNzU1cvnw51VuE106nqGgOBuwZlbXb7X0eJbyO+pqyWRo9OKiP0URO+5/o6Ik2PKOeRRuh6fukS271/4SJQhcbRjYMBsORQvcIAdKW3toQSj/16nV0jwz99Os+IWsjLE7i1FkwGpDL5VAul8V/gkTBNQtjm3eWwnKs+umex2WqhxP1LbfcIo3NSDKosWDahvugiJPkh2NpNBooFAoYDAaYTqdYW1tDu92WyAWjHPoa82/qP8bjMTY2NjAej9HtdlMN8FwHTx2hYVUMdSe8lrR51+mULD2GW9KsS3p1VEvfe31PjXAsJqzFvMFgOHLoyYzg5K1D+ow26KdhvQ9OhrrkUr84celIB0WPLCtlqiNJEqn60E/50+kUzWYTzWYTnU4H/X5fjsWndT3RcsxxHGN9fV08L6bTqVRwkPSQgOjj0Y0U2OvAyuhGGIbi97GxsQHP88RwS6dFdPRH/z0YDHDmzBnUarXU8qxSVZdwBUGQqoDhOtrUi9u7gl/CJXL6WFkk1LC4sMiGwWA4UrhCQZ0uobARSPf+cLunulUQsyZZl2xoASjfp+kVe56wioMpAGonKFykeJL6BZ0qICmgwRcAbG9vp0SQAFJRhTiOUSwWU23a6QfSaDRQr9elbLRYLKJarUr7eADY2toSjQZTHjwGz5XiVZ7r+vo6kiQR51TtyKpN0nTkw/M8IRtZnif6/mjRr9bh8KcWf+rIVZZRmav3MCwGjGwYji34hbiIsHbXh4OrtwD2ep1QvKh9NrhuVorEFY5m6T345M0JWKcXtKslJ0SmPjjxkRTozqaa+GjbcU7SjJIw9RBFUcoxVPt9DIdD7OzsiPU5x8ZyWwBCfnT7dR43CAKUy2V0Op2UgJbnrd1UPc+TPijUrrBKRqecgD0/FEZW8vk8oihKGYRpXQbTUtrci9ea+8yyNtfEQ8MlFllEg66mhuOJhScbizwhGQwnHW6uHoD4N2j9AyctACnSoG2uOaGNRiMMBoNMLYcmHsViEWfOnBFCwFSFthLXVSqj0QiVSgW+7+PSpUtYXV3FysoKtra20Ol0pIcKtRWc7LWIkikSNzUDQEpLO52OpHQ0SapWq1Kmysk8iiLZnh1ttaCSbqS8TiQcnuehWCyiUqmg0+mkCBP7rujrTUKkoxQkZPwOLhaL0v1Va2B0VAMAarUafN8X7w63DFnff13R4pIRi2wsFhaebGgma8TjmYN9mA03All5eD3B6zA639PrAUhN5HwCd30cCB2SpydFvV4Xa25Ocvl8XnqmFAoFqfIAdr9zGNnodrsywTIqwuNorQjH43kefN8X19CdnR0Ae0/5rGjp9XpSmcFxVSoViUrw3EhKGF0g2eEkrVMSegxMfTBlw2tG8WkQBOImStLDc+e5kjBxHZYIa00NyQ/JSZLs+ZDoiAfHnHW/XDKqz9+wOFgYsmFE4sbCPsyGGwXXz0ETCk04uK4OvROe50njtCxBoavp4M9+v4+1tTWsra1Jrw9O1JxM19bWEAQBBoOBpDgqlUqq+oOTrBaG6vQMIy7FYhFhGOLUqVPi8Mmne5ICmorFcSzkoVKpiIdGPr9rV86UBytTWq2WEB9GCEhCdPSHWhhGSwaDgURI8vk8ut0u7rjjDgDAhQsXJMKjdSuaIDCFEkURoihKnTvX0TbzvK/cjvfCNf/SJMO+jxYfC0M2DNcP9mE2HCWyJhj+DaT7Yui0gt6GNt5ZVQ/u/zaPwSf/wWAgKRRGJliVwsm80+lgZ2dHJmUSE6YCeAymUPiZcj1DoiiSCMVgMBB9A8WlAHD69OlMi27d6ZZRD2onSCiCIJA00nA4TJmD8Vr1ej14noeNjQ25Rq1WC6VSCdPpVCps6CPiXlsd+WGEgykbrfEgtAEal8dxLAJTkpesCiMtFNbL7Ptq8WBkw2AfXMORQZtJAWlvDE7E7vpueWSSJDLxcR29Dxc68lCv1+U4fHqv1+tSVhoEAS5fvixpDWomGGEJw1AmTaY8SC7cShMSBAorfd+XtAkjGTT1Inmg+FMTG076cRxLaiefz+PUqVMAgGaziXa7jSAIROypO+Umya5FebPZxGAwwKlTp3DmzBlcuXIF3W5XCFgul8Ntt90GAHjiiScwnU5RLpcRhqG0pO90OnINeH6amDDC4kYqxuMx2u12Sq/BVJJbCWPRjeWAkQ2DwXBkcCcQrbWYp7sgoaBBFbBnmX0YPwb9xEwNRafTkSdtTn6dTge9Xk90CZyoAaREqToNoqtXdAmnfnLv9/sAIK6cujfJzs5OSuTJyZnj1kJPEgCOqdPpYDgcolQq7fMX0ftjKe54PMbW1hZWVlYQBIGQmsFggHK5LOTrlltukYhIGIZoNpsSNSGB4XXTmhtdWaLForx+XE5oIy9ddaSvnZGOxYSRDYPBcKTQGgt3gtHpBF2FwEkty2Y7q3SS+yfogjmZTKSnCXUaTBvo1ut6/0C6eRxTMFrI6nkeBoNBijToc+p2u9J3hSkZRlsYHdEVN3rcHGelUkEURdLWvtPpoNlsIo5jMSNzjcxYWaJdP4fDITqdjlzbYrGIZrOJlZUVVKtVTCYT3HXXXbLOYDBAs9lMXU9GZ3TljY5o6Guol2nfDfca6numq1EMiwkjGwaD4UjBCUZHBFxhKJA2f6KZltsNVAs0dfjd9elg5QejG6PRCOVyWTwwdAt46i1cEy69H6ZH6KNBkkFBJh1EWfZJAsGoBsdFMy9aqOuyTwpGkyRJlcdy381mM1XCq0X1OlXFMdMmHYC0nSdJKJfLMn5ei2q1KuelyYzWZLhCzyyR7izCwG215oVjt1TK4sPIhiEF+0AbbjR0RIL6iSzdhRaPcuKnToPLmUrhJKonPbdCRKcAtCeGDuPrqIJORXBy1S3XaXpFMSP3Eccxut2unB+1FuPxGP1+X/ZJwywKN9n3hOmNbrcrFTC5XA6dTkcaq9E1NIoiaQ7HMfFaasJB51AajekUh05zkAxtb2+nGtCtrq4KqdLETpNFEiFea51W4n11SQrvP5vJaa8TfR8NiwcjG4YU7INsOCowxeB6a7hPx4xsUFeRz+fFdpyT9mg0kknU7f5K3QFTKezxUavVxHkzDMOUVgLYK+PkeCiGZIUJx9DpdIRQMF1CR1CSAV2iyjGtr6+Liyi1H5y46QzaaDSwubkpgtV2u40wDCXiMZlMsLW1Bc/zUK1W4XmeVNDwOCQB9XodjUZDIjskVhSdXr58GZcvX5aKlziOce7cOWxsbKDRaKBWq0m5MbDrXsr7w+tGoat+uYJZHl9rdVhhQw8R/tTRK8NiwciGwWA4FuBkyd/1cneCoSBRG07RlVL7QrhPzoyEkNSEYbhPZMpt+TeA1GSYNWECkIqMMAyRJIloPnREhcfm9vqJncfS5mDahp2TLlMgHCvHT62JJg7UUDAVVC6XRUtSLpdTESDdOwXYdRIlkaCDaj6fR6fTQbFYxPr6uvib6LJYfZ800WN6ROs7qG1xy14ZVXFt041oLC6s66vBYDgWICnIIhruem4UhL9rt0rdwpyTm06NcAKjhTj3xQmOXhv6uNRRaH8JYHcS9DxP9BvseUISwO21jiIrDUTypI9NUSfPm46iJEUcCwWn1IgwckItSKVSkffL5TIAoNvtShSHkSJef5IAEh+OJ45jdDqdFClzo1D6uMViUbrqakM2nqN7z/X/gr7P+jiGxYNFNgwGw7FCVgUDsP+pVj/9UshIO3BOnLoUkxoNpk20ELRWq6UammnNiNZvMMLBFA0AGYN2Py0Wi7hy5YpUlgAQEqHPSduF7+zsSAdZN13DCAP7jpAccF88H+6LBILXQ0cUSIjYP4bHY0SE4lSeux47Ux5MY7nEUPdTAZAiTJqsaX1HVsWRbuCmNTUW2VhcGNkwGAwLBy0U5RMyIw30ztDpClZ5sK+H1hZwO5ISTsDavIvVJpywK5WKRCnotHnp0iUx91pZWcFTTz0lpEFHUahtIFkiWaCQtFqtAthLO3DiZ5krAHHr5HnyHGgSxkn/7NmzQqJoJsZ98diDwSDl0KnbyfM66eobrkuvEL2O9snQwlASEze6oyMpGloo7BIaw2LCyIYhE/YEYTgK6MqUrPeyxKJ8gteTbL/fh+/7qVLMXC6HMAylnwkAmYSTJEGj0Ui1WSd0CSs/F4PBAJVKBbVaDd1uF+fPn0c+nxfi0e12JYJAHUWxWESv18NwOBQPCy12nU6nuHLlSsqVk++32+19rprAnpjzwoULouFgSSyjKyRdYRii2+0KgdFmXNw3yQvFmdqEi2ZhJA6XL19Gt9sVQuGmQ0j0SJaYrmJfFzacm3XvNdHISqcZFgtGNgyZMKJhOG7QBNg1qmKfEV3ySc0AsCc+ZRSEfg6s1OCkHkVRquQSgEQ59MTb7/dx+fJliZTkcjn4vo9qtYpisYjt7W0hLDqyQctwTtyMsnC8rPzg+xyL62VBYgHs6i4GgwHq9brsTzek4096iDB9AuylaJIkSfUq4X6Y6tCEgdEj2rmzOyy9OXiu2trdLT0GkCpRdu+vvsfzCKhhcWBkwzAXFuG4Nmi/BcMzg6z/Q+0FoStKdH8NHZEgMdBiyEqlIkZbrqOl/puN2dillamMUqkkJaa6z4mubKFXBp/o+/0+VlZWUCqVpGGaJhL0zNDaDWBPiApAJneWiXLfPH/qK0qlEqrVakpkqcWXWszJc2ZERutFdLUJz3NlZQXFYhHtdjultaCVOT8D2r2U46D242rut2FxYWTDMBf2gTfcaMwjuG4oXYs2dfkmzb34NK2jFIxCcCJm2gHYE0LqUkxGIJha2NnZSY2D7eV1eSaFmVo4SrIBQCzCKeRk5EIbWGnNBF8kCdVqFUEQoN/vo1qtyjUg2dATuhZmMpJDy3KSAVaK0DOE29CNlOfFa1cqlRCGIXzfR7lcRq1Ww/nz5+V6u5U/JHqsqmFqadb9te+d5YORDQMAi2AYjg8O+j/U+fvpdIper4darSZGViwNpUFXHMdS5ZHP59FoNKT6IwxDISAUV/JJnZMmlwPA2toabr/9dnz729+WiIp2zyT4OyMbjFLQ5ptEhw3PKpWKVIR0Op1UpYeu8KC517lz51AoFHDq1ClUq1VxKKUzKCMLZ8+elUqbOI4xGAz2VeycPn1avDuiKILv+/jhD38o0RKmkQCgUqnINSERGQ6H6Ha7oskgyaKfh3YGpdkZBapXc98Niw0jGycQWcTCPujPPCyV8swjy4ODGgU+rTNKwQoPHf7v9XoiHOVTPCd/APuauzGdwAkyiiKsr69jY2NDtBd00dRRgCAIxJ2Ux9cN1igAJXHY3t5GEASoVquo1+tyfjqywTRPq9VCEAS46aabUtbkSZKgXC6nyks3Njake+vOzo5oK3K5HLa2tuD7Pm677TYRa3I9t2SWEZUkScSZlN1h6S7K9A1TQ7rCR6dqdFmxvo+G5YaRjRMIV4RlRMNw3JHlIKoxGo2kz0itVhONgJ7cOHHy6b5QKKDdbkuDMdqEU5PBCIEWm/KJfH19XQScW1tb2NzcTPVVufXWW7GyspLqK1KpVMQoi0LS8XiMZz3rWWi1WtjZ2UGv15MqFhITjoXHLhQKuOOOO1LundRJnDp1SjrZUvRJEsBIxfr6Onq9nvhxsCKFlSbdbleIhr7OrHQhWaMlvDYtI9FjdAnY070wDZUV1ci6x4blgpGNEwSLaBgWFTqKQeinYaZLqBmg7oATOlMGuospQ/0ApDS0Xq+nykh1JUgQBBgMBtjZ2cH6+joajQY8zxOi0u12US6XsbGxgY2NDRGFkgT4vo/HH388lVYYj8dYW1vDqVOn0O/30Wq10Gw2pbpGazTCMES1WpVoDKtWePy7774bpVIJ/X4f6+vr2NnZQbVaFWJAAsDJn2mb4XAoWo52uy06EG19zp4zPF+mZWhpTitzikLpoKp1M1pzkvU9pHUphuWDkY0TBPsQGxYZ8/5/OTGPRiN5MmdTM2CPaHOSpwcEJ8fxeIxarSYT5Gg0klSBFlyyCoNlpiyJZTrjzJkzohvp9/tS6cKqlZtvvhkXLlxAHMdCGijqrFar8H0fq6ur4v8BQPqY8HhMAVE30Wq1sL6+LmkiRidKpRK63a6QBqZMAGB7exu5XE48Rlg+TD8P7T9CUkfhKytUmJZhVYu2PWcEhLoNlu2SYDEC5JYy23fU8sLIhsFgdK7rsgAAGmhJREFUWAjMeup1BaNRFGF7exu33HKLEA6G7hm+p8aC5Z30hODybrcrHVvZrI3OoJcvX0a9Xken08EPf/hD6fK6urqKra0tjEYjrK+vI5/Pp/qTjMdj3HXXXbjzzjsRRREuXLiAzc1NrK2tSckoUw96rHQcJfng+61WC57n4ezZsygWi7hw4QLy+Tzq9TrW19cxHA5RLpfR7/fR6XRw7tw5NJtNVKtV0bMMh0NcunQJp06dQqfTkeM1m00Rc1arVayurorQ9MknnxRBqo76VCoV6bVCF9TBYCARC0aLuMy9hwfdZ8NiY2HIBnOKBoPhZGHWU6/7VMxlTKmwOoJOnL1eL2VSFUWRiHhZycHJvlKpYHt7W7QS2vp8Op0KwWAqg1UkbPne6/Vwzz33oNFopMgOG6A1Gg1Uq1WUy2WJdNALg6SC5bksQWVEhpqTU6dOpVxPb7rpJpTLZRHK5nI5XLhwARcvXkSz2Uy1bSfZAIBms4mbb74Z9Xod29vbIvjM5XJS1kqdRqvVksoardFgNChJEimjZYpKd+alxbl7f+fpcQzLgYUhGwaD4WRiVj5/VgWDDtfTzpupDD3ZZZl+tVot3HrrrWg2m1LyqnuTjMdjrKysYDKZoFwui8fFcDhEu92WqpOtrS0pyQ2CQMSc1E2wMuVZz3oWqtUqLly4IOSHnV11xIbEB9idvO+8806pPAEg46nVahiPx+Js2mw2sbOzgziORVPBlBANyugoGgQBwjBEv9+XShlWsvi+j06nk7I2J6EhkWDreaaGqCfRrq79fj/zvlk0Y/lhZMNgMCwcdDnlLIvrfr8vT/kUjTJq4HZM1e3o+/2+iEEZ+aDVt3b0LJVKqNVqAPa6vNIJdDweo9lsypM+xacXL15EHMcIgkBcSCuVCm6//XYAu4RmZ2cHm5ubqFQqWFtbS+lGqHegmdn29raMg0Sl1+uJo2e3293nKqpdQHktKPBkJIhkQ5OHwWAgxIQkQ3uATCYT8QvpdDqIoijV9K7f70s0hdde30cjHMsNIxsGg+FYY1YVlRYuZr3farUwmUywuroq0YtyuSzNvzhhD4dD+L6PSqWC1dVVhGGIdruN1dVVqfpgmScAmfC3trbQarVkQtYdXKMoQrPZBADpNksRaaFQSBEfRjtYdruxsSGltmtra4jjGJcvX8ZNN92EQqGAVquFra0t5HI5rKysoNfroVQqYWVlBXEco9Pp4MKFCwAg5IDpGQpmGQVpNptot9t46qmncOedd2JjYwPVahWDwUDSIQDQ6/VQLBZRr9cxGAxE76HJBFNEm5ubSJIEYRhK5KXZbErH2oN0N4blhJGNBYIxf4MhGzqi4YpF6YoJALVaTXQbjFaQSOgyU21KxaqPMAyRz+exsrKCdrstGrLt7W2MRiOZpLmf8+fPo9vtYnV1VfbR6XRQqVQAQCo02GVWe2kwAtFsNsVng9sy0gBA0jEUpjLSUCqVRF/BVBBLUmu1Gur1ulTKdDoddLtd/PCHP0StVsNoNEKz2YTneWg0GhIxoWkZRa8cF4+pK2QYfWGn2yythr5f2sDMvuOWE0Y2FgjH5UPolqwdl3EZlhOz/r+ylrti0dFoJEZZYRgCgHhI5PN59Ho9MbtipIEkhNbmFFUyFcGoBCd3Tvy6aRtLSVnhQv1DpVKRzquMtuhjs4KFjpzdbhf1el0MuoBdIqHdaVkpE0WRiDJ7vZ6IXqkByeVyaDQaOHPmDCqVCjzPE4dTVvCQ+LB8OJ/Po1qtIooilMtlcTnVHiW81p7nCZEiyaH/iHYM5fVx759FNpYbRjYMVw33acRguBGY58XgPh0TrEyhTTlFo3S0vHLlimg2WP7qeZ54RuhKEFafjMdjiX5oPQW1GtSJ8Ge/3xfBaqVSkfc4PgBiL84xkITQO4MaCa7PlAz9QLjPbreLTqeTMjLTXiC33XYbTp06JdU43L5YLIqrKZ1Tgd329axO4TlrB1B93Wu1mhiFJUmCIAhw4cIFSd0cBPsuWW4Y2VhSPJMRB3MeNRw13Kfew/5/kwAMBgOpDmEkolQqpSzEdWl9sVgUcy3+vb29LVESEhGSG6YZNCng73TbnE6nuHDhAoIgQKPRkLQMIxwApHRVRy6SJMHq6qo0idNdaLe3t8WavN/vCzEg2WBFCLerVCqplAYdTFdXV6VRG8tZe72eeG2srKyg0+lgZ2dHSm1JMpgKYnSF0REAKW8QnosWhXKZYflhZMNwICxlYjhqHER2Z3lusEqCvUBqtVrKSbRWq0n5Kt03c7mc9CkhKaArJhuPff/73xdBKUWb1C7QUXMymewjIGz+xvGRzLDHCYkGoydMoQBpv4pOp4Pt7W3s7OykJnhWzlDzUa/XpbpkZWUFOzs7AHbLXqMowpUrVzCdTrG9vS0+IvQ0IsloNBq4dOmSaDU0aHhGssN9d7tdqcbRsO+QkwsjG0sK+0AbTiKynpy5nCkA3TKeUQVGKQBI2mE4HKLVaonjptutNIoitNttBEEgXWB1hQnTCdx/Pp+XdAxJEKMITInoCg+OhePkekmSpMpQdVMzil1zub129NRmMHJDW3JuT7Gn53lSdaJFqNRfaPKmRbjUrnC74XAonhyHuVeGkwEjGwuOG/mkYATGsGjQ5GM6naLdbovYk9EHmlYNBoN9+gISDnZwJRlgN9hWq4VyuYxGo7HPA4MpFHZwZVqD+gbX+4JkQPtfMB2je4mMx2NsbW2h2+3KhE7BJtMmLOUl0SDZYDqJ4k6KWkmuoijC6upqiuxQ4OmOQ3eAZcnvaDRCq9WSqpxZ94O/23fKyUH+qAdgeHq4lg+rNibi31nrGAzHHQf9n2oyTrFlt9sVHwtO3lpnQGLAyZCiS9/34XmeTNTcNooidLtdKfnU1Szan4PpFKY5OHamR1hGSkKim5yRLDGN0263JeLAzzMjFWEYYmVlRUpbPc8TIkPbciAtTqWuheSIPxlRoQmYNjZj1IRkBdgVlDIldK1Oofbds5ywyMYJgvvFOw/2xGG4EXi6PY+yhIbzwvM026ImwvWE0D1DKIIcDAYYjUYIwxDlcllICydjkoCVlRXcdNNNOHfunPQhCYIA/X5fhJdra2tYW1uTxmS6KRkJBm2/wzBEEASIokiiKzw+3T61a2ixWMTGxoaISWlWViwW0el00Gq1UufG4zKVwkZz5XJZRLPa8ZMkI5/PCzFjJMXzPJw/fz6l67jW7xD77llOGNk4QZj3JWDCLcOi4mqflPkUXywW4ft+SodRKpUksqBttPXES4LBdAejFVtbW1hbW0O9XhcSVSwWxQyL0ROmathYjakdCjlJOtiHhDoTlsCyqyoJBclSrVaTtMxwOBTCwOgL+6PwfBkt4XmWSiVpIsf9ZoHnxUhMPp+XsuB59+dqolCG5YOlUU4Q3PQJYblTwzJgXmM2/TudOqkrYAqAlRj83X3pyZ2pDb3/VquFzc1NFItFrK+vS9SiUqmgXC6jXq9L5QZJQK/Xw+bmZkpAynJYakToA8JlujyVmgtGQbg8CAKsrq5iNBqh3W4LgXJ1INSuABAXU2o09LkzkkKdCUkGbdr1Nln3JSv6ZDhZsMjGCcI8xz4tpDMYFg3u/67+3SUhnHT55E+yASBVycHoAitAWFXCCZdP/jq9wDQCBaXb29uSZmCTMo6NeguSDFavsHKGqQoAKVJAspLP58UKnX4YHKM2BHNLct3JX6dFdP8S3XsmCIJUhIIvRk20m+hB98m9P1n3zLB8MLJhELhf0EZADIuCWf+js6IdrBhhioLln9RIUPRIAqCFkUyHaL0FsFeeyojJ2toaBoMB+v2+CC6ZXuF+uB31FRRrcn1dycLzpL7i1KlTErEol8uYTqfodDoi9NTn6pILpkB4HApTdYmr3kZX8GhEUYReryfX6VruUdY9s++c5YORjRMGVyQ664NtRMOwDJjluwHsRhY2NzdRrVbRaDTkCZ8VFjTF2trakhQDsKfZ0C6fOoVQLBbR7/clyhEEgVSFAJAoBnUOjEhw4qdvBhunkSyweiaKopQLKDUa2rdDazH4ItHQaRymbNhmnlbpvHY09yKRInK5HFqtlpTfzvqeyHqAOcw9MywfjGycMLhirXkfbBOSGhYR+n80i1xraA1EuVxOtUynmNL3fVSrVUynU9EmzIocAHvpES4fjUYyIbOiRQtBPc+TpmfcHkCqNLfdbksDOXpcxHEsHh3chmkeni9/kmTw3LS4leejzcEYzeBLj6tQKGA0GknPl2v9PrDvkpMFIxsnAFf7oZ61vvtFbV8WhuMIV7sxj1hT9EltQ6VSkVQCm5vR8ptgozO+rys3dKVKLpeT7bjPfr+PXq8nreKpz9A25Uy36IZswF6kg2mZfr+/L3Kh1wcg2g5txqV1G1yfx9IREKZO3FQR9S4HpU7c6Ki77rVEPQ6CjjYZjheMbCw5ZhGErKe8eevPqmIxGI473CiHSz5IOOiNoQWh2ouCzdby+Tw6nY6kLcrlsrR0ByC+IYyOuMZYFG4GQZDSa2jhpyYi2nCMpbStVktIBT1C9Dm5587f9Wef14OTM6MYJB7u2Ek8RqOR6FKyvktmfV9kQX8fGZYbRjaWHPO+fIBspb77xZG1ncGwqHCJBJ/sKfikXbfuhcLf6dDZarWQy+UQx7GYd9HRk46d7PaqJ2w9sfI9eniwLJZjo8uotkBnc7fxeIwgCPat4z5M6Fb2fN8dD7BHNHREA9j7fmA0ZDweS/pklg8HoatZDqPpMCw3jGycYLhhTv204+KwYc7DaEEMhqNA1hO31jDQRrxYLEqZqo4acHKNogg33XSTWJ+zeoWTMe3Qda8T3XJeayB4PGC386t+H4D0bSEBGI/HuHLlihiJaeFoGIYyFgBS1cI0CtMj/J3aC7a65+dfO7rq7wamgEh6iKzPfJZmxnCyYWTjBGHWl4L7NHQYwjCvisVgOK5wq1PcKB7b0QNAuVxOVYNwO9qMe56HcrksT/o6FQLsVYTozwSFmK6glLoNLmcZLomKFqFqUzGW5zLqwuPpUlmX4JD0jMdjMQxjxEOncvT1iaIIURQJgZkF/d0xK21lOJkwsrHAOEwU4qAnC/2lN+9L4Wq/KOyJxnBc4VanuJ+V4XAon4UwDIU8aKtvTsxhGCKXy0mVCsWdWoipCYcmDPrzRv8NEgBCa0b44r71eGZV3ZAwsLstl/Fv6kYYlQEgug0SjiRJJOozK3Vy0HeGfRcYzK58gXGYPGiWQMxd9yAdx9Uc+7DvGwzHBW6EgzbhfJqnYFSXedKuO0l2y1Cpn9COpFlCU63bcPVQ1F/wb9fdlF4aOuqQlfrUVupMBXH8Oo3CaEdWakmfXxzHGA6HKZ2G+73hPqhk6b4MJxsW2TDMhftFZhGLq4OV4h1vuJMj0wicXKMoQqPRgOd5qQmUaQgAUqXC9Aqw50WRVd3Fn/qzxGiIm4ZgqakbWWB6h+vOSgvpPig8LrvbUhCqIze69JXnPxwOxamU56vHn0VWDAYXFtkwCA4KhV6tSNRgWARklYNzomaVCvUKwF5lBydnHclgCoQTNn8n3MiG+5nSHWcBiGGXJi5as5EVadHH0kQjn8/D930xL3PHqV1HWf1CMei81JPBcBhYZGOB8UxFGdx87ywclmjYk41hUTDrqZz/x4xyEOxVoiMJ+v+dDdrclEiWnkIv1+6hg8FAxKIkGlrj4eqs3H1n7Z/r6fHrNI0rCmUqieJVvS+D4VpgZGOB8Ux9+A/az2FTKfaUY1gUuMJNvUyD4k1OwoxeuBM1t9e9RtxoyaxjcDkjC0y7cdJn9YcrBp31kMD32GiN67HHiY50ANhXXUJBKHu4ZLWOzxrDrGtsMABGNgyHwGFTKfbFYlgUzPtfddMEjFTo9zzP26d1IPTknJVymEXKNXFgRIMRCL0PnS5x0zFuVCNJkpRXB1NButQV2OtYC+z5f2jL9MM+kBw2Smo4eTCyYbgqXM0XiD3ZGBYJWboELmOEgekFdomlfkNP9IVCAdVqFe12Wyb0WdUb/F27f+r3df8RLSbVRMEVnXLdyWSCMAyFGE2n032kguMlqRmNRoiiCIPBINMnZN410z8NBhdGNgwzMc934zCwLx7DosN9YmfpKW3KmZbQ62i3UKZb3EiHq9Vwox56otdEhss5Di7TlSR6G6ZiKCDVlSQ8PlM+Oppx0GfXPZ8b/WBhFV6LByMbhpkwsmA4qcjSbjACMR6PEcextJ+nKFRbgidJgmq1ik6ns8/Ay92v3oYiTr3cjTBoV1MiS1fFpnJMmejzIFjZwqoTtq0/bN+TWdcra0xXAyMTywcjGwaDwTADWZMlJ2hgr+RURw3077Qz15O8m5pgpAJIC0Xd0lm37buuetElrgDES4OupjymG2kBIJ4io9Eo5acx61ocNuI5730jEycPRjYMKZjOwnCjQavu4w6tS4jjGMViUaICtC3XxIE/6/U6hsMh4jiWKAMnfB210FUjjJzQfMvtt0KTsSAIkCS77qBclsvtNVPTlTMUi2qtyXQ6Ra/XO3QXV02UjDAYrgZGNgwpHFZ1bjAsK7L+x91lOrrB98vl8j6NBctg6dYZRdE+UanWetB5lPuM41jMuLg+jcb0uHQzNRIMTQ5YAktQo8ES16z0jpEJwzMJIxuGq4IRDcOyI+t/PKuSxPXSyCo9ZVSBJaee50kUQUc16M9B0sDJfjqdwvM8ISwsY43jOJVeIdFgIzhgN6rBaEpWRct4PEa73b4OV9Bg2A8jGwaDwXAVcKtDWNExHA4lleG2hGeEgykOdxnNwqjTIOkgieB2TJmUSiVx9tQ9Uij0ZBSl2WwewRUyGPbDyIbBYDAcAFcU6ZbD5nI5EWvSalxvB+z5WWhDLRIN7lNHSnSflclkkoqGALskY3t7+4ZdA4Ph6cDIhsFgMByAWb4S/DkejyVVMplMJBqhiYR+3wiD4aTByIbB8AzDhHXLi6zIBqF7mFCXkc/nLZVhMMDIhsEgMJJguBq4XhW6O6zBYEgjB8DKC64Si+AJcFJgBOH4o16vH7uqh6v9DNv/mcHw9JA/6gFcD5w+fRqf+9zn8KMf/QhJkuDs2bOp99/97nfjqaeews7ODr7//e/j7W9/u7x311134bOf/Sw2NzextbWFxx57DM95znNu9CksPdiH4em+DMcf14NovO51r0On05FXr9dDkiR40YteBGC3xPTBBx/ExYsXsbW1hc9//vO49dZbZ+7P/s8MhuuLpSQb0+kUjz32GF7zmtdkvv/hD38Yz3ve87CysoKXvOQleN3rXodf+ZVfAQA0Gg18/vOfx3Of+1zcfPPN+Pd//3d87nOfu5HDP7Z4pgiCfXkbni4eeeQR1Go1ef3u7/4uvvvd7+LrX/86AOAP/uAP8LM/+7P4qZ/6Kdx6661otVp44IEHZHv7fzQYbiyOnGz84R/+IT7zmc+klv3VX/0V3vOe91zzPjc3N/Hggw/ia1/7Wub73/72t9Hv9+Xv6XSKH//xHwcAfO1rX8NHPvIRbG9vYzwe4z3veQ+e97znYW1t7ZrHc9QwgmA4avzar/1aKhIRRRG+/OUvP2P7/43f+A18/OMfl7+f/exn40tf+hI2NzcRxzE+/elP4/nPf/4zdjyDwXD1SI7ydfr06aTb7SYrKysJgKRQKCSXLl1KXvSiFyXvf//7k+3t7czXE088ceC+C4VCkiRJcvbs2X3v3XvvvUmn00mSJEm++93vJrfddlvmPn7pl34pOX/+fGpZqVS67q+jvi/2stf1etVqteS//uu/kje/+c3JvffeO/Mzvr29faj93X777cl4PE5+7Md+TJb99E//dPKVr3wlueWWW5IwDJNPfvKTyXve854jP3d72esEv458AMkXv/jF5E1velMCIPnFX/zF5Fvf+tYzst95ZIOve+65J7n//vuTarW6773bbrstOXfuXPLrv/7rqeVGEuxlr2t75XK55Atf+ELygQ984Bnb5zvf+c7ky1/+cmpZrVZLHnnkkSRJkmQ0GiVf//rXk9XV1SM/f3vZ66S+jjyNAgAf+9jH8PrXvx4A8PrXvx6f+MQnDr3ty172MgnNfvOb37zqY3/jG9/AYDDAH//xH6eWb2xs4B//8R/xgQ98AJ/+9KdT71mqwWC4Nvzpn/4parUa3vrWtx56mzNnzqRSMC7e+MY34mMf+1hq2YMPPoggCLC2toZKpYK/+7u/w6OPPvq0x28wGK4dR854fN9Pms1m8vznPz/pdDrJmTNnEgDJgw8+mHQ6nczXN7/5zQP3e5jIBoDkHe94R/LZz35W/m40GsnXv/715M///M+P/NrYy17L8nrta1+bPPnkk8nGxoYsu++++2Z+xjudzoH7fMlLXpJ0u919kcn//M//TF796lfL3ysrK0mSJMn6+vqRXwd72euEvo58AAmA5G/+5m+SJ554Ivmnf/qnZ2R/vu8n5XI5SZIkec5znpP4vp8Au2HcN7/5zUmj0UgAJC9+8YuT8+fPJ7//+7+fALvh169+9avJAw88cOTXxF72WpbXPffck2xubiZ33333M7rfhx56KPnYxz62b/lHPvKR5DOf+UxSr9eTYrGY3Hfffcm5c+eO/DrYy14n+HXkA0gAJC996UuTJEmS3/zN33xG9pcFYJdsPProo8nW1lbS6XSS//mf/0nuu+8+2e6Nb3xjkiRJ0u12U09YjLbYy172uvrXu971rmQ0GqU+U1/84hef1j5930+2t7eTn/u5n9v33traWvK3f/u3yaVLl5Lt7e3k3/7t35IXv/jFR34d7GWvk/o6Ng6iZ86cwX//93/j9OnTmXlZg8FgMBgMi4ljIRDN5XJ429vehk9/+tNGNAwGg8FgWDIceSO2crmMS5cu4Qc/+AFe+cpXHvVwDoWHHnroqIdgWCC85S1vOeohGBzYZ3h5YZ+344ljk0YxGAwGg8GwnDgWaRSDwWAwGAzLCyMbBoPBYDAYriuMbBgMBoPBYLiuMLJhMBgMBoPhusLIhsFgMBgMhusKIxsGg8FgMBiuK/4/AX+FPLQdDXoAAAAASUVORK5CYII=\n", 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\n", 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\n", 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\n", + "image/png": 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\n", 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\n", 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\n", 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" + "
" ] }, "metadata": {}, @@ -433,7 +320,8 @@ "anat_mean = '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1322/anat/sub-1322_space-MNI152NLin2009cAsym_desc-preproc_T1w.nii.gz'\n", "\n", "plotting.plot_stat_map(t_plot,\n", - " bg_img = anat_mean)\n", + " bg_img = anat_mean,\n", + " cmap = \"RdBu\", colorbar=False) # use RdYlBu because it is negative originally\n", "\n", "plotting.plot_stat_map(t_plot,\n", " bg_img = anat_mean,\n", @@ -456,52 +344,6 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 48, - "metadata": {}, - "outputs": [], - "source": [ - "def threshold(tstat, pstat):\n", - " t_plot = nib.load(tstat)\n", - " p = nib.load(pstat)\n", - " t_plot_data = t_plot.get_data()\n", - " p_data = p.get_data()\n", - " thr = 0.95\n", - " # threshold raw t map by p values\n", - " p_mask = p_data < thr\n", - " t_plot_data[p_mask] = 0\n", - " return(t_plot)" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], "source": [ "# plotting FLAMEO\n", "\n", @@ -516,132 +358,14 @@ }, { "cell_type": "code", - "execution_count": 81, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "ename": "ImageFileError", - "evalue": "Cannot work out file type of \"/\"", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mImageFileError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mdisplay\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplotting\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot_stat_map\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mimg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mthreshold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mbg_img\u001b[0m \u001b[0;34m=\u001b[0m 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\u001b[0mcolorbar\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 677\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 678\u001b[0;31m \u001b[0mimg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_utils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcheck_niimg_3d\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mimg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 679\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 680\u001b[0m \u001b[0;31m# Make sure that add_overlay shows consistent default behavior\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/_utils/niimg_conversions.py\u001b[0m in \u001b[0;36mcheck_niimg_3d\u001b[0;34m(niimg, dtype)\u001b[0m\n\u001b[1;32m 320\u001b[0m \u001b[0mIts\u001b[0m \u001b[0mapplication\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0midempotent\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 321\u001b[0m \"\"\"\n\u001b[0;32m--> 322\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mcheck_niimg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mniimg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mensure_ndim\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 323\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 324\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/_utils/niimg_conversions.py\u001b[0m in \u001b[0;36mcheck_niimg\u001b[0;34m(niimg, ensure_ndim, atleast_4d, dtype, return_iterator, wildcards)\u001b[0m\n\u001b[1;32m 269\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 270\u001b[0m \u001b[0;31m# Otherwise, it should be a filename or a SpatialImage, we load it\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 271\u001b[0;31m \u001b[0mniimg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mload_niimg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mniimg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 272\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 273\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mensure_ndim\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m3\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mniimg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m4\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mniimg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/_utils/niimg.py\u001b[0m in \u001b[0;36mload_niimg\u001b[0;34m(niimg, dtype)\u001b[0m\n\u001b[1;32m 108\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mniimg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_basestring\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 109\u001b[0m \u001b[0;31m# data is a filename, we load it\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 110\u001b[0;31m \u001b[0mniimg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnibabel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mniimg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 111\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mniimg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnibabel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mspatialimages\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSpatialImage\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 112\u001b[0m raise TypeError(\"Data given cannot be loaded because it is\"\n", - "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nibabel/loadsave.py\u001b[0m in \u001b[0;36mload\u001b[0;34m(filename, **kwargs)\u001b[0m\n\u001b[1;32m 51\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 52\u001b[0m raise ImageFileError('Cannot work out file type of \"%s\"' %\n\u001b[0;32m---> 53\u001b[0;31m filename)\n\u001b[0m\u001b[1;32m 54\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 55\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mImageFileError\u001b[0m: Cannot work out file type of \"/\"" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "display = plotting.plot_stat_map(img, threshold = 2,bg_img = anat_mean)\n", "display.add_overlay(pstat)\n", "plotting.show()" ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Analyze difference between groups" - ] - }, - { - "cell_type": "code", - "execution_count": 58, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of Ketamine patients is: 11\n", - "Number of Midazolam patients is: 10\n" - ] - } - ], - "source": [ - "# lets see the difference between groups\n", - "import pandas as pd\n", - "allDat = pd.read_excel('/home/or/Documents/kpe_analyses/KPEIHR0009_data_all_scored.xlsx')\n", - "medDat = allDat[['scr_id','med_cond']]\n", - "medDat.at[17, 'med_cond'] = 1 # change subject 1464 medication to 1\n", - "medDat = medDat.append({'scr_id' : 'KPE1468' , 'med_cond' : 0}, ignore_index=True)\n", - "medDat = medDat.append({'scr_id' : 'KPE1480' , 'med_cond' : 0}, ignore_index=True)\n", - "medDat = medDat.append({'scr_id' : 'KPE1499' , 'med_cond' : 1}, ignore_index=True)\n", - "\n", - "groupList = np.array(medDat['med_cond'])\n", - "groupList.shape\n", - "subjectList = medDat['scr_id']\n", - "ketList = []\n", - "midList = []\n", - "for i in medDat.iterrows():\n", - " sub = i[1].scr_id.split('KPE')[1]\n", - " if i[1].med_cond ==1:\n", - " ketList.append(sub)\n", - " elif i[1].med_cond==0:\n", - " midList.append(sub)\n", - " else:\n", - " print('No medication condition')\n", - "\n", - "print (f'Number of Ketamine patients is: {len(ketList)}')\n", - "print (f'Number of Midazolam patients is: {len(midList)}')" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['008',\n", - " '1223',\n", - " '1293',\n", - " '1307',\n", - " '1315',\n", - " '1322',\n", - " '1339',\n", - " '1343',\n", - " '1387',\n", - " '1464',\n", - " '1499']" - ] - }, - "execution_count": 59, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ketList" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "ket_func_ = ['/media/Data/KPE_results/seed2voxel/MNI_space/trauma_seed_righttAmg_sub-%s_ses-1_z_MNI.nii.gz' % (sub) for sub in ketList]\n", - "ket_func_ses2 = ['/media/Data/KPE_results/seed2voxel/MNI_space/trauma_seed_rightAmg_sub-%s_ses-2_z_MNI.nii.gz' % (sub) for sub in ketList]\n", - "mid_func_ses1 = ['/media/Data/KPE_results/seed2voxel/MNI_space/trauma_seed_righttAmg_sub-%s_ses-1_z_MNI.nii.gz' % (sub) for sub in midList]\n", - "mid_func_ses2 = ['/media/Data/KPE_results/seed2voxel/MNI_space/trauma_seed_rightAmg_sub-%s_ses-2_z_MNI.nii.gz' % (sub) for sub in midList]" - ] } ], "metadata": { diff --git a/task_based_analysis/DiFuMo/.ipynb_checkpoints/analyze_difumo_ts-checkpoint.py b/task_based_analysis/DiFuMo/.ipynb_checkpoints/analyze_difumo_ts-checkpoint.py new file mode 100644 index 0000000..0d93ec3 --- /dev/null +++ b/task_based_analysis/DiFuMo/.ipynb_checkpoints/analyze_difumo_ts-checkpoint.py @@ -0,0 +1,578 @@ +# %% +''' +@author: Or Duek +@date: Jul 16 2020 + +This is a sciprt that uses the nee DiFuMo dictionary +atlas (https://www.sciencedirect.com/science/article/pii/S1053811920306121#appsec7) + +In this file we will create a task based +''' +# %% import libraries +import pandas as pd +from nilearn.input_data import NiftiMapsMasker + +from nilearn import datasets +import numpy as np +import nilearn.plotting +from sklearn.model_selection import StratifiedShuffleSplit +import os +import glob +from nilearn import connectome +import seaborn as sns +import matplotlib.pyplot as plt +# %% Set output folder +output_dir = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/DiFuMo/' +# set session + +## condition labels (ketamine , midazolam) +# read file +medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv') +subject_list = np.array(medication_cond.scr_id) +condition_label = np.array(medication_cond.med_cond) + +group_label = list(map(int, condition_label)) + +# %% +subject_list = subject_list[0:24] # removing 1578 + +# %% fetch atlas +maps_img = '/media/Data/work/DiFuMo_atlas/256/maps.nii.gz' +labels = pd.read_csv('/media/Data/work/DiFuMo_atlas/256/labels_256_dictionary.csv') +#coords = nilearn.plotting.find_parcellation_cut_coords(labels_img=maps_img) +coords = nilearn.plotting.find_probabilistic_atlas_cut_coords(maps_img) +# plot atlas (only if we want) +nilearn.plotting.plot_prob_atlas(maps_img, draw_cross=False) +# %% read files and stratify to relevant script +# method to generate subject array of timeseries +def pooledTS(subject_list, ses): + event_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/sub-{sub}_ses-{ses}_30sec_window.csv' + duration = 60 #set duration of event in seconds + sub_ts = [] + for sub in subject_list: + subject = sub.split('KPE')[1] + + # load the npy file (timeseries) + ts = np.load(output_dir + '/sub-' + subject + '_ses-' + ses + '.npy', allow_pickle=True) + event = event_template.format(sub=subject, ses=ses) + events = pd.read_csv(event, sep='\t') + onset = int(events.onset[events.trial_type_30=='trauma1_0']) # take onset of trauma first script + ts_script = ts[onset:onset+duration, :] + sub_ts.append(ts_script) + return sub_ts +# %% +from nilearn import connectome +connectome = connectome.ConnectivityMeasure( + kind='correlation', vectorize=False) + +mat_ses1 = connectome.fit_transform(pooledTS(subject_list, '1')) + + +# %% plot mean matrix +nilearn.plotting.plot_matrix(connectome.mean_, + colorbar=True, labels= range(256), reorder='average') + +# %% lets run ses 2 +mat_ses2 = connectome.fit_transform(pooledTS(subject_list, '2')) + +nilearn.plotting.plot_matrix(connectome.mean_, + colorbar=True, labels= range(256), reorder='average') + +# %% +nilearn.plotting.plot_connectome(connectome.mean_, coords,black_bg=False, edge_threshold="99.5%") + +# %% +# Plot stength of edges +## plot strength +nilearn.plotting.plot_connectome_strength( + connectome.mean_, coords, title='Connectome strength for DiFuMo atlas' +) + +## just positive +from matplotlib.pyplot import cm + +# plot the positive part of of the matrix +nilearn.plotting.plot_connectome_strength( + np.clip(connectome.mean_, 0, connectome.mean_.max()), coords, cmap=cm.YlOrRd, + title='Strength of the positive edges of the DiFuMo correlation matrix' +) + +# plot the negative part of of the matrix +nilearn.plotting.plot_connectome_strength( + np.clip(connectome.mean_, connectome.mean_.min(), 0), coords, cmap=cm.PuBu, + title='Strength of the negative edges of the DiFuMo correlation matrix' +) + +# %% +# fisher-z transformation +mat_ses1 = np.arctan(mat_ses1) +mat_ses2 = np.arctan(mat_ses2) + +# %% +## Generate matrix of just ROIs (amygdala, hippocampus, vmpfc and caudate) +# get index of each ROI +labels = pd.read_csv('/media/Data/work/DiFuMo_atlas/256/labels_256_dictionary.csv') +labels_list = list(labels.Difumo_names) +amg = labels_list.index('Amygdala') +hippo_post = labels_list.index('Hippocampus posterior') +hippo_ant = labels_list.index('Hippocampus anterior') +vmPFC_ant = labels_list.index('Ventromedial prefrontal cortex anterior') +vmPFC = labels_list.index('Ventromedial prefrontal cortex') +caudate_inf = labels_list.index('Caudate inferior') +caudate_ant = labels_list.index('Caudate anterior') +caudate_sup = labels_list.index('Caudate superior') +index_list = np.array([amg, hippo_post, hippo_ant, vmPFC_ant, vmPFC])#, caudate_ant, caudate_inf, caudate_sup]) + +mat2ROI = mat_ses2[: ,index_list,:] +mat2ROI = mat2ROI[:,:,index_list] + +mat1ROI = mat_ses1[: ,index_list,:] +mat1ROI = mat1ROI[:,:,index_list] + +# %% +mat2ROI.shape +labels = ['amygdala','hippoPost','hippoAnt','vmPFCAnt','vmPFC']#,'Ca_Ant','Ca_In','ca_sup'] +nilearn.plotting.plot_matrix((np.mean(mat2ROI, axis=0)), + colorbar=True, labels= labels, reorder='average') + +nilearn.plotting.plot_matrix((np.mean(mat1ROI, axis=0)), + colorbar=True, labels= labels, reorder='average') + +# %% +# show groups +group_label = np.array(group_label[0:24]) +ketSes2 = mat2ROI[group_label==1] +midSes2 = mat2ROI[group_label==0] + +ketSes1 = mat1ROI[group_label==1] +midSes1 = mat1ROI[group_label==0] + +# %% +group_label + +# %% +## First session +sns.heatmap(np.mean(ketSes1, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Ketamine") +plt.show() + +sns.heatmap(np.mean(midSes1, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Midazolam") + +# %% +np.mean(ketSes1, axis=0) +# get 5-95% percentiles for amg-hippPost +amgH = ketSes2[:,3,2] + +np.percentile(amgH,[.05,95], axis=0) +#amgH + +# %% +amgH = midSes2[:,3,2] + +np.percentile(amgH,[.05,95], axis=0) +#amgH + +# %% +sns.heatmap(np.mean(ketSes2, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Ketamine") +plt.show() + +sns.heatmap(np.mean(midSes2, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Midazolam") + + +# %% +import scipy +t, p = scipy.stats.ttest_ind(ketSes2, midSes2) +tArr = np.array(t) +thr = 0.05 +tArr[p>thr] = 0 +sns.heatmap(tArr, xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) + +# %% +p + +# %% +# now compare difference between ses1 and 2 for those groups +# divide matrix of 1ses to groups +#group_label = group_label[0:24] +ketSes1 = mat1ROI[group_label==1] +midSes1 = mat1ROI[group_label==0] + +# run simple t test to show whats going on +t, p = scipy.stats.ttest_ind(ketSes1, midSes1) +tArr = np.array(t) +tArr[p>thr] = 0 +sns.heatmap(tArr, xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) + +# %% +# create delta arrays +ketDelta = np.subtract(ketSes2, ketSes1) +midDelta = np.subtract(midSes2, midSes1) +sns.heatmap(np.mean(ketDelta, axis=0), + cmap='coolwarm', xticklabels=labels, + yticklabels=labels, annot=True, vmin = -1, vmax = 1) +plt.show() +sns.heatmap(np.mean(midDelta, axis=0), cmap='coolwarm', + xticklabels=labels, yticklabels=labels, annot=True, vmin=-1, vmax=1) +plt.show() + + +# %% +t, p = scipy.stats.ttest_ind(ketDelta, midDelta) +tArr = np.array(t) +fdr = sm.multitest.fdrcorrection(p, alpha=0.05, method='indep', is_sorted=True) +#fdr = sm.multitest.multipletests(pvec, alpha=thr, method='fdr_bh') +print(fdr[0]) +tArr[fdr[1]>.05] = 0 +print(tArr) +sns.heatmap(tArr, xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) + +# %% +print(1/10*0.30) +p + +# %% +# lets run NBS +ketDeltaReshape = np.moveaxis(np.array(ketDelta),0,-1) +midDeltaReshape = np.moveaxis(np.array(midDelta),0,-1) + +ketSes2_reshape = np.moveaxis(np.array(ketSes2),0,-1) +midSes2_reshape = np.moveaxis(np.array(midSes2),0,-1) +print(ketDeltaReshape.shape) +print(midDeltaReshape.shape) +from bct import nbs + +# we compare ket1 and ket3 +pval, adj, _ = nbs.nbs_bct(ketDeltaReshape, midDeltaReshape, thresh=2.3, tail='both',k=1000, + paired=False, verbose = False) +print(pval) + +# %% +# ok lets threshold using adjacency +#tTresh = t[np.tril(adj)] +tTresh = t* adj +#tTresh[np.triu(tTresh)] = t +sns.heatmap(tTresh, xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) +plt.show() +sns.heatmap(np.mean(ketDelta, axis=0), xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) +plt.show() +sns.heatmap(np.mean(midDelta, axis=0), xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) + +# %% +sns.barplot() + +# %% [markdown] +# ## Create a dataframe to test correlation between amygdala, hippocampus (vmPFC) in groups and session (1,2) + +# %% +dfCors = pd.DataFrame({'amg_hippPost2': mat2ROI[:,0,1], 'amg_vmPFC2': mat2ROI[:,0,4], + 'amg_hippPost1': mat1ROI[:,0,1], 'amg_vmPFC1': mat1ROI[:,0,4], + 'amg_hippAnt2': mat2ROI[:,0,2], 'amg_HippAnt1': mat1ROI[:,0,2], + 'amg_vmPFCAnt2': mat2ROI[:,0,3], 'amg_vmPFCAnt1': mat1ROI[:,0,3], + 'hippAnt_vmPFCAnt2' : mat2ROI[:,2,3], + 'hippAnt_vmPFCAnt1' : mat1ROI[:,2,3], + 'hippAnt_hippPost1': mat1ROI[:, 1,2], + 'hippAnt_hippPost2': mat2ROI[:, 1,2] + }) +dfCors['groupIdx'] = group_label[0:24] +dfCors['amg_hipp_change'] = dfCors.amg_hippPost2 - dfCors.amg_hippPost1 +dfCors['amg_hippAnt_change'] = dfCors.amg_hippAnt2 - dfCors.amg_HippAnt1 +dfCors['amg_vmpfcAnt_change'] = dfCors.amg_vmPFCAnt2 - dfCors.amg_vmPFCAnt1 +dfCors['amg_vmpfc_change'] = dfCors.amg_vmPFC2 - dfCors.amg_vmPFC1 +dfCors['hippoAnt_vmpfcAnt_change'] = dfCors.hippAnt_vmPFCAnt2 - dfCors.hippAnt_vmPFCAnt1 +dfCors['hippoAnt_hippPost_change'] = dfCors.hippAnt_hippPost2 - dfCors.hippAnt_hippPost1 + +dfCors + +# %% +# add group condition +group = {1:'ketamine', 0:'midazolam'} +dfCors['group'] =[group[item] for item in dfCors.groupIdx] + +# %% +## create plot for publication +fig, (ax1, ax2) = plt.subplots(1,2, figsize=(8,5),gridspec_kw={'wspace': .05}) +g1 = sns.boxplot(y = 'amg_hipp_change', x= 'group', data=dfCors, ax=ax1, + boxprops=dict(alpha=.4)) +sns.stripplot(y = 'amg_hipp_change', x= 'group', data=dfCors,size=8, ax=ax1) +ax1.text(-.4,0.8, "Amygdala-Posterior Hippocampus") +g2 = sns.boxplot(y = 'hippoAnt_vmpfcAnt_change', x= 'group', data=dfCors, ax=ax2, + boxprops=dict(alpha=.4)) +sns.stripplot(y = 'hippoAnt_vmpfcAnt_change', x= 'group', data=dfCors, size=8, ax=ax2) +ax2.text(-.4,0.8, "Anterior Hippocampus - vmPFC") +# g3 = sns.boxplot(y = 'hippoAnt_hippPost_change', x= 'group', data=dfCors, ax=ax3, +# boxprops=dict(alpha=.4)) +# sns.stripplot(y = 'hippoAnt_hippPost_change', x= 'group', data=dfCors,size=8, ax=ax3) +# ax3.text(-.4,0.8, "Anterior-Posterior Hippocampus") +ylow = -0.9 +yhigh=0.9 +ax1.set_ylim(ylow,yhigh) +ax2.set_ylim(ylow,yhigh) +#ax3.set_ylim(ylow,yhigh) +ax1.set_xlabel("") +ax2.set_xlabel("") +#ax3.set_xlabel("") +ax2.set_yticks([]) +#ax3.yaxis.tick_right() +ax1.set_ylabel("Difference before/after treatment", fontsize=14) +ax2.set_ylabel("") +#ax3.set_ylabel("") +ax1.set_xticklabels(['Ketamine', 'Midazolam'], fontsize=14) +ax2.set_xticklabels(['Ketamine', 'Midazolam'], fontsize=14) +#ax3.set_xticklabels(['Ketamine', 'Midazolam'], fontsize=14) +fig.savefig("changeCorrelation.png", dpi=300, bbox_inches='tight') + +# %% [markdown] +# ## Use PyMC3 to compare the difference in correlation + +# %% +# Using Pymc3 +import pymc3 as pm +from pymc3.glm import GLM + +with pm.Model() as model_glm: + GLM.from_formula('amg_hipp_change ~ groupIdx', dfCors) + trace = pm.sample(draws=4000, tune=3000) + +# %% +pm.summary(trace, credible_interval=.95).round(2) + +# %% +# Using Pymc3 - compare antrior hippo and antvmpfc +with pm.Model() as model_glm2: + GLM.from_formula('hippoAnt_vmpfcAnt_change ~ groupIdx', dfCors) + trace2 = pm.sample(draws=4000, tune=2000) + +# %% +pm.summary(trace2, credible_interval=.95).round(2) + +# %% + +# %% +sns.boxplot(y = 'amg_hipp_change', x= 'groupIdx', data=dfCors) +scipy.stats.ttest_ind(dfCors.amg_hipp_change[dfCors.groupIdx==1],dfCors.amg_hipp_change[dfCors.groupIdx==0]) + +# %% +sns.boxplot(y = 'hippoAnt_vmpfcAnt_change', x= 'groupIdx', data=dfCors) +scipy.stats.ttest_ind(dfCors.hippoAnt_vmpfcAnt_change[dfCors.groupIdx==1], + dfCors.hippoAnt_vmpfcAnt_change[dfCors.groupIdx==0]) + +# %% +sns.boxplot(y = 'hippoAnt_hippPost_change', x= 'groupIdx', data=dfCors) +scipy.stats.ttest_ind(dfCors.hippoAnt_hippPost_change[dfCors.groupIdx==1],dfCors.hippoAnt_hippPost_change[dfCors.groupIdx==0]) + +# %% +# lets plot that on the brain +coordsROI = coords[index_list, :] + +#nilearn.plotting.plot_connectome(tTresh,coordsROI) +nilearn.plotting.view_connectome(tTresh,coordsROI) + +# %% [markdown] +# ## calculating correlations with amygdala for behavioral correlations + +# %% Run through and extract correlation of each edge here +labels = pd.read_csv('/media/Data/work/DiFuMo_atlas/256/labels_256_dictionary.csv') +def makeConnDF(mat, subject_list, labels_list = list(labels.Difumo_names)): + # takes array (Nsubject X Nodes X Nodes) and returns a dataframe of connectivity between + # inputs: mat = array (subjectXNodesXNodes) + # subject list + # labels list (Difumo atlas) + # Amygdala, hippocampus (posterior/anterior), vmPFC (and antrior), caudate (inferior, superior and anterior) + # + # Behaviour correlation - get indexes of Amygdala, Hippocampus and vmPFC + + amg = labels_list.index('Amygdala') + hippo_post = labels_list.index('Hippocampus posterior') + hippo_ant = labels_list.index('Hippocampus anterior') + vmPFC_ant = labels_list.index('Ventromedial prefrontal cortex anterior') + vmPFC = labels_list.index('Ventromedial prefrontal cortex') + caudate_inf = labels_list.index('Caudate inferior') + caudate_ant = labels_list.index('Caudate anterior') + caudate_sup = labels_list.index('Caudate superior') + scr_id = [] + amg_hippPost = [] + amg_hippAnt = [] + amg_vmPFC = [] + amg_vmPFCant = [] + amg_caudInf = [] + amg_caudAnt = [] + amg_caudSup = [] + for i, sub in enumerate(subject_list): + scr_id.append(sub) + amg_hippPost.append(mat[i,amg,hippo_post]) + amg_hippAnt.append(mat[i,amg,hippo_ant]) + amg_vmPFC.append(mat[i,amg,vmPFC]) + amg_vmPFCant.append(mat[i,amg,vmPFC_ant]) + amg_caudInf.append(mat[i, amg, caudate_inf]) + amg_caudAnt.append(mat[i, amg, caudate_ant]) + amg_caudSup.append(mat[i, amg, caudate_sup]) + # create dataframe from that + corDF = pd.DataFrame({'scr_id':scr_id, 'group':group_label, 'amg_hippPost': amg_hippPost, + 'amg_hippAnt':amg_hippAnt, 'amg_vmPFC':amg_vmPFC, 'amg_vmPFCant': amg_vmPFCant, + 'amg_caudAnt': amg_caudAnt, 'amg_caudInf': amg_caudInf, 'amg_caudSup': amg_caudSup}) + return corDF +# %% +labels + +# %% +pclDf = pd.read_csv('/home/or/Documents/kpe_analyses/KPEIHR0009_DATA_2020-08-31_1301.csv') +# take only KPE patients +pclDf['scr_id'] = pclDf['scr_id'].str.replace(" ","") +pclDf = pclDf[pclDf['scr_id'].str.startswith('KPE')] +dfP = pd.DataFrame({'subject': pclDf['scr_id']}) +dfP_PCL = pclDf[['scr_id','redcap_event_name','pcl5_1', 'pcl5_2', 'pcl5_3', 'pcl5_4', 'pcl5_5', 'pcl5_6', 'pcl5_7', + 'pcl5_8', 'pcl5_9', 'pcl5_10', 'pcl5_11', 'pcl5_12', 'pcl5_13', 'pcl5_14', 'pcl5_15', 'pcl5_16', 'pcl5_17', + 'pcl5_18', 'pcl5_19', 'pcl5_20']] +# remove NAs +dfP_PCL = dfP_PCL.dropna() +# set list of columns for analysis +colList = list(dfP_PCL) +colList.remove('scr_id') +colList.remove('redcap_event_name') +# set total pcl scores +dfP_PCL['pclTotal'] = dfP_PCL[colList].sum(axis=1) +sns.distplot(dfP_PCL.pclTotal) +# reshape it to wide +df2=dfP_PCL.pivot(index = 'scr_id',columns='redcap_event_name', values='pclTotal') +list(df2) +df2 = df2.rename(columns={"30_day_follow_up_s_arm_1": "Days30", "90_day_follow_up_s_arm_1": "90Days", + "screening_selfrepo_arm_1": "Screening", "visit_1_arm_1": "Visit1", + "visit_7_week_follo_arm_1": "Visit7"}) +#df2['scr_id'] = dfP_PCL['scr_id'] +df2 + + +# %% Call makeDF function on session 1 and 2 +dfSes1 = makeConnDF(mat_ses1, subject_list) + +# %% ses 2 +dfSes2 = makeConnDF(mat_ses2, subject_list) + + + + +# %% +# merging two data frames toghether +dfTest = pd.merge(dfSes2, df2, on = 'scr_id') +# create difference pcl score +dfTest['days30_1'] = dfTest['Days30'] - dfTest.Visit1 +dfTest['days30_s'] = dfTest['Days30'] - dfTest.Screening +dfTest['days7_1'] = dfTest['Visit7'] - dfTest.Visit1 +dfTest + +# %% +import scipy +sns.lmplot(x='amg_hippAnt',y='Days30',hue='group', data=dfTest) +naMask = np.isnan(dfTest['Days30']) +scipy.stats.pearsonr(dfTest['Days30'][~naMask], dfTest['amg_hippAnt'][~naMask]) + +# %% +#compare correlations of only ketamine and only midazolam +ketCorr = scipy.stats.pearsonr(dfTest['Visit7'][~naMask][dfTest.group==1], dfTest['amg_hippPost'][~naMask][dfTest.group==1]) +midCorr = scipy.stats.pearsonr(dfTest['Visit7'][~naMask][dfTest.group==0], dfTest['amg_hippPost'][~naMask][dfTest.group==0]) + +from corrstats import independent_corr +checkCorr = independent_corr(ketCorr[0], midCorr[0], n=11, n2 = 10, twotailed=True, conf_level=0.95, method='fisher') +print(f'Correlation difference between CC and PTSD with anhedonia is {checkCorr}') + + +# %% +sns.lmplot(x='amg_vmPFC',y='Visit7',hue='group', data=dfTest) +naMask = np.isnan(dfTest['Visit7']) +scipy.stats.pearsonr(dfTest['Visit7'][~naMask], dfTest['amg_vmPFC'][~naMask]) + +# %% Caudate? +sns.lmplot(x='amg_caudSup',y='Days30',hue='group', data=dfTest) +naMask = np.isnan(dfTest['Days30']) +scipy.stats.pearsonr(dfTest['Days30'][~naMask], dfTest['amg_caudSup'][~naMask]) + +##### +# %% [markdown] +# ### So it seems like there's a general positive correlation between symptoms at 30 days and connectivity between amgygdala and +# ### hippocampus. While we see a general negative correlation between amg-vmPFC connectivity. +# #### But - it seems like we have group differences - lets check the interaction of group and each of them + +# %% +# amg and hippocampus +import statsmodels.formula.api as smf + +model = smf.ols(formula='Visit7 ~ group * amg_hippPost', data=dfTest) +res = model.fit() +print(res.summary()) + +# %% [markdown] +# ### Indeed we see an interaction between the group and the correlation. + +# %% Now for vmPFC +modelvmPFC = smf.ols(formula='days30_scale ~ group * amg_vmPFC', data=dfTest) +resVMpfc = modelvmPFC.fit() +print(resVMpfc.summary()) + +# %% Now we should check the delta in all of these association and the correlation to +# Using Pymc3 +import pymc3 as pm +from pymc3.glm import GLM + +with pm.Model() as model_glm: + GLM.from_formula('days30_scale ~ group * scaleamgHipp', dfTest) + trace = pm.sample(draws=4000, tune=3000) + +# %% +pm.summary(trace, credible_interval=.95).round(2) + +# %% +# lets scale everything +dfTest['scaleamgHipp'] = (dfTest.amg_hippPost - dfTest.amg_hippPost.mean()) / dfTest.amg_hippPost.std() + + +# %% +dfTest['days30_scale'] = (dfTest.Days30 - dfTest.Days30.mean()) / dfTest.Days30.std() +dfTest['Visit7_scale'] = (dfTest.Visit7 - dfTest.Visit7.mean()) / dfTest.Visit7.std() + +# %% +# Creating a delta between connectivity of second - first session +dfTest['amg_HippPost_Change'] = dfSes2.amg_hippPost - dfSes1.amg_hippPost + +# %% +sns.lmplot(x='amg_HippPost_Change',y='days30_1',hue='group', data=dfTest) +naMask = np.isnan(dfTest['days30_1']) +scipy.stats.pearsonr(dfTest['days30_1'][~naMask], dfTest['amg_HippPost_Change'][~naMask]) + +# %% +model_delta = smf.ols(formula='days30_1 ~ group *amg_HippPost_Change', data=dfTest) +resdelta = model_delta.fit() +print(resdelta.summary()) + + +# %% +# check changes in connectivity between amygdala and hippocampus +sns.stripplot(y='amg_HippPost_Change', x='group', data=dfTest) +scipy.stats.ttest_ind(dfTest['amg_hippPost'][~naMask][dfTest.group==0], dfTest['amg_hippPost'][~naMask][dfTest.group==1]) + +# %% [markdown] +# ## Check correlation with SCR + +# %% +scr = pd.read_csv('/home/or/kpe_task_analysis/scr_deltas.csv') +scr1 = scr.drop(columns = ['med_cond', 'groupIdx']) +scr1 + +# %% +dfMerge = pd.merge(dfTest, scr1) +dfMerge + + +# %% +sns.lmplot('amg_hippPost', 'Trauma_2vs1',hue='group',data=dfMerge) +#scipy.stats.pearsonr(dfMerge.days7_1, dfMerge.Trauma_2vs1) diff --git a/task_based_analysis/DiFuMo/.ipynb_checkpoints/difumo_script-checkpoint.py b/task_based_analysis/DiFuMo/.ipynb_checkpoints/difumo_script-checkpoint.py new file mode 100644 index 0000000..07029e9 --- /dev/null +++ b/task_based_analysis/DiFuMo/.ipynb_checkpoints/difumo_script-checkpoint.py @@ -0,0 +1,108 @@ +# %% +''' +@author: Or Duek +@date: Jul 16 2020 + +This is a sciprt that uses the nee DiFuMo dictionary +atlas (https://www.sciencedirect.com/science/article/pii/S1053811920306121#appsec7) + +In this file we will create a task based +''' +# %% import libraries +import pandas as pd +from nilearn.input_data import NiftiMapsMasker +from nilearn import connectome +from nilearn import datasets +import numpy as np +import nilearn.plotting +from sklearn.model_selection import StratifiedShuffleSplit +import os +import glob +from nilearn import connectome +import seaborn as sns +import dask +# %% Set output folder +output_dir = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/DiFuMo/' +# set session +ses= '1' # session is a string +# %% Functions +# extract RS data and create vector for each subject +def removeVars (confoundFile): + # this method takes the csv regressors file (from fmriPrep) and chooses a few to confound. You can change those few + import pandas as pd + confound = pd.read_csv(confoundFile,sep="\t", na_values="n/a") + finalConf = confound[['csf', 'white_matter', 'framewise_displacement', + 'a_comp_cor_00', 'a_comp_cor_01', 'a_comp_cor_02', 'a_comp_cor_03', + 'a_comp_cor_04', 'a_comp_cor_05', 'trans_x', 'trans_y', 'trans_z', + 'rot_x', 'rot_y', 'rot_z']] # can add 'global_signal' also ,, + # + # change NaN of FD to zero + finalConf = np.array(finalConf.fillna(0.0)) + return finalConf + + +# %% functional files +subject_list = ['008','1223','1253','1263','1293','1307','1315','1322','1339','1343','1351','1356','1364','1369' + ,'1387','1390','1403','1464', '1468', '1480', '1499'] + +func_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{session}/func/sub-{sub}_ses-{session}_task-Memory_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz' +confound_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{session}/func/sub-{sub}_ses-{session}_task-Memory_desc-confounds_regressors.tsv' + +## condition labels (ketamine , midazolam) +# read file +medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv') +subject_list = np.array(medication_cond.scr_id) +condition_label = np.array(medication_cond.med_cond) + +group_label = list(map(int, condition_label)) +# %% +# create a mean mask of all subjects +# load mask of brain + + +brainmasks = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-*/ses-%s/func/sub-*_ses-%s_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz' %(ses,ses)) +print(brainmasks) +# %matplotlib inline +#for mask in brainmasks: + # nilearn.plotting.plot_roi(mask) + +mean_mask = nilearn.image.mean_img(brainmasks) +#nilearn.plotting.plot_stat_map(mean_mask) +group_mask = nilearn.image.math_img("a>=0.95", a=mean_mask) +#nilearn.plotting.plot_roi(group_mask) + +# %% fetch atlas +maps_img = '/media/Data/work/DiFuMo_atlas/256/maps.nii.gz' +labels = pd.read_csv('/media/Data/work/DiFuMo_atlas/256/labels_256_dictionary.csv') +#coords = nilearn.plotting.find_parcellation_cut_coords(labels_img=maps_img) +coords = nilearn.plotting.find_probabilistic_atlas_cut_coords(maps_img) +# generate time series +# +mask_params = { 'mask_img': group_mask, + 'detrend': True, 'standardize': True, + 'high_pass': 0.01, 'low_pass': 0.1, 't_r': 1, + 'smoothing_fwhm': 6., + 'verbose': 5} + +masker = NiftiMapsMasker(maps_img=maps_img, **mask_params) + +# %% Generate npy files of timeseries for each subject per session +# we will use it later on, stratify to scripts etc. +# build a specific folder +try: + os.makedirs(output_dir) +except: + print('Folder already exist') + +subject_ts = [] +for sub in subject_list: + print(f' Analysing subject {sub}') + subject = sub.split('KPE')[1] + func = func_template.format(sub=subject, session=ses) + confound = confound_template.format(sub=subject, session=ses) + signals = masker.fit_transform(imgs=func, confounds=removeVars(confound)) + save = np.save(output_dir + 'sub-' + subject + '_ses-' + ses, signals) + subject_ts.append(signals) + + + diff --git a/task_based_analysis/DiFuMo/__pycache__/corrstats.cpython-37.pyc b/task_based_analysis/DiFuMo/__pycache__/corrstats.cpython-37.pyc new file mode 100644 index 0000000..e270992 Binary files /dev/null and b/task_based_analysis/DiFuMo/__pycache__/corrstats.cpython-37.pyc differ diff --git a/task_based_analysis/DiFuMo/analyze_difumo_ts.py b/task_based_analysis/DiFuMo/analyze_difumo_ts.py index 04d560b..0d93ec3 100644 --- a/task_based_analysis/DiFuMo/analyze_difumo_ts.py +++ b/task_based_analysis/DiFuMo/analyze_difumo_ts.py @@ -1,3 +1,4 @@ +# %% ''' @author: Or Duek @date: Jul 16 2020 @@ -7,10 +8,10 @@ In this file we will create a task based ''' -#%% import libraries +# %% import libraries import pandas as pd from nilearn.input_data import NiftiMapsMasker -from nilearn import connectome + from nilearn import datasets import numpy as np import nilearn.plotting @@ -19,10 +20,10 @@ import glob from nilearn import connectome import seaborn as sns -#%% Set output folder +import matplotlib.pyplot as plt +# %% Set output folder output_dir = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/DiFuMo/' # set session -ses= '1' # session is a string ## condition labels (ketamine , midazolam) # read file @@ -32,49 +33,59 @@ group_label = list(map(int, condition_label)) -#%% fetch atlas +# %% +subject_list = subject_list[0:24] # removing 1578 + +# %% fetch atlas maps_img = '/media/Data/work/DiFuMo_atlas/256/maps.nii.gz' labels = pd.read_csv('/media/Data/work/DiFuMo_atlas/256/labels_256_dictionary.csv') #coords = nilearn.plotting.find_parcellation_cut_coords(labels_img=maps_img) coords = nilearn.plotting.find_probabilistic_atlas_cut_coords(maps_img) - -#%% read files and stratify to relevant script +# plot atlas (only if we want) +nilearn.plotting.plot_prob_atlas(maps_img, draw_cross=False) +# %% read files and stratify to relevant script +# method to generate subject array of timeseries +def pooledTS(subject_list, ses): + event_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/sub-{sub}_ses-{ses}_30sec_window.csv' + duration = 60 #set duration of event in seconds + sub_ts = [] + for sub in subject_list: + subject = sub.split('KPE')[1] + + # load the npy file (timeseries) + ts = np.load(output_dir + '/sub-' + subject + '_ses-' + ses + '.npy', allow_pickle=True) + event = event_template.format(sub=subject, ses=ses) + events = pd.read_csv(event, sep='\t') + onset = int(events.onset[events.trial_type_30=='trauma1_0']) # take onset of trauma first script + ts_script = ts[onset:onset+duration, :] + sub_ts.append(ts_script) + return sub_ts +# %% +from nilearn import connectome connectome = connectome.ConnectivityMeasure( - kind='correlation', vectorize=False) -# set events file template - here we can choose either whole scripts (120seconds each) or just part of -event_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/sub-{sub}_ses-{ses}_30sec_window.csv' -duration = 120 #set duration of event in seconds -mat = [] -for sub in subject_list: - subject = sub.split('KPE')[1] - - # load the npy file (timeseries) - ts = np.load(output_dir + '/sub-' + subject + '_ses-' + ses + '.npy', allow_pickle=True) - event = event_template.format(sub=subject, ses=ses) - events = pd.read_csv(event, sep='\t') - onset = int(events.onset[events.trial_type_30=='trauma1_0']) # take onset of trauma first script - ts_script = ts[onset:onset+duration, :] - mat.append(connectome.fit_transform([ts_script])[0]) +mat_ses1 = connectome.fit_transform(pooledTS(subject_list, '1')) -mat = np.array(mat) -mat.shape -meanMat = np.mean(mat, axis=0) -# %% -nilearn.plotting.plot_matrix(meanMat, - colorbar=True) +# %% plot mean matrix +nilearn.plotting.plot_matrix(connectome.mean_, + colorbar=True, labels= range(256), reorder='average') + +# %% lets run ses 2 +mat_ses2 = connectome.fit_transform(pooledTS(subject_list, '2')) +nilearn.plotting.plot_matrix(connectome.mean_, + colorbar=True, labels= range(256), reorder='average') # %% -nilearn.plotting.plot_connectome(meanMat, coords,black_bg=True, edge_threshold="99%") +nilearn.plotting.plot_connectome(connectome.mean_, coords,black_bg=False, edge_threshold="99.5%") # %% # Plot stength of edges ## plot strength nilearn.plotting.plot_connectome_strength( - meanMat, coords, title='Connectome strength for DiFuMo atlas' + connectome.mean_, coords, title='Connectome strength for DiFuMo atlas' ) ## just positive @@ -82,41 +93,342 @@ # plot the positive part of of the matrix nilearn.plotting.plot_connectome_strength( - np.clip(meanMat, 0, meanMat.max()), coords, cmap=cm.YlOrRd, + np.clip(connectome.mean_, 0, connectome.mean_.max()), coords, cmap=cm.YlOrRd, title='Strength of the positive edges of the DiFuMo correlation matrix' ) # plot the negative part of of the matrix nilearn.plotting.plot_connectome_strength( - np.clip(meanMat, meanMat.min(), 0), coords, cmap=cm.PuBu, + np.clip(connectome.mean_, connectome.mean_.min(), 0), coords, cmap=cm.PuBu, title='Strength of the negative edges of the DiFuMo correlation matrix' ) -#%% -# Behaviour correlation - get indexes of Amygdala, Hippocampus and vmPFC + +# %% +# fisher-z transformation +mat_ses1 = np.arctan(mat_ses1) +mat_ses2 = np.arctan(mat_ses2) + +# %% +## Generate matrix of just ROIs (amygdala, hippocampus, vmpfc and caudate) +# get index of each ROI +labels = pd.read_csv('/media/Data/work/DiFuMo_atlas/256/labels_256_dictionary.csv') labels_list = list(labels.Difumo_names) amg = labels_list.index('Amygdala') hippo_post = labels_list.index('Hippocampus posterior') hippo_ant = labels_list.index('Hippocampus anterior') vmPFC_ant = labels_list.index('Ventromedial prefrontal cortex anterior') vmPFC = labels_list.index('Ventromedial prefrontal cortex') -#%% Run through and extract correlation of each edge here -scr_id = [] -amg_hippPost = [] -amg_hippAnt = [] -amg_vmPFC = [] -amg_vmPFCant = [] -for i, sub in enumerate(subject_list): - scr_id.append(sub) - amg_hippPost.append(mat[i,amg,hippo_post]) - amg_hippAnt.append(mat[i,amg,hippo_ant]) - amg_vmPFC.append(mat[i,amg,vmPFC]) - amg_vmPFCant.append(mat[i,amg,vmPFC_ant]) -# create dataframe from that -corDF = pd.DataFrame({'scr_id':scr_id, 'group':group_label, 'amg_hippPost': amg_hippPost, -'amg_hippAnt':amg_hippAnt, 'amg_vmPFC':amg_vmPFC, 'amg_vmPFCant': amg_vmPFCant}) -# %% -pclDf = pd.read_csv('/home/or/Documents/kpe_analyses/KPEIHR0009_DATA_2019-10-07_1121.csv') +caudate_inf = labels_list.index('Caudate inferior') +caudate_ant = labels_list.index('Caudate anterior') +caudate_sup = labels_list.index('Caudate superior') +index_list = np.array([amg, hippo_post, hippo_ant, vmPFC_ant, vmPFC])#, caudate_ant, caudate_inf, caudate_sup]) + +mat2ROI = mat_ses2[: ,index_list,:] +mat2ROI = mat2ROI[:,:,index_list] + +mat1ROI = mat_ses1[: ,index_list,:] +mat1ROI = mat1ROI[:,:,index_list] + +# %% +mat2ROI.shape +labels = ['amygdala','hippoPost','hippoAnt','vmPFCAnt','vmPFC']#,'Ca_Ant','Ca_In','ca_sup'] +nilearn.plotting.plot_matrix((np.mean(mat2ROI, axis=0)), + colorbar=True, labels= labels, reorder='average') + +nilearn.plotting.plot_matrix((np.mean(mat1ROI, axis=0)), + colorbar=True, labels= labels, reorder='average') + +# %% +# show groups +group_label = np.array(group_label[0:24]) +ketSes2 = mat2ROI[group_label==1] +midSes2 = mat2ROI[group_label==0] + +ketSes1 = mat1ROI[group_label==1] +midSes1 = mat1ROI[group_label==0] + +# %% +group_label + +# %% +## First session +sns.heatmap(np.mean(ketSes1, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Ketamine") +plt.show() + +sns.heatmap(np.mean(midSes1, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Midazolam") + +# %% +np.mean(ketSes1, axis=0) +# get 5-95% percentiles for amg-hippPost +amgH = ketSes2[:,3,2] + +np.percentile(amgH,[.05,95], axis=0) +#amgH + +# %% +amgH = midSes2[:,3,2] + +np.percentile(amgH,[.05,95], axis=0) +#amgH + +# %% +sns.heatmap(np.mean(ketSes2, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Ketamine") +plt.show() + +sns.heatmap(np.mean(midSes2, axis=0), annot=True, + xticklabels = labels, yticklabels = labels, + vmin = -1, vmax = 1, cmap='coolwarm') +plt.title("Midazolam") + + +# %% +import scipy +t, p = scipy.stats.ttest_ind(ketSes2, midSes2) +tArr = np.array(t) +thr = 0.05 +tArr[p>thr] = 0 +sns.heatmap(tArr, xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) + +# %% +p + +# %% +# now compare difference between ses1 and 2 for those groups +# divide matrix of 1ses to groups +#group_label = group_label[0:24] +ketSes1 = mat1ROI[group_label==1] +midSes1 = mat1ROI[group_label==0] + +# run simple t test to show whats going on +t, p = scipy.stats.ttest_ind(ketSes1, midSes1) +tArr = np.array(t) +tArr[p>thr] = 0 +sns.heatmap(tArr, xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) + +# %% +# create delta arrays +ketDelta = np.subtract(ketSes2, ketSes1) +midDelta = np.subtract(midSes2, midSes1) +sns.heatmap(np.mean(ketDelta, axis=0), + cmap='coolwarm', xticklabels=labels, + yticklabels=labels, annot=True, vmin = -1, vmax = 1) +plt.show() +sns.heatmap(np.mean(midDelta, axis=0), cmap='coolwarm', + xticklabels=labels, yticklabels=labels, annot=True, vmin=-1, vmax=1) +plt.show() + + +# %% +t, p = scipy.stats.ttest_ind(ketDelta, midDelta) +tArr = np.array(t) +fdr = sm.multitest.fdrcorrection(p, alpha=0.05, method='indep', is_sorted=True) +#fdr = sm.multitest.multipletests(pvec, alpha=thr, method='fdr_bh') +print(fdr[0]) +tArr[fdr[1]>.05] = 0 +print(tArr) +sns.heatmap(tArr, xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) + +# %% +print(1/10*0.30) +p + +# %% +# lets run NBS +ketDeltaReshape = np.moveaxis(np.array(ketDelta),0,-1) +midDeltaReshape = np.moveaxis(np.array(midDelta),0,-1) + +ketSes2_reshape = np.moveaxis(np.array(ketSes2),0,-1) +midSes2_reshape = np.moveaxis(np.array(midSes2),0,-1) +print(ketDeltaReshape.shape) +print(midDeltaReshape.shape) +from bct import nbs + +# we compare ket1 and ket3 +pval, adj, _ = nbs.nbs_bct(ketDeltaReshape, midDeltaReshape, thresh=2.3, tail='both',k=1000, + paired=False, verbose = False) +print(pval) + +# %% +# ok lets threshold using adjacency +#tTresh = t[np.tril(adj)] +tTresh = t* adj +#tTresh[np.triu(tTresh)] = t +sns.heatmap(tTresh, xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) +plt.show() +sns.heatmap(np.mean(ketDelta, axis=0), xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) +plt.show() +sns.heatmap(np.mean(midDelta, axis=0), xticklabels=labels, yticklabels=labels, cmap='coolwarm', annot=True) + +# %% +sns.barplot() + +# %% [markdown] +# ## Create a dataframe to test correlation between amygdala, hippocampus (vmPFC) in groups and session (1,2) + +# %% +dfCors = pd.DataFrame({'amg_hippPost2': mat2ROI[:,0,1], 'amg_vmPFC2': mat2ROI[:,0,4], + 'amg_hippPost1': mat1ROI[:,0,1], 'amg_vmPFC1': mat1ROI[:,0,4], + 'amg_hippAnt2': mat2ROI[:,0,2], 'amg_HippAnt1': mat1ROI[:,0,2], + 'amg_vmPFCAnt2': mat2ROI[:,0,3], 'amg_vmPFCAnt1': mat1ROI[:,0,3], + 'hippAnt_vmPFCAnt2' : mat2ROI[:,2,3], + 'hippAnt_vmPFCAnt1' : mat1ROI[:,2,3], + 'hippAnt_hippPost1': mat1ROI[:, 1,2], + 'hippAnt_hippPost2': mat2ROI[:, 1,2] + }) +dfCors['groupIdx'] = group_label[0:24] +dfCors['amg_hipp_change'] = dfCors.amg_hippPost2 - dfCors.amg_hippPost1 +dfCors['amg_hippAnt_change'] = dfCors.amg_hippAnt2 - dfCors.amg_HippAnt1 +dfCors['amg_vmpfcAnt_change'] = dfCors.amg_vmPFCAnt2 - dfCors.amg_vmPFCAnt1 +dfCors['amg_vmpfc_change'] = dfCors.amg_vmPFC2 - dfCors.amg_vmPFC1 +dfCors['hippoAnt_vmpfcAnt_change'] = dfCors.hippAnt_vmPFCAnt2 - dfCors.hippAnt_vmPFCAnt1 +dfCors['hippoAnt_hippPost_change'] = dfCors.hippAnt_hippPost2 - dfCors.hippAnt_hippPost1 + +dfCors + +# %% +# add group condition +group = {1:'ketamine', 0:'midazolam'} +dfCors['group'] =[group[item] for item in dfCors.groupIdx] + +# %% +## create plot for publication +fig, (ax1, ax2) = plt.subplots(1,2, figsize=(8,5),gridspec_kw={'wspace': .05}) +g1 = sns.boxplot(y = 'amg_hipp_change', x= 'group', data=dfCors, ax=ax1, + boxprops=dict(alpha=.4)) +sns.stripplot(y = 'amg_hipp_change', x= 'group', data=dfCors,size=8, ax=ax1) +ax1.text(-.4,0.8, "Amygdala-Posterior Hippocampus") +g2 = sns.boxplot(y = 'hippoAnt_vmpfcAnt_change', x= 'group', data=dfCors, ax=ax2, + boxprops=dict(alpha=.4)) +sns.stripplot(y = 'hippoAnt_vmpfcAnt_change', x= 'group', data=dfCors, size=8, ax=ax2) +ax2.text(-.4,0.8, "Anterior Hippocampus - vmPFC") +# g3 = sns.boxplot(y = 'hippoAnt_hippPost_change', x= 'group', data=dfCors, ax=ax3, +# boxprops=dict(alpha=.4)) +# sns.stripplot(y = 'hippoAnt_hippPost_change', x= 'group', data=dfCors,size=8, ax=ax3) +# ax3.text(-.4,0.8, "Anterior-Posterior Hippocampus") +ylow = -0.9 +yhigh=0.9 +ax1.set_ylim(ylow,yhigh) +ax2.set_ylim(ylow,yhigh) +#ax3.set_ylim(ylow,yhigh) +ax1.set_xlabel("") +ax2.set_xlabel("") +#ax3.set_xlabel("") +ax2.set_yticks([]) +#ax3.yaxis.tick_right() +ax1.set_ylabel("Difference before/after treatment", fontsize=14) +ax2.set_ylabel("") +#ax3.set_ylabel("") +ax1.set_xticklabels(['Ketamine', 'Midazolam'], fontsize=14) +ax2.set_xticklabels(['Ketamine', 'Midazolam'], fontsize=14) +#ax3.set_xticklabels(['Ketamine', 'Midazolam'], fontsize=14) +fig.savefig("changeCorrelation.png", dpi=300, bbox_inches='tight') + +# %% [markdown] +# ## Use PyMC3 to compare the difference in correlation + +# %% +# Using Pymc3 +import pymc3 as pm +from pymc3.glm import GLM + +with pm.Model() as model_glm: + GLM.from_formula('amg_hipp_change ~ groupIdx', dfCors) + trace = pm.sample(draws=4000, tune=3000) + +# %% +pm.summary(trace, credible_interval=.95).round(2) + +# %% +# Using Pymc3 - compare antrior hippo and antvmpfc +with pm.Model() as model_glm2: + GLM.from_formula('hippoAnt_vmpfcAnt_change ~ groupIdx', dfCors) + trace2 = pm.sample(draws=4000, tune=2000) + +# %% +pm.summary(trace2, credible_interval=.95).round(2) + +# %% + +# %% +sns.boxplot(y = 'amg_hipp_change', x= 'groupIdx', data=dfCors) +scipy.stats.ttest_ind(dfCors.amg_hipp_change[dfCors.groupIdx==1],dfCors.amg_hipp_change[dfCors.groupIdx==0]) + +# %% +sns.boxplot(y = 'hippoAnt_vmpfcAnt_change', x= 'groupIdx', data=dfCors) +scipy.stats.ttest_ind(dfCors.hippoAnt_vmpfcAnt_change[dfCors.groupIdx==1], + dfCors.hippoAnt_vmpfcAnt_change[dfCors.groupIdx==0]) + +# %% +sns.boxplot(y = 'hippoAnt_hippPost_change', x= 'groupIdx', data=dfCors) +scipy.stats.ttest_ind(dfCors.hippoAnt_hippPost_change[dfCors.groupIdx==1],dfCors.hippoAnt_hippPost_change[dfCors.groupIdx==0]) + +# %% +# lets plot that on the brain +coordsROI = coords[index_list, :] + +#nilearn.plotting.plot_connectome(tTresh,coordsROI) +nilearn.plotting.view_connectome(tTresh,coordsROI) + +# %% [markdown] +# ## calculating correlations with amygdala for behavioral correlations + +# %% Run through and extract correlation of each edge here +labels = pd.read_csv('/media/Data/work/DiFuMo_atlas/256/labels_256_dictionary.csv') +def makeConnDF(mat, subject_list, labels_list = list(labels.Difumo_names)): + # takes array (Nsubject X Nodes X Nodes) and returns a dataframe of connectivity between + # inputs: mat = array (subjectXNodesXNodes) + # subject list + # labels list (Difumo atlas) + # Amygdala, hippocampus (posterior/anterior), vmPFC (and antrior), caudate (inferior, superior and anterior) + # + # Behaviour correlation - get indexes of Amygdala, Hippocampus and vmPFC + + amg = labels_list.index('Amygdala') + hippo_post = labels_list.index('Hippocampus posterior') + hippo_ant = labels_list.index('Hippocampus anterior') + vmPFC_ant = labels_list.index('Ventromedial prefrontal cortex anterior') + vmPFC = labels_list.index('Ventromedial prefrontal cortex') + caudate_inf = labels_list.index('Caudate inferior') + caudate_ant = labels_list.index('Caudate anterior') + caudate_sup = labels_list.index('Caudate superior') + scr_id = [] + amg_hippPost = [] + amg_hippAnt = [] + amg_vmPFC = [] + amg_vmPFCant = [] + amg_caudInf = [] + amg_caudAnt = [] + amg_caudSup = [] + for i, sub in enumerate(subject_list): + scr_id.append(sub) + amg_hippPost.append(mat[i,amg,hippo_post]) + amg_hippAnt.append(mat[i,amg,hippo_ant]) + amg_vmPFC.append(mat[i,amg,vmPFC]) + amg_vmPFCant.append(mat[i,amg,vmPFC_ant]) + amg_caudInf.append(mat[i, amg, caudate_inf]) + amg_caudAnt.append(mat[i, amg, caudate_ant]) + amg_caudSup.append(mat[i, amg, caudate_sup]) + # create dataframe from that + corDF = pd.DataFrame({'scr_id':scr_id, 'group':group_label, 'amg_hippPost': amg_hippPost, + 'amg_hippAnt':amg_hippAnt, 'amg_vmPFC':amg_vmPFC, 'amg_vmPFCant': amg_vmPFCant, + 'amg_caudAnt': amg_caudAnt, 'amg_caudInf': amg_caudInf, 'amg_caudSup': amg_caudSup}) + return corDF +# %% +labels + +# %% +pclDf = pd.read_csv('/home/or/Documents/kpe_analyses/KPEIHR0009_DATA_2020-08-31_1301.csv') # take only KPE patients +pclDf['scr_id'] = pclDf['scr_id'].str.replace(" ","") pclDf = pclDf[pclDf['scr_id'].str.startswith('KPE')] dfP = pd.DataFrame({'subject': pclDf['scr_id']}) dfP_PCL = pclDf[['scr_id','redcap_event_name','pcl5_1', 'pcl5_2', 'pcl5_3', 'pcl5_4', 'pcl5_5', 'pcl5_6', 'pcl5_7', @@ -134,32 +446,133 @@ # reshape it to wide df2=dfP_PCL.pivot(index = 'scr_id',columns='redcap_event_name', values='pclTotal') list(df2) -df2 = df2.rename(columns={"30_day_follow_up_s_arm_1": "30Days", "90_day_follow_up_s_arm_1": "90Days", +df2 = df2.rename(columns={"30_day_follow_up_s_arm_1": "Days30", "90_day_follow_up_s_arm_1": "90Days", "screening_selfrepo_arm_1": "Screening", "visit_1_arm_1": "Visit1", "visit_7_week_follo_arm_1": "Visit7"}) #df2['scr_id'] = dfP_PCL['scr_id'] df2 + + +# %% Call makeDF function on session 1 and 2 +dfSes1 = makeConnDF(mat_ses1, subject_list) + +# %% ses 2 +dfSes2 = makeConnDF(mat_ses2, subject_list) + + + + # %% # merging two data frames toghether -dfTest = pd.merge(corDF, df2, on = 'scr_id') +dfTest = pd.merge(dfSes2, df2, on = 'scr_id') # create difference pcl score -dfTest['days30_1'] = dfTest['30Days'] - dfTest.Visit1 -dfTest['days30_s'] = dfTest['30Days'] - dfTest.Screening +dfTest['days30_1'] = dfTest['Days30'] - dfTest.Visit1 +dfTest['days30_s'] = dfTest['Days30'] - dfTest.Screening dfTest['days7_1'] = dfTest['Visit7'] - dfTest.Visit1 dfTest # %% import scipy -sns.lmplot(x='amg_hippPost',y='days30_s',hue='group', data=dfTest) -naMask = np.isnan(dfTest['days30_s']) -scipy.stats.pearsonr(dfTest['days30_s'][~naMask], dfTest['amg_hippPost'][~naMask]) +sns.lmplot(x='amg_hippAnt',y='Days30',hue='group', data=dfTest) +naMask = np.isnan(dfTest['Days30']) +scipy.stats.pearsonr(dfTest['Days30'][~naMask], dfTest['amg_hippAnt'][~naMask]) # %% -sns.lmplot(x='amg_vmPFC',y='30Days',hue='group', data=dfTest) -naMask = np.isnan(dfTest['30Days']) -scipy.stats.pearsonr(dfTest['30Days'][~naMask], dfTest['amg_vmPFC'][~naMask]) +#compare correlations of only ketamine and only midazolam +ketCorr = scipy.stats.pearsonr(dfTest['Visit7'][~naMask][dfTest.group==1], dfTest['amg_hippPost'][~naMask][dfTest.group==1]) +midCorr = scipy.stats.pearsonr(dfTest['Visit7'][~naMask][dfTest.group==0], dfTest['amg_hippPost'][~naMask][dfTest.group==0]) +from corrstats import independent_corr +checkCorr = independent_corr(ketCorr[0], midCorr[0], n=11, n2 = 10, twotailed=True, conf_level=0.95, method='fisher') +print(f'Correlation difference between CC and PTSD with anhedonia is {checkCorr}') + + +# %% +sns.lmplot(x='amg_vmPFC',y='Visit7',hue='group', data=dfTest) +naMask = np.isnan(dfTest['Visit7']) +scipy.stats.pearsonr(dfTest['Visit7'][~naMask], dfTest['amg_vmPFC'][~naMask]) + +# %% Caudate? +sns.lmplot(x='amg_caudSup',y='Days30',hue='group', data=dfTest) +naMask = np.isnan(dfTest['Days30']) +scipy.stats.pearsonr(dfTest['Days30'][~naMask], dfTest['amg_caudSup'][~naMask]) ##### -#%% Now we should check the delta in all of these association and the correlation to -# symptoms change +# %% [markdown] +# ### So it seems like there's a general positive correlation between symptoms at 30 days and connectivity between amgygdala and +# ### hippocampus. While we see a general negative correlation between amg-vmPFC connectivity. +# #### But - it seems like we have group differences - lets check the interaction of group and each of them + +# %% +# amg and hippocampus +import statsmodels.formula.api as smf + +model = smf.ols(formula='Visit7 ~ group * amg_hippPost', data=dfTest) +res = model.fit() +print(res.summary()) + +# %% [markdown] +# ### Indeed we see an interaction between the group and the correlation. + +# %% Now for vmPFC +modelvmPFC = smf.ols(formula='days30_scale ~ group * amg_vmPFC', data=dfTest) +resVMpfc = modelvmPFC.fit() +print(resVMpfc.summary()) + +# %% Now we should check the delta in all of these association and the correlation to +# Using Pymc3 +import pymc3 as pm +from pymc3.glm import GLM + +with pm.Model() as model_glm: + GLM.from_formula('days30_scale ~ group * scaleamgHipp', dfTest) + trace = pm.sample(draws=4000, tune=3000) + +# %% +pm.summary(trace, credible_interval=.95).round(2) + +# %% +# lets scale everything +dfTest['scaleamgHipp'] = (dfTest.amg_hippPost - dfTest.amg_hippPost.mean()) / dfTest.amg_hippPost.std() + + +# %% +dfTest['days30_scale'] = (dfTest.Days30 - dfTest.Days30.mean()) / dfTest.Days30.std() +dfTest['Visit7_scale'] = (dfTest.Visit7 - dfTest.Visit7.mean()) / dfTest.Visit7.std() + +# %% +# Creating a delta between connectivity of second - first session +dfTest['amg_HippPost_Change'] = dfSes2.amg_hippPost - dfSes1.amg_hippPost + +# %% +sns.lmplot(x='amg_HippPost_Change',y='days30_1',hue='group', data=dfTest) +naMask = np.isnan(dfTest['days30_1']) +scipy.stats.pearsonr(dfTest['days30_1'][~naMask], dfTest['amg_HippPost_Change'][~naMask]) + +# %% +model_delta = smf.ols(formula='days30_1 ~ group *amg_HippPost_Change', data=dfTest) +resdelta = model_delta.fit() +print(resdelta.summary()) + + +# %% +# check changes in connectivity between amygdala and hippocampus +sns.stripplot(y='amg_HippPost_Change', x='group', data=dfTest) +scipy.stats.ttest_ind(dfTest['amg_hippPost'][~naMask][dfTest.group==0], dfTest['amg_hippPost'][~naMask][dfTest.group==1]) + +# %% [markdown] +# ## Check correlation with SCR + +# %% +scr = pd.read_csv('/home/or/kpe_task_analysis/scr_deltas.csv') +scr1 = scr.drop(columns = ['med_cond', 'groupIdx']) +scr1 + +# %% +dfMerge = pd.merge(dfTest, scr1) +dfMerge + + +# %% +sns.lmplot('amg_hippPost', 'Trauma_2vs1',hue='group',data=dfMerge) +#scipy.stats.pearsonr(dfMerge.days7_1, dfMerge.Trauma_2vs1) diff --git a/task_based_analysis/DiFuMo/att.txt b/task_based_analysis/DiFuMo/att.txt new file mode 100644 index 0000000..d98f96a --- /dev/null +++ b/task_based_analysis/DiFuMo/att.txt @@ -0,0 +1,256 @@ +0,0.9058823529411765 +1,0.8705882352941177 +2,0.8666666666666667 +3,0.9647058823529412 +4,0.9372549019607843 +5,0.8666666666666667 +6,0.9176470588235294 +7,0.8941176470588235 +8,0.9686274509803922 +9,0.9607843137254902 +10,0.9215686274509803 +11,0.8784313725490196 +12,0.9529411764705882 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+3.936893548882144955e+01 -1.824240180296531832e+01 1.949076156456912656e+01 +2.616358506198679379e-01 -5.735773338157406442e+01 5.163856213961639696e+01 diff --git a/task_based_analysis/DiFuMo/corrstats.py b/task_based_analysis/DiFuMo/corrstats.py new file mode 100644 index 0000000..62a9a71 --- /dev/null +++ b/task_based_analysis/DiFuMo/corrstats.py @@ -0,0 +1,114 @@ +""" +Functions for calculating the statistical significant differences between two dependent or independent correlation +coefficients. +The Fisher and Steiger method is adopted from the R package http://personality-project.org/r/html/paired.r.html +and is described in detail in the book 'Statistical Methods for Psychology' +The Zou method is adopted from http://seriousstats.wordpress.com/2012/02/05/comparing-correlations/ +Credit goes to the authors of above mentioned packages! + +Author: Philipp Singer (www.philippsinger.info) +""" + +from __future__ import division + +__author__ = 'psinger' + +import numpy as np +from scipy.stats import t, norm +from math import atanh, pow +from numpy import tanh + +def rz_ci(r, n, conf_level = 0.95): + zr_se = pow(1/(n - 3), .5) + moe = norm.ppf(1 - (1 - conf_level)/float(2)) * zr_se + zu = atanh(r) + moe + zl = atanh(r) - moe + return tanh((zl, zu)) + +def rho_rxy_rxz(rxy, rxz, ryz): + num = (ryz-1/2.*rxy*rxz)*(1-pow(rxy,2)-pow(rxz,2)-pow(ryz,2))+pow(ryz,3) + den = (1 - pow(rxy,2)) * (1 - pow(rxz,2)) + return num/float(den) + +def dependent_corr(xy, xz, yz, n, twotailed=True, conf_level=0.95, method='steiger'): + """ + Calculates the statistic significance between two dependent correlation coefficients + @param xy: correlation coefficient between x and y + @param xz: correlation coefficient between x and z + @param yz: correlation coefficient between y and z + @param n: number of elements in x, y and z + @param twotailed: whether to calculate a one or two tailed test, only works for 'steiger' method + @param conf_level: confidence level, only works for 'zou' method + @param method: defines the method uses, 'steiger' or 'zou' + @return: t and p-val + """ + if method == 'steiger': + d = xy - xz + determin = 1 - xy * xy - xz * xz - yz * yz + 2 * xy * xz * yz + av = (xy + xz)/2 + cube = (1 - yz) * (1 - yz) * (1 - yz) + + t2 = d * np.sqrt((n - 1) * (1 + yz)/(((2 * (n - 1)/(n - 3)) * determin + av * av * cube))) + p = 1 - t.cdf(abs(t2), n - 3) + + if twotailed: + p *= 2 + + return t2, p + elif method == 'zou': + L1 = rz_ci(xy, n, conf_level=conf_level)[0] + U1 = rz_ci(xy, n, conf_level=conf_level)[1] + L2 = rz_ci(xz, n, conf_level=conf_level)[0] + U2 = rz_ci(xz, n, conf_level=conf_level)[1] + rho_r12_r13 = rho_rxy_rxz(xy, xz, yz) + lower = xy - xz - pow((pow((xy - L1), 2) + pow((U2 - xz), 2) - 2 * rho_r12_r13 * (xy - L1) * (U2 - xz)), 0.5) + upper = xy - xz + pow((pow((U1 - xy), 2) + pow((xz - L2), 2) - 2 * rho_r12_r13 * (U1 - xy) * (xz - L2)), 0.5) + return lower, upper + else: + raise Exception('Wrong method!') + +def independent_corr(xy, ab, n, n2 = None, twotailed=True, conf_level=0.95, method='fisher'): + """ + Calculates the statistic significance between two independent correlation coefficients + @param xy: correlation coefficient between x and y + @param xz: correlation coefficient between a and b + @param n: number of elements in xy + @param n2: number of elements in ab (if distinct from n) + @param twotailed: whether to calculate a one or two tailed test, only works for 'fisher' method + @param conf_level: confidence level, only works for 'zou' method + @param method: defines the method uses, 'fisher' or 'zou' + @return: z and p-val + """ + + if method == 'fisher': + xy_z = 0.5 * np.log((1 + xy)/(1 - xy)) + ab_z = 0.5 * np.log((1 + ab)/(1 - ab)) + if n2 is None: + n2 = n + + se_diff_r = np.sqrt(1/(n - 3) + 1/(n2 - 3)) + diff = xy_z - ab_z + z = abs(diff / se_diff_r) + p = (1 - norm.cdf(z)) + if twotailed: + p *= 2 + + return z, p + elif method == 'zou': + L1 = rz_ci(xy, n, conf_level=conf_level)[0] + U1 = rz_ci(xy, n, conf_level=conf_level)[1] + L2 = rz_ci(ab, n2, conf_level=conf_level)[0] + U2 = rz_ci(ab, n2, conf_level=conf_level)[1] + lower = xy - ab - pow((pow((xy - L1), 2) + pow((U2 - ab), 2)), 0.5) + upper = xy - ab + pow((pow((U1 - xy), 2) + pow((ab - L2), 2)), 0.5) + return lower, upper + else: + raise Exception('Wrong method!') + +# + +#print dependent_corr(.40, .50, .10, 103, method='steiger') +#print independent_corr(0.5 , 0.6, 103, 103, method='fisher') +# - + +# print dependent_corr(.396, .179, .088, 200, method='zou') +# print independent_corr(.560, .588, 100, 353, method='zou') diff --git a/task_based_analysis/DiFuMo/delta_Difumo.txt b/task_based_analysis/DiFuMo/delta_Difumo.txt new file mode 100644 index 0000000..a4c6ff7 --- /dev/null +++ b/task_based_analysis/DiFuMo/delta_Difumo.txt @@ -0,0 +1,256 @@ +0.000000000000000000e+00 -3.266007694970746861e-02 -5.102582034627426572e-02 2.790555015663987934e-02 2.085761062689779621e-02 4.638795421464277091e-02 -1.027337242893691382e-01 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0.000000000000000000e+00 diff --git a/task_based_analysis/DiFuMo/difumo_script.py b/task_based_analysis/DiFuMo/difumo_script.py index 1bdf9ff..484e66b 100644 --- a/task_based_analysis/DiFuMo/difumo_script.py +++ b/task_based_analysis/DiFuMo/difumo_script.py @@ -1,3 +1,4 @@ +# %% ''' @author: Or Duek @date: Jul 16 2020 @@ -7,7 +8,7 @@ In this file we will create a task based ''' -#%% import libraries +# %% import libraries import pandas as pd from nilearn.input_data import NiftiMapsMasker from nilearn import connectome @@ -19,11 +20,12 @@ import glob from nilearn import connectome import seaborn as sns -#%% Set output folder +import dask +# %% Set output folder output_dir = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/DiFuMo/' # set session -ses= '1' # session is a string -#%% Functions +ses= '2' # session is a string +# %% Functions # extract RS data and create vector for each subject def removeVars (confoundFile): # this method takes the csv regressors file (from fmriPrep) and chooses a few to confound. You can change those few @@ -39,9 +41,7 @@ def removeVars (confoundFile): return finalConf -#%% functional files -# subject_list = ['008','1223','1253','1263','1293','1307','1315','1322','1339','1343','1351','1356','1364','1369' -# ,'1387','1390','1403','1464', '1468', '1480', '1499'] +# %% functional files func_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{session}/func/sub-{sub}_ses-{session}_task-Memory_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz' confound_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{session}/func/sub-{sub}_ses-{session}_task-Memory_desc-confounds_regressors.tsv' @@ -53,23 +53,23 @@ def removeVars (confoundFile): condition_label = np.array(medication_cond.med_cond) group_label = list(map(int, condition_label)) -#%% +# %% # create a mean mask of all subjects # load mask of brain brainmasks = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-*/ses-%s/func/sub-*_ses-%s_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz' %(ses,ses)) print(brainmasks) -%matplotlib inline +# %matplotlib inline #for mask in brainmasks: # nilearn.plotting.plot_roi(mask) mean_mask = nilearn.image.mean_img(brainmasks) -nilearn.plotting.plot_stat_map(mean_mask) +#nilearn.plotting.plot_stat_map(mean_mask) group_mask = nilearn.image.math_img("a>=0.95", a=mean_mask) -nilearn.plotting.plot_roi(group_mask) +#nilearn.plotting.plot_roi(group_mask) -#%% fetch atlas +# %% fetch atlas maps_img = '/media/Data/work/DiFuMo_atlas/256/maps.nii.gz' labels = pd.read_csv('/media/Data/work/DiFuMo_atlas/256/labels_256_dictionary.csv') #coords = nilearn.plotting.find_parcellation_cut_coords(labels_img=maps_img) @@ -79,11 +79,12 @@ def removeVars (confoundFile): mask_params = { 'mask_img': group_mask, 'detrend': True, 'standardize': True, 'high_pass': 0.01, 'low_pass': 0.1, 't_r': 1, - 'smoothing_fwhm': 6., 'verbose': 5} + 'smoothing_fwhm': 6., + 'verbose': 5} masker = NiftiMapsMasker(maps_img=maps_img, **mask_params) -#%% Generate npy files of timeseries for each subject per session +# %% Generate npy files of timeseries for each subject per session # we will use it later on, stratify to scripts etc. # build a specific folder try: @@ -98,7 +99,7 @@ def removeVars (confoundFile): func = func_template.format(sub=subject, session=ses) confound = confound_template.format(sub=subject, session=ses) signals = masker.fit_transform(imgs=func, confounds=removeVars(confound)) - np.save(output_dir + 'sub-' + subject + '_ses-' + ses, signals) + save = np.save(output_dir + 'sub-' + subject + '_ses-' + ses, signals) subject_ts.append(signals) diff --git a/task_based_analysis/Digraph.gv b/task_based_analysis/Digraph.gv new file mode 100644 index 0000000..45ab049 --- /dev/null +++ b/task_based_analysis/Digraph.gv @@ -0,0 +1,16 @@ +// KPE CONSORT +digraph { + node [shape=rectangle] + A [label="Total Screened"] + B [label="Total Eligible"] + C [label="Participated in 1st visit + N=25"] + D [label="Participated in 2nd visit"] + E [label="Participated in 3rd visit"] + F [label="Participated in 4th visit"] + A -> B + B -> C + C -> D + D -> E + E -> F +} diff --git a/task_based_analysis/Digraph.gv.pdf b/task_based_analysis/Digraph.gv.pdf new file mode 100644 index 0000000..1c93d0b Binary files /dev/null and b/task_based_analysis/Digraph.gv.pdf differ diff --git a/task_based_analysis/NistatsAnalyses/.ipynb_checkpoints/Nistats_1sesion-checkpoint.ipynb b/task_based_analysis/NistatsAnalyses/.ipynb_checkpoints/Nistats_1sesion-checkpoint.ipynb new file mode 100644 index 0000000..7fec515 --- /dev/null +++ b/task_based_analysis/NistatsAnalyses/.ipynb_checkpoints/Nistats_1sesion-checkpoint.ipynb @@ -0,0 +1,6 @@ +{ + "cells": [], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/NistatsAnalyses/Nistats_1sesion.ipynb b/task_based_analysis/NistatsAnalyses/Nistats_1sesion.ipynb new file mode 100644 index 0000000..0bedebd --- /dev/null +++ b/task_based_analysis/NistatsAnalyses/Nistats_1sesion.ipynb @@ -0,0 +1,80 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "ename": "ModuleNotFoundError", + "evalue": "No module named 'sklearn.externals.joblib'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnilearn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mnistats\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfirst_level_model\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mFirstLevelModel\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m~/.local/lib/python3.7/site-packages/nistats/first_level_model.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 25\u001b[0m \u001b[0mTransformerMixin\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 26\u001b[0m )\n\u001b[0;32m---> 27\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0msklearn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexternals\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoblib\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mMemory\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 28\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mnilearn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minput_data\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mNiftiMasker\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 29\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mnilearn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_utils\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mCacheMixin\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'sklearn.externals.joblib'" + ] + } + ], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import nistats\n", + "import matplotlib.pyplot as plt\n", + "import nilearn\n", + "from nistats.first_level_model import FirstLevelModel" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# extract RS data and create vector for each subject\n", + "def removeVars (confoundFile):\n", + " # this method takes the csv regressors file (from fmriPrep) and chooses a few to confound. You can change those few\n", + " import pandas as pd\n", + " confound = pd.read_csv(confoundFile,sep=\"\\t\", na_values=\"n/a\")\n", + " finalConf = confound[['csf', 'white_matter', 'framewise_displacement', \n", + " 'a_comp_cor_00', 'a_comp_cor_01',\t'a_comp_cor_02', 'a_comp_cor_03', \n", + " 'a_comp_cor_04', 'a_comp_cor_05', 'trans_x', 'trans_y', 'trans_z', \n", + " 'rot_x', 'rot_y', 'rot_z']] # can add 'global_signal' also ,,\n", + " # \n", + " # change NaN of FD to zero\n", + " finalConf = finalConf.fillna(0.0)\n", + " return finalConf" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.7.7 64-bit ('neuroAnalysis': conda)", + "language": "python", + "name": "python37764bitneuroanalysiscondaa23731adadc74dd9881a406adec17ad1" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/ROI_analysis.ipynb b/task_based_analysis/ROI_analysis.ipynb new file mode 100644 index 0000000..3ac3be9 --- /dev/null +++ b/task_based_analysis/ROI_analysis.ipynb @@ -0,0 +1,2681 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## ROI analysis for KPE study - basic ROI will be: Amygdala, Hippocampus, Striatum, vmPFC, vACC" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/sklearn/externals/joblib/__init__.py:15: DeprecationWarning: sklearn.externals.joblib is deprecated in 0.21 and will be removed in 0.23. Please import this functionality directly from joblib, which can be installed with: pip install joblib. If this warning is raised when loading pickled models, you may need to re-serialize those models with scikit-learn 0.21+.\n", + " warnings.warn(msg, category=DeprecationWarning)\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "import glob\n", + "import nilearn\n", + "from nilearn import plotting\n", + "import os\n", + "import subprocess\n", + "from nilearn.input_data import NiftiMasker\n", + "work_dir = '/media/Data/work/KPE_ROI'" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# build grouped mask\n", + "mask_img_temp = '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-*/ses-[1,2]/func/sub-*_ses-[1,2]_task-Memory_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz'\n", + "mask_files = glob.glob(mask_img_temp)\n", + "mean_mask = nilearn.image.mean_img(mask_files, n_jobs=5)\n", + "plotting.plot_anat(mean_mask)\n", + "\n", + "group_mask = nilearn.image.math_img(\"a>=0.95\", a=mean_mask)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(group_mask)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Compare before-after scans" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'tstat_list' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtstat_list\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtstat_list\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mtstat_ses2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mglob\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mglob\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_*/con_0002.nii'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mtstat_ses2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtstat_ses2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'tstat_list' is not defined" + ] + } + ], + "source": [ + "tstat_list.sort()\n", + "print(tstat_list)\n", + "tstat_ses2 = glob.glob('/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_*/con_0002.nii')\n", + "tstat_ses2.sort()\n", + "print(tstat_ses2)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1322/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1322/con_0002.nii\n", + "1322\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1387/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1387/con_0002.nii\n", + "1387\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1339/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1339/con_0002.nii\n", + "1339\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1464/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1464/con_0002.nii\n", + "1464\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1315/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1315/con_0002.nii\n", + "1315\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1223/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1223/con_0002.nii\n", + "1223\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1468/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1468/con_0002.nii\n", + "1468\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1499/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1499/con_0002.nii\n", + "1499\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1307/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1307/con_0002.nii\n", + "1307\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1351/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1351/con_0002.nii\n", + "1351\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_008/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_008/con_0002.nii\n", + "008\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1390/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1390/con_0002.nii\n", + "1390\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1263/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1263/con_0002.nii\n", + "1263\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1369/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1369/con_0002.nii\n", + "1369\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1364/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1364/con_0002.nii\n", + "1364\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1293/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1293/con_0002.nii\n", + "1293\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1253/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1253/con_0002.nii\n", + "1253\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1343/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1343/con_0002.nii\n", + "1343\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1356/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1356/con_0002.nii\n", + "1356\n", + "/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_1403/con_0002.nii\n", + "/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_1403/con_0002.nii\n", + "1403\n" + ] + } + ], + "source": [ + "# create diff image\n", + "group = 'all'\n", + "contrast = '02'\n", + "tstat_list = glob.glob('/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_*/con_00%s.nii' %(contrast))\n", + "tstat_ses2 = glob.glob('/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_*/con_00%s.nii'%(contrast))\n", + "import os\n", + "os.chdir(work_dir)\n", + "\n", + "for ses1,ses2 in zip(tstat_list,tstat_ses2):\n", + " print (ses1)\n", + " print (ses2)\n", + " sub = ses1.split('id_')\n", + " sub = sub[1].split('/')[0]\n", + " print(sub)\n", + " diff_file = 'kpe' + sub + 'diff' + group + 'con' + contrast\n", + " cmd = ['fslmaths', str(ses2), '-sub', str(ses1), str(diff_file)]\n", + " subprocess.call(cmd)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['/media/Data/work/KPE_ROI/kpe1369diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1364diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1307diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1356diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1468diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1403diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1343diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1322diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1387diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1499diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1315diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1390diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1339diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1464diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz']" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "diff_list = glob.glob(work_dir + '/kpe*diffallcon%s.nii.gz' %(contrast))\n", + "diff_list" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "# create mask\n", + "mask_file = '/media/Data/work/KPE_ROI/binConjunc_PvNxDECxRECxMONxPRI_vmpfc.nii.gz'" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.image.resampling.resample_img...\n", + "resample_img(, target_affine=None, target_shape=None, copy=False, interpolation='nearest')\n", + "_____________________________________________________resample_img - 0.1s, 0.0min\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe1369diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1364diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1307diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1356diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1468diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1403diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1343diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1322diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1387diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1499diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1315diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1390diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1339diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1464diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 20),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 3.2s, 0.1min\n" + ] + } + ], + "source": [ + "from nilearn.input_data import NiftiMasker\n", + "\n", + "# here I use a masked image so all will have same size\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(diff_list)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from kpe1403diffallcon02\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.1s, 0.0min: Loading resample_img...\n" + ] + }, + { + "data": { + "text/plain": [ + "NiftiMasker(detrend=True, dtype=None, high_pass=None, low_pass=None,\n", + " mask_args=None,\n", + " mask_img='/media/Data/work/KPE_ROI/binConjunc_PvNxDECxRECxMONxPRI_vmpfc.nii.gz',\n", + " mask_strategy='background',\n", + " memory=Memory(cachedir='/media/Data/nilearn/joblib'),\n", + " memory_level=1, sample_mask=None, sessions=None, smoothing_fwhm=4,\n", + " standardize=True, t_r=1.0, target_affine=None, target_shape=None,\n", + " verbose=2)" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(diff_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(449,)" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[Memory] 6.4s, 0.1min: Loading unmask...\n" + ] + } + ], + "source": [ + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_all_Ses1_2' %(contrast))" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plotting.plot_stat_map(delta_img,threshold = 0.5)\n", + " #bg_img = anat_mean)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Run actual TFCE using fsl Randomize" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Group difference" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "KPE008\n", + "KPE1223\n", + "KPE1293\n", + "KPE1307\n", + "KPE1315\n", + "KPE1322\n", + "KPE1339\n", + "KPE1343\n", + "KPE1387\n", + "KPE1464\n", + "KPE1499\n", + "KPE1253\n", + "KPE1263\n", + "KPE1351\n", + "KPE1356\n", + "KPE1364\n", + "KPE1369\n", + "KPE1390\n", + "KPE1403\n", + "KPE1468\n", + "KPE1480\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "\n", + "ketamine_list = list(medication_cond['scr_id'][medication_cond['med_cond']==1])\n", + "ket_list = []\n", + "for subject in ketamine_list:\n", + " print(subject)\n", + " sub = subject.split('KPE')[1]\n", + " ket_list.append(sub)\n", + "\n", + "\n", + "midazolam_list = list(medication_cond['scr_id'][medication_cond['med_cond']==0])\n", + "mid_list = []\n", + "for subject in midazolam_list:\n", + " print(subject)\n", + " sub = subject.split('KPE')[1]\n", + " mid_list.append(sub)\n", + "mid_list.remove('1480')" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'contrast' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mket_func\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'/media/Data/work/KPE_ROI/kpe%sdiffallcon%s.nii.gz'\u001b[0m\u001b[0;34m%\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0msub\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcontrast\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0msub\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mket_list\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mmid_func\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'/media/Data/work/KPE_ROI/kpe%sdiffallcon%s.nii.gz'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0msub\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcontrast\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0msub\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmid_list\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m(.0)\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mket_func\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'/media/Data/work/KPE_ROI/kpe%sdiffallcon%s.nii.gz'\u001b[0m\u001b[0;34m%\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0msub\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcontrast\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0msub\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mket_list\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mmid_func\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'/media/Data/work/KPE_ROI/kpe%sdiffallcon%s.nii.gz'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0msub\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcontrast\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0msub\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmid_list\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'contrast' is not defined" + ] + } + ], + "source": [ + "ket_func = ['/media/Data/work/KPE_ROI/kpe%sdiffallcon%s.nii.gz'% (sub, contrast) for sub in ket_list]\n", + "mid_func = ['/media/Data/work/KPE_ROI/kpe%sdiffallcon%s.nii.gz' % (sub, contrast) for sub in mid_list]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Start with Ketamine" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for sub in ket_func:\n", + " plotting.plot_stat_map(sub, threshold=0.8, title = sub)" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "[Memory] 0.0s, 0.0min: Loading filter_and_mask...\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1307diffallco\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "[Memory] 0.0s, 0.0min: Loading unmask...\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# here I use a masked image so all will have same size\n", + "group = 'ket'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(ket_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(ket_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1)\n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Midazolam" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "[Memory] 0.0s, 0.0min: Loading filter_and_mask...\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1356diffallc\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "[Memory] 0.0s, 0.0min: Loading unmask...\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# here I use a masked image so all will have same size\n", + "group = 'mid'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(mid_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(mid_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Striatum - Ketamine" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1307diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1315diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1322diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1339diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1343diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1387diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1464diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1499diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 11),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 1.8s, 0.0min\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1307diffallco\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.masking.unmask...\n", + "unmask(array([-0.358917, ..., 0.006478], dtype=float32), )\n", + "___________________________________________________________unmask - 0.1s, 0.0min\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/binConjunc_PvNxDECxRECxMONxPRI_striatum.nii.gz'\n", + "group = 'ket'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(ket_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(ket_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Midazolam" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1356diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1364diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1369diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1390diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1403diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1468diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 9),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 1.5s, 0.0min\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1356diffallc\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.masking.unmask...\n", + "unmask(array([0.033937, ..., 0.211592], dtype=float32), )\n", + "___________________________________________________________unmask - 0.1s, 0.0min\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "group = 'mid'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(mid_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(mid_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1.5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Amygdala - Ketamine\n", + "I used neurosynth to generate a mask file. Used metaanalysis with the term Amygdala, then thresholded it accordingly. " + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=19\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.image.resampling.resample_img...\n", + "resample_img(, target_affine=None, target_shape=None, copy=False, interpolation='nearest')\n", + "_____________________________________________________resample_img - 0.0s, 0.0min\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1307diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1315diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1322diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1339diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1343diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1387diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1464diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1499diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 11),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 1.8s, 0.0min\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1307diffallco\n", + "[NiftiMasker.fit] Resampling mask\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.image.resampling.resample_img...\n", + "resample_img(, target_affine=None, target_shape=None, copy=False, interpolation='nearest')\n", + "_____________________________________________________resample_img - 0.0s, 0.0min\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.masking.unmask...\n", + "unmask(array([-0.945631, ..., -0.022562], dtype=float32), )\n", + "___________________________________________________________unmask - 0.1s, 0.0min\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "group = 'ket'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(ket_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(ket_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1.5)" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1356diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1364diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1369diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1390diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1403diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1468diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 9),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 1.6s, 0.0min\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1356diffallc\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.masking.unmask...\n", + "unmask(array([-0.252159, ..., 0.671368], dtype=float32), )\n", + "___________________________________________________________unmask - 0.1s, 0.0min\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "group = 'mid'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(mid_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(mid_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1.5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## vACC - Ketamine first" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/ventral anterior_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=4\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1307diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1315diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1322diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1339diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1343diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1387diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1464diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1499diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 11),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 3.4s, 0.1min\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1307diffallco\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.masking.unmask...\n", + "unmask(array([-0.142441, ..., -0.63876 ], dtype=float32), )\n", + "___________________________________________________________unmask - 0.1s, 0.0min\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "group = 'ket'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(ket_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(ket_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1.5)" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1356diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1364diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1369diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1390diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1403diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1468diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 9),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 2.7s, 0.0min\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1356diffallc\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.masking.unmask...\n", + "unmask(array([-0.0658 , ..., -0.253689], dtype=float32), )\n", + "___________________________________________________________unmask - 0.1s, 0.0min\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "group = 'mid'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(mid_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(mid_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1.5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Hippocampus - Ketamin" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1307diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1315diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1322diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1339diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1343diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1387diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1464diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1499diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 11),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 1.9s, 0.0min\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1307diffallco\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.masking.unmask...\n", + "unmask(array([-0.064044, ..., 0.438721], dtype=float32), )\n", + "___________________________________________________________unmask - 0.1s, 0.0min\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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HCrOnwoyGdUh8P+jV+5OULalZ/+5P/z0qBsXnGfVJMhtRzEbUN2vtW8RosFiXNUI83qK2MPPKfYkKu3xJOEZr8uTJSiQSvQMZPJFIJBIdDBtkNsAiMT8qhfqTBiIzKrh85+VaevHUsCDIcEQZH9TtkJoHEDP4udY+ldtFsRc0kpmZQ3FHOwQG09mdfeLj+dPHc7xKYsfQ4cbGCy+8UCoytHnzZknlAUeFUNJt7vCs1sqAn0phGan5mnXEGjDeggONA6ySbiPDwDX3SIKXlWojbQNmRZA+jdrBNnPAvvzyy/rb3/7WbED2FDjrxFLE7mOMa2B8g+97lBnl50lGyseN+qDBvmVw8o40YHicWtkoZM9Ia3s7s2V+cTG90mBgHlm8qM+TefR+1jh59tlnJWWtlUSiJ6NdjY1Zs2ZJkvbff39JzSfmRNfAXXfdVSqR7hdJLdGvRCLRNoiMzCj+IEpLZkp75PWzauxzzz0nqWwI0qEzokBkVp2txVIwHiSKyahlMFe23edgfRYa4GRCovgVBvpH4o0G70midWhXY+Oggw6SVJbi9YBgvIE9IjIZkSSuPTCqc3L9nJ2MmQccuKTR2B52+kpmgwIxUVCU6dOo1gWPw3tEjzlSqOQk5Wty270u7+Ny0rr55psllTMIupvXaTVaMxNF6q+ewIio0m+kNcE+FE2wjOUh1UzmI8qgYnZKJRgcaFAvhplNFILy9mQefU85Hpm9ErFx1jhx1oqZjnHjxtW81kQi0X2RMRuJRCLRweCyaBSUziVeigba8LMhyNIN/uR57HTYQbMxHWWCUJ7fS20UUqxkBSJBwsig5rnIVDBLJCpO6XtiCYQoyJrLffx7xHQkWod2MTZuv/12SSrFZjjAhh6WO7gpvWiNmN6kEW3P80VeKQeOvX1XtTSY5VIrKMsdm9kdZEGoEErv016lBwYHM6k/skBkbby/2+e2+7vb4SwNivc4eMppsF1dI+Fb3/qWpOYsV8TkMMXQz9h9kvc3Kovt49UbD2T4uH5ZUGclYvkMxv5U7kONFcZqkGGkwBPjfnyvGF/kT/ctsjrUKHG7fDxfu/ueM4dOPvlkJRKJnoFkNhKJRKKDcdZZZ0mSvv/970tqvrzHZT8uGdsJoC4HU+RtQFaqOFceP0rjjxgOZsWwnZVg2j0N8UhAj4hE6Wyk+tqZKWOjlsHfXD6PljJ9Tbx3idahTY0Nr5Ob0WBnoLfOKHk/VHcG1g9h52W6F9O83NmYUeBOZu/eXuzTTz9d1T4WP2JsR+X5nVlDapB0JoVlWKWVf2f8CQcoGQ3GaPjazLDQ64w0EvzsPJlF1Um7ClzrxQyN74cnXQr8+H47XsDfGZdjlouVTn3fo8wLZm5EsRf+uzVm2LfZX6KslsoCWGRDooJT7gO8NlaB5TkYX0QGhfR30UuFejmO5XAm0YYNGyRJF154Yc39E4lE10cyG4lEItFJ8NKTjU164WQ8GGNhZ4CGpQ1COxdckmbQfOTVGzRyuSRnVDIiUdaJQWczkuZnHRdeI5fjuCxop5KZM8xqiYLx7bAldgxtYmzMnj1bUjnFNSrpywh80mKRiiM7lTtHlJnBDAF6VPZa3Yn86c7tARx5hOyctY7B+BTSodQeoGIlWRqmtpHlYWyAPXJmCkTUJoVuPJlxArjzzjslSSeddJK6AubNmydJ2nfffSXFgW5F6Xa+vwy480TlPuP7GTEMfP4M3ItKc1PkiVlN7NMGa+xUbhuxahx30ThhmyNhJ7J5FFPiM/Ekz2BG9mVKa2dBrESi+yKZjUQikegkWNDMS0cU/WO8AtOPyYAYNj6j6q5mUijmFxnplAGoB1FciNvMLBLGpXAZ3UudPh5TtOng0Ui248CSD1HRRW+XsvptgzYxNlzbhN5ZVI6Y3p87DUVb3InYqVg+2Z00SoUymPZlL9XwAGSqFnUJ+CmVi/VQoZJtcxvMhPieOeCLA4YKo/QGqW3ga/PAMnwPI00TfpKy9HV5UjSjMGXKFHUmfN85+dI7ZhyDr4cTHdk00tGciCKvn+dl3y9SFCUlTOaEfbvyJeB7YYaQmi1sK5mOKGiQL8CoqjLjkMxMkF1z+8zCMWPLYADgtddeK0k688wzlUj0NixdulTTp0/X1q1bdcYZZ+iiiy6q+v3CCy/U/fffL2n7+2Djxo0lo/bJJ5/UGWecoaeeekp9+vTR4sWLNXDgwA5pdzIbiUQi0Umgt83lVC6jUgmUXnpU2dTGq/9u54ZMBQ1NGpxc5uVSWuWyKx0tg2ndNKi5dMvYDoMGO5fVDS5ZR1okTNXuilkoW7du1bRp07Rs2TI1NTVp6NChGjVqlI488sjSNl/96ldL/7/qqqv08MMPl76PHz9eF198sd7znvfo+eef79DA/x0yNubOnStJ6t+/v6TmEfdM46JXxrgEe+X+pIdGT4zeY7T2bLBgjweD2YXIO6bGBTunVK69wSwSepU8htkVTxrMnIk8cxYd4qTDe8WALnr4pF2pO+H2ez9fb2dh4cKFksqsGidhZgyxzzFAjil8fg6c9Bl74+PzvkUMhhHVOImUQjn5R6yDVO7PZNc4+UfPnIFyjKkwIllnxr/4+NSY4aROFs9Mo0F2acGCBZKkMWPGKJHoDXjooYd06KGH6uCDD5a0ve8vWrSoytioxC233KJLLrlEkvTb3/5WL730kt7znvdI6vjyIclsJBKJRCeBxSUpC8BgXKZEcz9/GjbcbJRzCZvGLZ0iMh1c+mbNlkoDlH/juaOaKRGDQcfA126Hi44RA6C5zBdln7RU76WzsXbt2lIihiQ1NTVpxYoVNbddvXq1Vq1apeOPP16S9Pjjj2uPPfbQSSedpFWrVmn48OG67LLLOqz2yw4ZG/Y8WKY4Uk2MvD6qOdJrZ3ATA4LIaBR5hwZjQDwwo/oZDFiqpO3olfFeRNU8KTATSehywFArhDLGRbVWGDgW7UeNEYoKdfT6+Te/+U1JZS0X9j3G01Bx1eAExomPfZPMCSdSTs5F9GTEVBTJRUcxHJXnc1utOeJnyoA4sjscP2Th2Id8PNLhUS2iSADKY8aeFlklKv7y2S5atEiS9MQTT0jKbJVEz0Wt+SF63y1YsECnnHJK1ZLXAw88oIcfflgHHHCAPvzhD+v666/vsKKbyWwkEolEJ4F1PAxmmTAol8JpXka1g8b96UREWSeRgcksmSgJoNKQpEHOZTYGJPPaCcrsO8jepQjoyPGTgdFsp6+Z5Sos7dAVilE2NTXpqaeeKn1fs2aNBgwYUHPbBQsW6Oqrr67a9y1veUtpCWb06NH62c9+1rWNDd98R7Eysp8DgkqD9LSo9OmH74ETrYfTk4rWvekNsrYDvXt78xyAXHOuZVEym4Beoo/Nv0fWqcGBQ086UmtlRU96tWQ4KPHLCp5kcJwN0t5w0NOhhx4qqXlNE8onkwlgUBonOLJk/HsUE1LEUETlsw2OFYP7NVqeu7LtVkmN2lakGcLAOt9r3jNWS2adHmaZUK3WfYpMJl+43t4gu5VI9FQMHTpUK1eu1KpVq7TffvtpwYIFpQrdlXjssce0ZcsWveMd76jad8uWLdq0aZP22msv/fCHP9QxxxzTYW1PZiORSCQ6CTSonKLowHEWkYycDQZ+c1mQ8QeRk0OniBkeEfPh7e3cSM0D7rkMbpCRoBFLg5ylGPxJZ5DHIcPBe2N2yWUrfG/8DLoCdtppJ82ePVsjRozQ1q1bNXnyZA0aNEif+9zndMwxx2jUqFGStgeGjhkzpur59u3bV1/5yld0wgknaNu2bRoyZEiHShe0ytiw1gJ1NQx2EqZH0VMyOHDccd0JyGxEap0E1+Eda8LBQGqScRSkBWuleTG2wefgJ2lNduio5LSv1ft7P7IzXNdmvAm9ScoeM96GOhxuHzMG2gv77LOPpOYiRIyJYdYJPX7GbtBLZ5wBjxdNzlF2Sb2I2AVOtPXGeNRqQ6SPEQXm8ThUBCYr5hckmcGivsSYLb6MomwYg/V9brrpJknSuHHjam6fSHRnjBw5UiNHjqz626WXXlr1fcaMGTX3fc973qNf//rX7dW0FpHMRiKRSHQw7rrrLkll2QDD8QIbN26UJG3atElSOSDbn4w/sLPAWAoadEZUA4WOFWM2mAHiTxei9HepHKBsRDVOWKU1EoOMlue5vEdpg4gpoVPJdnDpNLFjaJWx4U5EoRgjqvLIGIko9iGq7upOxDoePE4U/FSUYeCB7k8PHGYgMN+/8v+MkaDny3Vpo7JqZ0vwdmYUoniWInEfahn4e1QVlhQka3a44u/EiRPruo564fggBzVRNTbS0ShSkTU44URCQ5HuScS2tcQ41Dp+a9FSdHpR/AjHRVEbI5bNLzoWvvL4ifZn3JD7ILVkmO7J9rOisY/jteyxY8fWvL5EItFxSGYjkUgkOghO0/VSNKu12iBjSrudAjt6RUvKNOCYks9U/HoDnJm+bIPQS2iVLEC0lMtla7IrdGgIBuFTyJAlBgyWitiyZUvV73vvvXfVJwUab7vtNknSqaeeWrNdiZbRkLHhqouDBw+W1Hz9np0pyh7xd+pl2DOidC+j2KMaKZHnFkX6Gx4w7oRkJ1hHhO2sPAdZD2oT+FodaxGpMjKoyfA9dd0J3wMyKdFxWImTVUnpRZJCjApEmd5ta7iaK2vH+JlFNVAihVCD9yeK/SDIoNTLCkTHiRgQtjfar5auRxTvUxQX0ih4bo5H9zWq2xpR7AeFqrw/6wF5OzORbg/r22QMRyLR+UhmI5FIJNoZNniampokNS8TwCUjGs1cLqXhSAOPgeN0wJjSHhmoDLSmsU1HsbJdjJEwGGtBh4YxF9HSpa+Ry2nU8+B5fQ3U07BD42fDpW23I43X1qEhY4NpWEbkfdO7NKKyxf70eWpJ4ErN637wuEQUuR8FSTFjw+2kOmVlBgkzW3jOaN05Kj4UXRMZEsYY0LuLdCbYTlbg9KcnJT4rDkRmEOwozKINGjRIUnMd/yhDqEiOmRNdFCBHBqetYyuK+iq/N5pBUrkNx2cUgBf9vaiNvGccn1TcLaLVqSDsJYVI2yR6Kfh3j81vfOMbktRhIkaJRKKMZDYSiUSinWFhNWpN+JNLxSyZQMeIBiIrm5LRYBq/DTcul5LJoGonWQN/mhWozEaJylOQuYiumUKEFCxkgLKPb+OUQn9sB5eQyZwwzsXt6ighw56GhoyNyHslpWZPgx0/yhAw6E2SESEi77RoHZ3bsdIqj+eBaFncWufxPag3BY2MRr1epBFlSfAZsK08nycRMxnMJPCA5cRBVqnoWTUKT84sSMXrYPZNxHCQoWCAHJmfokJV/N5odkmjtVAinY2WqstGMRr1fo8Q3ZOoujP7CuOLqBjsYMOowBYzq/x3SnZTlMnP1vV1Jk2aVNf1JhKJHUcyG4lEItFOmDdvniTpoIMOktR8+TMyamkUM9Cc20XLm6xoGi3rFgkZcvmWSQAM7q3clmwJA3qLEgp4TmbwkPmIjFnGpxBsDx1D3xs7pzfccIMkacKECTWPl6hGQ8YG1S+5Nktq0A+fAyryoKJOEKHeOIfo7xyoEYXIbJVax6MXZYYjohIjZiPKEGhUxyGKVeBkQy0R1qnhJBVlybQ1s+GBzsmOFCgnHk40Bvsq77/bbzo4ijMqYjb493q/R8crEjRqidGIKggTrWU86r2GIobDlH4Uo+H9nYFFpoLl1allQ7VeHydjOBKJjkMyG4lEItFOsGETLedFxntkZNLpsMFFgUWWT6DRTmYjqrXCvzOOIso4qfyN9V/InkRVWnlPogBhMih0HqMEBiNayub+dFg6qlRDT0FDxgazSxiTwdiMljpiLRRVa+Xfi343orQuMiOMY+BAjGJBaoH7kt6MmItIP6FeRiO6Vu9H7QIGazGuxu0ms8AB6wE4a9YsSdL555/fYjsjfOtb35Ik7bnnnlXtsrdLvY0oIylScCWNTfo5iqnh8Y1G2bp6GY9oAqyHzSvap6U4j1rbNfp7VDKcL0gjqhYbCVSRLmcsB+ch9lX/nUGZiUSi/ZDMRiKRSLQTouU4FqeMlnBtiD3zzDOSygaYA6i5ZG1waYnOCjM1jCjwnA6ej2snwNVq7bxIZccg0ruIEBncRfGjWNYAACAASURBVMYvHYZIBK5oqTqqDsvt6i0xkdiOhowNUoEMcjLo1ZOOoqcTKYxG1GEUiR+lh0XeY+T9ewBR9MWMBwdyZVu9jyPqfY9YlCjyiKM2F62jRwOT5ZPdLlKZRKRESkahKJajXlx55ZWSpH/+53+WVL5fVJP0dTgmJqrdYvB+RkqjkZ4GaeWIFYjUayMmKmI8ij6j41S2J4r/4TVwu+hFw2tsLXgNfgZeaiAocMVsOKZj+oUbLVWQWXEfWrhwoSTpQx/6UOMXlUgk6kIyG4lEItHGcAHBffbZR1LZWGZcAQOUabTT2KWxz7R9OxdeJo0cLWa3RA4gmRdmePi6zGhUStI7oJ7xJFHhzih4nqUUGKtBo5PGpLd3G83CsCwG762Px9IINNrnz58vSTrjjDOUiNGQsRHV8aCyZhR9TkRSuBHzQMYiCvShl+9ORforGmCOdme8QBQ0Vfk3f5rK87Gie+HtqWvB9eei2AB6r9QG8afPU8QaFRVHihiUeuNziAEDBkgq08OeKHw+xpj4mRi8T4w9iSZPo4hJiFgAg30u0sXg7zx+W6IoWyS6N0U6OPUyHEWKpByPrCbNeCJmr/ClE6n0Ri9w9wH3ublz50qSzj777LquL5FI1I9kNhKJRKKNwdR3ZmIwSJVyAja4zFy84Q1vkNS85km0hB2pdjKdP9L5MPh3Vlzl9Tm2RCoHeVMygccsWoJlnEvkbPpe+t6wkCeX/ckqRXVe6Eyzmi2VRhO10SbMBr040mKRFx1pBUTedqSCGdFt9oBWrFghqdypBg4cKKlMcbK9HhQe4A508kThAV8Zzc5gqCgS3vDAWb9+vSTp8ccfl1T22N3Gww47TFJ5cEfeIlkXU5imDH1clmM26D2S2fCziFisWiWmGwEVQ7k+z+v2ZElvOYotqTe1kF4/1XGJIiYjEkdy34xiTYrA6658XvXWdymKzeC4jcZx9PJoSQuk1jVQhdd9wH3X7FwkPMUsMgZBsm9R7tqlxROJRNsjmY1EIpFoI3j93kGvTLGmIWYDyQaPvXFWb2XmQ5RdwiXsyuyQyvPbG49SrIsMyig1v9LZiAz0aPmagf6RoiizS1gzhctrrOLq5TovzfpesKQE2Sg6sYb3z2qwLaNV2ShRBgU9H2ocRGvIjUa5RwPA51u7dq2ksnf/7W9/u2q797///ZKkIUOGSJL69+9f87hcUybNVnk9HBgRPBjXrFkjSfrlL38pSVq6dGnN7S+++GJJ0v7779/i8UmPmmnwgPJ56d15gDP4qUhUKMryYJpbEVyn4uCDD5bUPB6GlXcJVghtqeR1reuJSmzXqxFD7zqSgWadjy1btkgqv5T4PCKtjHrSAqPgwigwryjjJbonRdkr3L/euKOonhAzoFhMjPE6fFn4d9L63t7H+frXvy5JOuuss2q2M5FINI5kNhKJRGIH4eBSL8VES1NFBQVtCFHAzIYVl4Yig5JLR1F9ES49eT/GPbh9XP5rCVHNE7aFS7fRUibZnUg4sUgY0d99bb7XNvh97b43/rRj408ex/tfd911kqTJkye3eH96GxoyNiK9jEi1MtK7qDev3yjypn1+e4+/+c1vJJW9R+Luu++WVKbTLDtryjK6nkiAp1Ybo/gUt8ltjBgN48knn5Qk7bvvvlXnNkgteiDQ64vEe6ioyeNGHjQHsAe6Yy/qhYPIfF2sk0GmIrqvvM4i5dVGvW3ux3S6P/3pT5KkjRs3Smr+UvB3pt8xdZHnLcpqaanN0XiMGI0iBrIogynKtKkX0UvCk7jHKdko9mHS8HxZcanC8HGzhHgi0fZIZiORSCR2EGY0GDzO5TVmZNDAirxtL4tGKdN0Arw8578zfZ/ts/duo95Og4/n89sZoBZFLbAiLFkUZta4jXQ0eM+8ve8Rg9n5nQ4JVVV5z6mvQVaJjprb4/0y0Lg26jI2rrrqKknSMcccI6k4yt3gwOA6eZF3GXlOUbCSvcs777yznstqpgjKFKZ69T9qtZFgahjVSSNs3rxZUnkAMl4kynrggCvKSIiqtkb3PhLicaBbEbwubsVQH88TDuvRUDGU7fNEwEwDg/EG9SqCRvD5HHvzyCOPSCpmqrwfRZeiGA0iYhUaaXvEkpCCjwL5eJwi9qheDZHo+OwDFLSK4mSYbcIYEPcVzwPuW5GiaSKRaD2S2UgkEolWwmXqDzjgAEnNs06o6Bml2dtgsgFlr59Lu1FKN7NebECRLbAB59/93e1wCj+9e7IANATdzsplVB+Ty1lMo/c1e5nM94yZNFwq9fF8bm7HZXyD10ymhA4BdTWitHh/+h7ecMMNkqQJEyYoUaexwdQgZqVwXTmqq8GUJcrL2tMo8rLpAblzrVu3rsXrOOGEE6q+e+BQmKbeSqv1rE3Te6R3dfzxx1cda/ny5VX7L1myRJI0dOhQSeXBHHmvpB4NBmuxNkiRHgUZANKnfgb1ZqNY48Rep4/PSTIK7qKeicHJntdRNBFF2i4GGaqVK1dKKmY0DO/XqB5JoyxBS2BQoRHpXvBe1Jt5xfMV6enw72wXgyjdZ5l5xT7CFzLTNMlyebtrrrlGkjR16tS6rjORSMRIZiORSCRaCQeTRvU1DDMLlNk3aBDZW+eSDh0zpu+yiCT1PKJlUWan+HfGMUS1VxynUFlwkgG4jI2opc1RuR3rsBhcIrbzSjG4iL2hYCC1THzvvD+dUDIazPDx94zdqEZdxgZriRh+yAz8iTIgjKgKo2k0D7Codgo9Hw9kxzcYZgH+9V//tapdjC+gfG2R8mEjXibvga/NHdxt9z34l3/5F0nS/fffL0k69thjJZUHgDs+2SV/5wDnQOVkSKVTTpJF6/XUMKhXCZMlst3HOOA9qVk90s/EVCWp2igegev6rc2YcHscq1Epz1wP3MeNiK2LyltH2SmV+0eMAxnHKEPJYGwWWbMi3R0etyhTKCpnHsXVMBuNKq18mfnZRfE6UZxQIpHYcSSzkUgkEq0EMyooEEZDjQUFI8PMDIE/6STwvNSEsEHIonVGpMbJOIhI9M9/pwZFpQFLMTYGIHNJmcJ3NAaZYMB7bIfEjgyD6Zm9EgW1R1VeGRfD6yLz4eO6AvC5556r3oy6jA0qgvphRIE0UT4+j0fq0AOEDz+qf+HzsGTwsGHDJEm//e1vq/bz8V1hdL/99pPUnNmIYlFaWqOOBrPhfT2IjzjiiKo20XMfOXKkpOYxDL7H9Cq5Th2xQgzWioogcTKKFEZZ9rloHX/OnDmSyjEoHKC+P6SFozS0KDuH7SYlygyMepVGPSG6r5mBIt797ndXnf/BBx+sOg/jB6I+zvYYrWHXomdIcLwbZIfISkUMB/tGEaMSIRpjDDgk08qsM+9HvQ1KeTeqGZNIJGIks5FIJBINwiqRb3zjGyXFwfM0ppnlQWfCsCHHGivUmqBRSp0PL0f6fDYg7dy4vT6PDSz/3QYatSkM//2JJ56oOo9ULkFg4b6o2KOv1UYflTrJpjBAmfEyNjJpTJKh8P6+9qiqa7TkTEeN7bMR7uvv7ajL2PBDirxMpihFATSRF1nkPUdeszuFYzWYV+/vTkszo2Fqsijrhd/rWeePWBwyC+6Anhw8+K0w6gh7FgGyR00ZYcZuREWQIo0SKo5GtT6iDAZuF8HXzRLVjN9hMBf7GJ9dVPmXFUPNTPi8FE8qqmxMxVRnE/3whz+UJA0fPlxS84nPcUOu7htRy/XqfRQpn1aC/be18SqM+SBLFL0A2Y4iXZ5IpZZgnyHlz8yjSHsmyshKvY1Eou2QzEYikUg0CDIONPJp0EWZC5HjZqfCgdAsSMhlNLfDRraLUG7atElSbCjaaaG+BmM5GMQb1Rfx9pVtpuNDh4D3zseKikn6uIzFsOPGe8M4F95LPovKa5CaZ/xEDkGkeZKBxttRl7Hhm8bSunwopKeMiBkggxDVUok0D+yl2mv1gOEAbWpqkhQXH4o8P4rLRFUmK49N6o60KvUeGNBl9sUDjLoMpkWd1UBmIIr4N5hFwgEWZRZFaWgGq5tGYLt5rw0K7jA2o94aMWaKNmzYUNU+BosxE4HH40TCkuDvfOc7q66HLwH3yUiCuV4U6aDUQr3aHEUxHEaUTkmKP2oTx1tRBlOR7gZjvfx3xvfwpUFWi2MzYgcTie6MpUuXavr06dq6davOOOMMXXTRRR1y3hxNiUQi0SC4DEhHK6p9EgmOFRXHo3FOw8ifXjZ00DyZCRrr1JiIHL6oPIHvg4PtK1O7Hf8RBauTPaFR6bYxhsMOg6+Zy/Y2OqOKuHTQouBsGqc0ivmsyXLRqO0K2Lp1q6ZNm6Zly5apqalJQ4cO1ahRo3TkkUe2+7nrMjbcaegNRloABr3DyAvzQ42USA12UsdqeD/HA1DLgN525L3aUzN7YK/Y+3Ndv/K63TYPCHY0esKRN0fKz8Iwbovb5kkl0jqIvEZeI72/6JMMB6nDotowhu+h20eKNKrQydRCZiRFn6RKI6VSykGzL1IHxGPC1XiLxI68ndvPQletrR9ST6lv9gFS6UXFvYqere+lr520eL3sTZGmS7R9tITBvhplajENlXFSiURPwUMPPaRDDz20FLw7ZswYLVq0qOsYG4lEIpEog8wEDSt67ZGXTeOZGRaRwefj21iO9Du4BE5D0uchs0FDK9KSMLxMWOnFFzkGZH2om+FjUdCQTIiv2cvpPp4dm8hRYbtYpbZomS8qAUHmpCstx61du1b7779/6XtTU5NWrFjRIecudosSiUQikUh0e9RiCRuNG2st6jK5bOmx4l9U1CqitA1allSSi2SJfVMoT+4lCuZL0wsoKvhEb8HR0MyJpwhQ5TY/+MEPqo5puXG3sV+/flXfaQXznno5xZ6D2+RlFVv/pIi5BGXYw3G0ur9HJer57Gi9Rx7PV7/6VUnShRdeWHN/b2+PzPfcz8xeiZ8lo+Wj5QdGybMSIwNioyj7aK2da+6HHHJI1fHXrl0rqXz/XHCO3hGX5IrSOwmm1tZKZ+U5o6DcqKplJG5n8Lv7EvtihMhrL0rrLUov9/VQpyFaauS983d71IlET0FTU5Oeeuqp0vc1a9aUkhLaG12H30kkEoluAuqkRNpCpPojxV06XHYiopgoG+l2GphZR8fQYJwKlw6i+laROBl/r9S/YVxXJH1OI5dLOv60MRvJhvu4Xk7xPbLD5lg+Grl8Br73kSEfPfMo7dnXfdVVV0mSzjvvPHUWhg4dqpUrV2rVqlXab7/9tGDBAt18880dcu66jI2orHckmhOJchUprbEAGyOxfXznjrvzuRNF3jgDxFhYzhMAU1uNn/zkJ9GtKQTX8xjwGEWtM5U0KlTmqHNXn+QkwMmAIlw+Pgc8nw0HFNeqCQ9wgn3I7SDjQSlsnteIZLz5MvB53cfYN6M+G3n1Pr6Pa6bKAaFcZ/bE5+9mqHx9RlERwIj1q2xfFG0fTZrRtRcFfvN4ZEqoZ1CvpD8RMRlRCiz7UiSX7vZ63DPuwS/yRKKnYKeddtLs2bM1YsQIbd26VZMnT9agQYM65twdcpZEIpHogaB3TmOaejHMdKEhVFRvxrAxS0VcOjde3qOBSMXiqOCb20vUo0obKcIavDaemzpKXmq1c+lPXyuX96nCTNYocqwoUBYxFVGl7OiedVRsRBFGjhxZqr3VkWioEJs/I4ovitUoYjY4MHk+f3qAWaCJa8IUYPJ+9jrdbtJ07sz2ZNyp77vvvqJbUzcoBuW2kGmI4l/sfZGqW79+fdU1edLwvSG96smMueiM8YiowiiXnKJgHICmEB3DwmfPyHF+kgGI2LSiPmhEsRIRPVzklRu+r/70ZG6v2XCfM9Pl7RkhT9QzcUflAKI4HiI6dxELxO2i7Ysm3aLYqui77+Ub3vAGSc3pdYN9nsymn5mfUSKR2HEks5FIJBINgrEN1PJh4LY/qcRLA5DxCJEQFpfpjEhtOdIkWb16ddX2Vlu2cU9DMhIVq8eQpfHJWAkb+nb23Lann366qo1RzS2m61IB2kuodPQoXMbg8qiKOR2WontQFDDd01GXsUHPiOW9ua5eJAYUPTSej16zGQ13Rnce0mHU5GfhNXced0IPXLIAbYHly5dLkk455ZSqNjEbhbURWBI9kvV221etWlV1fNOnvLd+Zo7xcGxFJMUesU+MoykqG+6gqIcffrhqe+ayM9aCyozsg1GwGdffmZsfFXzjen/U96OsHU5Yfs5kNry95eiZ4cTzFol5VfbZKPuCMQvcnveQLEtRTEekX8AXZlGhtogpKYrpcN8xve5n67HEUvOku30czytk0xKJROuRzEYikUg0CDoF9HJpUDHAO2IOCKo1s/ZPVKXYiILjDzzwQEll+YDHHntMUplFcKVsSm1HhqxReT3R8jrZFx/LS8JmNOxU2mBnIbXIIeN5WdwuuhY6PFFgM68vqlqeqEZdxgY9A6rWMeKfGRdcv486Kr1qSkv7Ifbv319S88JLEbNBzQazAVyTtUfjAdeWiFT0PIB8z5gl4ntML4wUn7f705/+VHU8rltHBeOi2AaDsSVRoJtRVLAtoo+jWApep/sgWTB675xookC+SCMiktCPZN3ZHkvoW1+FsTBunzOsvL0RUbNkfionOF8LxwWzLzguyexF8UNkIFhczt8j1id6QUZ0NBmTSIeD1+ux5fa4vb5+viQ4z6VceSLRdkhmI5FIJBpEkfdK54A1dqJy5UZUF6qoJlHEGjAuwsuodtgs9LRmzRpJ5SXrgw46SFK50JrB49fKSmGbuTxnh8FLwAx2t9gU6whFQeFGdE8iwz0yhqPU8WhptShmo94A7Z6KuowNMwEUOyGYQuSO7PgB6lsUKRTy4TjK3A+XAUKRx0T6jPt7IFJV05kTVoG01+uUqsr7QCbB9KS3JUPBUu4MDPM983HtARukVUm3ss5A0To7i1PR2yNDQK+PA5HtNczYsNqkEQVfMabF7YgC36IaDmTPqA3BdkeZFVEMBxkkn9/6G2SWqOng4znugJoZBgWOKp8r1ViZdulPT+JGFH8T3QsyiUwp5DwRXQuFpsha8fhR9c1oHuAL18czohiTqA8nEonGkcxGIpFINAiWIacjZcMlKp8eZVYUSbbbYLIxasORBh6Pb0ONAeRRlsy6deskleMnzIT4OrnkVkuTIpL893efw8yG2+KMGFZKdhvtsERLuDRquaxfJCYXGcORwxHFpPAzctJ7CxpiNugJGaTJSOVxLTfyTBhfQHqKEr1c/+aA80A0JRiVd2etFXs0ZlIcTOX2OaajknnxvfE57D39/ve/l1S+h/6k1gfvFdvq796eXiorJRqcfKKB5O3sVfqTMRaR0A1ZpEiS1xoGRVoIjEnh9frvpIcjhU3eX8ZkkKEgirQk2KcYe+P4IN9/X78VYL2dGQv3xUgm2mDsRq028IVH4Sif020gExCpxnryZp0X9pGo1LzvtfuMx4bHt/f3i5XH9TjlS4UxW5yfeH1sj49/zjnnKJFItA2S2UgkEokGQQeJzEYUMB3J6RcVoyM74IBjxoZEgdcscsnlSv9uI9jOhg0/G8teUo6k3iuXV72MThVVXwv1Mxz47yVHG5kMOGYRRy4hUxzS99RLt0XsUVQ6gsZulNodPbsLLrhAvRl1GRvueJFGQSSVG9UiYcBOVJeD6/XMgjGi47JSqjuLj09Gg4yJt7c37vPYA6uVVcO1f3qiHGDejnRnpK8RZUNE6+cR+8OB6ON4UolEgyLpXrevqFKms2UceMaBTW+U2S9FcQCRWm3UZ6N4oSh2JAIZIk6+vi9+Pt7ek7vbxXggxnTwpWV4rEnlZ8/YBN4rjyfG3xTVMCLjQXYoUvJldpmvyffGf+f4ZlwPM5IMZliRUTU4TzDLzplBiUSi7dCisTFs2DBJ5bLZfIFFlhwn6ih1LbLmCVb9iyK1DR/P640f//jHa56fL25POqTGKyfyWuevPDYNFXoeNMh4L3mveE3R+qH3jwTWil6W0QujXoEzvmxnzZpVczuv07JkfGQk8MVQJIFPb6JIdKzo+hqtZxBFvrt9TzzxhCTpIx/5SNXxaXhH68NReyv7S9SHoj7GNheN5yKPMGpbtIxSlF3AZZxIYp9jsKjvcywdcsgh+tjHPlZzW4LLeWxDdC+i51kUuB0xFryHNKaj/mWngl679zMr4e38DmDshudkG442lqXmUgh+jnY4vITo9wpFGqMx7u0Yb1IU5xIFoxcxGzZufa3c34jE8Xp7FopRF7PhtCd7+BEDUaQcGqUi0ROKUpCKFA15HtJeUbYL1//59ygqvbKzcWDQCCjSNKAWQL2ZAbXaUokiFccigzG6tzxvUXqZ4XQ2TzSNvhDqpUCjyb7e8xUFjUV/53k5AXFyj7JoIuVQ/53GZGU/4bhixkqkm8H4nshIqNeAjbLDGhVBKhKH4vE5Fovg/f76179q/fr1GjNmTF37JRKJ+tGisWGpbWPZsmWSyvLfLGwWvWgZDcwy217O8O9MlfXL3oGetrajaGQf/1Of+pQk6Ytf/GLV8Q0GbXoCN53KJQ6iMsDMbaFEsuH1R7bRVjpTXRkYGeWSG742r3v6GZGpIFvDVFkWoSLbEzEE3s658h/96EfVEn74wx9KKq/PchnIn/YqGEDJvsUXqrfjmjKXlaLCbdFSQuTtG/SGuK786U9/WpJ09dVXS2o+ltxepkwzOJqS3JVeVxSMyiBZlgOwdDqDlOkZRuwZDSQuo3KpzdfCwFQ+A98bt8Pjkp4miwNS6C0qHOnjeTm1Hvj5eF8yDewvUdovQeM9arvhe8m5inMWWVw/64jl4rPYuHGjpDIrYaeBwcK1GDbOiWac3WY/30qjrxKM/YiYbRbUMxy8X8TIE0xM8DOnMRs5OFF7eisaChB15+BgjZT3ojVTTy6MxGfxIg5UT8z+u/eLqjoyLsKdhUaRg558HsdVUDOBapOVa91RSWi/NP1y8He/EPgyjLzPaLnFbaOUr4/re+xn49+5ru1PGz8+v+9xVPCJkxgnigjO0vEzZy2XSKQo0s/wM+Y6PON9ipikiM6OmKCi6riG2+HjMwbDfZtGhF8mvC/UymAWklResnLfYAEqjl+qmfrYfjZF4kkGxy+zTfwsOI6iuJrICGEZdBZDiwpf0ciwgT1+/Pia21fCS8tRhlv0AitaYi5i2vidy55RsTDut3LlSknS9OnTa7aPx+WL0n2JjmMtx49jwb95HqZWDB2giOkuYsyjZbjI4IvuWRQvVy+4/+WXXy6puRPfW5DZKIlEItEguMxZtBxp1BtoXO9yXhS/EhkbZPSKYsP4dxuOfKHXehFHhhFFFXkt0XJ8a+PYIqOzaAm03uW7CJHx01vRkLFhmpEMAz2kiMZkFDlVNWktM7PBv7t+BD0jRvDTi/DvDEiiMqrPY8+Ocrl//OMfq84vlQOnvK0ZBbI8TDHzNUb3gktVXNv3dr4W/84lqkg/glkSpixJXdKDYtaFv5999tk1z0OceeaZkqTbbrtN0vbgPKm5FxQFhpLBYJVXPxvuFzFEkfYLwb5OMHODnxwzVEL19duDdH8iOxixdVLZ23afrHcJjtlbps6LXqBkGvy72+g+yKUwLu0xjTTKNDL8DMxMeH7y/FJvsGcjsFd61VVXSZKOOOIISc0VcYsy9KgJEgW/RvFqvpcO3KwMzKzcnuPFS8qf/exnq9oTZeh52cTj39fpOL6WMvR8jd7Hx/RSq7f1XOP+yoBSZlc1mqHnpWUup0RzAZdizfS1NkPPS1YnnXSSejOS2UgkEokGYdG6xYsXS2pe7DEKzC6SAeDyBWOsmMrtF7O3Z9AtM/m8REyvPwpgtmPp8/mF62XQlrz9KP2cGS10iMiE0EhlQHOUxRQZFUYUhG1ERk20nBItjWVBv+1oyNiYNGmSJGnRokWSmouusMqqP+kF04tnx+fanrfzwLIXz4qXkcqkj28hHEr3Ml3VfzeDQqGbWpkX3sfncFttzfMa3SE9mH1sSvHy+LTy6Ukx5Taq5eF75/NR38HeBj1+Ti5RUFe9OPXUUyVJ3/nOdySVJyIKAHESJrMRqdeSoYkyFCI6ml63t+PEZ1DsKKqw6v5AtVsqzPo++Dp4PrMHlcwVAyujNWeyPT6n+7u9Wj9be6ic3CPWhWXYI/XZKG05qlvjeCczL+eee64SiUTXRjIbiUQi0UrQ+C0qAhelltugoqYDDTFmCNnhoxHcUuBmPe0w7AzZ2PVShJdvbADWWu5jELRrnXi5LhIuZJsoKkmnlEH0ZH0YsEwDn0vSRYHFPB+Zmyi8oLejVcaG19y47shP33QPADIP7izenoVy6M1GEdisCMoIamaCRPoD7MzejymCtahDDhQPTmZJkGrzsTgwGGEflTUmO8OBwsmP3iI/yVBEwVHe3oyIJ5/W4oMf/GDV9zvuuKOqvdSX8P1iTAv7HFPzIqamKPKcEwurvPr8ZBOoJBqJp3ECc7s9iTM2h0FxlZkYUXZHpG/Ba/W9df832xK1OVoCoOorz8/j+N5SYdSfyWAkEt0XyWwkEolEK0E5gCi11YhUjJkeTOOay2ren+nM1P+gYGGU6cFlSZ6XS+ReLmbKfOX1MgjeDpjb4m19TLed104BRC/nUYWZ8S1MI+eSr8/n/ah1FGmkkFFh0L5BZqa3o1XGhjMObr75ZknNvXKDWSIMyKHmg/ePMie4Dk59AMPHI71Fr9adhFUxGTnO6ORaKVX08uiBe8B5Ow4A7u+Oz4h+f6dgEj14DmhObmSXokA1xoD4d7fDLFdU5bW1OPnkkyVJt99+e9V1UfCNzzZa5+fExsk0Ss/j/SFVG6lWUo2W7aRGRES1+rieON2fmCFVGeRGITH2DTKFzCYxfC5H0ztWgn0rYjZ87ynM5sn3rLPOqnnNiUSi5yGZjUQikWglmHJKL7uoLhTT9Wko2uBjADQdHm5HJdOi5UPux2J7FMOjkU7xucrfCSCB5wAAHeBJREFUaKDTSI3qwHC/KBYj+mRaMQvueXmO548cg3qVR7m8X68cQE/HDhkbY8eOlSRdf/31ksoSttR8iDIHWJWSmRj0kGpF3leeh7QZByQV7dhpIo+P0fPu7JWIPF1miUT1WKJYA9OkbgszenzPfBxmqfAaitRWuR3ZIw9UZypYL6Otceutt0oqX4czg0gjR965tyN7ZbAoUyS7HNXvIHNhRMqinFgZD+SXlu8vY0LcfjM7pqSZESaVGQhWT+ULjtfOvsgXixkOw23xdu673s7ZIp7UZ8yYoUQi0TuRzEYikUi0ElOmTJFUrhtVpPzJv9OYpJFJJyZSo6RDFTEsEbNCA5TGe5RSTjG9yvZRmJDLdBQwpDMaVbqlcWxj2I5WVFE7yvhh7RaWduA9jZgXOpYZq1GNNjE2Jk6cWPX961//uqRyJ4uKC0UBOZEuh+H9/EmKjwOLwVWkufxJNU3Dx6GqY2WMCr08Booxu4TUICk/nptt8GBnUSvqNLBGBycNDmzeQ+o/8Fm3F6zad9hhh0kqX3dEbUbSwAziiooisUQ3NWIYU8FgtEhQiHESjAvihGY1TF+/n6v7HFVz3e98fyqPzUJn3tffyYKRrfE1mKn0362OS9VIFqzy9sloJBKJZDYSiURiB2HDy0Zf5HREFUojQUIG10f1Ohh3EKln1qtV4fabsag0ZivP57/z91rwsek8csmXy+711ocpqqFC9ojHYVA57wWXcKNCc26Pjf3EdrSLsdHaKHPXG2C5cZbhpoqmO09UJZAqku4MXNenUikHJjUOKr3kKF6EaqRusz3VKA2MlF80iXCyYUVd0pv+PP/889WVYU2FH/zgB5Ka075RcBmzdFi7JZq4WE3V3xl0xvtINoBMSiSVHNHTVHY1TT979mxJ5QmMcUzum1J54ve4cX8240D6mVlkfEGyVgVZOn/62j3e3A5nFJ1yyilKJBK9E8lsJBKJxA7CwbA28Oj1Uu4+CnqPvHOjXmaDQoTMRqERHMkSsL1czozaX9kmCt3RqYsKBTLIPkIklBhVlaU8P7VOCBbujJZiKcvvUhWJ7ehSxoa1GmbOnCmpXFnQ4jAG6TBG0TNgh8I3UZYKOx+3o9ZD5To+tT04UDwJUQeDLAwnKSPKGvF5fH56oU888YSkrs9kRPAEEKXg8T4y08kTBJkiMh2klfnJl0YkjhRNnKxhQ+qVsTHTp0+vOg7VM+fMmSOpnAFWOUbMNLjf+1xmHDgeokylSKeGlUsZLMilAGb+JBKJ3ocuZWwkEolEd4S1FO6++25JzUs2UL0yYgS4H5dZWQCQTkpRVopBZyhiUmyYsmCjjXgzHazJIjWPcfC1+xqjGA4aucxi4XbRNdBB8ydjRMgyRYUCGcRPAUAmGlx44YU1291b0SWNDXdwMwgcgJF2ATMJ6H0WlQiO0tNqqTRK1YOAAyLq6FF55Cgmw/eC3qc/6eFTDIjr8d0NjI3wgPak5+v3pOdnxKwf1vtgYJ7BCsYRA8XtDQbyRZO6+6onYGahFOGcc86p+n7jjTeW/u+CVwx0i/pxJE4UXVukbeJPx5VYbyM6fiKR6D3oksZGIpFIdEc8/fTTkppXNqVxy6BaBiJzadcGmw05ljWgg0VmI2IujEj/I9LVsPfOYPpKA5VZJWRdfA+4HB6l4UdtphEdBXEzIJrZL5RC4JIn28MSB97P8TttjW3btmn69OlavHixdt11V11//fU6+uijq7b5y1/+omOPPbb0fc2aNRo3bpyuvPJKSdLChQs1Y8YM9enTR0cddVSp5EhHoEsaG9TbIKPBgCMjqoFCjywS3ikKMGL7KgdW5L1FKWf8PYoVYI0Ve8LU6eD6O6+5u8IDmHV0PIFRSZUKrBTsYbVYpuxFmjAEnxO3Y0lvBuS5PZ6YnnrqKUmtj60ZP3586f/Wuenfv7+k5qJKkYQ2/84XFcdPVEWWqq0dpc2SSPRkLFmyRCtXrtTKlSu1YsUKTZ06VStWrKja5rWvfa0eeeSR0vchQ4bopJNOkiStXLlSX/7yl/Xggw/q9a9/fbsZRRG6pLGRSCQS3RE2rBYvXiypeVYHGY6oKqz3oygca6dEAoSRgqhBY5gOFGu2MCODQcB0cirPzQB+Mhp2AHxtNHbJWEQVdumk0viNShJQ0I/xNNRA8fX4d4rlnXHGGWoPLFq0SOPHj1efPn309re/Xc8++6zWr19fWjYlVq5cqY0bN5aYjnnz5mnatGmlZIW99967XdoZoUsaG37YTh1yJ6BgDmk3lkc2GC8RZRQwloNsQUveKwcv/x5lwnCgcAC5Q1s3w9fICH8WGfK9mzp1as12dRe4BsuBBx4oqXzdnvz8PaoUzImKFYJND7NP8HhRXyBzxD4UTfKOZ9iwYYOk5jEYOwLr3Fx33XWSmivjkqrni4m0MyfrqMYKJ/cMkEsk2g5r167V/vvvX/re1NSktWvXhsbGLbfcog9/+MOluerxxx+XJL3zne/U1q1bNWPGDJ144ont3/D/jy5pbCQSiUR3ho1IO0hc32c2SVFAcbTMyuXSKNA8Cg6m8UyGw8Y5U+zJDhi1nC6Wn/A2dhgYuB8t45GxiBw8bhcxHIxLiQoSUoHUYKxGe+tq1LreloKvFyxYoG9961ul7y+99JJWrlyp5cuXa82aNTr22GP16KOPlgQm2xtd0tiwxoAVRd0JrSXASqiucungKWsPFKV3RZkhBAOWjMrtqehZxIZEDAe38zWtWrVKUtlLpWKpO74ZEGc3dHdYX+K+++6TVNYrobplJOvMOASm1XFCMfg86MUXxWhEk7vbZ8bG7bj22msltU8VXU7WEZtWFCvFFx/7esQQJhKJ1uHqq6/WvHnzJElDhw4txXZJ24M//a4jfvWrX+mll17SkCFDSn9ramrS29/+dr3yla/UQQcdpMMPP1wrV67U0KFD2/ci/j+6pLGRSCQS3RmTJ0+WJN1xxx2SyuUJoiyTiLkgaDiyaiyN6CgYmAKGkTidl97McHh7Lz+yKm2lcR0F4FNN1YyHr4E6HLzmontVJLAXyQgYESvk/RjD4TT8yiDttsK0adM0bdo0SdL3vvc9zZ49W2PGjNGKFSu0++67t7iEctppp1X9bfTo0brllls0ceJEbd68WY8//rgOPvjgNm9zhC5pbDhNx1SdA2/c4elhuZP679YqYABPlKUSrbPz79HAlJp7d/SsucbPcspUsHTshT1g0rCmabmfr7lI4re7Yc2aNZKkfv36SWp+vZ7AKLwTxcLw04ieRxTIZ5DG5t89Ifm5m153zRyzc20J93u/6HgtjNEoKkPO7BN/Z0nterVCEolE/Rg5cqQWL16sQw89VLvuuqu++c1vln4bPHhwVRbKwoULS0HKxogRI/T9739fRx55pPr27asrrriimTp3e6JLGhuJRCLRE3DyySdLKiuLsgCjEYnIRQwHg+IZC2JwqcuwI0eDkQwGlU29rOvtKX1faYRTadPGKPU2uGzHwOUIUVYKnUU6EAZ/52cU3+LrsRNsx6+90adPH1199dU1f6s0NCTpj3/8Y839Z86cWSoH0tHoksZGJFcbZY9Y2IYD2Z3DcQyk79j5vf4flWU2ogmg1j6RF2jqkBVso6JArPXBe2MvlpOGq4WytkZ3g1MKly1bJqn8zFm7hJkWUeAdaWQKAHFy5nONSnIbfgk4aIzlps3QGGaw2hIMyOMLJmLBotLbkb6GWRtfQ1tm1iQSiZ6BLmlsJBKJRE+CDTHHOtjws9HLUgtMbaeIn50JOhd2mIyoyF4kn0+2wZ9ur9tH49hOU6XhSpbES4dRFkpUKTcKzo70OOhoENESaxTg7HvM9Hmnr7eXrkZPQ5c0Nqyi6NgNd06qPpIuizJASAmaBXBkrzuT18+d8WDvmYFNjOqXmit5Rl6fv7utrmwbRfqT0mMBJMOeMxmO7s5oEI899pgklSKoGUxGZihSYmWFUqb2+XmwdgqZDKpyUiGU4kjsH/77mDFjGrkNdcHBY2TRqKrqPhOJJHGcuc1mDB0MmUgkEhG6pLGRSCQSPQn2fu+8805JzY3kqO4GvX2metupsOHIIHo6HwaZjWhpjIYojWwHA3tJuhK+Bsvm24mj08cMGWbqFOlwGJFyKK81yjbhMjv1QQzLD5x66qnNrjkRo0sbGxdccEHV97lz50oqdwpSdxx4/u5186hQjweoteJ9fDMb7JScECqPzUAp1sBg6hhLThOeZCgOxOArDwwzHD2N0TB8XU4pHDhwoKTyfSd1S1raz4nbkYqlVHGkj1IUxOaXgydaw0FlLtw1fPjwFo/TGjD1zZVh3Zcc48QUPqYi+tNl1BOJRKJRdGljI5FIJHoSXBTr+9//vqRYXC7KpLCDRaPZ+3HZz4Yil2PJqERCbXaGbIhyOwc6e3m30gGjY8WlQ9YkoWNAp473hDICDOq2oR/FcJDRYBC5mRdfu+/FunXrlGgc3crYsGdVmV8sNafHSAmSsWBBINYPWbhwYdX3SCSm1jaRwIw7KqlAdnh/MpCMHre9Tw8EX2NPZTQIpxQ6l9z54r5PnLjcN8h6cfIldRvVRKm3OqxBLQvTzx1Zu4aiQy4v7Vgls2Knn356h7UpkUj0DnQrYyORSCR6AlavXi2pObNBBsLGKbNB7Iz4O9OTo3ogBGUGfJ6ovoidJp/PjAYzTKQyg8GgeEoNMEuFaene3tfKJVM7EL5nUd0WLrPTgeB56RhaeC8LDLYO3dLY2GuvvSSVO6fpLneGiFo0G+BO5qwXgp23HkQlm7mm/8lPfrLqu2ti+Fo8UBhPwsHPyam3ahuMHDlSkrRkyRJJ5b7hyTVKY4uEfkhjc/JmQF2kuhkdj8JAnYmxY8d2dhMSiUQvQbc0NhKJRKI7Y8qUKZLKS7Y2ju1s0Gil1oTZAC4Xsm6HQW+ev5PhIIsQ1RVhXEPlUrP/ZtihMqNhdsbfqarqY/meRBV0/Z3HcZu9XM4l1IjhoIPg62iPIom9Cd3S2Hjf+94nSbr33nslNU8js6aFO0uj6+JRCeOWlEPZQSPhGMIdnsWGyIx4oHqAFh23t+G9732vJOmee+6RVGY4eJ9IkXKCI+PASTaqeWNElVBJP0esWiKRSPREdEtjI5FIJHoCPvShD0mS7rvvPknNReVY7sBMgo1YZm5Qb8OfDG5nIUgGUvO4UeyHl6YZfF95bh/L8R277767pDJj4XNGS4xkRJjV4nP6d5/PjIY/eS+5xOpr8Pmtp+FnlNgxdGtjY8SIES3+/o1vfKNVx/WAjjJHajEf7LhGVCDJaDR7ZMGCBVVtyYFQDbNeN910kyTpgAMOkNT82UWiRnyOkYQxa6iQAeGE5WyhffbZZ0cuL5FIJLolurWxkUgkEj0BW7ZskVT2+qmmSeE1G8ssPGhHyYyDjWkLuFEQMUrn93lZw4VGe0vLxVz6dcwFYytYwdYMBCvgkl0hG+PtfQ+8dGlmg0ug/PR5U0+jfZDGRg24s/qT6/pGS/ESHoyeHJiG1Vq0Rw2Nnohx48ZVfbfiqPU4HOcTleCm7gZBBsN9xUyGizSxbsj111/f4JUkEolE90caG4leAYuAvfjii/qv//qvTm5NIlEN19n40Y9+JKl5/IERLdvRWKY+h+MlzAqYQYlS6ilCZ2Pa7APjJyxSV7ncaHVRnytSK2UQfFSM0gyFHQV/km2hxgiLVtKR8PY+fmaftA/S2KgBd2LXVPEgaKk2Cov4WPPDHdiDPdG5eNWrXqVhw4bplltukVSeEJnRxGfMwDvT1K58mqqbiUQiEaNTjI37779f559/vp566in17dtXxx13nGbPnl0qt/7MM89o6tSp+sEPfiBpeyDoNddcUyqMlujd+N73vqcvf/nLevTRR7XLLrvo/e9/v2bOnNnMoHvmmWd0+OGH6/DDD9dPfvKTTmptIlE/1q9fL6ns4FD3ghoSdIDISERVZX18ak5Qfj/6pNJoLThWg+qiZCgiNVTL55tpiJazfdwoi4XB3BTYM2vja7GTmWhbdIqxceSRR+ree+/VgAED9MILL+jf/u3fNHXqVH33u9+VJH32s5/Vli1b9Mc//lHbtm3TySefrBkzZmjmzJkd0j6Xg77uuusklVkJazfU0lgg3bhmzRpJ5QHAqp+J1uPPf/6zPvvZz+q4447TCy+8oLFjx+qTn/xkqSqw8elPf1pHHHFEzSA4VkQ1vva1r0lqHrx23nnnteUlJBKJRK9CobFxxRVX6Gc/+1kpwE7aPvH27dtXV155ZatOyvS/vn376ve//33p+6pVqzR69OgSk/HBD36wZIgkuhf+8Ic/aOjQobrvvvt09NFHa926dXrzm9+s22+/XcOGDWvVMStltnfddVdNmTJFn//856u2+elPf6pHH31UZ555ZqtToBOJjoYDwC2/b0bCDg91OCKFT2pXMNPDy4A2plnKwcY2l4ejWipUHJWaV6glg8CMGmaTkLFg23xN3J4MCKvKUqfDx3FQtwt+JtoWhcbGuHHjNGPGDD377LPaY4899NJLL+nWW2/VkiVLdM4555QqRxIHHHCAfv3rX4fHffLJJ/XmN79Zzz33nPr27at58+aVfps2bZrmzJlT8j7vuOMOjRo1qtFr22E4k8CaDZTXdSeXyoPSFNyGDRskpUd8yCGH6PLLL9dHPvIR/eIXv9CkSZM0ceJEDRs2bIf6TyV+/OMfa9CgQaXvW7du1bRp0zRv3jz9z//8T0PtnT59ekPbJxKJRKIYhcbGvvvuq+OOO0633XabpkyZoqVLl2rPPffUkCFDNGTIEM2ZM6dVJz7ggAP07LPP6plnntG8efP0pje9qfTb0UcfrRdffLGUpnjCCSe0qtDY4MGDW9W2RNtiypQpuvvuu/W2t71Nffr0KbFUc+bMaXX/MZYtW6YbbrhBK1asKP1t1qxZetvb3qYhQ4Y0bGy0N7JPJuqB5fetLMrYC1aLNcwsmC2w1+6UbNb74PKvvX5/Uu+DcRVUGK1M8Scr4rYwDoVFE31u/50lGpjVwmXtqMYKhft8zQ7yHj16tBLth7piNiZMmKBrrrlGU6ZM0U033aSPfvSjdZ/ggQceKA2cAw88UL/5zW+qfu/Xr58mTJigo446SmvXrtVOO+2kU089VUcddZQWLVqkbdu26ROf+ITGjRtXKlpUL1q7zENYs2Hx4sWSyvEXDmCSypPB2rVrJSWjQUyZMkWjRo3StddeW5oI60FL/ednP/uZxo4dq9tvv12HHXaYpO1CPLNmzdIvfvGLtr2ANkJb9clEIpHoTqjL2Bg9erSmTp2qRx99VPfcc4/+4z/+Q9L2tS0vMRB+MRx77LHNqv8RL730kjZu3KjnnntO/fr1069+9SvNmTOnlB999tln613velcj15XoQnj++ed1wQUX6PTTT9eMGTN08sknq1+/fjvUfx5++GGNGjVK1113nU444YTS3x966CGtX79eRx55pKTta9F/+9vf1L9/f61du7ZZSflEoitj+PDhklTKzGNKNhkFpm6zv7MwoGGmgoqhVO2MSjb4e6UuCONKvPxMBVHHi3i7KOaCzAYzY1i8km2mQqhVWx9//HFJ5XudaB/UZWzssssuOuWUUzR27Fi99a1vLdWbmDt3brMMgHpw5513atCgQXrjG9+op59+Wh/72Mf0lre8paR5MHToUM2fP79k1Fx77bU66qijGj5PW8OshV9+lS9Bd/RJkyZ1fMO6OKZPn64hQ4Zo/vz5OvPMM3X22Wdr4cKFre4/jz76qE488URdddVVev/731/123vf+1498cQTpe+33nqrbr75Zi1atCgNjUQikegk1J36OmHCBM2fP7+UDrojWLt2rT7+8Y9r48aNeu1rX6thw4bpO9/5Tun36667Tueff76ampq0bds2vfWtb02Z526KRYsWaenSpaXYiZkzZ2rw4MH69re/rY985COtOuZ//ud/atOmTTr99NNLYlpmQnbeeWf179+/tO3uu++uV77ylVV/SyS6G8ze3XvvvZLKGX3U32D8gtkCMh7ej9VfDbICzAgxS8BMkEowc8WMho/tbBAfw0y2PxlrQWbD4Lm9ndtoXQ9fgxmN//3f/5WkVsUDJhpHn21ROVLgySef1Jve9CZt2LAhxbUSiUSiE9BaY8Mv9vHjx0sqawjZ2PAL2emqTrXlUgiDPZ0u6uy7SmlwizRGBdUiY8MBoW1lbLitkbGRqa4tY8CAATrrrLPC3++++279/Oc/LzxOXczGyy+/rJkzZ2rMmDFpaCQSiUQnYcSIEZK2M4bS9mxBqWwksO4HWQX/7he6X8R+gVOHg/EOfrHbUHD8A2M4KuE2UEfD52DVVmbYMOOFxgbbbqPCx3cmztNPPy1Jet/73idJeve7392srYn2Q6Gx8de//lX77LOPDjzwQC1durQj2pRIJBKJRKIHodDYeM1rXlOYTZJIJBKJjsMHPvABSdINN9wgaXvMklRe/mBdEGdsmEVgxVTqbXhZxcwFdTgMKotW/u59KP3vY/s7VVHNSHh/VrA1G8NlFdY68XvrqaeekiR96EMfUqLz8IriTRKJRCLRFZEv0ER3QZaYTyQSiU7Eiy++qLFjx+rnP/+5Vq9erfvvv7+qbtAVV1yhG264QatXr9aee+6pc845R5/85CclbWcFJkyYUNr27rvvliTtv//+kpprVLCqK4M2/bvZBTMbZiNo3FjokJVVpbLoIc9lRoPBrY61IJtCFobwfmZVHLT6hz/8QZKq7k+i85DMRiKRSHQy3vWud+mmm26qmaK9bds23XjjjdqyZYuWLl2q2bNna8GCBZ3QykSi9UhmI5FIJBrArbfeWtJ3kbZ71u94xzu0fPnyVh3vVa96lS644AJJzRU/JelTn/pU6f+HH364PvCBD+jBBx8sVYithEXunNp68MEHSyqXWGA2CRkP6mc4cyPCyJEjJZVjRyrbz3TZ3XffXVLzeBKDKa6O0WAWin8n+7Jp06aqNvcW1enf/e53mjRpkn75y1/qi1/8oj7xiU/U3G7ixIn60Y9+VHoO119/fYfWakpmI5FIJBrAhz/8YT3//PN6/vnntW7dOh188ME67bTTdNlll2mPPfYI/7UFtm3bpgceeKCqynEjOOKII3TEEUe0SVsSXQP9+vXTrFmzQiOjEldccYUeeeQRPfLIIx1eFDKZjUQikWgFXn75ZY0dO1bDhg0riR5ddNFF7XrOGTNm6OWXXy4sizB58uSq72YeHL/gSqfM5DBLUFlksh7UiouYPXu2pLIAGWujGGZDWGHWcPaJ2RgzIBs3bpQk/f73v5ckTZ06taE29xTsvffe2nvvvfW9732vXY4/YMAAff7znw9/d5xQEdLYSCQSiVbg4osv1l/+8hfNmjWr7n2efPLJUpFASQ3JCsyePVs33nijHnjggYYqJycSxsUXX6xLL71UJ5xwgi677LK6+tGee+6pY445psXf60HdcuWJRCKR2I4FCxbooosu0n//939rr732kiR96Utf0pe+9KVwn3oMi6amJt10001V2SjS9hiMz33uc/rxj39cisPYEZh1sJIo23juuefu8DmIW265RZJK98uaINTZMMy2mGWxAqil0VuS0O6NmDFjhnbbbbdwOWX9+vXq37+/XnzxRZ155pk65JBD9LnPfa7D2pcxG4lEItEAHn74YZ133nm66667Si9OSfrMZz5TiuWo9a8lvPDCC6VlghdffFF///vfSwGW3/72t/WZz3xGy5YtaxNDI9H9cfXVV2vw4MEaPHiw1q1bV9c+++67r/r06aOdd95ZkyZN0kMPPdTOraxGMhuJRCLRAGbMmKEvfOELJf0HSTr22GO1ZMmSVh9z4MCBWr16ddXfVq1apYEDB+qggw7SmjVrqijvcePGae7cua0+X1fC/PnzJTXX+rDx1VtjMRpFPczGvvvuq23btunCCy/ULrvsossuu6zD2pfGRiKRSCQ6DWls7Bg2bNigY445Rs8995xe8YpXaLfddtNvf/tbve51r9PIkSM1f/58DRgwQMcff7w2bdqkbdu2afDgwZo7d26zZbT2RBobiUQikUgk2hUZs5FIJBKJRKJdkcZGIpFIJBKJdkUaG4lEIpFIJNoVaWwkEolEIpFoV6SxkUgkEolEol2RxkYikUgkEol2RRobiUQikUgk2hVpbCQSiUQikWhXpLGRSCQSiUSiXZHGRiKRSCQSiXZFGhuJRCKRSCTaFf8PlZIovbW+JIYAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "group = 'ket'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(ket_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(ket_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1.5)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1356diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1364diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1369diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1390diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1403diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1468diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 9),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 1.5s, 0.0min\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1356diffallc\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.masking.unmask...\n", + "unmask(array([-0.314107, ..., -0.610047], dtype=float32), )\n", + "___________________________________________________________unmask - 0.1s, 0.0min\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/plotting/displays.py:767: UserWarning: empty mask\n", + " get_mask_bounds(new_img_like(img, not_mask, affine))\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "group = 'mid'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(mid_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(mid_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1.5)" + ] + }, + { + "cell_type": "code", + "execution_count": 121, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 121, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# surface plotting\n", + "from nilearn import plotting, datasets \n", + "from nilearn.plotting.cm import _cmap_d as nilearn_cmaps\n", + "\n", + "\n", + "view = plotting.view_img_on_surf(mask_file,surf_mesh='fsaverage5', threshold = 0.01) \n", + "\n", + "view" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Insula - Ketamine" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/insula_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=10\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "[Memory] 0.1s, 0.0min: Loading filter_and_mask...\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe008diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1223diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1293diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1307diffallco\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "[Memory] 0.0s, 0.0min: Loading unmask...\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "group = 'ket'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(ket_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(ket_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.nifti_masker.filter_and_mask...\n", + "filter_and_mask([ '/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1356diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1364diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1369diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1390diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1403diffallcon02.nii.gz',\n", + " '/media/Data/work/KPE_ROI/kpe1468diffallcon02.nii.gz'], \n", + ", { 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': None,\n", + " 'low_pass': None,\n", + " 'sample_mask': None,\n", + " 'sessions': None,\n", + " 'smoothing_fwhm': 4,\n", + " 'standardize': False,\n", + " 't_r': None,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, memory_level=1, memory=Memory(cachedir='nilearn_cache/joblib'), verbose=2, confounds=None, copy=True, dtype=None)\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 9),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/image/resampling.py:543: RuntimeWarning: NaNs or infinite values are present in the data passed to resample. This is a bad thing as they make resampling ill-defined and much slower.\n", + " fill_value=fill_value)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "__________________________________________________filter_and_mask - 1.6s, 0.0min\n", + "[NiftiMasker.fit] Loading data from [/media/Data/work/KPE_ROI/kpe1253diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1263diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1351diffallcon02.nii.gz, /media/Data/work/KPE_ROI/kpe1356diffallc\n", + "[NiftiMasker.fit] Resampling mask\n", + "[Memory] 0.0s, 0.0min: Loading resample_img...\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.masking.unmask...\n", + "unmask(array([-1.463832, ..., -0.551494], dtype=float32), )\n", + "___________________________________________________________unmask - 0.1s, 0.0min\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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nj0W1mGAqSZJkTelRg40kSZINGToC00GcS1Z1NTRmIp+NKM8G/SGYg8LH5+C3XuVU/10qD2I9IKZRyGnrSLHgOfIcIgWkngFIJ35/19TUVDGN6XP3+SRrR48YbDh/hpOo2FqnzMaIDjr6eHum3LU6YOvRnd3r8wGNig6xcFAxXwcjXLjkOTBTqJeOFPCD4peTrwlDzygRUkqM5NZUOFbPrbfeKkl697vfLan8o0AFyffdypQVKd/PYvlqqVpF83r2M+KPj196DPdz3/P9LIZCun8WX/zFfVHBc9v83Hh7v1x9LD9PL7/8sqRy1lNvl3k9kiSJ6BGDjSRJkg0ZVxDdf//9JVVHk0T+BIz24BQu63wwtJ7GiOH+uB4dlwmTDnoa0YNuqTz16HV8zjb+orwaNNToHM22cwDuttUyCqVqw6uYUbRopNEI9SA9o1LWjm4dbDjLIjsfrThGdjBTqDuXrUImpHGn83qGRYqoZFDGi76vdYzogYnkTT4wVl98bSivck6fLwdKi37QLWVGL5HeiqNM7JPhfCZUGpiYiOWxvbRSwUJW3o/vr//u9d136QjI4/J47ifF77xv5nphISvmo3EfobLBvrvVVltJKv+oOIrslFNOUZIkSZFUNpIkSToZD1qjQaOx0eGBIpc0mDjdZgOMmUCjeiP0uYgUFw9U6eBuJcPt9kBVKg9CPV1NQ4dTvyw6yBIPvmY0Dq3+MIspP3PAz+n64r0oRqMY37viwD5pnG4ZbNjDnzebnvfuJKwv4geGygZ9Mvx9reiR4n4iB6OoXLOPW/TOjxyxIlWEbYjKKDP6hOvRcSwqu2wYjjZ16lRJ0sknn6zeiCVR1ybxi9F9iL4WfPFR2uX1d+0S9l2/eP3i8kvbS9b14f1mae9iP/A2zp9B3yf2GapkXo+SvJ8vngN9QW677TZJZf+Vs846S0mS9G5S2UiSJOlkPMCrlzOCTu90NPb3VEYYDWKr3usx3J/GyGuvvSapbP23trZKqnZQ9sDVU2hWOhyaX0yEGOUIiRQNO8e/+uqrksrTeKwbQ2N0/vz5FZ85De/1fW382YPlYn2a9vb2qnvCzyyumDRGlw42PC/O0sJ8EJlzgEV/3FmoNPABpdc957lNpGjw+FG2x2IbIsesqFwyXxpRkh9an4yKYMQM5Vfja+L9Otqlt5VRpqLhFw5lbqpe7AO+r4wO8f7cJ/nyp+xt+KPB/sSaOkwfXetYUcIot43SPJ9PRlRRXaP0zqrL6cuRJEkqG0mSJJ1MlEuChk9UG4XreXAb5Y7woNeDVk7LEasKjz/+uKSy0rHnnntWbM92egDLwXqxDdyG09qeOvzTn/4kqRxifcABB9TcjkqFpyo9UKczPQMMmIivaGBY2Si2nde4VgHOpD5dOtiIEtYYer3ze0aLRJVVqXjQWo2sVi8pZdLfolYymChzJ+fcDS1lP8xUHqiMMF8HLWtaxsz6yJeefQYsWbqK6cSJE7Uh8qMf/UiSNGzYMEllOTjK3cIXI1/qtuqjl7+vLyM5fB+sUFAa9ouQfZp+Fd5vUcHyy9R9KOpTPibXp+rCiBvD55CKCFW63u4flCQdwYwZMzRp0iS1tbVp3LhxOv/88yv+/sILL+i0007Tq6++qq233lpTp05Va2urfve73+kLX/hCab0nn3xS06ZN09FHH90l7U5lI0mSpJOJBq2RgcUpX/+dBRs9kGNpBmYApXVP1YHRK88991zF34cPHy6pMi1+kVrVZiMlw589oH744YclSX//+98llf1FovB8Xjt+b5WGSgQDCzgVXRxM15r2rlWAs6tpa2vThAkT9Otf/1qtra3ab7/9NHr06NL9kaTzzjtPY8aM0dixY3X//ffrq1/9qn7605/q0EMP1axZsyStdN4eNmyYPvKRj3RZ27tksBH5akRJWqg8GIY8+TM99TlnTD+HKC2uLTjPedtaZHIY+o4U206iks/GHdwypI/N/TGNMK9dpGjUS2jjJX0BNlScR8Nhecxjwj5A650qF/0WmF/FfS6KVqEq5/35+L4frFfC0ES3Wyq/bFk3h2oIU1WzBpG/Z7IkE0WvRH4tvmapcCTJ2vHQQw9p2LBh2mWXXSRJJ5xwgu6+++6Kwcbjjz+uSy65RJJ06KGH1lQu7rjjDn3sYx/r0vd9KhtJkiSdjAeDzAFBZ3gOzDiV6/U9kHOoduSgzqlqqgscVG+//fYV+7X/hFUHTz8W82nU2n8RGk42iLxP+4e4NIDbQB8NTuPRQGK5CR/H58BimJzmc12U9vZ2LV++vMrpPkqR0JXMmTOndH2klSrQgw8+WLHO3nvvrTvvvFOTJk3Sz372M73xxhuaP39+KWJIkqZNm6YvfvGLXdZuqYsHG1QeGAoVqQN8QCLHI845U/Fg5kR2ZqsDtgxZkdN/d/6ColrBOXdDX4yoUJKviTsE61pEvhqsMuq2Uo3hy4wJdGixT5kyRZJ07rnnakPg9ttvlyRtt912kqp9IagUUEXjjwD7Kq17JhCKMshSBXCfjfoec1yYYn/xtq6ezGgUKhJ++VI1YUSTj+E2MxeJX/p0anQfpS+IFc+sqZIkjVFroEPV/N///d91zjnn6IYbbtBBBx2koUOHVgw6X3rpJf3tb3/TkUce2entLZLKRpIkSSfjAeArr7wiqTwAq5eUz0aADSBD6zxKAsfoE1rrxalgqXpa1/u3f8Wzzz4rSdp5550llQec3H8R/0BaRfnHP/4hqTx49b4Yzu31OR1YLxKGod8+J58Dz704sG9ra1N7e3upfECx/R50e//dQWtrq1588cXS59mzZ2vIkCEV6wwZMkR33XWXpJX95s4776yoWHvbbbfpmGOO6fJ8IZ062LDlwnlpzw17yVwBnPemtcl6I9w/K51GfhP01XDn94NNiZFWbnEO2x2Zc+h8YCxPUvrjvDl9AIrFgorQjyQqPlTvmtQLyVtfcf4Q+2owrwWvUxQlQh+NKEMr1bsoc2yUtZMRI+6TPB4jrYrRKFTLorBL1n1hn3WftgzNc/T2XPIHh8XFWP/HeTj8gp88ebKSJKlmv/3209NPP63nnntOQ4cO1bRp03TzzTdXrPPaa69p6623VnNzsy688MKq3Em33HKLLrzwwq5stqRUNpIkSTodDwDpsxE5rXuARodvT7PSJyPK0smEiTakOHjm4JjO+h5Iuj3PPPOMpLKfxerqhXggbIvcbbC1zSlMDsQjgyAKA6dR6nNj0UNf02LUiwfE8+fPr/Kb8T0rVrbtavr06aPLL79cRx55pNra2nTaaadpxIgR+vrXv673ve99Gj16tGbOnKmvfvWrampq0kEHHaQrrriitP3zzz+vF198UQcffHDXt70zdupcDfQvoMXlDhz5btAqjJydauW9KP49igQwTPLCtLas/eDt582bV9qHt+W5uk1+YCK/Ej4oUdQB/VailwOjLHht+BLxNfD6bu/6Pq8+aNAgSeXrzetIXwj6XrBvRjVp2Bejvu/rSonXx/V9owOf+xfrB7Edxe8i/xOeC8uERwqf5Wpv58+N+kL5pW1Fg4mi/OOzvve5JOlMRo0apVGjRlV8961vfav0/+OOO07HHXdczW132mknzZkzp1PbF5HKRpIkSSfjQb2VCQ+46lVj5eCV60ch9Yb+Cp4SYwXTesnpaCg6a6fzcdjvougH4H3Nnj27Yhsfk4YWB94+Zw+G7ZgfhekzUSJzlPgcPXj2spaB0Ldv3yrDrt61TlZPpww27Jfgm8dsjJEsRp8Lw05EaTDqDFFdC0MnLFqddEzyfiy/FTu7rTLWcbGV6HNnyFqUi6BeB+c52cpkjgRar74XvJZRtVlG16wvTJs2TVI5QVCUO4L+Qb4evk58GUd5TqLoFC5ZyZg/Hnb84wvYRL4ixZe828LcHCaqWBv5LtXLm+HjRFFiUcgh20V/miRJNhxS2UiSJOlkaK3zMwfBdH6nEUKnW1aDpaHngSMH10xKV0/hoArw0ksvSaoelEtl5cCyvQ0sTiFyyZwh3g9Drzl9Tud4GgBen5E7bnu/fv1K+/LAWKq+tnSYThqjQwcbN910k6TqdLO++e40fACiZCnsdJyDjogekKh0sNsZVa9k+JePX6vqqzuyz9lWX2QBR22KUvwaOnjRQYvz9H4QqTL5nni9KELhmmuukSSNHz9ePRn7C+22226Sqn0v6HRGVSuK5uGLjX2S+zFcn34KlJKd2dTt9n2N8qX4+EWVzcey7MzngEodn4/o+WFOFiZLogJCNYmRVXyevfQ597ZKxEmyIZPKRpIkSSdhZ1dbylQiOC3HopMMaacRQofyorIgVeeWMJwCo4HFMOUoGZ0HnM4fUpzOsyHDY1CZoKLByJhiWHfxGvjcfG05qPVxfS7FlP5S9XTiN/ffX89vtpl2efNN9e/fv7RdFGiQrBkdOtjYdtttJVWHNPkm2a+A3unusO4clPSoOHAuOAp9MpEvh7EFNnDgQEnlB4zKjC3FWglxvE9acz5Xb8MKnJF1yXOJQuP48uHLjC8rtof5QXyPeO6si9FT2WabbSRVRzpRto5UL0u1XkZ5NKiU8MeC94V5TkiUd8OOhLyvLApVzChqJ0SngV6wYIGkavWNeTgYaeN9RiGFdvjzy57PIfcT5ftwn2TEjfdrxXTMmDFKkmT9JJWNJEmSDubiiy+WVD0tWS/tvaGTr1UChsxzv0wRbyODjsac9vP6nAJjaD3X91S4B4xFA4zGmYmiT1g40/vm9oalGhjybWgcRurQJElflrTxpptq2Hvfq0f/9KeK7dxuX5urr75aknTGGWfUbF9SSYcMNpwBcI899pBUnXaW/gP0+GcdCJZR5rw7Q59Yijjy0YhkMO/PDkzMgOjOTMemIqyeaquMHZzWJLfnOUTHiaqTRvIrX1pcny9FJgnaaqutJElXXnmlJOnss8+u2b7uxu1kBVJG7zDvhvF1cR+0tU2ZOto+8neop2xEPzpUHaLkS0X53P3Yf7PEzXwZdEJkPhl/ZoZfnwOfC6/vvua/+3v3Me8/ktMZEeV74QijE044oea16goOOeSQhtZzuCejvhj9xWkJ9h/+UFIBi6LKGGlH+L7h/qhiMecR/fB8j4v9m35G9epDsQ08dgTPmVNRkb9cVfKwzTfXs7NmqY+kjxxyiN5cpbhH98RLZvCsx8yZM9do/Q2FVDaSJEk6mOgHlQOsyEHcREYI9xs5+TZKlE6ff49+yFeX94MDFa4bDXSic4jUoWgAFxWhrFfFtd6gqN4gKKmkQwYb9KBngRd2zKjOh+H8NB2MqGTYe50PHonCxwiVl6geRbEd/M5trTXiL8JrUq+OC5UNS4106KLESGcpPmDM+ujPVJGsHPQ0brzxRkkrM+RJ1cpR5BzGGjVUNpgAKPIjos8Mc7bwekcvbypkfIFSKaHEK5UtSPtOMQqML39GtET+Q+5LlOqd/tmKCZ0K7XfC543PP2slMaLLx7v++uslSaeeeqq6mkatUjuG+l7Yj8b3xO8S96MoVHX+/PmSytfA14h5daykMiOwl9EPtD+7Hd6P+x1TfHvpYmoOfR0+fLikynf/q6++Kqk8neJ1fA6+Bj6mv2e/op8SVSAmKHN/93GtkPt7n5OP7/755oEH6suHHKItJf1q5kw98fDDFdeQ98aK4dixY5XUJ5WNJEmSDsaDhyiBGQf3HAhSMeCghD4b9VLTR4pH5OthGIJtZ2MvaVQVz9MDn7lz50oq1xTxj7sHGUXn5mIbowyeUQkADvCZmJDTLCxHcaOkVyT1f/NN/d+jj1a5ARgalD/+8Y8lSWeeeaaSmA4ZbLDEr/EIspbzUJHI6oseSBKpBvXUAcNObext7yX9HIqOSyx05AfBD1S9hzz6Pmqb16NvAa8d58EZDeMHjfk3TBQd0dOgRWai5Ee+d/ZvYD4LqnG+94zq8fWMooGYcplz4e4vb2B+2C95P1t0DIxk+eL/fU6DBw+WVJ0UiS9x+hPRSTGqgMu+RZ8Nn2MUXmno0+E+7eP6e0e9TZ06VZJ08sknK0mSnk0qG0mSJB2MB7EeJHqAxpwRhoN9FkakNc0wZQ5iOSAknMr2Zya1ixIdFjNsFvdTnEbhANnTGF6XA3XmEmHqhGiaPCpyyGROXwEAACAASURBVHPnAJ1TzRMfeEBPLlqk9uZmvfPOO1VKCNWnqMhlUpt1ukqOTNhnn30kVTvO2MLx3Jk7GzsDvYmZR4M1U2wBUVGpl6uiniMQ16NE6U5ZK8ukO6LPlfOIPFY9v5J6+EFlLgQeh9CrnTU7vGSiHb4gegrMGEqvf76ImNGVL0lfT75YWBGV0SEM26OvDPOvMMeMZWm30/2GeTqoeNXqT8zkaT8BFq6KcrlQpYvCG33NvH9fA4Zd+rlndWW2N0qdzR9i/vBee+21kqRx48YpSZKeSQ7JkiRJOggnIBs6dKikePBZL4Oo/+7BL7Nr0hmfygahMzCVEYaZ0hGZxtOQIUMq1mdYq1QeLHpdO5dzXQ5GaWzy3KLIG9Z7YZg7FRKWanjrrbe0YsUKtbe3a8mSJVWKi5d0qvV+e3pagO5mnQYbzKdBPwI/WLSMaAVGXup8sHw8+w3Qqo+sPUYa1Ev5Sy96t9ftd5bKYrspMzKXgImqr/IBi3w8OL/urKd+CdRLwsMHmnIqfQ7YTrfP3vbnnHOOuhPL1e4bfgFEdXV4XXxPrVjw5U7pl5VUmUuCPx70EeHLnZVWIyc4wx8FvkCLx4hyMUR+QHy5WqVjVIDhObMPsmKwHQTZp6LMov6790sVzvh5TJKk55LKRpIkSQfhgY8HrRxQGQ5yWQeElUmjZRS+TyOGykbkuBwNclmOgdPD9uEohph7wO422nijH0uUdItGJ306Imd6DsTdZt8D+sN4EDx//nwtW7ZMzc3NpaCAWsfztaNj9PpS0qG7WKfBBnNIRNa0v2f8P+exo6qvfnBpdbKTGVp7fPD8QNty83y5rWSrBbSOG4nIiCJgbCG//PLLksrz1pZbvU+eW5Sql0oI/WWi+fLogfYDxMqeLK9smOuku2AtF96zKKkSfTIYdRM54nE7ytbMq8FngdIrX7hRn2NkiPsPs3hK1bkcqO5EWU9J1HZfCz8vrLXC58190Mfxyz1qj68pMwfzB5Iv/UwfnSQ9l1Q2kiRJ1pEf/ehHkqQRI0ZIqnas5oCKvhx2FGYBQA/UWKWVVnWU+p2KRZTvgwM/Ou9zqtkDTbf7scceq2ifJLW2tkqqTjzGNnB6jwNxTuEyQV+9FAd05qYPiPf7yiuvaPny5SVlg24CTARIhYbtSipZp8GGLYvIUYcdmV7k9HOgNckaDdHcblTtlZ8pVXrpLH3OiucHyQ8LlY5aEQC0UP2ScJY579vz33aWsuzKByuqscFzNlFYWL358SiShw8kVaqeEu7FvCFRfYSodgytZL9IvPQ9Z5SOifJwMDcFM7c2muXW2zOTqX+UfLyi0sR1vS+/7FnXhW2hYsBjsNIsrz0TPVHRpFrGH9yohoXhNff5WR3sKf5ESZKU6Rm/GEmSJOsxNhoYthsVSGOUhwfBNkY81eTBro0TDhA5cIx8NTgdSEOwXiFIGpA8L7fb6cul8uDUBTo96KQBFbWNA286OtdK1V8LhlzTAPFgd9myZWpvby/9YzVaLjkl6sH3VVddJUn6/Oc/v9p29TbWabARVS6NnI44B8wsi755rJFQrzNFx2Xkh61Bhp05w+Jrr70mSZozZ44k6ZlnnpFUrmtgpWO77baTVJm3wP4ffticotf+IH5peFuHg9GPhC+PKO9GZCHzZca6MYx6qDePH4XSRcmCuhr3HbafeUNYe4Q+LuybrBfC8DdDBSVSTviy5gvWn31/aoUSFvdLX42i0uRjeF/s94MGDZJUHVrIvmMlgm03UaZfhgb6+eG1ZEptKzH+UXD7uF9eUx/HP/g9xZ8oSZIyqWwkSZKsI1Ye6NQalZaPks55e3/2gI/O+BxQRdEj9LUwUSJDtjNydOYA1FPPVmSk6sJ8nEqkoRMlrCMchNabamZ4OQfjLhi3fPlytbe3q7m5WRtttFFpWo4+Ggyv9/792YVJk0o6ZLBRT1ngepSxmJ42qm8R5Z7g58jvIJIK3Xls8fn7xx9/XJJ0xx13VGx37LHHSipHkhTX/c1vflOx7sEHHyypXI3U1pc7pqGFzcq5JnKiMlFuBVvKjG6JihzVU6n4cutqPC+/++67S4r9cWwtM3eKr6/Xo/pmRcQvdaZnps8E85cw5wxrrfC+sK6IZWnul4qNz6eoQHEd+pFQnfFnFrDyS5ZZVCMHO/6A0rHPz5mvBcM++UPGiqPMIMw8PFRKrrvuOknS6aefriRJupdUNpIkSdYSh9vuueeekqqn9aKidVQaPNDytCetZYb/MrKCcEqMSgWNilq1TaR4mpCDZg/GiwYY0+PTyZyBA/TZiHwyeG5RegDD43D6reg839TUpD59+mizzTYr3QsvGeJtvD9OPyaVrNNgI8oVUC+Eicuos0W5BZisJcpkyuPzwYtS81oStdJB7rzzTkllhUOqVjTMzjvvLKl6PrleqFqkJPjBsuc+PfgZZsbjRaFvfAHQSo2uaXdh2ZYPvvuKr4vvcWQN+4VDJYROX1FOGKah5o8D+65fXMwd4/MxXt8+P1FFZVNUA5ntlP4qfOkXpW9JVfKx28y+SCWEuU2iNNNun4/D0ES3mz4nfF/wx4L3In03kqTnkMpGkiTJWmLnVw5iWeuEU04cMHmg5IEdp7w4tczpUhNFodDA4t85UGTSOhqMxOdTTHjIfUaDUDpNU12JfDKobEQpEDi45dSpv+/Tp49aWlrU3NysTTfdtKRkUNngFCmLVtqAcO6Vs846S8k6DjY4H00HH970yCKyBcWbaIvGqWNtrXo9O+IwQ2KU04DZMtnZKQ3Wc/RZXXraI444QlI5RwdD33gtIvnS8OVla9TXxt/73GyhW6Vhyl4T1dqIyjTXK/jUVVi5oWLBe8hcD74+tNaZPpp5NZh7gteLUqqPy5wXvl9MxUxlgyocnxX3PfcDKyDFNkf1WPiyddt8zv67+z9rBPHlGmUA5X5ZGIsvc5+rI7us7jQaORX9iCVJ0v2kspEkSbKWeNBLJ9koyRyndJnQkLkoHI5vBYVWvgef0fRrrQSExc+RMz7bS+f+yGm/uL9IaYiOFTkWR1EsnPqlKsPjRKUGiqHazc3Nam5uVr9+/aoMDLeHhiDvnQfX0TR8b2WdBhss0ct55Sj1La1FL70fWzS2cKxo+CZG9SX8d7eLx2H0SeSIxAd5baC8Ws9fhfPPjHLg/HMU6cO5fL4M6mV95T2LrNbuLjrke8OXPOXcqHJwJDczrI41Zpi/xLC2CVU2Vz523/Z67idUTKJILbbf/cYRG1J1/R2rW1QM2UZK9/X6aOT/Q9XF187f+1yt+ll2ZhVoZhqlT5fPjwqrz8/X+JprrpEkjR8/XkmSdA+pbCRJkqwlzBRKxSCqMcJ8GXQs9oCMhpa/N1QsOA1ar24IifJpcP1o6qpo9fNvrLYapfqPKtrSGOQ5RufmNtkQY94NL7fccks1NTWpqalJLS0tVWU12A4mxTPM+pqspEOUDXYSyl184DivbXzT/YDZGnQnoXMVrX0/kLS63R4/qFGFTyocUa4Ls7pcE7aso7wUUaiZ207VyG2j7wGdpPhg0Tr1AxC9pPggs93MkNnVOL+GQw1ZBMnn4b5lq5lFk3h9vJ7vh61mZlyls5m3owMgrzvLW9NHhGF2UbZO+nDUyrLLXCE8F0NfDv7Q0P8n8iviy97n6P34s59nb8doMiom/p6+HcbKiZdUlzKjaJL0HFLZSJIkWUM86N13330rvo/m8+sVLvRAygND52pg8rgID9Qi59ioSGaU74O+GVH6Ag4w3f7iOZDILyRy6KUPRlT/JWprVOeF4fEbb7yxmpub1dTUpL59+1YV3uR+61WX9SA5CwOuZJ0GGw7puffeeyVVz1dTQeC8ur+3BcZ5baaXtXXK/XGOl52P3vecx49S8nr9j370o5KkGTNmVJz/6pQNpheOKmJSDaLUZ1jPhdeQtTj82dfI15Jz/lSd+BLig+p71V0PDtUwVleNKv2yL3hZryAV7wMd+6iWRYoRX97eL3NcME8KUyKzHW53sbS3f7gc4WJ/Dlc35vPE54dLKxtcv/jDUrwWzOPhe+A2ss/zZR3lzWEmU6pJrCJNxebKK6+UJJ199tlKkt7KjBkzNGnSJLW1tWncuHE6//zzu+S4qWwkSZKsIfSd4ICKhfJYT4NRIN6fB4gc6LGYHqfA6BNSr15IpCZEjuf1Eje6nVYLim2rV8CP8NpQLYoSDUaGQz01xlOim266aSnPxiabbFI19VovWyunAW0QMqy9O2lra9OECRP061//Wq2trdpvv/00evRoDR8+vNOP3SGDDT8Inr+m1R1FofjmUclgbgJaj1Em0KjuB61JdyK+CFhDIgoPM6ubC+Y2VDb80vG5RBY3Xw6M/KGPgKHTFaMqeA5eRiWko+27GvYdRtFEoX5UGJhtklIt+wb7kJfsm3zBRX4OzFRqWDGVjoOMVqklrzOfBRNHufBUpPDxeaLy6L8/+573SJIGz5pVcXxeK2b0tPJCmdrt9t997az+WKHxD5rbS78cFuCiGpgkvZWHHnpIw4YN0y677CJJOuGEE3T33XevP4ONJEmS3gQHStFUlAdEHlzSKZYGGQvrefnKK69IKhtmVDZoVdMoiZIKcqrLRMn/omKatZyQuU5kGESGUpQuIDL+GCZOAyOaznP4+WabbaaWlhb16dNHm2++edXUchTZUy/niAfDPYE5c+Zo++23L31ubW3Vgw8+2CXH7t7SnUmSJEmSdAm1poI4iOosOkTZcPItj9bthUzHLc5lRaF53p/hNExUnCyab4wkcDqicWojCoEdPXq0pMq5uA9+8IMV+4icR2lpGIYL8txZRCsKgfX6TNDE2PLlkOnpwMjMh4xJ7y5owVFyN/QMp9c9z8tw2oKF3mhlcZ6YfZQhrTw+p+z8mSG2XkaJuIrTW5GTsffJUFSmQvd6PMYl++238pxXrbf3qv3+Y9X+OOXHKUE7vfr9EBWMowOp/84pL98bTstQZegpxQOTpLtpbW3Viy++WPo8e/ZsDRkypEuOndMoSZIkawgz8XKqgHlvmAOIRgP9yDwg4wCJ/iqMJqOBFPmpRMXRomWUetzn59o8xQglJiLjdEM0HRJN6XDKydCPi2nOme/FA3MPfr3ccsst1adPHzU3N1cYGfWyKDPHD30HabB0J/vtt5+efvppPffccxo6dKimTZumm2++uUuO3SGDDXcqzyv6YvuBoQc2rXjffDuA+e8s0ESrNiq8FMlCLBAVObDywXVn/tCHPiRJ2m677SraIak0D2ZVpp40RY9otyl6uDm3yhoLfLmw6JYt+NI9WNWOYe99ryTpiYcfrmgP02zPmzdPknT66aev9rw6Gya14pLXg4oB54PZN5nB0da+v4/SuUeOqd6P54W9H/9o+L74Jc2XPNPP85lg8UKpOoKB6fupXHg91vXg82ncdx5Ztfzh/vtLkr7+P/8jqdxXvV/+oPrc7PjJEFb6M/DHiuHPUTVRJqDjtUyS3kafPn10+eWX68gjj1RbW5tOO+00jRgxomuOvbo/HnLIIQ3tZM6cOZKqPfCZCyBKxsKRYlR5NFrWk0nrVZ+lk1dklXjJiqHFtnsbr8Nz5zWhwxXbymvFCJnICSoKB/N2zz73nCTpI6vu8ZJVg4ooDbFf2Ndff726Ew96GAXSaDRKlNwoSoUcVRqtV+jK8DpGy2g7DoKijK5Fa4rfRWmfo3LjfC78+eVV2WffXBV98uVVfWfOqv2ejZwhkfMizyHq21H9Hp5Po+8VD5ruvPNO1WLkyJG69NJLa/6NRM9fdL+5HqeoosGtp2qZg4Tl0TmNyGtdrxIu+3HUfmbS9d9/85vfVO1z2LBhFedAokrTkdrCMF9GXbH/cOqU0Yiuauysyg59Le6rCCPZvOTvFs+vpzFq1CiNGjWqy4/bodMonMeOqvnxRvJBrfcDEkl69SS/KL47kvPoG0IP9GJnoiUdET1AjQ6UIqKkVFElRP80zV213Dz4MY4epO6iXiXJaJDB6xyFNUd9NMpKWG+QUa+OQzRQjgbA/BHhj17xb3weo0E3X/phGPWqz+47HmQMXSWh+/toMMABH68B14sGP/WiHOqpgUmSdD2rHWzMnDmzoZ1MmTJFUnkEGznZ0QHND7+nHpjlkk6QHsVTZqUCUe/lFjnveT+M57c17ZGsJfFi9kfP+3nbwYMHV5yDR9M+B59TVLcicjBlLQ86CHp/dBD1333csy66SJI0cdU93v+BByrO0ee+cOHCiu/PPPPMmu3qKm6//XZJ0g477CCpuk9wfpTXhdlhowyvdCyNpm+i+8S+xgymLh3u/sI6I7Qk3b9shblf+f76PhX36Xl0f2YWWua58TnRgdPnftkxx0iSnlmlaIxY1XfO+eUvK9bzOfpH3qW2mQiLfdTHd992O3xv3X7WTmJNFJ+X1/P07uzZsyVJkyZN0rrCgU+9RFWGqhOneLxkv+a1MPXU43opvKOBG6eiovPyNT/88MMlVSb14jMTqSaRkmaixGIccHOajr87HLBb2fCz1dLSUmE8cKqbTvIsVhcZ0T1V4ehqOlTZ8M3zg8Lscn7pMTqEPh6UEt1pKJdROYmsxeh7dxq+fNlJ+PJju6Vyh3fxJxOlq6a0G3VYw5cFB1L01YheLh7YvbZqv+9elWr+VezPD6QHVkxN3V1E9zrKcxANNihbc5BCnxXj9dwnOIA20fQXJVxGDxkOIlkWnmpbUaqOBlK+91HSOv/QMTrFfeqFVft33zlp6lRJ0oJVnzno9/asQVFPqje+pvTZ8DXhvTGRv0sm9UqS7iOjUZIkSdYQDm7r+ZNwSd8ND4w8kKKKakOHGW0jXyO2M5p+rFfVOVI2PHj3suj3YNxWDwo5DR21iX4hVG/q+bHxew/sqYi7fTQU2tvb1dbWVnVPvKRBQ3WLg+nuqpDd0+iQwca5554rqVyojJEBTJdsydcyL+Pk6WDKeWmGNtEhiEXJImWjKvcEHIA4d8zU4kUVgp7ylEuZHyGSKRt9ALlfzlvTYYz+MENWOfX6HliRYcr5nuKrYfhA82XJcDQuIxi14pcow9ood/t6Wc3z/Y/kbKbkdp/ni4tTH4ykivYjxdU2fe+tcPgceA2pGLgvXbBKyfj2yy9XtImKA9OEswAiQxXrEUWXGL43vD6V0dUVTkySpHNJZSNJkmQtiXwdaG2zhhHD7jmQ4vQoo04iqz6qyWSoqESF2yJHZg9QHYHogamnuooqgdfxvpwegJFkbCuVhkgt4nY8V0ar1FNWli1bphUrVmjFihVavHhxyQhljhQakpH6E6WC76106GCDHZhluDnfTiuRDyx9KLw9w7+oKjAHfpSoxtA5s17EQq1c+LRco7A9WpNRlITxZz6gPB7n9qMQWF5LO7IyJ0qt0uU9AWZY5XWmvE2nYb54omyZUWSU9++XLPuwfSeY2TSqs8Asu1FhNt9X5rBwu4uOgz62Hd94rXzO9qVgjg8qfPXCc6k8UFlwO9wuOtfWC3Hkft1++ttQ8aS6l3k2kqT7SGUjSZJkDeF0WRR2T6WDU8ORL4eJwnbrKRpRuDOViigahe31QG3u3JXB8p7mo1JTNJY4JemooNbW1prb0HCgkkDFI1JGIgOk3tTrokWL1NbWpra2Ni1cuLBqCpZTmtE9IWx3b6VDr4KtLVsy7iSWAI1vlp2KXnrpJUllS4uOQawLQiWDnYCRBe70UXU+Wst8cfihWN1+qGBw/ph+IlFoGh8IW290DGObWDKd+7Xy4fl6WoeMzqBV21OcnBja63vHlz5fnoxo8pLXMXp5U5miEkJJ1X/3s8AXa7200FYBfJ+isDsvi9FC3hcVDoYKMszXzx+zrUaqW/Sy5XNDnycrG/TNMvwB5P7o8xFFEnl7n1dHhLwmSbJ25JArSZJkDWEOoCgxWZRYjNOZ0fRpZC3TKPFxnPvHA0YOqrl95DzPQoU2CL384x//KEk67LDDKrYvDhx9zs7XdPDBB0sqGzTOv8IpZRpibDv3T0f+KEMt0wEYX6t//vOfWr58udra2koqR3H/9TLXRvfMfeWHP/yhpN476O3QwYY7usO1GD7lTsYHwTfDkRHusExz6+08X04rlHPHTPFL6zOSFOk9byjrFeey+ZD6nOqFxDFcixE8/syXGeta0LHMx7XF6yRSfDCZU8HnznMtJuvpTsaNGydJuu+++yRV+wMZFmWi/xB9U+ijwfA1zvdHkm1VHRFUGGb4Xb0sn4zgsFrBSKricaNU2KwcS38RH4Phl+x7UV0Z91n3OWahpVrm49GPhs8d7wXzf/jvrANkqf/EE09UkiTdSyobSZIkDWLrdOTIkZKqlY0oUVnkO1HPMTxSPjjw8wDLaQUYIUHHZtarYaJFDxg97WpD0IqGuf/++yVJn/jEJyr2J1UPvH//+99LkkaPHi2pPPjlAL9eVAqNSjrdOxyd0SfRlHVxMLxixQq1t7dX+M5Evh7RPYqCBHpS9dfuoEMHG+PHj5ck3bsqKyXza9CKZnry+fPnSyo7ErkT0qveCoo7CS0sqgxUKmgZRVk++YDSQitGakThULS82SGjokG0TmndMdEMHcv8vVOt+zOlS1rOfskwFG8Rimx1N7Za/WLhy5dKUVQvhOnLI8nWcL8mqsLq++fr5/7ACI2oQB9VBfo70BdFKt9r/oB4G18zKhtUu5gzhjI09+Nzp4LJ6q4+jttOBYZ5eug/w8ge/kD6h/H5559XkiQ9g1Q2kiRJGsTz7X/4wx8kVQ+06JxaL8dCVFXYn6NpQn72ANPTnR4o+nMtA0mKq8NSKakXAm8D0zVSpLKSQTz4dGSLM3xy8GpoSDFM3+fIKeJoqjRKJtfc3FwzUWPk88FlFGEU+Yr0NjplsOGbbwuH1rutORYp8/fu4C+++KKk6porXt8WTaQS0DKiksE536i4EiMMfH7F/ByskUEJ0UT5NThfHR2bYVhUYdy2l1dlebQqw6JzzN/BaBn6BEycOLHm+XQXVsHcJ5iDwfAFwPtSy7GtCF9MjKCIHPhYJ4Q+HbbCfT/Yt6PoFRNFfEhlZcA/MOxDVEmiDLleui8wSy39irhfn6N/XPyZ6aL9I+P2sdgdlQ2qbr6mVjSeeeYZST2vzyZJbyaVjSRJkjWEkRJc1vPdiKxkTmV5IMZpuigKxdOLtv7pN8AKrJxG9X49zWdjxNlAjzjiCEnSb37zm5rX5be//W3N72tBY48pDqJKuj5XFp+kQUan78hno5bB4Hwbxb9HxiwH21Eod2+nUwYbtKb5QDEFry0T591gpIUjKdjJbBlFpexpIbmTMTcC/Sl8fOb5iDp1sW2cd6YPBFUW5oGglMgS1JRpfS5WNGzx+3tWBWUyIqpEjLTpKdVeyTnnnCNJuuOOOyRVS5T0D2BfoepVLyEPo4QMVbJ6DoGMGmLfYvvYh2spGTx/+jBFSYkoO1NdYVQKaxGxL/Fc3Zfdp9w3WenYP4yuz+O+yh9AwwghKxrHHHOMkiTpmaSykSRJsobQmZyD9yiPRb2cDVGoNuGUrwdyNsw8oHMaAqZ2p2OxB3aGxSltCK5Lynfn2fDgcocddqj4zCyqHJhzaYPK58rqsh60RiUHDFWlpqYm9e3btyo8nakWou+pbpnernB0ymDDNzuqKmmrzR3YnY2RAbaq6Z/gz8zLYUuKslcUdcJID3cSt5vz5kx7W4QvlahSpR9qqir1JEQqDfZr8QPGDJ++Fr62fvDoR+NzYflkztf3VI477ria39thzdfL8jLvdVRp2EuqZQyno29N5EdkorTWkeJh6OfAOiO1+iTVG1ZFZhZSysBWOvyDR8XPUjvbyufL6zEPxuTJk6vaXOT666+vOL7xfk455ZTVbp8kSc8hlY0kSZI1hFNLhgM2Todxfj+qcRLVOiEeODofBqdVvXReEE9VRYNg78/7obHB7dYE+oN4wMy8GCyRwIG4P1vF8ZKpEIYMGSKpWm0ixcCFlpYWNTU1ldpU3C5aRr4cdA4/++yz44vTC+iUwQbLIbvz2Apn0hZ3PkqStiajyqm27v1A2aKi1Vov5IiVUt2ZLUHSsqvlWETHLv+NciTXp2VNX46oUq4tdfp8+Np7ycgfn5OPb8s/mp+nvLq+4CRDt99+u6RqVYxRKXS8Y8ZOv3z8mVVj60V4uE/xxyTKrxGpDsyv4vtcrPoaORPyB4/qFRUPysV+aUf5b/hjYHxOrPNTj1NPPbWh9ZIk6fmkspEkSbKGeLDvwTunWg2T53HQyqnaRnNCGBsxTDwYFZNkuQM6oHOqi4UPI4VlTaCKQsOGfiWccnRYv41ND7y9nlUeFgbl8U0x8sfKxmabbVbXx4IqFvODsKBhb6dTBhu+6H6gmPXSSgRlKOfTcCfzAxRV+GRUif/u7ZjXg1k4mbjG7dt+++0rlsYvGO//vPPOK/3tsssuk1S2NJ2p09s8+eSTksoPq8+VvgKMTjA+VybX8bXy/hh14qX9Y9w+5uXwS4UVQ9e3B2Xq1KkVn1kfh5FKvN608n1dfM/pM8FcMYwEiZzT+OMS1UiJlI4oeqh4jvyB4fPG9QwrzBr6QFGtoWLJXCTM8JskSe8hlY0kSZI15OSTT5ZUrmjKARsHixzURjkfTORfEIVUcxDqwa/9FmxkeABJHw8OZlmIsVGlZXX87ne/kyQde+yxkqpLIPhYnK5j8jify8CBAyVVBxTYaOR0XnRNi+pTMXMrAxO4HyobVI1YsqC30ymDDfobUCpkFkWuZ+vcVqOVB3ZORghQArTjkB8sH983/6yzzpIkXXDBBZLKcpvb4XLKrtXiF0wtmK3wl7/8paTyg+E2vvDCCxXnYsXBx3bHpcVKhy2uzxA2f7bi4fWZ94O+C/Q5Wd9S7Ppl6D7EpEiG/guGPwLMpEo1zEv3RR/PfZd9n8dhJtkozTVDHVenODHPRZQdlc8dq8JSjmbdH6t2jHqJQgwNnSqTJNnwSWUjSZJkyswunQAAHJxJREFULWECQw7WGULNWif1Moty0M9BJkOzbcR44Dh48OCK9Wm40a+Ax6Mzb6QONMKBBx4oqTppo3EbmLjO52bDzNfaU9VUEKIIoShzqJf9+vVTU1OTWlpatMkmm1SlL4hUKN5LTuv3tCKW3UWnDDYoG3Hu2EuGWdmSooMQHYXcCZlXwzfXDwh9LGzFf+UrX6loHyMP7IDk9q1NyNKoUaMkSTfccIOk6hC4L3zhCzW3s+8H5739kmIRIs6Ls4CTXzpWfXyN/eD43vAlWStL6voAX0yMpvF1YAIgqmTRS58lxd13vT9muWUEBqOK7DPDfCnui5aKrUwx9bJfbMUXN3N8eF8minTxudPHif49rIbMH4eo+rKP5+yvSZL0HlLZSJIkWUucWJBh8lGyOFrBnGqK8m1E2/k42267raTyAJAO4TTsmM6fBQmjaUC34wMf+IAk6X/+538klY2r4nSlj+WpW+7D63ow6vVoXDIhYhTeb0PKbfY5MDDA1EqzX1SkogihKHEjHac9uHZ2195Opww2fNMZFkYJMbLSrECwKiTDtAzzc1DCpLU+ZcoUSWWrcffdd5dUflBfffVVSdIXv/jFNT954CyHP/7xjyWVI1wcNWFL2OqJz92+Fl7y4WeeBuMHldkdLZ9SumR2Rj4wvibrC1R8orwWLLnt8+SPBaNLuJ3Xt4Lh++cXjK+7r+vaJvaZNm2apHJSpsghsdg2t5W5P/ycWanw+t4nky75h4tSO/sK1Ts+d+tbX0qSpONIZSNJkmQtGTNmjKRytVMPOmn4MOEZc0ewQimte+7PA0YP7IYOHSqprA7YQdoDQCb/o9HCnBKc+mbVWP/9k5/8pKTazsjM/Ok2eIDuQS1TEdB3w9fGf/exOFXJpZUPQ6N0dbS3t1el3aeDdOToTEXn85//fN3j9QY6ZbAxfvx4SeWIDOYioFJBi4kOOO48zMbIeXM64vBBcefwg9ja2lqxnaNXOkLRIGeeeaYk6eabb644trnpppskla+NFQ1mY2XiG1YFpaVt6zUKA/N+jB9oW8Vjx45dsxPtZqhmMdqDkRfuk1QsGIbH+ju+bnRKYx4PRzStLpKpEU444QRJZUXMPy5UOKTqSBqGQ/KHjgWtKANb4XCf5A8iI6UYjcYIniRJeh+pbCRJkqwjdka3tc5Bq4kUDTrpcsBmWBnV23uqy0YMfUQ4WGZ7oiq2zB1hY4ah5LWqx0aZOj3Qd1t4rvQnYcJDt5WRPr72jlJxW6NEerUigfxv2bJlVTlJPJjmeXHa3vfefSJZSacONuw8xeyK7mT+njfd1hofAHZKponlA+ybTnnN29s346ijjuqAs22Mk046qeKzq5PS4uZD7bb7gWLiGy7pDEV1ieWQma54fQ3XYl2PKM+F4UuS1VupXNAXxH2ZMrmXDD1cV6yQ3HLLLZLKjoFFhYovbZ8D207nRbbdfcDnRqncfZIvcb+kWSTs3HPPXevzTpJk/SaVjSRJknVkzpw5kspO50yYFvkJMNrEcOrXnzl4pu+GHYjpGxJVm6VaQKXFn+kf4XZ7IOmBbVHZYMoBKw5RThKGhxsaocT7sbrDwAQaICzoWTR229ra1NTUpKVLl1YFLnj9yL+F+503b17N9q4t7e3tmjRpkn75y19qk0020Q033KB/+Zd/qVrv1ltv1Xe+8x21tbXp4x//uL7//e9LWpluwVlclyxZonnz5nWp+tKpgw1bYffcc4+k8k3xkrUZaH0yeyNvNnNKsG6F13Mno1rQE+p+8EGgL4bPqVjVUypbnT5HFlxiVIYVE75MGAHkpXONrG/45ecXG1/2UQlvvvD4oqEfA697vdLi9tWhsrW2nHjiiZKkn/70p5LKaaml6qgvhujRz8fXiD9wVkSiVNruk1Fqbv/YjBs3bu1PNEkSSdJ9992np59+Wk8//bQefPBBff7zn9eDDz5Ysc78+fP15S9/WX/+85+1zTbbaOzYsfrtb3+rww8/XJdccklpvcsuu0wPP/xwl7Y/lY0kSZJ1xFNE06dPl1QdbkwlgT4RUdSKofLBqWaWLYiOVy9NAHNJsB00fuz06/WK7WTbPAVMgyoa+BtG6vDvkXM8fTU86GYivaLhsHz5cjU1NWnRokVV+2U0Cg0S798GD0tYrCt33323xowZo6amJn3gAx/Q66+/rpdeeknbbbddaZ1nn31Wu+66a0nhOuKII3TnnXfq8MMPr9jXLbfcUirT0VV0yWDDUR6+aQ4JMgzzMqy8aYWDmQ/5QNBy43w7lZHuhP4ovhZuG6uT2g/GCgTDxPwy8DlHWVh9XO/HqpH3v75mebSa9qtf/UpSXE03UiTolMYEQd4+qsLqPsr7x6ifjuJzn/ucpHI0k1SOVIny2EQ+T4wmidI+Rz9Y/IE69dRT1/X0kiRZxZw5cyoqkbe2tmrOnDkVg41hw4bpySef1PPPP6/W1lZNnz696vfxhRde0HPPPafDDjusy9oupbKRJEnSYbz44ouSyuH1TJdv6E/AQTAVBlr1nHpmBAf9CKhwGE4v0knYhp6NEa/naVmmsC/6M7AgIB2MWX6C5xhN3/EcaFAxgsafWaqAykZzc3PJZ2Px4sVhWgEms+Pg3OHuHU2tiru8RltttZWuuuoqHX/88WpubtYHP/hBPfvssxXrTJs2Tccdd1yVotTZdMlgwxbOHXfcISl2TuLJMyKA4WSMQvH6UapfdsKeEHHBiJ0I5oGwIsEOGKU3ppXKRDq+Fscff/xanEXPw9V1jV8UUWZRWv184UV9Kar74/tlmbmzHbGcXEqSfvazn1W0jc6Bhrlb3Kf4A0YVh7VRvJ0/r6/+PknS07jiiit0zTXXSJL222+/0mBWkmbPnl3hq2U++clPlpKtXX311VW/q9OmTdMVV1zRia2uTSobSZIkHYTn6W+//XZJ1VY3p/Nq1eeotfQ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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "group = 'mid'\n", + "nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + "fmri_masked = nifti_masker.fit_transform(mid_func)\n", + "from nilearn import input_data\n", + "brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_file,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + "brainMasker.fit(mid_func)\n", + "\n", + "mean_diff = np.mean(fmri_masked, axis = 0)\n", + "mean_diff.shape\n", + "\n", + "delta_img = brainMasker.inverse_transform(mean_diff.T)\n", + " # save it as file\n", + "delta_img.to_filename(\n", + " '/media/Data/work/KPE_ROI/con%s_%s_Ses1_2' %(contrast, group))\n", + "\n", + "plotting.plot_stat_map(delta_img,threshold = 1.5)" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [], + "source": [ + "def createDelta(func_files1, func_files2, mask_img):\n", + " from nilearn.input_data import NiftiMasker\n", + " \n", + " # here I use a masked image so all will have same size\n", + " nifti_masker = NiftiMasker(\n", + " mask_img= mask_img,\n", + " smoothing_fwhm=6,\n", + " memory='nilearn_cache', memory_level=1, verbose=2) # cache options\n", + " fmri_masked_ses1 = nifti_masker.fit_transform(func_files1)\n", + " fmri_masked_ses2 = nifti_masker.fit_transform(func_files2)\n", + " ###\n", + " from nilearn import input_data\n", + " brainMasker = input_data.NiftiMasker(\n", + " smoothing_fwhm=4, mask_img=mask_img,\n", + " detrend=True, standardize=True,\n", + " t_r=1.,\n", + " memory='/media/Data/nilearn', memory_level=1, verbose=2)\n", + " brainMasker.fit(func_files1)\n", + "\n", + " ####\n", + " deltaCor_a = fmri_masked_ses1 - fmri_masked_ses2\n", + " print (f'Shape is: {deltaCor_a.shape}')\n", + "\n", + " # run paired t-test \n", + " testDelta = scipy.stats.ttest_rel(fmri_masked_ses1, fmri_masked_ses2) \n", + " print (f'Sum of p values < 0.005 is {np.sum(testDelta[1]<0.005)}')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "amygdalaDiff_Ket = createDelta()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/task_based_analysis/ROI_connectivityAnalysis.ipynb b/task_based_analysis/ROI_connectivityAnalysis.ipynb new file mode 100644 index 0000000..e5e3d6c --- /dev/null +++ b/task_based_analysis/ROI_connectivityAnalysis.ipynb @@ -0,0 +1,3203 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Connectivity betweeen ROIs" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import numpy as np\n", + "import pandas as pd\n", + "import nilearn\n", + "from nilearn import plotting\n", + "import glob\n", + "import os\n", + "from nilearn.input_data import NiftiMasker\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import scipy\n", + "import pymc3 as pm" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "# put functional file, confound file and event file here - this is for one subject\n", + "func_file = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz'\n", + "confound_file = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_desc-confounds_regressors.tsv'\n", + "events_file = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/sub-{sub}_ses-{ses}_30sec_window.csv'" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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scr_idmed_cond
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\n", + "
" + ], + "text/plain": [ + " scr_id med_cond\n", + "0 KPE008 1.0\n", + "1 KPE1223 1.0\n", + "2 KPE1253 0.0\n", + "3 KPE1263 0.0\n", + "4 KPE1293 1.0\n", + "5 KPE1307 1.0\n", + "6 KPE1315 1.0\n", + "7 KPE1322 1.0\n", + "8 KPE1339 1.0\n", + "9 KPE1343 1.0\n", + "10 KPE1351 0.0\n", + "11 KPE1356 0.0\n", + "12 KPE1364 0.0\n", + "13 KPE1369 0.0\n", + "14 KPE1387 1.0\n", + "15 KPE1390 0.0\n", + "16 KPE1403 0.0\n", + "17 KPE1464 1.0\n", + "18 KPE1468 0.0\n", + "19 KPE1480 0.0\n", + "20 KPE1499 1.0" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "medication_cond" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['KPE008', 'KPE1223', 'KPE1253', 'KPE1263', 'KPE1293', 'KPE1307',\n", + " 'KPE1315', 'KPE1322', 'KPE1339', 'KPE1343', 'KPE1351', 'KPE1356',\n", + " 'KPE1364', 'KPE1369', 'KPE1387', 'KPE1390', 'KPE1403', 'KPE1464',\n", + " 'KPE1468', 'KPE1480', 'KPE1499'], dtype=object)" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "subject_list = np.array(medication_cond.scr_id)\n", + "subject_list" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "def removeVars (confoundFile):\n", + " # this method takes the csv regressors file (from fmriPrep) and chooses a few to confound. You can change those few\n", + " import pandas as pd\n", + " confound = pd.read_csv(confoundFile,sep=\"\\t\", na_values=\"n/a\")\n", + " finalConf = confound[['csf','white_matter', 'framewise_displacement', 'dvars', 'std_dvars',\n", + " 'trans_x', 'trans_y', 'trans_z', 'rot_x', 'rot_y', 'rot_z',\n", + " ]] # can add 'global_signal' also , \n", + " #'a_comp_cor_00', 'a_comp_cor_01',\t'a_comp_cor_02', 'a_comp_cor_03', 'a_comp_cor_04', 'a_comp_cor_05'\n", + " # change NaN of FD to zero\n", + " finalConf = np.array(finalConf.fillna(0.0))\n", + " #finalConf[0,2] = 0 # if removing FD than should remove this one also\n", + " return finalConf" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=25\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "\n", + "masker_amg = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " smoothing_fwhm=4, standardize=True, detrend=True, verbose=5, t_r=1,\n", + " high_pass=.01)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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rjvXnk+bcJYO2j833Z8S4adGhtcl9pQJeFNdhX7WtG9OnT9f6DvpKS2YZsUezQ88ZWkQiH7UX5Lx+vu5+TvN5xJQrz1nfM5zz5f6cS/yMmDP34/3hMWA2DseTVgRq77s9j12kBhn9bSSQPulEIpFIJLoUqSqSSCQSXQIzQrJlqV25kAzZDNqWETNd1hQwoop+tnzQakQwIpo5/XW6Dk2W0SZElijGDEV6FrYe/fa3v609LuN2yMDL82Lc1EhhRF7SDgix3nNUbaUE04UYQNFUiMCI0peaTMNR1ZWoDqnPqTR30/QZmUSjYxrsIwMxopQIgxOfNzNTsuqkJL2NSzUuWbJEknT44YfX9rkbYTOqVM1Fm3Spg0yRED/AGIzjMYxKTro9BlVFuscM6nF7UZBf6Tqpc2+UcyGa49Ru9ifvOYP3EoPdmMYWBVfyHFju0wVgHLyXKVqJRDLpRCKR6BrYT7zVVltJao0q5mKIdb7NpKMofcbZ0BdtcKFodEqA6D8uwYwB+pybYjqieJ1I0pS68yRftFhQO4AR9FK1gD/xxBPbzm8kMKwv6YsuukhSezEMmgxYgEKqBs+rejv2my5OlOrC1XuTtGaUtsQAAt4YpTklKk3JmyQKjjCaAsmarAEsm2jTjieuU+A4Ecs2faMbPpcrrrhCknTssceqW2EGXYrlmClH1W8ofUmhBjJrz09WEmJ7FKVosob4uDTrEVGQYDkfowceA358jmTSTGehhSYqNsI+MtCIVqioTOxXv/pVSdIpp5xSe66JxPqAZNKJRCLRJZgxY4Yk6frrr5dUrwZIguLFFpk06w3QzeWFIwlR5Kc1mohOp9uXv0VMmr9HxCQiWVHON6O8Sb4MugzLfUYLw/KSdnqL/ZcMIHCqBVOUSgbnCeWJ40+Km5AZM+iBjKbJHx4xErKGps+yD01tNxXQiOQ/2S73o6XC4+5gFJcDNcOsE4QpBWZKuA9uw3reH/rQh2q3HwvYkjNhwgRJrdYAmrmisp5RHAH9rzZL+pMPvkjogf5c+mkpscgAlrK/LqzxwgsvtJnzyv/bCsACG5EVIRLRieoNM70xEhCi7CT9+7Z2uL9uf7REIxKJbkQy6UQikegy/OY3v5FUsWSpfdHvxZUXo158k5hESnDenuyS7krDv5NcEP3VIIjclxHxoF+bTJmuE/qiuTCMCBFzzUnqynKbXpiPFob0kp4/f74kaffdd5dUhf6byT399NOSKp8oL37pw2KJQE88lvajX4t+MEaOUhLT4ATjxfDx+N2rfJ9Tafqwv9LnSR8gP/uT/qs7p+imYI1W98lRsmYoW2yxRUv/6thXdGP6GBQB6Qacf/75kiqW70juUtqP14+ISpny5uYDzWPsm5wFBOj7pjWJc4E+cfqHvX85J8p5Uc6l6GFLFk+zaNO8pDXAiOoLR8VDGPTjc/Y8tTKhj/eNb3xDkvToo49KkmbPnl3bv0RiXUIy6UQikegysCa31O428IKNFZtILKjC5UUd3V7enoqQXkx5Acp69UYUsV0iYuFcGHIBR9cfq1XRXcpFMheWEcnweNNFVDJpp2OOFob0kt5xxx0lVSteFon3QJtt+LNO4pCrbUrNccLRL0b/mL9HgQX0afsimBHR/OF++OYxky6Z2VNPPdVyLJ8Lc7+ZW0v5PZ5jFO3tvrtvNsOYSft4ZiY8bl0wBi0PzNf1p9vuBklHp6tQ4rOcX7zZbBmISuNFxU44T/3d88CfjI5nO5y3UcALH4RNVpXy74zapshEkw85ynPm/vSXk6nT5x1Fh0e+cZ+TYw1sKXFe9bRp02rHIpFYF5BMOpFIJLoUJYOjq8OfdElRYSyqOMXocFbv8+LI7VKliz7tpqjv/sAFGXXE6XbiWLjP3i5i/1wAmnmTzJmk1dU76KQy3XBiUC9pR/buvffektpNDD4xX3xPCrLRkiVw9e22PBE8QbiKp9+rKUSfbNR99UVx38xGWWjBE3nLLbeU1BpE4IlD/yfVrVgwg6kRURERTmSmB3iczSjN5jyWZMVst9yGFgSPB5miz9nxCaNZLevrX/+6pIpJs+xk+XDw/HC/m5i0EcUy8KFAnzQLY3D/SAEvsp7UnVPEpg33jQ9T9y1irJHinbfnPRWVGTSikq28Z6OCNJzv3M+MWkpWnVj3kEw6kUgkugxeuHvxJ8XBsvSfMuiVC0Z/t/vR7koGMRpuj9K4Ub1wkoZyoctj0CXibU0OqKbGBSNJl/czqSstEeVxvKCn1YDfSeKkOE11pDCol/TWW28tqZ1BM//Z31kCz7+XJ07/GYMiGABAn15UDs+IGLYnuBm0J6IvbhRNXmfCMYPlzeCJQ9ZGvWfmLUfKZDR3eeJRWJ/MKdJcLhFpVvuG5rm6TefIjwbsB580aZKk6gam+a+OdXKeNZUijRh2neKcVI2f5w/jAKKSqexnk65709/Kv1PQgeND33PE4omoBCYtQnzo80HL/kTWBaoL+rrbVy11Z/5+IjEUJJNOJBKJLoFdOA72LF0Idq2ZUJAkkUmzShMFfSgy5fa4KKI4ldv3Qt6LLgbd2kVWkjGfF1m4++BFrkkB858jN5H75rRfjxWtCFH6oeHt3fc6Ru425s6dK2nkC8EM6iVtxtap4hDzL8nspHYGxwhdX0Su1ptyjKOkeU9+XwxPWF8MMnp/8iKWx/fFo2/a503W7r97O4rBs+9k4BwbqrOxnBsT/2kiKvtmBu1Pt8nKSRzPefPmSZJOPvlkjRTsg2bFqf6sJ4ycp9oW2SLnFQNZItUt5qxHedA0qxmMR+hEt73cpvw/H2jRg4mItOGj7TgGnguRGiBfAvQ5R6pwUXnCEr5vzz77bEnSnDlz+j2HRKLbkUw6kUgkxgheTEyePFlS5Uqk60aq2OXjjz8uSXriiSckVYtVRmkzWptgQZNogejFf1QoiVHlJjDuZ3kOJngGF60mBWbfrFbF4EWm0Eaky2AKJBfjJiw+vo9nC0AJk6ORxoBe0lZ22muvvSS1R19GJdCi7cqVcKTFHUW3ss1IPq4p/J8TlKYf+159UW1OqWuXqlBUPfMn0wK4fyQmb0QFzjlhfRNFjMfXp4xQ9+R2H5mqwHOj39sPmZHAokWLJEmvetWrJLXn7fZX1o7zhJH1kT46H3Den9HdrF7FylG8N6Ignf4kFct+Wbe7bhu21ak/nMfoFJEFjdeH/WK/o3ufMSx+kNMiJbXrtqfud2JtRzLpRCKRGCNYEMoMs5SylVoXTHTveDFjIhFFaUfqXgzoJZOOAl8Npt4xJdSLqjLH2H/jopalWcnamTLZpG7GxTfZP/vGvGgL5jBIumzTqY1XX321JOk973mPRgIDekm744wWpemA5dUY7Vy38qesW8Q0jIh5R9tFal5ecTNq3BfAN43NKDyH0pTD83IbHg8zAEYYM/AjinKNROipV26QBTKPmHEA5fmwnjJNaBQN8HZ+UIwEzJJ4Hk1+3PJvNJNRE56ZCfQlcz5SkpHjEVXRih4yTT7oJutK3b5MU4miriMMlFnThMjj+h6KApJ4rt7ezNmfbq80obKKmF9gCxYskCR98IMfHNC5JBJjjWTSiUQiMcqwGX6nnXaSVDE/L/roNpHaF+8Mbo0YNAWiSIgMpsIxEJVuOy7GIsnbOiLDBTWDCFm8JSpcQ3dSWTVMamf5HFczaIpWsYpWKbzl/3tRafIwUgvBAb2kqY0cTQrmTZt9RSaLss2mYIeIEUW+vWg/H9vWAZ9bxD46EY83ONFYAcnjQJ9yp4XNOUF5M/rmY7s0/VBzWaomORk0NaTZJ+bEDyecFz1x4kRJ7VaUOqsGETFY78MaxnX1m8tPPvhokWH8Be+Runrk5f4G52GEOlbcaS52dMz+NN5L8ByifGsyaVunGJjE54qvjR+KBjMNpGqe8sXiY46FMl4iMRQkk04kEolRBv3HJDRUEZOqhQZTO6OFHhdJUU1l1lBmIKoXpBQNagoc9vZ1RV8i1x0rcHEBSXcjGblJAl16dKXQPcVg58gaUZ4X/diWih5uDOglHQ1wxAo4ASN/W12b0QSMormJiCXQvFJXkasEy7zRt1iy0EjjOKrYFUW5kilHTMegNYHsLRr3SOms7m9Mt4gCOHzu5513niRp1qxZbW0PFHw4lCZAqb1CV3QOUruJjuYv5slH89JoYrid+pyj703WFf6/Ln860q0nmnzPTfs1+bh5fOaUGyxXyAcz1QhLJs3rRf3yulSaRKKbkUw6kUgkRhlU0CJzqxNpoouPf2+SYeX29DlHaa7uK91K/u5FVpTeWC6qo6Ip7ksUqElm3RT1TWtAnY54+Z2uMy4MyzGNSrHaZTrcQjoDeklTJSla3dNXyolo9Ldy5+BEuaBRWxFjYR+jvrIKVOSbLtkbfWhc+TMYgufaqdJYZB3guUbjy4lfngN9tKx+xeASTliDqSSDgSe786LJwPjQIMMu+xT1pynfvglN1yT6exODbsp9Lj/r9Abq2m6aD9H2kTUgsqhFjJqpP3xJ0LrFe5RxK9TKl6r7lS8OqvNdeumlkqQPfOADtX1NJLoFyaQTiURilHDBBRdIqorDGJFrom5hRX+qFyYUGmIaJd0NXiRFojJ0y9Enzv0o99xUwrRuH54/5Xu5cOMCr9NAS4ILUuZrl2iSvx7uNNQBvaSbfE9RHiRX3HX+3CgftIlBR4gYi3MsH3roIUnVBHbSOvMsWVfaF88qXc59liqG4D4zCIITwTJ/Tz75pKQq39MVpaJqQp3m0kaMx+jvOvh86Tfk5GUaCNseChhxzxu6KUK6zsoR9Y8sLXqwNVk12IdOI/abmHe0n/9fd5wm61I0nzq13HQa/c3+eKydumJrDCUcPdfIgh2j4L/7HpXayykangvex35s16LOOtSJbkUy6UQikRglUASIiz+KKpWLSy6C6JLyosdkgdHVXvQ0scWIjNG/y8A+FhD6zW9+03Kcsm9RSqLBBSR9zp0WoInyrjupfV3uX0dkCPdlOFx9JQb0kiZziarcRAPpE2Xh7fI3o9Mo2E79Zu6LRd9/+MMftvz91a9+tSTpNa95jaQqf9oT3xPPDNq/O2pUqiag/2Ym6AniSXzvvfdKku6++25JVTm0XXbZRVJlLmHOMcezKTaA6MQfylxr+qD5UImkAYcC57Juv/32kmLFOp4Ple/Kh0xk/fFc9AONWu1EJ3nyJZpu6KjdThh1XR/661cU59HkszaazqXTyHTqKXis+bBnEBH1F1ixTWp/EfFFRuue2zznnHMkSbNnz64/+URijJBMOpFIJEYYTkn0YtCLCTM6ytLWBZsyDdQLaefnsigQJY0ZBEvVrcg9STZLRu126SKrq2vtAkX+jYtjLtyMKCrbiIKUWbfai3Iv5FmK14giuEv4PHm+btsiTNOnT2/bdyAY0EvaE4p5jVFye6c5oFI8AWj+idgSTTZRPisv3i233CJJ+v73vy9Jesc73iFJ2nPPPSVJO+ywg6SKHZfMuQnuk9n7z372M0nS4sWLa7d/7Wtf27JfZAIiItNQk+Wjrl1eO9bxJmuNzFADjZIuYQbtutGeC37YRAwtqkNc9tfn6oeB4wBsvaCpKpIvJAaaY9zExJt82ANBE0tvQmRC7FSBjO1E8QHUGWAajff3PCA7ltpNuSxxSElH/045yUSiW5BMOpFIJEYINqNbRIVBkGaxZHwsDStVC0gvKLwYMhtl8ZsokNfw7wyCpXuSi6towWoXoPv86KOPSqrYsyRts802LX00+2bAX1TQJmLQlF7232mZ8NgxWNGuE7sevR0DSss+Mk3X5NX7mGRceOGFkqTjjz9eg8GAXtLsDFkV1bnIdvtjvywhRr8U1bFohojYAZmd2zFbI5YuXdrSj0ceeURSJYTvKPC66GUfywET999/vyTpwQcflCTddNNNtcc89NBDW9pme0YUTct6u9SdZsk5ygqWpiUyDsYR8Joz+ITiBIOBzXe+6Snpx7Y7iWb3ufrms3nNx+A8ivLoiUjnOvLhR5HRRKd51/21Ee3b5EM2mnzMTdsbkS+cD2DOxyjVyNe/v4h2z2Oajb0P7xXvl9HeiW5DMulEIpEYITid0kwsktclO2PJWKmdSXvR0qSixcA7wwvTstSn1C5cxLZubXwAACAASURBVMhnSq3aVeS+0j3lBVG5LYsNmcH6/KlAFrnsTCLcl6h0rMEob4+JF+sGLRnlfmb9jCswvA/J6mAxoJe0B5vBDpRsa/J91ZlfPOFYjJsOe14sRlJzO05gTySbXf7sz/5MkvTtb39bknTIIYe07PfAAw9Iqibc61//ekntvlqpmtw//vGPJVWM2udw8MEHS5Juvvnmlj5ZUctmK5qrIt++j+0J/utf/1pSu/XB8KSieH/JpBmcEllFKHTAYJTBaHYvXLhQkrT33nu39J/1tilsEPniy5vD14tR+bQCNalqNeUWG51GaUfbN0Ve00rQH5uOhDEiJjzYCPaIoUfxIVH+P9NeyI5Z6arsJ+cvLUB8OVL4w9+HW9oxkRgskkknEonEMOPyyy+XVLmwokhpSi3TNVWSDy/iTRgi5S8uVrlwYfCkF6xe0PjYDNBzHydPniypSk9lmhtZbslCuSAz8zXDtm/4iSeeaGmT1oDId89FGUsfcwHPaHDWj64rvRsJO7GglI/pa3jVVVdJko466qi2NvvDoHzSZm4GzSBe4dIX7QnICVm27YsSsSSaYNy2J7BBNkCfpNmrL8Luu+9e2w9PGjMwH8/+5vIG2XHHHVuO4fMje3vd617Xsh0DPyJ2x2pX/nsUdW8wEptMpjQJRWyLvjtqXXvCerwGA2oxU26P2uicC2RJpanQDwGb9qjmZkQRyJFvuVOm3JQ/zvZopuPDPEIn2t1NnxHDHmiePveLshOafOXez9fT91OdUhlzq90mTcP+u+9/liosTbSJxFgimXQikUgMM7woZEBilKbKhUkdS/ai3gsLMjjmFjO1LRKMYt/oyvPCx4ton5ujtp966qmWfvGcy3PjYtdt+NzshvR3kiGOQZN7juNNckdQFtjfy4UgSQJdK3QJ+ti2PAwUg6on7YG2A92rVIqhc6A4iUqftJlrqR5U/p0Rnwy17zTC1XB7HjgW8vZxycoee+wxSdK5557bdozTTjtNUmUOsk/a+5pJ0+zUlNrQ5JPm+DKtgawiMtP0Bx6TUdxO4/ANOxDY/7fzzju3tMnCAb4xGaASBXCU1hWPPeMn6mT/yvOLmHNk5aC1g/7gTlW5on6UD52enp5+WW2TSl+EKGKdfY7uuSZ9hAidClTQtFla5BgJbsuO72cWlWDaEgOREomxRjLpRCKRGCa4BKarXHEhETE7Lnz893LhSUUxwwsMqmoxwJKKY4w0p1vCpIx9ve+++yRVC3MqoFEoqFyksY62Xadm1O6jyZNZO3OQDbpWo7xpjqvBsTN8Lr5ePlepXXqWC7yInLrNK6+8UpJ0zDHHqBN09JJ2Qv6uu+4qqT260hPJLNSr1yjvsS7yOlK48sVhIAUHplO/GCXcOEHdLpm1AxlsfqnDT37yE0nSxIkTJVWTlKLyTZrn/ZWpqwOFEHw9HO3NicuxqLuJaLoxyF4ZRDEY7W7nrPvGdBuuEuZ+Ms2CVccoa1je0FFObmQh4DXiJ/P6y0pMUnu0cGSGMzgHyPg7RX951E350px/jA2I7jGm6ERWiibza3QOkY+cGQZSe9wMrX20PhlRsFUiMdbImZhIJBLDBC80WcKVgYpeQHqRS/EmL0TKYFAvSr34p7ATmaxh0uQFZbS4MqLgUC/+TWAcbGt4IWSi4wC/Mg/bffWxzZTti3YbJkUMBOTiNZKDdl8ZWOyx8SKb/n3DZNBjU14HkoGovjSFoNyW1ec6RUcvaU88TzjWXPZ3RttGEav+vdTL9cWi/5Th/fT9GU1+WyPyLXIlzZxcTzR/WiWshMeBYfw8dsSQm3yIke+alaii47D6WN0EZLWvyJTjv7MmsFnvRRddJEmaMWNG7bmWsHyembLPg3KFkWUmEsGvC1jhfOB8opWH84MpIv70GJpBe554fJjmQktFE5OuY7HlPIjiGerOvYmdc75xDhg+Fq1S0f3PWs6MrObxO0V5Poxn8HdG/vvcaAHy776eA5nHicRIIJl0IpFIDBO8SPOChuU1DUZOezFBMlK6aczuqD9t+FjexwuT2bNva/m+bFmvK+AjH/lRy/5/+7e9pXIZne3FlRmgP1kb2+dsVwPJQ9l3b+sFusfNx/QC3YvgyKdveJH14Q//uyRp3rw31vaBPnEK5TBV14s9+rLLvtCiwU8STy9OL7jgAknSCSec0NZ2iY5e0mYBXPmShUS+IwYekHWUbZPleSC8rycA83aJyNdo0DTR5IP0gNuEQ/3g8jdGwTeNy0B90FGEtc1ZjIr2ze1PMs4yOtZ+YDNGCs2TVdHXGkVa18HC8/vtt5+kyiRFv6DPy237BqYeO7MKSkRWnaiQPfXQPS7WcneUv8f63/7t31qO9653vUtSu8yjr4GvNU2TnCuRb7o8n9WrV/dbdazTzIem/Ghea44lmXRk6fGLyNfbzxc/D6K87U4i4yPTYyTo4T5SwrJOtS6RGAskk04kEokhwvWid9ttt9rfyeDoNjJxoXneC9Pyb4y+NugO+8AHlrZ8r9wQdlM4cLR3/7/9295Sup/73Gsktaep+jMqruO/O/XUUeDlAtIKbPZn02Xic7L70+Pkcr8cp89+9pct5zBuXO/2J5/8A0nVwn3Roj9vGQsuOLlA9Fh6EV4iEluKgkMjxu1zbEJHL2nmJZq5cCXdVP+Y7Kr8PXKyex8yHG5vNK26jYjFNuWS0hRUtssL3RRFy4sd9ZWISs6RxdovasZiVkzTUumT5oOAuclkJDS5kSX1hygAxp8MviGjNttntG+dvjZ9jlRKY+yD/eBm7dRH9+///u//XntuTimJfNu8cdnnaA6UD1z7pVetWlWr6tVkZYoi8aMa2mTU7HvkR2c2gcfa3/3J2Be2z/7zuOW+NAlHcR3lS7BE3UsykRgLJJNOJBKJIcKL0mjhTfbLhagZGwPe6qRUI3dAE7Fh0Zbx41sf//77F77wP5KkL31p35Zzc1+Yhsl27bN++OGHJbW60+zuYVQ13ZcsNWqXiBe/X/jCvS+26MWsx6LVxWJm/f73Xy+p/fpcdtnhktrVwRgzUKbkkY1H6cBRUSJ/dkJkpA5f0jwI0woikGlHUaJSNVmp881oTbJ5RppHfYg+I9WvCGaU1Ocu/0Y0aSU39ZUXn2wsUnoje+CkYlRu+Tfuw7xfRieTJXWSZ8rxohoUg2/cJk2C0TiWTJFskPPLTNmmOjNozztv77YjBm0wGpzXgpH2LAwQzYXSv2smXc798pwjK1ETS4/OhQzboOm2U6ZOH3XkN+b59KcWx+h6mmSp7UCrFOdtpDeeSIwWkkknEonEEEGFKprqowU6F6L+pNtJapdCNmi6r0SAWn3QXLxTDIaLoEiEiYGAPCcH0LqIkV1EkrTDDju0nZcUCyy5L3R5ffGL+0iSPvGJu1SHaqHooMbW42ywQe+5v/e910qSLr/8nbXnUlcNy+Mc+Z6bcrsjV22Ejl7SnBSdRlZHQRIe8Lp9yMi8yvbE8ARg7eVownSaIxqt2rnSZt9LpaloPCITmNFp/nTkt2S5Nk8ifkZmr5KJ0QxHfzYj16Pc+E5AyUSPZVMRgujB1h/ridgfLSlGVI+80wh8skpfA/q8KeQfVbtiP8t52Skzbvoe7R9lSPBBxr4zjYgvID9waT7175EJMor1kNrnDivE+TtTnphqw3zpRGKskEw6kUgkhohIN5uMOkr5rPN9ln+X2rW0uVixy+ZDH7q1to9VW170muW3LsLcPnO+yaTZLqObLfdbKo6xHC1dKNTipnvIfXI+dJMrsVpgrsanz7W3XTPqK654V8txKRMttQcTkoySANSVBJY6l55Nh0sikUgkEl2Kjl7lTEdgMYEoVYO2dwbJlAEfNKUxWMXmVkoKGlGtVCMyGUdBXPTb0GfiKMOytKbHxavFKFWFx4gQiZ64PY8R/SYMhvInK774s6xzyjSbSMWIEaRGpAdcBzKDqLgF54LPl6vy/saTv/n8WLCFgYEOJLNp1jj44IMlSTfffHO/x+Mqm35AB5ZRTaopoHHNmjXq6ektVelPYqDmbW7XFLxmNMmH0ifHoK2ByuX2Z+7mPeZnls3ZTLljsCL7WJcnm0iMJtLcnUgkEkOEFyiMUG8SuIhqENSZv+tiSKRq4eyAMZqt2/FCy2dUX54xH17Y0ETPc2KsTF01uihjhYQvWviddlpvANoZZ9z34jFax7vtjAPFQZqmuZCl3nw5HhznSKo0itvpNL6lo5e0Lz6ZWiSx2J6P18pSHOBUsmGyaw8EZRSdL0dGEgXccNIbvBhR8Qq2a0b1ne98R4RVdKjM01Q4g31kRGikM0sBC08k99HHNxugiIS3Z33aEpTHZBtkzJG1pcS8efMkSQcccICk9pQ+MmsG87CgRmRFqWOOvM7+zuIx9qM5GtVznsF4+++/v6T2kpUslciau0xhmzHjRklVlGkUJFiy1p6eHvX09Gj8+PFtNW6l+CHAaxZF9/J33ht8wEaSmwYfVk1SvYNJf6IPkwF8hv9O37HPkfKgEQ466CBJlWWNL5WBpsERZb+jfZkf/atf/U716N3/2WcfkiTddddXX9y/9aXt40ydennLOTQFU0YvqbK/kQRy1GZkGfHn/fe7eliU1tr3P9WB/Tn88K819m8gwbHlvpGw0Ste8Qrdcsst4f7JpBOJRGKY0akra7C/lyBZ6mdL7Fffzo47btTSXqe1BZo04Ot+4zb97Vv26b77Wt1Pa9Z4YddvF8O+Nh2/XCx0mhXRtMDzdg8//LDmzZunk08+uXa7jl7SZgX0KbMzZNJMvYhSg6Qqes6MhilWHizq1TYJWUSDHqW4kEFzf/fnrW99q6RqbMq+UTKziREwtajJBEP/pvvMtCmyXQqRGHViJiyaEEk5Rr68MjeyCZG2LU2C9ElHAiB10ZSRiak897rtyIwoiRsdk7ELHg/KqJ5++h0t7bPaj0H2usEGG6inp0fjxo3TRhttVCvN2+STju6RyBfNh060P9thHAPNfpHZ1GiK4K1jm7wXKNJjRLKsLO4SwQzopptukiRtueWWkipLTPQsaErHrNuOL2Ofq601v/xlr4713/3dz1p+J8yg99xzjqTqevg6feQjvVHZ++zTm4tsBTGPIceEFjDGLNRZd6J0PZq5eb/dc889L/bxRy3700RPuAvOGa+qYvU+E1/60l4r7z/901+09K/uOnHeRzEbfM8xHdDvjh//+Me1fTaSSScSicQQEZkyqeMQudkibYC6Y0SmYONzn9tTUvWyjhAVgDjrrMde3L+VOFFT3S+jKPCzE0QpZ/z7k08+KamqPvc3fzNRkjRv3pMt+w3UFO2X9qWXvqNlfxLNuuBELpqifH+66zpl2kZHL2mvCinjSOc7JyQnLrVeyxUX/Y0UdzA4IaK8Q/rNI8YdlduM/MAei4kTeyeJJ49UVXiJlIGiSdzfjVm3fRTl7etgwRcWK4lET0prAKO2OQEjJm3U1V0lbNb5/ve/37JP9ACLgm/I1Dh+ZUGXiPlzLkY3TpTBEDFp/933jK+J4ztOO+0/W/rsc5027V9aztG/+yHCa22fNAuGlNt2ek5GdI4ROO4eS8dC2E8fSXFS4rdJzKbpfpGqOeP7lVWNouAq+s1p+UgkRhvJpBOJRGKIIFvyYilivWTQJiX9LQoi8yojkKOFMhckUQGIz39+L0nSAw88IEm6++67JUl77LFHy3ZRQFQktlIey2gKHjRz/sUvftHSZwulfPWrO0uqzN+dLiibKhB2wsgZVEsGTb1/HiP6TnT0krZfh1qukYmHOcURKysnkwfP+zAPmoy4aXCj0oCRTyhiq1GxismTJ0uSttlmm759HHke+RMjX0aTKhHPhcyS/h0yEx+HDNS+LPtNpXYLRMQgDaacGJ2YvDipm9qmz8usqPIvtVpfSiZtNscHCSNj7S9qeuBE/l3OdT847ddzDVlXGPK5fPKTP21pj/PNtYEXLnx7337OkV6zZk1bWojU/rCIEDFp9iVKD2LsgK+LLTSU//T2tuiY7fKe53U2GJld3m9NFjAfgy9VPnCNprFLJEYayaQTiURiiGBgpb+T1XLBQ3ceXTr9+UINL0S8APSCMwp+5bHd7te+1ivQ48W7F0ePPPKIpEp4xwTFLpyIQNUt1ElEuCD0+N1///2SKjbvBZ2LdvjYHqezz/4/kqrF+N/8zY9f7FNvu//3/+7Xsr376sVb5EKpc5fSfcvyonR5NaXannLKKeoPAyqwwXxn+vMif2WU71pH8yMWajB6dvr0G1t+//nPexWijj++N9ry3HMPbDkWyx4yIo+Rk1E5zjqfeZTnTCsBmS2FD6J80hNPvKX2OBEcqcj+9Hcdmvx+/Dv7HqlS1SEqTUmmRt8zi1SQWdX5Z2l+ZNR2JK7QFFcQPQDdnh/WLn3p6F8/ZKxoxnM02K+pU69/8XvvXN9jjwl6/vnn2/QFyj4ygMXw3/3wNTy3aZHhfItiA5iX77FnqVuPAbUP3A5zzT0GLPpSx6QjFTreC+57FInbX75/IjEaSCadSCQSQwRN+tFCO2LSTDmqC4ojE2PwLNNWI/WtPfaY0LKfXSiMSPciyoukxx9/XFK1CHv9618vqVrUGazUVjLqiPQYDz74oCRp2bJlkqoFnd2KForyuUZWgbPPfmPL8aJIdlY1jJh0uRini4wBkXRrknQMVNBmQEyaPlRfTBZSjwIUvL3bKf2YVr3yBefgMBJ51ixXeqn3nbovxx13Q0ufLr74zyS1r94jlS+OQeSX628bnm+UC+tx9E1xwgnfbWkvMitVx21lEe9733WSpMsuO7xle/9eF2gSRTnz3KjLTj+wWdT8+fMlSSeddJIIn6ej4iMfdMRu/J1530yFKP9PTXIey5988BhR/IXBa04NaDNqP2z82c7sXK6x1cpQWqfWrFmju+9+SlOmLOn73Q/c8tw8Ph4XP5h8D9AS5nuRNZIj0Qya/2j287lRY54a997eLzzf62b6kUxl2Z/oekQBQ97Xffax/fnUU08pkRhLJJNOJBKJIYIlFhmY2OT+YRpiHcvqRA1LqhYcc+f+saR2187Uqb3Sl3YF0grgBSXTCL3I8uLaC87I/Uk/fYko6NCiP27LjJllM7moZrEeuqPI6tme0ZSyW7bhRWnEoCMy1blCXC86eklHq1GfaLQqZfQuO19Gc3oi0A/pT1+8v/qr77W0EX0y0tSwRrLrhnIgqUwUmZjqck+blJoi5TC3beZg9u9x9E1G00wULU6ltzq1Kqm9ipQUR1pH1ZwMsqhO4BxzB4N4DkQPOJqXDKo50ddd/p/azqzQRoWjyCfdpLJHTQA/2HyN3b6DfRy0Y+tJFMdR91BZtWpV3/GOPfZbfb9Rkc1t+OHs+9d+cj9UfQ5msGTCtD7xXmOFKVqdPMa0xHk/VqyiPCWPW74EmpQGo8AlWoAcK/ChD31IicRYIpl0IpFIDBEscBIFkXYqU1zHtqJoYS5qvbhilDcDU8vUy/LvdBfR7+tF0cMPPyypctlwkWwfdlnOd9KkSZLa03m9KHKfSApYuIeMmsGRTAOmK5bEJxL26U8WNErbNSJLB/vWhI5e0mQJXMmWlXmk/vRTB65L61W1WVekFMR2DPqBZ83qDbn3pHD+qidglLvLyOi64zGPmQyGurS8aR56qLc6DSdUf+IAvd/92Xrx7aOeOvWfJbVHezOHtOzjYHVpmRvfn/SdWcoNN/RaDmhW4/iROUVVl+oirzvVTI7ABxXjM3hD+h6IMh/84PLvvgYLFvyppOphNGfOD1qOV0oxOk+6ZNflg8P3Dpmv2/DDnNeKlgg+CGk+9Rxwe2TCNFn6k/1g3nukRBdZGerQpE/ufc2g7YM+4ogjwjYTidFEvy/pqAwbH0ydyPSV6G873kw0pbH6CeEybD/96dkt7fkFdsYZvQ9PvxAYzBZJdkb9q0PTAiJK77JviKXm/LJ1ObYmRIuhd77zgpbj1/Wz6fwiE36UbueXzTXXXBO26QVTJAsZtc1VcfSyLv/WlKITnX+n15R/b6olG0V+ur/Lli2vPa7kud6jn/zkH2r77/9W17v3+4wZF7Ycu8ktYzQxuEgOmIGjkfBNNKeYsshAtv4w0Pnshcjf//3fa99999XcuXMbjyG1+3UNBjUaXABFY1IX/EgyxOsRuYe46PVCsUmgJyqIYuJ03333SZK22morSe0FJPxdqvzYvoZeoP3qV7+SVI0/F7l+/nOcGFjMBToXfO47pYS5fX+Esmn+N70PmV/dhI6YNC8iO9NkhulEPL7pZmrKCSZ8iKqPvfs/+GDvhJ08uT4/tom19tffptD6yPxBNspo7YGiGt/OXup1+0Yv304rH/nT9Zj7g2/iKNI+ytVuUp1rfWF19iLqNC2CfSGil2+kIscXmvfbbbfeNJh77nkm6MELL/a5/Zr39LQuUP1btCBtiqnguTXNlabqVk2R8lF/on53sm90bn6Ib7vttm1tJRJjiX5f0i7DtnRpryShA0xsxydz4QPGq0iWSKx74UY3qldazp9zab/o4egybHvvfUrLdqtWeXXZ+0L4u7/bVZL02te+tqVvNNWRbfT3Imh6ufh36vQ+8cQTL/b9LklVZZfx4232Vb/tEu4TS4va3B3JiZagchLHJUrV8n4uJPGnf/qn/fZVks4//3xJ0ute9zpJlY/LfiuKmPiT5Qh9Pu5rKdJB0y9dMhELbLIWRb/7GnvsmVbENCX3y8F8To/y77Nm/auk1vlWzvV631krm99gg95t5s//E0ntczuSyuSKn+lrNBn709vZlO/nh68rhV78nezI/fDY+Lh1QZx8kUfSxBResbVwxowZGgxOPfVUSdKNN97Y0g+mKvKZyehko06m1P+nuAwD+lhAp6msLH2j0b3h43gh4/vQ6mD2URMl+zXrtopZaSko2+axaRXgODJQ0+ACjv55g/MkWljWtUkXYLS4ZUopRYQidMSkbRbxTRLd1DQReCD8ELU5pM5nHQnTe1tfPEYsRwOx4YbOf1VLn1av7u2zgxqcsP/qV79aUrspLfKB86UltUvMsQ0yRT+U/ud//qdlu6985Y8kSZ/+9C9a2onYfWWScbR46xhceOEhLX1mVH75gPd18A3ofaKya+zDQNMLJOnEE0+UJF199dWS2k2ETVHxlGD091Ityv93W8yPjvobmacNWov86XFjnXTPAd9T7hfrT/th5AULc52jXOVynlZzv9WnPGdOb/Wxs87av6XPbMuffol6rvueYeoNzbE+Zz83fA5cAEYvVGaJcL7W1Tf2g8/jOnPmTCUSazMyujuRSCSGCZEkMn3P0eKOVolyAeKFnxdqtNb402l9BhdDDG6MtKZpUXEcj9v3udk37U8fj4syqd2l57ZMwmxl8bnaIkdrWtTXiMAw/c8LSAZLeuFH+eg6S1XkIqXVhtvTitOEjl7SZp00N7ETZDjuNFfI/LtUrdb96cGxicwT8pxz3ixJmj37tpZjGtXN0HpqPvaXv9wrZedABZtdtttuu5bjsl2aV3zzlCYLM+moT2TjPldPPPeBEefVOVBurrXd//f/3iSpXZnJOea+eWxK9diWzJUmzjLoozwWLQ68pp1OwBLvec97JEnXXnutpIqxRQFhvEGjYuvlNnS9cIybooD58OX50tXA36mLzSyGuoezJM2b1ytzeMopt7/4l56WCO86ExvZP1XLfEyaTyNTrAP8/DvnO82tnmdUCKPIBZ8PdGt4LPwS8AN11qxZSiTWdSSTTiQSiWGCFxRReV7G63BBH0mrSu0LQ/phvahi4RGKy1AWmAvFyGXlhSX963Zjmrz5eGbJJQs1M/Z4mCjQlUorAXPA3VfvRxcqUyZZFpUs3wtCRon3F7cTBR1HrjHD59hp8ZaOXtJz5syRJF155ZWSKobDiUbTArV66Usqk9zti/PfvK99et7X233607tLqurwVoyodYA8IGbgDtKKVvc+Hm8eXhDrTZv11p0nLQds0+caBZRdeuk7JFWVvjbYoLedCy54q6T2AAR/8np4QvMBEpnHpHaLAdlrnXa51O5bHQze+c53tnxfvHixpPaHkq+hb0CPH5XZyn25TyQ0EAXEMXKZaS9kiWSDzBVmWhKDptyeH26ex3/1V99reRB1UnUssn6wzjNzwSN/usfSjNnbMd/d5x6V9GMAmS0/qfaVSCSTTiQSiWGDFxoMkiWzpk+1E93ryG0RpcQyCp86BHTJRG4I+rBJOnxcL9ZcsaquCpe38bGYGUS3jRd6lAKmKybKIPJ3uplIpLgo5mK8BI8R5UszkJqL4g9/+MNtbddhQC9pBgRwhU3RAg8go0A94HUpMj4B6vqyUo778qlP7SapMnucfHKrchOZHVWNWN6tCR5wn3udGSQSWue2nPQeDzMRH+PSS1tLyXn8zGhYb5fXxeD+ZnmlhrqvlfvACNooKMJw29OmTav9fTDweXhcfX68dlEaS/l/6lOzLjgZbaS6xYh9qnBRLMHfWWWJaXK0UPDG937nn3+Qpky5QPfcs1zjx49vUxMr961ETXo/zzjjtS19Y/AS63JTmc5Ml0FAkTgP4zd8L9o6kIw5kYiRTDqRSCSGCccff7wk6Tvf+Y6kOOAwKtRCrekyAJOLUbI8BkxS/pfbc1HFBXgkSsN26NaItK1LkEFzkcmyqlQ9o8+arhYumpsEdehmYs5zuV/kp47Evsi0mRvehAG9pI877jhJ0re//W1J7YEEZBVkA5SrK005Ubh6lCPLAaHD36t0+ruszevJb8H3SL4vUijqT3EsSr9g9Kx9+x4v942TwIzRoMCIx5HjHVUfYz/LCG4yTEbwssA5J7fFOoYTjBdg7jDNc8wDl2IxC4MpF9EnmTJNWsx8oOXFnwyAIbOmX5hR9z09PVq9erV23XUzzZ//J20CH+W2vGaMheB9S0lGjj8lX32vGRQh8fG8ne9FC4AkEokYyaQTiURimOFFFxfYRKSQjdpjUwAAFpxJREFUVqfoF+UAG2SBXPBF0cgkDxETZ4EVBnBSJa0ud5l94YLax2AQo7+zb/yM9N25qKZbK0q1JAEof+N3kjL2ncG4nWJQL2lHSDMx3wNuRAnmZBlS+4nQlxfJ7EVqRc7pNGOxH82fZIpN2r79FW+IzoFh/JwIZC6PPvpoy++skETBA7bPiccoWk4eytSVfad1hP5fMkB/RtKAQ4HHgUpXnAtkx6WJilHUPnf3m1KWZMh8qDBmgg88MmAGuvh3BsaYdbI4vbcr59Dq1au1Zs0aPf30022CFuWxeK/wgeffaSpkqUNv5+vgv/se81hGwhyRBGYikYiRTDqRSCSGGTbtU52LIGOjT7YkA1F9A5ICyqiy9KvR5MLzYstuTQaeMlLa3xnRXvaXBIGpsAwOjSRhmwrkRJXz2I8oQJRjVV4HthUVlKJamceN7qEmDOolPXXqVElV3rRzhT2gTZOiTh2JdXd9ovZ7MWSerJXpA1YSs//LEaSf//znJVWsIYqAjm4EMuoSUaF3fjfIbD0ujJ512oJvAibos2Qd6wFHUoW0UpRgpH40qT3uVqU7+eST29oaKpjXHQWDcBxK0KdOXzFzsKPrz2vGIJ4otoL70WRoS4W3e+CBByRVc8HX3lkMG2+8sZ5//nn19PRo+fLlbay5PBbnH8eL+eVRFkIUSOTfzag5//iQYjpNIpGIkUw6kUgkhhnvf//7JUk333yzpHihTIUxuu3qEEnXRhHjdItFiEoLk5GbOJFRM3C17nj0CZMwMF3Xf6fLJoqSj2SKmfPN/kRphHWBppT49SKVC30Gkfr3gRKZIb2kjznmGEnSwoULJbUrkTGKmFGmJfybB82MwQNCMwdVyxxVbJm5KVOm1PbZrN8DzMnRxITIMvpj1NymzhcvVRPDIvM2h8yePbv2HObPny+pGm9WGeJEoyygz7UuFYATjKkMPgdfl8cee0xS9VAaCfgat9fbrv/0w6GMkSgZaCdtRWVH+fBgcI2vgb9TT9zt8KFDa4HnudX+iPnz52vlypXacMMN9eSTT9bKI/I+jMxyzIxgnr3bZmS7x9DnynuKIhnOjx5IhbREYn1HMulEIpEYITiAlawrKrMaRS9LceQy3QtR5aao1jI/I8lbt2tXoY/LSHYv2pg3XZ6/z8HbcEFpts48arpKIn86U3ijNFW6biJ53pKc8VgMmGZkvvts1+tAMSwvaedPjwTOOeccSe2r/ohhfP3rX++3vV122UVSez1fTzwiSuCPajuX2/aXUy21Mw7rgddpT5c46aSTav8+b948SZX5iUpmlKHz9nXmF487zU9+qER9GAn4WNddd52kdqEBMjmjFILwjUO9aaaNRBrYvJkj5h35a2nWZOAMo7ubKjyddNJJfZrmU6dO1bnnniupyiGX2qO1aQWigISvLRXdPK4es0h4g+X+mLJD6cVEItGMZNKJRCIxQnjooYckVWmUTD+Lql4xx1lqd6mwOJAXXVycRZHlRsSkySq96KW6F9XR+HtJUqJ8aMOLZYoqMeCTbJXn0BSlzQBkBnSyP2VuM48RudIoNmXX4EDR9S/pyC87WNx7772S2v1wZiCMGh8Moghhsi0zXEdG+2JGVoImDDQgob/th3vchwMssUc9bD+sWGmq3JZ+VFsdzBKjtJQ682MdohQRmir5MDIczT1QOHvh/PPP7/sbo7UZgc4HHTMs/Ok0Iko0GjTl+uFkKxUDl0455ZRBnWMisT6i61/SiUQisbbC0qdOV/VCh2I3Jg30jZYLzUiu1YshitKwKBHFpaIocYNBjpQjZiGgptzl8v/um8+7lLutazNizMwnj4obRdHeHlOmGRo+97piUBRTiiLTHdTcadUrYr17SZ9wwgm1f7/lllskVX7hSCy9PzQFZlDhy6awJv9johd+GPkasfwcswfKIBP6iskaaaKLisjX5fh3sh1Nhj4XH98BRkON7zjxxBP7/m+fNaOzo5J6kQWIY8F8aCqSGQxAoiJcIpFoxnr3kk4kEonRhtNVly5d2vJ3yh0zyK/0Sfv/kT82KkoU/Z19YJoh/+6FrF01DnL0Ipk63HUEhwvFqOSrQT1yup3IoJukqPkZMXcG/5bpqjwmrSH0SQ9VKjlf0i/il7/8paR2RmVEsnF1PkpObvopzaDf/e53D98JrAewtvn2228vqV3XmuIB0UOpBNNMmM9MpbWISTMAhrnIvmEdE2Hfs9svI9GHC9bYt7+due8Rg+Zcj3zVjOpm5Lq387kNVA4xkUjkSzqRSCRGDY7wZSQ286cjKeHyb0wPJbPrlGEbUalbLoLNnO32MKPmcSlQJVUkiAtFgwtB5o2z75GLpqk8LxfylPmlqFPp8qGQEc/Xvnu7sIaarpov6RfxwQ9+UJJ02WWXSZL22GMPSRVba1Kk4v/rvrte9LJlyyRJb3vb24bvBNYDOOr9X/7lXyS1m6gi32iJqLpVJIpPDPTvPp4fZDYV9lexa7jgCH1rB3B8IoU6KoLRBMl5zbxoww8tZy8MNmshkVifkS/pRCKRGCVMnz5dknT11VdLqlip0R+Tpq+YiysvkrxoMguNxGwivzDZJkVpqDxmN4bdGlGt5rJPdIl4wcgiOZQjNiJhHv5OXz+10ZkeGJGwsv3IL06p6qOOOkrDgXxJA9b89k00adIkSRWjjioLlaDZyZP4F7/4haTuzEFem2C/rn2tvGnq8qQjnzFvTj6gIt9zZEqMUj6oi021NKdpDCesKMfxoCKdH4zUaSdYNc2fFNXwdp73o6lOl0isa8iXdCKRSIwy3vOe90iSbrjhBkntroi6BRNdNdyHhXT8nVK2Bpk5Ay8Z2UypW29vNTX72x2w6N9LFsqCRhbKsQQtS8o2pTw2lQc26LIxqDxm9CdmFS3APd4OcB0u5Es6gG8i+6ipulQXOeyJQB1m+6Lt904MDc4rt5a3o73Jip2LLLU/kFiTm7W4aVJkYE+TIAQfcG7flcvcrufIjBkzBjACncGKcpdccomkKpCFbJ8VuBiIxE/qnbu61bRp04b9HBKJ9R35kk4kEokxgtmnF4H9BT0ymtuLLfpryewYFEkm6Hbot+WijAtY9tmM2lHfdcGUPoZLBnsfCj1RurYpUj0qgEN/e1QgJyqUw7Ep+0b3jl1Wxx9/fNt5DwX9CxEnEolEIpEYMySTboADyQyWcCzhVZpXVmneHln8xV/8hSTpe9/7nqQqIIoKQFK7ohGVj5hG1JRf6e0jTWGyEEa1ev7YfzeSsBn6y1/+sqSKEe2www6SqnOiGAnHxp92I4xkidr1Bb42lnCl4EzpR2Z0NWsw8/nDmsgG52h0zKjULsvWEjvuuKOkimmX+9O1EtXEpl+clbkIRmszwt3t+LhNzwOmZpbHdZu2GJhB810xXEgmnUgkEolElyKZ9ACR6VPdB4vD7L777pLao1+lWMCDeruMdGWgWLRCZxBWFHRl+HtZp3akcfrpp7d8v/DCCyVJ22yzjaQqZcqSpVlScvRw5JFHSqq0vesYo+ce60qTCbMyVATO7cifS2uQ4fuLsrD2MzPvugT9ucyH9rHchi1P3o4iU/QT07dNRTH6/snEDY5FXR+ffPLJtvMbTiSTTiQSiUSiS5FMOrHWwypOl19+uSRp5513ltS6WmaxiMgXzQhaqgpFnxGTjuAVf11sw2hhuKNQE0MHo71LRFWwPIfIEsmEKdvKKG5amdwe5zR1tTn3y9TH8u9S5b8163YcCSPBI+br7fz3SG+cvuWB3s+0RpRjR23ukbY4JZNOJBKJRKJLkUw6sc7gve99r6SqoIQlXaX2aO3IfxdFuDLqtMn3HJXJ9H5mPxZiSSSkyip07bXXSmq1tJg1kt1xrnIOk0kzE4G+aeYMM0qb1ieWLrWGt+MtSl+2Wbbb9L7+zk8KFLEqlRk2q2UxtoTbsW8cE/q6ywj55cuXSxoZAaI6JJNOJBKJRKJLkUw6sc7h6KOPliRddNFFfX+bPHmyJOnlL3+5pHZfMn1XzN80IjnQSBeZka+sVHTssccO8OwS6wOcP+9IaamSsPUc9Ryyj5T5096Oc85z1/dCmQUhtVuFWIyGCmRmx9QnYGWr8thk6fZNR/Wmfb/St8x8Zp47LWYsGUtFMo6Fz9E50VL1fBktJJNOJBKJRKJLkUw6sc6izmfkEqRbbrmlpLg8I3ND63SIS5it2F/lXGNHs7rYRSKRSAwE+ZJOrFdwdbPnnntOP/jBD8a4N4lEPSwp7EpvUlXOkSUlo8AwCoTQ1ExzN1O2ouBIt0PTsj/7Sy9kXXWatxkQxvrtlDS1OZo10+l+ohALJVVZgINSuCMtWNIf8iWdWC+x0UYb6S1veYsWLVokqVLdim5ygw8Hl2m0D/Gkk04auU4nEon1DmPykv7nf/5nnXnmmbrrrru08cYb6/DDD9dZZ53Vt7L7+te/rrlz5+rOO+/UG97wBt1yyy1j0c1El6NpHu211166//77+7ZfuXKl3vGOd2jJkiVj1eVEYkB44IEH+v7vIDKzTrPQSBAnkrQ1GGhm0NVDYR6z4ahUpvez66f83QFivkd9bMp3kmEz8MtpXmbeDPyMUiU9VkztMmyNYBqZU+PGAmPykl6+fLk++clP6sADD9Qf/vAHTZkyRR/96Ed13nnnSZImTJigU089VT//+c918803j0UXE2sBmubRT3/6075tX3jhBe2888466qijWtqYOnVqbdtnn322pPYavKndnkgkRhONL+mvfOUruv322/sCbiRpzpw52mCDDTR37txBHbQs6fWyl71MM2fO1Kc+9am+vx1yyCGSpAULFgyq/UT34Ve/+pX2339/3XTTTfqjP/ojPfLII9pnn320ePFiHXTQQYNqs2kelbj11lv1xBNP9PmkE4m1AeWi0LK3XjiajTI1KyotSUEflls1a6VvmgIfBuVD6fNm+Umpl4BJFaONSlHS383CNmzbfYlSHt2Omfxmm23Wchy3awbtz0cffVRjjcaX9NSpU/XpT39azzzzjDbffHM9//zzuvLKK7V06VLNnj1bl112We1+EydO1E9+8pOOOnHrrbdqr732GljPE2sVdt55Z33pS1/S+973Pv3nf/6npk+frmnTpumggw4alXm0cOFCHXnkkdpkk006amvOnDkdbZdIJBIjicaX9HbbbacDDzxQV111lWbOnKkbbrhBW265pfbbbz/tt99+Ouecc4bUgRtvvFELFy7UD3/4wyG1Y+y7777D0k5i+DFz5kwtWbJEf/zHf6yenp4+6cNzzjlnROfR73//ey1evLjveOsKcq6vX7Ds7eLFiyVJr3rVqyS1l3Oki8agH9ZR2N7O+0dMOBISYWR0JAwitfuQ7TOOxEgoy+m+sx2fA6VKybRZiINWBfugXehk5syZbecw2uhIzOS4447ri4JdtGiR3v/+93d8gNtuu02bbrqpNt100zaWc/vtt2vKlClavHixdttttwF0O8bcuXMHbYZPjDxmzpypu+66S3PmzKmt9BNhKPPommuu0YQJE/SWt7xlyP3vJuRcTyTWffS8EFUCKLBy5Uptt912uu2223TAAQfo7rvv1sSJEzVr1qy+lzcxadKklsAd4o477tChhx6qCy+8UIcffnjtNgsWLNCiRYsyunsdwYoVK/S6171Ob33rW7V06VL993//tyZMmDDi8+htb3ub3vjGN+qzn/3ssJxHItENuOqqqyRVhWTsZzUjNnukL/nII4+UJF1wwQWSKkZtf7BZrP203t8sl4ycEdEW8nF6YikUtN1220mqcr5Z2Ib+beZFR35ysna+1hj9TWZt2c+HHnpIkvSud71L3YKOmPTGG2+sI488UlOmTNEb3vAGTZw4UZJ03nnnacWKFbX/+nuw3nXXXXr729+us88+u/bBunr1aq1cuVLPP/+81qxZo5UrV7bVQk2sfTjllFO03377acGCBfrzP/9zzZo1S9LIzSOp96b77ne/q+OOO25EzimRSCRGEh0xaUn63ve+pze/+c266KKLhpwzNn36dC1cuLAv0k5qZUyXXHJJ2zGOO+44XXLJJUM6bmLs8K1vfUuzZ8/uY88rVqzQvvvuq8985jN63/veN6g2m+aRJJ155pm6/vrrddtttw35HBKJboStUDvttJOkilEz19is02mIF198saR2RTJGOpPlsjQmt3/mmWckVezU+0sVk46Ke7gN+4h9b5t5s2QsmTT7xoj2qKymo7i7iUEbHb+kH3jgAe2xxx567LHH+iZBIpFIJMYW+ZJet1/SHYmZrFmzRmeddZaOPfbYfEEnEolEF8GCPOeff74kaZdddpEkbbHFFpLafdSM5qbP2i9I+2/9InOxGJaPpIY486XL9qle5pcrX57Mm2bpSuqT0/9O/XGfk8tq2l/+8MMPS9KAgqFHG40v6WeffVbbbLONJk2apBtuuGE0+pRIJBKJREIdvKQ32WSTloLXiUQikeg+nHjiiS3fr7nmGknStttuK6kyGZttMpqbVa6Ye2wtbucS06RcmrWliiWXZV7NaM2YDTNft2GW74hyMm3mVTPvmcfzO8zVrJYtWyZp7SiI01F0dyKRSCQSidFHlqpMJBKJLsJzzz2nKVOm6Ec/+pHuv/9+ffe7363Vt3/uuee0zz77aMWKFX35vSX+8i//UlLlq3ZgmVkr86MNMmmDgWIsVmO4yhyZtlSxcMPBbax+xXxp78f60ZEP2vA52vfswLBDDz20tu/diGTSiUQi0WV405vepEWLFvWZquvwla98RVtvvfUo9ioxFug4BSuRSCQS7bjyyit1/PHH931ftWqV3vjGNw6LUuKOO+6oRYsWtTHpe++9V4cddpjOOusszZw5s5ZJR3jNa14jSTr33HMlSa985SsltdeVtj/XNZwd3X3YYYcN6Bzmz5/f939GnDsVa/PNN5dUpVyVfuyyL1Q/s2/ajNm+Z6eBPfjgg5K6Q4N7sEgmnUgkEkPAMccc06eQ98gjj2innXbSe9/7Xn3xi1/U5ptvHv4bCubMmaMzzjijzzw8EEyaNKlPSjTR/UifdCKRSAwD1qxZoylTpuiggw7qi7T+2Mc+NuzH+cY3vqHnn39e7373uwfF1plKa1GTrbbaSlJ7jWWz06OPPnpQ/a2LoLZuuBkzK3AxP5pCKsx7NnO+//77JWnIqpjdhHxJJxKJxDDgE5/4hH73u99p3rx5He/zwAMPaM899+z73pTu+uyzz+r000/X9ddfP+h+JtYupE86kUgkhogrrrhCH/vYx/Qf//EffYz0jDPO0BlnnBHu04n+BH3Sd955p/bff/8+3+5zzz2n5cuXa6utttLtt9+uyZMnD/lcxgKuy2D/uH3V9JM7H9qKYa77PHv27NHo5pggmXQikUgMAXfccYfmzJmjG2+8se8FLUkf//jH9fGPf3xQbf7hD3/oSz967rnntHLlSr3kJS/R3nvv3RcMJUnf//73ddJJJ+m//uu/Wo6dWHeQL+lEIpEYAr71rW/p6aef1pve9Ka+v735zW/W0qVLB93m7rvv3udfdU7vvffeq8mTJ7ekZU2YMEHjxo3rN1VrbcC0adPGugtdizR3JxKJRCLRpcgUrEQikUgkuhT5kk4kEolEokuRL+lEIpFIJLoU+ZJOJBKJRKJLkS/pRCKRSCS6FPmSTiQSiUSiS5Ev6UQikUgkuhT5kk4kEolEokuRL+lEIpFIJLoU+ZJOJBKJRKJLkS/pRCKRSCS6FP8fJ9W4u8s61tQAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# hippocampus mask\n", + "mask_file_hippo = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file_hippo = nilearn.image.math_img(\"a>=13\", a=mask_file_hippo)\n", + "nilearn.plotting.plot_roi(mask_file_hippo)\n", + "\n", + "masker_hippo = nilearn.input_data.NiftiMasker(mask_img=mask_file_hippo, \n", + " smoothing_fwhm=4, standardize=True, detrend=True, verbose=5, t_r=1,\n", + " high_pass=.01)" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#vmPFC\n", + "mask_file_vmpfc = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file_vmpfc = nilearn.image.math_img(\"a>=5\", a=mask_file_vmpfc)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file_vmpfc)\n", + "\n", + "masker_vmpfc = nilearn.input_data.NiftiMasker(mask_img=mask_file_vmpfc, \n", + " smoothing_fwhm=4, standardize=True, detrend=True, verbose=5, t_r=1,\n", + " high_pass=.01)" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Dir is already there\n" + ] + } + ], + "source": [ + "# now start running subjects and generate average hippocampus and amugdala activity - and correlate between them\n", + "#subject_list = ['KPE008']\n", + "ses = '2'\n", + "output_dir = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/connAnalysis_ses%s' %(ses)\n", + "try:\n", + " os.makedirs(output_dir)\n", + "except:\n", + " print('Dir is already there')\n", + "scr_id = []\n", + "corr_amgHipp = []\n", + "corr_amgvmpfc = []\n", + "corr_hippVmpfc = []\n", + "\n", + "for sub in subject_list:\n", + " try:\n", + " file = np.load(output_dir + '/sub-' + sub + '.npy', allow_pickle=True)\n", + " except:\n", + " try:\n", + " print(f' Analysing subject {sub}')\n", + " subject = sub.split('KPE')[1]\n", + " scr_id.append(sub)\n", + " func = func_file.format(sub=subject, ses=ses)\n", + " confound = confound_file.format(sub=subject, ses=ses)\n", + " event = events_file.format(sub=subject, ses=ses)\n", + " # get timeline for each region\n", + " amg = masker_amg.fit_transform(func, confounds=removeVars(confound))\n", + " hippo = masker_hippo.fit_transform(func, confounds=removeVars(confound))\n", + " vmpfc = masker_vmpfc.fit_transform(func, confounds=removeVars(confound))\n", + "\n", + " print(amg.shape)\n", + " print(hippo.shape)\n", + " # save timeseries for each subject\n", + " x = {'amg': amg, 'hippo': hippo, 'vmpfc': vmpfc}\n", + " np.save(output_dir + '/sub-' + sub, x)\n", + " except:\n", + " print(f'Subject {sub} has not data')" + ] + }, + { + "cell_type": "code", + "execution_count": 465, + "metadata": {}, + "outputs": [], + "source": [ + "ses = '1'\n", + "output_dir = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/connAnalysis_ses%s' %(ses)\n", + "sub = subject_list[0]\n", + "duration = 120 #set duration of event in seconds\n", + "scr_id = []\n", + "corr_amgHipp = []\n", + "corr_amgvmpfc = []\n", + "corr_hippVmpfc = []\n", + "for sub in subject_list:\n", + " subject = sub.split('KPE')[1]\n", + " scr_id.append(sub)\n", + " # load the npy file\n", + " file = np.load(output_dir + '/sub-' + sub + '.npy', allow_pickle=True)\n", + " # load each matrix\n", + " amg = h.item()['amg']\n", + " hippo = h.item()['hippo']\n", + " vmpfc = h.item()['vmpfc']\n", + " # average for all voxels\n", + " amg = np.mean(amg, axis=1)\n", + " hippo = np.mean(hippo, axis =1)\n", + " vmpfc = np.mean(vmpfc, axis=1)\n", + " event = events_file.format(sub=subject, ses=ses)\n", + " events = pd.read_csv(event, sep='\\t')\n", + " onset = int(events.onset[events.trial_type_30=='trauma1_0'])\n", + " # correlate\n", + " corr_amgHipp.append(scipy.stats.pearsonr(amg[onset:onset+duration], hippo[onset:onset+duration])[0])\n", + " corr_amgvmpfc.append(scipy.stats.pearsonr(amg[onset:onset+duration], vmpfc[onset:onset+duration])[0])\n", + " corr_hippVmpfc.append(scipy.stats.pearsonr(hippo[onset:onset+duration], vmpfc[onset:onset+duration])[0])" + ] + }, + { + "cell_type": "code", + "execution_count": 466, + "metadata": {}, + "outputs": [], + "source": [ + "# fisher z transformation\n", + "corr_amgvmpfc = np.arctan(corr_amgvmpfc)\n", + "corr_amgHipp = np.arctan(corr_amgHipp)\n", + "corr_hippVmpfc = np.arctan(corr_hippVmpfc)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "arrays must all be same length", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m df = pd.DataFrame({'scr_id': scr_id, 'corr_amgHipp2': corr_amgHipp, 'corr_amgVmpfc2': corr_amgvmpfc,\n\u001b[0;32m----> 4\u001b[0;31m 'corr_hippVmpfc2': corr_hippVmpfc})\n\u001b[0m\u001b[1;32m 5\u001b[0m \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmerge\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmedication_cond\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrename\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m'med_cond'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'group'\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, data, index, columns, dtype, copy)\u001b[0m\n\u001b[1;32m 433\u001b[0m )\n\u001b[1;32m 434\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 435\u001b[0;31m \u001b[0mmgr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0minit_dict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolumns\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 436\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mMaskedArray\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 437\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmrecords\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mmrecords\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/internals/construction.py\u001b[0m in \u001b[0;36minit_dict\u001b[0;34m(data, index, columns, dtype)\u001b[0m\n\u001b[1;32m 252\u001b[0m \u001b[0marr\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mis_datetime64tz_dtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marr\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0marr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0marr\u001b[0m \u001b[0;32min\u001b[0m \u001b[0marrays\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 253\u001b[0m ]\n\u001b[0;32m--> 254\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0marrays_to_mgr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marrays\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata_names\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolumns\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 255\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 256\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/internals/construction.py\u001b[0m in \u001b[0;36marrays_to_mgr\u001b[0;34m(arrays, arr_names, index, columns, dtype)\u001b[0m\n\u001b[1;32m 62\u001b[0m \u001b[0;31m# figure out the index, if necessary\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 63\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mindex\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 64\u001b[0;31m \u001b[0mindex\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mextract_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marrays\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 65\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 66\u001b[0m \u001b[0mindex\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mensure_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/internals/construction.py\u001b[0m in \u001b[0;36mextract_index\u001b[0;34m(data)\u001b[0m\n\u001b[1;32m 363\u001b[0m \u001b[0mlengths\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mraw_lengths\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 364\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlengths\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 365\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"arrays must all be same length\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 366\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 367\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mhave_dicts\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mValueError\u001b[0m: arrays must all be same length" + ] + } + ], + "source": [ + "# for ses 2\n", + "df = []\n", + "df = pd.DataFrame({'scr_id': scr_id, 'corr_amgHipp2': corr_amgHipp, 'corr_amgVmpfc2': corr_amgvmpfc,\n", + " 'corr_hippVmpfc2': corr_hippVmpfc})\n", + "df = pd.merge(medication_cond, df)\n", + "df = df.rename(columns={'med_cond': 'group'})\n", + "#df['group'] = medication_cond['med_cond']\n", + "df = df.replace(to_replace={'group': {0.0:'midazolam', 1.0:'ketamine'}})" + ] + }, + { + "cell_type": "code", + "execution_count": 467, + "metadata": {}, + "outputs": [], + "source": [ + "# for session 1\n", + "df1 = []\n", + "df1 = pd.DataFrame({'scr_id': scr_id, 'corr_amgHipp1': corr_amgHipp, 'corr_amgVmpfc1': corr_amgvmpfc,\n", + " 'corr_hippVmpfc1': corr_hippVmpfc})\n", + "df1 = pd.merge(medication_cond, df1)\n", + "df1 = df1.rename(columns={'med_cond': 'group'})\n", + "#df['group'] = medication_cond['med_cond']\n", + "df1 = df1.replace(to_replace={'group': {0.0:'midazolam', 1.0:'ketamine'}})" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'df' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdfBoth\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmerge\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mdf1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mdfBoth\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'hippAmgDelta'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdfBoth\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcorr_amgHipp2\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mdfBoth\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcorr_amgHipp1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mdfBoth\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'amgVmpfcDelta'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdfBoth\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcorr_amgVmpfc2\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mdfBoth\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcorr_amgVmpfc1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mdfBoth\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'hippVmpfcDelta'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdfBoth\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcorr_hippVmpfc2\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mdfBoth\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcorr_hippVmpfc1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mdfBoth\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'df' is not defined" + ] + } + ], + "source": [ + "dfBoth = pd.merge(df,df1)\n", + "dfBoth['hippAmgDelta'] = dfBoth.corr_amgHipp2 - dfBoth.corr_amgHipp1 \n", + "dfBoth['amgVmpfcDelta'] = dfBoth.corr_amgVmpfc2 - dfBoth.corr_amgVmpfc1\n", + "dfBoth['hippVmpfcDelta'] = dfBoth.corr_hippVmpfc2 - dfBoth.corr_hippVmpfc1\n", + "dfBoth" + ] + }, + { + "cell_type": "code", + "execution_count": 471, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ttest_indResult(statistic=-0.6368133926734911, pvalue=0.5318447722366961)" + ] + }, + "execution_count": 471, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(x ='group', y='amgVmpfcDelta', data= dfBoth)\n", + "sns.stripplot(x ='group', y='amgVmpfcDelta', data= dfBoth)\n", + "scipy.stats.ttest_ind(dfBoth['amgVmpfcDelta'][dfBoth.group=='ketamine'], \n", + " dfBoth['amgVmpfcDelta'][dfBoth.group=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'df' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;31m# first code new variable for group index (1=ketamine, 2= midazolam)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mgroup\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m'ketamine'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'midazolam'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mdfBoth\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'groupIdx'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mgroup\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mitem\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroup\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;31mNameError\u001b[0m: name 'df' is not defined" + ] + } + ], + "source": [ + "# a difference between amgVMPFC coupling at sesion 2 but not 3\n", + "#lets pymc3 it\n", + "import pymc3 as pm\n", + "# first code new variable for group index (1=ketamine, 2= midazolam)\n", + "group = {'ketamine': 2,'midazolam': 1} \n", + "dfBoth['groupIdx'] =[group[item] for item in df.group] " + ] + }, + { + "cell_type": "code", + "execution_count": 509, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (4 chains in 4 jobs)\n", + "NUTS: [sd, groupIdx, Intercept]\n", + "Sampling 4 chains, 0 divergences: 100%|██████████| 8000/8000 [00:02<00:00, 3025.46draws/s]\n", + "The acceptance probability does not match the target. It is 0.8915758399676582, but should be close to 0.8. Try to increase the number of tuning steps.\n" + ] + } + ], + "source": [ + "# play with glm module of pymc3\n", + "from pymc3.glm import GLM\n", + "\n", + "with pm.Model() as model_glm:\n", + " GLM.from_formula('corr_amgVmpfc2 ~ groupIdx', dfBoth)\n", + " trace = pm.sample(draws=1000, tune=1000)" + ] + }, + { + "cell_type": "code", + "execution_count": 510, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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meansdhpd_2.5%hpd_97.5%mcse_meanmcse_sdess_meaness_sdess_bulkess_tailr_hat
Intercept0.460.010.430.480.00.01361.01361.01372.01500.01.0
groupIdx-0.020.01-0.030.000.00.01379.01332.01405.01478.01.0
sd0.020.000.010.030.00.01446.01426.01376.01471.01.0
\n", + "
" + ], + "text/plain": [ + " mean sd hpd_2.5% hpd_97.5% mcse_mean mcse_sd ess_mean \\\n", + "Intercept 0.46 0.01 0.43 0.48 0.0 0.0 1361.0 \n", + "groupIdx -0.02 0.01 -0.03 0.00 0.0 0.0 1379.0 \n", + "sd 0.02 0.00 0.01 0.03 0.0 0.0 1446.0 \n", + "\n", + " ess_sd ess_bulk ess_tail r_hat \n", + "Intercept 1361.0 1372.0 1500.0 1.0 \n", + "groupIdx 1332.0 1405.0 1478.0 1.0 \n", + "sd 1426.0 1376.0 1471.0 1.0 " + ] + }, + "execution_count": 510, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pm.summary(trace, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "code", + "execution_count": 511, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.03425" + ] + }, + "execution_count": 511, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.distplot(trace.groupIdx)\n", + "sum(trace['groupIdx']>0) / len(trace['groupIdx'])" + ] + }, + { + "cell_type": "code", + "execution_count": 519, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Presenting differences between the groups using scatter plot for each group + \n", + "## The resulting Bayesian analyses plots (density of differences and boxplot)\n", + "\n", + "sns.set_style(\"whitegrid\")\n", + "plt.figure(figsize=(5,5))\n", + "grid = plt.GridSpec(2, 20, wspace=.1, hspace=0.0) # building a grid to put the graphs in\n", + "plt.subplot(grid[:, :10])\n", + "#fig.add_subplot(grid[0,0])\n", + "g1= sns.stripplot(x='group',y='corr_amgVmpfc2',hue = 'group', data=dfBoth, s=8)\n", + "#g1 = sns.boxplot(x='group',y='meanAct',hue = 'group', data=df)\n", + "#g1.set_ylim(.35,.5)\n", + "g1.legend_.remove()\n", + "\n", + "plt.subplot(grid[:, 10])\n", + "g3 = sns.boxplot(trace.groupIdx, orient='v')\n", + "#g3.set_ylim(.35,.5)\n", + "g3.set_yticks([])\n", + "\n", + "plt.subplot(grid[:, 11:13])\n", + "g2 = sns.distplot(trace.groupIdx, vertical=True, color=\"Green\")\n", + "#g2.set_ylim(.35,.5)\n", + "#g2.set_yticks([])\n", + "g2.yaxis.tick_right()" + ] + }, + { + "cell_type": "code", + "execution_count": 413, + "metadata": {}, + "outputs": [], + "source": [ + "######## T test instead?\n", + "with pm.Model() as model:\n", + " ketamine_mean = pm.Normal('ketamine_mean', mu = 0, sd=.1)\n", + " midazolam_mean = pm.Normal('midazolam_mean', mu = 0, sd=.1) \n", + " \n", + " ketamine_std = pm.Uniform('ketamine_std', lower=1, upper=30)\n", + " midazolam_std = pm.Uniform('midazolam_std', lower=1, upper=30)\n", + " \n", + " ν = pm.Exponential('ν_min_one', 1/.05) + .01\n", + "\n", + "with model:\n", + " λ1 = ketamine_std**-2\n", + " λ2 = midazolam_std**-2 \n", + "\n", + " group1 = pm.StudentT('group1', nu=ν, mu=ketamine_mean, lam=λ1, observed=dfBoth.corr_amgVmpfc2[dfBoth.group=='ketamine'])\n", + " group2 = pm.StudentT('group2', nu=ν, mu=midazolam_mean, lam=λ2, observed=dfBoth.corr_amgVmpfc2[dfBoth.group=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": 414, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (4 chains in 4 jobs)\n", + "NUTS: [ν_min_one, midazolam_std, ketamine_std, midazolam_mean, ketamine_mean]\n", + "Sampling 4 chains, 0 divergences: 100%|██████████| 10000/10000 [00:02<00:00, 4000.37draws/s]\n" + ] + } + ], + "source": [ + "with model:\n", + "\n", + " diff_of_means = pm.Deterministic('difference of means', ketamine_mean - midazolam_mean)\n", + " diff_of_stds = pm.Deterministic('difference of stds', ketamine_std - midazolam_std)\n", + " effect_size = pm.Deterministic('effect size',\n", + " diff_of_means / np.sqrt(\n", + " (ketamine_std**2 + midazolam_std**2) / 2))\n", + " trace = pm.sample(2000)" + ] + }, + { + "cell_type": "code", + "execution_count": 415, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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meansdhpd_3%hpd_97%mcse_meanmcse_sdess_meaness_sdess_bulkess_tailr_hat
ketamine_mean0.0810.095-0.1000.2570.0010.0018707.06382.08702.06302.01.0
midazolam_mean0.0760.097-0.1140.2490.0010.0017741.05984.07741.06553.01.0
ketamine_std1.1590.1761.0001.4590.0020.0017754.07409.06124.03666.01.0
midazolam_std1.1830.2071.0001.5280.0020.0027356.06942.05478.03544.01.0
ν_min_one0.4520.1260.2250.6850.0020.0017035.06916.06845.05519.01.0
difference of means0.0040.135-0.2480.2580.0010.0018115.05015.08128.06273.01.0
difference of stds-0.0240.273-0.5370.4740.0030.0027699.06079.08201.06570.01.0
effect size0.0040.116-0.2100.2260.0010.0018399.05086.08405.06633.01.0
\n", + "
" + ], + "text/plain": [ + " mean sd hpd_3% hpd_97% mcse_mean mcse_sd \\\n", + "ketamine_mean 0.081 0.095 -0.100 0.257 0.001 0.001 \n", + "midazolam_mean 0.076 0.097 -0.114 0.249 0.001 0.001 \n", + "ketamine_std 1.159 0.176 1.000 1.459 0.002 0.001 \n", + "midazolam_std 1.183 0.207 1.000 1.528 0.002 0.002 \n", + "ν_min_one 0.452 0.126 0.225 0.685 0.002 0.001 \n", + "difference of means 0.004 0.135 -0.248 0.258 0.001 0.001 \n", + "difference of stds -0.024 0.273 -0.537 0.474 0.003 0.002 \n", + "effect size 0.004 0.116 -0.210 0.226 0.001 0.001 \n", + "\n", + " ess_mean ess_sd ess_bulk ess_tail r_hat \n", + "ketamine_mean 8707.0 6382.0 8702.0 6302.0 1.0 \n", + "midazolam_mean 7741.0 5984.0 7741.0 6553.0 1.0 \n", + "ketamine_std 7754.0 7409.0 6124.0 3666.0 1.0 \n", + "midazolam_std 7356.0 6942.0 5478.0 3544.0 1.0 \n", + "ν_min_one 7035.0 6916.0 6845.0 5519.0 1.0 \n", + "difference of means 8115.0 5015.0 8128.0 6273.0 1.0 \n", + "difference of stds 7699.0 6079.0 8201.0 6570.0 1.0 \n", + "effect size 8399.0 5086.0 8405.0 6633.0 1.0 " + ] + }, + "execution_count": 415, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pm.summary(trace)" + ] + }, + { + "cell_type": "code", + "execution_count": 416, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pm.forestplot(trace, var_names=['ketamine_mean',\n", + " 'midazolam_mean']);" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# check association with PCL score\n", + "## read pcl scores\n", + "pclDf = pd.read_csv('/home/or/Documents/kpe_analyses/KPEIHR0009_DATA_2019-10-07_1121.csv')\n", + "# take only KPE patients\n", + "pclDf = pclDf[pclDf['scr_id'].str.startswith('KPE')]\n", + "dfP = pd.DataFrame({'subject': pclDf['scr_id']})\n", + "dfP_PCL = pclDf[['scr_id','redcap_event_name','pcl5_1', 'pcl5_2', 'pcl5_3', 'pcl5_4', 'pcl5_5', 'pcl5_6', 'pcl5_7',\n", + " 'pcl5_8', 'pcl5_9', 'pcl5_10', 'pcl5_11', 'pcl5_12', 'pcl5_13', 'pcl5_14', 'pcl5_15', 'pcl5_16', 'pcl5_17',\n", + " 'pcl5_18', 'pcl5_19', 'pcl5_20']]\n", + "# remove NAs\n", + "dfP_PCL = dfP_PCL.dropna()\n", + "# set list of columns for analysis\n", + "colList = list(dfP_PCL)\n", + "colList.remove('scr_id')\n", + "colList.remove('redcap_event_name')\n", + "# set total pcl scores \n", + "dfP_PCL['pclTotal'] = dfP_PCL[colList].sum(axis=1)\n", + "sns.distplot(dfP_PCL.pclTotal)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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redcap_event_name30Days90DaysScreeningVisit1Visit7
scr_id
KPE 1560NaNNaN77.0NaNNaN
KPE 1565NaNNaN60.0NaNNaN
KPE006NaNNaN36.0NaNNaN
KPE00856.049.0NaN58.061.0
KPE1205NaNNaN43.0NaNNaN
..................
KPE1548NaNNaN43.0NaNNaN
KPE1549NaNNaN12.0NaNNaN
KPE1556NaNNaN0.0NaNNaN
KPE1561NaNNaN57.0NaNNaN
KPE1563NaNNaN50.0NaNNaN
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65 rows × 5 columns

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" + ], + "text/plain": [ + "redcap_event_name 30Days 90Days Screening Visit1 Visit7\n", + "scr_id \n", + "KPE 1560 NaN NaN 77.0 NaN NaN\n", + "KPE 1565 NaN NaN 60.0 NaN NaN\n", + "KPE006 NaN NaN 36.0 NaN NaN\n", + "KPE008 56.0 49.0 NaN 58.0 61.0\n", + "KPE1205 NaN NaN 43.0 NaN NaN\n", + "... ... ... ... ... ...\n", + "KPE1548 NaN NaN 43.0 NaN NaN\n", + "KPE1549 NaN NaN 12.0 NaN NaN\n", + "KPE1556 NaN NaN 0.0 NaN NaN\n", + "KPE1561 NaN NaN 57.0 NaN NaN\n", + "KPE1563 NaN NaN 50.0 NaN NaN\n", + "\n", + "[65 rows x 5 columns]" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# reshape it to wide\n", + "df2=dfP_PCL.pivot(index = 'scr_id',columns='redcap_event_name', values='pclTotal')\n", + "list(df2)\n", + "df2 = df2.rename(columns={\"30_day_follow_up_s_arm_1\": \"30Days\", \"90_day_follow_up_s_arm_1\": \"90Days\",\n", + " \"screening_selfrepo_arm_1\": \"Screening\", \"visit_1_arm_1\": \"Visit1\", \n", + " \n", + " \"visit_7_week_follo_arm_1\": \"Visit7\"})\n", + "#df2['scr_id'] = dfP_PCL['scr_id']\n", + "df2" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'dfBoth' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# merging two data frames toghether\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mdfTest\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmerge\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdfBoth\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdf2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mon\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'scr_id'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0;31m# create difference pcl score\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mdfTest\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'days30_1'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdfTest\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'30Days'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mdfTest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mVisit1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mdfTest\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'days30_s'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdfTest\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'30Days'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mdfTest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mScreening\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'dfBoth' is not defined" + ] + } + ], + "source": [ + "# merging two data frames toghether\n", + "dfTest = pd.merge(dfBoth, df2, on = 'scr_id')\n", + "# create difference pcl score\n", + "dfTest['days30_1'] = dfTest['30Days'] - dfTest.Visit1\n", + "dfTest['days30_s'] = dfTest['30Days'] - dfTest.Screening\n", + "dfTest['days7_1'] = dfTest['Visit7'] - dfTest.Visit1\n", + "dfTest" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'dfTest' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlmplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'days30_s'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'corr_amgHipp2'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mhue\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'group'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdfTest\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mnaMask\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0misnan\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdfTest\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'days30_s'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mscipy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpearsonr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdfTest\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'days30_s'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m~\u001b[0m\u001b[0mnaMask\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdfTest\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'hippAmgDelta'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m~\u001b[0m\u001b[0mnaMask\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'dfTest' is not defined" + ] + } + ], + "source": [ + "sns.lmplot(x='days30_s',y='corr_amgHipp2',hue='group', data=dfTest)\n", + "naMask = np.isnan(dfTest['days30_s'])\n", + "scipy.stats.pearsonr(dfTest['days30_s'][~naMask], dfTest['hippAmgDelta'][~naMask])" + ] + }, + { + "cell_type": "code", + "execution_count": 479, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Unnamed: 0Event.NrCDA.nSCRCDA.LatencyCDA.AmpSumCDA.SCRCDA.ISCRCDA.PhasicMaxCDA.TonicTTP.nSCRTTP.LatencyTTP.AmpSumGlobal.MeanGlobal.MaxDeflectionEvent.NIDEvent.Namescr_idscantrial_typemed_cond
0010.00.90160.40520.32460.32460.74021.411312.33601.301615.65690.782955KPE14644trauma11
991-1.00.6380.11620.20630.20630.74231.994312.29201.363713.67810.996755KPE14643trauma11
181810.00.6579-0.395-0.4127-0.4127-0.23150.605712.7850-0.348319.21130.079955KPE14642trauma11
272712.0-1.10472.23712.07432.07431.28061.037111.33802.204714.13522.544955KPE14641trauma11
36361-1.0NaN-0.5283-0.5194-0.5194-0.5895-0.19250NaN-0.333313.00940.000055KPE14804trauma10
454512.0-1.0119-0.3137-0.3186-0.3186-0.33562.19350NaN-0.432816.43140.004355KPE14802trauma10
545410.01.70122.64792.64942.64942.66210.85100NaNNaN7.60361.056755KPE14801trauma10
636311.01.0568-0.08470.64610.64610.57652.327511.83302.42292.84020.015255KPE13873trauma11
72721-1.0NaN-0.7928-1.0284-1.0284-0.19812.27880NaN-0.33334.58910.001955KPE13872trauma11
818110.00.48342.60382.64062.64062.63181.76340NaN-0.48494.39480.692555KPE13871trauma11
90901-1.01.05840.48920.98540.9854-0.0878-1.103413.10501.33610.05670.174355KPE13644trauma10
99991-1.01.46370.50390.40990.40990.4436-1.356113.20500.40436.82890.239955KPE13643trauma10
10810810.00.677-0.3778-0.1953-0.19530.0338-1.01720NaN-0.36499.95260.132455KPE13642trauma10
11711710.0-0.31330.63020.76260.76261.24480.128211.97700.32649.37870.250155KPE13641trauma10
12612611.00.5426-0.5826-0.5854-0.5854-0.55540.518412.2810-0.21744.23360.034955KPE13903trauma10
13513511.0-1.66182.25322.36492.36491.6086-0.89770NaN-0.63033.90651.092655KPE13902trauma10
14414411.0-0.09402.66072.65832.65832.63661.869211.86202.661615.74441.088355KPE13901trauma10
15315310.00.4695-0.4381.66061.66061.72320.75340NaN-0.540713.31850.615355KPE13394trauma11
16216212.0-0.2056-0.4125-0.4331-0.4331-0.66491.26060NaN-0.817611.51760.587255KPE13393trauma11
17117110.00.13610.96081.20421.20421.84982.069511.50401.30113.70530.305055KPE13392trauma11
18018010.00.03752.62442.63032.63032.6288-1.096911.70702.66287.91781.196655KPE13391trauma11
1891891-1.0NaN-0.8582-0.8380-0.8380-0.69470.354413.9690-0.24123.61220.001355KPE13152trauma11
19819810.0-1.7728-0.3381-0.4779-0.4779-0.43850.73480NaN-0.43814.91840.000655KPE13151trauma11
2072071-1.00.52820.3457-0.0817-0.08170.07480.35700NaN-0.471928.27220.001255KPE13434trauma11
21621610.0-0.3553-0.6013-0.6499-0.6499-0.60931.441721.73901.428.13900.026855KPE13433trauma11
22522510.0-0.4958-0.4394-0.6157-0.6157-0.7353-0.144711.43700.31187.38170.014555KPE13432trauma11
23423411.00.21872.50122.34652.34652.31351.203512.16302.509111.78310.581555KPE13431trauma11
24324312.0-0.8518-0.4893-0.5349-0.5349-0.59680.127513.4510-0.55348.17230.027155KPE12234trauma11
25225210.00.5943-0.0942-0.1871-0.1871-0.64980.747531.574-0.09189.93740.499355KPE12233trauma11
2612611-1.0-1.02651.05071.62771.62771.52771.284612.90701.72029.85390.316055KPE12232trauma11
27027011.00.5223-0.4497-0.5267-0.5267-0.38802.26630NaN-0.589616.13220.000055KPE12231trauma11
2792791NaNNaNNaN2.66232.66232.66371.98820NaNNaN4.24320.089655KPE12934trauma11
2882881NaN-1.0909-1.0868-1.0922-1.0922-0.86640.832431.909-1.07823.69050.070055KPE12933trauma11
29729710.0-0.92611.27571.07431.07430.9665-0.997031.1260.3391.97660.205355KPE12932trauma11
30630610.0-0.82482.49662.57342.57342.32030.377311.13702.55125.83750.479355KPE12931trauma11
3153151NaNNaNNaN0.61390.6139-0.43682.07940NaNNaN2.20000.001055KPE13564trauma10
32432410.01.72632.28152.30482.30481.3996-0.41360NaN-0.732114.69894.232455KPE13563trauma10
33333310.0-0.43121.30851.70211.70211.4030-1.08480NaN-0.342611.92785.683355KPE13562trauma10
34234210.01.18832.40491.91111.91111.1299-0.842611.98102.630710.43032.502455KPE13561trauma10
\n", + "
" + ], + "text/plain": [ + " Unnamed: 0 Event.Nr CDA.nSCR CDA.Latency CDA.AmpSum CDA.SCR CDA.ISCR \\\n", + "0 0 1 0.0 0.9016 0.4052 0.3246 0.3246 \n", + "9 9 1 -1.0 0.638 0.1162 0.2063 0.2063 \n", + "18 18 1 0.0 0.6579 -0.395 -0.4127 -0.4127 \n", + "27 27 1 2.0 -1.1047 2.2371 2.0743 2.0743 \n", + "36 36 1 -1.0 NaN -0.5283 -0.5194 -0.5194 \n", + "45 45 1 2.0 -1.0119 -0.3137 -0.3186 -0.3186 \n", + "54 54 1 0.0 1.7012 2.6479 2.6494 2.6494 \n", + "63 63 1 1.0 1.0568 -0.0847 0.6461 0.6461 \n", + "72 72 1 -1.0 NaN -0.7928 -1.0284 -1.0284 \n", + "81 81 1 0.0 0.4834 2.6038 2.6406 2.6406 \n", + "90 90 1 -1.0 1.0584 0.4892 0.9854 0.9854 \n", + "99 99 1 -1.0 1.4637 0.5039 0.4099 0.4099 \n", + "108 108 1 0.0 0.677 -0.3778 -0.1953 -0.1953 \n", + "117 117 1 0.0 -0.3133 0.6302 0.7626 0.7626 \n", + "126 126 1 1.0 0.5426 -0.5826 -0.5854 -0.5854 \n", + "135 135 1 1.0 -1.6618 2.2532 2.3649 2.3649 \n", + "144 144 1 1.0 -0.0940 2.6607 2.6583 2.6583 \n", + "153 153 1 0.0 0.4695 -0.438 1.6606 1.6606 \n", + "162 162 1 2.0 -0.2056 -0.4125 -0.4331 -0.4331 \n", + "171 171 1 0.0 0.1361 0.9608 1.2042 1.2042 \n", + "180 180 1 0.0 0.0375 2.6244 2.6303 2.6303 \n", + "189 189 1 -1.0 NaN -0.8582 -0.8380 -0.8380 \n", + "198 198 1 0.0 -1.7728 -0.3381 -0.4779 -0.4779 \n", + "207 207 1 -1.0 0.5282 0.3457 -0.0817 -0.0817 \n", + "216 216 1 0.0 -0.3553 -0.6013 -0.6499 -0.6499 \n", + "225 225 1 0.0 -0.4958 -0.4394 -0.6157 -0.6157 \n", + "234 234 1 1.0 0.2187 2.5012 2.3465 2.3465 \n", + "243 243 1 2.0 -0.8518 -0.4893 -0.5349 -0.5349 \n", + "252 252 1 0.0 0.5943 -0.0942 -0.1871 -0.1871 \n", + "261 261 1 -1.0 -1.0265 1.0507 1.6277 1.6277 \n", + "270 270 1 1.0 0.5223 -0.4497 -0.5267 -0.5267 \n", + "279 279 1 NaN NaN NaN 2.6623 2.6623 \n", + "288 288 1 NaN -1.0909 -1.0868 -1.0922 -1.0922 \n", + "297 297 1 0.0 -0.9261 1.2757 1.0743 1.0743 \n", + "306 306 1 0.0 -0.8248 2.4966 2.5734 2.5734 \n", + "315 315 1 NaN NaN NaN 0.6139 0.6139 \n", + "324 324 1 0.0 1.7263 2.2815 2.3048 2.3048 \n", + "333 333 1 0.0 -0.4312 1.3085 1.7021 1.7021 \n", + "342 342 1 0.0 1.1883 2.4049 1.9111 1.9111 \n", + "\n", + " CDA.PhasicMax CDA.Tonic TTP.nSCR TTP.Latency TTP.AmpSum Global.Mean \\\n", + "0 0.7402 1.4113 1 2.3360 1.3016 15.6569 \n", + "9 0.7423 1.9943 1 2.2920 1.3637 13.6781 \n", + "18 -0.2315 0.6057 1 2.7850 -0.3483 19.2113 \n", + "27 1.2806 1.0371 1 1.3380 2.2047 14.1352 \n", + "36 -0.5895 -0.1925 0 NaN -0.3333 13.0094 \n", + "45 -0.3356 2.1935 0 NaN -0.4328 16.4314 \n", + "54 2.6621 0.8510 0 NaN NaN 7.6036 \n", + "63 0.5765 2.3275 1 1.8330 2.4229 2.8402 \n", + "72 -0.1981 2.2788 0 NaN -0.3333 4.5891 \n", + "81 2.6318 1.7634 0 NaN -0.4849 4.3948 \n", + "90 -0.0878 -1.1034 1 3.1050 1.336 10.0567 \n", + "99 0.4436 -1.3561 1 3.2050 0.4043 6.8289 \n", + "108 0.0338 -1.0172 0 NaN -0.3649 9.9526 \n", + "117 1.2448 0.1282 1 1.9770 0.3264 9.3787 \n", + "126 -0.5554 0.5184 1 2.2810 -0.2174 4.2336 \n", + "135 1.6086 -0.8977 0 NaN -0.6303 3.9065 \n", + "144 2.6366 1.8692 1 1.8620 2.6616 15.7444 \n", + "153 1.7232 0.7534 0 NaN -0.5407 13.3185 \n", + "162 -0.6649 1.2606 0 NaN -0.8176 11.5176 \n", + "171 1.8498 2.0695 1 1.5040 1.3011 3.7053 \n", + "180 2.6288 -1.0969 1 1.7070 2.6628 7.9178 \n", + "189 -0.6947 0.3544 1 3.9690 -0.2412 3.6122 \n", + "198 -0.4385 0.7348 0 NaN -0.4381 4.9184 \n", + "207 0.0748 0.3570 0 NaN -0.4719 28.2722 \n", + "216 -0.6093 1.4417 2 1.7390 1.42 8.1390 \n", + "225 -0.7353 -0.1447 1 1.4370 0.3118 7.3817 \n", + "234 2.3135 1.2035 1 2.1630 2.5091 11.7831 \n", + "243 -0.5968 0.1275 1 3.4510 -0.5534 8.1723 \n", + "252 -0.6498 0.7475 3 1.574 -0.0918 9.9374 \n", + "261 1.5277 1.2846 1 2.9070 1.7202 9.8539 \n", + "270 -0.3880 2.2663 0 NaN -0.5896 16.1322 \n", + "279 2.6637 1.9882 0 NaN NaN 4.2432 \n", + "288 -0.8664 0.8324 3 1.909 -1.0782 3.6905 \n", + "297 0.9665 -0.9970 3 1.126 0.339 1.9766 \n", + "306 2.3203 0.3773 1 1.1370 2.5512 5.8375 \n", + "315 -0.4368 2.0794 0 NaN NaN 2.2000 \n", + "324 1.3996 -0.4136 0 NaN -0.7321 14.6989 \n", + "333 1.4030 -1.0848 0 NaN -0.3426 11.9278 \n", + "342 1.1299 -0.8426 1 1.9810 2.6307 10.4303 \n", + "\n", + " Global.MaxDeflection Event.NID Event.Name scr_id scan trial_type \\\n", + "0 0.7829 5 5 KPE1464 4 trauma1 \n", + "9 0.9967 5 5 KPE1464 3 trauma1 \n", + "18 0.0799 5 5 KPE1464 2 trauma1 \n", + "27 2.5449 5 5 KPE1464 1 trauma1 \n", + "36 0.0000 5 5 KPE1480 4 trauma1 \n", + "45 0.0043 5 5 KPE1480 2 trauma1 \n", + "54 1.0567 5 5 KPE1480 1 trauma1 \n", + "63 0.0152 5 5 KPE1387 3 trauma1 \n", + "72 0.0019 5 5 KPE1387 2 trauma1 \n", + "81 0.6925 5 5 KPE1387 1 trauma1 \n", + "90 0.1743 5 5 KPE1364 4 trauma1 \n", + "99 0.2399 5 5 KPE1364 3 trauma1 \n", + "108 0.1324 5 5 KPE1364 2 trauma1 \n", + "117 0.2501 5 5 KPE1364 1 trauma1 \n", + "126 0.0349 5 5 KPE1390 3 trauma1 \n", + "135 1.0926 5 5 KPE1390 2 trauma1 \n", + "144 1.0883 5 5 KPE1390 1 trauma1 \n", + "153 0.6153 5 5 KPE1339 4 trauma1 \n", + "162 0.5872 5 5 KPE1339 3 trauma1 \n", + "171 0.3050 5 5 KPE1339 2 trauma1 \n", + "180 1.1966 5 5 KPE1339 1 trauma1 \n", + "189 0.0013 5 5 KPE1315 2 trauma1 \n", + "198 0.0006 5 5 KPE1315 1 trauma1 \n", + "207 0.0012 5 5 KPE1343 4 trauma1 \n", + "216 0.0268 5 5 KPE1343 3 trauma1 \n", + "225 0.0145 5 5 KPE1343 2 trauma1 \n", + "234 0.5815 5 5 KPE1343 1 trauma1 \n", + "243 0.0271 5 5 KPE1223 4 trauma1 \n", + "252 0.4993 5 5 KPE1223 3 trauma1 \n", + "261 0.3160 5 5 KPE1223 2 trauma1 \n", + "270 0.0000 5 5 KPE1223 1 trauma1 \n", + "279 0.0896 5 5 KPE1293 4 trauma1 \n", + "288 0.0700 5 5 KPE1293 3 trauma1 \n", + "297 0.2053 5 5 KPE1293 2 trauma1 \n", + "306 0.4793 5 5 KPE1293 1 trauma1 \n", + "315 0.0010 5 5 KPE1356 4 trauma1 \n", + "324 4.2324 5 5 KPE1356 3 trauma1 \n", + "333 5.6833 5 5 KPE1356 2 trauma1 \n", + "342 2.5024 5 5 KPE1356 1 trauma1 \n", + "\n", + " med_cond \n", + "0 1 \n", + "9 1 \n", + "18 1 \n", + "27 1 \n", + "36 0 \n", + "45 0 \n", + "54 0 \n", + "63 1 \n", + "72 1 \n", + "81 1 \n", + "90 0 \n", + "99 0 \n", + "108 0 \n", + "117 0 \n", + "126 0 \n", + "135 0 \n", + "144 0 \n", + "153 1 \n", + "162 1 \n", + "171 1 \n", + "180 1 \n", + "189 1 \n", + "198 1 \n", + "207 1 \n", + "216 1 \n", + "225 1 \n", + "234 1 \n", + "243 1 \n", + "252 1 \n", + "261 1 \n", + "270 1 \n", + "279 1 \n", + "288 1 \n", + "297 1 \n", + "306 1 \n", + "315 0 \n", + "324 0 \n", + "333 0 \n", + "342 0 " + ] + }, + "execution_count": 479, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "## Loading GSR data\n", + "dfGSR = pd.read_csv('/home/or/kpe_task_analysis/testing.csv')\n", + "\n", + "# add KPE at the beginning of each scr id\n", + "dfGSR['scr_id'] = \"KPE\" + dfGSR[\"scr_id\"].map(str) \n", + "# pclDat[((pclDat['redcap_event_name'] == 'screening_selfrepo_arm_1'\n", + "dfGSR_trauma1 = dfGSR[(dfGSR[\"trial_type\"]=='trauma1')]\n", + "dfGSR_trauma1" + ] + }, + { + "cell_type": "code", + "execution_count": 480, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MultiIndex([('CDA.PhasicMax', 1),\n", + " ('CDA.PhasicMax', 2),\n", + " ('CDA.PhasicMax', 3),\n", + " ('CDA.PhasicMax', 4),\n", + " ( 'med_cond', 1),\n", + " ( 'med_cond', 2),\n", + " ( 'med_cond', 3),\n", + " ( 'med_cond', 4),\n", + " ( '3rd_1st', ''),\n", + " ( 'begin_endPE', '')],\n", + " names=[None, 'scan'])\n" + ] + } + ], + "source": [ + "# make it wide\n", + "dfGSR_wide = dfGSR_trauma1.pivot(index='scr_id', columns='scan', values=['CDA.PhasicMax', 'med_cond'])\n", + "dfGSR_wide['3rd_1st'] = dfGSR_wide['CDA.PhasicMax', 3] - dfGSR_wide['CDA.PhasicMax', 1]\n", + "dfGSR_wide['begin_endPE'] = dfGSR_wide['CDA.PhasicMax', 2] - dfGSR_wide['CDA.PhasicMax', 1]\n", + "print(dfGSR_wide.columns)\n", + "gsronly = dfGSR_wide[['3rd_1st','begin_endPE' ,'med_cond']]" + ] + }, + { + "cell_type": "code", + "execution_count": 481, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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CDA.PhasicMaxmed_cond3rd_1stbegin_endPE
scan12341234
scr_id
KPE1223-0.38801.5277-0.6498-0.59681.01.01.01.0-0.26181.9157
KPE12932.32030.9665-0.86642.66371.01.01.01.0-3.1867-1.3538
KPE1315-0.4385-0.6947NaNNaN1.01.0NaNNaNNaN-0.2562
KPE13392.62881.8498-0.66491.72321.01.01.01.0-3.2937-0.7790
KPE13432.3135-0.7353-0.60930.07481.01.01.01.0-2.9228-3.0488
KPE13561.12991.40301.3996-0.43680.00.00.00.00.26970.2731
KPE13641.24480.03380.4436-0.08780.00.00.00.0-0.8012-1.2110
KPE13872.6318-0.19810.5765NaN1.01.01.0NaN-2.0553-2.8299
KPE13902.63661.6086-0.5554NaN0.00.00.0NaN-3.1920-1.0280
KPE14641.2806-0.23150.74230.74021.01.01.01.0-0.5383-1.5121
KPE14802.6621-0.3356NaN-0.58950.00.0NaN0.0NaN-2.9977
\n", + "
" + ], + "text/plain": [ + " CDA.PhasicMax med_cond 3rd_1st \\\n", + "scan 1 2 3 4 1 2 3 4 \n", + "scr_id \n", + "KPE1223 -0.3880 1.5277 -0.6498 -0.5968 1.0 1.0 1.0 1.0 -0.2618 \n", + "KPE1293 2.3203 0.9665 -0.8664 2.6637 1.0 1.0 1.0 1.0 -3.1867 \n", + "KPE1315 -0.4385 -0.6947 NaN NaN 1.0 1.0 NaN NaN NaN \n", + "KPE1339 2.6288 1.8498 -0.6649 1.7232 1.0 1.0 1.0 1.0 -3.2937 \n", + "KPE1343 2.3135 -0.7353 -0.6093 0.0748 1.0 1.0 1.0 1.0 -2.9228 \n", + "KPE1356 1.1299 1.4030 1.3996 -0.4368 0.0 0.0 0.0 0.0 0.2697 \n", + "KPE1364 1.2448 0.0338 0.4436 -0.0878 0.0 0.0 0.0 0.0 -0.8012 \n", + "KPE1387 2.6318 -0.1981 0.5765 NaN 1.0 1.0 1.0 NaN -2.0553 \n", + "KPE1390 2.6366 1.6086 -0.5554 NaN 0.0 0.0 0.0 NaN -3.1920 \n", + "KPE1464 1.2806 -0.2315 0.7423 0.7402 1.0 1.0 1.0 1.0 -0.5383 \n", + "KPE1480 2.6621 -0.3356 NaN -0.5895 0.0 0.0 NaN 0.0 NaN \n", + "\n", + " begin_endPE \n", + "scan \n", + "scr_id \n", + "KPE1223 1.9157 \n", + "KPE1293 -1.3538 \n", + "KPE1315 -0.2562 \n", + "KPE1339 -0.7790 \n", + "KPE1343 -3.0488 \n", + "KPE1356 0.2731 \n", + "KPE1364 -1.2110 \n", + "KPE1387 -2.8299 \n", + "KPE1390 -1.0280 \n", + "KPE1464 -1.5121 \n", + "KPE1480 -2.9977 " + ] + }, + "execution_count": 481, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dfGSR_wide" + ] + }, + { + "cell_type": "code", + "execution_count": 482, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/reshape/merge.py:618: UserWarning: merging between different levels can give an unintended result (2 levels on the left, 1 on the right)\n", + " warnings.warn(msg, UserWarning)\n" + ] + }, + { + "data": { + "text/plain": [ + "Index([ 'scr_id', 'three_one', 'begin_endPE',\n", + " 'med_cond', ('med_cond', 2), ('med_cond', 3),\n", + " ('med_cond', 4), 'group', 'corr_amgHipp2',\n", + " 'corr_amgVmpfc2', 'corr_hippVmpfc2', 'corr_amgHipp1',\n", + " 'corr_amgVmpfc1', 'corr_hippVmpfc1', 'hippAmgDelta',\n", + " 'amgVmpfcDelta', 'hippVmpfcDelta'],\n", + " dtype='object')" + ] + }, + "execution_count": 482, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "gsrMerged = gsronly.merge(dfBoth, left_on='scr_id', right_on='scr_id', how='outer')\n", + "# drop NAs\n", + "#gsrMerged = gsrMerged.dropna(subset=[('3rd_1st', '')])\n", + "# change wierd column name\n", + "gsrMerged=gsrMerged.rename(columns = {('3rd_1st', ''):'three_one'})\n", + "gsrMerged=gsrMerged.rename(columns = {('med_cond' ,1): 'med_cond'})\n", + "gsrMerged=gsrMerged.rename(columns = {('begin_endPE', ''): 'begin_endPE'})\n", + "gsrMerged.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 484, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(0.2845731067763817, 0.45798341866666903)" + ] + }, + "execution_count": 484, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "gsrMerged\n", + "sns.lmplot(x='three_one', y='amgVmpfcDelta', data=gsrMerged)\n", + "naMask = np.isnan(gsrMerged['three_one'])\n", + "scipy.stats.pearsonr(gsrMerged['three_one'][~naMask], gsrMerged['amgVmpfcDelta'][~naMask])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Lets load the AAL atlas and look only on the right amygdala-hippocampus" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "first = np.load('/home/or/kpe_task_analysis/trauma_ses1.npy')\n", + "second = np.load('/home/or/kpe_task_analysis/trauma_ses2.npy')\n", + "\n", + "deltaMatrix_each = np.array(second) - np.array(first)\n", + "deltaMat_zfisher = []\n", + "for mat2, mat1 in zip(second, first):\n", + " mat1z = np.arctanh(mat1)\n", + " mat2z = np.arctanh(mat2)\n", + " deltaMat = mat2z - mat1z\n", + " deltaMat_zfisher.append(deltaMat)\n", + "\n", + "deltaMatz = np.array(deltaMat_zfisher)\n", + "\n", + "#first = \n", + "#second = np.load('/home/or/kpe_task_analysis/trauma_ses2.npy') # load second session 21 subjects using AAL atlas" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'gsrMerged' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mleft_amg_hippo\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdeltaMatz\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m36\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m40\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mgsrMerged\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'left_amgHippo'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mleft_amg_hippo\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;31mNameError\u001b[0m: name 'gsrMerged' is not defined" + ] + } + ], + "source": [ + "left_amg_hippo = deltaMatz[36,40,:]\n", + "\n", + "gsrMerged['left_amgHippo'] = left_amg_hippo" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'gsrMerged' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlmplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'left_amgHippo'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'three_one'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mhue\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'group'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mgsrMerged\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mscipy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpearsonr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgsrMerged\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'three_one'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m~\u001b[0m\u001b[0mnaMask\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgsrMerged\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'left_amgHippo'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m~\u001b[0m\u001b[0mnaMask\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'gsrMerged' is not defined" + ] + } + ], + "source": [ + "sns.lmplot(x='left_amgHippo', y='three_one',hue='group', data=gsrMerged)\n", + "scipy.stats.pearsonr(gsrMerged['three_one'][~naMask], gsrMerged['left_amgHippo'][~naMask])" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'dfTest' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdfTest\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'left_amgHippo'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mleft_amg_hippo\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0msns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlmplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'left_amgHippo'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'days7_1'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mhue\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'group'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdfTest\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mmaskNan\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0misnan\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdfTest\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'days7_1'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'dfTest' is not defined" + ] + } + ], + "source": [ + "dfTest['left_amgHippo'] = left_amg_hippo\n", + "sns.lmplot(x='left_amgHippo', y='days7_1',hue='group', data=dfTest)\n", + "\n", + "maskNan = np.isnan(dfTest['days7_1'])\n", + "\n", + "scipy.stats.pearsonr(dfTest.left_amgHippo[~maskNan], dfTest.days7_1[~maskNan])" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'dfTest' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# lets scale it and run bayesian to make inference better\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mdfTest\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'left_hipAmg_Z'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mdfTest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mleft_amgHippo\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mdfTest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mleft_amgHippo\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m 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"Sampling 4 chains, 0 divergences: 100%|██████████| 40000/40000 [00:05<00:00, 6753.17draws/s]\n" + ] + } + ], + "source": [ + "# run pymc3 GLM\n", + "# play with glm module of pymc3\n", + "import pymc3 as pm\n", + "from pymc3.glm import GLM\n", + "\n", + "with pm.Model() as model_glm:\n", + " GLM.from_formula('Days7_1Z ~ left_hipAmg_Z', data= dfTest, \n", + " # priors= {'Intercept': pm.Normal.dist(mu=0, sd=2),\n", + " # 'left_hipAmg_Z': pm.Normal.dist(mu=0, sd=2),\n", + " # }\n", + " )\n", + " trace = pm.sample(draws=5000, tune=5000)" + ] + }, + { + "cell_type": "code", + "execution_count": 213, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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meansdhpd_5%hpd_95%mcse_meanmcse_sdess_meaness_sdess_bulkess_tailr_hat
Intercept0.0420.244-0.3540.4390.0020.00217211.07825.017703.012051.01.0
left_hipAmg_Z0.6710.2430.2791.0690.0020.00117035.015917.017614.012540.01.0
sd0.8970.2060.5891.1910.0020.00111779.011316.012123.09485.01.0
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" + ], + "text/plain": [ + " mean sd hpd_5% hpd_95% mcse_mean mcse_sd ess_mean \\\n", + "Intercept 0.042 0.244 -0.354 0.439 0.002 0.002 17211.0 \n", + "left_hipAmg_Z 0.671 0.243 0.279 1.069 0.002 0.001 17035.0 \n", + "sd 0.897 0.206 0.589 1.191 0.002 0.001 11779.0 \n", + "\n", + " ess_sd ess_bulk ess_tail r_hat \n", + "Intercept 7825.0 17703.0 12051.0 1.0 \n", + "left_hipAmg_Z 15917.0 17614.0 12540.0 1.0 \n", + "sd 11316.0 12123.0 9485.0 1.0 " + ] + }, + "execution_count": 213, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pm.summary(trace, credible_interval=.9)" + ] + }, + { + "cell_type": "code", + "execution_count": 188, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(200,)" + ] + }, + "execution_count": 188, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "trace['Intercept'][-200:].shape" + ] + }, + { + "cell_type": "code", + "execution_count": 216, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 216, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "t=trace\n", + "x = dfTest['left_hipAmg_Z']\n", + "y = dfTest['Days7_1Z']\n", + "sns.scatterplot(x='left_hipAmg_Z', y='Days7_1Z', data=dfTest, label='data')\n", + "for a_, b_ in zip(t['Intercept'][-300:], t['left_hipAmg_Z'][-300:]):\n", + " plt.plot(x, a_*x + b_, c='gray', alpha=0.1)\n", + "#plt.plot(x, a*x + _b, label='true regression line', lw=3., c='red')\n", + "plt.legend(loc='best')" + ] + }, + { + "cell_type": "code", + "execution_count": 503, + "metadata": {}, + "outputs": [], + "source": [ + "def pearsonr_ci(x,y,alpha=0.05):\n", + " from scipy import stats\n", + " ''' calculate Pearson correlation along with the confidence interval using scipy and numpy\n", + " Parameters\n", + " ----------\n", + " x, y : iterable object such as a list or np.array\n", + " Input for correlation calculation\n", + " alpha : float\n", + " Significance level. 0.05 by default\n", + " Returns\n", + " -------\n", + " r : float\n", + " Pearson's correlation coefficient\n", + " pval : float\n", + " The corresponding p value\n", + " lo, hi : float\n", + " The lower and upper bound of confidence intervals\n", + " '''\n", + "\n", + " r, p = stats.pearsonr(x,y)\n", + " r_z = np.arctanh(r)\n", + " se = 1/np.sqrt(x.size-3)\n", + " z = stats.norm.ppf(1-alpha/2)\n", + " lo_z, hi_z = r_z-z*se, r_z+z*se\n", + " lo, hi = np.tanh((lo_z, hi_z))\n", + " return r, p, lo, hi" + ] + }, + { + "cell_type": "code", + "execution_count": 505, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(0.6587333583234611,\n", + " 0.007571957688924434,\n", + " 0.22106909036290767,\n", + " 0.8755474295202351)" + ] + }, + "execution_count": 505, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pearsonr_ci(dfTest.left_amgHippo[~maskNan], dfTest.days7_1[~maskNan])" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/ROI_timecourse-Alternative_scripts.ipynb b/task_based_analysis/ROI_timecourse-Alternative_scripts.ipynb new file mode 100644 index 0000000..ba22e04 --- /dev/null +++ b/task_based_analysis/ROI_timecourse-Alternative_scripts.ipynb @@ -0,0 +1,857 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Time course based ROI analysis\n", + "In this notebook we will take ROI timecourse in the first 30sec of the trauma script and compare different groups and sessions" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/sklearn/externals/joblib/__init__.py:15: DeprecationWarning: sklearn.externals.joblib is deprecated in 0.21 and will be removed in 0.23. Please import this functionality directly from joblib, which can be installed with: pip install joblib. If this warning is raised when loading pickled models, you may need to re-serialize those models with scikit-learn 0.21+.\n", + " warnings.warn(msg, category=DeprecationWarning)\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import nilearn\n", + "from nilearn import plotting\n", + "import glob\n", + "import os\n", + "from nilearn.input_data import NiftiMasker\n", + "import matplotlib.pyplot as plt\n", + "from connUtils import removeVars, timeSeriesSingle\n", + "import scipy\n", + "work_dir = '/media/Data/work/KPE_ROI/timecourse'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# put functional file, confound file and event file here - this is for one subject\n", + "func_file = '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz'\n", + "confound_file = '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_desc-confounds_regressors.tsv'\n", + "events_file = '/media/Data/KPE_BIDS/condition_files/withNumbers/sub-{sub}_ses-{ses}_30sec_window.csv'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Amygdala" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=19\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# here I use a masked image so all will have same size - create a function that does that\n", + "def generate_timeSeries(sub, ses, mask_file): \n", + " nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4, standardize=True, t_r=1,high_pass = .01,\n", + " verbose=5) # cache options\n", + " fmri_masked_ses = nifti_masker.fit_transform(func_file.format(sub=sub, ses=ses), confound_file.format(sub=sub, ses=ses))\n", + " # memory= os.path.join(work_dir,'nilearn_cache_alternative'), memory_level=0,\n", + " return fmri_masked_ses\n", + "\n", + "def plot_series(time1, time2):\n", + " # recieves two time series and returns a graph of the two with std's\n", + " time1_mean = np.mean(time1, axis=0)\n", + " time1_std = np.std(time1, axis=0)\n", + " smooth_path = time1_mean\n", + " under_line = (smooth_path - time1_std)\n", + " over_line = (smooth_path + time1_std)\n", + " time2_mean = np.mean(time2, axis=0)\n", + " time2_std = np.std(time2, axis=0)\n", + " smooth_path2 = time2_mean\n", + " under_line2 = (smooth_path2 - time2_std)\n", + " over_line2 = (smooth_path2 + time2_std)\n", + " plt.figure(figsize = [10,5])\n", + " plt.plot(time1_mean, \"blue\")\n", + " plt.fill_between(range(120), under_line, over_line, color='b', alpha=.1)\n", + " plt.plot(time2_mean, \"red\")\n", + " plt.fill_between(range(120), under_line2, over_line2, color='r', alpha=.1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "\n", + "ketamine_list = list(medication_cond['scr_id'][medication_cond['med_cond']==1])\n", + "ket_list = []\n", + "for subject in ketamine_list:\n", + " print(subject)\n", + " sub = subject.split('KPE')[1]\n", + " ket_list.append(sub)\n", + "\n", + "\n", + "midazolam_list = list(medication_cond['scr_id'][medication_cond['med_cond']==0])\n", + "mid_list = []\n", + "for subject in midazolam_list:\n", + " print(subject)\n", + " sub = subject.split('KPE')[1]\n", + " mid_list.append(sub)\n", + "mid_list.remove('1480')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_amg_sad', ket_func1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_amg_sad', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_amg_sad', mid_func1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_amg_sad', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_series(ket_func1, ket_func2)\n", + "plot_series(mid_func1, mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Calculate correlation between first and seond session in this timecourse. \n", + "cor_mid = []\n", + "for i in range(len(mid_func1)):\n", + " cor = scipy.stats.pearsonr(mid_func1[i], mid_func2[i])#, rowvar=False)\n", + " cor_mid.append(cor)\n", + "np.mean(np.array(cor_mid)[:,0])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# removing one subject that has problems in data in session 2 (1351)\n", + "np.array(mid_func2).shape\n", + "del mid_func2[2]\n", + "del mid_func1[2]\n", + "\n", + "##\n", + "del mid_func1[4]\n", + "del mid_func2[4]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## generating boxplot to show the activation around the peak (3-15 sec)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# before that, lets see where are the global maximums of each subject (location = second in the script)\n", + "ket1=[]\n", + "for mat in ket_func1:\n", + " print(np.argmax(mat))\n", + " ket1.append(np.argmax(mat))\n", + "ket2 = []\n", + "for mat in ket_func2:\n", + " print(np.argmax(mat))\n", + " ket2.append(np.argmax(mat))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid1 = []\n", + "for mat in mid_func1:\n", + " \n", + " mid1.append(np.argmax(mat))\n", + "mid2 = []\n", + "for mat in mid_func2:\n", + " print(np.argmax(mat))\n", + " mid2.append(np.argmax(mat))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# lets plot the locations of maximums for subject\n", + "plt.figure(figsize = [10,5])\n", + "plt.scatter(ket_list + mid_list,ket1 + mid1, color = \"blue\", alpha = 0.6)\n", + "plt.scatter(ket_list + mid_list , ket2 + mid2 , color = \"red\", alpha = 0.3)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# boxplot on the first part of script\n", + "#ket1_mean = np.mean(ket_func1, axis=0)\n", + "mid1_mean = np.mean(mid_func1[5:20], axis=1)\n", + "mid2_mean = np.mean(mid_func2[5:20], axis=1)\n", + "ket1_mean = np.mean(ket_func1[5:20], axis=1)\n", + "ket2_mean = np.mean(ket_func2[5:20], axis=1)\n", + "plt.figure(figsize = [10,5])\n", + "plt.boxplot([ket1_mean, ket2_mean, mid1_mean, mid2_mean])\n", + "#plt.boxplot([ket1_mean[0:15], ket2_mean[0:15]])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# now lets built it around individual global maximum\n", + "def maxVec(funcArr):\n", + " vec = []\n", + " for mat in funcArr:\n", + " vec.append(np.argmax(mat))\n", + " maxi = []\n", + " for i, x in enumerate(vec):\n", + " maxi.append(funcArr[i][x])\n", + " return maxi" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket1_max = maxVec(ket_func1)\n", + "ket2_max = maxVec(ket_func2)\n", + "mid1_max = maxVec(mid_func1)\n", + "mid2_max = maxVec(mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid1_max" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.figure(figsize = [10,5])\n", + "labels = ['','Ket_ses1', 'Ket_ses2', 'Mid_ses1', 'Mid_ses2']\n", + "x_pos = np.arange(len(labels))\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "plt.xticks(x_pos, labels)\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Hippocampus" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_hippo_sad', ket_func1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_hippo_sad', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_hippo_sad', mid_func1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_hippo_sad', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_series(ket_func1, ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_series(mid_func1, mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "x1 = np.array(mid_func1)\n", + "x2 = np.array(mid_func2)\n", + "a = scipy.signal.correlate(x1,x2)\n", + "a.shape\n", + "#plt.xcorr(x1, x2)\n", + "a[0].shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## vmPFC" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/binConjunc_PvNxDECxRECxMONxPRI_vmpfc.nii.gz'\n", + "#mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_vmPFC_sad', ket_func1)\n", + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_vmPFC_sad', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_vmPFC_sad', mid_func1)\n", + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_vmPFC_sad', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_series(mid_func1, mid_func2)\n", + "plot_series(ket_func1, ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket1_max = maxVec(ket_func1)\n", + "ket2_max = maxVec(ket_func2)\n", + "mid1_max = maxVec(mid_func1)\n", + "mid2_max = maxVec(mid_func2)\n", + "plt.figure(figsize = [10,5])\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Striatum" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/binConjunc_PvNxDECxRECxMONxPRI_striatum.nii.gz'\n", + "#mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_striatum_sad', ket_func1)\n", + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_striatum_sad', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_striatum_sad', mid_func1)\n", + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_striatum_sad', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_series(mid_func1, mid_func2)\n", + "plot_series(ket_func1, ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket1_max = maxVec(ket_func1)\n", + "ket2_max = maxVec(ket_func2)\n", + "mid1_max = maxVec(mid_func1)\n", + "mid2_max = maxVec(mid_func2)\n", + "plt.figure(figsize = [10,5])\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## vACC" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/ventral anterior_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=4\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_vACC_sad', ket_func1)\n", + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_vACC_sad', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_vACC_sad', mid_func1)\n", + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='sad1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_vACC_sad', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for i in range(len(mid_func1)):\n", + " plt.plot(mid_func1[i]) \n", + " plt.plot(mid_func2[i]) \n", + " plt.show()\n", + "#plot_series(ket_func1, ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.plot(ket_func1[0])\n", + "plt.plot(ket_func1[1])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket1_max = maxVec(ket_func1)\n", + "ket2_max = maxVec(ket_func2)\n", + "mid1_max = maxVec(mid_func1)\n", + "mid2_max = maxVec(mid_func2)\n", + "\n", + "plt.figure(figsize = [10,5])\n", + "labels = ['','Ket_ses1', 'Ket_ses2', 'Mid_ses1', 'Mid_ses2']\n", + "x_pos = np.arange(len(labels))\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "plt.xticks(x_pos, labels)\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Compare timecourse of different regions" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "vmPFC = np.load('ket_func1_vmPFC.npy')\n", + "amygdala = np.load('ket_func1_amg.npy')\n", + "hippo = np.load('ket_func1_hippo.npy')\n", + "vACC = np.load('ket_func1_vACC.npy')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_series(hippo,vmPFC)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for i,x in enumerate(ket_list):\n", + " plt.plot(hippo[i])\n", + " plt.plot(vmPFC[i], color = \"red\")\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/ROI_timecourse.ipynb b/task_based_analysis/ROI_timecourse.ipynb new file mode 100644 index 0000000..1ec2812 --- /dev/null +++ b/task_based_analysis/ROI_timecourse.ipynb @@ -0,0 +1,3036 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Time course based ROI analysis\n", + "In this notebook we will take ROI timecourse in the first 30sec of the trauma script and compare different groups and sessions" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import nilearn\n", + "from nilearn import plotting\n", + "import glob\n", + "import os\n", + "from nilearn.input_data import NiftiMasker\n", + "import matplotlib.pyplot as plt\n", + "from connUtils import removeVars, timeSeriesSingle\n", + "import scipy\n", + "work_dir = '/media/Data/work/KPE_ROI/timecourse'" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [], + "source": [ + "# put functional file, confound file and event file here - this is for one subject\n", + "func_file = '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz'\n", + "confound_file = '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_desc-confounds_regressors.tsv'\n", + "events_file = '/media/Data/KPE_BIDS/condition_files/withNumbers/sub-{sub}_ses-{ses}_30sec_window.csv'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Amygdala" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=19\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [], + "source": [ + "# here I use a masked image so all will have same size - create a function that does that\n", + "def generate_timeSeries(sub, ses, mask_file): \n", + " nifti_masker = NiftiMasker(\n", + " mask_img= mask_file,\n", + " smoothing_fwhm=4, standardize=True, t_r=1,high_pass = .01,\n", + " verbose=7) # cache options\n", + " fmri_masked_ses = nifti_masker.fit_transform(func_file.format(sub=sub, ses=ses), confound_file.format(sub=sub, ses=ses))\n", + " #memory= os.path.join(work_dir,'nilearn_cache'), memory_level=1,\n", + " return fmri_masked_ses\n", + "\n", + "def plot_series(time1, time2):\n", + " # recieves two time series and returns a graph of the two with std's\n", + " time1_mean = np.mean(time1, axis=0)\n", + " time1_std = np.std(time1, axis=0)\n", + " smooth_path = time1_mean\n", + " under_line = (smooth_path - time1_std)\n", + " over_line = (smooth_path + time1_std)\n", + " time2_mean = np.mean(time2, axis=0)\n", + " time2_std = np.std(time2, axis=0)\n", + " smooth_path2 = time2_mean\n", + " under_line2 = (smooth_path2 - time2_std)\n", + " over_line2 = (smooth_path2 + time2_std)\n", + " plt.figure(figsize = [10,5])\n", + " plt.plot(time1_mean, \"blue\")\n", + " plt.fill_between(range(120), under_line, over_line, color='b', alpha=.1)\n", + " plt.plot(time2_mean, \"red\")\n", + " plt.fill_between(range(120), under_line2, over_line2, color='r', alpha=.1)" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "KPE008\n", + "KPE1223\n", + "KPE1293\n", + "KPE1307\n", + "KPE1315\n", + "KPE1322\n", + "KPE1339\n", + "KPE1343\n", + "KPE1387\n", + "KPE1464\n", + "KPE1499\n", + "KPE1253\n", + "KPE1263\n", + "KPE1351\n", + "KPE1356\n", + "KPE1364\n", + "KPE1369\n", + "KPE1390\n", + "KPE1403\n", + "KPE1468\n", + "KPE1480\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "\n", + "ketamine_list = list(medication_cond['scr_id'][medication_cond['med_cond']==1])\n", + "ket_list = []\n", + "for subject in ketamine_list:\n", + " print(subject)\n", + " sub = subject.split('KPE')[1]\n", + " ket_list.append(sub)\n", + "\n", + "\n", + "midazolam_list = list(medication_cond['scr_id'][medication_cond['med_cond']==0])\n", + "mid_list = []\n", + "for subject in midazolam_list:\n", + " print(subject)\n", + " sub = subject.split('KPE')[1]\n", + " mid_list.append(sub)\n", + "#mid_list.remove('1480')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_amg', ket_func1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_amg', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# mean and std - plot timeseries\n", + "ket1_mean = np.mean(ket_func1, axis=0)\n", + "ket1_std = np.std(ket_func1, axis=0)\n", + "smooth_path = ket1_mean\n", + "#path_deviation = 2 * ket1_std\n", + "under_line = (smooth_path- ket1_std)\n", + "over_line = (smooth_path +ket1_std)\n", + "plt.figure(figsize = [10,5])\n", + "plt.plot(ket1_mean, \"blue\")\n", + "plt.fill_between(range(120), under_line, over_line, color='b', alpha=.1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# mean and std - plot timeseries\n", + "ket2_mean = np.mean(ket_func2, axis=0)\n", + "ket2_std = np.std(ket_func2, axis=0)\n", + "smooth_path = ket2_mean\n", + "#path_deviation = 2 * ket1_std\n", + "under_line2 = (smooth_path- ket2_std)\n", + "over_line2 = (smooth_path+ket2_std)\n", + "plt.figure(figsize = [10,5])\n", + "plt.plot(ket2_mean, \"blue\")\n", + "plt.fill_between(range(120), under_line2, over_line2, color='b', alpha=.1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.figure(figsize = [10,5])\n", + "plt.plot(ket1_mean, \"blue\")\n", + "plt.fill_between(range(120), under_line, over_line, color='b', alpha=.1)\n", + "plt.plot(ket2_mean, \"red\")\n", + "plt.fill_between(range(120), under_line2, over_line2, color='r', alpha=.1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Calculate correlation between first and seond session in this timecourse. \n", + "cor_ket = []\n", + "for i in range(len(ket_func1)):\n", + " cor = scipy.stats.pearsonr(ket_func1[i], ket_func2[i])#, rowvar=False)\n", + " cor_ket.append(cor)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "np.array(cor_ket).shape\n", + "np.mean(np.array(cor_ket)[:,0])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_amg', mid_func1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_amg', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_series(mid_func1, mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Calculate correlation between first and seond session in this timecourse. \n", + "cor_mid = []\n", + "for i in range(len(mid_func1)):\n", + " cor = scipy.stats.pearsonr(mid_func1[i], mid_func2[i])#, rowvar=False)\n", + " cor_mid.append(cor)\n", + "np.mean(np.array(cor_mid)[:,0])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# removing one subject that has problems in data in session 2 (1351)\n", + "np.array(mid_func2).shape\n", + "del mid_func2[2]\n", + "del mid_func1[2]\n", + "\n", + "##\n", + "del mid_func1[4]\n", + "del mid_func2[4]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## generating boxplot to show the activation around the peak (3-15 sec)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# before that, lets see where are the global maximums of each subject (location = second in the script)\n", + "ket1=[]\n", + "for mat in ket_func1:\n", + " print(np.argmax(mat))\n", + " ket1.append(np.argmax(mat))\n", + "ket2 = []\n", + "for mat in ket_func2:\n", + " print(np.argmax(mat))\n", + " ket2.append(np.argmax(mat))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid1 = []\n", + "for mat in mid_func1:\n", + " \n", + " mid1.append(np.argmax(mat))\n", + "mid2 = []\n", + "for mat in mid_func2:\n", + " print(np.argmax(mat))\n", + " mid2.append(np.argmax(mat))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# lets plot the locations of maximums for subject\n", + "plt.figure(figsize = [10,5])\n", + "plt.scatter(ket_list + mid_list,ket1 + mid1, color = \"blue\", alpha = 0.6)\n", + "plt.scatter(ket_list + mid_list , ket2 + mid2 , color = \"red\", alpha = 0.3)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# boxplot on the first part of script\n", + "#ket1_mean = np.mean(ket_func1, axis=0)\n", + "mid1_mean = np.mean(mid_func1[5:20], axis=1)\n", + "mid2_mean = np.mean(mid_func2[5:20], axis=1)\n", + "ket1_mean = np.mean(ket_func1[5:20], axis=1)\n", + "ket2_mean = np.mean(ket_func2[5:20], axis=1)\n", + "plt.figure(figsize = [10,5])\n", + "plt.boxplot([ket1_mean, ket2_mean, mid1_mean, mid2_mean])\n", + "#plt.boxplot([ket1_mean[0:15], ket2_mean[0:15]])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# now lets built it around individual global maximum\n", + "def maxVec(funcArr):\n", + " vec = []\n", + " for mat in funcArr:\n", + " vec.append(np.argmax(mat))\n", + " maxi = []\n", + " for i, x in enumerate(vec):\n", + " maxi.append(funcArr[i][x])\n", + " return maxi" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket1_max = maxVec(ket_func1)\n", + "ket2_max = maxVec(ket_func2)\n", + "mid1_max = maxVec(mid_func1)\n", + "mid2_max = maxVec(mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid1_max" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.figure(figsize = [10,5])\n", + "labels = ['','Ket_ses1', 'Ket_ses2', 'Mid_ses1', 'Mid_ses2']\n", + "x_pos = np.arange(len(labels))\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "plt.xticks(x_pos, labels)\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Hippocampus" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_hippo', ket_func1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_hippo', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_hippo', mid_func1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_hippo', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_series(ket_func1, ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_series(mid_func1, mid_func2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## vmPFC" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/binConjunc_PvNxDECxRECxMONxPRI_vmpfc.nii.gz'\n", + "#mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_vmPFC', ket_func1)\n", + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_vmPFC', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_vmPFC', mid_func1)\n", + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_vmPFC', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_series(mid_func1, mid_func2)\n", + "plot_series(ket_func1, ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket1_max = maxVec(ket_func1)\n", + "ket2_max = maxVec(ket_func2)\n", + "mid1_max = maxVec(mid_func1)\n", + "mid2_max = maxVec(mid_func2)\n", + "plt.figure(figsize = [10,5])\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Striatum" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/binConjunc_PvNxDECxRECxMONxPRI_striatum.nii.gz'\n", + "#mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_striatum', ket_func1)\n", + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_striatum', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_striatum', mid_func1)\n", + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_striatum', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_series(mid_func1, mid_func2)\n", + "plot_series(ket_func1, ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket1_max = maxVec(ket_func1)\n", + "ket2_max = maxVec(ket_func2)\n", + "mid1_max = maxVec(mid_func1)\n", + "mid2_max = maxVec(mid_func2)\n", + "plt.figure(figsize = [10,5])\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## vACC" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/ventral anterior_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=4\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_vACC', ket_func1)\n", + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_vACC', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_vACC', mid_func1)\n", + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_vACC', mid_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for i in range(len(mid_func1)):\n", + " plt.plot(mid_func1[i]) \n", + " plt.plot(mid_func2[i]) \n", + " plt.show()\n", + "#plot_series(ket_func1, ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.plot(ket_func1[0])\n", + "plt.plot(ket_func1[1])" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " T test for ketamine group diff Ttest_relResult(statistic=1.5433996488468762, pvalue=0.15376419602078736)\n", + "T test for midazolam group Ttest_relResult(statistic=0.7009216115690157, pvalue=0.501070531766361)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "ket1_max = maxVec(ket_func1)\n", + "ket2_max = maxVec(ket_func2)\n", + "mid1_max = maxVec(mid_func1)\n", + "mid2_max = maxVec(mid_func2)\n", + "\n", + "plt.figure(figsize = [10,5])\n", + "labels = ['','Ket_ses1', 'Ket_ses2', 'Mid_ses1', 'Mid_ses2']\n", + "x_pos = np.arange(len(labels))\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "plt.xticks(x_pos, labels)\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## dACC" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/dacc_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=4\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_dACC', ket_func1)\n", + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_dACC', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1253/ses-1/func/sub-1253_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1263/ses-1/func/sub-1263_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. 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Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1464/ses-2/func/sub-1464_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1499/ses-2/func/sub-1499_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/rostral anterior_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=2\", a=mask_file)\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "\n", + "ket_func1 = []\n", + "for sub in ket_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('ket_func1_rACC', ket_func1)\n", + "ket_func2 = []\n", + "for sub in ket_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " ket_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('ket_func2_rACC', ket_func2)" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. 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Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1403/ses-2/func/sub-1403_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1468/ses-2/func/sub-1468_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/input_data/base_masker.py:217: UserWarning: [NiftiMasker.fit] Generation of a mask has been requested (y != None) while a mask has been provided at masker creation. Given mask will be used.\n", + " ' will be used.' % self.__class__.__name__)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1480/ses-2/func/sub-1480_ses-2_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz')\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "mid_func1 = []\n", + "for sub in mid_list:\n", + " timeSer1= generate_timeSeries(sub, '1',mask_file)\n", + " timeSer1mean = np.mean(timeSer1, axis = 1) # average across voxels\n", + " time1 = pd.read_csv(events_file.format(sub=sub, ses='1'), sep='\\t')\n", + " t1 = int(round(time1.onset[time1.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func1.append(timeSer1mean[t1:t1+120])\n", + "np.save('mid_func1_rACC', mid_func1)\n", + "mid_func2 = []\n", + "for sub in mid_list:\n", + " timeSer2= generate_timeSeries(sub, '2',mask_file)\n", + " timeSer2mean = np.mean(timeSer2, axis = 1) # average across voxels\n", + " time2 = pd.read_csv(events_file.format(sub=sub, ses='2'), sep='\\t')\n", + " t2 = int(round(time2.onset[time2.trial_type_30 =='trauma1_0'])) # must be integer\n", + " mid_func2.append(timeSer2mean[t2:t2+120])\n", + "np.save('mid_func2_rACC', mid_func2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Compare timecourse of different regions" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [], + "source": [ + "vmPFC = np.load('ket_func1_vmPFC.npy')\n", + "amygdala = np.load('ket_func1_amg.npy')\n", + "hippo = np.load('ket_func1_hippo.npy')\n", + "vACC = np.load('ket_func1_vACC.npy')\n", + "dACC = np.load('ket_func2_dACC.npy')" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "plot_series(hippo,dACC)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for i,x in enumerate(ket_list):\n", + " plt.plot(hippo[i])\n", + " plt.plot(vmPFC[i], color = \"red\")\n", + " print(np.corrcoef(hippo[i],vmPFC[i]))\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Midazolam\n", + "vmPFC_mid = np.load('mid_func1_vmPFC.npy')\n", + "amygdala_mid = np.load('mid_func1_amg.npy')\n", + "hippo_mid = np.load('mid_func1_hippo.npy')\n", + "vACC_mid = np.load('mid_func1_vACC.npy')\n", + "for i,x in enumerate(mid_list):\n", + " plt.plot(hippo_mid[i])\n", + " plt.plot(vmPFC_mid[i], color = \"red\")\n", + " print(np.corrcoef(hippo_mid[i],vmPFC_mid[i]))\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [], + "source": [ + "## Build a function that takes group, regions and plot timelines + correlations\n", + "def timeCorr(group, region1, region2, session1, session2):\n", + " region1_mat = np.load('%s_func%s_%s.npy' %(group, session1, region1))\n", + " region2_mat = np.load('%s_func%s_%s.npy' %(group, session2, region2))\n", + " if group=='ket':\n", + " group_list = ket_list\n", + " elif group=='mid':\n", + " group_list = mid_list \n", + " for i,x in enumerate(group_list):\n", + " plt.plot(region1_mat[i])\n", + " plt.plot(region2_mat[i], color = \"red\")\n", + " print(scipy.stats.pearsonr(region1_mat[i],region2_mat[i]))\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(0.4480781783740552, 2.869739194878977e-07)\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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AKXROOAm/5Cn8ecNJ+Eui8Dnh2311nj2dw/GxEhTdwM41aWztT7Zn6axbZ9cXOAl/0yb6vXUrcOIEYMwMCPO+Te1aOlzhxxzJCKlo0KpB8bCA8Ah/cTE8XYFcligHXxBQrKoQGeEf711vzafFVVcBY2OQp/JIs8rDuhBFu/LTqfBNEzh6FFL/agCA7Cn8+aOW8ItFmh7UQXAPH7Dz0nkgf0NPDHvP5HCI+fdXrknj8oEkzubE1tQ2J/zBQfr73DmydPr77YrMrVtJXIyMzPh3XtHdrqVjK3zb0umKhVwrGQ8LAFmmH4/wFw9TogKjwubZgnKNy2GydI5l12Mkz4Kra9YAAIIjw+iKzUL4kmQTvlPhDw8DpRJKO64CAMiewp8fZJkC305LB2hpeE07qNRR+NzDf/3OAVyYquBnR8aQjASwvieGyweSMEzg5HiTF3jDoP45g4OUgZRI2Ap/82Z7u61b6ffx4zOewgratkn4Zcc8W45sIoTJsjyv3H4PNehwHx3AI3wXDMPEtKRAkKswWWlzsapals7x3vUY5QqfEX5ofNSydOpCksjzDwTcCp/ZOdLOXQAApewp/HmB2zdOhe+8v0OoqjqCfhpOb1s6pHxfv4MGsTz60jh2rk5DEARcPkCKvOnA7fg4ZXetW0f1BTw1swXC54Tdvodvz7Pl6EmEIGuGNevWwwLAI/zFRaGiwjCBkK7CCBHhl6oaxHAMZjKJ0VQvRrnCX0t594mJsbktnUQCyGbdCp8RvrZrNwBAKbWXI+2BgQdoeR4+V/gdDtxWVQPZBB0rZW7pSAqiQT92r81Yx8aVa2l/1nfHEAr4mvfxeUrmunX0e/164NgxUv2XXWZvt2YNEIvVV/jz9vDtebYcPXF6z7ny0rRrflliuRC+IAhvEAThmCAIJwVB+PM6j/+eIAgTgiC8wH7etxCvu9DgQyzCmgqNEX6xouKbe94O4d570ZeK2Ap/NXnv6ekJdM2l8GMxoK9vpsLPZCBs3AAA0Ly0zPmBE/sSKPzepC0OAGBaUtEVo8ytV2zoBgDsXEOEH/D7sKUv0bzCryX8wUE72O9U+D4fsGVLXcIX52npcIUfr1H4ADBZ7vDgl5WE5UD4giD4AXwewBsBbAdwpyAI2+ts+m3TNHezn3+b7+t2AlOc8HUVaoD1C6lqGLlsG/D2t2NVOmoTfjQKo6sbA+UcMo08fFWlCtp4HOjtdSv8I0eA7dsRSSYAeIQ/b/Be+LWE33GFryMRDiAS9KHkSMtMMxGwZ3MPAGAXU/gAcHl/svnUTGeVLWBn6gBuwgfI1qlH+FYefostHRisAebnTtNK9YUXrFWNp/AXEMuB8AFcD+CkaZqnTdNUAHwLwFsW4HkXHVMiHbxhTYESpBO2WFGtZlGrMxGMOPqjqAOrMFCahfB5U7RGCn/bNkTSRPi65Fk680KtwmeWztd/Uj83faFQ1XREg34kI0Gr8CovKVYg/903rMd//P5NWN8Tt/7n8oEkLharKDST5XLhAqX1dtNKwSJ+wG3pAET4p0+T0HCAK/xqm5aOpGgI+ASEnnkayOWA++6zFH7HRzuuJHDCT6dn324eWAjCXwPAOWxziN1Xi7cJgnBAEITvCIKwrt4TCYLwAUEQ9gmCsG+iNmd9EZBzKHzFz6f6aBbhD6SiGM1XrcyEat8A+su5xh4+J/FYzK3wczm6vW0bImkK4hmiR/htgVs2DSydixfGOvryFUVHJOhHMhywmonlK6olAkIBn2XrcFyxihTcoZEm7Kbz5+2ALWATfleXfRHg2LqV0lDPnHHdLS1ApW0s5Idw5Ajd8Z3voJu1SPYUvgM/+xnwmc+0///LROELde6rzdX6AYANpmleBeBhAPfXeyLTNL9smuZ1pmle19vbuwC71hqmmB8Z0lVU/dzSUa1WCaszEVRU3SopL2f7MVDKNfbwOeHH46Twi0VKH2S99LF7N6IpUviG5PXSaRn3308X0scem0n47KSJlOe2TopVFQ8emJm/3gyqqoFw0IdkJGC1SM5LyqyZW9cMZuD3CXimme6VPAefg1s6tXYO0DBTZ76tFSRFI//+0CG68AwPI7zvOSQjAc/Dd+JLXwI+9rH2/3+ZEP4QAKdiXwvAdfaYppkzTZNLga8AuHYBXnfBkRMVJMIBxAwVks/u+c1Huq1KU3omt3UK3X3IinlkGiXpOC0dfgGbmCAlEIkAe/bAHw5BF3xe87RWUSoBH/kI2Rcf/jC1CA4G7armYBDVcBRhqTRnrvi3f3kBf/SN/RgvVVveDbnG0jFNk6qvZ8ncSkaC2LU2jadPTc79ArWEv3o1tfeYjfCPuYesSPO0dLjCx+HDwJvfDIRCwH/8B7KJsGfpODE0RCvOUouV1BzFIqVvsxqgTmAhCP85AFsEQdgoCEIIwLsAPODcQBCEVY4/fwPAUVyCmJYUdMdDiBgaKoLd85tbOqsy9EXwPue5TC98MNFVaKDUnJZOXx/dHh8HHnoIeOUr6YsVBMjBEEyP8FvDJz8JjI0Bf/zHwP79wNe+ZvfCZyhH4khWRcja7MHKUxNUA9GUp14Dy9KJBFCqaijLGjTDnD1zC8DNl2VxYKgw+yBwTQNGR92EHwgAf/ZnwO/+7sztu7spqFqj8KV5VtqKioZ+vULFgjffTEOAvvMdZKMBqCOjwAc+YDdzW8ngA+bbHTTP2yoI9UyThcG8Cd80TQ3AHwH4KYjI/900zcOCIPytIAi/wTb7X4IgHBYE4UUA/wvA7833dTuBKZEIP6qrKAsB6AYNJecj3Vax9sfDeVKCE6ksACAx2cAndlo6XOHv308B29e9ztpMDoYheEHb5nHuHHD33dQl8u67gWuvJWLkdg5DORJHUhatLJVGOD1JK7F2moFVNQMRZumUqppVdJWerfoawM2be6AbJn55ZqrxRiMjVGnrDNQCdLF7wxvq/0+dTB1u6WiGCbXV4Sug5mubcyxMt2MH8I53AENDuP3ok/irf/x96tL5yCMtP+/LCqoKXLxIt50Da1pBh/voAEBg7k3mhmmaPwLwo5r7Puq4/RcA/mIhXquTyJUVrEpHENYUlOG3PNkkU/j9yQjiIT9OsqKZ0Til3PlGG/i/TkuHf5Hf+Ab9vv12azM1GIav2rqdsGLxV39Feeef+AT9/qd/Al79arvoiqEQjiMli5AUHT2zPN0Zi/Bba/er6gZ0w0Q06EciTJYOJ/y5FP41g10IB3x4+mQOr93WX38jThxr19Z/vB62biXLkEE3TFRVA8lwACVZQ0XVEfS3pvNERcNlY2fpjx07aCURDOIDn/9LSCFmP6x0wTI6ag+guYQJ36u0dYAr/KCuomT6LcWXYkFbn0/AtlUpHBml4MqFGCOY4eH6T1ibpQNQgLG/H7jySmszJRyBUPUsnabx8MPAO99pWx233kqD4F/9atdmxRARfnkWhV+qqpgoyex2a4TPLRJu6YiKjkmW2tswVZchEvTjug1d+MVsPn5t0VUz2LqVVgasVQe3c7KsOKwdH7+i6Fh/8SytVNevp7TBt74VYqYHv/2u/0MbrfS5zE4bxyP8Sx+maRLhJ0IIqgqKCFhNsFKOANz21SkcHS3BMEwM+2NQAqG5CT8ep5MkGCQVcPvtLp9OC4Xhlz2F3xRMkwbJrKnJ/P3yl8nqcGAiksK6/BgqhcYN1Li6BzC7n14HvDdNmBE+QN1WAczeUI/h5suyeOliyZqFPAOcRFolfIBaJcNubZxlefPt+PiiomHNyGlg+3ZaUQHA/ffjv/7zKbwwsBWm3+8pfI/wlxfKsgZFN9ATC8KvKpD9QWsGKA/aAsD2VSmUZQ1D0xXkKxrymWxjwndaOoJgq3yHfw8AWjgCv+zlMzeFQoFyzbPZWTdTNAPf2PU6dFVL6PryFxtu5yT8Vic4yaxyNRr0W8fIhWk6ZtLR2S0dANizmd5Dw/TMCxeo/XErJMAvDuyY5K2Ree+bdghfUnQMDJ0iO4cjEkGmhwKMRizuKXxO+Js3e4S/HMDbKvRE/PAZBuRAEGcZGfCgLUAKHwCOjBaQrygoZfubs3QAm/Bvu821mRGOIKh4Cr8psDGRmKNOo6Lo2Ld2Bx7afAPWfuVz9v/V4PSECEEA/D6hZYVvWzo+S+HzkYZzWToAsHN1CslwoLGtU5uS2Qx4Nhgr8uPTrnhlbDsN1ML5aSSnJ92ED/siokciHuEPDdF5ftVVHuEvB/B84myAVJviD+LM5EyFv7U/CZ8AHBkpIi+pkHoH5iZ8nhu+YQNwzTXAqlWuzYxIBAHFU/hNgVcrz6HwJZWU7T++6j0ISCLw939fd7szkyLWdkWRYlk2rYBbOpGAHwmL8CtIhANNBUYDfh+u39iNZxtl6gwNtRawBdz1HrAzdHjvm1YVvqIZ2DRxjv6oIXxuE6mRmGfp8O9q3Toi/HbmBDDCf+zYOB452pkKcY/wGaYZ4XczMS8HQjibYwrfQfiRoB+X9SZwYLiAUlWD0r+Kvux6X7Ao2nYOQOlrDz44YzMjEkXI8/CbA1fqcxE+U7Ins4M4+evvAL7wBeozU4MzkyI2ZhOuXjjNgk+7iob8VibX+SmpKXXPcfVgBqcnxPopoe0o/HicjjnWt8kK2jJybrUnfkXRsXXyPP2xc6frsR52EZFDYU/hOwlfFFvv0qppdNFMpfCVJ07j84+d7MhueoTPwBV+j49OYtlvWzpcvXFsX53Cc0yVGatWA9Wq3a3RCd4amaO3d4a6BwAzGkVY9aYHNYUmCd9pXTz77j+gPOkf/MC1jWmaOD1RxqZsHMlIoOW0zHqWTsHRR6cZ7FpHtQMHh2oIQlGosKxVwgdcfZt44zROzhWltTx8SdWwZfIclHhyxmojEw3CJwDVUMRT+END9F3x76tVW4dX56ZSGC/J6E91ptrWI3wG7uFn/MzSCQSRExUkwwH4fe7Kt+2rUvakn7UsW6SerVNL+I0QjSGsKa75qB4aoEWFDwDj6V5qRzA5iZF8BT89TAUyEyUZoqJjU2+cFU61maUTsLN0gLlz8J24ag0R/gsXato4j4wApolPHS5b+9s0ensthS/O09KRFB2XT5xDedOWGRWgPp+A7ngYUmCFK3xdp++LK3ygdcJ39NEZL1bRx9JoFxoe4TNMiQrCAR+iBp30fua7JyMza9N44BYA/OuY6qlH+KJIS+w5IESjiGiytfz2MAsmJ2nA/Byfq/OzLKsmFQtNTuL+Z87ig197HodHClaF7cZsHKlIsG0PPxryu2y/WSeg1SAdC2JTNo4XawmfEcYBIYXDwy3aA319tsJnhN/TZlpmtSRh9+hxlK66uu7j2UQIoj+8shX+2BiR/gIQvhJLoFjV0Ocp/M4iV1bQEw9BYOmR4TgRfqrOybttlU34kfWs7P3IEeCf/xn44AfJjwOaVvhCLIqIprhUqYcGmJwkdT9HvxGnpSMpGv3P5CTyIl3QP/vICSslc2M2zjz8NoO2QT/CAR8CbCXYisIHyNZ5cag+4Y8ke1GotNjywWHp8GMqG68pvDIM4F3vAh5/fNan8j33S0Q0BeItt9Z9vCcRQskfWtkKn6dkrl1Llq3f3zrhs+3zASL6Xk/hdxZToozuRIjaFwMIJ0lBOpUbRzYRtpZc8Y3siv7hDwN/8idUAHSSBVyaJHxfLIagoUOSvEydOTExMWdKJmATnd8nkP3GCJ+T508Pj+FHB0cRDviwOh0lD79FYuUWXCTggyAI1mqwFQ8foGlYY0UZFwuOwD0jgIvJnpZjC5alY5oQZQ3hgA/xMM2jtRR+Lgd8+9vAD38461NFn3wcuuCDcvMtdR/vjodR8IVWtsJ3Er7fT6Rfj/C/+c0ZnUzx3e8CN90E/PqvA34/xjKUVutZOh0GtVUIUwAWQDRJRO3MwXeC2zqZdAJ473uBu+4CPv1pepA3UWrS0vHH6bUqxTbbqq4kcIU/ByRGbD3xEA0AYYRfrKrY2p9AMhzAkycmsTEbh88nIBUJoKxoMIzmA+dOSwewey7N1gu/Hnjg1uXjDw1BS6YghmOtK/y+PjqORREi62Uf8PsQ8vtswufprSOzzwFIPfMkDvVfhnBvd93He+Ih5IXgilP4D7w4gu+/wGxcJ+EDZOvUdsw8fx747d8G/rYCajEAACAASURBVOVf3Pd/5CO07Sc+AZw4gQt95Bj0JT1Lp6PIiQq6Y0FL4cdSRNTJOgofoOZXyXCAVN099wD33mtX0I6xHNomFX6AEb5SLM/zXawANEn4Febh9ybDVG2azQK5HAoVFeu6Yrjrlo0AyM4ByLozTaDcQhyl4sjDB+x4TzNtFZzYtiqFoF9w2zoXLkDqXw0AMwhf1nTos12Y+ApofBySrFvqPhL02VYXH7c5G+FLEjIHfoVn1l9F/fDrIJsIoSiEYEoSXryQxzd/eb7x872M8H9/dgz3/eIs/TE0RHGlHtaij+fiO8GbJjrHnPK/3/Y24M//HNi4EeNFEpz9KU/hdxTTNQo/nuKWTn2F/4FXbsKP//jX4HNm8AwM0G+u8JslfGYfVYtNqqQPfhD4+Meb2/blhgaE/6fffgF/+u8vWH9LjnREyWHpFCsKUtEg/seejeiJh3DVWlLXnKxb8fGrqoGQ32cdA+1aOpGgH9tWpfDCeTfhl7PURbPWavr1zz6FLz0+S/95R7VtWdYQD9F+RUN+Ow+fK/zR0cbP8/TT8GkqfjF4FWKh+udBTyIMKRiGoCh4/z178bEHDr/s04tzZRlnc5LVWsPKwedxpdriK9OkeQ2A/bkDxDWlksuiHC/JCPiEluNAzcIjfNDSXFR0ymSwCJ9GD9YL2gJ0kq7tqiHzri5qkNaipRNM0DZqeSbhHx4pzJwb+sgjwPe+N+fzvuygaVTvUIfwT02KOD5mW2IVRUc4QPnxoqyR+lJVaPkC0tEg0rEgnvjfr8YHX7kJgL2SayU1s6rqiATtUygRbs/SAYBdazM4OFywlfvQEPJZEhBOha8bJk5NlHFqfJbVoKPaVlJ0S51Hg37b0mlG4T/6KHR/APvWbm+o8HviIVSCpEalQgmKZrQec1hm2M8uzFWNfZYXLrhrFNatIx7JsR5J+/dTUkcg4CZ8fttB+GNFGb3JsFtILiA8woedg98dt4O2qQwj/AaWTl0IArU+blHhhxjhK6WZhP+ee3+JL/y8Rs3l8xT8MVZY3v4Ua0FQh/Blx6xhABbRxUN+W+EDCOanrVVbPByYoc5baaBGhG8TIX/e2cYbNsKudRmUZQ2nJ8p0DI6PY6qLlLqT8AsVFaY50+ZxwWHpcA8fIJFiWTqcbIpFq5XyDDz6KC5ecRWkUBTRYAPCT4RRCZLffOtaOtZ5u+mXCz7x46P49322RbP/AhVZzlD4HLWpmV/7Go2F/M3fnJPwx0udy8EHPMIHUEP4TOGnMkkA9fPwZ8XAABG+aTZP+Mw+0moCX4ZhIicqGCs6sjdMk8q2KxWa/LSSMEvRlawZLhIUFQ2xUACxEFP47H+6xELdVVuqbYVvE6Ht4beu8HeuoSSAoxdLVsBvPE1EIGuGZcXwY7WW8EtV1SZzh8IXayydGQofqG/rFArAvn04c+UNiAR9DRXnQDpiKfy7dtMF6uVE+BcLVXz5idP4zMMnLKvqV+dI4cuaTqJreLgx4WsaZee86U3A5ZfTMcyFGid8bsGBPrveDgVsAY/wAQBTZRlJWUSPQ+H39dIJ2Ndq8IQTvizTF9uEpRNmCl8ru1PbREWDacKaogSAiJ7n+R+9JEcDdw6zNE6TVR3Fqmpl2VQUHdGQH/GwH6Kiw2QBta5KsS7ht+vhO5VvbzKMcMDX0AacDb2sEnaqLFuEP5qylR/vtZOX6hP+++7fh49+/xD94einI8o6YmHb0pnh4QMzbZ1KBfjrvwYMA8e2X9vQvweANZkoPvBGGubT46PPbqJRf/9liAcPjMA0geF8BQeGyHLjwXVZNehzVFU34fORlB/8ICVyjI0Bv/M7dCHWdbsNS12FL7fOOS1gZRP+6CjwiU/g6jfuwQufuRPZs8cthb9pXRb/9Qc349atfXM8SQ0GBugLrm2NPAsCnPBrcpl5p8N8RbHvzDsCe0eOtLZvyx2ztEaWNcOVZcMtnViIZhMrGUor7K4U61bCtuPhV2o8/N+9eQP+8w9untGKoxmko0EIAjAlqZYVMJywBzPywC1X+LXN1s7lJJzLOY4fVnwlKhoSzNKZ4eHzC6dT4T/2GDVJ+9zngLvuwpEtuxvaORxXbKJYQzfos598GSn8HxwYxabeOAI+AT86OIpjF0uQFB1rMlHy8Hn6pXMgT38/Ze3deiutwrduBe64Y0Yn01rCVzQDU6LiWTodwx13AH/5l6imMhBME90P/9gifITDuHqwq/XgycAAnUy8GVIzvXTYNqboJnyuNqdFx8nt7MK30hT+LJYOV64FthqqKDqiQfLwAUBK0TjKrkqpAeEzD78lha8j7PLwg9ixOt30/zsR8PuQjgZJwTPCPxftthI/uKKfbqDwpyUFU5JDGLD2CpKsWwo9Eqrx8Hftottc4ZsmjY4EgEcfBe69F5KGhgFbC2wVm9BkBP3Cy0bhn8uJePFCHv/tunW4ZUsWPzw4iufPkzq/cVMPVN2EfqEmB5/jrrvIyjl1iuJt4fBMwh8fp0BuhjLF+OSzTjVOA1Y64Q8PA+9/Px74l3/HoYHLEHvsEbJiAgGqmGsH/f20bDvP8pGbsHR4v3yjAeHnnScyJ3yf79Ij/Gq1s/vECb9n5khyWSNflBOhpGqk8Jm6LYdjMAIBsnTqBOIjQT9CAV/9NsUNUNWMOdVvK+iKhUjBnz4NdHVh0gyin/m5PJg8zS5oVdUgDxl0cZM1w32c9PbCGBuHohvWRY8sHYd/vGULEInYhH/xIn3Gf/In1nxgZ5ZPQzDB4qtWkE2EXzYe/oMHaOXzpl2rcceVqzA0XcHX955DTzyELf2U1KHzwGztyM16qKfwHW1CeKzOU/idQqEAdHejXNXw+MZr4X92L9kxkXlcYXkuPu+93lS3TCJ8s+IeZM7tBVHRoTBCsyydK68kcr2Ucp7vvx+4+urOVV1OTtLIv7D7hNB0Axrz7rn1QUQVsAKWkmpATnWhWyoi3SBPvtUhKFXFbenMiaEhO1WvDrpiQRTKVZqZ8OpXo1hVsbaLjg1L4Ys2qdeq/mlJtXPgHQ3U4rWWjq7TfvT1AatX24TPLcJt26zX4LGQWcFFjSi+rAj/gRdGcN36LqzJRPG67f0I+AS8dLGEqwe7EAnQ965fGCZx2N8/9xPy4CwPmE9MuAK24+xz61SVLbCSCb9apZ7j6TRERcPeLddC0HXgxz+eQSgtYT6EL9USvk0+lo/PFf5NNxH5j3VmMk5bGBujFdJUgwlO80WDoiuu7gHb265wD58FLEVFQyWdYQq/fhCy1QZqVc2dpTMnfuu3gD/904YPd8VCWHPgOVLa73oXSlVtBuFPOQi/WEP4umHallRvL4QJ6qfDK22j3NLJ5Ugo9Pa6CZ+vzhyETyulOTLV+DEuiuhNhhsPZV9GOHaxhGNjJbx5F1U7Z2Ihawbx1YMZy8ozh4fonG/GEeDHrlPh1wRsgTYSRVrAyiV8rpTTaZRlDSc37aR5kqOjC6PwT7Hc+RYsHaHqJnwetAUcmTpOwgcuLVuHB515b++FBl8C18BJ+AWXwvdbAUtJ1iEmM+iuFK37atFqA7Wqqrdm6Vy8CJw92/DhrngIN/7yISAeh/7GO1CWNau4z1bz7px8wI5bAA77r7cXgiwjrlRsD58pfJOLBK7wedD26FEgnXYN6ZFaUfiShN6XicLfe5pWYrdvt5X7m66iz+UVG7qtlZ0wMtKcnQNQLn463ZDwJ4pVCAIVs3UKK5fwOXGm0xBlDZFYBHjta+m+xVb4wSAMwTeD8J0ZIxbh8wvVjTfS7yUi/FxZxqHaPu2c8Fsd79YsGih859g+ToJkRQQs/1lUNBTjGWSrRQgNWiunWhxzWFFaVPii6E6HrEE2LODWQ08Ab3kLyj466bviIcRCfpea5558vYuAdZtZBc4LHL84qRcZ4dcq/CNHSN07Pp+KoiM213t0WDq9yTByotJSEzoL1erc2ywScqJCdZSOAOpvXbMWX3/fDXjFhi6EWf8kXyuED7haV9dT+D3xMAJNzENuFx7hZzJ2ccob3kD3zUfhJxJ0Apw5Q383Q/iCADUUhq/mgC877AW+bEehQMvHLVvIz14iwv/S46fw7n971n1npxX+5GTDlEyOYkWDphtQdINV2hLZibKGfCyFrkrjjqTJVj18zUC4FQ9/DsLfefQ5ZColyG97h2VNJSMBpKNBl4e/gTV8q/Xw+eMArM8pK+YdrRVoX5WRGoVfLlNW2dGjLjsHoM9tzqBtJEIXCUlCNhGCbpiufWoKp0/T8fzCC3NvuwjISwrS0aArxdbvE7BncxaCIFgKP3CxTcKXZTqXXW0Vqh1rmsbhEX46jVJVo7m1r3893Tcfwgfs4iugOUsHgBqOwF+j8J0pggWnpZNO0wm2bduS5eJPSyoKFdU9pWsxCL+upeNW+Lw1stvD1zEVSSItFRsGulshfMMwobSSpaNpdJLnchQ0rYMdT/wYhXAcuT23WoSfigTdhC8p2NDDCF9yF2PxxwFYRNJdKdhBW0bc2phD4XP75tAhisFs3+7ap4pKK6VZIQgkbETRqhJtOTXz9Gn6jI4fb+3/OoQpUZlZMT05CbzvfUC5jHDAj6hShb9YbI3w+/ooaMszzmqCtp3M0AFWMuE7PHyrOGX9euCKK5pT5bPBGbFv8rm0cAQB2a3wS1XNyhm3TuR8nggfIMJfIoXPR+dNlhxKrpOWTqVCCrmupeP28HmuedSh8CVZw0QkCb+hN9y/ZCTYdFomb5zVtKXDM5dMs35Qu1rFusd/ih9fvgdTmmClYaaiAaQiRPi6YSJfUbG+h/v6dqomd2FqLZ0eseDqpQMAxtg4kXRPDyl8gPLuAZfCV3UDqm7OrfABOs4lyZrU1LKPz+tWeBXqEiMvqTPbXD/xBLVCf/xxRII+DJRZxlU7Cr9RlW0HM3SAlUz4Lg9ft04K3H8/8KlPze+5uY8PNE34ejiCgCK7WsuWZRX9qTCCfsE+kQsFq1AD27ZRwK2WwGrSOzsBPsTdpeQ6qfB5OmODtgocxapqtUaOhfyWAhcVHeMh6o9kqasapCJBSIoOTZ+7KZ1z2lVTcKaq1rN1nnsOAbGMh7bcgGlJcSn8VDSIYlWzGqf1JsOIh/wu1T+QisAnzLR0eioFVx4+AJgTE0T2fr9N+I88Qr+dGTqOz3FOxOOWhw+0Qfj8mMnnZ99ukVBX4fPv8MgRhAN+DJTaJPzJSTs1k31PumEiV+5sWwXAI3wgQ10KE2zpj+uvtwOi7YITvs/XdADYiEQQUmUoDrIpVTUkI0FkYiEUnGmZXOHz5ffhw/YTDQ3RwO4f/GB+72EOSFzh1yP8Tij8ORqnAURMTpspGqRumLGQH5KsYTQYdz9XDXi1rTM7qhFqp13NibkI/8UXAQCH+i/DtKRa1hK3dIoV1dXkz2nzkBoNIRML2SvBWAxqNIZuqWAVn/F9FZzBQk74Tz9N2WLr11u7VLEIv4kGgkzhZ9mw9JZTM7nCv0QIf1pS0FWbLcO7ih49ikjQh/52Fb6m2WNQ2feQK8swzM4WXQErnfAFAUgkUK5qDVP12gIn/FhszmHbHGYkioiqQJJttVqWNSQjAXTFgnZ7Baelc8019HvfPvuJnnySsh2++935votZwRV+XcLvhMKfpXEaJ9++ZNhl6XBlGgsFICo6hv3NEX4zPn5FbdPSARoSvtHdg7FED6ZFxcrKcQZtuVffFQsh5SJ8BV3xIDKxoKvRnpTqQo9UsLJsuML3TzoKfpJJUueKQt0cHfnk/MLZisJPhAOIBH3tWzqXEOF3NyL8+Sp8wBZp7O+xIn1eneyUCaxkws/ngVQKOgRUVIelsxBwEn6TMCMRRDTFCjgCDoUfDbmzdLils2YN/TzryJbhtx96qKNVuHU9fE5qS6Tw+5IRFCvaDCsiHvZjWlQwFkq4n6sGvIFaMzNk+UWGp+fNiWYU/q5dgCBgWlKsi04yEkAqGkBZ1iwS7YqFLNUPkMLPxELo5q0ZGMqpLvRWi1Y/KH5x8ucc2U6CYKv8mgwdSWlhFcMUviAI6E22kYt/CVk6FUWHKVVwxakD7gdclo6A/nIOSjxJmXnNgl9oDx+mi2sX9XgazpNYWpX2CL8zYNaIyFRMxxR+s4hGEdFkyyoBKA8/EQ4gE7PVnMvSAYAbbgD27rX/fvZZOolHRoCXXprHm5gdXP3lxEVS+NzznEXh96bCKFbUGUQVDwUwWqxiOkotrxt6+NHmFT738Ju2dJxDRmoJX9OAgwfh270LqUiAFH5VRSzkt5qqAcD5Kfp8u+LM5qnaHn5XLOi2dAAUMlmsLdp97/m+hqYmXdkhVqZOnQwdoDWFD1Cr55azdC4hhT8tKXjLkcfx1g/d6T5W+HdYKiE6fhEDpRzEbBMtFZzgF9ojR+hY9hEFHxktwScAW/uTC/AOGsMjfEawC6rweZZOkymZtG0MUVW2rBKAiCcVCaCLn8iGQWTqJPwbb6SUtokJWpbv308l/ACp/A5BlGexdDqh8M+coc9zVoUfhqIbFulx7zke9mM0X0E5FIURCDbsZ9PKEJSqNcB8AYK2J06QDbdrF7rjIUxJKkpV1dofTvhnc/QcTg/fMEwUKuThd9VYOic2X4WNExesFOFo0A+/oSNUyLvrGeZQ+K1k6QBANhF2r/yawSVE+FOigu5KEUJtRpXjOwyfeAkDpRzK2RbbpzsbqDm+g6OjRWzMxpsXEG1iZRN+JmMVNy21wheiMbJ0mHJWNAOyZlgKf1pSYRZZDjm3dABS+ADwy18CBw5Qrvc73wls3twxwtcN01J/ddMyO6HwT50CLrusbkzEaekAwGiespScHv5EWaYCt67uBfHwq+16+LVzTQErYItdu5CJhZCXFBQrmrU/nPjPTIoIBXyIBv0W4RerKgyTer3QxUKxMr32b72Wnpdl4ESDfnRL7LtxKvwGhF9xBL/nhFPhJ+srfE03GlfgLqWlc++99nkEssiiKkuRLjkK9cplinkACL70EvrLORS72yT8mttHRorY3mZr7Vawsgmf9dEBFpjwucJvgfD98SjCmh205fuVjASQiYXoAjDJcpSdCv/aa8kL3LvX9u9vuAG4/Xbg5z+naTwLDGexlaXwDcMuje8k4deBM2gLAKMF2g+nh8/DGUZPz5wefjO5+C1bOpzwBwfrE34gAGzbRqQtKijJqjU5i3f3PJeT0B0LQRAEpKOUQmr7+kHrOOEX4yfja1GOp4GHH7b2tbvCVl9O4rnlFuq+unmza7daTstkF/zeZBhTogK1Jr31bV/8Bf75kRP1/38pFf4Pf0iCiRXETUkKYpzwnVZcuQxs2ABksxAOH0ZfeQr5rhYJPxy2Lhr8OyhIKobzFWxflZrnG5kbC0L4giC8QRCEY4IgnBQE4c/rPB4WBOHb7PFnBUHYsBCvOy+wbBduTSyopRMOUzCmBUvHH4uRh89O1pJVWh+0CkCKF4kovnW8gC/ywebxOE0oevZZ+unvJ1K5/XY6QJ3+/gKBE0E44LOVnDP3f6EtHcMATp+GuWkTHjwwgls/9Ri+8POT1sNc4WcZ4V8scsIPuH7TRtnWFf5f/AXwkY+47rKydFoN2m7YUJ/wt28HwmEr08ap8LmlM1qoWqmC/GLAp1xlYvZxMi2pUHUD56arGLrmJiJ800Q44EOPyAjVqfDf+lZaHYbcWSliq5aOQ+EDQK5sr/5M08SR0SLOTjZonb2UhH+ABWfZBWtadBC+U+GLIp1v27YBP/85AqaB6czMVh9zgn/27PeRURJI21cvA8IXBMEP4PMA3ghgO4A7BUHYXrPZ/wAwbZrmZgCfBvCP833deaNG4fMWsguGrVtdXQfngj/OLB22P5x0EhGydABAnCDv+aFhGQ8fdbRFvuEGUih799JtQaABFj5fR2wd/pkNdsdQqmqksLmdE4ksvMIfHgZkGfeO+vBH39iPszkJh4ft15A1HeGADxlGghcLVYQCPqsPStxBWL56hH/iBPChDyEokO0xw8P/+tftSlQG29Jp8hTiSnH9+vqEz6ZP8Uybeh4+AIvU+X3npjjhh6yLwbSoYGi6As0wUb7lVVSbcfw4BEHAKoURWJ2eRLWwLJ1mFX6lAhgGsokwsuI0clM2WRYqKlTdtMTCDPBjplpd3CZqomh3tmXf0bSkIKoyIVNr6SQSdHFm/5Nrh/D5Z89+W4S/TBT+9QBOmqZ52jRNBcC3ALylZpu3ALif3f4OgNcKjVoWLgZM0/LwedA2GW598PSsePBB4NOfbnrzQCKOoKFDkuhAc6blZVjFX3WCLJ0JfwQjeYeivvFGej8nTtheZCYDvOIVHSF8bjvxEv+cqNiEv2oV3V5IK4mdXI8Zafzdb+7EjtUpK7sKoGHSkaDfUr0XC1WXKo05Vm+B/t6ZhP/AA8BnPwsMD8/sp5PL0cjBmqEuFuG3YulEIhTfmZy0U2YnJiijihF+VzyEiqpjvCRbWUPOCV2c1C3CZ4FcCtoywpcUnJ4g8gq/kfWHYrZOn9w84UutFl4BQKWCvrCAR7/y+wh9+UvWw9z6q6gN4iNOYu1Ut9V6OHLE/i7YdzwtKkgZysz9EkWb8BkmUzOnr82JWsIfKaI3GbZWRp3EQhD+GgAXHH8PsfvqbmOapgagAGDGJyUIwgcEQdgnCMK+iVm6Cs4bkkR+XScVfjZre3VNIJyiXN7CFF3tLUsnHLROZHmSMgZK4TjGilXbI3UEnFy3X/GKjjRX42Q72E2W1WRJdhM+4D5R5gtG+OqGjfjvN65HMhJwFahxhc9JsCRrrpa+cSt464e/t5cyL5wNzHjWjiiiOx5yZx7x7o2NCL8VSycetystuXXhCNgCsL5rSdGtmEIk6EOItcztjrktnbPM0umqsXROT9D+rrt2B9lIjPD7K0UYgo+qsedARdFdK6VZ4eiJ31/KISWLwKnT1sN8uEdDhV8q2VbHYvbTOeDIteeEL6lI6XUIv1ym9+kg/PHkzKyxOVFH4S+GugcWhvDrHQ21ofhmtoFpml82TfM60zSv621CgbSNmuEnwAJ7+G3AxxRSbpwOdnfQlk5kZYoeK4bjMEx7BiauuIKGtwgCkTxHJkMHrDF3b5hWwFdFG7K0z5Nl2SZEnqG0kCrt5EloPj+6L98EgPLqaxV+OOhzTbJy2hBcoaYiQboQG4bbK+aKv1zGuu4YLkw5Vk/791uPOVFVDfgEIOhvcqHqJHzAtnVqCL87bqt5ruwFQbAIvp7C9wm0LX8sLyk4PVlGd5zaLeC224DHHgPuvx9v2/s9TPSvbWpCU1PzbDkcU696pigN1JywawB4cLlSj/BNk47Tdevo78X08Q8etG87LJ2ELrvus247FL7u82Mi3kZmjYPwFc3AyfHSovj3wMIQ/hCAdY6/1wIYabSNIAgBAGkAHZqD1wRqhp8EfALCzeZTdwps6lVukvbNbenQyW2wE6EUJjU1kmeE7/MBe/YAV11FxM+RTtPJtMAzZnkwb7DbQfi1Cn8BfXztxElcSPdjyxpSpbFwwKUUq5qOSICKlHi2ldOG4Ku3dDRo5/E7bR2u8MtlDHbHcH5KspvYzaLwo0F/w2EqMzAb4a9aZd2fcTTsSjouYNzeqfXwh6YrSEeD8PkEK4YxJSo4NSFiE+ubj9tuo2P+934PFwY24DMfurupXZaaGX7C4RiCEh4ZBsAqehkmZlP4okjH6VIQ/oEDlCHF9wNsyEw9D59/h6tWAek08qluVPQ2nGlH0PbEeAmqbi4rhf8cgC2CIGwUBCEE4F0AHqjZ5gEA72G33w7gUdNcwunbtcNPwoHmT9xOgRH+dK5AGRWHXsRHfn4fuq6/GuH7/l/EQn4Y09OQA0Fs20Ck5fLx770X+P733c/JyX+Bg6g8sLye9WWfLDs8/A4ofOX4CZzLrMK2AbLI4iG/tcoAbIUPwFL5ToXPV2+paKApwq+oup19xBW+LFs2kKobyIlK69Ou6hH+vn12TyTA1b8l5QjWcoLvrlH4umFaNlDA70MyEkCeWTqbehkJv/71wKteBdx9Nz7+Z1/A2Z61Te1yRdWaTzvlCl+SgPPnAQChaVvTTbKMnbqEz0l1cJB+LxbhmyYp/Kuvpr+5whfr5OEbhu3hCwJw5ZWYzK6y2mS3hNe8hr6TjRtxZGTxMnQAYN4+hmmamiAIfwTgpwD8AO41TfOwIAh/C2CfaZoPALgHwNcEQTgJUvbvmu/rzgvO4ScXFrhxWrtghC/mS9C/+EW86w//EKrPD184BPznfyLzax+GkptGMRzHa7f148WhAoadhO9syczhJPxWGjzNAW43dcdDSIQDpN60Dil800TgzBmc2/pr+DVG+LFQwGUNVDXd6mmTigYxUhO05T3xGyp8h6UzuJmI68KUhL6ASe0pkkmgVEJ+Yhp/8IOT2HduGopmYEtfCz1UuB3gJPzpaZpn8O53W5t1NVD4nOD547wAq6Lq1gqQP35+SsJkWcamXrZ/mQzVZAAI3fNsU91AAW7pNHluOBQ+zp2juwo24duWTp3XXirCHxuj7/7OO4HnnnMp/IhSQ/g87Zj3zbnnHnztuy9CVtuwS3fvBn7yEwDk30eDfmuoTaexIExnmuaPAPyo5r6POm5XAbxjIV5rQeC0dE5KlxThh1QFxmf/FaOX7cB73v43eGT0B8BDDyHz+hCkiSkUw3Fct74LXbGgS+GfHC+jqurYucbhKXLCX+CsB67S4iE/sgkW5DRqFP5CEX4uh1C5iJGe1daKIh72Q1Q0mKYJQRBYlg4pfE6Mriwddps8fGpW1VDhs8yj81MSrh07ScruppuAn/0M//XUcfzi1DTeu2cjdq1L46ZNLWRoiKLLusHEBKXSAq523E7ydmbn8NvOC0I6GmSEb9/XFQ/hV+cp1mNZOg5Eg/6mG5s1NcCco47CT4q0WoUgWCsmSdWt780CP1YW29LhAdubbgI+9zlAFFFVdUiKjpDMzi1O7qbzzAAAIABJREFU+NzL5xe2rVsxvb6M6uj8jvMjI0VcsSrZXGB8AbAyK22d065kfeEzdNoBI/xrhl9C8NhRPP2qt0Dv6SE1MDqK9XoJ8UoZpXAM21alsDoTdRH+X3/vEN7/1X2uASpWRe4CWzqioiEc8CHg91HfFKeHv9CWDsvQ0TZeZp0U0ZAfhmkXXMma4VL4gLsdgG3p1FH4puki/DWZKAQBOJ+r2P79LbcAAH70zAncsjmLj755O96yew36Ui10NuSWTiRCKnFiguomBIFmMDAEmS0DwBWEthR+fKbN41b4dj8dS+E7EA35XUPfZ0NF0V01DLPCqfAZ4QcNHRKrHeEXGdN0zyAGYJNqXx8Vfy0W4fOA7U030e9y2erDFOTjRjnR89+OzpjhgK89hc+gaAYODBWwa21m7o0XCCuT8B0Kv8w8/CUHU0h3vvgTGIEgntx9K6Xl7d4NANg+fgZJWYQST6ErHsLqTNRqIWCaJg6NFDBaqFpFHAA65uGLjs+MCF/pWNDWZIMioldsse5zDiYHKIDajMJPR4P0OUciLhvHqhkQRUSCfgykItSZcv9+umju2EEPTxXxnps3tPdGOOED9pi7Z56hKuma9N2umtRL5/uqVfi19/Hbfp9gBdWdiAb9jVMjayApWvOWjiNLB+fPQ87QSmri9BAACuzf8dJT2DF2aubrc8JPpch+aofwn3mGGuy1goMH6XjlKwtRxLSoIqBr8Guqe9940N5RPR8J+l3zlFvFweE8KqqOGzfNnSK7UFi5hO/3A/E4RFlzeaVLBqbwN02P4MwNr8LFQJysJpaut2XkJJKyBF+GVPuaTNTy8C9MVaysnsdeslPhOhe0tVdF2WTIrfCzWfpsZ1H4VVXHpx86Tl7yffcBf/VXkDUd/8//97wVxOIQj9JQ6+xVdmMvTuCcOJwKvx7hc8suHQ2SonZW29Zpf0upmRIp/N27LVW3PmLiNVe02DvFeiM1hD8+Tq0w6kxXs9onOCydt16zBh9903aXOLFSNWs8fIAyqEJ1Ms8S4UDTHn6lFUuHv7ehIUAUUbmShMr0uWFrfN8nf/oveO++77sH3wP28ZlMtkf4igK84Q3A3/xN0/8iazrOPPoMClu20fEajVoK32qrAMy0dBZQ4e89TTGO6ze2UbzVJlYu4afTgCCQwm9WxXQSjPAB4Jmb3mhNu0J3NzA4iPUXTiAliwhnSQ2szkRQqmooVlUcHiFyTUYCeKQDhJ+XFIwX7ZNAVOzPLJsIIy+p0MsipbeFQvTZzvKaPz82js88cgIPHbkIfO97wFe+giMjRfz40EX86OAo5Yy/733A1BTEwy9hNNGDrevtugxOejwXnxdeATZJOpVpXyqCv//NnfiN3awrpJPwna2S2Uk92B3D0GSJPN7du3GWre7ftDnVvtfKi3YAIvxnnyVi43aCA12xIAI+wdW24bLeBN57y0bXdralE3L9L1DfvwfoYiIpelO2jthKHj5/b0ePAgB811KnzvKFi5gSFUSrElLVMlJVcWYuPifVdgn/8cfpeBsbm3tbhqGJElaPnMHJ/o32/osia6vAjnVBmJXwI0F/e1k6DHtP53DFQHLmZK0OYmUSvmNM4CVj6TDCL0cTePSy61Cqakjwlcfu3Rg4cwxJWUSin9TA6gxtP5qv4vBIEX6fgP9+43q8cCGPHE8p5FbBPP30v/3BEbz/a89bf4uyTQTZBJWDVwsle1mfSs36mr86Tyf0SxdLtDKYmMCJs5SmeHS0CHz1q8A99wA33YTQr57Hua5VuHzAtj34a/PGd1XWWgEA0tGAaxuO37lxvbWvzRB+9Nxp2rerr8YDJ+m93LqmzUwKVaUfTha9vfYFsY7C5/3u50oVtnPzbcLIMPLY2IDwObk4B6U0QksKnwsWRvjRm6niuzJ6ERMl2RoHmJLFhbd0HmBZ4A2a4tVD/sRZhHUV57Msey2RYJaOghjPwc9mZ7d0An6ougm9UcvnWaDqBvadncaNrQT+FwArk/CZwjdNE6J8iaRlsgPphRtvx1nRcDXPwu7dyFw4jZgqo2cNWQqc8EfyFRweKWBLXwJv3LkKpgn8/BjL8Q4E6HnnqfBHC1WyOBhExe3hA4DsJPw5FP6vzlEWydHRkmUFjR2mtrlHRouU1jc4CExOouv8KYz1rkVPwu4zwl9bqqPweSvhWYmqnqUTCLgIf9MUFQ/pV2zDw+fp/rjaZlOvWrLggeNMhubI1uADr9yEf/itK+d82nQdS4e3XqgXsKVt6XFnJ8t60HQDim4g1kwvfIBskUgEOHYMABC8niq+1YvjmCzLWF2iYzJVLc8k/GKRigej0dYJ3zTbIvzyBfp+h0IssSEeZ5aOals6AwN0TBhGfUuHrcDa8fEPDBUW3b8HVjLhZzKoqgYME7aSXkokk8B99+H5uz6E4ekKys4L0a5dEFh7hFQ/kcUaRvjD+QoOjxSxfXUKO1an0JcM49FaW2eehF+SVUxLCjTWu0eSdcvS6U0SgSilclMKX9EMHBimx14aLVqEXzxGwdnRQhX6mTOUGbN3Lw5s3o1TN7/G9RxOD980TVRVo46l0yThc4U/OOjy8FNVIunDVT9GdXclZsuoJXyemnnDDdaIOyeuGEjh9Tvq1FXUoJ6lwxvaXbW2fsl/T2J2hW8YJkzTtNp0N23pAPbUq0gEGByEHAwDExNM4dPnnZSlmQ3USiUYiSSu+fuHkQ/FW+ulc/AgZQXN0va6HipD1P7hLB9szxT+lKigByxgyzPOJKmBwmeE34aPv/c0HXeL6d8DK5nw02mUZPpiLwlLBwDe8x6kNg1C1uhClHRYOhbYtKveRBhBv4AXL+QxXpKxY3UaPp+A11zRhyeOT9iN1RjhjxerbS09AWrzYJo0GAIgGywWdls6WklsSuEfGS1C0QxcPZjBeEkm7x+AeuYc1nZF4TN0CENDwPr1qG7YhLf/t39A9Y1vcj0H9+clRYPC3mc42DhoOwPZLKlIVSXCFwRg7VqXwk/KtF+PjsjQIsyuWGjCr+Pft4Kr1qaxrjuKdd12/GfnmjR++ZevdddjOMAVvnPYuRNv+fzT+ORPXrJ89pZG7vH3NzhI8bFUFwJTk5goy1hdJDJuZOnI0RimRAUXfWH6bpotxOfq/t3vps/ZOZdhFqijRPinELP3nQVte31s/zjhl0oNFD59NtzH1w0TSm3KaQMshX8PrCTCNwz7ILLm2dIXlbgU8vAZuHIH7AlM2LDBDsCy2IPPJ2AgHbHU/A5Wmv2aK/pQkjU8d5ZVOaZSMAoFvObux/GvT5yaewc++Ungi1903cUzgHJWebw7aAsAhig2pfC5nfPb11NVpcYIv2vyIt569Rr0l6fg0zRgwwbsO0sVrbXL3rjDw+c53VzhX7k2jbv2bMBNm2bpYsgtlakpIvyuLtpnRszZRAjdGhHHDy9IuPJyFuxdKMLnVc8339ze8zFcu74bT/7v19jHCcNs9QHdjp75tdANE4dHCvjqL87NmBrWFPj3zypm5a5uRArTmCjJWCvR8ZiQJUi18waKRUgR+mxygRhl3VSpG+xf/tdBnGk0NAUgwr/+ekpvBRrOK66FOU7nzQnEaOVqBW1VZAW2f3xynZPwHVPseFCdK/xP/fQY3vbFX8z52kvl3wMrifAvvxy4mzWNsqZdsU6Zl0KWDsOaLpvwLavJ57PSM53jDVeno9SLHnYvjivZUv7spGRtr0/nUZY1/Pjgxbl34BvfoIEfDKZpWq2aedtgUdGtVVE8HEAiHIAhSm7Cb6Dwf3V+GqvTEdx6OcUiTGbprC5OYM/mLHaqbDm/YQMePz6OkN8348SIOTx8nm3C1VY44MfH3rzD8vLrwll8NTkJ9PSQcmMntSAIWC0oqAQjODEl47adq2mKWbuEX6sOX/taGqt3223tPd88QMFgYEqaOa8gV5ZhmDTN656nKKe9JcJ3KnwAencW6XIBpybKGBSJiH0woeVrxECphFKQLlJjfnb85/M4NVHGN549j4ePNMi+GR2llgi/8Rv0HQJN2zq+iXFIwTDEYITOIUfQtkeosXRKJfruo1FXl1GeCswV/snxMg6NFObMgFoq/x5YKYRfqQAnTwL/9m+k9ItF9zzbS8HDZ1ibsRWEqz6A2zqOAeZ8NbCuOzpjOlKhwg7aVApGgcj34HDBbqncCJJEJxJDVTWg6rQyypVpTqmiGa4KzNWZCCA1Z+nsP5/H1eu70JsMI5sIwceW4KtL47hiIIlrTUYG69fjieOTeMXGrhnFP9GgQ+EzdRVppdupk/BzOfrbQfgA0G9UUQzT+3nttv4Zj8+Jv/s74Kmn6Hatwvf7gTvuqDuQvdPws66a9RQ+71kfC/nx4AFqeBttRQzx73/9egCA0NeLHqmAA0MFK2gLAPpUTVC2VELezwbQC2x1ks/jfE7CrpFjkM6cq/96rB8N3vzm+j2SZkF4KoepGJ1LFwtVl6XTZdYhfN4LyYFahZ+XFJimPXayEV64QO//2vUe4XcGU8zeOHaM+peYpmva1SWRpcOQigYsMk0692vPHsokcYxNXJWhk2PHKlv1R4N+BP2CPYg7lYJQssnXFdCtB1GkCUzM/nKO+5ssy9bgEecUqVXpKBG3U+GzZbkTY8UqhvMVXDNIVZjb+hIIsSZVg+UcMrEQtiuk8IcSWRwbK+FVW2fORfD7BFYxqtmWTiudK2sJv0bhA0CPXkEpFMP2VSm6sLIlf1OQZeBjH6P0UqBuwG8p0RUPWfEYJ8ZL9F2879c2We7nfBR+sL8P3ZUCpkQF2fwETGZlmTVZOGaphAmBrMELBvO083nkDx7F97/2YXzo914DXHcd8KUvuf4PBw+S6t65s2XCj+VzqHTRqmCsSIRvsqBtmk+74oRfLrsL5xgshc8UfZ6JLD5trBFOjpfQFQsuyoSrWqwMwnf6evfcQ78voeEnTgiCYNk6Lm/2ne+k0nHuK8JOzdzhaK0qCAJSkaBL4Qssl1gQgEeOzkH4kkREzTz4omPc30RZtoqdnHGP1ZkI/NWKW+EDM1Q+9++vGSRltaObTm7d58dAYRwwDKwvjWM83oV/e57sp1fWIXyAN1CzC4hammcwG+EzpssoEkrhOG7bxiprWyH8c+foeUbYWIhLjPC7YyFM1UnLHC+Swn/HtWtxGWutHG3lQlrj4UfXDCCmyugtTyNaESFwn72G8I1CAYVABNGgH2e1oLVN7PHHAADff9276bj8wz+kiynH8ePAli1kebZA+JKiIVPOw2DB87GSbH3/kqwhK7BjvtbDb6TwNVvhA8Dp2WIOIOtncyudVhcQLz/Cn5gAXvlKquDk4IQfiwHf+hbddlo6lxDhA7ZV47J0eCaJA7xXys6aFLx01E34gXIJME3suSyLp09ONvYYncNSmK3jVPi5smKtipw2y6p0FCFFhhZ1KHxgRuD2V+enEQr4sGM17e/2LjamLzOAoKYC4+PozV3EcKoP337uAvpTYVzeX39MZCwUgCTbCr+l3vROv9fp4ZumleWRViSUInHccRVbUbVC+GfP0u9hyvW+5Ag/Hqqblsktnb5UGL//KmpW19eKCq1R+Ik19NltH2ejDq9ktQWFGoVfLKEciuL6jd2YCNgefv/zv8BIMov/+9r3Ah/9KNmxx4/b/3jsmF3H0NVF50gThD9elNEj5RFcNQC/T8AYs3QEw0BYV5H161Qx3sU6q3LCn0Xhm6ZpNa3j4yUbwSP8hUQsBjz5pPvA4JbOu95lL9sdQdtLjfC5cp8rtrDnsiy+9DvX4lVb3Co4FQ2iyAk/nYZgmogrFbz16jWoqDqeOdUgk0FV7VmvFuHbCn+yLMP/ox8iolZdHUZXZ6KIqVWI/pD1mvj/2zvz4Miu+t5/Tu/7on000oxm8wxj47E9Y2M8ZjfGEDAkLwTnOSwBiioSEvKSQHCcf1KphLzivUBSRfweBUmchCLkEYgJdiAEE7PZJh7HmGHsGc8+Gm0z2tWbWtJ5f5xzum+3uqVuSSOpW+dTpZL69m31vX1vf+/3/s7v/H6wyOE/d2mCG7pjhRov+6Pq95lWXbzq4kWCg/0MJDvJ5Od59b72qrNNQz5VBMxMeqnL4ZuKlf39yjmaGD4Uzo9wZoY7Du/hQJe+eNUj+KaIl3H45aV1N5iWsK9iWubwVJZkyIvf4+adR3p5+vffUF9FULN/uhiZq1PdHV0/rLPDtMN3O88LKXHNzJDyBblzbxtTfn0cxsa47sQz/GjnIYanc8iX6VpKpkfz7Kz6nK+7Tj32eJRA1yT4WVrTk3i7OmmP+FVIRx//YD5LC3m1L+acMIO2Szj8mdwcczrt+ezV6iGd0Zkc4+k8e6pMjLvWNJ/gh8Mqrudsgm4c/gc/WFyWSDCTm0eIOuOU68Btu1rY1xEhssyAmcsluOeGLlxl9V3iTsHXbjsym+bu6zsJ+dx858UqWQ9px2BTmeB3xwP4zp1l9/t/mbe++IOSzKbumJ9gPseUy1vynuUO/+yVFNc5HHtfUG33adOB6fx5xIULZLqVYLxmf/W+xgXBz6/A4YMSeT0rlNbW0vK+ets9SUfZ2noGbY3gj4yoi6j5n46Uvo0kqR1+edO5kekcHdGiwLdF6owx33GHypjx69fpkMliwXecF9ksrvk5MoEwR/qSTOn0TPn97xNPTfL0rkNk8wtM7ditQjdG8M+dU+bEOVO5xslX4wPDeBfm8Xd30Rnzq5COPv5tclbNqC4X/AohHafDN+4+6HVz9kqq8NnO5OZKCgKeHlHnkHX4a4mpRmgwgn/TTWp2I6iQTlblk294e8My3n7Tdr79269ZJOS1EisL6QC0LmSJBry8am8rTxwfXPRlB0odbFlIp68tTPiSErJkeqpk3KM76MKFZIIywXc4uclMntHUbEmNF7+uWXLOOPynn4Z8HveuPlwC7txbPZc+7FeNzFfk8EGJw4svqr9NSAeKom4K7BXecAUOH2BoqGJK30bSEvKRn5eLqmaOTOfoiK1iIPE97ylts6nj6tcPn0UKAdqlexxJBKZWjT8ZpycZIufxMe/zIR99FIDxVxxV2zYL7NlTFHxzsTYO37xfDYI/fVGd2+HebjpiAVUYUAv+gagLkU6rx263ukjPzFQO6TgcvhH8Q71xJjP5wh3UZ759ind89oeFJIrTV6zgrz0dHYsdfjCofu67T93+tbfruu6b40u4lsSDnkWC34U6Ad/z0vf46iffxeXLFcI6Szj8XW1hokMqJh3LpUruirq8ymWPS30RMELpcPjn9UBWn7Ool36/2J6dSnC//30A7rzrMP/33UdKSgaUE/K5SefmyeZLJ17VTFtbMf20XPBzOTVw7UiBrVvwTWPsgYGKGR4bSbIw+ao0F//KVHZtM0e0w++bGGShsxNCIbK+AL4ZR2NwLfjhtiStYR8+j4tMOIprZoazyW5236wuEsNTOTh4sCj4JmS7AsHPXFahtlDPNrpiAYYcIZ29YVF6vHR7y0ohHafDN2MiJgPNTBZ7/OQIs/ML/FiXQj49MkPI56Y7HmQjaE7BL3f4Y2OqzDDAb/wG/Oxn0NLCzOwmqZS5xsSDXqayqgWgEd92nWp2Xf8p2tMT9P/bE4X1f9o/yd2ffoJv/+fZ4j9xOHwhVI2W7nGVORPNpUrGPQLaqV9d0BeBCg7//Kj6AuyqIPgP/OJhNdD37LNqW19+gDceLGYjVSLsK3X4KwrpOP92Cr6jQU7xDesUfNMY+/LlTSf4Lbpr1miqmPGysCC5MpOjs56Y/XIkEizoC5/oVQO5mVAUf6p4XszrSVixzhZcLkF3PEAqoMJ+T+68kcM7lYAOTWWV4J86pcJkp06p77kZWIWaBX9+UIU0RWcnnTFV3ntShyP7glQW/AoO3xnDNymZZnvPXklxaSxdGMD94Rm1XadHZtjTHlnx3ftqaV7BL3f4JjPD7S64glRurjTXvUmIB73ML0hSs/MF8W1fUDnWLWPqZJ994vuF9R/96SCnhmd46LGfFv+JFvyp7BwRn4eOaICeSXURjeVSJXn4RrhH5ksF/8L54gSuc1dTCEFpFyb9Ok80ogTfDBibZtZLEPKbQdtVOHxDucNfjeDPzCjROapCEZvS4YcWF1AbT8+Sn5f1ZeUshxC49Ofs6lXjNNlwhECq6PCvDighbO1S389t8SCTesLbD3fexBEtoMNG8Ofm1CTKkydL3T2oYzo6umwdHlNWgc7OwqD0c+Pq3Nvhk4sFf0oX+Stz+D63CyEgl58vpGTesD2O1y04c3WGJ04pDdrZGuJHp9Ud9UZm6ECzCr4J6ZgD7xR8B6nNUgt/jTGzbicz+WIMf14JvvuyajkXf/bpwvrHLoxxqCfOh29TE00m460lIZ1owENrxEfPpHL4sewMIaej1sI9lFenU9blIef2cvzEpcIq566mODw/QWB4cNHrCIUKszNpb69JHMM+D6nc4tIKNbMSwZ+dLbZDrIZJybz1VhXWGRio6A43ktawEvUxR0inkJIZXUOHD8VCcTpzZzYcI5AuDn4PDyhR7Niu1utOBBn1qc/q5IFbaI34iQU8Ks5+8KB60YkTyuGXl5Zua1OhuPTSM13dV68U1u/Sgv/MiNr/Ht98qeBHIqqxipSLBF8Igd/jIuuI4beEfexsDXP2SoonTl2hJxnkXbf2cnJ4mvNXUwxOZq3grznt7Sqf2jiysbGKgj+dbU7BL5RXSBcFP6EF3zSY3v3S88g5FRL5Sf8kt/a18Mad6lb6Uuv2kpBOLOilLeIvOPxEPlN6S6q/YAN5tez5/kmmAmFaXjqBnFNjAPnjJ3j4sx+GD3940esIhYquvq+vpn0M+Tzk5hYKlRfrKq0ARcGPRFTO9XKCb55fzuWbAds9e9SsaOPwIxv3JS/HNEJ3lldw5uCvKeZzNoIfjRHOFB3+2KBy+N09KoVzeyLA88kdHN9/mEivKlrXGQuoGP6BAyrX/qmn1GB4ucOvsZ6Ob2yUVDQBHk8hhPXDITX/opX8Yoc/pGtQVbho+z1ucjqGH/F78Lpd7G4Lc2p4mh+dvsprrmvn6B71Gfz9U6pExEalZEKzCn6Hnh1pwjqjo8UYvoOJdJ5EcIkiWw1KST0d3fUqkc8o93PlCpM7dhPNpRl+8hjHL6tyxUf6kgUBPh/vLNzGTmXzRAMe2pilLa2EMJ4rEz39ujHpYTqb59iFcT5/6zt45ZlnmXnfB5FDQzzwlx8jnJ4uDbVVEnzj9JfBDBpPpPO4XQKPe4WCb3470zLNTNDyQVvzPMCf/Al0d8ODD6p8foMR/F271PObMIavhEmUlFcwLSzXNKQDRYevJw3ORaKEM8XzZ3JEDWYmTEgnEeSTr/1V3vmLf0SvnnHeGQswPJ1V50lfX3FSZaWQDiwp+Nn8PNGpMXK6rEKnvsCdySiz4ja1700KbTRabJ1Y4aId8LrI5pXDT5j2ku0RLoymSc3O85rr2rlhe5xowMM/PqPueK3DX2vMSWbCOhUcfm5unuHpLD3JzZEbvZbEHIK/4HKT8gaIzqYLwpT5hXcCMPrNxzl2QX3hDu9sKYjZqaiuITI4qEM6XpJXlONPe/3EygVfvy7j8TM4meXYhTEevvOX+PM77iP6xYeRB6+nfXqU8V3XlU7GWo3D19lVo6nZ+uP3UBQHc16YL/hSIR0oCv6TT6rz6pOfVNv8jW+o5efOqf/V3q7KIG/CGL4QgmTIV9nhX+OQzlwsTjSXKtSNT11V5TaEvhM1kw4zcwuF8Z6OmL9Q9oGDB1UMHyqHdGBJwb8ynaMtPclcm9queNCrMoN0tU5SqcUO34Txqjn8ORXDLwq+Ws/jEtyxtw23S3D77lamsnN4XKLQpGYjaG7BHxlRAjM3t0jwL49nkBJ6khuTHnUtMQ5/KptnOjfHjD9EJJeCS8phtNzzeoairYgf/ZBjF8bZ2RpS6XhagM/FywXfg+eiuh19sb2PSLayw894A1yeyHDswjhvuWEbD73u3fzgv30QMTXJb731d8jccmSx4AuhJurs3q2W7dtX0z6aiV/jqdn6M3RgseA7c65rEfyhIXjd6+DMGSVmn/mMWn7unHL3QiiHvwkFH1SsedQh+Femc0QDnvoantRCmeAvxOKqkbmeA1Aolazd8/ZE8YLTqwW/MxZgZDrLwoIsxvFdLhU2c1KD4I9M52hNTRSiAEIIumIBZt0e5t0elZGTyZQKvmEJhz+ezhcGw00doiN9yUI229E96jzrawvjrfdudA1pTsF3hnRMWYWykM6lcRWz621pXoc/lckzlckz4wsRzqYLgu/bvYuTe26k4/ljHLswXkglM2J2IanrxwwOMq1DOmYw8kTHbsLZVDGjBhyC7+fJM6OMp/PctquFl/ck+PQbfpVHHj/ON/cfJdSWXCz4oVCxTtAPfgDvfW9N+2hCOmvm8KE4m9YIfqxYlK4gAGZi1vCwqqa4axe8+93w+ONK3I3ggxL8iQklQJtM8Msd/vBUdu3DOaBKF3/gA4WmLzIex7cwR3paf47T0+QCoUKrx22O/PRefffdGfWTn5cqq8gIfl9fcUavoRbB12UVPF3FtN/OmB+EYCEYKoYcnYO2hoqCrxz+ZCZfMFp72iP43C7uelnxPY7qSYR7NzB+D80q+NpV9J88z19//Rm1rMzhm6bczvZwzULU70EIFdKZzOSZ9gcJZIsOn54exm+5jbaxIXwD/RwxdbnTaaQQXIqrE1VevlwI6XDuHDmvn3NJ3f2pQmgm5/PzjZ+oSS2HdyY51JPg+OVJXkhJ3C5BtKNVOSjdn7cg+IajRxd/iatgBttX7PCNAXBm6zgFPxotnRnrHLSVUjl8U03x/vvVsi99SV0YTViqW39WudymE/yWshLJ5WUV1oxbblF9KLSgCz0ukrs6RjY/jzedYi5cFMGw31MQTvPd7Iqr7RpyZuqUx+9Bjbm4XEuHdMZnSGan8W8v9gwu1AuKhIus5kScAAAau0lEQVTx+koOv2JIxzj82YLDT4R8/Ptvv4b33dFXWG9vR4RX7m7l9Qc6qm7betCcgq/r6Zx/8QLf/eELalm54I+n8blddF6Lk3yDcbmKJZKnMnmmfWECaS34bW0QDOJ51asAONL/ghqwBSX4oTDjwRgLHi9zlweYW5AFhz/W0c1UQH85nXVyzIzZljgDk1niQS972iMc6k2Qm1vgW8eH6E0GcSd0iMS45HLBrwPj8MfSK3T4Xi/8wR/Au95VXGYEX3dEK8EZ0hkfV3FdUy99/35Vr/2hh9SF0Onwnf97E5EMe8ti+Nm1z9CpgBH8/NUxRqZyRGYzLIRLP5vuRBCXKMbzjSCPTOUK5RkqCr7Lpb7nSwj+TL8aiwp2F/tKdMcDuF0CdzRanLBZc0jHTSavHH7S0WVtR2uoJJFACMGXPnQ7v3Rrb9VtWw+aU/ABOjpwXb1KIqtTwMoEv38sw/ZkcMNmvF1rTAG1yUyeGX8Ib3pGCb6OpW5/zStIeQPcNvJS8TYzlYKwCrGkWtqY01PQjcOf6eopFLcqqWmuBb+lVYVAbtmRwOUS3NSrvtznR9OqpEL5DNxVCL5x+LNzCysTfFBdqcwEKSh1+EsJvknT6yq6RH7lV1Q8H4qCb3rXOl+/SWgJ+5nI5JlfkEgpGZnKXZuQThluXZBudmyckekskdl0qaiiyoN3J4KFWLdJnRyeyqp1//7v4aMfrfwGy8y2zV5Wx87lCOl84M7d/NX7bsUVCS8t+FUc/pXpHFJCfIlSIJuF5hX89nZ8Y1dJmJzfshh+/3i6KQdsDTFdT2cqq2L4nukplYOvBf9lPUmuhpPsEY6c+nQaEQoR8LqYSrQhB5QbimmHn+3ZwZS/iuCHQnTrmOuRPvVZ9ySDhabZfa1rK/jOWj51T7qqhplNu5zgm9t+p+Dfd18xBFTJ4W82wQ95kRJ9jqi+AmtaVqEK7hZ1Nzk/Ns7IdI5ILoPLOVYCfPye/fzvdx4qPG7XVTuHTabO/fcXB/nLWa68ghH0jmJopSseUJ3VwsuEdCo4fL/XXegUllyqj/ImoakFPzQ5RsesTjXMlx6MS+OZphywNZgmKMrhB3HPTJc4/IDXTbijlQPBheKLUilEOEx71M9YrBUxpAQ/kU/D+DjzOxyCXx7SCYUKt+CmgJQQgkO6OcuuNXb4zgYsK3b45TgdvjMHH0oHbY3Dd3Qfo7Oz2JTcCH48rgr2OV+/STAF1MZSuUIO/nq03PO2KTOwMDbOyFSWvokB3Lv7Sta5rjPKKxyN630eF61hn8rFX45lBN89qgdlOyrE0iORQgOcehy+6fmcsIK/ccy3tRObmeBwdIEpf5hHTxQn/KRyc4ylZpva4ZcIfiCMmJxUQtZbjCG2bW8nmc8UX6QFuD3iZzicxKPdTqvOwXft2l2M4Vdw+LfsSLKzNVQI5QAc0n+vveA7HL5njRz+UjF8s53VQjoAf/iH8Pu/X3ytSc2ETSf4LQXBz1+7HPwK+LTDX5iYZObiZdpTE/gO37zs6wpljJdjGcH3mVLplQTfeYzKs3QCgYrlrZ0JA0tVd90sNK3gp+JJ2tKTdM+lSUfj/OvxYg2XS+M6Q6cJJ10ZlODPMZWZI+8cFHMIPvH4YqeuHf7lQALvxBje+TyJYTVhy79vD9O6sFUlwb/nhi6e+NjrSnK57z7YxcFtMW7sia+p4Ps9Ltw6FGWqFq6apWL4brdy60bwfb7FdwGveAX88R+XLtukgm8ySsZSs4WQxHoM2vq1w2dyAu+J4wC4Dh1a4hWKrpi/GNJZCiP4VQqoBSdGmfN4Fh9fKA3ZlDv8KoPuzrvLRpi137SCPxFOEJibJXF1EE9bG6eGZzg9ouL5l8aaNwffEAt4mcoqh78QccRInZUoywVfTylvj/q54NNVNlPjRHQd/LaX7ycX0l+ACq+rxMHuGI999FXK/ayh4AshCi5/TR3+9HRlwYdijN/k4NfSOMcM3G6yLB3j8P/uqfP82bdVbfn1iOEH4xFmXR7E5ATRUzqD7sYbl31dp6lbvxytrWqiZVl7TQApJeHJMTLxlsrHrpLDN4Jf5YLtdPhJ6/A3jqsh9YUNnztNdHsnQsCjz6tb8UIOfhOHdGJBL7NzC4xMZ5ExRxxyOYcfCtEW8XPepz6/jz3xt0S++ShEIrTu2MYTD9yFjEQWO/xaHOwaCj4UZ9v619Lh53Iq5bLcvUNR8J05+MuxSR1+S9iH3+PiyTOj9CRCfPpdh9alt3PI72XaH8I1NUXH2RcZT7SXzoWoQlc8wNWZXKH/QVWWmHyVzS8QzUwzG6twbGFpwV/G4QtRnPC4mVnVERZCtABfBvqA88AvSSnHK6w3D5hi6xellPeu5n1rYdinDpRnbBRPZzu39rXwL88P8Jtv2Mul8TQhn7vgcpoRM3nl0liGw7EKMWVQgj81pSZCuVyFEgDtUT/Pde/nzMHD3HX6aTwnMnD77SCEyomOxxcLfiWBLMd8edZI8E09ncBaOnxDNYdvBm1rqNkPbFrBD3jdPPqbryIe9K7LYK3B7RJMByJ4pqbo7T/NyK7rSC7/MnqSIaSEwYlsade0csy4ysDAotILk5k8kVyahVi0wgupHNIxy6oIvnH4sYC3EGLczKzWGn0C+I6Uch/wHf24Ehkp5U3655qLPUC/x3GAWlt526FuTo/McHJ4mktjGXqToU3Xy3YtMYI/OJnBZSY8bdumJhwVVoqrWKduM+cctB0Lxfn4R/6COz7xVTV79LHHiq9LJCreGSyL262+SJvV4TtFeamQztDQ4gHbatx7L7z//bVfINaRvR2RdRV7QyoYwTc+yq6Ri0xdd7Cm15gEi/7xzNIrmnRNZ19hzURmlshsGlmWBlrAHH+Xqzjj2+VSy6tcsI3Db4SUTFi94L8deFj//TDwjlX+vzXjvMtxgFpaeMsNXbhdgn/5yQD94+mmLKngxNxeLkiKM1x7y2b5lfeeNYKvReDc1RSxoE+VLHa2kkskKg7a1rZhMSX4+bz6WYXgm8HhdXP4kYja9itXahf8ffvgC18o9ri1kA6G6X7pOL6FOWYP3lDTa4qCv3RzE3buVHeyZ88uemoynVd5//Eqgm+OfzhcGuOPRJZ1+I0w6QpWL/idUspBAP27WqGIgBDiGSHEU0KIdbkovIRD0FtbaY34Obq3jX/5ySCXxtJNWRbZSdwRT/Qmqwi+CcNMTqqwjiNLB1QGRzRQQagqhXTqFXyT77wqh68Hbdcyhm+oFsO/cEF9VrUKvmURmVCUcEaV1xCHlh+wBeiKqfIHyzp8n0+d5xUEfyKTJzKbxlXpYg5FF1/u5vv6qt6hNZrDX9Z2CCH+Hah0dj9Yx/vskFIOCCF2A48LIX4qpTxT4b0+BHwIYMcqb4EvZgWzvgC+2WyhrMLbbtzGx77yPNCcZZGdOAU/0Krd+VIOP6szIPSgraGi4CcSqqeoYSWC76yFv0JMX901nXhlqBbSGVDlJmoetLUsIhtWMfSc20P45dfX9BqP28W2eGB5hw8qrFPN4c9mkMk6Bf9b31IXkgoYh98IKZlQg8OXUt4lpbyhws8jwLAQYhuA/j1S5X8M6N9ngf8AKs60kFJ+Tkp5REp5pN3U0V4Bc/MqOyWT1Dm/WvDvvr4Ln67P0cwpmVAq+P7WFrj7bnjTm8pWcgi+qfMeDhPwugtCHw1UOJHXIqSzBoJvHP6KqmVWohbBN1iHv2JyESX4p1t30NFae7pqbzK0vMOHqoI/NZMlMpvBV03wnSEdJ84Z02UYs9EIk65g9SGdrwOmgPl7gUfKVxBCJIUQfv13G3AUOLHK912SKzM5FiTMtegULV1HJx708tr96kLSzJOuoNSZx8N+5VKWEvwyATZhnSVDOlIW4/G1ZOnA2jp83wY4fIMV/BWT1/NCXuzoK7mbXI6eZLB2wR8cXNTMPDWuTIovuUxaZh3nZMHhN0hIZ7XflD8F3iiEeAl4o36MEOKIEOLzep2XAc8IIX4CfBf4UynlNRX8wUkdntBtzJyVMt93tI+bdyQKbciaFa/bVXDAVfODlxL8yBKCn0ioBijpNLygJ8+Ut5urxlo6fP81mHgFKjOj0iCdc5kN6ayYOZ0lc3773rq6P/UkQwxPZ5fPxTeZOrppj2F2TAm+qDeGvwTFGH5jOPxVpQ5IKUeBN1RY/gzwQf33j4CXr+Z96mVIC757m/5SOgT/jj1tfO3Xlp/o0QzEg15Ss/Ml4Z3SFSqHdMDp8KuEdEC5fCP4B2tLr7sWDn/NSiuYL3osVmjYUfH5cHjTzZxtJOYi6ry7uqtGk6DpSQZry8U3gn/2bMl5mdOCT7W0zGohnSXYag5/U2IcfqBvhzp41Q5wk2OcfVXBDwRUXv5KQjqgBP/ECTWgZSpELrtRWvDNBWYtsnTW2uEv5wBtOGdVXDp8lC/edA/DNx6u63V15+KXxfHnJvT8j+Xy8OsQ/Jdti/G7d1+34Z2saqUpBX9oMoPf48L/ex+D732vtponTYgR+lgl0Qb1uZjyCmUOvy1Sg8OfnFQOf//+2vPMYzEVDjJVC9cihr9WDt/vV5PDrOBfUxa6unjwTR8h2VrjuI+mRydaLJup09amLt5lgr9QqVexkxU4fLdL8JHX76v8PdmENOVskMHJLNviAURLy6LGJ1sJ4/CXrPFhBmCrOPyKFwtnSOfECdXer+aN0l82U2J4M5VWEEJ96a3gX1PMhLl6q3N2Rv14asnFF6Jipo6c1A4/WqW0gjkXN1kZjLWkSR1+ttD4eCsTD3oJ+dxLD4wZh7+SkM7goJrCXmv8HtZU8F+1r51fe+0eDmyr8gVeCZFI9YwjIwR2wHZVmCqn9bZU9LhdbEvUkYt/pnSqj8uUEKnm8F0uVQrjzjvr2q5Gomkd/m27tq6zN/z8zdtV45GlMHVxykI6t/W18O7bdxbaFS56DcCPf6xSM01j6VpYQ8GPB718/J4DK359RW6/HW66qfJz5pbfOvxVEdShuJU0XOlJ1JiLv2cPfPOb6vwUgoUFiTu1jOADPLIos7ypaDrBX1iQDE9Zhw9wdG8bR/cuk5EUj8NLLy1y+GG/hz96R5U6J0bwn3xS/V6Nw68yoWXD+MpXqj9nQzprQsi7spAOqIHb77+0RM9aw+7davb40BBs28Z0do5ITp/j1UI6W4CmC+lcTeWYW5Bss4JfG+WDtrU47kBAZeYcP65ug/ftq/39nILv9ZZW79zs7NoF7e1wuL7sEksph3oTHN6Z5LrO+oW37lx8HcefyMwSyaWZCwS3dCG7phP8RNDHP//6Ud50vXVhNeGM4dcjwImEul3eu7dYSrYWnIK/inDOhtDZCSMjcMstG70lDc3ejgj/9OE7qqcLL4HJxR+YWKb7Vbng6zo685Gt6+6hCQXf53FxU29iXdq1NQXxuKqHPzNTnwCbsE498XsoCv74eOMJvmXDWWmZ5EldKVNu4XAONKHgW+rENEEZHq4vHc1k6tQTv4fS+KkVfEudFHPxlxm49fuhp8cR0lHdrrbqJEyDFfytjhHugYH1cfh+fzEEZAXfUifFuvg1pGb29RXq6UwWauFbwbdsZdZb8KHospp4govl2uB2CTqifoYmc8uv3N2t5ooAk+lZork0nkSVSXVbBCv4Wx3nJKqVhHQOrCAP3gi+dfiWFdAZCzA8tcygLagezjr9dyKdJ5rPVO92tUXYuvlJFoX5AmSz9Qnw296m0ttWUjXSCr5lFXTFApy5MlPDil0qISGV0iGdjI3hb/QGWDYYZxmBehz+vffCQw+t7D2t4FtWQVc8wFAtDt9MkBsaYiI9S9gO2lrB3/I4b3HXS4Ct4FtWQWcswHR2jvTs3NIrbtumfg8Okp5O4Z2f29KzbMEKvsUKvqXB6NQlGUyjo6o4HH5+bJnSyFsEK/hbHVMmAdYva8YKvmUVdOlJlcuGdRwOf35ymW5XWwQr+Jaiy7cO39IAdOo6Wctm6rS2qsSCoaFiLXwr+JYtjxV8SwNRcPjL5eK7XNDZydzlAXxpndVjBd+y5TGCb0M6lgYg7PcQ9XsqOvzByQy//eXnigO6XV3MDwwSntWlGKzgW7Y81uFbGozOeKDioO03fjLIV//rMs9d1DH7bduQg4O2Fr7GCr7FOnxLw9EVq5yL/+zFccBRXK2rCzE8RNQ6fMAKvgWsw7c0HJXKK0gpOXZBCf4lU1xt2za8o1eJZW0MH6zgW6A423a9BPjAAdWg4vrr1+f9LE1HV9zPyHSO+QVZWHZ5IsPItBrIvTSmBb+rC9fCArsnh5Bu9+ZrqbnO2Fo6lvUP6XR3w5kz6/NelqakKxZgfkEyOpOjQ2ftGHffEvZxyYR0dC7+/qlBRCymmqJsYazDt6x/SMdiWSWdFSZf/dfFCUI+N6/d317i8AF2jF7e8uEcsIJvASv4loajIPiOTJ1nL45zY0+cvtYwI9M5svl5pBb8+NSYFXys4FsAfu7n4Hd/F/bv3+gtsVhqoqtstm1mdp4TA1Mc3pmkt8X0vc0wGm0pvmiLp2SCjeFbADo74VOf2uitsFhqpi3ix+0ShZDO8/0TzC1IbtmRJB70AqrR+WTAi9cfJp5LWYePFXyLxdKAuF2C9kix1eExnX9/844ks3MLAFwazxDxzxIPJ63ga2xIx2KxNCSd8WIu/rMXJtjdFqYl7KMj6sfncdE/lubiaIaRiA7rWMG3gm+xWBqTrpif4aksjzx3mf84OcLte1oBcLkEPYkgl8bTXBhLMZNQy63gW8G3WCwNSlcswNmrKX7ry89xeGeSB958oPBcT0uIS2MZLo6myXV0qoVW8G0M32KxNCZd8SDzC5LXH+jgL++/hYDXXXiuNxnk+f4JfG4XwnS+slk6VvAtFktj8vM3b8fncfGeV+7E6y4NVvS2hJhI5wHw9WxXC63DX11IRwjxTiHEz4QQC0KII0usd48Q4qQQ4rQQ4hOreU+LxWIBlYv/gTt3LRJ7gN5kcRJhZGeP+sMK/qpj+MeBXwC+V20FIYQb+CzwZuAg8MtCiIOrfF+LxWKpipl8BRA9+gp49avhtts2cIs2B6sK6UgpXwAQSxckug04LaU8q9f9B+DtwInVvLfFYrFUo8fh8Lfv3g5PPLGBW7N5WI8sne3AJcfjfr1sEUKIDwkhnhFCPHPlypV12DSLxdKMJENewj43Ub+HZMi70ZuzaVjW4Qsh/h3oqvDUg1LKR2p4j0r2X1ZYhpTyc8DnAI4cOVJxHYvFYlkOIQS9LSFcQiwXgdhSLCv4Usq7Vvke/UCv43EPMLDK/2mxWCxL8tE37LNiX8Z6pGX+J7BPCLELuAzcB/z3dXhfi8WyhXnzy7dt9CZsOlablvnzQoh+4JXAo0KIb+nl3UKIxwCklHPAR4BvAS8A/yil/NnqNttisVgs9bLaLJ2vAV+rsHwAeIvj8WPAY6t5L4vFYrGsDltLx2KxWLYIVvAtFotli2AF32KxWLYIVvAtFotli2AF32KxWLYIVvAtFotliyCk3JwVDIQQV4ALq/gXbcDVNdqcjcbuy+bE7svmpJn2Berfn51SyvZKT2xawV8tQohnpJRVa/Q3EnZfNid2XzYnzbQvsLb7Y0M6FovFskWwgm+xWCxbhGYW/M9t9AasIXZfNid2XzYnzbQvsIb707QxfIvFYrGU0swO32KxWCwOrOBbLBbLFqHpBF8IcY8Q4qQQ4rQQ4hMbvT31IIToFUJ8VwjxghDiZ0KIj+rlLUKIbwshXtK/kxu9rbUihHALIf5LCPEN/XiXEOJpvS9fFkL4Nnoba0UIkRBCfEUI8aI+Rq9s1GMjhPgf+hw7LoT4khAi0CjHRgjxV0KIESHEcceyisdBKP5C68HzQohbNm7LF1NlXz6lz7HnhRBfE0IkHM89oPflpBDiTfW+X1MJvhDCDXwWeDNwEPhlIcTBjd2qupgDfkdK+TLgduDX9fZ/AviOlHIf8B39uFH4KKrxjeF/Ap/W+zIOfGBDtmpl/DnwTSnlAeAQar8a7tgIIbYDvwkckVLeALhRnega5dj8DXBP2bJqx+HNwD798yHgoXXaxlr5Gxbvy7eBG6SUNwKngAcAtBbcB1yvX/OXWvNqpqkEH7gNOC2lPCulnAX+AXj7Bm9TzUgpB6WUz+q/p1GCsh21Dw/r1R4G3rExW1gfQoge4OeAz+vHAng98BW9SiPtSwx4NfAFACnlrJRyggY9NqjmR0EhhAcIAYM0yLGRUn4PGCtbXO04vB34W6l4CkgIITZN78NK+yKl/DfdKRDgKVQfcFD78g9SypyU8hxwGqV5NdNsgr8duOR43K+XNRxCiD7gZuBpoFNKOQjqogB0bNyW1cVngI8DC/pxKzDhOJkb6fjsBq4Af61DVJ8XQoRpwGMjpbwM/C/gIkroJ4FjNO6xgerHodE14f3Av+q/V70vzSb4lVrUN1zeqRAiAvwT8FtSyqmN3p6VIIR4KzAipTzmXFxh1UY5Ph7gFuAhKeXNQIoGCN9UQse33w7sArqBMCr0UU6jHJulaNhzTgjxICrM+0WzqMJqde1Lswl+P9DreNwDDGzQtqwIIYQXJfZflFJ+VS8eNreh+vfIRm1fHRwF7hVCnEeF1l6PcvwJHUaAxjo+/UC/lPJp/fgrqAtAIx6bu4BzUsorUso88FXgDhr32ED149CQmiCEeC/wVuB+WZwstep9aTbB/09gn8428KEGOL6+wdtUMzrG/QXgBSnlnzme+jrwXv33e4FH1nvb6kVK+YCUskdK2Yc6Do9LKe8Hvgv8ol6tIfYFQEo5BFwSQuzXi94AnKABjw0qlHO7ECKkzzmzLw15bDTVjsPXgffobJ3bgUkT+tmsCCHuAX4PuFdKmXY89XXgPiGEXwixCzUQ/eO6/rmUsql+gLegRrbPAA9u9PbUue13om7Rngee0z9vQcW+vwO8pH+3bPS21rlfrwW+of/erU/S08D/A/wbvX117MdNwDP6+PwzkGzUYwP8IfAicBz4O8DfKMcG+BJq7CGPcr0fqHYcUGGQz2o9+CkqM2nD92GZfTmNitUbDfg/jvUf1PtyEnhzve9nSytYLBbLFqHZQjoWi8ViqYIVfIvFYtkiWMG3WCyWLYIVfIvFYtkiWMG3WCyWLYIVfIvFYtkiWMG3WCyWLcL/B8DZOajpMrTuAAAAAElFTkSuQmCC\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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sSRXdAxEyqKlBlVELuycA39JlwNatqZ+bAsNOH9z+YNKErQCpn05qCPr9yiSEb9SJgiEhwo9L+B+jtagac2dV4v1D/eCWLAEq+JhyDq8eT1NZp5efmnYgE8L/+c9Jak2UwJ4AskH43QDEEXslgCi25DhumOM4IXP5JIAzsvC+kwMhwk+D8IWiK8HGd8m8Uty6qg5n8o2+AIrwrU7fhDU8IbIXhnJMCBYL/cRz6AhI05rZMjCKJqMG6O6GurEeAMIDLgCQrLNxY8LEarfVjUGHN3yxTIqOiPVTIObheYvp/gn27hGa31WlkHQAqraVIvzk2NwyiFmluSgSrXZjUcCfGwAihG82kwuHR9uAA2XHDsC96Ax8eUklemxuHO4VySMzZlDtyHQlfP58TTvC9/mA558HzjkHUKVY8Y4D2SD8HQCaGGN1jDEVgGsBvCnegDFWJvrzcgDTt1Iigwi/w+JEqUEDjVIOgKowf3LZHGhV8vA2Rr0KgRAHuzsFQXAcWQwT5A56eMLvyYakI9jZEkX4ACVuOzuTaqPUR8iFhXInEAxCXlcLk16FfofoorRmDWC3E+nHwZ6uNPV7IEL4lZVhrb29YR7dN0FZp8ua2oMvQGqRnBrH+hwpL+JGvQpOXxAefzBywQ6Fos69V17bDJPbjrq152HN7GLIGPDeof7Ii6hUFLhMU8IX5iIf6XXAFxA1ikuUI3z7bWpJ8vWvT8r+TJjwOY4LALgLwHsgIn+F47hDjLH7GWOX85t9lzF2iDG2D8B3Adw00fedNKQg/B3tFvTbaZvOYReqTckJwpQjFF/FWDMfe4x+9uyhYpKVK8nVclt8x6oQ4Y9bw7/ySuB//od+T4fwZ8ygi1Bra8JNuqxu+IIhzPHyMlNNDUoMGgzYRYS/di1587/xDSr0isFhsx0quQyzSnNT/w+dnVRZqVaHP/dDpY2AQjFxwucj/MqC5Bo+QNZMaepVYoRCHKwuP0z6xNE9ABTw7RVsLj8RoJK3w/KJ21CIQ++HVGiVu/psmHLUWFpjxPuHYlZzc+YAhw5l95/IAkIhDv12D6qMWviCIRzvd9ADW7dSO5N4NSTPPkutIi6+eFL2KSs+fI7j3uY4bgbHcQ0cx/2Kv++nHMe9yf9+L8dxczmOW8hx3Pkcxx3NxvtOCpJIOqEQh68/vR03P7MDvkAIHRby4CeDUR+ngdrwMHDnnfSzZAm1Jxb60LzzDg0kiYEQKfSOjEPSMZuBf/wD+M1vSFoRCL++PvFzBKfO9u0JN2nl3Th1Lr6Vck0NSgxq9IkJPzcXeOklGopy221jLJoWpxdGvQoKeRqHYkcHJWlBq6k8rRLtrhCwcOGEdfwuiwuFOSron30a+N//TbrtdBhk7g0E8ewn7bj+qa3hhn3TBQ4PdRMdUzQXA6FjpsXpowh/Id8zidfxrS4f5nYfQ1CloipbABfNLcHRPkc4fwaAnDotLVQ7MlG0tlJNQBYwNOqFP8jhojmlAESyzoEDdPtIzBCfoSHgX/8CvvY1CmImAVKlbSyECD+OS6fX7oHLF8ThXjt+995RDDq8YYdOIgjtFYbE1bZCYuqRR4AXXwT+9CdyzTz1FDUCe+yxyLYDA4DNBjOvBY4rwhciib4+4L336L2qqgBtkmh23jz6ufNOckTEgWDJLLXyJ0h1NUoMmmgNH6AGbb/6FXXnfPzxqIesLn+46jIu7riDngvQ5yZU8gKoMmqpHcLy5cCOHWlXBsdDl9VFMtHjj9P3kQQne8zhuiP9OP93G3Hfm4ewpWUYuzuylMjPEoRiKoHQE0GI8K1Ovg/TmWfSA/z5MeDwYmHvcdhnzgvr2QJ5vn9YFOXPmUNS0Hga/sXiyiup+V8WYOaDsxX1JuRqFNjPE763lQI67s03o6fDvfgi5S8mSc4BJMIfC3GEHxONdvBFRk3FOXjy4xMAgGpT/KISAcIA7L4REVELhH/WWdRK+PbbAZ2OnAdf/CLw9NO0H21twLx5CHzjdlicPuhVcgw7faR5ZoING6hPfVERVRInc+gIUKnoefPn0z69/PKYTVoGRlGUq4bG3E3LUK0WJQYNhka9CMQOtrjnHmD16jHTsGwuX3LCf+UVqnx+660xhF9t1JEUs2IFMDo6IR23y+Im/T6NBDANQTl5Ef5P/3EIGqUcj1y3GMA4V32TCKEhWr4uVYRPjzv6BilZ2dhIc5X582PQ6sS8/lb4Fi8JP6fapMOMkhxsPCaybGfTqdPZmVTGzAS9fHBWnq/BvPK8cITfvO0g7Cod8csTT0Se8Je/AIsXh1czkwGJ8MXgOIrwtVoi3JHozPqJYSL8//3q4vAkpFSSTmGOClqlHJ0WEeELxSW8PBGFu+4iB82jjwKXXgoMDiJ4jCIXoX1Dxif4hg0kG11/PfDmm6R3piJ8ACgsJEvl8uXALbeMSeC2Do6isSiH+uDzRFxi0IDjgMHRmChfJgPOO49OKJHdzObyhyO9MXC7I7r/9dfTkl30mVUV6NBtdSO0jI8MM9TxgyEOwRCHQDCEHpsb9ZoQffbDw0ktcbkaJTz+0EmZ1mR1+tBjc+OaZVX4woIyqOQy9E03wuflS2MKwhckH28Xv5ouLaXvlyd8374D0Ps9kJ11VtTzzm4oxK4OayQJOnMmHV8T1fG9XjIYZGkmsxDhl+dpsaAyD0d7SYrytJ7A4ZJ6HF64kqbD+Xwkt+7eTSNGJxES4YsRCNDSsKGB/o7R8duHnFArZJhRnIv/uWYRzmkqxMwUyUbGGEWiVpHm2NlJ1YLx6gxWryZN8p57gBMngKVLwXh56QyB8DORdTo7aaVw/vnAzTfTktHhSG7JFMNgoFJ2lyuqopXjOLQMjKKhWE9RcZjwKWcxRtYBKGcQCkUNMUkq6QhOhv/8z4hcI4rwK406+IIhDJRWAwUFGev41z2xFSsfXI/fv38cwRCHmV6RNJJEx83VKNAw1AXff2VnqlcmEPzc8yvywBhDaZ5m2kX4Qr4qVSFdPt+XKNDNn2dlZVGEr9xB+SP96pVRz1tRb4TbH8T+bj4YUKspgJko4QuFnr29WenP1GtzQ6OUIV+nxLyKPPiCIXz3pT2osPXDV1GFx+deRKvJ1auBH/4QuOYakjAnERLhiyFEsAkI/8SQCzUmHWQyhuX1Jvz11uVhS2YyVAnSg4DOTtLQ45WcMxbREJ95BvjCF6CyDEEV8GMZ7+/PyJop6Pfnnw8sWEBJYiC9CF/AueeSg+KDD8J3DY36YPcEMCNPSRcUPskrSFj99jgkJCSJ+aQ0x3G8pJOAGATCP+880tY1mqjlruDF77TyOn4GEb43EMTuTit8wRAe/4iW8LWjIpkgSWuNXI0SX933LvT/+e9pteDIJg6aifDn8pO4SvM00y/C5yWdVElbhVyGPK0SXB//GZaW0nnBr4AN+3fDojNAN3tG1PPOrKPum1vbRBPVmprimh0ywsAA3YZCWZnJ3DviQXmeFowxzOe/r0PtgygdHUbJgln4V/lCeCur6Lj9yU+oA6g6ubNpopAIXwwhYSsQU2yEP+xEbQrNPh6qjTp0WlyR4quuLjqwE+GWWyjC/OpXwxWFxU4LFlWRr9mcSfHVhg2AyUQJWCBi+xR0z3SQk0P5BhHhCwnbua4Bir7nzgWQgvCFCyl/Yjp9QQRCXOLulMLnX15OzgW7nap3eVTk03uZbW7gjDNoEEaaJeknhpwIhDjc94U5eOs7q/CjS2dhptcS2SDJCW/QKFBj5fdtx46E200GDvaMoNqoC0/bKsvTRLuipgGsLj+Ucga9KnUwZNSrIBdWU0KEb7MBdjtKj+zFsZo5YwIjo16FWaW52Nom+r5EF4pxQyB8YFyyzoajA7jn1X3h89w84kYZf4zWmHTI1ShQ77GCcRyqFs0G5HK8/u//Rc68++/P2uS2ZJAIXwwhwhcIX+TUCYY4dA67UFc4HsLXwuULRlosdHbG1+/FKC6m28pKAMDcoB16tQKFOepwuXZKCMVc550XOZjuuIOaUQkdMdPFhRdSzcAQWTAP8AOp6wb4BDR/ATHpVZDLWHzCLy2lKJ0nfEHrzdemiPDL+Lo9ZfSFoYifOzDg8JClLxhMO3F3rI880TNLczGvIg+3r26AXFzWnyLCr7XyjyexrY5BV1f8bpAZ4EDPSDhaBCIR/nTpxgjQ91qgUyXtOiqgQKeEcrAfIbUG/72tD7ZCcuHgwAGUmU+gozF+AnNFvQk7OywRHb+qinIvLlfc7dPCBAjfbHPjey/twWu7usPNA3ttHpTlkROOMYbvXzADP55Hq1LdzAYsqS7Ai6yM7NhTBInwxRCiQ5MJyMuLivB7R6jIqHYchC9Ub3ZaXKQNms2pCV8AH+HPCFI5eUW+Jn1J58QJuricf37kPpmMouFMccEFdLtuHUa9AfxpUyuW1RagoL2ZXpOXdGQyhuJcdXwNXyajHiG8C8LGd0pMquErlfR9xIFBo4BGKcOA3RvxcKc58vB4vwMKGUN9YU7kTiEXwVjSCD9XyVA1wj+eSYT/jW+QC0OY2hSLLVvoAn3iRFR7AQE2lw9dFnfUYPVSgwa+YGhadWS1OH2pG+HxMOpVCPSY0a3Jw8PrW7DBzVuFX38dADAwd3Hc562oN8HjD0V0fGHFPJGE6zgJPxjicPcre+HlLz6ftA4jEAxhwOFBeV6kr9atq+pwjoq/INXW4vxZxTjQMzKldRQS4YshEL5GQzKCiPDbh6I7Y2YCQWvusrjoNUOh5JKOGHyEX+ehhGJZnjb9JJ1Yv58oli6li+AHH+CxjS0YGvXhx5+fA3bkCK2IRJ5+8uIn2Mf6+nCEb3On0HrNZloVJFjqMsZQnMsPi29ooH1Ik/CP9TlQX6SPnlvb0UGvU1iYNMI32gahDgYQ0GiJ8NONrvfsoTkLa9eObTWxfTuwahVVW9fX008M6QstdudVGML3CW6x6ZS4tbp8iZ1XMbhiUQVmMxf0tVUw6lU4puQvZq++ihAYnAviE/7yOspnhXV84XyaiKwzOEgaulab0es8+XEbtrZZ8Isr56GyQItPWofQ7/AixAGleTG1Lu3tFFBUVuK8mWTa2HR8aPz7nCEkwhdDkHS02jGEL1gyxyPpCH1fuiyuiAc/zQg/lGuAS6lGpYsIvzxfC7PNnd4SfvNmio5nz069bSooFMDnPofAe+/jqU1tuHJRORZW5ZOEEpMPKDGo4xL++qP9OKorIsLnqPweiLg1xqC3l76HJCjOVVOEJJdTQjddwu93YEZJjMNKiPBLS5Nr+N3ttPnKNYDVmp5ve2CAfn74Q1rlXHop8PHH9BjHAd/7Hr3ve+8B3/oWRZgxnSMFh868crGkQ4QynRK3VpcfBSmKrgR8YWE5ZoZGYWqoRl2hHgeCOvouu7vRYqqCoTR+t80CXsf/NJuEPzBAUmplZdoRft+IB//1/jGsnVeKq8+oxNkNJmxts4TbIgsafhjt7bRqV6kwp8yA4lw1NhwbGPvCkwSJ8MUQR/gVFTERvhMapQwluXEGhqSAViVHca6aJJ1kHvw4GHb50ZdjQpGdooDyfA1cviBG3H4EQxye3nwi8XL+k0+As8+O7wYaDy68EIruLtRaevDvl8yiCPT48XDCVkDcalsAj3/Uhn85tWQLHR4O90JP6NIxmyP6fQIUG9QU4QMk6+zblzLidnoD6LK4wwNrAJAHu7eXksJlZUkjfG0nFd0dWn0p3ZGOrHPwIN2uWQOsX0/f/+WXU6L5hRfIUvrAA8BFF1ExHhBpgcHjQM8IKgu0USsiIcKfSOK2ud+B257diRFXdorJBA0/bfT2AmVlqDHpcMLmDcuYe8pnRs2WiMWKehN2dVjhDQTDK+GpJvxXNx3DR//7ddzvPwLGGM5uKMSI2491RygRXR4b4YsszIwxLK7OR7PQY2cKIBG+GLGSTm8vyS8gwq816SGTjY88BadOOGpLU9Ix29zoyy1EgYWigPJ8LX+/B+8c7MX9bx0O2wqjMDhIZLxy5djHxgnfeSQNfS/Ujop8LRGS3x8nwtdgxO2PqggOhTgcMdtxRMtHbK2t6Wn4KSN8DQbtIsK3WlMOr2nmk2ozxDUUol77qSJ8eVsbvHIlDs4/i46VTAhfmPX7zjskH6xdS3UGZ5wRKfcvlvQAACAASURBVKkXLLMxK4dDPSNR0T0AFOaoIZexCUX4j33Uig+P9OPFHalnGAOgC+q//Rv5x2NAjdPS1/Dh8ZArp7QUtSY9zCMehPhzY0/5zKTtlc9qIB1/b6eNPsvi4okTflHRWMJ/803gtdfGbO4PhrDvrY0odwyhaB9N5Tq7gfJNb+yhYzBuhC9ymhn16inNv0iEL0aspOP3h10pJ8ZpyRRAbQDcdEAWFJDVMQ0Q4ZugGyICEiI6s82NP2+mSPNvu7ujW68CwKef0m0WCb+vqAqtxgos3cXnBgRHTBzCB6KtmV1WFxzeADryeBdGWxusLh9y1Aoo4zVO83io6jVFhF+Uq4bDG4DbF0w7cXtccOiII3xRr32UlRHhJ1optLbCbCyDNcCoriGeU2doiFYyAg4coNxASQn9XVdH7SIGB+kC9fDDeG2PmYi7rIyOQVGEb/f40T7swvzKaMKXyxhKctXj1vBtLh/e2k+rmb9+2oFgKIVUyHHAd79Lg8Q//nhMB1S7x48Ql7qtQhjChZWP8AHAWUzf+Z6KWUkJf0W9CTIWGbYyYWumOMI3myPFfj/8If3EYN2RflS08Z3e+YtzsUGDxuIcDDi8yFErYNCIgplAgC4kIsI36VWwuvwIpfrcswSJ8MWIjfABwGxGMMShy+Ial0NHQJVRB/OIGyFRx8d00MMTvrKPVhsVfIT/rwO92NNpw+dmFWNo1If1R2MqQ7dsIYfLeBw5CWC2e/DP2atRtHsrnRCHD5NcNGtW1Hbxqm2FhGNXPk94bW2wJauyFYggDQ0f4K2ZCxbQnSkI/2ifAxoFQ/Uffge8+irdKSb80lIqd7cmaErW0oK+okpqoLZsGZXEiyszHQ66EIjL5A8epOheLK8tXQq8/z7w1FOwLFqGe17dh+e3ddA2DQ1REf4HfA94sUNHQGmeBn328bXNfn13D3yBEL63pgk9Njc+PJKkUyTHAd//PvCHP1BdBjBmKpqQl0nVOC0M4XvmI3wA6K2fDWdRKZpNVShOIqHmaZVYVJWPTc1ZIHyOo4uvQPiBAF0ArFaS3Vpboy/gAP5vayfOtLbTH6LvSojyy/Ji9r2nhy4iompxo16FYIjDyBS125YIXwwhwo8hfLPNDX+QQ11h5g4dAdVGHTgO8J/oSN+hA5JuLPlFYIEAMDiIwhw1lHKGN/b0wKBR4H+uXYRSgwYv7aADfXjUi689tQ22dR8R2SfriJkh+kaI8BnHUVOzw4cpWtFFfy7xIvxDfIWoR6mBp6iEJ/wkWq+QP0mp4QtefC+1gairSx3h9ztwz5F3Ifv5z6mqORgkwpfJ6GQX3jOejs9xQEsLBkur4PD6ifDd7mj//333EfG8/Tb5wkMhIvx4TbFWrgRuvTXcBVWYoobGRqClBYfNdtzw5234t1f3odqow5I4Q0XG216B4zg8v60DS6rz8Z3PNaIiXwv17bdRAjkeHn2UOrz+4AdUBQ6MIXxBnkhbwxfVWgiE/9FlN+KpP78LyOUppaFzmopwoNtG+aCJEL7TSd+jQPgARePi1ZvQ1hhA2+AoNrcMYbmlnb+jLSz/hgk/P45DB4iO8MPzMqZG1skK4TPGLmGMHWOMtTDGxqx9GGNqxtjL/OPbGGO12XjfrEOI8AVJBwB6enCC75I5IUmHX67KerozivDNNjf8pZF9kcmofwoAXLe8GgaNEl9ZWomPjg+iZWAUtzy7E9uP9kK/f09W5RyAKgdbTVUILlxIPe4PHx6TsAXiE/7BHnt4dWIrreQlnTT66KQifCHCt8ckbpNAu+0T3Pz3R+nE6+4mi2RHByULlUqK8IH4On5fH+ByYaSsiqaYCS19BQltzx7g4YeBRYvoeNqwgfIDo6ORauc4EGorOoQWHA0N4FpbcfOft+Jgzwh+/PnZeP8Hq5GrGft5lRq04yq+2tpmQdugE19dXgOFXIYbVlRj8a6NCD7zl7F1ANu2EdFfdhnw+9+TbVShGBvhp9lHJwyRpJOnUyJfp0S71Q2zl4XzE8mwekYhQhx531FVRdXYdnvS58SF4MEXE35XV3R/JtFx9equbuiDPpg6W+g5Xm84SFlRbwJjiPLgA4heRfIQPiehHcVkY8KEzxiTA/gjgLUA5gC4jjEWW7d/KwArx3GNAP4bwG8m+r6TgliXjskEfPgh2idgyRRQbdRB53NDabNmRPjdNld0xAHK/CtkDDedXQsAuHoprRiueuwTHOi24Sx7J5R+Hzl0soi+EQ8MGgXk111HBHDoUNwWDUJBVHSEb8eKehN0Kjn6Cyv4pG0afXQykXQAIvzm5oQVl9a2LvzqxV9gtLyKTua8POC556LcE0kjfF5Xt1fW0hCUxkb6Pr/zHeCb36RK5sJC4N13Ab2edHohMkzS9jYS4dOxhsZGMK8XrLcX31vThNvOqU/Yt6ksj5xbDm9mDb+e39YBg0aByxbQ/3tdhQx5XifkDjsG3hENnh8eBq6+ms6JZ5+llZBSSaQfG+G7xhHhMxZuJFhj0qNj2IXBUW9S/V7Awsp85KoV+Lh5cGLWTIHwi4qii7g+/ZS+t/z8KMI/MejE+f5+sGAQuOoqupOXdfJ1Kvzyynm44awaREGI8EXnv/A5DY+eIoQP4EwALRzHtXEc5wPwEoArYra5AsCz/O+vAVjD0qm7nmqIk7YKBbXk/fvfsXn7MZTnadI6ABOhKEeNGleMZzgFAsEQmvtHkd9YS3fw7pMbz6rFjy6dHS7brjLqcF/XRvzi5V/hwfMqcLWXjySyTPhmoVT8mmvojmAwLuEzxqKsmQN2D4ZGvZhbbkBpngbd+SVAdzecDmfyPjoKBZFnEhToVFDIWLQ1MxRK2Dlx5M9/QbHTiuY/Pk0J1K98hao6jx6NEH6yCJ8/qd01daThM0b1DrfdRjLHjh2U0CwpIYulmPDjrIbC/y5P+DaXn/Rcvu9Qrc2MhuLkCX5hxZeJU8cXCOHDI/24YlFF+EKS1xwZRPfmA0/hgbePUDLxe9+j3k6vvkr96gXMnDmG8G1pNk4Lo7eXImR+wlOtSYf2YScGHJ60zjeFXIazGkzYdHwI3ESsmUKnzOJiOuZUKlqZbdtG+YqYlaPF6cOiAV63v/pquhXp+Ncvr8HcGEcV2tspmNBEIn9B0pkqp042CL8CgPgT7ubvi7sNPwN3BED8evmTCY+HohdhvNgttwA+H0rfegNfO6smrd4giSCTMcwP8UvNNCP89mEnvIEQqmbXhYtRAODzC8pwy6q6yIa/+Q1uev73uPzIJnzlzquwbOc6dOSXwmYwJnjl8aHPzjeDqq2NJO0SNGGrK9RjR7sF3kAwnLCdW25AqUGD1txigOOQ229OXnSVpMpWgEzGUJSrjkg6QuJ2//4x24ZCHHo278SQLh/V5/P7f+ONpN/290cIPzeX8hKJInyFAoGqKtg9fpJRqqpI325pAd54g5reASR/dHeTz76mhnIMCWAWkXXnsCtszay29qGhKDnhj6fa9kCPDR5/CCsbRachf2HyLV6Cz3fvwROb2rBz836S777zHUoyizFzJq2mRJPGLE4/VHJZWo3TANAFUpT0rzHpYba5YbZ5knrwxThnRhF6bG505fDBwUQi/OLicCUs1q8nF9KKFUT4Bw6E/9dhpxezelvoArhqFXFGqgI88SqShyDpWGJnXk8SskH48VgwVkxMZxvakLHbGWM7GWM7B4Wr7lTB7aarr0DsCxeip24WvnJwHa5blr4Mkwiz/byFLU3CP9xLroDZlfkUGcTzl//612QZu+46ssk5nSg5vA87K2aHO1pmC30jnojz4JvfpEgoAeHfuqoOvSMevLKzO5ywncNH+Ie0tHyvsvZNqOhKQLjaFqCLkVIJtLTglZ1dOPNXH+Ife3vAcRx++94xaFuOwTdjZsT9sXJlpFmecDIyltiL39IC1NYiV6+FP8iF+6fQP1RFI/KE4+dSvjDr0KGk+j1AEX4hH+11WJxAVRWCcgWa7H0oNSQv9otE+Ok7dbafIAeS0HIbAF0kq6qguuFrKOtpQ+VIPwqeeYIS1d/5ztgXmTmTtGtRRbDVSRPM0gqOenooal67NnxXXaEOIY4i3nRX1Oc0EtF/5FBQgDBRSQcgwt+zh34/6yzKyTidYVK3OH2o7zxKxgilko6dmEK5KHR1kTwkWId5qBVy5KgVp1TSthuAWKOoBBA7ATy8DWNMASAPgAVxwHHcExzHLeU4bmlRvAEhkwlh2hUPm8uHp2ecj3l9LShoOTLhl69zWxBkMnBpEtmRXjuUcoam4lzST2MJv6sL+NGPSGJ57jmKNLZvh/MLV+ClhReHu/aNB8OjXix/4ENsOk4XXW8giKFRX1hGwo03UlSsj5/XWNVYiGW1Bfjj+hbs6bTx7WGVKMvTYI+aTtCmoY7EJfhpFF0JKMrVRCJ8uZwuqO3t2NNpxYDDi++9tBdXPfYJHt/Ygjm2HpSdFRmZB8bofwGi3BMJq21bWoCGBhj4lYk9mZ2utDSS1E0xts5sc2N5PUXbHcMuQKHAYGEZZrkGUxb7FedqwFhmEf72E8NoLM6BKUdEqgcO0Arp858HAFx6dDOqX38e+NKXxkSmACIdV0WyjiWToqt336Vb4cIIivAFJLNkilFj0qHKqMWmEzb63sZL+Dk5kfNfkIfy86kxoKjGIxji4HK4UNLZGpkvEWOjHYN776UL5733jnnIqFedUpLODgBNjLE6xpgKwLUA3ozZ5k0AwmTeLwNYz02nfq4CPJ4ofe3F7V14beZqhFSqiA1tvPD7sXDHBrQZK9DnSi+5dqTXjoaiHGrwFa/cW0gC3XJLRIaqrobm729gX90CtA4603qfHpsbFzz0UVSJ98Zjg+i3eykZBqB/hAi1VOw8SCK3MMbwgwtnoM/uwbqjA5hbbuCfr8WANh+jtQ1Y2bEvcWvkTCJ8gzq642BdHXDiBPrtXswqzcV/XDITB3pGcEUxg8Y1Charpd95J/Dtb0e7muJF+LwlE42NMGjo87anGmZ+2WV0myTC9wVCGHB40ViUg6JcdThxeyKvFLW21ANWVAoZTHp12hp+MMRhZ7sVZ9aJonufj/IY8+cDTU3gGhrw/S0vQO0YSWzTjEP4Sa22sXjnHQpkRJ+N2AmXboTPGMPyOhN2d1jBpWHNDIY49Ns9ONA9EqkGF4quBAiEv2IFHedz5lAwsW8fbC4fGgc7IA/4owcKJSL87duB558nC3CcC2fBqUT4vCZ/F4D3ABwB8ArHcYcYY/czxi7nN/szABNjrAXA3QDGlq1NBwiSDihh+tdP2zFnbi1kV15JA4YznJkahUceQUHbMfz23K+juT+9yPtIrx1zynjdN16En8DJIpcx1Bfq047wtzQPoWVgFK/tilxQhIZOh3tJfzfzcsGY3iBJcHZDIVbUE6kICawyXp5oXngWVnQeRIE8zlxYr5ecIWlG+CW5Glhd/ki1cW0t0N6OfrsHFfla3HleIz69dw0emsevJmJlqKIiKiYSr1biRfgbN9Kc47lzwxWUKYeZX389kUaSjqX9dg84DqjI16LGqEPHsAtuXxDHckpQMtCVVjfOTAahHOm1w+EN4IYP/wr8619057FjZMVcsABgDOzzn4fO70Vv49zE9t6iIoqAxRF+uq2R/X4aqHPppVHFaAU6JXL5i2kmJonF1fkYdvrgKkkQ4a9fD+uAFfe8ug+zfvIOlj+wDl/4w2Y8vI6fTyAUXQkQEz5AvDBrFrBvHyxOH+b38fKNUNjY0EB6vyVGuOA4srOWlMSt1gWo2vaUIXwA4DjubY7jZnAc18Bx3K/4+37Kcdyb/O8ejuOu5jiukeO4MzmOm+AsskmCSNJ591AfzCMe3LyylqbRGI3AOedQci7TxUlPD/Czn8F3yVp80Lg83MslGSxOH/rtXswWCL+ykir9xB7jJF71huKctAlf6ML49sFecBwN9RaknMNmOziOC0ePY3qDpMA9F82EQsbC7WyFFcIntYugDXhRemj32CeJvNnpoJiv7A0PTq+rA/r7YRsaCRdmFeaoIT/Gu1DSmfZVWkonsGDV9Xopb1FfD9x0EwxaPsJPVSFZX0/abZKLl+DBL8/XotpEPZfahkbRmV8GlcsZbu8RxpNPAv/4R/Tu5mnQm+YktO0nLND4PZj1p4coeg+FIk4iIel9OcVqGy+9PnHzPcbGOHWS1laI8ckndCyL9Ht6SRaO8tNN2gLA4ip+3nNuERG++BwdHATWrME7V9yKv+/pwTXLqvCLK+ehqTgHuzv4aurYCF+Q98RON96pYx2w4EuH1iNgyIvkf4RpbrFR/ltv0f/6y1+SGSAOTjVJ5/SBKML/8+YTqDXpsGZ2CR3Uu3bR1Kdvf5sKazLB3XcDgQBUf/wDTDlqtAyk7o53hI+sZ4sjfCA6yu/tJfuYcawbp6EoB11WV1QDs0TY3zMCuYyhy+LGIbMde7tssHsCWFFvhNXlR++IJxzhjykXT4GltUbsu+8iLOWTg8Lz3zTOgF8mR/6Wj8Y+KU0PvoBI8ZUocQtA29sdbvMAgArFjMboEzsRhIuNcPF58EFqRvfYY4BWK4rwJz7sWrBkluVrUGPUo8/uwWGzHe0F/D6Ik4Ht7SRB/f73Ua9RwbfNTgfbT1hwnttMHvLWVmrvsH8/JR/5QTZYswbf/MGT+OiMC5O/mIjwQyGaUWzUq2hgzo9/nPh5b79N77dmzZiHhJ46mUT4M0pyoFPJ0azKp/NY1Bajde9xAMAX97yLt2+aj19eOR83rKjBinoTDpntZD0VGqcJWLuWbKjC4B+ACL+rC7OuvhRLeo5i4P4HIxfDRIT/xhu0ChK32YiBSa/CsNM3JVPLJMIXg4/wd3VYsafThptX1kUq/QoKgH/+k0rpX3wx/dfcupXaENx7L1Bfj8binLQknQjh81FBPI+xYF2ME4E1FueA4xCuEk4EfzCEI712XLmoAnIZwzsHe7Hh2ADkMoY7VtNBfNhsR9+IB3laJXQqRRr/dDT06shzjHoVVHIZjrlk2Fs+E+oN68Y+Ic0qWwHF4VGHoggfQKWtL1z1S/8I37s/HQeJ4MXftYukhwceICfURRcBQDhp60gl6aQBgajL87SoLaQWHBuPD6JTIHwxifz619TnJYZYKvK1cHgDKSUmjuOwo92CS5y8syY/H/jjHynCnzMnaozkUNMc2FMVc82cSUHI6Gi4cVqBVklR7Z/+FHdyFwDS71etimtVXVFvwuwyQ0bHmkIuw4LKPOxl/PkiOk8+3ED+ea3XjRn/fCV8//yKPIx6A+gYGh0r6SgUwJe/HH2s8IlbXXsbbv/Sj6G4+abIY0KkL/5eOI4S0xddFMmxxYFRr4IvEILTlzo4mygkwheDT9o+vfkEDBoFvnxGZfTjMhk5GHbuHKvVJcKDD1JUeffdAICmkhw0D4ymvJof7rWjOFcdcVEIVs7YuasJSLGR926nsmY294/CFwhh9YxCnFVvwtsH+rDh6CDOqCnAsjojGKN9oaKrzGcBxIKxSGuInU1ngO3eTXq9GML/mG6EbxCqbXnC5yP8ypGBSITPcQkrg+NCuMB++ct0wup0VFDFIxzhu7MQ4Y94YNSroFXJw9PRNh0bBGrriHAEuaWzk8wDOTn03YuqiSNts5NH+a2DTgw7fVjcd5z+x7vuIh1/y5YxTqI8rTJ1Uy8hcXv8eFiWKGZ+irKHhsjLPmYnWul/ErlzxPjaihq8871zkr9vHCypLsCOAJ+H4Qm/d8SNlv38Cqm+nnoB8Y3u5vKTw44e7aT7Uq38zjkHuP12vP7b57C+8czo4jKdjs5FMeHv20ffU4xsFQvhdaxTIOtIhC+G2w23XIl3DvbiuuXVUZFpGBdeSJpnvAM5FocPk9b6ne+E2yE3FedixO2P6M0JcKTXEZFzAJJ0ZLJIPw4gqZOlvkgPxpBSxz/I6/fzK/Kwdn4pTgw5cbjXjvNmFiFHrUCtSU8Rvt2dFcIHIjr+gbkriIjXxUT5u3dTkisd6QW0JGYMGBQkndJSBNUaVI30R6x9g4N0kU6X8OfPJ6vr00/Td3jwYCTqB6BRyqCQsdRJ2zRgtrlRzudGBFuiwxtAdYWRJI/f/Y5+HnyQnvDTn9JtWyQVJjw/FeELE6LKjx8ky+gdd9BxNTIS0e95GDIh/GPHwv1gilyilskvvRS9fShE76nXU5VzFrG4ugA9el7e5KXPv2xpR6GwP7/4BV00//Y3AMCMklyo5DJ0HOXPqVTHm04H/OlPOFwzGwZNnLbesU6dd96h2xRDyk36qWugJhG+GB4POlwhMMbw9bNq429z5pm0DH3//dSv95vf0EFy113hu5r4MvmWJLKOLxBCy4ADc8pFhK9UEumLCT9JhK9RylFZoE1J+Pt7bGFiv2hOaXgFe/5MOvjnlBlwuJcknTHzOccJ4cLRP2NueE5uFHbsIOkszcpmhZxsieEInzGMlpSjcqQ/Iukk6N2fEIwBN9wA3HwzJTArKmIeZjBolamTtmnAbHOH3U8FOiVy+UCjoUhPF5svfxn4j/+g/MHNNwPnnUdPFJGL0JhOGK2XCH/b3Y1F+iCU7W30GVdWAlfwnVDiRPgp/7/GRvqsjh+HxUnbmpy8fl5VReTqESWTH32ULvAPPZRRT6l0sKgqH0P6AoRkMqCnBw6PHy9s68QyjY8uMNdeS/vLr9SUchlmleWiv4VfUaZZ92Nx+eM7kRoaovMt77xDQ+tFgUI8TGW1rUT4YrjdGPTLMK/cEF4ij4FCQVHX++8nd+t0dFBJ/Te+EdUPprGECP94krFmrYOj8Ae56AgfIA+vQPheb8oBIQ1F5NT5tHUYP3rjQNzZmQd67Jhbbgi3KFhRZ0J5ngaz+GlQc8oN6LS4MDTqG9v9b5wQIvy8XB0N7RZ/lg4H+cGXLcvoNanaNnLCDBdXoHqkPxw9ZUz4acCgUVA/nQmA4zj0WN3h440xFu6s2lCUQwHDSy8BP/sZff/33hs3QViYo4ZKLkNPEqfOkV479nTa8E0dT8hCUdiPfkTVpIIFUfj/tEo4vIHkwzk0GiLKnp5whJ9v51//rrvIiSMUWB0/TheutWvpvMgyinLVKC/MgT3PBPT04Jkt7XB4A1is8tCKUSYjp9W2beEalnkVeRhp540Qaa4oLU5vfMJftIhW3f/4Bzm8PvkkpZwDACY9yY5T0UBNInwxPB4MBWUpe5fgwguJeJubE28jOHl47V5AUY4aeVplUmvmjnbKD8xJRvhpWBcbi3JwtM+B657cihe2deKn/ziIQDDiexcStvNFQzUeumYhnrt1ebg0XrwPpdkifD7qztcqgYsvpmX2Ud4yuWsXkX+mhB9TfNVXUIoq+0CkSvXwYVqZpZkXSAcGrXLCko7dE4DTFwxH6ECk+CjcNE0mox77wng8o5GSrSLCl8kYyvI1SSWdF7d3QqWQ4dyRExSVCx7yM84gcsqP7rVv0CjAcUjdhZOvERFcUgY7n5O57jq6GLzwAhkXLrqILhBPPZW9OcsxWFxVALPeiJ6DLXjog+O4ZG4pChzWSJTNVxHjvfcA0ED4kgE+wZvmsTE86oNRH8dB9M1v0md5003An/9MfXfSIHzjFDZQkwhfBM7jgTUoS9mdUHBqJJV1Nm2ipXfMspUxhqbinISEHwpxePaTdsyvyKMlvRg1NVRtGwik5WS5YlEFLltQhoevXYSHr12ELosb7x6KVI8KCVvx2LyyPC0aRf//XJGslHDVkyEESSdfp4rom0IUKMyHzZDwy/O16Bx2hZPhnYZi5LvskSlFmTh00kSuRjFuSUfQxs0iD74AwZZYn6wdNz8gRYzyvMTWTLcviDd29+Dz88ug3bOLiojyxk7PEiMvnfYRQJjwWwedKM/TQDU8RJ9zWRl1knz1VWr/kZdHCeIsXnRjsbg6H93aAjjaOnDRnBI8fN0iCo4Ewp85k85JnvDnV+Th4uOfwjZnQfqSjtMXWTmKoVYDL79MeYp77qH/N2bVFA96lRwqhSzcWnoyIRG+CJzbDa9CNZZoY9HQQBn/WO05/EIcRf8xo/8ENJUkLor6uGUIrYNO3LKqdmwDqpoaihrM5rS86vMr8/CHry7hib8cdYV6PLGpLUyKB3oomTU/ztg8AUW56nBTr6xF+CK9GjU1wOzZkQTXjh0UxaZoixyL2WUG2D2BcBFTq55/fnt7ZOJUFuUcgJw6mfrwgyEO//3BcSy6/338/J+Hwpp7uaig7foVNfj91Quj+9zEIk7vlvIkXvy39pvh8AZw3bKqSI4kBQTracrEbZjwRylY6u+nWRIKBdUMnH02uYt27450WZ0kLK8zoT/XhCqPDX+8fgnUCjkRvjBLmDEKMj78EPD7McNnwaLe49i7/ILkL8yD4/gh7TkJqokbGmgFA5ASkMSOKYAxBqNOBYsk6UwhQiHIfD54FCrUp5J0AIry16+P7zMeGCDtsqkp7lMbi3NhcfowHMep8/TmEyjKVePz8+MQudCHo6MjY6+6XMZw2zl12N89gq1tJBkd6BkJJ2wTgTEWziVky6VTVUADXMJR7dq1wEcfUTfCNMkoFsJK5DDfivmwhm/7e+IErcT4astswqBRZuTDtzp9uPkvO/DwumbMKjXgmS3t+OW/KLcglnQq8rVjLcGxaGig40A0S7cin9or+INj21W8sL0TjcU5WCYfJUIW9PskSDvCLy8HhobQabaQHNrfHyHYuXPJ8nnTTdSLZpIxp9yAL6xdBv3oCJQ+L/UIsliiE6cXX0wrv61boX6TKpbfakwdiQMkwfmDXPwIX8DVV1Otzi9/mfZ+T1W1rUT4AngngU+pCi+pk2L5chpbJ3bNCDhOlX3hqsUYCE6dWFmnZcCBj44P4sYVNdQwLRaxhC+Tpb0MBYCrllTCpFfhoQ+O4Z5X9+GVnd1YVJWfshvj6qYizCzJHVfRVTyYctR47wercfki/qJ2ySV0Yr76KkXk4yD8xFVpAQAAIABJREFUWaW54ZoBjz+II2qe8NvbyXtdWkpulyzCoFVk5MO/68Xd2No6jAe+OB9vf3cV7ji3Hu3DLijlNM4vIzQ0ENmL6jLK87UIcdGjJQGSjfZ02nD1GZVggmSWAeGnFeEDyLEO0epYTPgnAflNtfSL2Rxpeywm/DVr6OLz3nvAa6/BXDMT6wJ5aVW6WtId4XjttRHLahow5agkW+aUgid8nUFPy8BUKKDeHRgZGfuYkMxNRPi8U0eophXwzJZ2qBQyfHV5AruakA8QCL+kJKOoSaOU4+tn12JHuxVvH+jFl8+oxG++vCDl876xuh7v/WB12u+TDhqKciI+5tWryY3ywAP09zgIX6dSoK6QagYGHV5YtAb4tTqK7t95hxJqqjS7OKaJXI0Sbn8w0rRNhFd2duE9Ub7kQPcItrQM456LZ+Cry6vBGMMPL5mFey6agcsXVqS86I5BHKdORYFQfBVN+JubqRfPeTOLKSmuUIzx3MdDRpIOgBLH8NgI/2RANI86bG4Q709eHklLL7wAbNmCwYsvg9XlT1mVDoiGtKfbAjpNiCP8w2Y7trYNp3jG+CARvgCe8A0FiacSRUFIeMUj/OPHyTefwGdcaiDb4wvbOsOWt74RD17b1Y0vLqpIrN3qdBTRd3Rk1D5YjDvOrcfjX1uCrT9agwe+OD9KSjhpUKvJntncHO0eyRBCzUC/3QMwBm9VDSUJlUoq9skyhBbJ8WSd3713DHe/vBe9fA+iJz9uQ45agWvPjBwTjDHc9bkm/NdXFo55fkrEIfxE1babW4ZQnKvGjJIcqv6cM4c+8xQISzqpZCue8EsdwxEN/2QSvrjvVH8//R7rhb/kEpL7ABTffD0AYP3RsbblWAiknFTSGQeMelW40vbX7xzBnc/vTqsPVqaQCJ9H0Ell6gWmLBF+Q0PChA1jDN86rwHNA6N4/zBFIA+va0aI43DX5xqTv69gzUxSdJUMaoUcl8wrC7cGmDYQ3DqzZiXsKpgKc8oN6La6I1KZIIF95Sspi1/Gg0g/nWhZx+byYdDhhdMXxP3/PIwemxv/OtCL686syt7nXl5OFkcx4fPJ8B4R4YdCHLa0DGFVYyGZAPbuHTN1KRH0KjnkMpY6wucj6mqPDcXyIEmd04Xw40X4AOn4ADB3LspWLMbMklx8eKQ/5UsLxVFpD3lJE0adCg5vAJ+0DuHj5iHcsTrx0PqJQCJ8HgOD5FgxFSa3qoWRjPCbmxPKOQIuW1COWpMOf9zQitbBUbyyswvXL69BlTFF/mCChD9tIfiVxyHnCBBqBjbwkZqigW9oFW88XxaQqCe+cMFZUW/EOwf7cNcL1AL6ppV1yBpkMnKKiQhfq5LDqFdFEf6RPjuGnT6sbCwkPbu3lwqE0gBjDAaNIjXhG43wKVSYEbSDCZr5ySR8g4Eqa83mxIS/ZAlVwfIrvzWzi7Gj3Zryfx0OR/gZ5lxSQHD93P/PwyjMUeGGs+JMGMsCJMLn0d1L1YFFRRMk/FCICD+BQ0eAXEZR/oGeEdz+3E6oFTJ8+/wU0T0QIfyBgdOL8Ovrae6AqA1FphCGrGxpGYJKLoP6W3dQD5rly7O1l1GIjDmMjvCFKupff2kBGor02NNpw2ULyrIvn8WW8oPsnWJJR9DvVzUVkpwDpB3hA0J7hRSJacYwYDChxmONSCgnk/AZiwwM6u+nc1Ub89nLZGQT5YOBNbNLEAxx+Oh48jnallEftEo5tOkOaU8TgkR0tM+BO1Y3ZM0gEYsJET5jzMgY+4Ax1szfFiTYLsgY28v/xI4/nBbo6yPCLy3JT7ElD6Gtayzhd3VR24MUET4AfHFxJcryNGgddOK2VXXp9f+uqaF8A8edXoQPAD/5yYQi/KJcNYpy1XD6gig2qMEWLKACmElCbnjMYUyE3z8KnUqOGqMOv/7SAhTmqPHNcxuyvwMNDdRATeQuie2Lv7llCDNKcqin0DgJP1XU6/D40aMzosQxPD0IHyCZSZB00tiXRVX5MOpVWJdC1kl7oleGECp3C3PU+NqKyYnugYlH+D8EsI7juCYA65B4dKGb47hF/M/lCbbJPjguvuQSBwODtF3aSVulkpKosa+fwqEjhkohw90XzkBTcQ5uW12f3vuKZ2KeboSfBQiyTlQf/ElCop74zQMONBXnQCZjOLPOiJ0/vmBsX6RsoKGBahf6IyRVnq9Fj9UNjuPg8Qex/YQFqxp56+7evRT5ZlDUlqhj5mu7unHNnz6FLxBC26ATAzlG5NuGEksoUw0hwhdX2SaBXMZw/sxibDw2GNV+JBbDTh9MiYquJoDyfBpEf+d5DVlfPYgxUcK/AsCz/O/PArhygq+XXTz3HJGizZZy0yFewxcPMU+JvLyxhC948FNIOgKuXlqFD+4+N/1knpjwJ7FE/VSF0GG0dCoIX4jwx0g6o2gqGV/iOSPEs2bma+H0BWH3BLCz3QpvIIRVTXxNwr59aev3AhL1C/ro+CC2nbDg5R2daB0cRV+uCdrBvsjFJ81GZJOGioqIhp9mwv6C2cUYcfuxs8OKzmEXtrUNj/HmW5wZDGnPAJUFOqy7+1waqTqJmCjhl3Ac1wsA/G2ib1nDGNvJGNvKGEt6UWCM3c5vu3NwMLmelhJ/+QsNYuhPI/s+zHviY7W+ZEhE+Drd5JGxFOEnhRDhFxuym1SLB71KARmLlnQEh05Tqn5M2QA/2Uvo/AhErJlvH+jF7949Aj0XwPI6E8mAR45kJOcAiVskd1nI1fbI+hYc6BnBgKEQMrebxh0WFGS95iFjVFRQMV9bW9qrjVVNhVDKGW748zas/t0GXPPEVuwUZt7ySNhHJwuoL8oZ204ly0hJ+IyxDxljB+P8XJHB+1RzHLcUwFcB/A9jLKGgyXHcExzHLeU4bmlRBlWkY9DXRw3MgEgDrQQYcfnhG+WnB000whccOpP1xeXnR2yLJ3vZPA0hRPhTIenIZAw56ugGaoJDZ8ZURPjiQjweQmL43r8dwDUv/De2//Uu6D1Oah4XDGYe4WtI0omNdLutLswuM2DQ4cXzWzsRLOWDj927J8UCmzEEa2YwmPb+5GqUuPvCmbh8YQV+ehn1XdrZPpbwJ0PDnyqkTAVzHJewqxBjrJ8xVsZxXC9jrAxA3MoFjuPM/G0bY2wjgMUAWuNtmzX87W/kmAFSEv6JYSc0Ab6sOVPCj5WLjh8nu9dkgTGK8vv6Tn4UNQ1RX6jHfV+Yg7Xzpmb1Q5JHRNIR5hU3TkWELy7E4zGjJBfnzijCBXIbrvv9mzSo/P77qacNMK4I3x/k4PGHwtqyyxfA0KgPN6+sQ0W+Bh8eGYCmpoqecOwYcO65Wfn3JgTxCjuDC9C3zovEos992o49nRHCd/uCcPuDiRunnQKYqKTzJoCv879/HcA/YjdgjBUwxtT874UAVgI4PMH3TY1XXolUE9rtSTdtH3JCLRD+RCQdv5+q99JI2E4Is2dH9FsJUWCM4eaVdVnr7JkKsQ3Ujvc7oFPJp66CWTwjAeTFf/aWM3HDu8+AqdXAl75EvYReeYW86RkeNwYtxYTixG2XhVxAVUYd7rl4JhgT9a/huOmx8hRPKBvn/iyuLsCeLlt4dTPMF11NlqQzFZgo4T8I4ELGWDOAC/m/wRhbyhjje4RiNoCdjLF9ADYAeJDjuMklfEHOueoq+jtFhN8+7IQmOM4IX0z4J07QEnKyCf/RR4HXX5/c95CQFmIbqLUMjKKRd+hMCWIIHwAlZ196Cfj+92ksol5PjcLmz8+4Y2W8BmqCfl9VoMWsUgNe/9bZuOZyUbfJ6UD4ZWURWXWcEtOiqnwMOrwwj1DblYM9FDhWG1O0T5/GmBDhcxw3zHHcGo7jmvhbC3//To7jbuN//4TjuPkcxy3kb/+cjR1Pitdfp0jj1lvp7xQRfsewC4VyXqOcCOELQ6Xr07RYjheFhWNmrEo4OcjVRLtYjvc70FQ8Bfq9AIHwxRr7j39MuZ577iG3zM9+RvdnKOcA8fvpdFl5wuerwpdUFyDPmEs98IHpQfhKZcQpNO4In2pyBFnn/UN9yNcpsaw2brnRKYHTs9L21VepQZQwbSaNCL9IGSJNXJbBR5KXRy4goSe+4AaS3DOfGRg0ERfLiMuPAYeXmpRNFWpq6BgcoopatLUBb70F/Nu/RTq6fvvbwG23ATfemPHLC3bhEVe0pKNVysdKG4JuPh0IH4gEReO0iM4qNUCtkGFvpw3+YAgfHunHBbNLoJCfurR56u55Ijh5R8JXvkJ6vEyWloZfKA9lFt0DY9srCH1ETrYHWcKUwaCNDDJvHqDAommqCR+IWDP37KFboRkdQNHuk0/S5KkMEVfSsbpQZdSOtRAKBDtdCL+8nFYd4zQ3qBQyzKvIw54uG7a2DcPuCeDiudPAgTQBTE7DhpMJvZ4q7Lxe0vAMhqQR/ojLD6vLjwJ5KLOELRBN+IV8cyqNBsiZwhNewkmFQaOEwxtAMMThED9ta0osmQJqa+m2o4PaUuzfT0FOlsY5xpV0LC5UFcRp8jfdCP/GG8fdalvA4qp8/HVrB97a1wudSo5zmjIbvTndcPpF+ABFNALp5uYmjfA7LDT0IA+B7ET4xcWT58GXMO0gtFcY9QSw6fggakw6VMYjw8mCeAoaQITf1ESWzSxA6BckRPgcx6Hb6o7f1XW6STpXXx3JX4wTi6rz4Q2E8Lc93ThvZtGktCyeSpx+EX4sUkT47cOUgMpFMHuEL+EzA4EQB0e9+KR1GFcvTTGLNtvIz6djXEz4E4xqxVDIZXxxGclWNpcfo95AfMK/7DLy4Z9GLT8WV1MexB/kTnk5BzhdI3wxUkX4/Fgzfcg/MUkHIMKfLtGNhCmBkNTccHQAbn8Q586YQHX4eCE4dRwOStqOw42TDOKOmWGHTkGcc+XMM4GXX044+OdURHmeBsW5aijlDOfPOvWDudPnm0kEgyFpx8wTw06U5Wkg93qyE+Fn+WSTML0hFCb9c78ZKrkMK+pNU78TAuEfPEh/pzGvNhPkioagdFqiLZmnOxhj+NKSSox6/dNvStw4cPoTfm4u9ahPgI5hF2pMOmouNRHC5zhJ0vkMQiCB/d0jWNlogl59Ek6pmhpg82aSc4CsE36eqGOmuMr2s4Ifrp11snchazj9JZ0UGn7HsBO1Jj15mSci6YyMUHc+ifA/UxBHfSdFzgGI8G024OOP6Xivrk79nAxg1KvQOeyCxx9El9WFAp0SOSfjwiZhwjj9CT+Jhu/w+DE06kONST++CP//t3f3QVbV9x3H3x+QuyjPiICwYjChaZD4kG6J1CSND2PQWIl5mOhkRqamYWzrxDqdqTpM69Q0nXZ0+hgbw2hr0lptYkOkigqatCZ/+LAmxkARRXxaEV0VAaWwLHz7xzl39rrcy+5y7u7de3+f18zO3nPuj3t+P8/62d9+77nnN25c9kti505fg5+ockkH4Ld/rUHnvnylztq12ey+zleJXbJ4Htt37eUff/xcdklmQrP7VtP6v6bLM/yIQ/5HeCm/Qmf+jLykM9QZPvTdXsGBn6TyTHf25PEj+wnbSuVr8XfsqHs5B7K/XL74G+3c8j9bmVAayycXNOgvGSssjRl+RPYJ3H5efCvbd2K5pDPUGT448BN31NgxzJjYxtkfmTnsi1fUVLkozjAEPsCffnYh0yeU2LW3l/bpI3QnUKu71g/88mLjVer45Rn+Eb9pC4cGvi/LTM4PrljCdY18Y2/mzL6f3WEK/CnHjOObn1sEwAdn+JPkzar1A7+8OlSVOv6Lb77HzEltHFM6qn4lnSEsEG2tYf6MCUxq5CV7Ut8btYsWDdthzjt5Nv915SdYdnrrfLAqNWnU8OH9M/znn2fj0TO4f8N2Fs+fnpV8ipR0XnklC/zp07M3cs1G2vz50NvbN8EZJh9tnzKsr2/Dq/UDv/8M/6c/hU99iuuvuo3Js07kLy/+aPY/ysEjuHkavH+G7/q9NcpNNw14G3CzQiUdSV+StFHSQUkdh2m3VNJmSVskXVvkmEPWb4a/d+MmACbtfJvbL1+cLYX3f9mHSQrV8F9/3YFvjbNoESxZ0uhe2ChXtIa/Afg88EitBpLGAjcD5wMLgUsl1eferYPRb4b/woYtAFz1yRP7bmO7N1vC7IgDf8+e7JbMDnwzG8WKLnG4KSI2D9BsMbAlIrZGRA9wF7CsyHGHpN8Mf9/LrwKw8Ni2vjblwD/Skg5k9zLxFTpmNoqNxFU6c4HKm9l05fuqkrRCUqekzu7u7kIHfmzrW/zFI13ZRj7Dj+3bASgd6Ft4unBJB7L3ATzDN7NRbMA3bSU9BFS7EfTKiLhnEMeo9mmUqLIveyJiFbAKoKOjo2a7gTzybDdf+14n+/YfYOXYsSif4bd15+vO7tvX17hoSafMgW9mo9iAgR8R5xY8RhdwQsV2O7Ct4Gse1sObXuf3/+3nHD91PC+9tYeeCRNp272b3gMHmbQjX+y5p6fvH5TDv63t0BcbiAPfzJrESJR0ngAWSJovqQRcAqwZroPteK+Hr9/5Cz48exI/+oMzmXL0OPaUjoFdu3jl7T0c996OrGHlDN+Bb2YJKHpZ5sWSuoAlwH2SHsz3z5G0FiAieoErgQeBTcD3I2JjsW7XNm1CiVuX/yZ3fO3jTJtQ4uQ5k9k57mjYvZsXn9/G+N58Zl+vwC+/KQwOfDMb1Qp98CoiVgOrq+zfBlxQsb0WWFvkWEOx5IN9qw6dPGcyb49pY97OnWzf/EJfo+GY4fsqHTMbxVr+XjqL5k5hd+lo9u3YyY7nKy4WqncNv1R6/2zfzGyUafnAP3nOZN4tHc3+HTvZ+3JF4Ndrht/Wln3NnFn3hSfMzOqp5QN//oyJ7B0/gdi1iwPbXut7ol6BD9ks3/V7MxvlWj7wx44RbdOnMPa9d5m88y0OlErZ7RbqGfhTpzrwzWzUa/27ZQITj5vOMXv3MOvdt9g/czZj9+6pXw0f4IYbfB98Mxv1kgj8abOOZQzBiTu2M6Z9NrzaVd8Z/pe/XLyTZmbDrOVLOgAz5maLLp+041XGtc/Ngr3arRWONPDNzJpAEoE/a05Wbpmy9110/PFZsPcv6UhwVBJ/8JhZopII/KOmTe3bmD370Bn+vn3ZPl9WaWYtLInAf986n8cfn31Iqlrgm5m1sDQCv/ITsLVm+Edya2QzsyaSRuD3n+FXq+F7hm9mLS6NwK+c4bukY2aJSiPwyzN8KftEbK03bc3MWlga1yGOH59dcjl9evbdgW9mCSq6AMqXJG2UdFBSx2HavSjpV5KektRZ5JhHRMpm+bPzpXldwzezBBWd4W8APg98ZxBtz4qINwse78hNnpzV78E1fDNLUtEVrzYBqBk+sHTZZXDSSdnjaiWdiRMb0y8zsxEyUjX8ANZJCuA7EbFqhI7b54Yb+h67pGNmCRow8CU9BMyu8tTKiLhnkMc5MyK2SZoJrJf0TEQ8UuN4K4AVAPPmzRvkyw+RSzpmlqABAz8izi16kHxRcyLiDUmrgcVA1cDPZ/+rADo6OqLosatqa4P9++HgQRgzxoFvZkkY9uvwJU2QNKn8GDiP7M3eximHe7ms48A3swQUvSzzYkldwBLgPkkP5vvnSFqbN5sF/EzSL4HHgfsi4oEixy3MgW9mCSp6lc5qYHWV/duAC/LHW4FTixyn7kql7Hu5ju/AN7MEpHFrhf7K4e7AN7OEOPAPHIDeXge+mbW8tAO/p6f4AuZmZk0izcCvrOGXA98LoJhZi0sz8CtLOp7hm1ki0g58l3TMLCFpBn61ko4D38xaXJqB75KOmSXIge/AN7NEpB34ruGbWULSDHzX8M0sQWkGvks6ZpYgB74D38wSkWbgl0s6ruGbWULSDHzP8M0sQWkGvt+0NbMEFV3x6kZJz0h6WtJqSVNrtFsqabOkLZKuLXLMupCy0HdJx8wSUnSGvx5YFBGnAM8C1/VvIGkscDNwPrAQuFTSwoLHLa5U8gzfzJJSKPAjYl1E9OabjwLtVZotBrZExNaI6AHuApYVOW5dtLU58M0sKfWs4V8O3F9l/1zglYrtrnxfVZJWSOqU1Nnd3V3H7vXTP/DLdX0zsxY14CLmkh4CZld5amVE3JO3WQn0AndUe4kq+6LW8SJiFbAKoKOjo2a7wipr+KVSVtc3M2thAwZ+RJx7uOclLQcuBM6JiGoB3QWcULHdDmwbSieHRXmGv3evV7sysyQUvUpnKXANcFFE7KnR7AlggaT5kkrAJcCaIseti8qSjuv3ZpaAojX8bwGTgPWSnpJ0C4CkOZLWAuRv6l4JPAhsAr4fERsLHrc4B76ZJWbAks7hRMSHauzfBlxQsb0WWFvkWHVXWcN34JtZAtL8pC14hm9myXHgO/DNLBHpBr5LOmaWmHQD3zN8M0uMA9+Bb2aJcOA78M0sEekGvmv4ZpaYdAPfM3wzS4wD34FvZolIN/BLJdi/P7t5mgPfzBKQbuCXQ373bge+mSXBgd/T48A3syQ48Ps/NjNrUekGfuWShl4AxcwSkG7ge4ZvZolx4Pd/bGbWogotgCLpRuB3gB7geeB3I+KdKu1eBHYDB4DeiOgocty6qCzpOPDNLAFFZ/jrgUURcQrwLHDdYdqeFRGnjYqwB8/wzSw5hQI/Itbla9YCPAq0F+/SCHHgm1li6lnDvxy4v8ZzAayT9KSkFYd7EUkrJHVK6uzu7q5j9/px4JtZYgas4Ut6CJhd5amVEXFP3mYl0AvcUeNlzoyIbZJmAuslPRMRj1RrGBGrgFUAHR0dMYgxHBnX8M0sMQMGfkSce7jnJS0HLgTOiYiqAR0R2/Lvb0haDSwGqgb+iPEM38wSU6ikI2kpcA1wUUTsqdFmgqRJ5cfAecCGIsetCwe+mSWmaA3/W8AksjLNU5JuAZA0R9LavM0s4GeSfgk8DtwXEQ8UPG5xLumYWWIKXYcfER+qsX8bcEH+eCtwapHjDAvP8M0sMf6kbf/HZmYtyoHf/7GZWYtKN/BdwzezxDjwwYFvZklIN/DHjIFx47LHDnwzS0C6gQ99s3wHvpklIO3Ab2vLZvlj0v7PYGZpKHQdftNra8sWMTczS4AD34FvZolIu5ZRKrl+b2bJ8Ax///5G98LMbEQ48B34ZpYIl3Rc0jGzRKQ9wx8/Hnp7B25nZtYC0g78q6+Gffsa3QszsxFRuKQj6RuSns4XQFknaU6NdsslPZd/LS963Lq48EL4whca3QszsxFRjxr+jRFxSkScBtwL/Fn/BpKmA9cDHydbz/Z6SdPqcGwzMxukwoEfEbsqNicA1RYy/wywPiLejogdwHpgadFjm5nZ4NWlhi/pm8BlwE7grCpN5gKvVGx35fuqvdYKYAXAvHnz6tE9MzNjkDN8SQ9J2lDlaxlARKyMiBOAO4Arq71ElX3V/hIgIlZFREdEdBx33HGDHYeZmQ1gUDP8iDh3kK/378B9ZPX6Sl3Apyu224H/HuRrmplZHdTjKp0FFZsXAc9UafYgcJ6kafmbtefl+8zMbITUo4b/V5I+DBwEXgKuAJDUAVwREb8XEW9L+gbwRP5vboiIt+twbDMzGyRFVC2ljwodHR3R2dnZ6G6YmTUNSU9GREfV50Zz4EvqJvur4UjMAN6sY3cayWMZnTyW0auVxjPUsZwYEVWveBnVgV+EpM5av+WajccyOnkso1crjaeeY0n7bplmZglx4JuZJaKVA39VoztQRx7L6OSxjF6tNJ66jaVla/hmZvZ+rTzDNzOzCg58M7NEtFzgS1oqabOkLZKubXR/hkLSCZJ+ImmTpI2Srsr3T5e0Pl88Zn0zrSUgaaykX0i6N9+eL+mxfCz/IanU6D4OlqSpku6W9Ex+jpY067mRdHX+M7ZB0p2SxjfLuZH0z5LekLShYl/V86DMP+R58LSkjzWu54eqMZYb85+xpyWtljS14rnr8rFslvSZoR6vpQJf0ljgZuB8YCFwqaSFje3VkPQCfxwRHwHOAP4w7/+1wMMRsQB4ON9uFlcBmyq2/xr423wsO4CvNqRXR+bvgQci4teBU8nG1XTnRtJc4OtAR0QsAsYCl9A85+Z2Dl1Po9Z5OB9YkH+tAL49Qn0crNs5dCzrgUURcQrwLHAdQJ4FlwAn5//mn/LMG7SWCnyy1bS2RMTWiOgB7gKWNbhPgxYRr0XEz/PHu8kCZS7ZGL6bN/su8LnG9HBoJLUDnwVuzbcFnA3cnTdpprFMBj4F3AYQET0R8Q5Nem7I7qN1tKSjgGOA12iScxMRjwD978VV6zwsA74XmUeBqZKOH5meDqzaWCJiXUT05puPkt1dGLKx3BUR+yLiBWALWeYNWqsF/qAXWhntJH0AOB14DJgVEa9B9ksBmNm4ng3J3wF/QnZjPYBjgXcqfpib6fycBHQD/5KXqG6VNIEmPDcR8SpwE/AyWdDvBJ6kec8N1D4PzZ4JlwP3548Lj6XVAn/QC62MZpImAv8J/FG/JSSbhqQLgTci4snK3VWaNsv5OQr4GPDtiDgdeI8mKN9Uk9e3lwHzgTlkS5OeX6Vps5ybw2nanzlJK8nKvHeUd1VpNqSxtFrgdwEnVGy3A9sa1JcjImkcWdjfERE/zHe/Xv4zNP/+RqP6NwRnAhdJepGstHY22Yx/al5GgOY6P11AV0Q8lm/fTfYLoBnPzbnACxHRHRH7gR8Cv0XznhuofR6aMhMkLQcuBL4SfR+WKjyWVgv8J4AF+dUGJbI3ONY0uE+Dlte4bwM2RcTfVDy1BlieP14O3DPSfRuqiLguItoj4gNk5+HHEfEV4CfAF/NmTTEWgIjYDrySr/0AcA7wvzThuSEr5Zwh6Zj8Z648lqY8N7la52ENcFl+tc4ZwM5y6We0krQUuAa4KCL2VDy1BrhEUpuk+WRvRD8+pBePiJb6Ai4ge2f7eWBlo/szxL5/guxPtKeBp/KvC8hq3w8Dz+Xfpze6r0Mc16dRgTEnAAAAj0lEQVSBe/PHJ+U/pFuAHwBtje7fEMZxGtCZn58fAdOa9dwAf062Ot0G4F+BtmY5N8CdZO897Ceb9X611nkgK4PcnOfBr8iuTGr4GAYYyxayWn05A26paL8yH8tm4PyhHs+3VjAzS0SrlXTMzKwGB76ZWSIc+GZmiXDgm5klwoFvZpYIB76ZWSIc+GZmifh/RvZjOtZEQMAAAAAASUVORK5CYII=\n", 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\n", 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\n", 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\n", 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\n", 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X/kwakMSFbRN4f3FquVH5/1btJ6fQzmNjOvnMdx7asQEx4RbGdG98xrZ6EmE1c3n3Jvyy7Qi5RXZO5RezeNcxxvZswqvX9GDmXRcysE0CHy/bx5BXfnffaFbuPc6pfBujuzXmtkGtOXAin4UpR3E6JatSj5N+Mt/3B86cqXqGs2fz1E9/cNt/1+H8YQb07k3BxcP4x68f0floKj2evB/69lXn2TnE5pDER1oRooKI/PRpmDgRfv1VPf7vf1Uv7/rrz2n7zgYt5MDGA6fILbITbjExw4e9IqVkzJtLuWX62nLFPLfIzrZD2fRrVY9OjWNpXT+a2Vsrt26f3RDYCsgusHHwRDkXiZFd0qaNz5dnbTlM16fm0fWpeQx77XfeWbRHiV1ODp9cfANOCQ1iw/l81QHvN/bvD82aKXslI0NZJ2+9pcTSRZHdwabHXoI9e+CVV8hzKBvksq6NmPzvO1g3ZiJHmyQR9d3XYDbTuXEcOzJycDqlGoQdOxa+/NJr4PPpn/7gwyUlGTMbD5xCSnBKvP4HaVl5KgNjxgx1M/voI1Xo/5131MUGKgsnLg5uuIGEg6k8NO4hGDiQ29b/RGFhsZfwHHDt2xD0tg1i2HYom+x83xe6lJIfXd76u7/vZf/xPL5ee5AjOYW8e0NvxnRrzL/n7uCJmdsY0DqBO4e2ZWTnhvxy72BWTh5O16bxANwzrB1ZuUVMX5HGj5sOccNHq3j9111IKSm0Ofho6T4Gt6tPj+Z1fLajvixmyzf3M+7w2dXBvqp3UwpsDn7ZmsHsrRnYHJKxPZsC0LN5Hd69oQ8rHhnG4Hb1eebn7ew4ksPsLRlEh5kZ0j6RS7s0pGmdSF6eu4ORry/muqmrmPzD1rIfNGsW/OlPkJOD/dnnWL4ni9gTxzCtWQ0TJrD8kZdwCsGc6ffQd9lsaN9eCX9+Oee7H7A7nVjNJmLCLWdOP/z4Y9XLvfxyNe702WcwejQ0bHjO2na2aCEHFu86htkkuGd4O3YcOV0mPe6PwznsP57P0t1ZvDJ/p899bNh/EodT0q9VPYQQjOnemJV7j5NVgb1y6FQBF7/6Ow98e+YLsNjuZOLUVVzy+hI2HvDh2RpC3qpVmZd2Hz3NQ99toUOjWK7t24KE6DBembeTFXuzcIaF8/Xag1zYNoG/DG7Fuv0n2XnkdMmbDXtl7lwYN05ZIPXqKeF18f3CP2jxzmuk9xkIo0bx+85MiuxOLuvaGKvZRPKsL2h4cC/Urw9Ap8Zx5BU7OGgI6LXXwpEjypYBdhzJYfqKND5YkqrEHljnkfe8L6vk4v7Pgl3c99UmVdeidWvl94eFef8DIiNVz+LkSbYMGcOqdn3hH/+g+akjtFw6n/STyk4LM5tIcw3yGb+v79cCp4TV+3zbK5vTs0k7ns8DI9sTZjbx+MxtvPv7Hvq1qsfANgn8++rutG8YS0y4hf9c1xOzSbj+rcIrsu7fOoELWtfj5bk7uPerTWw/nMMbC3fz+oLdfLPuIFm5RTxevLPEiijN0qWYdqQgpk71/Xo59GlZl6SEKL7fkM6PGw/TtkEMXZrEeW3TMC6C16/tSVyElXu+3Mi87UcY0bkhEVYzFrOJWwe1Ym9mHtHhFi5oXY+1aSe8ek37v5qJ86qr1LT155/HsmY13Q9u55I9rtIC48ez1hnD46PvIb1rMhNueIW8/7ypellz5pzV8ZwNdofEYhbERVjLt1YcDpUY0Lcv9O6troXDh5WtUovQQg4s2ZVF7xZ1uK5vcywmUWbQc2HKMYSAK3o04YPFqczaUjbSXrPvBGaToE9LNdA0pntjnBK+XH2gzLYGJ/KKufHj1aSfLOCHDYdYvqf8Lvw7i/awPSOH6HAzt05fy55juUgpWZd2gt92HEXu3QsJCRAfz6cr0xj87994Z9EejmQXcsfnG4gKM/PhpGSevKIzn97an5YJUTz6w1Z+TTnKoVMFXNe3BVf3aU6Y2cQXq/dTbHfy7M/bmfDucorGX6WskzVrVLfyhhuU1ZKTg5QSx5TXqVeQw/29r+d4XjFztmWQEB3mLtIEeE1T7tRYCUVKRg7Fdif/zGuGLTJKRT3AVFcknpVbxMaDqn7zurSTtEyIAmBfVskqNzuOnCbmyCE1PnDTTeVPh77vPhg9mjk3P4jFLGDcOA7Va8yAmf8l/WQ+FpOgW7N49rs88n2uiHx8r6ZEWE1un1zZD5nu3f646ZAaFxmYxD9Gtmfp7iyO5hRx34h2CCGIDrfww50DmX//RTRM3aHsnltvVXbPM8+AvURAnrqiC39Kbsant/Zj3eMjuaZPM95cuJsX5+ygb/M42j/1T/W+LB/nyaJF6ve8ecoKqCRCCCb0bsaq1BOsSTvBuJ5NED583/ox4Uz5Uw92Hc3lVL6NMd1KLJxbBiax+MGL+fGuC7n1wlYU2pxsOuCqu223E37nHaTGNyZn5iy47z7youO4e9PPjD+wlsMNmkOnTvxxKIe9w8aw+7vZbG7Sga1tekKDBiqF9Bxhc0XksRGW8q2VmTMhLU3ZhvPnq7riLVrAmDHnrF1VIWSE3OGUzNx4qIy/mpVbxNZD2Qxpn0hCTDhD2ify46bDXoM3v+04Ss/mdXjtmh4kt6zLPV9upPvT8+j57Hxunb6WgyfyWbPvBF2bxhMdrtLaOjaKY1SXRry9aI97AK3Q5uBfc1J4dMZWPlqayi2frOHQyQI+u60fzetF8tRPf3it8m6w7VA27yzaw4ReTfn+joGYTSb+/NFqhr22mKvfX8mt09exY8VmHK1a8dHSVJ788Q+kVMWTBry0kNTMXN68rhcN4yIAiAwz8+KEbqQdz+f+rzdRN8rKJV0aUi86jNHdGvHDhkP86YOVTFu+jw0HTvGRrYHKiHnxRRWRTJyoPPKZM9m8dT9jF39LyoARbKjfipfn7mDRjmNc2rWRO/osTYdGsZiEmp344i8pfLfzJPNaJWP/9jsysnL4adNhru2aQJTTzvztR7A5nGw8eJKhHRpQN8rqjsiL7U72HMtlwraFaseTJpV/AnTtCrNnkx1XF4vZBGYzPw65hla7t9Dshy9pXCeCNonRbkslLSuP+jHh1I0Oo29SPVbszeJ0oY3rP1zNTdPW8OnKNOwOJz9vzmBYxwbER1qZNKAlvVrUYWiHRAa2qe/+6KhVK0i4dJjKyX/nHeW1LlkCTz+tegqu8YZOjeP499U9uKh9ImaT4KWrunNljyYU2Bw8GpuFyMxUmTj//nfZ4/v9d3UjLyrysr0qw/heTd1/G7aKLy5qn8idF7ehYVw4F7UvGUw3mQQtE6IRQtC/dQImUTJAfPSTz2l08ggvD76RD7ad5LQ5jP/1uJSLty+j5+6NzGrdnwKbk62HsunWNJ6uTZTVtO1oHlx1lbJkcs/N8nR2h8RiEsRGWMgxhDw7G/75z5Kl2l5/XfVyx42D2FhYuFANdoaHsy7thFeWU00SMkK+dHcm9329iY+W7vN63piAYJyY43s35UhOIatS1Yl4LKeQzenZjOjUkDCLifdv7MMdF7dhQu9mXNa1MatTj3PJ60vYcOAk/T0jUODpK7tgNZt4bOZWiu1O7v5iA1OXpDJ7SwbPz05h2+Ec3r6+N4PbJfLU5V3YcyyX6cvTvPZRPHs2uZdcRs+CYzx1RRdaJkQz/Za+2BxOEmPDeeXq7jx4aQciD+5nUVEMz89OYXS3Riz658XM+vsgxvdsynPjujKwbX2v/Q5sU5/r+jYnv9jBVb2buTMdru/fktNFdvYcy+XdG3ozsnND3luyj+PfzlSTawAuuECV4vzyS44+9xJxRXm0fOMlru/Xgm/WpZNf7PCK2EoTYTXTOjGGb9al88nyNK7p04zFvYZjOXmCX9/6guYnDvHC5D+x7u0b6PHUAxz45mfMubn0TapHq/rR7oh8b2YuDoeDq7ctJH/QkEqVB7U5JFbXDeb3IWPZ2rkfE6c+y90rvqFlvSiOnS4iv9hOWlY+reqrHsCFbeuz62guk6atYdfR0/RoXodnft7OK/N2kpVbxLheqr60xWzi2/8bwIeTkks+cONG5aceOqRqb2RkqMHdtDQ11jBzpvJe88rmbZtNgil/6sH8+y+i1+oFyiKaMEHNuD3iMU8hO1sNQt9xBzRuDN99V+H/wZPm9aIY2iGRwe3q07xe1Bm3fWhUR1Y8MrzcAlPxkVa6NY1XKY1SwpQppNZtQt7Iy5i2LI2v1x5kWs8xYDJhdtiZ27Y/P246RHaBjS5N4kmMDadRXITKXLn2WrVc2qxZZ3U8lcXmkFjMJmI9rZUPP1Q1xPv0UfbJ8uVq0NUYbxECoqLIKbRx7dRVvLGg6pOq/IqRGlWdH2AUsBPYAzxS0fZ9+vSR55t3F+2RLR+eJbs9NVeeyit2P3//Vxtlr2fnS4fDKaWUsqDYLns+M0+Oe2eZtDuc8qs1+2XLh2fJ7Yezfe730Ml8ecsna2TLh2fJZbszy7z+ybJU2fLhWfLS1xfLlg/Pkp+uTJNSSnk8t0hmni702vax57+SX/UeLbMeekzKb76R8uqrpVSXg8wcPKz8g7PZpMNikR8Nvlbe8+UGWWx3VOp/ciq/WD42Y4s8fCrf/ZzT6ZTfrTso9x47LaWUcvfR07L15NnyqR+3eb/5kUek02yWOeFRclv/4VJKKbNOF8quT86VPZ+ZJ20VtOHuLzbIlg/Pkle+tVQW2Rxy2bZ0mR0eLZe07ClP1k2UMiFB7hk1Xp4Oi3T/D+wtWspfrv6b7P/CAimllDM2pMtrrn9JSpB7X3u3Usd831cb5aCXF0oppbzhw1XymjcWyTk9hksJMn3UWDnqljfl9sPZMvn5X+UD32ySUkq5+eBJ2fLhWbLlw7PkDxsOytxCm/v77PrUXFlQbPf9YQcPStmkiZQtWkiZkeF7m+nTpTSZpBw+XMrCQt/b2O1SNmok5VVXSblrl5Rms5T33lvy+s8/q//RokVS3nWXlJGRUubmVur/YVBkc8giW+XOmzIcPaqOw6muoRfnpMi2j86WBQsXSQny3WsfkPsyc2WbybNl68mzZd/nf5XOW26RjqRWsu0jP8thry6SLR+eJTcdOCmllPK26Wvl8Nd+l9Jul7aGjWTKBcMrfU6fDT2emSefmLlV3vPlBjn45d9U+zt0kDI5WcpbblH/09hYKbPLXvvL92TKlg/PkkNfXeT3dp0JYJ30oanVLmMrhDAD7wAjgXRgrRDiJynl9jO/8/yy40iOe3R66tK9PHhpRxxOyZLdmQxuVx+TK0qLsJp56oou3Pf1JqavSGN16nGaxEfQsVGsz/02qRPJxzclczi7kKZ1Isu8fuOAJGZsPMTm9GyeuLwzN17QEoB60aUG5ObN49mXb6e4oJCwjb+AlNjDw3l98I1c0Loeg//7hurWDR9ethHp6Zjsdm7+8zDM1/Wq9P8kPtLK8+O6eT0nhOCqPs3cj9s2iOHavs3536r9xEVaWZd2gv3H87mmQTL3ORzEOvIJf/YpABJiwnnz+l7Y7E5lX5yBC9sksHJvFm9f35swi4kLuzRly6CRDF44E1v9RFj0O1HN25D87BwGHdhKv9MHud2+n1Hfvc+3MpH84iHsOHSC+5Z9wemwSPZddCmtz/iJCpvDidXlo0eFmTmcDXdeei9fde1I3+8+5peiH8na8BkXNxlIux43AdClSTzDOjZgaIdExvdS/5uPb+7L1e+t4LKujX1HpwUFKtI+fVqVPGjUyHeDblKfwc03q7+/+KKsz79ihYrAr7lGFWmaNEnl4D/wgMrD//13CA9XPSVQ9s0vvygbrJKEWVyfmZ+vyji0aaPy79u1O3Ou9OnTynbbuFHNKO7ShYFtEnh/8V6ynv4XUZFxmG++iaT60Vzbtzmfrz7ApV0aIR76AFFYSPf/bWX9/pNYTIIOrmusa9M4Fu44SkZuMSvaDuDyVbPYtTOdLp1blN+OKqCsFQ+PfMUKVWN82jQ1aH7LLSqEiIsr895th9S8h9TMPA6eyK+wJ3Ou8Ye10g/YI6VMlVIWA18BY/2wX7+y88hp+rWqxxU9mjBtWRobDpzk2g9WkpVbzKgu3hfZ2J5NGN6xAa/M28HS3VkM79TQ5wCQgRDCp4iD6h5/OCmZT2/t555SXYaPP0W5dI0AACAASURBVIYxYzC1SuLI6k0MeeInrv+/txly+4f8ccvdDHz3RWjZUk15d/pIf3RlrJh9ldP0A/cNb0e4xcSbC3dzIq+YLk3imHoymk2N27Ok93DaXjLYve3QDg24pEs5ouXBdf1asPrREV4XQLdXnqRo2AisS5dA1640jo+kfauGLGjTl5Rb/g5z5pDTrhP/mvcOB/Ycout7rzLwwBaeHX47J6hclTkjUwGUkO8/no8UJtLvf4S81DSeG3obzqNHeeWXN7jt6oFwxx2YpZNpN/flxgFJ7v00rRPJ4geH8viYcoomzZmjfNbp05U/fyZuukmVKvj6a1UxrzTffqtKDYwerR4/+aQS+zvuUEKzaJES8YgIGDxYTQY7S3vFzZdfqiyNe+5Ra1FedllJKYfS2O0qpXDjRvV4wwYAkpPq0iY7gybLFvBZr9GM6KPO+3uHt6NvUl0m9muhqgLGxjKwTQIA7RvGum+I3ZrGIyVc/+Fq/tfqQsIdNmxffV214zkDNocTq0fWivzoI2RsLF+26KfG0gYPViUrfLAlPZuoMNXe3z0Gv/OK7JWfHOVH/CHkTQHPObrprue8EELcLoRYJ4RYl5mZWfrlc4oxKNaxUSz/GNmeYoeTCe+uYOeR0/zn2p5cVsrPFULwwvhuWE1q0sawTmeuXVERDeIivAaHvMjPVxfNkCGwbBlJvTvx6d+HktqiI9bmzXjj2l6YoyLhhRfUBfP552X3YaQetq5MTFq19s+7/yLWPjaCufddxNRJyWx4YiTHf1lIizk/VHm/pQdDRa9ehC/8Va2q4uKSzipXt0/LuhAWRuZb75GQd4pGfxrL5XM+ZfHQCXzbfSSnysnzLo3d6cRiROThFvdF16xuJLFNGvLjsGu55G9TGXfja+SMv1pFvi+84HNfYRaTuydXhkWLIDpaTVCqDA8+qDJr3nzTu7aN06lyl0eNUoNtoMYCXnxRDWq++aY6L4YOVa+ZzcpHr+og4bRpamLVnj2qTfPmqdTT0hQWwl/+ol57/31Vz2f9egCiwixcf3IHJilZP3QcrRPVyh0N4iL49m8D6eyR3jjAJeRdm5Y8Z+TW78vKY8xfx7E7oTkNvi9Jd60Wdrv6n23YgN2pbuqxEVYiC3Lhm29Iv+RKJv+aVu7EQINth7JdYwqRLHaVDs4vtjNyymImvLei3HkH5wp/CLmvM7nMLUlKOVVKmSylTE4sb/r4OWJvZi52p6Rj4zha1Y/mrqFtGdohkTn3DmZcL9+j9I3iI3h+fFe6NY1nQOuEc9e4OXOUmD/+uPtCbVU/mgUPDGHWPYOJj3JFmhMnqgGYW26BkSNVFG+krqWmqgL3zZufs2Y2qxtFYmy4+3GE1czwHs1Iali22+lPxvduxoDWCYzopAS90cUX8u4F11Dnj81satyOXZOfw2ISnKxkoSXj4gWIDiuxRJq5egYtE6I5VWBnU5MOhH0yTU33f/ppWLDg7Bq+aBEMGlT5etRCqGyUrl1VDRwjhXDmTJW3fM013tv//e8qYrzvPhUxX3xxyWuTJqnB08qk7nlWn9yxQ9kLt96qrJXnn1fn1Isver9n9WqVU/3f/6oUyv/7P1VzxBWRAwzM2sWRmHr0vOjMtUh6t6hLlyZxjOxc0otrGBdB58ZxTBrQktsGt2Zuv8tosn2ju/BZsd3JpyvTKLaX9E5tDievztvJMVepBZ8cP65uiPfei3z2WRzOEmvlipQliPx8Fl6obryeUXZpsgtspB3Pp3uzOgxpn8iKvVkU2R18sjyNw9mFbD+czcQPV53XCqj+EPJ0wFNBmgGVm9J4njAmuBg+9z9GtueTW/pV6GuN7dmUn/8+yH/Lkm3apLrOa9aUPPftt6orXKoLFxNuISbcYwjDZFKR2sMPqxmMf/lLyco/qakqSjP7qZ21iKZ1Ivny9gtoFK9SJ6PDLXw96ibeuPxO/jrhCTq0TFSlcSsbkbtSzgAiw9T/12ISNHKlZhq56g1iw4mOsKp6NB07qunYhyt5Wh89qmpVG1FyZbFaYepUleHyxBPqJj9xohLJceO8tzWZVPQcGakslf79S14bMEC1+eOPz/x5Cxeqc8+YdPPJJ+oc+vOf1eOwMJWKt3Spyt6QUp1zAweqG83cucrmASXsGze6rb82u7ewrWUXxpYTKBlEWM3MvmcwIzt7z5Kcfc8gnh3bFSEE20eMxWEyq/YBC1OO8uSPf3hVGF2z7wRvL9pTfrG61FRVvmLpUtXjWLkSpMRqVumHE7b9RlHHzsyJUFK2ZFem1yxu6WEv/eHyx7s2jWdI+wbkFztYmHKM9xfvZUSnhnw4KZm9mbmMfWcZk6atYeLUVXy9tvz5JP7AH0K+FmgnhGglhAgDrgPOou7puSflSA5hZhOt6kef+w/buFGd3JMnq67pP/4B996rorNeveA//1Ei7HSqSHzWLNUVrowIN2miuvm7dyuR+PBDtZ+9e8+ZrVIbadawDq93GU1mTD06NoqlTlQY2QWVi35sjpKBWCMib1In0m3zJCWocyTJOFdiYpS1cfKkShesDMbknLMVclAi/Le/qc8aN04VOVu4UFkXpWnbVk0Xf/FFJeYGQsBtt6no2hXFlkFKeOwxdVwTJ8LWrfDpp2qii+fA7F/+ombk/utfStQfekjld2/bpgZDDXr3VlbO7t2QkUHYgf2MuG08bRKrtiCq55hUQuvmLGnXF/npp2Czse2wElIjRdjz79TMcsrvvvyyGjBevBjuuQdx7BjNs49iMZuoay+k5+GdHB9xGVsOZ9OiXhSnC+1scE1qOngin+5Pz3cvjLLVJeTdmsYzsE0CVrPgke+3kFtk58FLO3BxhwZ8cktfGsRGkFNgIyO7gMdmbGPPsXOTDw9+EHIppR24G5gHpADfSCn/qO5+K82XX6row7OIU3a2SuR31WnYkXGatg1isFaQSXHWvPKK8ts8ueceeO45lYv6zjuq9senn6pKblOmKD9x61Y1sPXLL6qNpbvNFWFcqPv2qYyF1NSQEvLWiUpk60WHkRgbTt0oKyfzfEfkx3IKyfMoxWp3qigMlEcOyh83MCLyVgkeN/1OnVTJ0rVrK9fARYuUTda7d6WPyYsXX1T1bXr1UpOH6tUrf9urrlL2SmluvFHZbdOm+X7fb78pi+Sxx1RUP2iQErpbb/XeLipKBSJz5qjz9+671Qzc+Hjv7fr0Ub83bCgpSzxwYOWOtwKSEqL5ossIxNGjMHeuu8ytLyHfm+lDLJ1O+PFHdZO64AJ1swR6H0rBYhI03rIWi3SyJqkHhTYnd1zcBotJuFdR+mDJXk4X2Xn91104nZIth7JpWieSetFhRIdb6JtUj5xCO+N7NnVn3gxsU5/v7xjIzLsu5Ps7BhIZZubZWdvP2YpKflE2KeUcKWV7KWUbKaXvkaFzxQcfqJShdetKnps6VUXC48dDURE7j5wuN32wWkyZokTb8BlzctRJPHmymtKen6+eO3lSdbXvvx/++lclCk8+qW5C9eurgc6zZcIEdTFNmaJuEiEk5EbU3LFRLEII4iPDyvXIr526ird+2+N+bHdKzCbviNxTyMtE5AbJyUqkKnMhLlqkvlNLFbN74+PV+bJiBdQ9c23xcmnYUKU/uqLYMjz/vOrhPf64KvlbUKCmxBuZMZ7cdZeyd154QQUuvsogdOqkUiA3bFDtDg9XNyI/0DoxmkWtk7HVbwDXX8+kVx/gpo2zGTLnC/IefJiib79nk6uUg8+IfPVqZXcZi0B07YqMiaH34R1YzSYS1iynyGzl2zBlq1zUPpHkpLr8vjOTY6cL+WZdOi0Toth9LJcFKUfZ5pqFajCqayMirWbuH9neZ/sTYsK5b0R7luzKZGFK9ZfY80Vgz+w8dkx5XlDyG1T3KTYW5s+n+OpryDqZS8fGfhbyjAwVwWRllXjev/2mRN2zy1kak0ldEHv2qC77+PFVu+AjI5WXaUzHDiEhNywyI/qpG2UtN2vlRF6xV+Eyu8PpntkZ5RbyEtuiQ6NYRndrxMjOpTKV+vRRN2SjXLAnu3YpC2L/fuVvG9ZXdYiOrv6Yx223qWvEKEFssGyZ6sk9+KCyZAYOVJH/N9/4HpytW1dZho8+Wn5OudWqApT165WQG6tU+YGkhGjsZgu/v/EpBddcR6cDKTwz/z2e/O1Dol57hfA/Xc016+fQN6kuR3IKyy6GMWOGap9xkzKbKe6dTO9DO1TWyoolrG/aidUZ+TSMC6dJfARDOzQgJSOHf81Owe5w8vFNfWleL5Ipv+5i//F8ujUrEfI/92/JqkeHn3HMbdKAlrRtEMNzs7f7LsNcTQJOyD27yfz0EzidFEVGI5cuU885HErUJ06Et94ibNbPPPL7J3RoVM3sis2blXgbeIzQu6cQz5unPFVX161cxowp2eZsbRVPbrut5O8QEvL2DZWAd3ddTHWjwzhVjkdudzi9shu888jLWisRVjPv3tCHtg1K3fgN68Cz5weq53XttWpgsX9/1UOC6gu5Pxg1Ss0/eOGFkvkHUqpMk8RE1Ts0GDKkaj1DT3r3VkK+fr3fbBVQJQTMJsHmhCRWPfQCA+6czvrFGxj44Lc8+dVaUvsN4V/z3uHh9GWM2L0ax4SrVIBUXKyOd8YM9X142EFFffvR6dg+4jKPYNm2lZUtumF3Sno1r4sQgqGuhTpmbjrMmO5NaNsghtsvasMOV+KEZ0RuMgn3Yt7lYTWbePLyzuw/ns+C7f6PygNKyJ+btZ0r3lrmLm3KDz+QmdiE79sPwr5smTpZN2+GnBxeym/A3IuvZt/wy5nwxyI6JVZj5tXx4yXLoxls2KCikz59VMQjpRLyoUMrjkSEgHffVYNa1bnge/Uq6b6GkJAn1Y/m57sHcWUPlRFRJ8pKoc3ptUKPgd0pvSIgm7NksLN1YjT1Y8LLrfHtRdeu6nt15Uq7efJJlY306quqlzRliopge/So+gH6C4tFWX8bNrgrS/LFFyqV8vHHVdTvT/r0UVZicbFfhdxqNtGiXhT7svL443A2CEH7fl3p2Lklyw+e5ok/P83Gjn1JfuFhPvrhOSJWLFVpm5Mnq8HePXvKrK1Z0LsfFumk0+dTEVKyMkl9X71bqnOhXYMY9yS/O4aoGv/X9GlG/RiVgusp5JXlovaJzPr7oLNa/KOyBJSQd28WT2pWHkt2Z8KpU8gFC/ixVX/WNuuCNScbtm1DujIGZsS15W//W8/UhO7UK8ghcfumkh0Z03B/+kldmBX5nm+6aiMvWFDih69fr4rfGyP+v/2mut1nslU86dlTpbZV1Uc1eOYZlTdcevApyOnWLN6daVInUt04ffnkSshLInKVO6ze16xuFOseH1G5zIrwcJVB4hmRL1micr//+lc1XX7VKlVC4eabyy+ne7654QZ1rj36KBw4oAbjBwxQvre/8RzcrahXepYkJSgh33Yoh6SEKGIjrFzQuh6pmXmszshnwQvvY3/qKf5y9ZO89/kSNSg7ZYoaqAW1uIgHub1UDytp5hcQHc3eJDVDt1cLNSYhhOD2i1rzl0Gt3BOYIqxmHh3dkfG9mrrX+jxbulbhBlAZasnZVjku69qYxNhwpq9Ig9mzETYbc9oPpNHlIwE4+PN8js2aT1qdxtx301DuGtqG2U26YzebEYaXLKWaVnzbbWplmuTkMy8zdvq0SgWrV08NKnpOR+7Tp2TmnjG1+pJLzs3Bl8cVV6iJGSFMXdekqdKZK1JKHE5Jka2UtVJVkfUc8LTZ1OSsNm1K7JSGDdXN3nhcGzCZVHbV/v3K+snNVTbQuZhz0LWrCkzatPH76jmt6seQdjyPbYez6eIqdTugtaroaXdK+nRuiuXpp9nT72J2nyxWx9yjh/o++vdXA7seFMXXY2+9plgKC2HQIKKio1RNeg+hvWlgEo9f3tnrfRN6N+P1a2vHgsueBJSQh1lM/Ll/S37fmUnel9+QFZeA6N+fu24eztHY+hz9eT6Rq1eS0r4Xf0puzoOXduTbh0fjGDioxMdevhy2bFF5pWvXKlF//vmSSEtKFV0fci0u8cEHapBr+nT1eMECyMxUpUh791ZRebt2Kipv1Url9mrOK3VcC+iW9sntLgvOy1px1deoEn36qEWuU1NV+mhqqkozjalarvR5Y8QI5ZcfOaJmqXYqpz5MdQkPVwOKV13l9123qh9FfrGD9JMF7gi5c5M4YiMsmAQkJ6kUzdaJMSoFMSJCfUfx8T7X1rQ7nWxs4ioFMWwYcZFWOjWO89/kv/NMtasfnm8m9m/Otz+txDJ/Hr90Hc41/VoSE2HlQK9+dFs+n3CHnSZXXurudndoFAvjrlRd3/37lTcdH6+6ltHRSqiXL1f2xNKlKm3x00+V33nffUrAhw9XkW/37krIjS6k8fuKK1QUdumltWZV7VCibrSKyEtnrtgdSsiLPWboeU7RP2uSXXXG165Vi1d36aJS/AKBDz5QPrmvolz+5Mcfz8luW9UvuVka9oTZJBjWsQHHcoqIi1DnQJvEaJbvycLplJg6dFAJCp6TpVzYHJK1zTpz9baFMGIEk2OaExkWmCIOARaRAzSICefDJR/gAD4bMME9cND0ihGEO1RGS7frvf0w98U2bZqqCnfzzSUDPXXqqOdTUlRE/dlnagGF8ePVxIyMDDVoAiqyWbZMCT+UDDROmKB+V7ZAksav1I3y7ZHbXZkantaKzeGsurXSpYsa8HzxRfjjD1UuobZ44RXRooWalVnZ2i+1jKT6JckKnmuKvnJ1D6bf2tf9uHViDEV2J4dOqXVYiYz0GVzZHU6+7zqcrZ/OgN69uah9In2TzjDxqpYTIGehB1On0mnzCl68+Ba6DulDrOtOHH+JqtNta94CU6sk7/cY9scLLyhv8847vV+/5BIVfcfEqHX5XnxRVRlct06J/LBharsRI9QM0g8+UD5gHVe2w4UXqgHUyy47d8etKRcj9au8iLy8wc6zJixM9cq2bFFpfdddV7X9aM6aJvGRhFlMNIwLd2eOgLJbjdWtAPfAtc8Znh7YnRK72ULehYPPuF2gEFhCnpqqLJLhw+n1r8n885IOJa917QqJiVgvGen7vZdfrjJORo5Uwl6aKVMgPV2JtYFRbdC4ow8erCKao0fLTr9u317bKjVEhNVMpNXMqTIReVmP3O5a3qvKGPbKP/8ZsNFtIGIyCTo1jnMvbl4eRvmGcmuuuDDWxq3yeEktI7A88ieeUKPt06YxoUWp1UJMJpX+lVBOydmrrlL1V4x0pNIIUbEQG5N9liypeh0NzTmhro8KiIa14lXu1FmNwU5Qg+P79pWtSaI553w0KblkJaNySIgOIz7SWnFE7uqt+b3+Ug0RWEL+/vtqwk9pETc406SYCy9UmSbNmpW/TWUYMUIJuTHTT1MrqBMVVjYiL2WtOJwSKam6Rw5qAldtmLUZgnjWwy8PIQStE6MrjMiNm3y1zoVaRGAdRWysqtJWVaor4qCslr/+tXrt0PgdXzXJS6wVp+ux6+INku60xjftGsSwOf0Uqz2qI5bG5o7Ig+NcCCwhrw00a6aqK0b6XqNTUzPU9RGRO5wlkbjd4XRH6FUe7NQEBHcNbUuj+Ahu+Gg1n61M81k6tuSmHhwSGBxHoQl56viogGhEXaByyd1CHiQXr8Y3LROimXnXhVzUPpEnfvyDn32sGmQLspu6PqM1QUHdqDBOFdi8oi/P1cyLbE5szuDKVNCUT1yElak3qnGsfT788mAb7AyOo9CEPHWirDickpzCkjLHNo8ZnUV2p1vYzUEShWnOjMVswmISFDt8VcUMrvESLeSaoMCot5LtYa94ReR2R0nucJBkKmgqJsxi8ko/NXAPdgbJuRAcR6EJedwVED0GPL08crunRx4cUZimYqxm30Jud+iI3I0Q4hohxB9CCKcQItlfjdJozpY6PuqtGN1nUNZKsGUqaComzGLyKppmYKSmaiFXbAMmAEv80BaNpsoYEbln5oq9lLXivni1Rx4yhJlNXrV2DILNZqvWzE4pZQqo2VQaTU3irknuGZE7vLNWwi1ayEON8HI8crtDYhKqhkswcN5uR0KI24UQ64QQ6zIzM8/Xx2pChNgIFZN4rqDuKGWtlBRKCo4oTFMx5Q52eqzdGgxUGJELIRYAjXy89JiUstJV5KWUU4GpAMnJyRUskqnRnB1GlO05wOn5t/LIg8sX1VRMuR65Q2INkmgcKiHkUsoRFW2j0dQ0QgisZuGVO146/dCwWnQeeegQZjZ5nRMGdkdwReTBcySakMdiMnkNcJaeEGR3amsl1CjfWpFBNcO3uumH44UQ6cAAYLYQYp5/mqXRnD2WM0bkumhWKFKekNurs+RfLaS6WSszgBl+aotGUy1Kd6NtTu8JQXqwM/SwlpN+qFaKCp4buj6jNUGDxSy8Ug4dXtaKwx2hB9MFrDkz5Q12KmsleOQveI5EE/JYzd4Xrb1M9UNtrYQa4WeYoh9M54EWck3QYDWbvCJyexmPPLiW99JUzJmKZumsFY2mFmIxCa/6KoZwG7P7dNGs0KP8WivVXIS7lqGFXBM0qEp3ZSPy6HCLKmOr0w9DjrByrRWprRWNpjZiNZeOyFU9jUirWS8sEaKEWXxPCLLpCUEaTe3EUsojtzlVrnC4xeSqtRJciwloKkYJucTp9K4KYtcTgjSa2onVLLz8UIcrV1gNeDmCbjEBTcUYNlppnzzYJgQFz5FoQh6VteKdfmg2CXdErotmhR7hFt9CbnPoiFyjqZVYTMKr4qHKTDARbjFTZPOcoq9P+1AhzBDyUgOedqeOyDWaWom11BR9IzMh3GpyrRDkRAg92BlKhJnLEXI9RV+jqZ1Yzd7VD+1OJeTGcl82h9QDnSFGeRG5zdVbCxaC50g0IU/peuRGzelwqzEhyBlUUZimYsLK8ch1HrlGU0spnX5oROThFrN7sFPbKqFFedaKnqKv0dRSSqcfGj6oylpxuAc/NaGDEZGXLmWrp+hrNLUU3+mHJsKM9MMg605rKsYQ8tKzO212nbWi0dRKLKbS1oqKuoyiWSp3WJ/yoUS51oqe2anR1E7KzOx0Twgyaq04tUceYpSbRx5kA99ayDVBQ+n0Q5vDidVVa8XhlBTaguvi1VSMr6wVp1PilME1May6iy+/IoTYIYTYIoSYIYSo46+GaTRni8UscDhLCiQZEblxMecV23UeeYjhy1opKWccPDf16p7VvwJdpZTdgV3A5Oo3SaOpGob/bVyoNo+sFYC8IruOyEMMX9ZKyQIjwXNTr9aRSCnnSyntroergGbVb5JGUzWMCMu4UFU9DUG41QxAfrEjqC5eTcW40w8dPoQ8iMZL/HlW3wr8Ut6LQojbhRDrhBDrMjMz/fixGo3C8DyNVDO7a9KHEZHnFtmD6uLVVEy4Wd3EfVsrwXNTt1S0gRBiAdDIx0uPSSl/dG3zGGAHPi9vP1LKqcBUgOTkZFnedhpNVbG6c4aNiFylmBlRWX6xQwt5iHFmayV4zoUKhVxKOeJMrwshbgIuB4ZLKbVAa2oMq0ukjeXeHK4JQeEWFZXlFtmDKgrTVIyvCUHG38E08F2hkJ8JIcQo4GFgiJQy3z9N0miqhuF/21wLMKv0w5LBzmK7Tj8MNcwmgUmUisiDcIGR6t6S3gZigV+FEJuEEO/7oU0aTZUwBjttXhF5iZBDcA1waSpHmMVUqgZPCHrkZ0JK2dZfDdFoqos7/dDhmX5ocnevIbgmgWgqR5jZ5D3YaSzCrSNyjab2YQi5MZjlMNIPXR45BFd3WlM5wlwlGgyMMZRguqkHz5FoQh5DpL3TD9VSbwbB1J3WVA6jaJqBLQizVvRZrQkarKay6YeWUh65LpoVeoSCRx48R6IJeUpmdroicqezjEceTL6opnIoj9zhfuzOWgmim7oWck3Q4E4/dJaOyD088iDyRTWVI6yMteLyyHVErtHUPtzph3YnDqdEukqVeqUf6og85PC1BKDxfLCghVwTNLizVpzOkswEs84jD3XCLCb3JDHQWSsaTa3GiLCKHdKrwp0Qwl2XOpi605rKEWYxe1U/1HnkGk0tpiSP3OkxDVs9Z0TlVh2RhxylJwSV9NaCR/6C50g0IY/FY0KQkbliWClGLnkwXbyayqHyyEuyVmy6HrlGU3sxou1ir4jcJeSuzBWdRx56lM0jN6yV4JG/4DkSTcjj01oxInLDWgkiX1RTOcq3VoLnXNBCrgkajAvT7vS0VtQpbkwKCqZMBU3lKJtH7orIg+hcCJ4j0YQ8RkTu21rREXmoUlrI3Tf5IDoXtJBrggar12CnYa0YWSvKI9eDnaGH1VzKI9cLS2g0tRezSSCEmoJt+KDmUlkrerAz9AizmLA5JMZKlMG41FvwHIlGg7o4bR4RuWGlGBOCtLUSeriX+vMob2wSYAqim7oWck1QYTULr6yV0hG5HuwMPYybuOGT21xVMYOJ4DoaTchjMZuUtVKq5rThkeuIPPQIs3gLud0hg26Gb7WEXAjxnBBii2vh5flCiCb+aphGUxWsZhM2p8RRTh65WUfkIUdYGWtFR+SleUVK2V1K2ROYBTzphzZpNFXGahbY7E53TXIjM8GdR64j8pCjrLUig65nVi0hl1LmeDyMBmR522o05wOLWWB3ShylSpWWFM0KrkhMUzFlrRVn0I2VWKq7AyHEC8AkIBsYeobtbgduB2jRokV1P1aj8YnV5ZEbs/fcg53uPPLgisQ0FWOMkxR5eOTBdh5UeFsSQiwQQmzz8TMWQEr5mJSyOfA5cHd5+5FSTpVSJkspkxMTE/13BBqNByr90On2yK2lytgGU8U7TeUonX6orJUQi8illCMqua8vgNnAU9VqkUZTDSxmgd0h3ZM+jIi8xCMPrgtYUzG+rZXguqFXN2ulncfDK4Ed1WuORlM9jKyV0hOCdEQeuhhCbtzcbQ4ZdDf06nrkLwkhOgBOYD/wt+o3SaOpPLKbCAAACtpJREFUOkbWiqPMhCAjjzy4LmBNxZTOWrE7nUGXtVItIZdSXuWvhmg0/sA92On0nhAUYdXph6FKaWvFpq0VjaZ2YzGbKHbIMhH5sI4NeWx0J1rXj67J5mlqgNITgoLRWgmuo9GEPFaTqrVSevGA+Egrf72oNUIEVySmqZiwMumHwWetaCHXBBVWswm7o2RCkDnILljN2RNeOmvFKYNuQlBwHY0m5LGYhdeEoGDzQjVnj7X0FH2HnqKv0dRqVPph2QlBmtDFZ9EsHZFrNLUXlX5YsviyDsg1ZSYEOUNwir5GE0hYzCbsTrWwhNUs9OCmBovHEoCgfgdbTy24jkYT8oSZXUu9OaVen1MDgBCCMLPJa2GJYBs70UKuCSosJuFaIUjqkrUaN2EWkzv90KYXltBoajcWV/qh3enUqYcaN+EWE8UOJ4U2Byfyi2kYF17TTfIrWsg1QUWYWWBzqvTDYMtM0FQdw1pJO56HlNA6Maamm+RX9JmuCSosZhNSqgyFYPNBNVXHalFCnpqZBxB0pRq0kGuCCiOtrMBmD7oUM03VMSLyfVlKyFtpIddoai9GXY2CYoeOyDVuwlweeWpmHo3iIogOr/Yql7UKLeSaoMIQ70Jb8GUmaKpOmGGtZOUGXTQOWsg1QYbVNYuvwKYjck0JntZK60Qt5BpNrcbIHS+0ObRHrnETZjFx9HQhp/JtOiLXaGo7JYOdDp1+qHETbjFx4EQ+AG2CLPUQtJBrggyrHuzU+CDMotJSIfgyVsBPQi6E+KcQQgoh6vtjfxpNVbF6RuTaWtG4MLKZrGZBs7qRNdwa/1NtIRdCNAdGAgeq3xyNpnpYPD1yba1oXBg9tZYJ0UGZzeSPI3odeAiQftiXRlMtjKwVtcCujsg1CqMmeTDaKlBNIRdCXAkcklJursS2twsh1gkh1mVmZlbnYzWacrF6+OLaI9cYGEIejKmHABVObxJCLAAa+XjpMeBR4JLKfJCUciowFSA5OVlH75pzgme3WVsrGgO3kAdpRF6hkEspR/h6XgjRDWgFbHatwtIM2CCE6CelPOLXVmo0lcRzUV1dxlZjEG42IvLgSz2ESgh5eUgptwINjMdCiDQgWUqZ5Yd2aTRVwnMJL6u2VjQuwq1mIHg98uCqHKMJeTyF3KytFY2Lq3o3o3F8BPVjgmtBCQO/CbmUMslf+9JoqopnpopVWysaF43iI5jQu1lNN+OcoUMWTVDhuU6nTj/UhApayDVBhdXimX6oT29NaKDPdE1Q4SneOo9cEypoIdcEFTr9UBOKaCHXBBXe6Yf69NaEBvpM1wQVngOcZm2taEIELeSaoMIzCtfph5pQQQu5JqgwmYQ7EtcTgjShgj7TNUGHka2iI3JNqKCFXBN0GKvBaI9cEypoIdcEHcaAZzCuBKPR+EKf6ZqgwxBwPSFIEypoIdcEHWFayDUhhhZyTdBhWCtWba1oQgR9pmuCDqse7NSEGFrINUGHTj/UhBpayDVBR0lErk9vTWigz3RN0GF1px/qiFwTGmgh1wQdOv1QE2pUS8iFEE8LIQ4JITa5fkb7q2EaTVVxR+TaWtGECP5YfPl1KeWrftiPRuMXDI9cWyuaUEGHLJqgw4jEtbWiCRX8IeR3CyG2CCGmCSHqlreREOJ2IcQ6IcS6zMxMP3ysRuObMIu2VjShRYVnuhBigRBim4+fscB7QBugJ5ABvFbefqSUU6WUyVLK5MTERL8dgEZTGndErq0VTYhQoUcupRxRmR0JIT4EZlW7RRpNNXFXP9TWiiZEqG7WSmOPh+OBbdVrjkZTfdxFs3StFU2IUN2slX8LIXoCEkgD/q/aLdJoqomOyDWhRrWEXEp5o78aotH4C+2Ra0IN3ffUBB1hFiP9UJ/emtBAn+maoMOwVLS1ogkVtJBrgg6LntmpCTG0kGuCjjBda0UTYvij1opGU6sY3a0xJpMgMsxc003RaM4LOmTRBB2tE2O48+K2Nd0Mjea8oYVco9FoAhwt5BqNRhPgaCHXaDSaAEcLuUaj0QQ4Wsg1Go0mwNFCrtFoNAGOFnKNRqMJcLSQazQaTYAjpJTn/0OFyAT2V/Ht9YEsPzanJtHHUnsJpuPRx1I7qcqxtJRSllkrs0aEvDoIIdZJKZNruh3+QB9L7SWYjkcfS+3En8eirRWNRqMJcLSQazQaTYATiEI+taYb4Ef0sdRegul49LHUTvx2LAHnkWs0Go3Gm0CMyDUajUbjgRZyjUajCXACSsiFEKOEEDuFEHuEEI/UdHvOBiFEcyHEIiFEihDiDyHEva7n6wkhfhVC7Hb9rlvTba0sQgizEGKjEGKW63ErIcRq17F8LYQIq+k2VgYhRB0hxHdCiB2u72dAoH4vQoj7XefXNiHEl0KIiED6XoQQ04QQx4QQ2zye8/ldCMWbLj3YIoToXXMtL0s5x/KK6zzbIoSYIYSo4/HaZNex7BRCXHo2nxUwQi6EMAPvAJcBnYGJQojONduqs8IOPCCl7ARcANzlav8jwEIpZTtgoetxoHAvkOLx+GXgddexnARuq5FWnT1vAHOllB2BHqhjCrjvRQjRFLgHSJZSdgXMwHUE1vcyHRhV6rnyvovLgHaun9uB985TGyvLdMoey69AVylld2AXMBnApQXXAV1c73nXpXmVImCEHOgH7JFSpkopi4GvgLE13KZKI6XMkFJucP19GiUWTVHH8F/XZv8FxtVMC88OIUQzYAzwkeuxAIYB37k2CYhjEULEARcBHwNIKYullKcI0O8FtQ5vpBDCAkQBGQTQ9yKlXAKcKPV0ed/FWOBTqVgF1BFCND4/La0YX8cipZwvpbS7Hq4Cmrn+Hgt8JaUsklLuA/agNK9SBJKQNwUOejxOdz0XcAghkoBewGqgoZQyA5TYAw1qrmVnxX+AhwCn63ECcMrjJA2U76c1kAl84rKJPhJCRBOA34uU8hDwKnAAJeDZwHoC83vxpLzvItA14VbgF9ff1TqWQBJy4eO5gMudFELEAN8D90kpc2q6PVVBCHE5cExKud7zaR+bBsL3YwF6A+9JKXsBeQSAjeILl3c8FmgFNAGiUfZDaQLhe6kMgXrOIYR4DGW3fm485WOzSh9LIAl5OtDc43Ez4HANtaVKCCGsKBH/XEr5g+vpo0Z30PX7WE217yy4ELhSCJGGsriGoSL0Oq4uPQTO95MOpEspV7sef4cS9kD8XkYA+6SUmVJKG/ADMJDA/F48Ke+7CEhNEELcBFwO3CBLJvJU61gCScjXAu1cI/BhqIGBn2q4TZXG5SF/DKRIKad4vPQTcJPr75uAH893284WKeVkKWUzKWUS6nv4TUp5A7AIuNq1WaAcyxHgoBCig+up4cB2AvB7QVkqFwgholznm3EsAfe9lKK87+InYJIre+UCINuwYGorQohRwMPAlVLKfI+XfgKuE0KECyFaoQZw11R6x1LKgPkBRqNGevcCj9V0e86y7YNQXaUtwCbXz2iUt7wQ2O36Xa+m23qWx3UxMMv1d2vXybcH+BYIr+n2VfIYegLrXN/NTKBuoH4vwDPADmAb8BkQHkjfC/Alyt+3oaLU28r7LlB2xDsuPdiKytap8WOo4Fj2oLxwQwPe99j+Mdex7AQuO5vP0lP0NRqNJsAJJGtFo9FoND7QQq7RaDQBjhZyjUajCXC0kGs0Gk2Ao4Vco9FoAhwt5BqNRhPgaCHXaDSaAOf/BwD9VaUh8QADiwAAAABJRU5ErkJggg==\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# amygdala\n", + "timeCorr('mid', 'vmPFC','vmPFC', '1', '2')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/RSA.ipynb b/task_based_analysis/RSA.ipynb new file mode 100644 index 0000000..c4bc90e --- /dev/null +++ b/task_based_analysis/RSA.ipynb @@ -0,0 +1,3288 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "# Map beta of each condition and correlate between sessions" + ] + }, + { + "cell_type": "code", + "execution_count": 433, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [], + "source": [ + "# import relevant packages\n", + "import glob\n", + "import numpy as np\n", + "import scipy\n", + "import nilearn\n", + "import nilearn.plotting\n", + "import nilearn.input_data\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import statsmodels.stats as sm # for FDR correction" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## No apperant contribution to before/after treatment in general. \n", + "- Lets look at group differences in ROIs $\\rightarrow$\n", + " * Amygdala\n", + " * vmPFC\n", + " * Hippocampus\n", + " * Striatum\n", + "- We compare pattern of ROI activation in the trauma > relax contrast on the 2nd day" + ] + }, + { + "cell_type": "code", + "execution_count": 460, + "metadata": {}, + "outputs": [], + "source": [ + "thr = 0.05 # set threshold\n", + "def fdr_corr(p, thr=0.05):\n", + " # FDR correction\n", + " # takes the p from the t test, flatten and return a 36x36 mask\n", + " # flatten p\n", + " pflat = p.flatten()\n", + " fdr = sm.multitest.multipletests(pflat, alpha=thr, method='fdr_bh')\n", + " fdrArr = fdr[1].reshape(9,9)\n", + " return fdrArr " + ] + }, + { + "cell_type": "code", + "execution_count": 435, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Amygdala as mask\n", + "mask_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=21\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "\n", + "\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " smoothing_fwhm=None, verbose=0).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 514, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# now lets do the same with vmPFC\n", + "mask_file = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=5\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None, standardize=True,\n", + " detrend=False, verbose=0).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 502, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [], + "source": [ + "# compare between groups\n", + "import pandas as pd\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "medication_cond\n", + "\n", + "group_label = np.array(medication_cond.med_cond)\n", + "group_label = list(map(int, group_label))\n", + "\n", + "sub_list = np.array(medication_cond.scr_id)" + ] + }, + { + "cell_type": "code", + "execution_count": 509, + "metadata": {}, + "outputs": [], + "source": [ + "group_label = group_label[sub_list!='KPE1390'] # removing one subject for now\n" + ] + }, + { + "cell_type": "code", + "execution_count": 504, + "metadata": {}, + "outputs": [], + "source": [ + "subject_list = []\n", + "for sub in sub_list:\n", + " sub = sub.split('KPE')[1]\n", + " subject_list.append(sub)\n", + "subject_list.remove('1390')" + ] + }, + { + "cell_type": "code", + "execution_count": 505, + "metadata": {}, + "outputs": [], + "source": [ + "# function to find ev number (lookin in run.fsf file)\n", + "def findEV(txtFile, condition):\n", + " # takes the txtFile and the specific condition\n", + " with open(txtFile) as f:\n", + " datafile = f.readlines()\n", + " lines = []\n", + " for line in datafile:\n", + " if condition in line:\n", + " # found = True # Not necessary\n", + " #print(line)\n", + " lines.append(line)\n", + "\n", + " return lines[0].split('evtitle')[1].split(')')[0]\n", + "\n", + "def getCorr(sub, condition):\n", + " fsf_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/allScript_ses{ses}_Nosmooth/modelfit_ses_{ses}/_subject_id_{sub}/level1design/run0.fsf'\n", + " betaTemplate = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/allScript_ses{ses}_Nosmooth/modelfit_ses_{ses}/_subject_id_{subject_id}/modelestimate/mapflow/_modelestimate0/results/pe{betaNum}.nii.gz'\n", + "\n", + " # get beta files for session 1 condition X\n", + " beta1 = fsf_template.format(ses='1', sub=sub)\n", + " number_1 = findEV(beta1, condition)\n", + " # find beta file\n", + " betaFile_1 = betaTemplate.format(ses='1', subject_id = sub, betaNum = number_1)\n", + " beta1_transform = masker.transform(betaFile_1)\n", + " # get beta files for session 2 condition X\n", + " beta2 = fsf_template.format(ses='2', sub=sub)\n", + " number_2 = findEV(beta2, condition)\n", + " # find beta file\n", + " betaFile_2 = betaTemplate.format(ses='2', subject_id = sub, betaNum = number_2)\n", + " beta2_transform = masker.transform(betaFile_2)\n", + "\n", + " #correlate it\n", + " cor = scipy.stats.pearsonr(beta1_transform[0], beta2_transform[0])[0]\n", + " return cor, beta1_transform, beta2_transform\n", + "\n", + "def generatCor(cond_list, beta1Arr, beta2Arr):\n", + " # this functuion creates a simple matrix of correlation between session 1 and 2\n", + " x = np.zeros([len(cond_list),len(cond_list)])\n", + " for i, cond in enumerate(cond_list):\n", + " \n", + " for j, c in enumerate(cond_list):\n", + " x[i,j] = scipy.stats.pearsonr(beta1Arr[i], beta2Arr[j])[0]\n", + " return x" + ] + }, + { + "cell_type": "code", + "execution_count": 506, + "metadata": {}, + "outputs": [], + "source": [ + "# get condition list\n", + "events_file = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/sub-1464_ses-1.csv'\n", + "cond = pd.read_csv(events_file, sep='\\t')\n", + "cond_list = np.unique(cond.trial_type_N)\n", + "#cond_list" + ] + }, + { + "cell_type": "code", + "execution_count": 507, + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 0 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. 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Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 1 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. 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Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 2 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 3 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 4 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 5 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 6 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 7 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 8 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 9 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 10 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 11 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 12 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 13 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 14 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 15 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 16 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 17 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 18 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 19 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + } + ], + "source": [ + "corTot = [] \n", + "corAll = []\n", + "corAllz = []\n", + "for i, sub in enumerate(subject_list):\n", + " print (f' Running the {i} subject')\n", + " beta1Arr = []\n", + " beta2Arr = []\n", + " conditions = []\n", + " for cond in cond_list:\n", + " cor, beta1, beta2 = getCorr(sub, cond)\n", + " corTot.append(cor)\n", + " conditions.append(cond)\n", + " beta1Arr.append(beta1[0])\n", + " beta2Arr.append(beta2[0])\n", + " corMat = generatCor(cond_list, beta1Arr, beta2Arr)\n", + " # adding z-fisher transformation\n", + " corMatz = np.arctan(corMat)\n", + " corAll.append(corMat)\n", + " corAllz.append(corMatz)" + ] + }, + { + "cell_type": "code", + "execution_count": 536, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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lvKfLbTEz61jCHeGW+QYTM6uUlGvHrXJiNrNKcY/ZzCwx0VaXOc23nTgxm1ml5HCrdemcmM2sUmoVKDI7MZtZpbjG3IKXd3l9t0Ns4jdbHVp4TIC9ex4qJe5tz/9FKXEP6Hm0lLixZfF1wdob9i08JsCkdc+UEndwiymlxM2DE7OZWWJqFcjMTsxmVinhwT8zs7QMDbnHbGaWlJQfTtQqJ2Yzq5QKzJZzYjazamnvzr80OTGbWaVUoJLhxGxm1eI7/8zMElPzrAwzs7RU4QaTMd/5J+lzkvYoqjFmZp2qwjv/mr2M9avAHZJ+IelvJO1SRKPMzDZXrRYtL6lqlphXANOpJ+i3AvdJ+pGkk7MXtI5IUp+kfkn9Fy+8PsfmmpmNLaL1JVXNaswRETXgRuBGSZOBo4ETga8DI/agI2I+MB/guaU3JXz5ZlY1QxV4Un6zxPyq5ytGxCvAImCRpK271iozs800EW4w+dBoOyJifc5tMTPrWOUTc0SU8+R3M7PNVIG87HnMZlYtle8xm5mNNynPT26VE7OZVcpEmJVhZjauuJRhZpYYJ2Yzs8RU4SFGXU/Ma3Z4Y7dDbGLWsosLjwkw8KZjSol7zNr/LiXu0zu+o5S4z7w8rfCYj73u0MJjAsz4+fmlxF05fU4pcXfK4RxF9ZglvQa4EtgLeAz4YEQ8M8qxvUA/8EREHNvs3M2elWFmNq4U+HS5M4GbI2ImcHP2eTSnA/e3emInZjOrlKHBWstLh+YBl2TrlwDHj3SQpOnA+4ALWj2xE7OZVUo7PebGJ2FmS18boXaNiNVZzNXA60Y57pvAF4CWfxJ48M/MKiVqrfeEG5+EORJJNwG7jbDrrFbOL+lYYG1E3CXpiFbb5cRsZpWS5wPwI+Ko0fZJWiNpakSsljQVWDvCYYcBx0k6BtgK2F7SZRHxkbHiupRhZpVS4ODfIuDkbP1k4NoR2vKliJgeEXsBJwA/aZaUwYnZzCqmNlhreenQOcAcSQ8Dc7LPSNpd0uJOTuxShplVSi2KeVZGRDwNHDnC9lXAJjc1RMQtwC2tnNuJ2cwqxbdkm5klpvKJWdIW1AvWqyLiJkknAW+nfgfL/OwdgGZmyZgIz2O+KDtmG0knA9sCC6nXVWbzpxFJM7Mk1NqYx5yqZon5LRGxv6RJwBPA7hExJOky4J7RvpTdPdMH8JV//jc+dMJJuTXYzGwstaGhspvQsWaJuScrZ0wBtgF2AH4PbAlMHu1LjXfTPPTI4+P/9wozGzcqX2MGLgQeAHqp34J4laQVwCHAFV1um5lZ2yqfmCPiG5KuzNZXSboUOAr4TkTcWUQDzczaUdQ85m5qOl0umyy9cf1Z4OqutsjMrAOV7zGbmY037TxdLlVOzGZWKRNhVoaZ2biS52M/y+LEbGaV4lKGmVliPPhnZpaYmAjT5czMxpPa4Pgf/FPKT2KS1Jfd3u24FYrpuNWNWWbcKkn91VLtvErcccdPTMetbswy41ZG6onZzGzCcWI2M0tM6om5rDrVRIo7ka51osWdSNdaKUkP/pmZTUSp95jNzCYcJ2Yzs8Qkm5glzZX0oKTlks4sKOYCSWsl3VtEvCzmHpJ+Kul+ScsknV5Q3K0k3Snpnizu2UXEzWL3SvqVpOuKipnFfUzSbyTdLam/oJg7Srpa0gPZ3/GhBcTcJ7vGjcvzks7odtws9t9m/57ulXS5pK2KiFs1SdaYJfUCDwFzgAFgCXBiRNzX5biHA+uASyPizd2M1RBzKjA1IpZK2g64Czi+gGsVMCUi1kmaDNwKnB4Rt3czbhb774BZwPYRcWy34zXEfQyYFRFPFRjzEuAXEXFB9v7MbbIXThQVv5f6i5QPjojfdjnWNOr/jvaLiPWSvg8sjoiLuxm3ilLtMc8GlkfEiojYQP39gvO6HTQifk79ZbOFiYjVEbE0W38BuB+YVkDciIh12cfJ2dL1n9KSpgPvAy7odqyySdoeOJz6uzOJiA1FJuXMkcAj3U7KDSYBW0uaRP0FzquaHG8jSDUxTwNWNnweoIBkVTZJewEHAncUFK9X0t3AWuDHEVFE3G8CXwDKeNJMADdKuktSEXenvQH4HXBRVrq5QNKUAuI2OgG4vIhAEfEE8HXgcWA18FxE3FhE7KpJNTFrhG3p1VxyJGlb4BrgjIh4voiYETEUEQcA04HZkrpavpF0LLA2Iu7qZpwxHBYRBwFHA6dmpatumgQcBHw7Ig4EXgQKGS8ByEonxwFXFRRvJ+q/2c4AdgemSPpIEbGrJtXEPADs0fB5OhX+lSir8V4DfDciFhYdP/v1+hZgbpdDHQYcl9V6rwDeLemyLsf8o40vFo6ItcAPqJfMumkAGGj4TeRq6om6KEcDSyNiTUHxjgIejYjfRcQrwELg7QXFrpRUE/MSYKakGdlP/ROARSW3qSuyQbgLgfsj4twC4+4iacdsfWvq/1M90M2YEfGliJgeEXtR/zv9SUQU0qOSNCUbXCUrJ7wH6Orsm4h4ElgpaZ9s05FAVwd1hzmRgsoYmceBQyRtk/27PpL6mIm1KcnnMUfEoKTTgBuAXmBBRCzrdlxJlwNHADtLGgC+HBEXdjnsYcBHgd9k9V6Af4iIxV2OOxW4JBu17wG+HxGFTl8r2K7AD+r5gknA9yLiRwXE/Szw3ayDsQI4pYCYSNqG+qymvy4iHkBE3CHpamApMAj8Ct+evVmSnC5nZjaRpVrKMDObsJyYzcwS48RsZpYYJ2Yzs8Q4MZuZJcaJ2cwsMU7MZmaJ+X9Taoj7nopsMAAAAABJRU5ErkJggg==\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "for cor in corAll:\n", + " sns.heatmap(cor, cmap=\"coolwarm\", vmin = -.5, vmax = .5)\n", + " plt.show()\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 537, + "metadata": {}, + "outputs": [], + "source": [ + "# seperate ketamine and midazolam\n", + "group_label = np.array(group_label)\n", + "ketArr = np.array(corAllz)[group_label==1]\n", + "midArr = np.array(corAllz)[group_label==0]" + ] + }, + { + "cell_type": "code", + "execution_count": 538, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot mean matrices\n", + "fig, ax_list = plt.subplots(1, 2, figsize=(16,4.5))\n", + "ax = ax_list[0]\n", + "ax.title.set_text('Ketamine')\n", + "sns.heatmap(np.mean(np.array(ketArr), axis=0), cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax, annot=True)\n", + "ax = ax_list[1]\n", + "ax.title.set_text('Midazolam')\n", + "sns.heatmap(np.mean(np.array(midArr), axis=0), cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax, annot=True)\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 520, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 520, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# compare the groups\n", + "t,p = scipy.stats.ttest_ind(ketArr, midArr)\n", + "tArr = np.array(t)\n", + "fdr = fdr_corr(p, thr)\n", + "tArr[p>.01]=0 # set p value to cut\n", + "sns.heatmap(tArr, cmap='coolwarm',xticklabels = cond_list, yticklabels = cond_list, annot=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 247, + "metadata": {}, + "outputs": [], + "source": [ + "# saving to mat\n", + "from scipy.io import savemat\n", + "mdict = {'ketamine': np.mean(np.array(ketArr), axis=0), 'midazolam': np.mean(np.array(midArr), axis=0)}\n", + "savemat('averagedMat_acrossSessions.mat', mdict)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Use PCA to see if groups differ" + ] + }, + { + "cell_type": "code", + "execution_count": 521, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(20, 9)" + ] + }, + "execution_count": 521, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# use the vector of correlations for each subject\n", + "listCorsubs = np.array(corTot).reshape(20,9)\n", + "listCorsubs.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 522, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.decomposition import PCA\n", + "pca = PCA(n_components=2)\n", + "X_r = pca.fit(listCorsubs).transform(listCorsubs)" + ] + }, + { + "cell_type": "code", + "execution_count": 523, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "explained variance ratio (first two components): [0.3003938 0.15593572]\n" + ] + } + ], + "source": [ + "print('explained variance ratio (first two components): %s'\n", + " % str(pca.explained_variance_ratio_))" + ] + }, + { + "cell_type": "code", + "execution_count": 524, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "colors = ['navy', 'red']\n", + "lw = 2\n", + "y = np.array(group_label) # make it an array so we can get mask for each place\n", + "target_names = ['Midazolam','Ketamine']\n", + "for color, i, target_name in zip(colors, [0, 1], target_names):\n", + " plt.scatter(X_r[y == i, 0], X_r[y == i, 1], color=color, alpha=.8, lw=lw,\n", + " label=target_name)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 469, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Try Hirarchical\n", + "from scipy.cluster.hierarchy import dendrogram, linkage, cut_tree\n", + "# That's the hierarchical clustering step\n", + "hier = linkage(listCorsubs, method='average', metric='euclidean') # scipy's hierarchical clustering\n", + "# HAC proceeds by iteratively merging brain regions, which can be visualized with a tree\n", + "res = dendrogram(hier, get_leaves=True) # Generate a dendrogram from the hierarchy" + ] + }, + { + "cell_type": "code", + "execution_count": 470, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[1 0 1 0 1 0 0 0 1 1 1 0 1 1 0 1 0 0 1 1]\n" + ] + } + ], + "source": [ + "# the order of merging above give us a good order to visualize the matrix\n", + "order = res.get('leaves') # Extract the order on parcels from the dendrogram\n", + "print(y[order]) # print group of subjects, according to order" + ] + }, + { + "cell_type": "code", + "execution_count": 471, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0 0 0 0 0 1 1 2 0 0 0 1 1 1 0 0 0 3 3 0]\n" + ] + } + ], + "source": [ + "part = np.squeeze(cut_tree(hier, n_clusters=4)) # Cut the hierarchy\n", + "# Each entry of the vector part is a parcel, and codes for the number of the network of this parcel\n", + "print(part) # e.g. parcel #7 is in cluster 5. What is the cluster of parcel number 10?" + ] + }, + { + "cell_type": "code", + "execution_count": 487, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Run same with hippocampus\n", + "## Hippocampus\n", + "mask_file = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=15\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None, standardize=False, \n", + " detrend=False, verbose=0).fit()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Lets try another thing - Using RSA for the same scan. \n", + "- Hypothesis here will say Ketamine will be fatster to recover, hence lower correlation in trauma" + ] + }, + { + "cell_type": "code", + "execution_count": 525, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 0 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 1 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 2 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 3 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 4 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 5 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 6 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 7 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 8 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 9 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 10 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 11 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 12 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 13 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 14 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 15 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 16 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 17 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 18 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 19 subject\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + } + ], + "source": [ + "cor_OneSes1 = []\n", + "cor_OneSes2 = []\n", + "for i, sub in enumerate(subject_list):\n", + " print (f' Running the {i} subject')\n", + " beta1Arr = []\n", + " beta2Arr = []\n", + " conditions = []\n", + " for cond in cond_list:\n", + " cor, beta1, beta2 = getCorr(sub, cond)\n", + " corTot.append(cor)\n", + " conditions.append(cond)\n", + " beta1Arr.append(beta1[0])\n", + " beta2Arr.append(beta2[0])\n", + " corMat1 = np.corrcoef(beta1Arr)\n", + " corMat2 = np.corrcoef(beta2Arr)\n", + " cor_OneSes2.append(corMat2)\n", + " cor_OneSes1.append(corMat1)" + ] + }, + { + "cell_type": "code", + "execution_count": 526, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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miXDCNjNLRM1NImZmaXAN28wsEWO1Xpege5ywzaxSPHDGzCwRbhIxM0uERzqamSXCNWwzs0Q4YZuZJaLKvUQmHVssaYGk52f7+0i6WNI/S/orSQeWU0Qzs/xqtfxbalpNBrEC2DNBxmeor6L+V9mxLzS7SdJiSRskbbjm+lWFFNTMLI+I/FtqWjWJDEXEaLY/LyKOyfa/LWlTs5siYjmwHODRrXcl+NdiZqlKMRHn1aqGvVnSudn+PZLmAUj6VeDZrpbMzGwKapF/S02rhH0+8EZJPwCOBL4raSfw+eycmVlfiYjcWyuSFkq6T9IOSUsnOC9Jf5udv1fSMXnvnYpJm0Qi4nHgdyQdALw0u34kIh4uIriZWdHGxop5jqRh4ArgJGAEWC9pdURsbbjsFGButi0APgcsyHlv23J164uInwH3dBLIzKwMBbZhzwd2RMROAEkrgUVAY9JdBFwT9er6HZIOkjQTOCzHvW3rzZIhZmZd0k4bdmOPtmxb3PCoWcCuhs8j2TFyXJPn3rZ54IyZVUo7NezGHm0TmGjav/FPb3ZNnnvb5oRtZpUSbXX/mHQq1hFgTsPn2cDunNfMyHFv29wkYmaVMlbLv7WwHpgr6XBJM4AzgNXjrlkNnJ31Fnkd8HhEPJTz3ra5hm1mlVIrqIN1RIxKWgLcAgwDKyJii6QPZOeXAWuAU4Ed1EeAnzvZvZ2WyQnbzCqlyJGOEbGGelJuPLasYT+AC/Pe26muJ+yvPz6v2yH28rzpvRnCdOYFHb8EnpJdY0/0JO4D2x/rSdzjfvPQ0mN+7fKNpccEOPHDr+1J3B03be9J3CJUeWi6a9hmVim1CmdsJ2wzq5RIcNrUvJywzaxSxsZcwzYzS0KeSZ1S5YRtZpWS4rSpeTlhm1mltDfSMS1O2GZWKRVuEXHCNrNqKWqkYz9ywjazSqm5l4iZWRqqPHBm0tn6JP2epDmTXWNm1k+KXNOx37SaXvXjwJ2SviXp/0o6pIxCmZlNVa0WubfUtErYO6lPvP1x4LXAVklrJZ2TLcw7ocZld772T80WczAzK15E/i01rdqwIyJqwDpgnaTp1FcJPhP4G2DCGnfjsjvXfzfBH2NmlqyxHCsTpKpVwn7O+jkR8Sz1VRNWS9qna6UyM5uiQR448+5mJyLi6YLLYmbWsYFN2BFxf1kFMTMrQoXztfthm1m1DGwN28wsNSn2r87LCdvMKmWQe4mYmSXFTSJmZolwwjYzS0SVJ3/qesKec9CT3Q6xlzsfaDpqvqveecS2nsRd/p1f6Unck0/szd/z6WMrS4+5bsG7So8JsOOm7T2J+7J3vqIncXn2vo4f4Rq2mVki3EvEzCwRY6PuJWJmlgTXsM3MEhE117DNzJKQ4sIEeTlhm1mluEnEzCwRtQq/dGy1RJiZWVJqUcu9dULSL0q6VdID2Z8vmOCaOZK+LmmbpC2SPthw7s8l/UjSpmw7tVVMJ2wzq5SoRe6tQ0uB2yJiLnBb9nm8UeAjEXEE8DrgQklHNpy/PCKOyrY1rQI6YZtZpZSYsBcBV2f7VwOn71WWiIci4u5s/2fANmDWVANOmrAlzZB0tqQTs8/vkfRZSRdmC/KamfWViMi9SVosaUPDtriNUIdGxENZzIeAF012saTDgKOBOxsOL5F0r6QVEzWpjNfqpeMXsmv2lXQOsD9wE3ACMB84p1UAM7My1drohx0Ry4Hlzc5L+hrw4glOfbSdMknaH7gR+FBEPJEd/hzwcSCyPy8Dfney57RK2L8WEa+WNA34EfCSiBiT9A/APZMUbjGwGOCP/vzTnP7b5+b4SmZmnauNjRX2rIg4sdk5SQ9LmhkRD0maCTzS5Lrp1JP1lyLipoZnP9xwzeeBf2lVnlYJe0jSDGA/YF/gQOCnwC8ATZtEGn9qfXfbE9XtFGlmfafE2fpWU29l+GT251fGXyBJwFXAtoj41LhzM/c0qQDvADa3CtgqYV8FbAeGqf8K8GVJO6m/7Sx/jkszsxZKTNifBK6XdB7wQ+BdAJJeAlwZEacCxwLvA74vaVN2359mPUL+WtJR1JtEHgTe3yrgpAk7Ii6X9I/Z/m5J1wAnAp+PiLum8AXNzLqq0/7VeUXET6i/zxt/fDdwarb/bUBN7n9fuzFbjnTMgu/Z/y/ghnaDmJmVxQsYmJklwrP1mZklosheIv3GCdvMKsXTq5qZJcJNImZmifBLRzOzRERJ3fp6wQnbzCqlNlrdl47q5+V0JC3Ohrk7boViOm51Y/Yy7iDo9/mw25nq0HHTiem41Y3Zy7iV1+8J28zMMk7YZmaJ6PeE3at2sEGKO0jfddDiDtJ3HQh9/dLRzMz+V7/XsM3MLOOEbWaWiL5N2JIWSrpP0g5JS0uKuULSI5JaLtVTYMw5kr4uaZukLZI+WFLc50m6S9I9WdyLy4ibxR6W9D1JLdewKzjug5K+L2mTpA0lxTxI0g2Stmf/jV9fQsyXZ99xz/aEpA91O24W+8PZv6fNkq6T9Lwy4g6KvmzDljQM3A+cBIwA64EzI2Jrl+O+AXgSuCYiXtXNWA0xZwIzI+JuSQcAG4HTS/iuAvaLiCezRUK/DXwwIu7oZtws9u8D84DnR8Rp3Y7XEPdBYF5EPFZizKuBb0XEldn6qPtmC4GUFX+Y+gLaCyLiP7ocaxb1f0dHRsTTkq4H1kTEF7sZd5D0aw17PrAjInZGxDPU149c1O2gEfFN6osMlyYiHoqIu7P9nwHbgFklxI2IeDL7OD3buv7TW9Js4K3Ald2O1WuSng+8gfraqETEM2Um68wJwA+6nawbTAP2kTSN+sLdu1tcb23o14Q9C9jV8HmEEpJYr0k6DDgauLOkeMPZwqCPALdGRBlxPw38EdCLGXoCWCdpo6QyRuO9FHgU+ELWBHSlpP1KiNvoDOC6MgJFxI+Av6G+IO1DwOMRsa6M2IOiXxP2RItW9l/bTYEk7Q/cCHwoIp4oI2ZEjEXEUcBsYL6krjYDSToNeCQiNnYzziSOjYhjgFOAC7MmsG6aBhwDfC4ijgZ+DpTyPgYga4J5O/DlkuK9gPpvwocDLwH2k/TeMmIPin5N2CPAnIbPs6nwr1ZZG/KNwJci4qay42e/pn8DWNjlUMcCb8/aklcCb5b0D12O+T/2LCgdEY8Aq6g3vXXTCDDS8JvLDdQTeFlOAe6OiIdLinci8O8R8WhEPAvcBPxGSbEHQr8m7PXAXEmHZ7WEM4DVPS5TV2Qv/64CtkXEp0qMe4ikg7L9faj/z7a9mzEj4k8iYnZEHEb9v+m/RkQpNTBJ+2UvdcmaJU4GutobKCJ+DOyS9PLs0AlAV18mj3MmJTWHZH4IvE7Svtm/6xOov5OxgvTlfNgRMSppCXALMAysiIgt3Y4r6TrgeOCFkkaAj0XEVV0OeyzwPuD7WXsywJ9GxJoux50JXJ31IhgCro+IUrvZlexQYFU9jzANuDYi1pYQ9yLgS1nFYydwbgkxkbQv9V5W7y8jHkBE3CnpBuBuYBT4Hh6mXqi+7NZnZmZ769cmETMzG8cJ28wsEU7YZmaJcMI2M0uEE7aZWSKcsM3MEuGEbWaWiP8PF0J9GuEZNdsAAAAASUVORK5CYII=\n", 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xMPBxst/w22lbXoiIh4F3Stod2D+7figiHshr2MysDCMjPWtqBrApIjYDSFoCzAWeXtA5IloXPL4VmJLXaEdTxiLiN8Bd3fTWzKwMPazpTgbubXk/BMxsc/27gP/Ma9TzdM2sVrp5DFjSIDDY8tGibCIAwFgr54zZuqSjaSbdV+XFdNI1s1rpZqTbOtNqDEPA1Jb3U4Atoy+SdDBwMTAnIn6RF9NJ18xqJbpa8abtMpCrgGmS9gPuA+YBJz3j29KLgKXA2yLih51EdNI1s1rp1WPAETEsaT5wAzAALI6IdZJOy84vBD4G/D7weUkAwxExvV27TrpmViuNHq7tGBHLgeWjPlvY8vrddDl91knXzGql6k+kFZ50P3hP+mcoPj15Yf5FBXh81uGlxL3gjgNLifvel64qJe7+0/dNHvO8s2/Jv6gAJ5z1ylLizrzzslLiNh8H2D47fNI1M0upUfGs66RrZrUSFV9P10nXzGplZMQjXTOzZPIWsimbk66Z1Yp3AzYzS6i7J9LSc9I1s1qpeHXBSdfM6qWXT6QVwUnXzGql4dkLZmbpVP3hiLZ7pEl6n6Sp7a4xM6uSXu2RVpS8jSk/Dtwm6TuS/kbSC1J0ysxsWzUa0fFRhryku5nmaukfB14OrJd0vaR3ZJtVjknSoKTVklavu/Wy3vXWzCxHROdHGfJquhERDWAFsELSJJrbEZ8InAuMOfJt3QLj9HN/Xe0Ci5nVykivVjEvSF7SfcZeFhHxJLAMWCZp58J6ZWa2jfr94Yi3jHciIh7vcV/MzLZbXyfdTjdaMzOriornXM/TNbN66euRrplZv/HSjmZmCfX77AUzs77i8oKZWUJOumZmCVV9wZvCk+76lRuLDvEsa845LXlMgEM2XlFK3BVL8p7mLsZee/5FKXFPXntG8pi/euADyWMCzLzzslLi3nboO0uJ+4Yntz9feKRrZpaQZy+YmSU0MuzZC2ZmyXika2aWUDQ80jUzS8YbU5qZJVT18kI5c43MzArSGG50fOSRNFvSRkmbJC0Y47wkfS47f7ekw/La9EjXzGqlEb2p6UoaAC4EjgWGgFWSlkXE+pbL5gDTsmMm8IXsv+PySNfMaiUa0fGRYwawKSI2R8QTwBJg7qhr5gKXR9OtwJ6S9m7XqJOumdVKN0m3dRPd7BhsaWoycG/L+6HsM7q85hnalhck7QTMA7ZExE2STgJeCWwAFmV7ppmZVUY3N9JaN9Edg8b4bHTjnVzzDHk13Uuza3aR9A5gN2ApMIvm0PsdOd83M0uq0bt5ukPA1Jb3U4At23DNM+Ql3ZdGxMGSJgL3AftExIikLwF3jfelbIg+CHDAyxewz/4n5IQxM+uNxshIr5paBUyTtB/N/DcPOGnUNcuA+ZKW0LyB9nBE3N+u0bykOyErMewK7ALsAfwS+D1g0nhfah2yH/3m26o9ac7MaqVXq4xFxLCk+cANwACwOCLWSTotO78QWA68HtgEPAacktduXtK9BPhBFvCjwFckbQYOp3knz8ysUnq5tGNELKeZWFs/W9jyOoDTu2kzbwv2z0r69+z1FkmXA68BLoqIld0EMjNLoVfzdIuS+3BERGxpef1r4JpCe2Rmth28iLmZWUJeZczMLKEezl4ohJOumdWKl3Y0M0vI5QUzs4R8I83MLKHo9yljZmb9pDFc7RtpqvLWFpIGs0eKHbdGMR23vjHLjNsvqr6e7mD+JY7bhzEdt74xy4zbF6qedM3MasVJ18wsoaon3bLqQjtS3B3pZ93R4u5IP2vfqPSNNDOzuqn6SNfMrFacdM3MEqps0pU0W9JGSZskLUgUc7GkByWtTREvizlV0jclbZC0TtKZieI+R9JKSXdlcc9OETeLPSDpTknfSBUzi/sTSd+XtEbS6kQx95R0jaQfZH/Gf54g5ouzn/GpY6uk9xcdN4v9gezv01pJV0l6Toq4/aSSNV1JA8APgWNp7ra5CjgxItYXHPdI4BHg8oj4syJjtcTcG9g7Iu6QtDtwO3BCgp9VwK4R8YikScB3gTMj4tYi42ax/xaYDjw3Io4rOl5L3J8A0yPioYQxvwh8JyIuzvYb3CXbDCBV/AGamyrOjIifFhxrMs2/RwdFxOOSrgaWR8RlRcbtN1Ud6c4ANkXE5oh4guZ+bHOLDhoR36a58WYyEXF/RNyRvf4NsAGYnCBuRMQj2dtJ2VH4v8CSpgBvAC4uOlbZJD0XOJLmXoNExBMpE25mFvCjohNui4nAztkO4ruQsx35jqiqSXcycG/L+yESJKKySdoXOBS4LVG8AUlrgAeBGyMiRdzzgL8HyliVJIAVkm6XlOKpqf2BnwOXZuWUiyXtmiBuq3nAVSkCRcR9wLnAPcD9NLcjX5Eidj+patLVGJ9Vrw7SQ5J2A64F3h8RW1PEjIiRiDgEmALMkFRoSUXSccCDEXF7kXHaOCIiDgPmAKdn5aQiTQQOA74QEYcCjwJJ7k8AZOWM44GvJIr3PJq/ke4H7APsKunkFLH7SVWT7hAwteX9FGr8a0pWU70WuDIilqaOn/3KezMwu+BQRwDHZ7XVJcAxkr5UcMynPbXJakQ8CHyVZhmrSEPAUMtvENfQTMKpzAHuiIgHEsV7DfDjiPh5RDwJLAVemSh236hq0l0FTJO0X/av9TxgWcl9KkR2Q+sSYENEfCZh3BdI2jN7vTPN/2F+UGTMiPiHiJgSEfvS/DP974hIMhKStGt2o5LsV/zXAoXOUomInwH3Snpx9tEsoNAbpKOcSKLSQuYe4HBJu2R/r2fRvEdhLSq5nm5EDEuaD9wADACLI2Jd0XElXQUcBTxf0hBwVkRcUnDYI4C3Ad/P6qsAH4mI5QXH3Rv4YnZ3ewJwdUQkncKV2AuBrzZzAROBL0fE9QningFcmQ0eNgOnJIiJpF1ozv55T4p4ABFxm6RrgDuAYeBO/Ejws1RyypiZWV1VtbxgZlZLTrpmZgk56ZqZJeSka2aWkJOumVlCTrpmZgk56ZqZJfT/8EFEyphalhsAAAAASUVORK5CYII=\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "for cor in cor_OneSes1:\n", + " sns.heatmap(cor, cmap=\"coolwarm\")#, vmin = -1, vmax = 1)\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 539, + "metadata": {}, + "outputs": [], + "source": [ + "# seperate ket from mid - numpy way\n", + "group_label = np.array(group_label)\n", + "\n", + "ketArrSes1 = np.array(cor_OneSes1)[group_label==1]\n", + "midArrSes1 = np.array(cor_OneSes1)[group_label==0]\n", + "\n", + "# second session\n", + "ketArrSes2 = np.array(cor_OneSes2)[group_label==1]\n", + "midArrSes2 = np.array(cor_OneSes2)[group_label==0]" + ] + }, + { + "cell_type": "code", + "execution_count": 528, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(9, 9, 9)" + ] + }, + "execution_count": 528, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "midArrSes1.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 540, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot mean matrices\n", + "fig, ax_list = plt.subplots(1, 2, figsize=(16,4.5))\n", + "ax = ax_list[0]\n", + "ax.title.set_text('Ketamine')\n", + "sns.heatmap(np.mean(ketArrSes2, axis=0), cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax,\n", + " vmin = -1, vmax=1, annot=True)\n", + "ax = ax_list[1]\n", + "ax.title.set_text('Midazolam')\n", + "sns.heatmap(np.mean(midArrSes2, axis=0), cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax,\n", + " vmin = -1, vmax=1, annot=True)\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 530, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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/y2Bhg82OAY5Psh44C/geQJKXArdU1aebf5ScmuRg4D7AbwE7JjmsOcZhVXXWpF6HJGl+WfrPMrut8Jrjby684bOviy482c2SNC0m0M07AZcO3b8MeMSMfd7HYG2By4G7AM9faPX2JR2MVtUlwN5D99/DYJrVzP3WNl+vBg6a5VCXMFhogaq6ldEX+qklCyxJGtsEFj6YSOFNK7tZkqbPYrs5yRHAEUMPrWuu879tl1l+bOa1/09hcBLzYOD+wBeTfL2qfjnX807snVFJ0nRY7HUpbRWeJEnTYrHdPLzA3BwuA+47dH9nBieEhx0OvKOqCrgoycXAg4DvzHVQB6OSpPEs8uxrW4UnSdLUWPpZS6cDuyfZDfgJ8ALgRTP2+THwRODrSe7F4GPFfjjfQR2MSpLGMoHVdCdSeJIkTYul7uaquiXJaxgshLcaOLqqzktyZLP9KOCtwMeSbGAwy+lPm0s/5uRgVJI0lmRpz75OqvAkSZoWS93NAFV1InDijMeOGvr+cgafZb3VHIxKksYzgc8ZnUThSZI0NSbQzZPgYFSSNJYJrKYrSZLG0JdudjAqSRrLBK4ZlSRJY+hLN0/FYPSs7/607Qi3ufsXL2w7whbu8aQ92o4w4rMf3tB2hBFPPmBj2xFG7LL7PduOMOLii69vO8KIL23/kLYjjHjcQ65rO8IMd1n6Q07guhStfD/83pVtR7jNzX9/VtsRRjzuD/ZtO8IWPv7ak9uOMOJxh+zadoQRV955m7YjjLj26m51z8kn/aTtCCPe9Ipb244ww/2W/pA96eapGIxqbl0biErqn76cfZUkaVr0pZsdjEqSxpLVq9uOIEmShvSlmx2MSpLG05NFEiRJmho96WYHo5KksfRlKpAkSdOiL93sYFSSNJ6eLJIgSdLU6Ek3OxiVJI2nJ2dfJUmaGj3pZgejkqSxpCdnXyVJmhZ96WYHo5Kk8fTk7KskSVOjJ93sYFSSNJb0ZMU+SZKmRV+62cGoJGk86cfZV0mSpkZPurmVIXOS62/nz+2S5LtJzkpyXpIjlzqbJGmRVq1a3E2dZDdL0grSk26e2DujSQKkqjYt4WGvAB5VVTclWQucm+S4qrp8CZ9DkrQYPTn7KrtZkqZGT7p5SYfBSXZNckGSDwBnAG9McnqSc5L81Sz7r03ypSRnJNmQ5FnN4wc0P7MmyZ2bM617V9Wvq+qm5sd/Y6nzS5IWL6tWLeqm5WU3S9L06Us3T+Kd0T2Aw4HPA88FDgQCHJfkt6rqa0P73gg8p6p+meTuwGnN2dTTkxwHvA3YFvhUVZ0LkOS+wBeABwCv88yrJLWsJ8vHTzm7WZKmSU+6eRIpf1RVpwFPbm5nMjgT+yBg9xn7BvjrJOcA/w7sBNyr2fYW4EnA/sDfbP6Bqrq0qvZhUHgvS3IvZpHkiCTrk6z/zzM/tWQvTpI0w6os7qY2dK6bLzr700v24iRJM/SkmyfxzugNzdcAb6+qD82z74uBewD7VdXNSS4B1jTb7gasBbZpHrth+Aer6vIk5wGPBY6deeCqWgesA/jdN1xet/vVSJLm1ZcP1p5ynevmF/7Jj+1mSZqQvnTzJFOeDLy8WcyAJDslueeMfbYHrmrK7gnALkPb1gFvBI4B3tkcY+ck2zbf3xV4NHDhBF+DJGkhPTn7KsBulqTp0JNunthqulV1SpIHA98aLN7H9cDvAlcN7XYMcHyS9cBZwPcAkrwUuKWqPp1kNXBqkoOB1cDfJikGZ3ffXVUbJvUaJElboSdnX2U3S9LU6Ek3L+lgtKouAfYeuv8e4D2z7Le2+Xo1cNAsh7oE+ESzz63AI4a27bNkgSVJ4+vJ8vHTym6WpCnUk26e2DujkqQp4ce1SJLULT3pZgejkqTx9GQqkCRJU6Mn3exgVJI0HhclkiSpW3rSzQ5GJUnjWbW67QSSJGlYT7rZwagkaTw9uS5FkqSp0ZNudjAqSRpPT1bskyRpavSkmx2MSpLG05NFEiRJmho96WYHo5Kk8fRkKpAkSVOjJ908FYPRw56/Y9sRbrPjtle3HWHEZz+8oe0IWzjovz+k7QgjLjr5wrYjjPjB+Re3HWHEEYfdp+0II67ZuKntCCM+/9Vu/Zp91IMncNCeTAVStzz+kPu1HeE2P7vm1rYjjPj4a09uO8IWXvbep7QdYcQZ+5/XdoQRZ5/WrW4+9Fl7tB1hxMYbq+0II970oUvbjjDiH/9mAgftSTd3619JkqT+6clUIEmSpkZPutnBqCRpPD05+ypJ0tToSTc7GJUkjacn16VIkjQ1etLNDkYlSWOpnpx9lSRpWvSlm/sxZJYkdVdWLe4mSZImawLdnOTQJBcmuSjJ6+fY5/FJzkpyXpKvLnRM3xmVJI3HAaYkSd2yxN2cZDXwfuBJwGXA6UmOq6rzh/bZAfgAcGhV/TjJPRc6roNRSdJY+jIVSJKkaTGBbj4QuKiqfgiQ5DPAs4Dzh/Z5EfC5qvoxQFVdtdBBPZ0tSRpPT6YCSZI0NRbZzUmOSLJ+6HbEjCPuBAx/QOtlzWPDHgjcNclXknw3yUsXiuk7o5Kk8Szx2ddJTQWSJGlqLLKbq2odsG6+I872YzPu3wHYD3gisC3wrSSnVdX35zpo598ZTbJrknOb73dM8uUk1yd5X9vZJEkMlo9fzG1ht00FqqpfA5unAg1b9FQgLR27WZI6bum7+TLgvkP3dwYun2Wfk6rqhqq6Gvga8NB5Yy7iJXXBjcAbgT9uO4gkaaCSRd3amgqkibGbJaljFtvNW+F0YPckuyW5I/AC4LgZ+/wr8Ngkd0hyJ+ARwAXzHXTZpukmuTPwTwxG0auBtwJ7AM9k8DbuqcArq6qS7AccDWwEvrH5GFV1A/CNJA9YrtySpAUscsW+tqYCaUt2syStUEu8mm5V3ZLkNcDJDPri6Ko6L8mRzfajquqCJCcB5wCbgI9U1bnzHXc5rxk9FLi8qp4OkGR74ItV9Zbm/ieBZwDHAx8F/qCqvprkXcuYUZK0SLX0H+2ytVOBrm4GQjck2TwVyMHo4tjNkrQCTaCbqaoTgRNnPHbUjPvvAra6I5Zzmu4G4JAk70zy2Kq6FnhCkm8n2QAcDOzVFOEOVbV5ZcRP3p4nG54G9oVjP7I0r0CStKVkcbeFTWQqkGbVWjd//cT53hyXJI1l6bt5IpbtndGq+n4zxedpwNuTnAK8Gti/qi5N8mZgDYPpWTOnY92e57ttGti/n3PT2MeTJM1uqc++TmoqkLbUZjd/6JTxjydJmt0k3hmdhOW8ZvQ+wM+r6lNJrgcOazZdnWQt8Fzg2Kr6RZJrkzymqr4BvHi5MkqSbocJnFGdxFQgbclulqQVqsV3OxdjOa8ZfQjwriSbgJuBVwHPZjBF6BIG07I2Oxw4OslGBmfGb5PkEmA74I5Jng08efiz5yRJy6tWrW47gm4/u1mSVqC+dPNyTtM9mRnlBawH/mKWfb/L6GfSvHlo264TiCdJur16MhVIW7KbJWmF6kk3L+c7o5KkFahm/SQWSZLUlr50s4NRSdJY+rJIgiRJ06Iv3exgVJI0np4UniRJU6Mn3exgVJI0lurJin2SJE2LvnSzg1FJ0lj6MhVIkqRp0ZdudjAqSRpPT86+SpI0NXrSzQ5GJUlj6cvZV0mSpkVfutnBqCRpLH1ZPl6SpGnRl26eisHoZ0/+VdsRbvPYg3ZsO8KIJx+wse0IW7jo5AvbjjDiXk/Zo+0II/b5xHltRxhx4tdvbDvCiN9+3Ka2I4y412+uaTvCxPXl7Ku65fOfPqftCLfZ88D7tx1hxOMO2bXtCFs4Y/9udc/DX7pX2xFGXPWu09uOMOKyy29qO8KI++/6G21HGLHtne3mrpiKwagkaYJ6cl2KJElToyfd7GBUkjSWoh9nXyVJmhZ96WYHo5KksfTls8wkSZoWfelmB6OSpLH05boUSZKmRV+62cGoJGksfVmxT5KkadGXbnYwKkkaS1/OvkqSNC360s0ORiVJY+nLdSmSJE2LvnSzg1FJ0lj6MhVIkqRp0ZdudjAqSRpLX6YCSZI0LfrSzQ5GJUlj6cvZV0mSpkVfurnzQ+YkuyY5t/n+SUm+m2RD8/XgtvNJ0rTblNWLuqn/7GZJ6ra+dHPf3hm9GnhmVV2eZG/gZGCnljNJ0lTry1QgTYzdLEkd05duXrbBaJI7A/8E7AysBt4K7AE8E9gWOBV4ZVVVkv2Ao4GNwDc2H6Oqzhw65HnAmiS/UVU3Lc+rkCTN1JepQNqS3SxJK1Nfunk5h8yHApdX1UOram/gJOB9VXVAc39b4BnNvh8FXltVB81zvP8KnDlX2SU5Isn6JOvPP+1jS/cqJEkjKlnUTZ3SWjdf+v1jl/BlSJKG9aWbl3MwugE4JMk7kzy2qq4FnpDk20k2AAcDeyXZHtihqr7a/NwnZx4oyV7AO4FXzvVkVbWuqvavqv33fORhS/5iJEkDVVnUTZ3SWjff94HPXfpXI0kC+tPNyzZNt6q+30zxeRrw9iSnAK8G9q+qS5O8GVgDBKi5jpNkZ+BfgJdW1Q8mn1ySNJ/q/lp4moPdLEkrU1+6edlSJrkPsLGqPgW8G3h4s+nqJGuB5wJU1S+Aa5M8ptn+4qFj7AB8AfizqvrmcmWXJM2tyKJu6g67WZJWpr5083KupvsQ4F1JNgE3A68Cns1gitAlwOlD+x4OHJ1kI4NV+TZ7DfAA4I1J3tg89uSqumrC2SVJc3CA2Wt2syStQH3p5uWcpnsyo+UFsB74i1n2/S7w0KGH3tw8/jbgbROKKEm6HfpSeNqS3SxJK1NfurlvnzMqSeqYvhSeJEnToi/d7GBUkjQWV8iVJKlb+tLNDkYlSWPpy9lXSZKmRV+6uR9r/kqSOqsvK/ZJkjQtJtHNSQ5NcmGSi5K8fp79Dkhya5IFP1Dad0YlSWNxgClJUrcsdTcnWQ28H3gScBlwepLjqur8WfZ7J1sujjcr3xmVJI2lKou6SZKkyZpANx8IXFRVP6yqXwOfAZ41y35/AHwW2KqP93IwKkkayyayqJskSZqsxXZzkiOSrB+6HTHjkDsBlw7dv6x57DZJdgKeAxy1tTmnYpruxutubDvCbY4/7pdtRxixy+73bDvCFn5w/sVtRxixzyfOazvCiIe/dK+2I4z4m2d+tO0II67/5R5tRxjx1t/5XtsRZnjYkh9xEtN0kxwKvAdYDXykqt4xx34HAKcBz6+qY5c8iCZm5wfutPBOy+Taa37VdoQRV955m7YjbOHs07rVzVe96/S2I4w49HUHtB1hxNsPXdd2hBGXPaxb3fyC5+zYdoSJW2w3V9U6YL7/cGY7YM24/3fAn1bVrcnWPf9UDEYlSZOz1FNvJ3VdiiRJ02ICl8VcBtx36P7OwOUz9tkf+EwzEL078LQkt1TV5+c6qINRSdJYJvDO6G3XpQAk2Xxdyvkz9tt8XUq33pKQJKllE+jm04Hdk+wG/AR4AfCikees2m3z90k+Bpww30AUHIxKksa02LOvzXUow9eirGumB20223Upj5hxjM3XpRyMg1FJkkYs9TujVXVLktcwmI20Gji6qs5LcmSzfauvEx3mYFSSNJa+XJciSdK0mMR6DlV1InDijMdmHYRW1WFbc0wHo5KksfTluhRJkqZFXz5KzcGoJGksty594U3kuhRJkqbFBLp5IhyMSpLGstRTgSZ1XYokSdNiEtN0J8HBqCRpLJOYCjSJ61IkSZoWTtOVJE2Fvpx9lSRpWvSlmx2MSpLGsmnmOreSJKlVfenmVW0HWEiSXZOc23x/YJKzmtvZSZ7Tdj5JmnZFFnVT/9nNktRtfenmvr0zei6wf7O4xb2Bs5McX1W3tB1MkqZVX65L0cTYzZLUMX3p5mUbjCa5M/BPDD4vbjXwVmAP4JnAtsCpwCurqpLsBxwNbAS+sfkYVbVx6JBr2PJD0CVJy6z8TdxbdrMkrUx96eblnKZ7KHB5VT20qvYGTgLeV1UHNPe3BZ7R7PtR4LVVddDMgyR5RJLzgA3AkXOdeU1yRJL1SdZ//4xPTuQFSZJgE1nUTZ3SWjd/7zsfn8gLkiT1p5uXczC6ATgkyTuTPLaqrgWekOTbSTYABwN7Jdke2KGqvtr83MhIsqq+XWDhCYwAAB19SURBVFV7AQcAf5ZkzWxPVlXrqmr/qtr/gQ9/yeRelSRNuaos6qZOaa2bH3Tgyyb3qiRpyvWlm5dtmm5Vfb+Z4vM04O1JTgFezeA6k0uTvJnB9J6wFVN8quqCJDcAewPrJ5dckjSfvkwF0pbsZklamfrSzcv2zmiS+wAbq+pTwLuBhzebrk6yFnguQFX9Arg2yWOa7S8eOsZuSe7QfL8Lg+taLlmeVyBJmk1fVuzTluxmSVqZ+tLNy7ma7kOAdyXZBNwMvAp4NoMpQpcApw/tezhwdJKNwMlDjz8GeH2Sm4FNwO9X1dXLkF2SNIe+fJaZZmU3S9IK1JduXs5puiczWl4wmMLzF7Ps+13goUMPvbl5/JPMuE5FktQurwPtL7tZklamvnRz3z5nVJLUMX25LkWSpGnRl252MCpJGosf1yJJUrf0pZsdjEqSxtKXs6+SJE2LvnSzg1FJ0lj6cl2KJEnToi/d7GBUkjSWvqzYJ0nStOhLNzsYlSSNpS9TgSRJmhZ96WYHo5KksbT5YdmSJGlLfenmVF+GzWP48oZfdeZFnn3xmrYjjLj44uvbjrCFZzz+jm1HGHHi129uO8KIM/7jnLYjjPiT4w9vO8KIE9/+7bYjjFh1h1VtRxjx93+43ZK30z+ftrjJQP/tkav60ZCaqG+cf0Nnuvk9H76q7Qidd/BTdms7wojLLr+p7Qgjvvovp7UdYcSfnXRE2xFGHP+2bv35XHFJt/6f/9cP7jG13ew7o5KksUzBOU1JknqlL93sYFSSNJZNPVmxT5KkadGXbnYwKkkaS1/OvkqSNC360s0ORiVJY+lL4UmSNC360s0ORiVJY+nLZ5lJkjQt+tLNDkYlSWOpnlyXIknStOhLNzsYlSSNpS9TgSRJmhZ96WYHo5KksfRlKpAkSdOiL93sYFSSNJa+nH2VJGla9KWbHYxKksbSl8KTJGla9KWbV823MckOSX5/ucIsJMlrklyUpJLcve08kqTBVKDF3DQeu1mStJC+dPO8g1FgB2CLwkuyejJxFvRN4BDgRy09vyRphqrF3TQ2u1mSNK++dPNC03TfAdw/yVnAzcD1wBXAvsCeST4P3BdYA7ynqtYBJLm+qtY23z8XeEZVHZbkY8CvgAcBuwCHAy8DDgK+XVWHNT/zQeAAYFvg2Kp6E0BVndlsX5IXL0ka36ZNbSeYOnazJGlefenmhd4ZfT3wg6raF3gdcCDwhqras9n+8qraD9gfeG2SHbfiOe8KHAz8EXA88L+BvYCHJNm32ecNVbU/sA/wuCT7LOZFASQ5Isn6JOtPOPYfFvvjkqSt1JezryvIiujm4/7p6MX+uCRpK02im5McmuTC5tKM18+y/cVJzmlupyZ56ELHXOwCRt+pqouH7r82yXOa7+8L7A78bIFjHF9VlWQDcGVVbWjCnwfsCpwFPC/JEU2+ewN7AucsJmhzJngdwJc3/Mp//kjShDjAbF0vu/kb59/gfzmSNCFL3c3NpSDvB54EXAacnuS4qjp/aLeLgcdV1TVJnsrg9/0j5jvuYgejNwwFejyDa0QOqqqNSb7CYEoQwPDLX8Oom5qvm4a+33z/Dkl2A/4YOKB5IR+b5RiSpI5wUaLW2c2SpBET6OYDgYuq6ocAST4DPAu4bTBaVacO7X8asPNCB11omu51wF3m2LY9cE1Tdg8CHjm07cokD06yCnjO7D8+p+0YFOu1Se4FPHWRPy9JWkZVtaibxmY3S5LmtdhuHr6MorkdMeOQOwGXDt2/rHlsLr8H/NtCOed9Z7Sqfpbkm0nOZbC4wZVDm08CjkxyDnAhg9HvZq8HTmgCnwusXSjI0HOeneRM4DzghwxW6QMgyWuBPwF+EzgnyYlV9YqtPbYkaek5vlxedrMkaSGL7ebhyyjmMNsqdbM+S5InMBiMPmah511wmm5VvWiOx29ijjOjVXUscOwsjx829P0lwN5zbDuMWVTVe4H3LpRZkrR8JrFiX5JDgfcAq4GPVNU7Zmx/MfCnzd3rgVdV1dlLn6Sb7GZJ0nwm0M2XMViHYLOdgctn7tQsbvcR4KlVtdB6BYu+ZlSSpBF9WSRBkqRpMYFZS6cDuzdrCPwEeAEwcmI0yf2AzwEvqarvb81BHYxKksbSl0USJEmaFkvdzVV1S5LXACczmLV0dFWdl+TIZvtRwF8COwIfaD57+pbmI8Hm5GBUkjSWTbcurvGSVUcAwwsjrGuuVdlstkUS5nvXc6sWSZAkaVostptnvyR0VFWdCJw447Gjhr5/BbCoNQMcjEqSxrLYs69tLZIgSdK06MvHrjkYlSSNZQLXpUxkkQRJkqZFX1a6dzAqSRrLpqU//TqRRRIkSZoWE+jmiXAwKkkay1KffZ3UIgmSJE0L3xntkG+cu03bEW7z8v3ObTvCiC9t/5C2I2zhmo0T+NDCMfz247qV5/pf7tF2hBEnPurbbUcY8bQ/69ane/z8Sxe2HWHiJlF4k1gkQd1y1iV3ajvCbZ757N3ajjDi5JN+0naELWy8sVv/sr3/rr/RdoQRlz2sW918/GNOazvCiGf+xSPbjjDipHed3naEiXMwKkmaCpv60niSJE2JvnSzg1FJ0liqW5MHJEmaen3pZgejkqSxVE/OvkqSNC360s0ORiVJY9nUk7OvkiRNi750s4NRSdJY+nL2VZKkadGXbnYwKkkaS08+ykySpKnRl252MCpJGkv1pfEkSZoSfelmB6OSpLH0ZCaQJElToy/d7GBUkjSWTT05+ypJ0rToSzc7GJUkjaUviyRIkjQt+tLNq+bbmGSHJL+/XGEWkuSYJBcmOTfJ0Um2aTuTJE272rS4m8ZjN0uSFtKXbp53MArsAGxReElWTybOgo4BHgQ8BNgWeEVLOSRJjU1Vi7ppbHazJGlefenmhabpvgO4f5KzgJuB64ErgH2BPZN8HrgvsAZ4T1WtA0hyfVWtbb5/LvCMqjosyceAXzEorV2Aw4GXAQcB366qw5qf+SBwAINSO7aq3gRQVSduDpbkO8DO4/4BSJLG05epQCuI3SxJmldfunmhd0ZfD/ygqvYFXgccCLyhqvZstr+8qvYD9gdem2THrXjOuwIHA38EHA/8b2Av4CFJ9m32eUNV7Q/sAzwuyT7DB2imAL0EOGmuJ0lyRJL1Sdav/9KHtyKWJOn22LSpFnXT2FZEN3/z39Zt5cuVJC1WX7p5ocHoTN+pqouH7r82ydnAaQzOwu6+Fcc4vgZD9Q3AlVW1oao2AecBuzb7PC/JGcCZDMpwzxnH+ADwtar6+lxPUlXrqmr/qtp//yf+9615bZKk26FqcTctuV5286OfesTWvDZJ0u3Ql25e7Gq6N2z+JsnjgUOAg6pqY5KvMJgSBDD8ktYw6qbm66ah7zffv0OS3YA/Bg6oqmua6UO3HSPJm4B7AK9cZHZJ0gTcequrErXMbpYkjehLNy/0zuh1wF3m2LY9cE1Tdg8CHjm07cokD06yCnjOIjNtx6BYr01yL+CpmzckeQXwFOCFzRlbSVLLalMt6qax2c2SpHn1pZvnfWe0qn6W5JtJzmWwuMGVQ5tPAo5Mcg5wIYPpQJu9HjgBuBQ4F1i7tYGq6uwkZzKYGvRD4JtDm48CfgR8KwnA56rqLVt7bEnS0nOAubzsZknSQvrSzQtO062qF83x+E0MnRmdse1Y4NhZHj9s6PtLgL3n2HYYs6iqxU4rliRNWE/6bkWxmyVJ8+lLN1sgkqSx9OXsqyRJ06Iv3exgVJI0lr58lpkkSdOiL93sYFSSNBY/O1SSpG7pSzc7GJUkjaUvZ18lSZoWfelmB6OSpLH05boUSZKmRV+62cGoJGksfSk8SZKmRV+62cGoJGksm3oyFUiSpGnRl26eisHoyZ/+5sI7LZOX73c3PnHWnm3HuM1O94IH3PO6tmOMuOwXd2b92Te1HeM2T300nPGDNW3HGLKRt/7Oj9sOcZu3nrAbq+6wqu0YI37+pQvbjjDibk/co+0I/8/NS/9n05ezr+qWC7/fne454GHbcfGlN7cdY8SbXnFr2xFGHL8B1p96adsxbvOkQ+/HN75+VdsxRrzgOTu2HeE2/3rK9VxxSbf+fE561+ltRxhx6OsOaDvC//OH09vNUzEY7ZIuDUShewNRoFMDUejaQJRODUQBB6IL6NRAdEL6skiCNBcHogvr0kAUcCC6AAei8+vUQHRC+tLNDkYlSWPpy/LxkiRNi750s4NRSdJY+jIVSJKkadGXbnYwKkkaS1+mAkmSNC360s3duthLktQ7tWnTom6SJGmyJtHNSQ5NcmGSi5K8fpbtSfLeZvs5SR6+0DF9Z1SSNJa+XJciSdK0WOpuTrIaeD/wJOAy4PQkx1XV+UO7PRXYvbk9Avhg83VODkYlSWPpy1QgSZKmxQS6+UDgoqr6IUCSzwDPAoYHo88CPlGDJz8tyQ5J7l1VV8x1UKfpSpLGUptqUTdJkjRZi+3mJEckWT90O2LGIXcChj/j6bLmscXuM8J3RiVJY3GAKUlStyy2m6tqHbBunl0y24/djn1GOBiVJI1lU7kokSRJXTKBbr4MuO/Q/Z2By2/HPiPmnabbzPP9/UWEnKgk/5Dk7GZ1pmOTrG07kyRNu023bFrUbWtMYsW+lcJuliQtZALdfDqwe5LdktwReAFw3Ix9jgNe2nT0I4Fr57teFBa+ZnQHYIvCa1ZTasMfVdVDq2of4MfAa1rKIUlqVNWibgsZWrHvqcCewAuT7Dljt+EV+45gsGLftLCbJUnzWupurqpbGPx+Pxm4APinqjovyZFJjmx2OxH4IXAR8GFm6aqZFpqm+w7g/knOAm4GrgeuAPYF9kzyeQZvxa4B3tPMNSbJ9VW1tvn+ucAzquqwJB8DfgU8CNgFOBx4GXAQ8O2qOqz5mQ8CBwDbAsdW1ZuaP4RfNtvTbPNCJUlq2aal/+zQiazYt4LYzZKkeU2gm6mqExkMOIcfO2ro+wJevZhjLjQYfT2wd1Xtm+TxwBea+xc3219eVT9Psi2Dz5r5bFX9bIFj3hU4GPht4Hjg0cArmp/ft6rOAt7QHHc18KUk+1TVOQBJPgo8jcE/Sv7HYl6sJGnpTWABo9lW45v5OWVzrdg3DYNRu1mSNK++LC642I92+c5Q2QG8NsnZwGkMzsLuvhXHOL4ZNW8ArqyqDVW1CTgP2LXZ53lJzgDOBPZiME0LgKo6HLgPg7eHnz/XkwwvT/zTHx2/1S9QkrQ4VZsWdduK5eMnsmLfCtbLbj731I9u9QuUJC3OYru5LYsdjN6w+ZvmbOwhwEFV9VAG5bSm2Tz8D4I1jLqp+bpp6PvN9++QZDfgj4EnNteffGHmMarqVuD/AP91rqBVta6q9q+q/X9zl2du3auTJC3aYj/LbPj3c3ObuZT8RFbsW8F62c17P+rwrXt1kqRF68tngC80GL0OuMsc27YHrqmqjUkeBDxyaNuVSR6cZBXwnEVm2o5BsV6b5F4MFqnYvHLiAzZ/DzwT+N4ijy1JWmITKLyJrNi3gtjNkqR59WUwOu81o1X1syTfTHIug8UNrhzafBJwZJJzgAsZTAfa7PXACQyu5zkX2Opl3qvq7CRnMpga9EPgm82mAB9Psl3z/dnAq7b2uJKkyVjqzzKrqluSbF6xbzVw9OYV+5rtRzFYQOFpDFbs28hg0Z2pYDdLkhbSl88AX2gBI6rqRXM8fhPNmdFZth0LHDvL44cNfX8JsPcc2w5jdo9eKK8kaXlN4ozqJFbsW0nsZknSfPqygNGCg1FJkuZTE1g+XpIk3X596WYHo5KksfTl7KskSdOiL93sYFSSNJY2l4SXJElb6ks3OxiVJI1lU0/OvkqSNC360s0ORiVJY+nLdSmSJE2LvnSzg1FJ0lj6cl2KJEnToi/d7GBUkjSWvlyXIknStOhLNzsYlSSNpS9nXyVJmhZ96eYMPjdcWyPJEVW1ru0cm5lnfuaZn3nmZx6pH7r2/4Z55mee+ZlnfuZZeVa1HaBnjmg7wAzmmZ955mee+ZlH6oeu/b9hnvmZZ37mmZ95VhgHo5IkSZKkZedgVJIkSZK07ByMLk7X5oSbZ37mmZ955mceqR+69v+GeeZnnvmZZ37mWWFcwEiSJEmStOx8Z1SSJEmStOwcjEqSJEmSlp2DUUmSJEnSsnMwKkmSJEladg5Gb4ckT2rpebdLcv9ZHt+npTy/meQ3m+/vkeR3kuzVRpb5JHlQi8+9zSyP3b2lLKuSrGq+v2OShye5WxtZ5pNk2VemS7I6ySuTvDXJo2ds+4sW8twpyZ8keV2SNUkOS3Jckr9Jsna580h9YDff9rx288LPbTcvQhu93Dyv3TwFHIzePv+w3E+Y5HnA94DPJjkvyQFDmz/WQp5XAt8CTkvyKuAE4BnA55L83nLnWcApy/2ESZ6Q5DLg8iSnJNm15TzPBq4AfpLkWcDXgXcD5yR5Zgt57jbHbUfgacudB/gQ8DjgZ8B7k/yvoW2/00KejwH3AnYDvgDsz+DvK8AHW8gj9YHdbDfPy26eN0vXehns5qlwh7YDdFWS4+baBOy4nFkafw7sV1VXJDkQ+GSSP6+qzzWZlttrgL2AbYEfAQ+oqp8muSvwZZb5HwVJ3jvXJmCH5czS+BvgKVV1XpLnAl9M8pKqOo12/r7eBDyUwd/X2cABVXVhkl2AzwLHL3Oe/8vgv5vhP4tq7t9zmbMAHFhV+wAkeR/wgSSfA15IO39fD6yq5yUJg3+oHFJVleTrDP7+pKlkNy/Ibp6f3Ty3rvUy2M1TwcHo3B4L/C5w/YzHAxy4/HFYXVVXAFTVd5I8ATghyc4Mflkst5uraiOwMckPquqnTbZrkrSR53DgfwA3zbLthcucBeCOVXUeQFUdm+QCBmemX087f19s/jtK8uOqurB57Eebpwctsx8CT6yqH8/ckOTSFvLccfM3VXULcESSvwT+A2ht6k1TcidW84HQzX0/HFrTzG6en908P7t5bl3rZbCbp4KD0bmdBmysqq/O3JDkwhbyXJfk/lX1A4DmLOzjgc8zOAu63DYl2aaqbgaevvnBJGtoZ/r36cC5VXXqzA1J3rz8cbg5yW8O/UPgvCRPZDBlaotri5ZDklVVtQl4+dBjqxn6Zb+M/g64K7BF6TE4c73c1ic5tKpO2vxAVb0lyeW0M/VmfZK1VXV9VQ3/fd0fuK6FPFJX2M3zs5vnZzfPrWu9DHbzVEgzqFfHJXkocENVXTTj8W2A51XVMcuc537A5c2ZquHHdwIeXFX/vsx57gbc2JwRbl2SQ4D/W1Vnz3h8B+DVVfU/lznPAcCGqrpxxuO7Ao+pqk8tZx7dfklS/uKWOsFuXjCP3Tx/Hrt5hbCbbz8HowtIsmdVnT/jscdX1VfM07086p8kewN7Ams2P1ZVnzBPN/NIXdC17jGPVpIu9k7XMnUtT585GF1AknOBTzKYorCm+bp/VR1knu7kSbKBea732HwB/HIxz9ZJ8ibg8Qx+oZ8IPBX4RlU91zzdyyN1RVe6xzwL5uhU95hnYV3sna5l6lqevvOa0YU9AngncCpwF+AY4NHz/oR52sjzjObrq5uvn2y+vhhoY3qQebbOcxmsJHhmVR2e5F7AR8zT2TxSV3Sle8wzv651j3kW1sXe6VqmruXpNQejC7sZ+BWDZbfXABc3F5qbp0N5qupHAEkeXVXDhfv6JN8E3mKe7uQZ8quq2pTkliTbAVcB/6WlLOaR+qMT3WOe+XWte8yzVbrYO13L1LU8vdbGymp9czqDX+gHAI8BXpjkWPN0Ns+dkzxm850kjwLubJ7O5lnfLBzxYeC7wBnAd8zT2TxSV3Ste8wzv651j3nm1sXe6VqmruXpNa8ZXUCS/atq/YzHXlJVn5zrZ8zTap79gKOB7ZuHfgG8vKrOME/38gxrVg/crqrOaTkKYB6pyzrYPeaZP0+nusc8W6eLvdO1TF3L00cORrdSknsyumLWbJ/DtGzMM79m2kSq6to2c2xmnnmz7APsytBlA1X1OfN0M4/UJR3sHvPMo0vdA+aZJ0fneqdrmbqWp8+8ZnQBSZ4J/C/gPgzmhO8CXEA7H2Ztnq3L9PTm+dckAQYfkmye7uVJcjSwD3AesPl6pgJa+YVuHqkfutY95tmqTJ3pHvPMm6NzvdO1TF3L03cORhf2NuCRwL9X1cOSPAF4oXm6mSfJUcCdgCcwWNnsubQ4j988C3pkVe3Z4vPPZB6pHzrVPeaZX9e6xzzz6mLvdC1T1/L0mgsYLezmqvoZsCrJqqr6MrCveTqb51FV9VLgmqr6K+Ag4L7m6WyebyXp0i9080j90LXuMc/8utY95plbF3una5m6lqfXfGd0Yb9Ishb4GnBMkquAW8zT2Tw3Nl83JrkP8HNgN/N0Ns/HGfxS/ylwExCg2vigb/NIvdK17jHP/LrWPeaZWxd7p2uZupan1xyMLuxZDH5J/BGDDyHenvY+k9E8Czu+WW77XQyW2i4GS2+bp5t5jgZeAmzg/1130SbzSP3Qte4xz/y61j3mmVsXe6drmbqWp9ccjC6gqm4Yuvvx1oI0zLOg7wG3VtVnmykUDwc+b57O5vlxVR3X4vPPZB6pB7rWPeZZUNe6xzxz62LvdC1T1/L0mh/tMock1zE4M3XbQ839zW/Fb2ee7uQZynVOVe2TwYdH/zXwt8CfV9UjzNPJPB8AdgCOZzDVBWhveXTzSN3Wte4xz1bn6lr3mGfuLJ3rna5l6lqevvOd0TlU1V3azjDMPFvt1ubr04Gjqupfk7zZPJ3Nsy2DX+RPHnqszeXRzSN1WNe6xzxbrWvdY565dbF3upapa3l6zXdGt0Jzpmr3qvpokrsDd6mqi83TvTxJTgB+AhwC7Af8CvhOVT3UPN3LI0m3V5e6xzwLZulU95hH6g4HowtI8iZgf2CPqnpgs8rZP1fVo83TyTx3Ag4FNlTVfya5N/CQqjrFPJ3M81FGp5QBUFUvbyGOeaSe6GD3mGf+PF3rHvPMnaVzvdO1TF3L03dO013Yc4CHMVjdjKq6PEmb02DMM4+q2sjQNImqugK4wjzdzAOcMPT9Ggb/PV3eUhYwj9QXneoe88yva91jnnl1sXe6lqlreXrNwejCfl1VlaQAktzZPJ3Oox6pqs8O30/yj8C/txTHPFJ/dK17zKMVoYu907VMXcvTd6vaDtBlSQKckORDwA5J/juD/9ha+ewn82gK7A7cr+0QQ8wjdUzXusc8WuG62Dtdy9S1PL3iO6PzaM4qPhv4U+CXwB7AX1bVF83TvTzqn6GPIdj88QM/ZfDfk3k6mEfqgq51j3m0knSxd7qWqWt5+s7B6MK+Bfyiql7XdpCGebRidO1jCMwj9UbXusc8WhG62Dtdy9S1PH3naroLSHI+8EDgR8ANmx+vqn3M07086p8kd2UwxWXN5seq6mvm6WYeqQu61j3m0UrSxd7pWqau5ekzB6MLSLLLbI9X1Y+WOwuYRytLklcA/x+wM3AW8EjgW1V1sHm6l0fqiq51j3m0UnSxd7qWqWt5+s7BqKTWJNkAHACcVlX7JnkQ8FdV9XzzdC+PJGll62LvdC1T1/L0navpSmrTjVV1I0CS36iq7zFYbMM83cwjSVrZutg7XcvUtTy95gJGktp0WZIdgM8DX0xyDe1+cLR5JEnTrIu907VMXcvTa07TldQJSR4HbA+cVFW/Nk+380iSVrYu9k7XMnUtTx85GJXUiiSrgHOqau+2s4B5JEnTrYu907VMXcuzEnjNqKRWVNUm4Owk92s7C5hHkjTdutg7XcvUtTwrgdeMSmrTvYHzknyH0c/C+23zdDKPJGll62LvdC1T1/L0moNRSW1aCzxj6H6Ad7aUBcwjSZpuXeydrmXqWp5eczAqqU13qKqvDj+QZNu2wmAeSdJ062LvdC1T1/L0moNRScsuyauA3wf+S5JzhjbdBfimebqVR5K0snWxd7qWqWt5VgpX05W07JJsD9wVeDvw+qFN11XVz83TrTySpJWti73TtUxdy7NSOBiVJEmSJC07P9pFkiRJkrTsHIxKkiRJkpadg1FJkiRJ0rJzMCpJkiRJWnYORiVJkiRJy+7/B7xkuP8Z+RBxAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot mean matrices\n", + "fig, ax_list = plt.subplots(1, 2, figsize=(16,4.5))\n", + "ax = ax_list[0]\n", + "ax.title.set_text('Ketamine')\n", + "sns.heatmap(np.mean(np.asarray(ketArrSes1), axis=0), cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax)#,\n", + " #vmin = -1, vmax=1)\n", + "ax = ax_list[1]\n", + "ax.title.set_text('Midazolam')\n", + "sns.heatmap(np.mean(np.asarray(midArrSes1), axis=0), cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax)#,\n", + " #vmin = -1, vmax=1)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 299, + "metadata": {}, + "outputs": [], + "source": [ + "# saving to mat\n", + "from scipy.io import savemat\n", + "mdict = {'ketamine': np.mean(np.asarray(ketArrSes2), axis=0), 'midazolam': np.mean(np.asarray(midArrSes2), axis=0)}\n", + "savemat('averagedMat_session2.mat', mdict)" + ] + }, + { + "cell_type": "code", + "execution_count": 531, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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9KWZmZrUiLbU5HSnNzKxileKzzCTNlPSspNWSLsuxXJL+LVn+pKRjspb9vaSVkp6SdIukXnvqq5mZWW9Iy+eMuhk1M7OC1NUrr6krycNxbiDz0JwjgLMlHdFhtVPIfD7mGGA28N1k24PIfP7lhOSBPfXAWcV6r2ZmZmlQ7NoMmfos6XFJt+dYtsdB4s74Ml0zMytICUZUjwdWR8TzAJIWAacDv8ta53TgR5F5JPwySQdIGpYs6wPsLWk7sA/QVOyAZmZmlaxEZzsvBp4G9suxLHuQeCKZQeKJOdZ7B58ZNTOzgqiuLr9Jmi2pMWua3WGXBwHrs+Y3JK91uU5E/B74BrAO2Ai8GhH/W9x3bGZmVtnyrc1d7k86GPgT4D/2sMquQeKIWAZkDxLvkc+MmplZQfIdfY2IhcDCznaZa7PurCNpIJmCeAjwCvD/JJ0bETfnFdLMzCzF8q3NycBw9uDwwqRe7/Qt4B+Bffewiz0NJG/s7LhuRs3MrCAluBRoAzAia/5g3n2p7Z7WmQa8EBGbAST9DPhjwM2omZnVjGIOFEs6FdgUEY9KOmFPh8y1266O68t0zcysICV4Yt9yYIykQyTtReYBRLd1WOc24FPJAxMmkbkcdyOZy3MnSdpHkoCTydzfYmZmVjOKXJs/DPyppBeBRcBJkjoO8nZnIPldfGbUzMwKUuzPMouIHZIuBO4m8zTcGyNipaTzk+XzgTuBjwGrga3AZ5JlD0u6FXgM2AE8TueXBJuZmVWdYtbmiLgcuBwgOTN6aUSc22G124ALk4cOTmT3IHGn3IyamVlBuvtI+HxExJ1kGs7s1+ZnfR3ABXvY9p+Afyp6KDMzs5QoRW3uqDuDxF1xM2pmZgXpzQ/LNjMzs3crVW2OiPuB+5OvuzVI3Bk3o2ZmVpBiX6ZrZmZmhUlLbXYzamZmBfGZUTMzs8qSltrsZtTMzApS16e+tyOYmZlZlrTUZjejZmZWkLSMvpqZmdWKtNRmN6NmZlaQtNyXYmZmVivSUpvdjHZDY2Mj8xcsoL29nZkzZjBr1iznqeA8lZjJeZynmvK8i9Ix+mrVZeIxA7n4c4dRVyduv2cjN9+63nmcJ9WZnMd5iioltblXWmZJW3q43XhJD0laKelJSZ8odraO2trauGHePK6+6ioWzJ/P/UuWsHbdulIf1nmqKJPzOE815clFdcprssqUptpcVweXnD+GS69YwbkXLGfalKGMGrFPqQ/rPFWSpxIzOY/zFFtaanPJmlFlFHv/W4FPRcSRwEzgW5IOKPIx3mHVqlUMHz6cYcOG0bdvX6ZOmcKyhx4q5SGdp8oyOY/zVFOeXFRXl9dkvadaavPhY/Zjw8Y3aXrpLXbsCO5duonJEweX8pDOU0V5KjGT8zhPsaWlNhf1yJJGSXpa0jzgMeDLkpYnI6VX5lh/gKT7JD0maYWk05PXj0u26S/pPclo67iIWBURzwFERBOwCRhSzPfQUUtrK0MaGnbNNzQ00NraWspDOk+BKi2T8zhPNeXJJS2jr7WqGmvzkMF7sall2675za3bGDK4XykP6TxVlAcqL5PzOE+xpaU2l6INfj/wI+ALwEHA8cB44FhJUzqs+xbw8Yg4BjgR+KYkRcRy4Dbgq8C/ADdHxFPZG0o6HtgLWJMrhKTZkholNd6yaFHP301Erp33fH+Fcp6uVVom5+mc83Su0vLkkJbR1xpXcbW5ee3iHr+ZXD8CuX5UysV5OldpeaDyMjlP55wnf2mpzaV4gNHaiFgm6RvAdODx5PUBwBhgada6Av45KYTtZArkgUAzcBWwnExRvCj7AJKGAT8GPh0R7blCRMRCYCHA82vW9PifR0NDA5tbWnbNt7S0MHjQoJ7urmDO07VKy+Q8zlNNeXLx2c5UqLjaPPm0JT2uzZta3mZow+6zEEMG96Pl5W2dbFFazpOuPFB5mZzHeYotLbW5FG3wG8mfAq6JiPHJdFhEfL/DuueQuZTn2IgYD7wE9E+WDSJTJPfNeg1J+wF3AHMjYlkJ8r/D2LFjaWpqorm5me3bt7Nk6VImTZpU6sM6TxVlch7nqaY8uaTlUqAaV1W1+ZnnXmPE8L0ZdmB/+vQR06YM5cFHeu/ydedJV55KzOQ8zlNsaanNpfxol7uBqyX9JCK2SDoI2B4Rm7LW2R/YFBHbJZ0IjMxathD4MnAIcC1woaS9gJ8DP4qI/1fC7LvU19czZ84c5s6dS1t7O9OnT2fkyJFdb+g8zuQ8zlOFeXLypbdpUhW1ua0drp+/muuvPIq6OnHHvc28sG5rOQ7tPFWQpxIzOY/zFF1KarOiiBc4SxoF3B4R45L5i4HPJou3AOdGxBpJWyJigKQGYDHQF3gC+DBwCjAFOCMi/kxSPfAb4HJgOPADYGXWYc+LiCc6y1XIZbpmZtXk0NGjiz78uXnuZ/L6P3bIV3/g06NlVKm1uZDLdM3MqskDi6fWbG0u6pnRiHgRGJc1/23g2znWG5D82QJ8KMeuXiTzoAUiog2YmLXs5qIFNjOzgvmhRJXNtdnMrPakpTaX8jJdMzOrAb4P1MzMrLKkpTa7GTUzs8KkZPTVzMysZqSkNrsZNTOzgqRl9NXMzKxWpKU2uxk1M7OCSOkYfTUzM6sVaanNbkbNzKwwKRl9NTMzqxkpqc1uRs3MrCBpeWKfmZlZrUhLbXYzamZmBUnLfSlmZma1Ii212c2omZkVJiX3pZiZmdWMlNRmN6NmZlaQtIy+mpmZ1Yq01GY3o2ZmVhDV1/d2BDMzM8uSltrsZtTMzAqTkockmJmZ1YyU1GY3o2ZmVpC0XApkZmZWK9JSm92MmplZYVLykAQzM7OakZLa7GbUzMwKk5LRVzMzs5qRktrsZtTMzAqilIy+mpmZ1Yq01GY3o2ZmVpiUjL6amZnVjJTUZjejZmZWEKXkiX1mZma1Ii212c1oNzQ2NjJ/wQLa29uZOWMGs2bNcp4KzlOJmZzHeaopz7soHaOvVl0mHjOQiz93GHV14vZ7NnLzreudx3lSncl5nKeoUlKbe6VllrSlh9uNlPSopCckrZR0frGzddTW1sYN8+Zx9VVXsWD+fO5fsoS169aV+rDOU0WZnMd5qilPTnV1+U1WkdJUm+vq4JLzx3DpFSs494LlTJsylFEj9in1YZ2nSvJUYibncZ6iS0ltLtmRlVHs/W8E/jgixgMTgcskDS/yMd5h1apVDB8+nGHDhtG3b1+mTpnCsoceKuUhnafKMjmP81RTnpyk/CbrNdVSmw8fsx8bNr5J00tvsWNHcO/STUyeOLiUh3SeKspTiZmcx3mKrsi1WVJ/SY9I+m0y8HhljnXOkfRkMv1G0ge72m9RC5KkUZKeljQPeAz4sqTlSaBcgQdIuk/SY5JWSDo9ef24ZJv+kt6TvOFxEfF2RGxLNu9X7Py5tLS2MqShYdd8Q0MDra2tpT6s8xSg0jI5j/NUU55cVFeX12TlVY21ecjgvdjUsm3X/ObWbQwZ3K/Uh3WeKskDlZfJeZyn2EpQm7cBJ0XEB4HxwExJkzqs8wIwNSKOBq4GFna101LcM/p+4DPAL4AzgeMBAbdJmhIRS7PWfQv4eES8JqkBWCbptohYLuk24KvA3sDNEfEUgKQRwB3AYcDnI6KpBO9ht4h3v9abI/vO07VKy+Q8nXOezlVanlxS8vj4GldVtTnXj0CuH5VycZ7OVVoeqLxMztM55+mBItfmiAhg5+0cfZMpOqzzm6zZZcDBXe23FL9BrI2IZcD0ZHqczEjsB4AxHdYV8M+SngTuBQ4CDkyWXQV8FJgA/MvODSJifdJtHwZ8WtKB5CBptqRGSY23LFrU4zfT0NDA5paWXfMtLS0MHjSox/srlPN0rdIyOY/zVFOenOqU32S9oeJqc/PaxT1+M5ta3mZow+6zEEMG96Pl5W2dbFFazpOuPFB5mZzHeYquBLVZUr2kJ4BNwD0R8XAnq/818D9dxuzWkfPzRvKngGsiYnwyHRYR3++w7jnAEODY5F6Tl4D+ybJBwABg36zXdklGXVcCH8kVIiIWRsSEiJhw9lln9fjNjB07lqamJpqbm9m+fTtLli5l0qSOZ6TLx3nSl8l5nKea8uQi1eU1Wa+ouNr83pGn9fjNPPPca4wYvjfDDuxPnz5i2pShPPhI712+7jzpylOJmZzHeYot39qcPViYTLM77jMi2pK6cDBwvKRxuY+tE8k0o1/oKmcpP9rlbuBqST+JiC2SDgK2R8SmrHX2BzZFxPYk9MisZQuBLwOHANcCF0o6GGiNiDclDQQ+DFxfwvdAfX09c+bMYe7cubS1tzN9+nRGjhzZ9YbO40zO4zxVmCenEpztlDQT+DZQD/xHRHy9w3Ilyz8GbAXOi4jHspbXA43A7yPi1KIHTK+qqM1t7XD9/NVcf+VR1NWJO+5t5oV1W0t5SOepojyVmMl5nKfo8qzNEbGQbtzjmaz7iqT7gZnAU9nLJB0N/AdwSkR02aEriniBs6RRwO0RMS6Zvxj4bLJ4C3BuRKyRtCUiBiT3oiwmc83xE2QK2CnAFOCMiPiz5BeK3wCXk/ml5Jtkrk8W8J3kG9ep59esqbSruM3MesWho0cXvXN866ffyOv/2P6zLu00Q/L//ioyl4NuAJYDZ0fE77LW+Rjwd2Sa0YnAtyNiYtbyS8hcSrpfrTejlVqbJ5+2xLXZzAx4YPHUNNTmIWQGL1+RtDfwv8C1EXF71jrvA34JfKrD/aN7VNQzoxHxIjAua/7bZEauO643IPmzBfhQjl29CPwoWaeNzC8aOx1dtMBmZla44j9Q6XhgdUQ8n9m9FgGnA7/LWud04EfJAxWWSTpA0rCI2JicqfsT4GvAJcUOlzauzWZmNaj4tXkY8MNkMLIO+GlE3L7zs6UjYj7wFWAwMC9zARM7ImJCZzst5WW6ZmZWC/L8uJbkPpTse1EWdjiTdhCwPmt+A+9sfPa0zkFkPvPyW8A/krmv0czMrPYU+aPUIuJJ4I9yvD4/6+vPsvvKm25xM2pmZoXJ86FE3bgvJddwbsfLjXKuI+lUMvc7PirphLyCmZmZVYuUPDDQzaiZmRWm+A8w2gCMyJo/GOj4uZV7WudM4E+Te0r7A/tJujkizi12SDMzs4qVko9SS0fLbGZmlauuPr+pa8uBMZIOkbQXcBZwW4d1bgM+pYxJwKsRsTEiLo+IgyNiVLLdL92ImplZzSl+bS4Jnxk1M7PCFP++lB2SLiTzMST1wI0RsbLDQxLuJPMk3dVkPtrlM0UNYWZmlmZFrs2l4mbUzMwKU/wn9hERd5JpOLNfy35IQgAXdLGP+4H7ix7OzMys0pWgNpeCm1EzMytMSh6SYGZmVjNSUpvdjJqZWWFScimQmZlZzUhJbXYzamZmhUnJpUBmZqVy+V2zu16pjK6Z2dmnZ1lNSEltdjNqZmaFScmlQGZmZjUjJbXZzaiZmRUmJaOvZmZmNSMltdnNqJmZFSYl96WYmZnVjJTUZjejZmZWkEjJ6KuZmVmtSEttdjNqZmaFScl9KWZmZjUjJbXZzaiZmRUmJQXPzMysZqSkNrsZNTOzgqTlUiAzM7NakZba7GbUzMwKk5LRVzMzs5qRktrsZrQbGhsbmb9gAe3t7cycMYNZs2Y5TwXnqcRMzuM81ZTnXVIy+mrVZeIxA7n4c4dRVyduv2cjN9+63nmcJ12Z6uqY/PB/8dbvX6LxjPPfsWjQlOOZ8LN5bH1xAwDNP7+H1V+7oazxev374zyFSUltrviWWdIoSU8lXw+W9CtJWyR9pxzHb2tr44Z587j6qqtYMH8+9y9Zwtp168pxaOepkkzO4zzVlCenurr8Jku93q7NdXVwyfljuPSKFZx7wXKmTRnKqBH7lOPQzlMFeSol0yEXfYotT6/Z4/KXH2jkgQln8MCEM8reiFbC98d5CpSS2py23wreAr4MXFquA65atYrhw4czbNgw+vbty9QpU1j20EPlOrzzVEEm53GeasqTS0h5TVZ1yl6bDx+zHxs2vknTS2+xY0dw79JNTJ44uFyHd56U56mETP0POpChp5zA+htvLdsx89Hb3x/nKVxaanPZmlFJ75F0h6TfSnpK0ickfUXS8mR+oZT5Tkg6NlnvIeCCnfuIiCWtO2cAACAASURBVDci4gEyha8sWlpbGdLQsGu+oaGB1tbWch3eeXqg0jI5j/NUU56cVJffZBUjrbV5yOC92NSybdf85tZtDBncr1yHd56U54Hez3TEN7/I05dfR7S373GdgZPG85FH/5vjFn+PAUccVrZs0PvfH+cpgpTU5nIeeSbQFBEfjIhxwF3AdyLiuGR+b+DUZN0fABdFxIfKmC+3iHe/1psj+87TtUrL5Dydc57OVVqeHEJ1eU1WUVJZm3P9COT6USkX5+lcpeWB3s009GMn8Pbml3ntsZV7XOe1x1fyy9En8etjT+fFG37MhFvLe5lupf2dOU/+0lKby3nkFcA0SddK+khEvAqcKOlhSSuAk4AjJe0PHBARS5LtftyTg0maLalRUuMtixb1OHRDQwObW1p2zbe0tDB40KAe769QztO1SsvkPM5TTXlykvKbrJL0Wm1uXru4x6E3tbzN0IbdZyGGDO5Hy8vbOtmitJwnXXmgdzMN/ONjGHrqSZz43H380U+up+HESYz/4XXvWGfH62/Q9sZWADbftRT17UPfwQPLkg8q7+/MeXogJbW5bM1oRKwCjiVT+K6R9BVgHnBmRBwFfA/oDwgoeGwhIhZGxISImHD2WWf1eD9jx46lqamJ5uZmtm/fzpKlS5k0aVKh8ZynhjI5j/NUU55c0jL6au/Wm7X5vSNP6/F+nnnuNUYM35thB/anTx8xbcpQHnyk9y5fd5505entTM/OvZ5fHjKVX405mcfPuYSWXy3jiU9//h3r9Dtw9+0Z+x93FKqrY3vrH8qSDyrv78x58peW2ly2j3aRNBx4OSJulrQFOC9Z1CJpAHAmcGtEvCLpVUmTk3tQzilXxlzq6+uZM2cOc+fOpa29nenTpzNy5EjnqdA8lZjJeZynmvLk5LOdqZXW2tzWDtfPX831Vx5FXZ24495mXli31XmcJ9WZ3jc7c/Jk3cJFvPfPZzBy9tlEWxttb77F4+deUtYslfb9cZ4eSEltVpTpAmdJM4DrgHZgOzAHOAM4C3gRWA+sjYgrJB0L3AhsBe4mM0I7LtnPi8B+wF7AK8D0iPhdZ8d+fs2aCruK28ysdxw6enTRq9Nrj96d1/+x+x07Ix0Vsgb0Zm2efNoS12arGpffNbu3I7zDNTMX9nYEy8MDi6fWbG0u25nRiLibTPHK1gjMzbHuo8AHs166ImvZqBLEMzOznvKlt6nl2mxmVqVSUpvL1oyamVl1Cnyi08zMrJKkpTa7GTUzs4L4oURmZmaVJS212c2omZkVJiUFz8zMrGakpDa7GTUzs4JESp7YZ2ZmVivSUpvdjJqZWUHScimQmZlZrUhLbXYzamZmhUnJ6KuZmVnNSEltdjNqZmYFScvoq5mZWa1IS212M2pmZgVJy+PjzczMakVaarObUTMzK0haRl/NzErlmpkLezuC2TukpTanI6WZmVUuKb/JzMzMSqvItVnSCEm/kvS0pJWSLu5k3eMktUk6s6v9+syomZkVJDyuaWZmVlFKUJt3AP8QEY9J2hd4VNI9EfG77JUk1QPXAnd3Z6duRs3MrCBp+SwzMzOzWlHs2hwRG4GNydevS3oaOAj4XYdV/w74L+C47uzXzaiZmRUkLfelmJmZ1YpS1mZJo4A/Ah7u8PpBwMeBk3AzamZm5ZCWJ/aZmZnVinxrs6TZwOyslxZGxLuezCVpAJkzn/8nIl7rsPhbwBciok3dPDPrZtTMzAriM6NmZmaVJd/anDSenT4WWlJfMo3oTyLiZzlWmQAsShrRBuBjknZExC/2tE83o2ZmVhDfM2pmZlZZil2blekwvw88HRHX5zxmxCFZ698E3N5ZIwpuRs3MrEC+TNfMzKyylKA2fxj4JLBC0hPJa18E3gcQEfN7slM3o2ZmVhBfpmtmZlZZil2bI+IB6H6HGxHndWc9N6Pd0NjYyPwFC2hvb2fmjBnMmjXLeSo4TyVmch7nqaY8HfnMqPWGiccM5OLPHUZdnbj9no3cfOt653GeVGdyHucpprTU5oofzpY0StJTydcflfSopBXJnyeV+vhtbW3cMG8eV191FQvmz+f+JUtYu25dqQ/rPFWUyXmcp5ry5NKu+rym7pA0U9KzklZLuizHckn6t2T5k5KO6e62Vrjers11dXDJ+WO49IoVnHvBcqZNGcqoEfuU+rDOUyV5KjGT8zhPsZWiNpdCxTejHbQAp0XEUcCngR+X+oCrVq1i+PDhDBs2jL59+zJ1yhSWPfRQqQ/rPFWUyXmcp5ry5BKqy2vqiqR64AbgFOAI4GxJR3RY7RRgTDLNBr6bx7ZWXGWvzYeP2Y8NG9+k6aW32LEjuHfpJiZPHFzqwzpPleSpxEzO4zzFVuzaXCplO7Kk90i6Q9JvJT0l6ROSviJpeTK/MHlKE5KOTdZ7CLhg5z4i4vGIaEpmVwL9JfUrZe6W1laGNDTsmm9oaKC1tbWUh3SeAlVaJudxnmrKk0ugvKZuOB5YHRHPR8TbwCLg9A7rnA78KDKWAQdIGtbNbS2R1to8ZPBebGrZtmt+c+s2hgwu6SGdp4ryQOVlch7nKbYS1OaSKGcbPBNoiogPRsQ44C7gOxFxXDK/N3Bqsu4PgIsi4kOd7O/PgccjYluuhZJmS2qU1HjLokU9Tx2Ra+c931+hnKdrlZbJeTrnPJ2rtDw5hJTXlP3/czLN7rDLg4Dsm282JK91Z53ubGu79Vptbl67uMehc/0I5PpRKRfn6Vyl5YHKy+Q8nXOe/OVbm3tLOZvRFcA0SddK+khEvAqcKOlhSSuAk4AjJe0PHBARS5Lt3nW5j6QjgWuBv9nTwSJiYURMiIgJZ591Vo9DNzQ0sLmlZdd8S0sLgwcN6vH+CuU8Xau0TM7jPNWUJ5cI5Tnt/v85mTp+yHauqtixzO9pne5sa7v1Wm1+78jTehx6U8vbDG3YfRZiyOB+tLycs/8tC+dJVx6ovEzO4zzFlm9t7i1la0YjYhVwLJnCd42krwDzgDOT+0y+B/Qn84vEHn9xkHQw8HPgUxGxptS5x44dS1NTE83NzWzfvp0lS5cyadKkUh/Weaook/M4TzXlySWoy2vqhg3AiKz5g4Gmbq7TnW0tkdba/MxzrzFi+N4MO7A/ffqIaVOG8uAjvXf5uvOkK08lZnIe5ym2EtTmkijbR7tIGg68HBE3S9oCnJcsapE0ADgTuDUiXpH0qqTJyefZnJO1jwOAO4DLI+LBcuSur69nzpw5zJ07l7b2dqZPn87IkSPLcWjnqZJMzuM81ZQnlxLca7IcGCPpEOD3wFnAX3ZY5zbgQkmLgInAqxGxUdLmbmxribTW5rZ2uH7+aq6/8ijq6sQd9zbzwrqt5Ti081RBnkrM5DzOU2xp+WgXRZkucJY0A7gOaAe2A3OAM8j8ovAimXt81kbEFZKOBW4EtgJ3kxmhHSdpLnA58FzWrqdHxKbOjv38mjW+RMvMDDh09OiiV6dn16zP6//Y948e0WUGSR8DvgXUAzdGxNcknQ8QEfOTh+p8h8w9j1uBz0RE4562zSdfLenN2jz5tCWuzWZmwAOLp6aiNpdC2ZrR3uRm1MwsoxTN6DNrNuT1f+wHRh+cjuFaKyk3o2ZmGaVoRtNSm8t2ma6ZmVWntFwKZGZmVivSUpvdjJqZWUF68yl8ZmZm9m5pqc1uRs3MrCBpGX01MzOrFWmpzW5GzcysIGkpeGZmZrUiLbXZzaiZmRUkLQXPzMysVqSlNrsZNTOzgqTlvhQzM7NakZba7GbUzMwK0p6S0VczM7NakZba7GbUzMwKkpZLgcys5y6/a3ZvR3iHa2Yu7O0IZhUtLbXZzaiZmRUkLZcCmZmZ1Yq01GY3o2ZmVpC0jL6amZnVirTUZjejZmZWkLSMvpqZmdWKtNRmN6NmZlaQtIy+mpmZ1Yq01GY3o2ZmVpC0jL6amZnVirTUZjejZmZWkLaUFDwzM7NakZba7GbUzMwKkpZLgczMzGpFWmqzm1EzMytIWi4FMjMzqxVpqc1uRs3MrCBpGX01MzOrFWmpzW5Gu6GxsZH5CxbQ3t7OzBkzmDVrlvNUcJ5KzOQ8zlNNeTpqj95OYLVo4jEDufhzh1FXJ26/ZyM337reeSopT10dkx/+L976/Us0nnH+OxYNmnI8E342j60vbgCg+ef3sPprN5Q3HxXwPXIe5ymhtNTmut4O0BVJoyQ9lXx9vKQnkum3kj5e6uO3tbVxw7x5XH3VVSyYP5/7lyxh7bp1pT6s81RRJudxnmrKk0ugvCZLv96uzXV1cMn5Y7j0ihWce8Fypk0ZyqgR+5T6sM6Th0Mu+hRbnl6zx+UvP9DIAxPO4IEJZ/RKI1oJ3yPncZ5SSkttrvhmtIOngAkRMR6YCSyQVNKzu6tWrWL48OEMGzaMvn37MnXKFJY99FApD+k8VZbJeZynmvLkEqG8Jqs6Za/Nh4/Zjw0b36TppbfYsSO4d+kmJk8cXMpDOk8e+h90IENPOYH1N95atmPmq7e/R87jPKWWltpctmZU0nsk3ZGMmj4l6ROSviJpeTK/UJKSdY9N1nsIuGDnPiJia0TsSGb7AyU/Ad3S2sqQhoZd8w0NDbS2tpb6sM5TgErL5DzOU015conIb7LKkdbaPGTwXmxq2bZrfnPrNoYM7lfqwzpPNx3xzS/y9OXXEe3te1xn4KTxfOTR/+a4xd9jwBGHlS3bTr39PXIe5ym1tNTmcp4ZnQk0RcQHI2IccBfwnYg4LpnfGzg1WfcHwEUR8aGOO5E0UdJKYAVwflYB7LjebEmNkhpvWbSo56lz/e2oF0f2nadrlZbJeTrnPJ2rtDw5tKO8JqsovVabm9cu7nHoXD8CvfnLlPPsNvRjJ/D25pd57bGVe1zntcdX8svRJ/HrY0/nxRt+zIRby3+Zrv/OOuc8nau0PLmkpTaXsxldAUyTdK2kj0TEq8CJkh6WtAI4CThS0v7AARGxJNnux9k7iYiHI+JI4Djgckn9cx0sIhZGxISImHD2WWf1OHRDQwObW1p2zbe0tDB40KAe769QztO1SsvkPM5TTXlySculQJZTr9Xm9448rcehN7W8zdCG3WchhgzuR8vL2zrZorScZ7eBf3wMQ089iROfu48/+sn1NJw4ifE/vO4d6+x4/Q3a3tgKwOa7lqK+feg7eGBZ8u3kvzPnqaY8uaSlNpetGY2IVcCxZArfNZK+AswDzoyIo4Dvkbm8R3TjEp+IeBp4AxhXstDA2LFjaWpqorm5me3bt7Nk6VImTZpUykM6T5Vlch7nqaY8uaTlUiB7t7TW5meee40Rw/dm2IH96dNHTJsylAcf6b3L151nt2fnXs8vD5nKr8aczOPnXELLr5bxxKc//451+h24+9aD/Y87CtXVsb31D2XJt5P/zpynmvLkkpbaXLaPdpE0HHg5Im6WtAU4L1nUImkAcCZwa0S8IulVSZMj4gHgnKx9HAKsj4gdkkYC7wdeLGXu+vp65syZw9y5c2lrb2f69OmMHDmylId0nirL5DzOU015cvETctMrrbW5rR2un7+a6688iro6cce9zbywbmspD+k8BXrf7MxVausWLuK9fz6DkbPPJtraaHvzLR4/95Ky56m075HzOE+xpaU2K8rUCkuaAVwHtAPbgTnAGcBZZIrWemBtRFwh6VjgRmArcDeZEdpxkj4JXJZs3w5cFRG/6OrYz69Z47F4MzPg0NGji16d7nri7bz+j505fq90VMga0Ju1efJpS1ybU+Tyu2b3doR3uGbmwt6OYFY0DyyeWvG1WdKNZJ4hsCl5pkCudU4AvgX0BVoiYmpXxy3bmdGIuJtM8crWCMzNse6jwAezXroief3HdLhPxczMepfvA00v12Yzs+pUgtp8E/Ad4Ee5Fko6gMxtHjMjYp2kod3ZadmaUTMzq06+D9TMzKyyFLs2R8RSSaM6WeUvgZ9FxLpk/U3d2W85n6ZrZmZVKC2PjzczM6sV+dbm7I/eSqZ8r80fCwyUdL+kRyV9qjsb+cyomZkVxGdGzczMKku+tTkiFgKF3Izdh8zT2U8m8xnVD0laljy1vdONzMzMesz3jJqZmVWWXqjNG8g8tOgN4A1JS8k8Z6DTZtSX6ZqZWUHaI7/JzMzMSqsXavN/Ax+R1EfSPsBE4OmuNvKZUTMzK4gv0zUzM6ssxa7Nkm4BTgAaJG0A/onMR7gQEfMj4mlJdwFPkvmYr/+IiKe62q+bUTMzK0haPljbzMysVhS7NkfE2d1Y5zoyn13dbW5GzcysIG3tvZ3AzErtmpmFPNfEzMotLbXZzaiZmRXEl+mamZlVlrTUZjejZmZWkHY/TdfMzKyipKU2uxk1M7OCpGX01czMrFakpTa7GTUzs4KkpeCZmZnVirTUZn/OqJmZFaScn2UmaZCkeyQ9l/w5cA/rzZT0rKTVki7LsfxSSSGpobBEZmZmlSctnwHuZtTMzAoSobymAl0G3BcRY4D7kvl3kFQP3ACcAhwBnC3piKzlI4CPAusKDWNmZlaJylybe8zNqJmZFSQiv6lApwM/TL7+IXBGjnWOB1ZHxPMR8TawKNlup38F/hFIyUVMZmZm+Slzbe4x3zNqZmYFKfPlPQdGxEaAiNgoaWiOdQ4C1mfNbwAmAkj6U+D3EfFbKR1PGjQzM8tXb156mw83o2ZmVpB8R1QlzQZmZ720MCIWZi2/F3hvjk2/1N1D5HgtJO2T7GN6d7OamZmlUVoeYORmtBsaGxuZv2AB7e3tzJwxg1mzZjlPBeepxEzO4zzVlKejfAte0ngu7GT5tD0tk/SSpGHJWdFhwKYcq20ARmTNHww0AaOBQ4CdZ0UPBh6TdHxENOf3Lqy3TTxmIBd/7jDq6sTt92zk5lvXd72R8zhPBWdyHucpprQ0o53eMyrpAEl/W64wXZF0YfJkxLI9AbGtrY0b5s3j6quuYsH8+dy/ZAlr1/XeMy+cJ32ZnMd5qilPLmV+Yt9twKeTrz8N/HeOdZYDYyQdImkv4CzgtohYERFDI2JURIwi07Qek7ZG1LUZ6urgkvPHcOkVKzj3guVMmzKUUSP2KcehnacK8lRiJudxnmKrlqfpHgC8q+AlTyrsDQ8C04C15TrgqlWrGD58OMOGDaNv375MnTKFZQ89VK7DO08VZHIe56mmPLmU+SEJXwc+Kuk5Mk/E/TqApOGS7szkiR3AhcDdwNPATyNiZcFHrhw1X5sPH7MfGza+SdNLb7FjR3Dv0k1Mnji4XId3npTnqcRMzuM8xZaWBxh11Yx+HRgt6QlJyyX9StJ/AisAJP1C0qOSVib3AJG8viXr6zMl3ZR8fZOk7yb7eV7SVEk3Snp65zrJet+V1Jjs98qdr0fE4xHxYjHeeHe1tLYypGH3QG9DQwOtra3ljOA8eaq0TM7jPNWUJ5f29vymQkREa0ScHBFjkj9fTl5vioiPZa13Z0SMjYjREfG1PexrVES0FJaoV9R8bR4yeC82tWzbNb+5dRtDBvcrZwTnSXEeqLxMzuM8xVbO2lyIrprRy4A1ETEe+DyZx+V/KSJ2fl7bX0XEscAE4CJJ3RkSGAicBPw9sJjMI/aPBI6SND5Z50sRMQE4Gpgq6eh83hRkHpCRFM3GWxYtynfz3XINFfTmExidp2uVlsl5Ouc8nau0PDmkZfS1ilRFbW5euzjfzbP28+7XevPflvN0rtLyQOVlcp7OOU/+0lKb8/2c0Uci4oWs+Ysk/RZYRuZhEWO6sY/FERFkRnBfSu7haQdWAqOSdWZJegx4nEwxPCLnnjoREQsjYkJETDj7rLPy3XyXhoYGNrfsHjhvaWlh8KBBPd5foZyna5WWyXmcp5ry5JKWglfFUlmb3zvytHw332VTy9sMbdh9FmLI4H60vLytky1Ky3nSlQcqL5PzOE+xpaU259uMvrHzC0knkLlH5EMR8UEyxal/sjj7LfXnnXb+TbVnfb1zvo+kQ4BLgZMj4mjgjhz7KJuxY8fS1NREc3Mz27dvZ8nSpUyaNKm34jhPCjM5j/NUU55c0vKQhCpWc7X5medeY8TwvRl2YH/69BHTpgzlwUd67/J150lXnkrM5DzOU2xpqc1dfbTL68C+e1i2P/CHiNgq6QNA9m9HL0k6HHgW+Hiyn+7aj0xhfVXSgcApwP15bF9U9fX1zJkzh7lz59LW3s706dMZOXJkb8VxnhRmch7nqaY8uUTeQ6qVdZlxCtV8bW5rh+vnr+b6K4+irk7ccW8zL6zb2ltxnCdleSoxk/M4T7GlpTarq6DJQxGOBt4kc+nOqcnr/YBfAAeRKWxDgCsi4n5JZwLXAuuBp4ABEXFe8iCE2yPiVkmjkq/HJfvLXnYTMBF4nswI7W0RcZOki4B/JPNh6JuAOyPis129yefXrPFYvJkZcOjo0UWvNv9+R34V7+/+pMJuek2haqjNk09b4tpsZgY8sHhqzdbmLpvRauBm1MwsoxTN6LcX51dILj7Nzai5GTUz26kUzWhaanNXl+mamZl1qgbGNM3MzFIlLbXZzaiZmRXEDyUyMzOrLGmpzW5GzcysIO1t6XhIgpmZWa1IS212M2pmZgVJy+irmZlZrUhLbXYzamZmBUnLfSlmZma1Ii212c2omZkVpD0tw69mZmY1Ii212c2omZkVJC2jr2ZmZrUiLbXZzaiZmRUkLQXPzMysVqSlNrsZNTOzgrSnpeKZmZnViLTUZjejZmZWkGjv7QRmZmaWLS212c2omZkVJFIy+mpmZlYr0lKb3YyamVlB2lMy+mpmZlYr0lKb3YyamVlB0jL6amZmVivSUpvdjJqZWUFS8lFmZmZmNSMttdnNqJmZFSTSUvHMzMxqRFpqc11vBzAzs3SLyG8yMzOz0ipFbZY0U9KzklZLuizH8v0lLZb0W0krJX2mq336zKiZmRWkPSWjr2ZmZrWi2LVZUj1wA/BRYAOwXNJtEfG7rNUuAH4XEadJGgI8K+knEfH2nvbrZrQbGhsbmb9gAe3t7cycMYNZs2Y5TwXnqcRMzuM81ZSno7Q8JMGqy8RjBnLx5w6jrk7cfs9Gbr51vfM4T6ozOY/zFFMJavPxwOqIeB5A0iLgdCC7GQ1gX0kCBgAvAzs622mnl+lKOkDS3xaSupgk/SQ5NfyUpBsl9S31Mdva2rhh3jyuvuoqFsyfz/1LlrB23bpSH9Z5qiiT8zhPNeXJJdrzm6wwrs1QVweXnD+GS69YwbkXLGfalKGMGrFPqQ/rPFWSpxIzOY/zFFu+tVnSbEmNWdPsDrs8CMjuuDckr2X7DnA40ASsAC6O6Lzyd3XP6AHAuwpecpq2N/wE+ABwFLA38NlSH3DVqlUMHz6cYcOG0bdvX6ZOmcKyhx4q9WGdp4oyOY/zVFOeXNoj8pqsYDVfmw8fsx8bNr5J00tvsWNHcO/STUyeOLjUh3WeKslTiZmcx3mKLd/aHBELI2JC1rSwwy6V4zAdi/oM4AlgODAe+I6k/TrL2VUz+nVgtKQnJC2X9CtJ/0mm00XSLyQ9mtyguqt7lrQl6+szJd2UfH2TpO8m+3le0tRkFPXpnesk63036chXSrpy17uNuDMSwCPAwV3kL1hLaytDGhp2zTc0NNDa2lrqwzpPASotk/M4TzXlySUyRazbkxWs5mvzkMF7sall2675za3bGDK4X6kP6zxVkgcqL5PzOE+xlaA2bwBGZM0fTOYMaLbPAD9LSsJq4AUyg5V71FUzehmwJiLGA58nc63wlyLiiGT5X0XEscAE4CJJ3RkSGAicBPw9sBj4V+BI4ChJ45N1vhQRE4CjgamSjs7eQXIJ0CeBu/Z0kOxTzbcsWtSNWHuQ6y9HuQYGysR5ulZpmZync87TuUrLk0N7e+Q1WcGqojY3r13czbebaz/vfq03xzmcp3OVlgcqL5PzdM558leC2rwcGCPpEEl7AWcBt3VYZx1wMoCkA4H3A893ttN8H2D0SES8kDV/kaSPJ1+PAMYAXQ3ZL46IkLQCeCkido7krgRGkTm1OysZze0DDAOOAJ7M2sc8YGlE/HpPB0lOLS8EeH7Nmh7/82hoaGBzS8uu+ZaWFgYPGtTT3RXMebpWaZmcx3mqKU8ulVaAa1Aqa/Pk05b0+F/Oppa3Gdqw+yzEkMH9aHl5WydblJbzpCsPVF4m53GeYit2bY6IHZIuBO4G6oEbI2KlpPOT5fOBq4Gbkloi4AsR0bLHnZL/54y+sfMLSScA04APRcQHgceB/jvzZm3Tn3fa+TfVnvX1zvk+kg4BLgVOjoijgTuy9yHpn4AhwCV5Zu+RsWPH0tTURHNzM9u3b2fJ0qVMmjSpHId2nirJ5DzOU015cmlra89rsqKrudr8zHOvMWL43gw7sD99+ohpU4by4CO9d/m686QrTyVmch7nKbZS1ObktoyxETE6Ir6WvDY/aUSJiKaImB4RR0XEuIi4uat9dnVm9HVg3z0s2x/4Q0RslfQBIPu3o5ckHQ48C3w82U937UemsL6anN49BbgfQNJnydwYe3JXT2Yqlvr6eubMmcPcuXNpa29n+vTpjBw5shyHdp4qyeQ8zlNNeXIJX3pbbjVfm9va4fr5q7n+yqOoqxN33NvMC+u2luPQzlMFeSoxk/M4T7GlpTarqxtWk4ciHA28SebSnVOT1/sBvyDzSN9nyYyIXhER90s6E7iWzON/nwIGRMR5yYMQbo+IWyWNSr4el+wve9lNwEQy1xhvA26LiJsk7QDWsruA/iwirurqTRZyma6ZWTU5dPToot9wesE3Xsnr/9gbLj2gsm56TaFqqM2FXKZrZlZNHlg8tWZrc5f3jEbEX+7h9W1kRkZzLbsVuDXH6+dlff0iMG4Py84jh4jI9x5XMzMrsZQMvlYV12YzM+tMWmqzC4iZmRUkLZcCmZmZ1Yq01GY3o2ZmVhB/dqiZmVllSUttdjNqZmYF8WeHmpmZVZa01GY3o2ZmVpC0jL6amZnVirTU7sspcQAAFNhJREFUZjejZmZWkLTcl2JmZlYr0lKb3YyamVlB0lLwzMzMakVaarObUTMzK0h7Si4FMjMzqxVpqc11vR3AzMzSLdojr6kQkgZJukfSc8mfA/ew3kxJz0paLemyrNfHS1om6QlJjZKOLyiQmZlZBSpnbS6Em1EzMytIROQ1Fegy4L6IGAPcl8y/g6R64AbgFOAI4GxJRySL/wW4MiLGA19J5s3MzKpKmWtzj/kyXTMzK0iZHx9/OnBC8vUPgfv5/+3de5BcdZnG8e+TcAnIJZBwSQADxqAiBuSWKMhFIqCCqMtGqBUV1ChKreuqK6WUArq76rrUrrVCyCqi6MquQGESKLnsykUlRaJCYrgolwJiEiABFQnBJPPuH30GmmHm9Exmps97up9P1dRMn+7p/oZJ5uXXffoc+Gyf2xwG3B8RDwJIuqL4vruBAHYobrcjsHJ0c83MzNrPp3YxM7Ou0Obde3aLiFUAEbFK0q793GYP4NGmyyuAGcXXfwdcL+nrNPYOeuNoxpqZmVXBBzAyM7OuMNTdeyTNAeY0bZoXEfOarr8J2L2fb/38YB+in229kWcBn4yIqyTNBr4NzBrk/ZqZmdWCzzNqZmZdIXp6hnb7xsJzXsn1Ay4OJT0maVLxqugk4PF+brYC2Kvp8p68sDvu+4FPFF//CPjWUNrNzMzqYKizuSo+gJGZmQ1LT08M6WOY5tNYUFJ8/nE/t1kMTJO0j6StgFOL74PGovSo4us3A78bbpCZmVk2bZ7Nm82vjJqZ2bC0eVegrwD/I+mDwCPAXwNImgx8KyLeFhEbJZ0NXA+MBS6NiOXF938Y+HdJWwDrefHuwmZmZh3Bu+mamVlXaOdBEiJiLXBsP9tXAm9runwdcF0/t/sZcPBoNpqZmVXNBzAyM7OuUJeBZ2Zm1i3qMpu9GB2EJUuWMPeSS+jp6eGE449n9uzZ7knck7HJPe7ppJ6+eqIeB0mwzjLjoJ34xIdfyZgxYuGNq/j+lY+2/ib3uCdxk3vcM5LqMptLD2Akabykj7UrphVJ35Z0l6Slkq6UtN1oP+amTZv45kUX8aULLuCSuXO5+ZZbePiRR0b7Yd3TQU3ucU8n9fSnZ2PPkD5seDybYcwY+PuPTuPT5y3jvR9fzKwjd2XvvbYd7Yd1T4f0ZGxyj3tGWl1mc6uj6Y4HXjLwJI0dnZyWPhkRB0TEdBoHrjh7tB/wt7/9LZMnT2bSpElsueWWHHXkkSy6/fbRflj3dFCTe9zTST39iYghfdiwdf1sfs20HVix6llWPraejRuDm259nCNmTBjth3VPh/RkbHKPe0ZaXWZzq8XoV4Cpku6UtFjSTyX9F7AMQNI1kn4paXlxEnOK7X9u+voUSZcVX18m6eLifh6UdJSkSyXd03ub4nYXS1pS3O/5vdsj4k/F9QK24YWTmI+aNWvXssvEic9fnjhxImvXrh3th3XPMGRrco97OqmnPz09PUP6sGHr+tm8y4SteHzNc89ffmLtc+wyYevRflj3dEgP5Gtyj3tGWl1mc6v3jJ4D7B8RB0o6Gri2uPxQcf2ZEfGkpG2AxZKuKo50WGYnGud2ewewADgc+FDx/QdGxJ3A54v7HQv8r6TpEbEUQNJ3aBwx8W7gU0P+Ew9Vf88USKP+sANyT2vZmtxTzj3lsvX0oy4HSeggXT+b+/snUOWL7u4pl60H8jW5p5x7hq4us7nVK6N93dE07AD+VtJdwCJgL2DaIO5jQTReC14GPBYRyyKiB1gO7F3cZrakXwG/Bl4L7Nf7zRFxBjAZuAd4z0APImlO8Qzukh9eccWg/4B9TZw4kSfWrHn+8po1a5iw886bfX/D5Z7WsjW5xz2d1NOfiJ4hfdiIq+VsXv3wgkH/Aft6fM1f2HXiC69C7DJha9Y8+VzJd4wu99SrB/I1ucc9I60us3moi9Fner8ono2dBbwhIg6gMZzGFVc3L8XH8WK9P6mepq97L28haR/g08CxxftPru17HxGxCfhv4K8GCo2IeRFxSEQcctqppw7uT9ePfffdl5UrV7J69Wo2bNjALbfeysyZMzf7/obLPfVrco97OqmnP9ETQ/qwEVfL2bz7lJMG96frx72/+xN7Td6GSbuNY4stxKwjd+Xnd1S3+7p76tWTsck97hlpdZnNrXbTfRrYfoDrdgSeioh1kl4NNP/f0WOSXgPcB7yruJ/B2oHGYP2jpN2AtwI3F+9FmRoR9xdfnwTcO4T73Sxjx47lrLPO4txzz2VTTw/HHXccU6ZMGe2HdU8HNbnHPZ3U0x8vMNuu62fzph64cO79XHj+6xgzRlx702oeemTdaD+sezqkJ2OTe9wz0uoym9Xq6EnFQRGmA8/S2HXnxGL71sA1wB40BtsuwHkRcbOkU4CvAo8CvwG2i4gPFAdCWBgRV0rau/h6/+L+mq+7DJgBPEjjGdr5wPeA22gMRAF3AWf1HjihzIMPPFCPn4aZ2Sh7xdSpI/6G0+Pff+eQfsde/90Dc73ptYY6YTYfcdItns1mZsDPFhzVtbO55WK0E3gxambWMBqL0eNO//WQfsfecPnrvRg1L0bNzAqjsRity2xutZuumZlZqfDpWszMzFKpy2z2YtTMzIalLu9LMTMz6xZ1mc1ejJqZ2bD4dC1mZma51GU2ezFqZmbD0lOTZ1/NzMy6RV1msxejZmY2LHV5X4qZmVm3qMtsHlN1gJmZ1VtdTqxtZmbWLUZjNks6QdJ9ku6XdE4/10vSN4rrl0o6qNV9+pVRMzMblrq8L8XMzKxbjPRsljQW+CbwFmAFsFjS/Ii4u+lmbwWmFR8zgIuLzwPyYtTMzIbFr3aamZnlMgqz+TDg/oh4EEDSFcDJQPNi9GTgexERwCJJ4yVNiohVA91pVyxGR+ok75LmRMS8kbivkeCecu4p555y7hm82378pkpOlG31NlInec/2b8M95dxTzj3l3DN4Q53NkuYAc5o2zevzZ9sDeLTp8gpe+qpnf7fZAxhwMer3jA7NnNY3aSv3lHNPOfeUc49ZPWT7t+Gecu4p555y7hklETEvIg5p+ui7yO5vcdv35dfB3OZFvBg1MzMzMzOzMiuAvZou7wms3IzbvIgXo2ZmZmZmZlZmMTBN0j6StgJOBeb3uc184H3FUXVnAn8se78odMl7RkdQtn3C3VPOPeXcU849ZvWQ7d+Ge8q5p5x7yrmnIhGxUdLZwPXAWODSiFgu6aPF9XOB64C3AfcD64AzWt2vGgc7MjMzMzMzM2sf76ZrZmZmZmZmbefFqJmZmZmZmbWdF6NmZmZmZmbWdl6MmpmZmZmZWdt5MboZJL2losfdQdLUfrZPr6hnd0m7F1/vIundkl5bRUsZSa+u8LG37GfbxIpaxkgaU3y9laSDJO1cRUsZSW0/Mp2ksZI+IulLkg7vc925FfRsK+kfJH1G0jhJH5A0X9LXJG3X7h6zOvBsfv5xPZtbP7Zn8xBUMZeLx/Vs7gJejG6eb7f7ASXNBu4FrpK0XNKhTVdfVkHPR4DbgUWSzgIWAicCV0v6YLt7Wrih3Q8o6RhJK4CVkm6QtHfFPe8EVgG/l3QycBvwdWCppJMq6Nl5gI8JNA4J3m6XAEcBa4FvSLqw6bp3V9BzGbAbsA9wLXAIjZ+XgIsr6DGrA89mz+ZSns2lLdnmMng2dwWfZ3QAkvqexPX5q4AJ7WwpfA44OCJWSToMuFzS5yLi6qKp3c4GXgtsAzwMvDIiVkvaCfgpbf6fAknfGOgqYHw7WwpfA44vzr90CnCjpNMjYhHV/Ly+CBxA4+d1F3BoRNwnaQpwFbCgzT1P0Ph70/zfIorLu7a5BeCwiJgOIOk/gIskXQ2cRjU/r30jYrYk0fgflVkREZJuo/HzM+tKns0teTaX82weWLa5DJ7NXcGL0YG9CXgv8Oc+2wUc1v4cxkbEKoCIuEPSMcBCSXvS+GXRbhsiYh2wTtIDEbG6aHtKUhU9ZwCfAp7r57rT2twCsFVELAeIiCsl3UPjmelzqObnRe/PSNIjEXFfse3h3t2D2uxB4NiIeKTvFZIeraBnq94vImIjMEfSF4D/Ayrb9aYYctdFcULo4rJPDm3dzLO5nGdzOc/mgWWby+DZ3BW8GB3YImBdRNzS9wpJ91XQ87SkqRHxAEDxLOzRwDU0ngVttx5JW0bEBuDtvRsljaOa3b8XA7+JiF/0vULSee3PYYOk3Zv+R2C5pGNp7DL1kvcWtYOkMRHRA5zZtG0sTb/s2+jfgJ2Alww9Gs9ct9sSSSdExE96N0TEBZJWUs2uN0skbRcRf46I5p/XVODpCnrMsvBsLufZXM6zeWDZ5jJ4NncFFYt6S07SAcAzEXF/n+1bArMj4gdt7nk5sLJ4pqp5+x7AayLipjb37AysL54RrpykWcATEXFXn+3jgY9HxD+2uedQYFlErO+zfW/giIj4fjt7bPNJUvgXt1kKns0tezyby3s8mzuEZ/Pm82K0BUn7RcTdfbYdHRE3uydfj9WPpP2B/YBxvdsi4nvuydljlkG22eMe6yQZ5062pmw9debFaAuSfgNcTmMXhXHF50Mi4g3uydMjaRkl7/fofQN8u7hncCR9ETiaxi/064C3Aj+LiFPck6/HLIsss8c9LTtSzR73tJZx7mRrytZTd37PaGszgK8CvwC2B34AHF76He6poufE4vPHi8+XF5//Bqhi9yD3DM4pNI4k+OuIOEPSbsC33JO2xyyLLLPHPeWyzR73tJZx7mRrytZTa16MtrYBeJbGYbfHAQ8VbzR3T6KeiHgYQNLhEdE8cM+R9HPgAvfk6WnybET0SNooaQfgceAVFbW4x6w+Uswe95TLNnvcMygZ5062pmw9tVbFkdXqZjGNX+iHAkcAp0m60j1pe14m6YjeC5LeCLzMPWl7lhQHjvhP4JfAr4A73JO2xyyLbLPHPeWyzR73DCzj3MnWlK2n1vye0RYkHRIRS/psOz0iLh/oe9xTac/BwKXAjsWmPwBnRsSv3JOvp1lx9MAdImJpxSmAe8wySzh73FPek2r2uGdwMs6dbE3ZeurIi9FBkrQrLz5iVn/nYWob95QrdptQRPyxyo5e7iltmQ7sTdPbBiLiavfk7DHLJOHscU+JTLMH3FPSkW7uZGvK1lNnfs9oC5JOAi4EJtPYJ3wKcA/VnMzaPYNrenvx+OMkAY2TJLsnX4+kS4HpwHKg9/1MAVTyC909ZvWQbfa4Z1BNaWaPe0o70s2dbE3ZeurOi9HWvgzMBG6KiNdLOgY4zT05eyTNBbYFjqFxZLNTqHA/fve0NDMi9qvw8ftyj1k9pJo97imXbfa4p1TGuZOtKVtPrfkARq1tiIi1wBhJYyLip8CB7knb88aIeB/wVEScD7wB2Ms9aXtul5TpF7p7zOoh2+xxT7lss8c9A8s4d7I1ZeupNb8y2tofJG0H3Ar8QNLjwEb3pO1ZX3xeJ2ky8CSwj3vS9nyXxi/11cBzgICo4kTf7jGrlWyzxz3lss0e9wws49zJ1pStp9a8GG3tZBq/JD5J4yTEO1LdORnd09qC4nDb/0LjUNtB49Db7snZcylwOrCMF953USX3mNVDttnjnnLZZo97BpZx7mRrytZTa16MthARzzRd/G5lIQX3tHQvsCkirip2oTgIuMY9aXseiYj5FT5+X+4xq4Fss8c9LWWbPe4ZWMa5k60pW0+t+dQuA5D0NI1npp7fVFzufSl+B/fk6WnqWhoR09U4efQ/Af8KfC4iZrgnZc9FwHhgAY1dXYDqDo/uHrPcss0e9wy6K9vscc/ALenmTrambD1151dGBxAR21fd0Mw9g7ap+Px2YG5E/FjSee5J27MNjV/kxzVtq/Lw6O4xSyzb7HHPoGWbPe4ZWMa5k60pW0+t+ZXRQSieqZoWEd+RNBHYPiIeck++HkkLgd8Ds4CDgWeBOyLiAPfk6zEz21yZZo97Wrakmj3uMcvDi9EWJH0ROAR4VUTsWxzl7EcRcbh7UvZsC5wALIuI30maBLwuIm5wT8qe7/DiXcoAiIgzK8hxj1lNJJw97invyTZ73DNwS7q5k60pW0/deTfd1t4FvJ7G0c2IiJWSqtwNxj0lImIdTbtJRMQqYJV7cvYAC5u+Hkfj79PKilrAPWZ1kWr2uKdcttnjnlIZ5062pmw9tebFaGt/iYiQFACSXuae1D1WIxFxVfNlST8Ebqooxz1m9ZFt9rjHOkLGuZOtKVtP3Y2pOiAzSQIWSroEGC/pwzT+slVy7if3WBeYBry86ogm7jFLJtvscY91uIxzJ1tTtp5a8SujJYpnFd8JfBb4E/Aq4AsRcaN78vVY/TSdhqD39AOrafx9ck/CHrMMss0e91gnyTh3sjVl66k7L0Zbux34Q0R8puqQgnusY2Q7DYF7zGoj2+xxj3WEjHMnW1O2nrrz0XRbkHQ3sC/wMPBM7/aImO6efD1WP5J2orGLy7jebRFxq3ty9phlkG32uMc6Sca5k60pW0+deTHagqQp/W2PiIfb3QLusc4i6UPAJ4A9gTuBmcDtEfFm9+TrMcsi2+xxj3WKjHMnW1O2nrrzYtTMKiNpGXAosCgiDpT0auD8iHiPe/L1mJlZZ8s4d7I1ZeupOx9N18yqtD4i1gNI2joi7qVxsA335OwxM7POlnHuZGvK1lNrPoCRmVVphaTxwDXAjZKeotoTR7vHzMy6Wca5k60pW0+teTddM0tB0lHAjsBPIuIv7sndY2ZmnS3j3MnWlK2njrwYNbNKSBoDLI2I/atuAfeYmVl3yzh3sjVl6+kEfs+omVUiInqAuyS9vOoWcI+ZmXW3jHMnW1O2nk7g94yaWZUmAcsl3cGLz4X3Dvek7DEzs86Wce5ka8rWU2tejJpZlbYDTmy6LOCrFbWAe8zMrLtlnDvZmrL11JoXo2ZWpS0i4pbmDZK2qSoG95iZWXfLOHeyNWXrqTUvRs2s7SSdBXwMeIWkpU1XbQ/83D25eszMrLNlnDvZmrL1dAofTdfM2k7SjsBOwD8D5zRd9XREPOmeXD1mZtbZMs6dbE3ZejqFF6NmZmZmZmbWdj61i5mZmZmZmbWdF6NmZmZmZmbWdl6MmpmZmZmZWdt5MWpmZmZmZmZt58WomZmZmZmZtd3/A1zyWA8kwavgAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# t test between groups\n", + "t,p = scipy.stats.ttest_ind(ketArrSes1, midArrSes1)\n", + "tArr = np.array(t)\n", + "fdr = fdr_corr(p, thr)\n", + "tArr[fdr>.05]=0 # set p value to cut\n", + "\n", + "fig, ax_list = plt.subplots(1, 2, figsize=(16,4.5))\n", + "ax = ax_list[0]\n", + "ax.title.set_text('First Session')\n", + "sns.heatmap(tArr, cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list,annot=True, ax=ax)#,\n", + " #vmin = -1, vmax=1)\n", + " \n", + "t,p = scipy.stats.ttest_ind(ketArrSes2, midArrSes2)\n", + "# threshold the t\n", + "tArr = np.array(t)\n", + "tArr[fdr_corr(p, thr)>.05]=0 # set p value to cut\n", + "ax = ax_list[1]\n", + "ax.title.set_text('Second Session')\n", + "sns.heatmap(tArr, cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, annot=True,ax=ax)#,\n", + " #vmin = -1, vmax=1)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 534, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(20, 81)\n" + ] + } + ], + "source": [ + "vecSes2 = []\n", + "for mat in cor_OneSes2:\n", + " vec = mat.flatten()\n", + " vecSes2.append(vec)\n", + "vecSes2 = np.array(vecSes2)\n", + "print(vecSes2.shape)\n", + "from sklearn.decomposition import PCA\n", + "pca = PCA(n_components=3)\n", + "X_r = pca.fit(vecSes2).transform(vecSes2)" + ] + }, + { + "cell_type": "code", + "execution_count": 535, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "explained variance ratio (first two components): [0.295198 0.15521719 0.09688818]\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "print('explained variance ratio (first two components): %s'\n", + " % str(pca.explained_variance_ratio_))\n", + "colors = ['navy', 'orange']\n", + "lw = 2\n", + "y = np.array(group_label) # make it an array so we can get mask for each place\n", + "target_names = ['Midazolam','Ketamine']\n", + "for color, i, target_name in zip(colors, [0, 1], target_names):\n", + " plt.scatter(X_r[y == i, 0], X_r[y == i, 1], color=color, alpha=.8, lw=lw,\n", + " label=target_name)\n" + ] + } + ], + "metadata": { + "celltoolbar": "Slideshow", + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/RSA_seperate_sessions.ipynb b/task_based_analysis/RSA_seperate_sessions.ipynb new file mode 100644 index 0000000..041f154 --- /dev/null +++ b/task_based_analysis/RSA_seperate_sessions.ipynb @@ -0,0 +1,692 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + " # Map beta of each condition and correlate between groups\n", + " - Mask for amygdala, vmPFC, hippocampus and caudate\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [], + "source": [ + "# import relevant packages\n", + "import glob\n", + "import numpy as np\n", + "import scipy\n", + "import nilearn\n", + "import nilearn.plotting\n", + "import nilearn.input_data\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import statsmodels.stats as sm # for FDR correction\n", + "import dask # for paralleliz" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [], + "source": [ + "#thr = 0.05 # set threshold\n", + "def fdr_corr(p, thr=0.05):\n", + " import statsmodels.stats.multitest as sm\n", + " # FDR correction\n", + " # takes the p from the t test, flatten and return a 36x36 mask\n", + " # flatten p\n", + " ptri = np.tril(p)\n", + " pflat = ptri.flatten()\n", + " fdr = sm.multipletests(pflat, alpha=thr, method='fdr_bh')\n", + " fdrArr = fdr[0].reshape(9,9)\n", + " return fdrArr " + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Amygdala as mask\n", + "mask_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=21\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "\n", + "\n", + "maskerAmg = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " smoothing_fwhm=None, verbose=0).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# now lets do the same with vmPFC\n", + "mask_file = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=6\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "maskervmPFC = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " smoothing_fwhm=None,\n", + " verbose=0).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Run same with hippocampus\n", + "## Hippocampus\n", + "mask_file = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=15\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "maskerHipp = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " smoothing_fwhm=None,\n", + " verbose=0).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/caudate_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "maskerCaudate = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " smoothing_fwhm=None, \n", + " verbose=0).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['KPE008', 'KPE1223', 'KPE1253', 'KPE1263', 'KPE1293', 'KPE1307',\n", + " 'KPE1315', 'KPE1322', 'KPE1339', 'KPE1343', 'KPE1351', 'KPE1356',\n", + " 'KPE1364', 'KPE1369', 'KPE1387', 'KPE1390', 'KPE1403', 'KPE1464',\n", + " 'KPE1468', 'KPE1480', 'KPE1499'], dtype=object)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# compare between groups\n", + "import pandas as pd\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "medication_cond\n", + "\n", + "group_label = np.array(medication_cond.med_cond)\n", + "#group_label = list(map(int, group_label))\n", + "\n", + "sub_list = np.array(medication_cond.scr_id)\n", + "sub_list" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "subject_list = []\n", + "for sub in sub_list:\n", + " sub = sub.split('KPE')[1]\n", + " subject_list.append(sub)\n", + "#subject_list.remove('1390')" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "# function to find ev number (lookin in run.fsf file)\n", + "def findEV(txtFile, condition):\n", + " # takes the txtFile and the specific condition\n", + " with open(txtFile) as f:\n", + " datafile = f.readlines()\n", + " lines = []\n", + " for line in datafile:\n", + " if condition in line:\n", + " # found = True # Not necessary\n", + " #print(line)\n", + " lines.append(line)\n", + "\n", + " return lines[0].split('evtitle')[1].split(')')[0]\n", + "\n", + "def getCorr(sub, condition, masker):\n", + " # takes subject, condition (relax, trauma, sad) and masker object\n", + " fsf_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/allScript_ses{ses}_Nosmooth/modelfit_ses_{ses}/_subject_id_{sub}/level1design/run0.fsf'\n", + " betaTemplate = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/allScript_ses{ses}_Nosmooth/modelfit_ses_{ses}/_subject_id_{subject_id}/modelestimate/mapflow/_modelestimate0/results/pe{betaNum}.nii.gz'\n", + "\n", + " # get beta files for session 1 condition X\n", + " beta1 = fsf_template.format(ses='1', sub=sub)\n", + " number_1 = findEV(beta1, condition)\n", + " # find beta file\n", + " betaFile_1 = betaTemplate.format(ses='1', subject_id = sub, betaNum = number_1)\n", + " beta1_transform = masker.transform(betaFile_1)\n", + " # get beta files for session 2 condition X\n", + " beta2 = fsf_template.format(ses='2', sub=sub)\n", + " number_2 = findEV(beta2, condition)\n", + " # find beta file\n", + " betaFile_2 = betaTemplate.format(ses='2', subject_id = sub, betaNum = number_2)\n", + " beta2_transform = masker.transform(betaFile_2)\n", + "\n", + " #correlate it\n", + " cor = scipy.stats.pearsonr(beta1_transform[0], beta2_transform[0])[0]\n", + " return cor, beta1_transform, beta2_transform\n", + "\n", + "def generatCor(cond_list, beta1Arr, beta2Arr):\n", + " # this functuion creates a simple matrix of correlation between session 1 and 2\n", + " x = np.zeros([len(cond_list),len(cond_list)])\n", + " for i, cond in enumerate(cond_list):\n", + " \n", + " for j, c in enumerate(cond_list):\n", + " x[i,j] = scipy.stats.pearsonr(beta1Arr[i], beta2Arr[j])[0]\n", + " return x" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "# get condition list\n", + "events_file = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/sub-1464_ses-1.csv'\n", + "cond = pd.read_csv(events_file, sep='\\t')\n", + "cond_list = np.unique(cond.trial_type_N)\n", + "#cond_list" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Lets try another thing - Using RSA for the same scan. \n", + "- Hypothesis here will say Ketamine will be fatster to recover, hence lower correlation in trauma" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running the 0 subject\n", + " Running the 1 subject\n", + " Running the 2 subject\n", + " Running the 3 subject\n", + " Running the 4 subject\n", + " Running the 5 subject\n", + " Running the 6 subject\n", + " Running the 7 subject\n", + " Running the 8 subject\n", + " Running the 9 subject\n", + " Running the 10 subject\n", + " Running the 11 subject\n", + " Running the 12 subject\n", + " Running the 13 subject\n", + " Running the 14 subject\n", + " Running the 15 subject\n", + " Running the 16 subject\n", + " Running the 17 subject\n", + " Running the 18 subject\n", + " Running the 19 subject\n", + " Running the 20 subject\n" + ] + } + ], + "source": [ + "cor_OneSes1_amg = []\n", + "cor_OneSes1_vmPFC = []\n", + "cor_OneSes1_hippo = []\n", + "cor_OneSes1_caudate = []\n", + "cor_OneSes2_amg = []\n", + "cor_OneSes2_vmPFC = []\n", + "cor_OneSes2_hippo = []\n", + "cor_OneSes2_caudate = []\n", + "\n", + "for i, sub in enumerate(subject_list):\n", + " print (f' Running the {i} subject')\n", + " beta1Arr_amg = []\n", + " beta2Arr_amg = []\n", + " beta1Arr_hipp = []\n", + " beta2Arr_hipp = []\n", + " beta1Arr_vmPFC = []\n", + " beta2Arr_vmPFC = []\n", + " beta1Arr_caudate = []\n", + " beta2Arr_caudate = []\n", + " conditions = []\n", + " for cond in cond_list:\n", + " cor, beta1amg, beta2amg = getCorr(sub, cond, maskerAmg)\n", + " cor, beta1hipp, beta2hipp = getCorr(sub, cond, maskerHipp)\n", + " cor, beta1vmPFC, beta2vmPFC = getCorr(sub, cond, maskervmPFC)\n", + " cor, beta1caudate, beta2caudate = getCorr(sub, cond, maskerCaudate)\n", + " conditions.append(cond)\n", + " beta1Arr_amg.append(beta1amg[0])\n", + " beta2Arr_amg.append(beta2amg[0])\n", + " beta1Arr_hipp.append(beta1hipp[0])\n", + " beta2Arr_hipp.append(beta2hipp[0])\n", + " beta1Arr_vmPFC.append(beta1vmPFC[0])\n", + " beta2Arr_vmPFC.append(beta2vmPFC[0])\n", + " beta1Arr_caudate.append(beta1caudate[0])\n", + " beta2Arr_caudate.append(beta2caudate[0])\n", + " corMat1amg = np.corrcoef(beta1Arr_amg)\n", + " corMat2amg = np.corrcoef(beta2Arr_amg)\n", + " corMat1hipp = np.corrcoef(beta1Arr_hipp)\n", + " corMat2hipp = np.corrcoef(beta2Arr_hipp)\n", + " corMat1vmPFC = np.corrcoef(beta1Arr_vmPFC)\n", + " corMat2vmPFC = np.corrcoef(beta2Arr_vmPFC)\n", + " corMat1caudate = np.corrcoef(beta1Arr_caudate)\n", + " corMat2caudate = np.corrcoef(beta2Arr_caudate)\n", + " cor_OneSes2_amg.append(corMat2amg)\n", + " cor_OneSes1_amg.append(corMat1amg)\n", + " cor_OneSes2_caudate.append(corMat2caudate)\n", + " cor_OneSes1_caudate.append(corMat1caudate)\n", + " cor_OneSes2_hippo.append(corMat2hipp)\n", + " cor_OneSes1_hippo.append(corMat1hipp)\n", + " cor_OneSes2_vmPFC.append(corMat2vmPFC)\n", + " cor_OneSes1_vmPFC.append(corMat1vmPFC)" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [], + "source": [ + "def plotRSA(arrGroup, cond_list):\n", + " # separate groups\n", + " groupArr = np.array(arrGroup)\n", + " #print('Running t test')\n", + " group1 = groupArr[group_label==1]\n", + " group2 = groupArr[group_label==0]\n", + " # plot mean matrices\n", + " fig, ax_list = plt.subplots(1, 2, figsize=(16,4.5))\n", + " ax = ax_list[0]\n", + " ax.title.set_text('Ketamine')\n", + " sns.heatmap(np.mean(group1, axis=0), cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax,\n", + " vmin = -1, vmax=1)\n", + " ax = ax_list[1]\n", + " ax.title.set_text('Midazolam')\n", + " sns.heatmap(np.mean(group2, axis=0), cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list, ax=ax,\n", + " vmin = -1, vmax=1)\n", + " plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "array_list = [cor_OneSes1_amg, cor_OneSes1_caudate, cor_OneSes1_hippo, cor_OneSes1_vmPFC,\n", + " cor_OneSes2_amg, cor_OneSes2_caudate, cor_OneSes2_hippo, cor_OneSes2_vmPFC]\n", + "for ar in array_list:\n", + " \n", + " plotRSA(ar, cond_list)" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [], + "source": [ + "def plotRSAttest(arrGroup, cond_list, thr):\n", + " # separate groups\n", + " groupArr = np.array(arrGroup)\n", + " #print('Running t test')\n", + " group1 = groupArr[group_label==1]\n", + " group2 = groupArr[group_label==0]\n", + " # t test between groups\n", + " t,p = scipy.stats.ttest_ind(group1, group2)\n", + " tArr = np.array(t)\n", + " fdr = fdr_corr(p, thr)\n", + " tArr[~fdr]=0 # set p value to cut\n", + "\n", + " sns.heatmap(tArr, cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list,annot=True)#,\n", + " #vmin = -1, vmax=1)\n", + " return t" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "t = plotRSAttest(cor_OneSes2_amg, cond_list, .01)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [], + "source": [ + "## build permutation test instead of FDR?\n", + "# for each iteration:\n", + "# shuffle groups\n", + "# run t-test\n", + "# end of itreration - compare actual t score of each cell with t-test distribution\n", + "# every t-score with chances lower than .05 in random distribution will be considered ok\n", + "import random\n", + "\n", + "def permutation(groupArr, group_label, numIter, thr):\n", + " # take groupArr, shuffle group labels and run t test\n", + " # returns a mask of things that crossed significance and a t matrix\n", + " # run the real t test first\n", + " groupArr = np.array(groupArr)\n", + " #print('Running t test')\n", + " group1 = groupArr[group_label==1]\n", + " group2 = groupArr[group_label==0]\n", + " t,p = scipy.stats.ttest_ind(group1, group2)\n", + " permAr = []\n", + " for i in range(numIter):\n", + " \n", + " #print (f'Iteration number {i}')\n", + " group_label_ran = np.array(group_label)\n", + " \n", + " # shuffle groups\n", + " random.shuffle(group_label_ran)\n", + " # stratify to groups\n", + " group1 = groupArr[group_label_ran==1]\n", + " group2 = groupArr[group_label_ran==0]\n", + " tPerm, pPerm = scipy.stats.ttest_ind(group1, group2)\n", + " permAr.append(tPerm)\n", + " permAr = np.array(permAr)\n", + " x = np.empty([9,9])\n", + " for i in range(x.shape[0]):\n", + " for j in range(x.shape[1]):\n", + " check = np.sum(permAr[:,i,j][permAr[:,i,j]>t[i,j]])/ len(permAr)\n", + " if check<=thr:\n", + " x[i,j] = 1\n", + " else:\n", + " x[i,j] = 2\n", + " x = np.array(x, dtype=int) \n", + " return x , t" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [], + "source": [ + "x, t = permutation(cor_OneSes1_caudate, group_label, 1000, .05)\n", + "halfx = np.tril(x)\n", + "t[halfx==2]=0 # using 2 as zero, so I can mask a only lower half" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.heatmap(t, cmap='coolwarm', \n", + " xticklabels = cond_list, yticklabels = cond_list,annot=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "celltoolbar": "Slideshow", + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/SPM_analysis.py b/task_based_analysis/SPM_analysis.py old mode 100644 new mode 100755 index 95cc1e2..b1e35a1 --- a/task_based_analysis/SPM_analysis.py +++ b/task_based_analysis/SPM_analysis.py @@ -93,124 +93,6 @@ def _bids2nipypeinfo(in_file, events_file, regressors_file, # Map field names to individual subject runs. session = '1' # choose session -infosource = pe.Node(util.IdentityInterface(fields=['subject_id' - ], - ), - name="infosource") -infosource.iterables = [('subject_id', subject_list)] - -# SelectFiles - to grab the data (alternativ to DataGrabber) -templates = {'func': '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-{subject_id}/ses-' + session + '/func/sub-{subject_id}_ses-' + session + '_task-Memory_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz', - 'mask': '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-{subject_id}/ses-' + session + '/func/sub-{subject_id}_ses-' + session + '_task-Memory_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz', - 'regressors': '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-{subject_id}/ses-' + session + '/func/sub-{subject_id}_ses-' + session + '_task-Memory_desc-confounds_regressors.tsv', - 'events': '/media/Data/PTSD_KPE/condition_files/sub-{subject_id}_ses-' + session + '.csv'} -selectfiles = pe.Node(nio.SelectFiles(templates, - base_directory=data_dir), - name="selectfiles") - -#%% - -# Extract motion parameters from regressors file -runinfo = pe.Node(util.Function( - input_names=['in_file', 'events_file', 'regressors_file', 'regressors_names'], - function=_bids2nipypeinfo, output_names=['info', 'realign_file']), - name='runinfo') - -# Set the column names to be used from the confounds file -runinfo.inputs.regressors_names = ['dvars', 'framewise_displacement'] + \ - ['a_comp_cor_%02d' % i for i in range(6)] + ['cosine%02d' % i for i in range(4)] -#%% - -cont1 = ['Trauma1>Sad1', 'T', ['trauma1', 'sad1'], [1, -1]] -cont2 = ['Trauma1>Relax1', 'T', ['trauma1', 'relax1'], [1, -1]] -cont3 = ['Sad1>Relax1', 'T', ['sad1', 'relax1'], [1, -1]] -cont4 = ['Sad1', 'T', ['sad1'], [1]] -cont5 = ['Trauma1>Trauma2_3', 'T', ['trauma1', 'trauma2','trauma3'], [1, -0.5, -0.5]] -cont6 = ['Trauma1', 'T', ['trauma1'], [1]] -contrasts = [cont1, cont2, cont3, cont4, cont5, cont6] -#%% -gunzip = MapNode(Gunzip(), name='gunzip', - iterfield=['in_file']) - -#%% Addinf simple denozining procedures (remove dummy scans, smoothing, art detection) -#extract = Node(fsl.ExtractROI(t_min=4, t_size=-1, output_type='NIFTI'), -# name="extract") - -smooth = Node(spm.Smooth(), name="smooth", fwhm = fwhm) -# Artifact Detection - determines outliers in functional images -#art = Node(ArtifactDetect(norm_threshold=2, -# zintensity_threshold=3, -# mask_type='spm_global', -# parameter_source='FSL', -# use_differences=[True, False], -# plot_type='svg'), -# name="art") -#%% - -################################################################ - - -modelspec = Node(interface=model.SpecifySPMModel(), name="modelspec") -modelspec.inputs.concatenate_runs = False -modelspec.inputs.input_units = 'secs' -modelspec.inputs.output_units = 'secs' -#modelspec.inputs.outlier_files = '/media/Data/R_A_PTSD/preproccess_data/sub-1063_ses-01_task-3_bold_outliers.txt' -modelspec.inputs.time_repetition = 1. # make sure its with a dot -modelspec.inputs.high_pass_filter_cutoff = 128. - -################################################ -#modelspec.inputs.subject_info = subjectinfo(subject_id) # run per subject - -level1design = pe.Node(interface=spm.Level1Design(), name="level1design") #, base_dir = '/media/Data/work') -level1design.inputs.timing_units = modelspec.inputs.output_units -level1design.inputs.interscan_interval = 1. -level1design.inputs.bases = {'hrf': {'derivs': [0, 0]}} -level1design.inputs.model_serial_correlations = 'AR(1)' - -####################################################################################################################### -# Initiation of a workflow -wfSPM = Workflow(name="l1spm", base_dir="/media/Drobo/work/KPE_SPM_ses-1") -wfSPM.connect([ - (infosource, selectfiles, [('subject_id', 'subject_id')]), - (selectfiles, runinfo, [('events','events_file'),('regressors','regressors_file')]), - (selectfiles, gunzip, [('func','in_file')]), - (gunzip, smooth, [('out_file','in_files')]), - (smooth, runinfo, [('smoothed_files','in_file')]), - (smooth, modelspec, [('smoothed_files', 'functional_runs')]), - (runinfo, modelspec, [('info', 'subject_info'), ('realign_file', 'realignment_parameters')]), - - ]) -wfSPM.connect([(modelspec, level1design, [("session_info", "session_info")])]) - - - - -##########################################################################3 - -level1estimate = pe.Node(interface=spm.EstimateModel(), name="level1estimate") -level1estimate.inputs.estimation_method = {'Classical': 1} - -contrastestimate = pe.Node( - interface=spm.EstimateContrast(), name="contrastestimate") -#contrastestimate.inputs.contrasts = contrasts -contrastestimate.overwrite = True -contrastestimate.config = {'execution': {'remove_unnecessary_outputs': False}} -contrastestimate.inputs.contrasts = contrasts - - -######################################################################## -#%% Connecting level1 estimation and contrasts -wfSPM.connect([ - (level1design, level1estimate, [('spm_mat_file','spm_mat_file')]), - (level1estimate, contrastestimate, - [('spm_mat_file', 'spm_mat_file'), ('beta_images', 'beta_images'), - ('residual_image', 'residual_image')]), - ]) - - - -############################################################### - #%% Adding data sink ######################################################################## # Datasink @@ -218,29 +100,6 @@ def _bids2nipypeinfo(in_file, events_file, regressors_file, name="datasink") -wfSPM.connect([ - # here we take only the contrast ad spm.mat files of each subject and put it in different folder. It is more convenient like that. - (contrastestimate, datasink, [('spm_mat_file', '1stLevel.@spm_mat'), - ('spmT_images', '1stLevel.@T'), - ('con_images', '1stLevel.@con'), - ('spmF_images', '1stLevel.@F'), - ('ess_images', '1stLevel.@ess'), - ]) - ]) - -#%% -wfSPM.write_graph("workflow_graph.dot", graph2use='colored', format='png', simple_form=True) -%matplotlib inline -from IPython.display import Image -Image(filename="/workflow_graph.png") -%matplotlib qt -Image(filename = '/media/Data/work/KPE_SPM/l1spm/graph_detailed.png') -wfSPM.write_graph(graph2use='flat') -#%% -#[] - -wfSPM.run('MultiProc', plugin_args={'n_procs': 5}) - #%% Gourp analysis - based on SPM - should condifer the fsl Randomize option (other script) # OneSampleTTestDesign - creates one sample T-Test Design onesamplettestdes = Node(spm.OneSampleTTestDesign(), @@ -276,10 +135,10 @@ def _bids2nipypeinfo(in_file, events_file, regressors_file, # SelectFiles - to grab the data (alternative to DataGrabber) -templates = {'cons': opj('/media/Data/work/KPE_SPM/Sink_ses-2/1stLevel/_sub*/', +templates = {'cons': opj('/media/Data/KPE_results/work/1stLevel/_sub*/', '{contrast_id}.nii')} selectfiles = Node(SelectFiles(templates, - base_directory='/media/Data/work', + sort_filelist=True), name="selectfiles") diff --git a/task_based_analysis/XGBoost-Betas.ipynb b/task_based_analysis/XGBoost-Betas.ipynb new file mode 100644 index 0000000..bac7780 --- /dev/null +++ b/task_based_analysis/XGBoost-Betas.ipynb @@ -0,0 +1,989 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "# Using machine learning XGboost classifier to look for different pattern between Ketamin and Midazolam groups\n", + "- Running on the Beta of trauma1_0 instead of contrast between trauma and sad (more similar to MVPA)" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [], + "source": [ + "# import relevant packages\n", + "import glob\n", + "import numpy as np\n", + "import scipy\n", + "import nilearn\n", + "import nilearn.plotting\n", + "import nilearn.input_data\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "from xgboost import XGBClassifier\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import accuracy_score" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## No apperant contribution to before/after treatment in general. \n", + "- Lets look at group differences in ROIs $\\rightarrow$\n", + " * Amygdala\n", + " * vmPFC\n", + " * Hippocampus\n", + " * Striatum\n", + "- We compare pattern of ROI activation in the trauma > relax contrast on the 2nd day" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Amygdala as mask\n", + "mask_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=21\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "\n", + "\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " smoothing_fwhm=6, verbose=5).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1]" + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# compare between groups\n", + "import pandas as pd\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "medication_cond\n", + "\n", + "condition_label = np.array(medication_cond.med_cond)\n", + "condition_label = list(map(int, condition_label))\n", + "condition_label" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [], + "source": [ + "# function to find ev number (lookin in run.fsf file)\n", + "def findEV(txtFile, condition):\n", + " # takes the txtFile and the specific condition\n", + " with open(txtFile) as f:\n", + " datafile = f.readlines()\n", + " lines = []\n", + " for line in datafile:\n", + " if condition in line:\n", + " # found = True # Not necessary\n", + " #print(line)\n", + " lines.append(line)\n", + "\n", + " return lines[0].split('evtitle')[1].split(')')[0]\n", + "\n", + "def getBetas(beta_list, condition, ses):\n", + " betaTemplate = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses{ses}_Nosmooth/modelfit_ses_{ses}/_subject_id_{subject_id}/modelestimate/mapflow/_modelestimate0/results/pe{betaNum}.nii.gz'\n", + " beta_files = []\n", + " for beta in beta_list:\n", + " # get subject number\n", + " sub = beta.split('id_')[1].split('/')[0]\n", + " # get beta number\n", + " number = findEV(beta, condition)\n", + " # find beta file\n", + " betaFile = betaTemplate.format(ses=ses, subject_id = sub, betaNum = number)\n", + " # add it to list\n", + " beta_files.append(betaFile)\n", + " beta_files.sort()\n", + " return beta_files" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1322/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1387/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1339/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1464/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1315/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1223/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1561/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1499/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1307/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1351/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_008/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1390/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1263/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1369/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1364/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1293/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1480/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1253/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1343/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1356/level1design/run0.fsf',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1403/level1design/run0.fsf']" + ] + }, + "execution_count": 75, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# get run files - for specific session\n", + "ses= '2'\n", + "beta_list = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses%s_Nosmooth/modelfit_ses_%s/_subject_id_*/level1design/run0.fsf' %(ses,ses))\n", + "beta_list\n" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['relax1_0', 'relax1_1', 'relax1_2', 'relax1_3', 'relax2_0',\n", + " 'relax2_1', 'relax2_2', 'relax2_3', 'relax3_0', 'relax3_1',\n", + " 'relax3_2', 'relax3_3', 'sad1_0', 'sad1_1', 'sad1_2', 'sad1_3',\n", + " 'sad2_0', 'sad2_1', 'sad2_2', 'sad2_3', 'sad3_0', 'sad3_1',\n", + " 'sad3_2', 'sad3_3', 'trauma1_0', 'trauma1_1', 'trauma1_2',\n", + " 'trauma1_3', 'trauma2_0', 'trauma2_1', 'trauma2_2', 'trauma2_3',\n", + " 'trauma3_0', 'trauma3_1', 'trauma3_2', 'trauma3_3'], dtype=object)" + ] + }, + "execution_count": 76, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# get condition list\n", + "events_file = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/sub-1464_ses-1_30sec_window.csv'\n", + "cond = pd.read_csv(events_file, sep='\\t')\n", + "cond_list = np.unique(cond.trial_type_30)\n", + "cond_list" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_008/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1223/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1253/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1263/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1293/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1307/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1315/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1322/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1339/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1343/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1351/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1356/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1364/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1369/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1387/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1390/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1403/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1464/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1480/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1499/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz', '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1561/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz']\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_008/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1223/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1253/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1263/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1293/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1307/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1315/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1322/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1339/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1343/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1351/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1356/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1364/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1369/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1387/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1390/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] 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/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1464/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1480/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1499/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2_Nosmooth/modelfit_ses_2/_subject_id_1561/modelestimate/mapflow/_modelestimate0/results/pe31.nii.gz\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "data": { + "text/plain": [ + "(21, 846)" + ] + }, + "execution_count": 77, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "beta_files = getBetas(beta_list, 'trauma1_0', ses='2')\n", + "print(beta_files)\n", + "allGroups = []\n", + "for func in beta_files:\n", + " print(f'Running {func}')\n", + " beta = masker.transform(func)\n", + " allGroups.append(beta)\n", + "\n", + "allArr = np.array(allGroups)\n", + "allArr_reshape= np.array(allArr).reshape(allArr.shape[0], allArr.shape[2])\n", + "allArr_reshape.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": {}, + "outputs": [], + "source": [ + "X = allArr_reshape" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "#from sklearn.model_selection import StratifiedKFold\n", + "from sklearn.svm import LinearSVC\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.model_selection import StratifiedKFold\n", + "from sklearn import svm\n", + "model = XGBClassifier(n_jobs=5, \n", + " verbose = 9, random_state=None)\n", + "\n", + "## Here we use stratified K-fold with shuffling to generate different shuffling of leave one subject out\n", + "cv = StratifiedKFold(n_splits=10, shuffle=True) # running for each subject\n" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [], + "source": [ + "scores = cross_val_score(model,\n", + " X,\n", + " y=condition_label,\n", + " cv=cv,\n", + " groups=condition_label,\n", + " scoring= \"accuracy\",\n", + " n_jobs=1, # set number of CPUs\n", + " #verbose = 5 # set some details of the activity \n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.66666667, 0. , 0. , 1. , 0.5 ,\n", + " 0.5 , 0. , 1. , 0. , 1. ])" + ] + }, + "execution_count": 81, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "scores" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## Use shuffle split to randomize and run the XGboost N times\n", + "- This will create a distribution of estimation level \n", + "- We can then better estimate how really its more accurate than chance\n" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running 1 iteration\n", + " Running 2 iteration\n", + " Running 3 iteration\n", + " Running 4 iteration\n", + " Running 5 iteration\n", + " Running 6 iteration\n", + " Running 7 iteration\n", + " Running 8 iteration\n", + " Running 9 iteration\n", + " Running 10 iteration\n", + " Running 11 iteration\n", + " Running 12 iteration\n", + " Running 13 iteration\n", + " Running 14 iteration\n", + " Running 15 iteration\n", + " Running 16 iteration\n", + " Running 17 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iteration\n", + " Running 87 iteration\n", + " Running 88 iteration\n", + " Running 89 iteration\n", + " Running 90 iteration\n", + " Running 91 iteration\n", + " Running 92 iteration\n", + " Running 93 iteration\n", + " Running 94 iteration\n", + " Running 95 iteration\n", + " Running 96 iteration\n", + " Running 97 iteration\n", + " Running 98 iteration\n", + " Running 99 iteration\n", + " Running 100 iteration\n" + ] + } + ], + "source": [ + "n_iter = 100\n", + "rand_score = []\n", + "for i in range(n_iter):\n", + " print(f' Running {i+1} iteration')\n", + " mean_scores = []\n", + " scores = cross_val_score(model,\n", + " X,\n", + " y=condition_label,\n", + " cv=cv,\n", + " groups=condition_label,\n", + " scoring= \"accuracy\",\n", + " n_jobs=10, # set number of CPUs\n", + " #verbose = 5 # set some details of the activity \n", + " )\n", + " mean_scores.append(scores.mean())\n", + " rand_score.append(mean_scores)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "### Plotting area under ROC curve ditribution and printing average and standard deviation of the distribution" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Area under curve: 0.50 (+/- 0.10)\n", + "90% CI is [0.41666667 0.58333333]\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 83, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "rand_score = np.array(rand_score)\n", + "print(\"Area under curve: %0.2f (+/- %0.2f)\" % (np.mean(rand_score), np.std(rand_score) * 2))\n", + "print(f'90% CI is {np.quantile(rand_score, [0.05, 0.95])}')\n", + "sns.distplot(rand_score)" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=8)]: Using backend LokyBackend with 8 concurrent workers.\n", + "[Parallel(n_jobs=8)]: Done 2 tasks | elapsed: 2.4s\n", + "[Parallel(n_jobs=8)]: Done 56 tasks | elapsed: 18.2s\n", + "[Parallel(n_jobs=8)]: Done 146 tasks | elapsed: 43.6s\n", + "[Parallel(n_jobs=8)]: Done 272 tasks | elapsed: 1.3min\n", + "[Parallel(n_jobs=8)]: Done 434 tasks | elapsed: 2.2min\n", + "[Parallel(n_jobs=8)]: Done 632 tasks | elapsed: 3.1min\n", + "[Parallel(n_jobs=8)]: Done 866 tasks | elapsed: 4.3min\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Classification score 0.3 (pvalue : 0.8291708291708292)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=8)]: Done 1000 out of 1000 | elapsed: 4.9min finished\n" + ] + } + ], + "source": [ + "## use sklearn permutation test\n", + "from sklearn.model_selection import permutation_test_score\n", + "score, permutation_scores, pvalue = permutation_test_score(\n", + " model, X, condition_label, scoring=\"roc_auc\", cv=cv, n_permutations=1000, n_jobs=8, verbose=5)\n", + "\n", + "print(\"Classification score %s (pvalue : %s)\" % (score, pvalue))" + ] + }, + { + "cell_type": "code", + "execution_count": 231, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(21, 3846)" + ] + }, + "execution_count": 231, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "X.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 219, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=4\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None, standardize=False, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Lets look at the hippocampus" + ] + }, + { + "cell_type": "code", + "execution_count": 210, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=11\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None, standardize=False, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Striatum" + ] + }, + { + "cell_type": "code", + "execution_count": 204, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/KPE_ROI/binConjunc_PvNxDECxRECxMONxPRI_striatum.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=0.001\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None, standardize=False, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# An unrelated region (Primary motor cortex?) V1?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "celltoolbar": "Slideshow", + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/XGBoost.ipynb b/task_based_analysis/XGBoost.ipynb index 8708c88..0db1660 100644 --- a/task_based_analysis/XGBoost.ipynb +++ b/task_based_analysis/XGBoost.ipynb @@ -13,7 +13,7 @@ }, { "cell_type": "code", - "execution_count": 187, + "execution_count": 15, "metadata": { "slideshow": { "slide_type": "skip" @@ -54,7 +54,7 @@ }, { "cell_type": "code", - "execution_count": 193, + "execution_count": 16, "metadata": { "slideshow": { "slide_type": "slide" @@ -63,7 +63,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -81,12 +81,12 @@ "\n", "\n", "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", - " sessions=None, smoothing_fwhm=2, standardize=False, detrend=False, verbose=5)" + " sessions=None, smoothing_fwhm=1, standardize=False, detrend=False, verbose=5)" ] }, { "cell_type": "code", - "execution_count": 194, + "execution_count": 17, "metadata": { "slideshow": { "slide_type": "skip" @@ -98,6 +98,7 @@ "import pandas as pd\n", "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", "\n", + "\n", "ketamine_list = list(medication_cond['scr_id'][medication_cond['med_cond']==1])\n", "ket_list = []\n", "for subject in ketamine_list:\n", @@ -117,7 +118,52 @@ }, { "cell_type": "code", - "execution_count": 195, + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['1253',\n", + " '1263',\n", + " '1351',\n", + " '1356',\n", + " '1364',\n", + " '1369',\n", + " '1390',\n", + " '1403',\n", + " '1468',\n", + " '1480',\n", + " '1561',\n", + " '1578']" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mid_list\n", + "## only for 3rd session\n", + "#ket_list.remove('1315')" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "mid_list.remove('1578')\n", + "# only for 3rd session\n", + "#mid_list.remove('1253')\n", + "#mid_list.remove('1480')" + ] + }, + { + "cell_type": "code", + "execution_count": 26, "metadata": { "slideshow": { "slide_type": "skip" @@ -125,13 +171,14 @@ }, "outputs": [], "source": [ - "ket_func = ['/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_%s/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz'% (sub) for sub in ket_list]\n", - "mid_func = ['/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_%s/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz' % (sub) for sub in mid_list]" + "ses = '2'\n", + "ket_func = ['/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses%s/modelfit/_subject_id_%s/modelestimate/results/cope2.nii.gz'% (ses,sub) for sub in ket_list]\n", + "mid_func = ['/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses%s/modelfit/_subject_id_%s/modelestimate/results/cope2.nii.gz' % (ses, sub) for sub in mid_list]" ] }, { "cell_type": "code", - "execution_count": 124, + "execution_count": 27, "metadata": { "slideshow": { "slide_type": "skip" @@ -139,12 +186,13 @@ }, "outputs": [], "source": [ + "#ketamine_list.remove('KPE1315')\n", "#mid_list.remove('1480')" ] }, { "cell_type": "code", - "execution_count": 196, + "execution_count": 28, "metadata": { "slideshow": { "slide_type": "skip" @@ -155,7 +203,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_008/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_008/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -168,7 +216,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1223/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1223/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -181,7 +229,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1293/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1293/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -194,7 +242,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1307/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1307/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -207,7 +255,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1315/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1315/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -220,7 +268,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1322/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1322/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -233,7 +281,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1339/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1339/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -246,7 +294,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1343/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1343/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -259,7 +307,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1387/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1387/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -272,7 +320,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1464/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1419/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -285,7 +333,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1499/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1464/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -298,7 +346,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1253/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1499/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -307,17 +355,43 @@ " [ 0. , 2. , 0. , -132.5],\n", " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", - "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n" + "[NiftiMasker.transform_single_imgs] Resampling images\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1253/modelestimate/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1263/modelestimate/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1263/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1351/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -330,7 +404,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1351/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1356/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -343,7 +417,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1356/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1364/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -356,7 +430,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1364/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1369/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -369,7 +443,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1369/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1390/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -382,7 +456,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1390/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1403/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -395,7 +469,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1403/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1468/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -408,7 +482,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1468/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1480/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -421,7 +495,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1480/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1561/modelestimate/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -439,10 +513,10 @@ { "data": { "text/plain": [ - "(21, 932)" + "(23, 559)" ] }, - "execution_count": 196, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } @@ -483,7 +557,80 @@ }, { "cell_type": "code", - "execution_count": 199, + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "## Check correlation between sessions\n", + "ses2 = np.array(X)" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(21, 846)" + ] + }, + "execution_count": 83, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [], + "source": [ + "cor12= []\n", + "for i in range(ses1.shape[0]):\n", + " corr = scipy.stats.pearsonr(ses1[i], ses2[i])\n", + " cor12.append(corr[0])\n", + "corDF = pd.DataFrame({'condition':condition_label, 'cor': cor12})" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 102, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(x='condition', y='cor', data=corDF)" + ] + }, + { + "cell_type": "code", + "execution_count": 89, "metadata": { "slideshow": { "slide_type": "slide" @@ -496,11 +643,48 @@ "from sklearn.model_selection import cross_val_score\n", "from sklearn.model_selection import StratifiedKFold\n", "from sklearn import svm\n", - "model = XGBClassifier(n_jobs=8, \n", + "model = XGBClassifier(n_jobs=7, \n", " verbose = 9, random_state=None)\n", "\n", "## Here we use stratified K-fold with shuffling to generate different shuffling of leave one subject out\n", - "cv = StratifiedKFold(n_splits=5, shuffle=True) # running for each subject\n" + "cv = StratifiedKFold(n_splits=11, shuffle=True) # running for each subject\n" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": {}, + "outputs": [], + "source": [ + "scores = cross_val_score(model,\n", + " X,\n", + " y=condition_label,\n", + " cv=cv,\n", + " groups=condition_label,\n", + " scoring= \"roc_auc\",\n", + " n_jobs=1, # set number of CPUs\n", + " #verbose = 5 # set some details of the activity \n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 1., 0., 1., 0., 0., 1., 0., 0., 0., 0.])" + ] + }, + "execution_count": 91, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "scores" ] }, { @@ -518,7 +702,7 @@ }, { "cell_type": "code", - "execution_count": 200, + "execution_count": 92, "metadata": { "scrolled": true, "slideshow": { @@ -629,5127 +813,1224 @@ " Running 97 iteration\n", " Running 98 iteration\n", " Running 99 iteration\n", - " Running 100 iteration\n", - " Running 101 iteration\n", - " Running 102 iteration\n", - " Running 103 iteration\n", - " Running 104 iteration\n", - " Running 105 iteration\n", - " Running 106 iteration\n", - " Running 107 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groups=condition_label,\n", + " scoring= \"accuracy\",\n", + " n_jobs=1, # set number of CPUs\n", + " #verbose = 5 # set some details of the activity \n", + " )\n", + " mean_scores.append(scores.mean())\n", + " rand_score.append(mean_scores)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "### Plotting area under ROC curve ditribution and printing average and standard deviation of the distribution" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Area under curve: 0.42 (+/- 0.15)\n", + "90% CI is [0.31515152 0.54621212]\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 93, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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- } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Area under curve: 0.73 (+/- 0.19)\n", - "90% CI is [0.55791667 0.86666667]\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 201, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "rand_score = np.array(rand_score)\n", - "print(\"Area under curve: %0.2f (+/- %0.2f)\" % (np.mean(rand_score), np.std(rand_score) * 2))\n", - "print(f'90% CI is {np.quantile(rand_score, [0.05, 0.95])}')\n", - "sns.distplot(rand_score)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, - "source": [ - "## Now we will do similar thing - just shuffling the condition label (Y) so we basically randomizing the lables\n", - "This should generate a chance level prediction" - ] - }, - { - "cell_type": "code", - "execution_count": 449, - "metadata": { - "slideshow": { - "slide_type": "subslide" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Running the 1 iteration\n", - "[1 0 0 1 0 0 1 1 1 1 1 1 1 1 0 1 0 0 0 0 0]\n", - "Running the 2 iteration\n", - "[0 1 0 1 1 0 1 1 0 1 0 1 1 0 0 0 0 1 1 1 0]\n", - "Running the 3 iteration\n", - "[1 1 0 1 1 1 0 0 0 0 1 1 1 0 1 1 0 1 0 0 0]\n", - "Running the 4 iteration\n", - "[1 0 1 0 0 1 0 1 1 1 0 0 0 1 1 0 1 1 0 1 0]\n", - "Running the 5 iteration\n", - "[0 1 1 0 0 1 1 1 0 1 1 0 0 0 0 0 0 1 1 1 1]\n", - "Running the 6 iteration\n", - "[1 1 1 0 1 0 1 1 0 0 0 0 1 0 1 1 1 0 0 0 1]\n", - "Running the 7 iteration\n", - "[0 1 1 1 0 1 0 1 0 0 0 0 0 1 1 0 1 1 1 0 1]\n", - "Running the 8 iteration\n", - "[1 0 0 1 0 0 0 1 0 1 1 1 1 1 1 1 0 0 1 0 0]\n", - "Running the 9 iteration\n", - "[1 1 0 1 0 0 1 0 0 1 1 1 1 0 0 1 1 0 1 0 0]\n", - "Running the 10 iteration\n", - "[1 1 1 1 0 1 0 0 0 1 0 1 0 1 0 0 1 1 0 0 1]\n", - "Running the 11 iteration\n", - "[1 0 0 1 1 0 0 0 1 0 0 1 1 1 1 1 1 0 0 1 0]\n", - "Running the 12 iteration\n", - "[0 1 0 0 0 1 1 0 0 0 1 0 1 1 1 0 1 0 1 1 1]\n", - "Running the 13 iteration\n", - "[1 1 1 1 0 1 1 1 1 0 1 1 0 0 0 0 0 0 1 0 0]\n", - "Running the 14 iteration\n", - "[1 1 1 0 1 1 0 0 0 0 0 1 0 0 0 1 0 1 1 1 1]\n", - "Running the 15 iteration\n", - "[0 1 1 1 0 1 1 0 0 0 0 0 1 0 1 1 0 0 1 1 1]\n", - "Running the 16 iteration\n", - "[1 0 0 0 0 1 1 1 1 0 1 0 0 1 1 0 0 1 1 1 0]\n", - "Running the 17 iteration\n", - "[0 1 0 0 0 1 1 1 1 0 1 1 1 0 1 0 0 1 1 0 0]\n", - "Running the 18 iteration\n", - "[0 1 1 1 1 0 1 1 0 0 1 1 0 1 0 0 0 0 0 1 1]\n", - "Running the 19 iteration\n", - "[1 1 0 0 0 1 1 1 1 0 1 0 1 1 1 0 0 1 0 0 0]\n", - "Running the 20 iteration\n", - "[1 0 0 0 0 1 0 1 1 0 1 1 0 1 0 1 0 1 1 0 1]\n", - "Running the 21 iteration\n", - "[0 1 0 0 0 1 0 1 1 0 1 1 0 1 0 1 1 0 0 1 1]\n", - "Running the 22 iteration\n", - "[0 1 0 0 1 1 0 1 0 1 1 1 1 1 1 1 0 0 0 0 0]\n", - "Running the 23 iteration\n", - "[1 1 1 0 1 0 0 1 1 0 0 0 1 1 1 0 0 0 0 1 1]\n", - "Running the 24 iteration\n", - "[0 0 0 0 0 0 0 1 1 0 1 1 1 1 1 0 0 1 1 1 1]\n", - "Running the 25 iteration\n", - "[1 1 1 0 0 0 0 1 1 1 0 1 0 0 1 0 1 1 0 0 1]\n", - "Running the 26 iteration\n", - "[1 1 0 1 0 0 0 0 0 1 0 1 1 1 0 1 0 1 1 0 1]\n", - "Running the 27 iteration\n", - "[1 0 0 1 1 0 1 1 1 1 0 0 0 1 1 0 1 1 0 0 0]\n", - "Running the 28 iteration\n", - "[0 1 1 1 0 1 0 1 0 0 0 1 1 0 1 0 0 1 1 0 1]\n", - "Running the 29 iteration\n", - "[1 1 0 1 1 0 0 1 0 0 0 1 1 1 0 0 0 0 1 1 1]\n", - "Running the 30 iteration\n", - "[1 0 0 1 1 1 0 1 1 1 1 0 0 0 1 0 1 1 0 0 0]\n", - "Running the 31 iteration\n", - "[0 1 1 1 0 0 1 1 0 1 0 0 1 0 1 0 1 1 1 0 0]\n", - "Running the 32 iteration\n", - "[0 0 1 1 1 1 1 0 0 0 0 1 1 1 0 0 1 1 1 0 0]\n", - "Running the 33 iteration\n", - "[1 1 1 1 1 1 0 1 0 0 0 0 1 1 0 1 0 0 0 1 0]\n", - "Running the 34 iteration\n", - "[1 0 1 0 0 0 0 0 1 0 0 1 1 1 1 1 1 1 1 0 0]\n", - "Running the 35 iteration\n", - "[0 1 1 0 1 0 1 1 0 1 1 1 1 0 1 1 0 0 0 0 0]\n", - "Running the 36 iteration\n", - "[0 1 0 1 0 1 1 1 1 0 1 1 0 0 1 0 1 0 1 0 0]\n", - "Running the 37 iteration\n", - "[0 1 1 0 1 0 1 0 1 1 1 0 1 0 0 1 0 0 0 1 1]\n", - "Running the 38 iteration\n", - "[0 0 0 0 1 1 1 1 1 1 1 0 1 0 1 0 0 1 0 0 1]\n", - "Running the 39 iteration\n", - "[0 1 1 1 1 0 0 1 0 1 1 0 0 1 0 0 1 0 1 1 0]\n", - "Running the 40 iteration\n", - "[0 1 0 1 0 1 1 0 0 0 0 1 1 1 1 0 1 0 1 1 0]\n", - "Running the 41 iteration\n", - "[0 1 0 0 1 0 1 1 1 1 0 1 0 1 1 0 0 0 1 0 1]\n", - "Running the 42 iteration\n", - "[0 1 1 1 0 0 0 0 0 1 1 1 1 1 1 0 0 1 0 0 1]\n", - "Running the 43 iteration\n", - "[1 0 0 1 1 0 1 0 0 1 1 0 1 0 1 0 1 1 1 0 0]\n", - "Running the 44 iteration\n", - "[1 1 1 1 0 0 0 0 1 0 0 1 1 1 0 1 1 0 1 0 0]\n", - "Running the 45 iteration\n", - "[1 1 1 0 0 1 0 0 1 1 0 0 1 1 1 0 0 0 0 1 1]\n", - "Running the 46 iteration\n", - "[0 1 0 1 0 1 1 0 1 0 1 1 0 1 1 0 0 1 1 0 0]\n", - "Running the 47 iteration\n", - "[0 0 0 1 0 1 1 0 0 1 1 0 0 0 1 0 1 1 1 1 1]\n", - "Running the 48 iteration\n", - "[0 1 0 0 1 0 0 0 1 0 1 0 1 1 1 1 1 1 0 0 1]\n", - "Running the 49 iteration\n", - "[1 1 1 1 1 0 0 1 0 1 1 0 0 0 0 0 0 1 1 0 1]\n", - "Running the 50 iteration\n", - "[1 0 1 1 1 0 1 0 1 1 0 0 1 1 0 1 0 1 0 0 0]\n", - "Running the 51 iteration\n", - "[1 0 1 0 0 1 0 1 0 1 0 1 1 0 1 1 1 0 0 0 1]\n", - "Running the 52 iteration\n", - "[1 0 0 0 0 1 0 0 1 1 1 0 1 1 1 1 1 0 0 1 0]\n", - "Running the 53 iteration\n", - "[0 0 1 0 1 0 0 1 1 0 1 0 1 0 1 1 0 1 1 1 0]\n", - "Running the 54 iteration\n", - "[1 1 1 1 0 1 1 0 1 0 0 1 0 0 0 0 1 1 0 1 0]\n", - "Running the 55 iteration\n", - "[1 0 1 0 1 1 0 1 1 1 0 0 0 0 0 0 1 0 1 1 1]\n", - "Running the 56 iteration\n", - "[0 0 0 0 0 1 1 1 0 1 1 1 1 1 0 0 0 1 1 1 0]\n", - "Running the 57 iteration\n", - "[1 0 0 1 1 0 0 1 0 1 0 1 1 0 0 1 1 1 0 0 1]\n", - "Running the 58 iteration\n", - "[1 0 0 1 0 1 1 1 0 1 0 1 1 0 0 1 0 1 1 0 0]\n", - "Running the 59 iteration\n", - "[0 1 1 1 0 0 0 1 1 1 0 1 1 1 0 0 0 0 1 0 1]\n", - "Running the 60 iteration\n", - "[0 1 0 0 1 0 1 1 1 0 0 1 0 1 1 1 0 1 1 0 0]\n", - "Running the 61 iteration\n", - "[1 1 1 0 0 1 1 1 0 1 1 0 0 0 0 1 1 0 0 0 1]\n", - "Running the 62 iteration\n", - "[1 1 0 0 0 0 1 0 0 0 0 1 1 1 0 1 1 1 1 0 1]\n", - "Running the 63 iteration\n", - "[0 1 0 1 0 0 0 1 0 1 0 1 1 0 1 0 1 1 1 0 1]\n", - "Running the 64 iteration\n", - "[1 1 0 0 0 1 1 0 0 0 1 0 1 0 0 1 1 0 1 1 1]\n", - "Running the 65 iteration\n", - "[0 1 0 0 1 1 1 0 0 0 0 1 0 0 1 1 0 1 1 1 1]\n", - "Running the 66 iteration\n", - "[0 1 0 0 1 0 1 1 1 0 0 0 0 1 1 1 1 0 0 1 1]\n", - "Running the 67 iteration\n", - "[1 1 1 0 1 1 1 0 0 1 0 1 0 0 0 0 1 1 0 1 0]\n", - "Running the 68 iteration\n", - "[1 0 0 0 0 1 0 1 0 1 0 1 1 0 0 1 1 0 1 1 1]\n", - "Running the 69 iteration\n", - "[1 1 1 0 0 1 0 1 0 0 1 1 1 1 0 0 1 1 0 0 0]\n", - "Running the 70 iteration\n", - "[1 1 1 0 1 0 0 0 0 0 0 0 1 0 1 1 1 1 1 0 1]\n", - "Running the 71 iteration\n", - "[1 0 0 0 1 0 1 0 1 0 1 0 1 0 0 1 0 1 1 1 1]\n", - "Running the 72 iteration\n", - "[0 0 0 0 1 0 1 0 0 0 1 1 1 1 0 1 1 1 0 1 1]\n", - "Running the 73 iteration\n", - "[1 0 1 0 1 0 1 1 0 0 1 0 1 0 1 1 1 0 0 0 1]\n", - "Running the 74 iteration\n", - "[0 1 1 1 1 0 1 0 1 1 0 0 0 1 1 0 0 0 1 1 0]\n", - "Running the 75 iteration\n", - "[0 1 0 0 1 0 1 0 1 0 1 1 1 0 1 1 0 0 1 1 0]\n", - "Running the 76 iteration\n", - "[1 1 0 0 0 1 0 1 0 0 1 1 0 0 1 0 1 1 0 1 1]\n", - "Running the 77 iteration\n", - "[0 0 1 1 0 0 1 0 0 1 1 0 1 1 0 1 1 0 0 1 1]\n", - "Running the 78 iteration\n", - "[1 0 0 0 1 1 1 0 0 1 0 0 1 0 1 1 1 1 1 0 0]\n", - "Running the 79 iteration\n", - "[1 0 0 1 1 0 0 0 1 1 1 1 0 1 1 1 0 0 0 0 1]\n", - "Running the 80 iteration\n", - "[0 0 1 1 1 1 0 1 0 0 1 1 1 0 1 1 0 1 0 0 0]\n", - "Running the 81 iteration\n", - "[1 1 1 0 0 1 0 0 0 1 1 0 1 1 0 1 1 1 0 0 0]\n", - "Running the 82 iteration\n", - "[1 1 0 1 0 1 0 1 0 0 1 1 0 0 0 0 1 1 1 1 0]\n", - "Running the 83 iteration\n", - "[1 0 1 1 1 1 1 1 1 0 0 0 1 0 1 1 0 0 0 0 0]\n", - "Running the 84 iteration\n", - "[1 0 0 1 0 1 1 0 1 1 0 1 1 1 0 0 0 1 1 0 0]\n", - "Running the 85 iteration\n", - "[1 1 1 1 1 0 0 0 0 0 1 0 1 0 1 0 1 0 1 0 1]\n", - "Running the 86 iteration\n", - "[0 1 1 1 0 1 0 0 1 0 0 0 1 1 0 1 1 0 1 0 1]\n", - "Running the 87 iteration\n", - "[0 0 1 0 0 1 1 0 0 0 1 0 0 1 1 1 1 1 0 1 1]\n", - "Running the 88 iteration\n", - "[0 0 0 0 1 1 1 0 1 1 1 0 0 1 0 1 1 1 0 0 1]\n", - "Running the 89 iteration\n", - "[1 1 0 0 1 1 0 1 1 1 0 0 1 1 0 0 0 1 0 1 0]\n", - "Running the 90 iteration\n", - "[1 0 1 1 1 0 1 0 0 1 0 1 0 0 0 0 1 0 1 1 1]\n", - "Running the 91 iteration\n", - "[0 0 0 0 1 1 1 0 1 0 0 1 0 1 1 0 1 1 0 1 1]\n", - "Running the 92 iteration\n", - "[0 0 1 1 0 1 0 1 1 1 0 0 0 1 1 0 1 0 1 0 1]\n", - "Running the 93 iteration\n", - "[1 1 1 1 0 0 1 1 0 0 0 1 0 1 0 0 0 0 1 1 1]\n", - "Running the 94 iteration\n", - "[1 1 0 0 0 1 0 0 1 1 0 1 0 0 1 0 1 1 1 0 1]\n", - "Running the 95 iteration\n", - "[0 1 0 1 1 1 0 1 1 1 0 1 1 0 1 0 0 0 0 1 0]\n", - "Running the 96 iteration\n", - "[0 0 1 0 1 1 1 0 1 1 0 1 0 1 0 0 0 1 1 0 1]\n", - "Running the 97 iteration\n", - "[0 1 0 1 1 0 0 1 0 0 0 1 0 1 1 1 0 1 0 1 1]\n", - "Running the 98 iteration\n", - "[0 1 0 0 0 1 0 0 1 0 1 1 1 1 0 1 0 1 1 1 0]\n", - "Running the 99 iteration\n", - "[0 1 1 0 0 0 0 1 0 1 0 1 1 1 0 0 0 1 1 1 1]\n", - "Running the 100 iteration\n", - "[0 0 0 1 1 1 1 1 0 0 1 0 1 0 1 0 1 0 1 1 0]\n", - "Running the 101 iteration\n", - "[0 1 0 1 1 1 0 1 0 1 1 0 0 1 0 1 1 0 0 1 0]\n", - "Running the 102 iteration\n", - "[1 0 1 0 1 0 1 1 1 1 0 1 0 0 1 0 0 1 0 0 1]\n", - "Running the 103 iteration\n", - "[0 1 1 0 0 0 1 1 1 1 1 0 0 0 1 0 1 0 1 1 0]\n", - "Running the 104 iteration\n", - "[1 1 0 1 0 1 0 1 0 0 1 1 0 0 1 1 0 0 0 1 1]\n", - "Running the 105 iteration\n", - "[1 1 0 0 1 0 1 0 1 1 1 1 1 1 0 0 0 0 0 0 1]\n", - "Running the 106 iteration\n", - "[0 1 1 1 0 0 1 1 1 1 1 1 0 0 0 0 0 1 0 1 0]\n", - "Running the 107 iteration\n", - "[1 1 0 0 1 0 0 1 1 1 0 1 0 1 0 0 0 0 1 1 1]\n", - "Running the 108 iteration\n", - "[1 0 0 0 0 1 1 0 0 1 1 0 1 1 0 1 0 1 0 1 1]\n", - "Running the 109 iteration\n", - "[1 1 1 1 1 1 1 0 0 1 0 0 1 0 0 0 0 0 1 0 1]\n", - "Running the 110 iteration\n", - "[0 0 0 0 1 1 1 0 1 1 0 0 1 1 1 0 1 0 1 0 1]\n", - "Running the 111 iteration\n", - "[1 0 1 0 1 0 0 0 1 1 1 0 1 1 0 0 0 0 1 1 1]\n", - "Running the 112 iteration\n", - "[0 1 1 1 0 1 0 1 0 1 1 0 1 0 0 1 0 0 1 0 1]\n", - "Running the 113 iteration\n", - "[0 1 1 0 1 0 1 0 0 1 1 1 0 1 0 0 1 1 0 0 1]\n", - "Running the 114 iteration\n", - "[1 0 0 1 0 0 1 1 1 0 1 1 0 1 0 0 1 1 0 1 0]\n", - "Running the 115 iteration\n", - "[0 1 1 0 0 0 1 1 1 0 0 0 0 1 1 1 0 1 1 0 1]\n", - "Running the 116 iteration\n", - "[1 0 1 1 0 1 0 1 1 0 0 1 0 0 1 0 1 0 1 0 1]\n", - "Running the 117 iteration\n", - "[1 0 0 1 0 1 1 1 0 0 0 0 1 1 0 1 1 1 0 0 1]\n", - "Running the 118 iteration\n", - "[1 0 0 0 1 0 0 1 1 0 1 0 1 0 1 1 0 1 0 1 1]\n", - "Running the 119 iteration\n", - "[1 1 1 1 1 1 1 0 0 0 0 0 0 0 1 1 0 0 1 1 0]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Running the 120 iteration\n", - "[1 0 1 1 0 1 1 1 0 0 0 1 1 1 1 0 0 0 0 1 0]\n", - "Running the 121 iteration\n", - "[1 1 0 0 1 0 1 1 0 1 1 1 0 0 0 0 1 0 1 1 0]\n", - "Running the 122 iteration\n", - "[1 0 1 0 1 0 1 0 1 0 1 1 0 0 1 1 0 0 1 1 0]\n", - "Running the 123 iteration\n", - "[0 1 0 1 1 0 0 0 0 1 1 0 1 0 1 1 0 1 0 1 1]\n", - "Running the 124 iteration\n", - "[0 1 1 0 0 0 1 0 1 0 1 1 1 1 0 1 0 0 0 1 1]\n", - "Running the 125 iteration\n", - "[1 0 1 1 0 1 0 0 0 1 0 1 1 0 0 0 1 0 1 1 1]\n", - "Running the 126 iteration\n", - "[1 0 0 1 0 0 0 0 0 0 1 1 1 0 1 0 1 1 1 1 1]\n", - "Running the 127 iteration\n", - "[0 1 1 1 1 0 0 1 1 0 0 0 1 0 0 1 1 1 0 1 0]\n", - "Running the 128 iteration\n", - "[0 1 1 0 0 1 0 1 0 1 1 1 1 0 1 1 0 0 1 0 0]\n", - "Running the 129 iteration\n", - "[0 0 1 0 1 1 0 1 1 0 0 1 1 1 0 1 0 0 1 0 1]\n", - "Running the 130 iteration\n", - "[1 0 0 0 1 1 0 1 0 0 0 1 1 0 1 0 1 1 0 1 1]\n", - "Running the 131 iteration\n", - "[1 1 0 1 1 0 0 0 0 1 1 0 0 1 1 1 0 1 0 1 0]\n", - "Running the 132 iteration\n", - "[0 0 0 1 1 1 0 0 0 1 0 1 0 1 1 0 1 1 1 1 0]\n", - "Running the 133 iteration\n", - "[0 0 0 1 0 0 0 1 0 1 1 1 1 1 1 1 1 1 0 0 0]\n", - "Running the 134 iteration\n", - "[1 0 1 0 1 1 1 1 0 0 0 0 0 1 1 1 0 0 1 1 0]\n", - "Running the 135 iteration\n", - "[1 1 0 0 0 1 0 0 0 1 0 0 1 1 0 1 1 1 0 1 1]\n", - "Running the 136 iteration\n", - "[0 1 0 1 0 0 0 0 1 1 1 1 1 1 1 0 0 1 0 1 0]\n", - "Running the 137 iteration\n", - "[1 0 0 0 1 1 0 1 1 1 0 0 0 1 0 1 0 1 1 0 1]\n", - "Running the 138 iteration\n", - "[0 1 1 0 0 1 1 1 0 1 0 0 1 0 1 0 0 1 0 1 1]\n", - "Running the 139 iteration\n", - "[1 0 1 1 1 1 0 0 0 1 0 1 0 1 1 1 1 0 0 0 0]\n", - "Running the 140 iteration\n", - "[1 0 0 1 0 1 1 0 1 0 1 1 0 0 1 1 0 1 1 0 0]\n", - "Running the 141 iteration\n", - "[0 0 1 1 0 0 1 1 0 1 1 0 0 0 1 1 0 1 1 0 1]\n", - "Running the 142 iteration\n", - "[1 1 1 0 0 1 1 0 0 1 0 1 0 0 1 1 0 1 1 0 0]\n", - "Running the 143 iteration\n", - "[1 0 1 1 1 0 0 0 1 0 1 1 0 0 0 1 1 1 1 0 0]\n", - "Running the 144 iteration\n", - "[1 1 1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 1 1 1 1]\n", - "Running the 145 iteration\n", - "[1 1 0 0 0 1 0 1 0 0 1 1 0 1 1 1 0 1 0 1 0]\n", - "Running the 146 iteration\n", - "[1 0 0 0 1 1 0 1 1 0 1 1 1 0 1 1 0 1 0 0 0]\n", - "Running the 147 iteration\n", - "[1 0 0 1 1 0 0 0 1 1 1 0 1 0 1 0 0 1 1 0 1]\n", - "Running the 148 iteration\n", - "[1 1 1 1 0 1 0 0 1 0 0 0 1 1 0 1 0 1 1 0 0]\n", - "Running the 149 iteration\n", - "[1 1 1 0 0 0 1 0 1 0 0 0 1 1 0 1 0 1 1 1 0]\n", - "Running the 150 iteration\n", - "[0 0 0 1 1 1 0 1 1 1 0 1 1 1 0 1 0 0 0 1 0]\n", - "Running the 151 iteration\n", - "[0 0 0 1 0 1 0 1 1 0 0 1 1 1 1 1 0 1 0 1 0]\n", - "Running the 152 iteration\n", - "[0 0 0 0 0 1 0 1 1 0 1 1 1 0 1 0 0 1 1 1 1]\n", - "Running the 153 iteration\n", - "[1 0 0 0 1 1 1 0 0 1 1 0 1 1 0 1 0 1 0 1 0]\n", - "Running the 154 iteration\n", - "[0 0 1 1 0 0 1 0 1 1 1 1 1 1 0 0 1 1 0 0 0]\n", - "Running the 155 iteration\n", - "[1 0 1 1 0 1 0 1 1 0 0 1 0 0 0 1 1 1 0 1 0]\n", - "Running the 156 iteration\n", - "[0 1 0 0 1 1 0 1 1 0 1 0 0 0 1 1 0 0 1 1 1]\n", - "Running the 157 iteration\n", - "[1 1 0 1 0 1 1 0 0 1 0 1 0 1 1 0 0 0 0 1 1]\n", - "Running the 158 iteration\n", - "[1 0 0 0 1 0 1 1 1 1 1 0 1 0 0 1 1 0 0 1 0]\n", - "Running the 159 iteration\n", - "[0 1 0 0 1 1 0 1 1 1 1 0 0 0 0 0 1 0 1 1 1]\n", - "Running the 160 iteration\n", - "[0 1 1 1 0 0 1 0 0 1 1 0 1 0 1 0 1 1 0 0 1]\n", - "Running the 161 iteration\n", - "[1 0 0 0 1 1 1 0 1 0 0 0 1 0 0 1 0 1 1 1 1]\n", - "Running the 162 iteration\n", - "[1 0 0 0 0 0 1 1 1 1 1 1 0 1 1 0 0 1 1 0 0]\n", - "Running the 163 iteration\n", - "[1 0 0 1 0 0 1 1 1 0 1 0 0 0 1 0 1 1 1 1 0]\n", - "Running the 164 iteration\n", - "[0 1 1 1 1 0 1 0 1 0 1 0 1 0 1 1 0 0 0 0 1]\n", - "Running the 165 iteration\n", - "[0 0 1 0 1 1 1 1 1 0 0 1 1 0 0 1 0 1 0 0 1]\n", - "Running the 166 iteration\n", - "[0 0 0 1 1 1 0 1 0 1 1 0 0 0 1 1 0 1 0 1 1]\n", - "Running the 167 iteration\n", - "[1 0 1 1 1 1 1 0 0 1 1 0 1 1 0 0 0 0 0 1 0]\n", - "Running the 168 iteration\n", - "[1 1 1 0 1 0 1 0 1 0 1 1 0 1 0 1 0 1 0 0 0]\n", - "Running the 169 iteration\n", - "[1 0 0 0 1 0 0 1 1 0 1 0 1 1 0 0 1 1 1 1 0]\n", - "Running the 170 iteration\n", - "[1 0 1 0 1 0 0 1 1 1 0 0 0 1 0 1 0 1 1 1 0]\n", - "Running the 171 iteration\n", - "[1 1 1 0 1 0 0 0 1 0 1 0 0 0 1 1 1 0 1 1 0]\n", - "Running the 172 iteration\n", - "[1 0 1 1 0 1 1 0 1 0 0 0 1 0 0 1 1 0 0 1 1]\n", - "Running the 173 iteration\n", - "[0 0 1 0 0 1 1 0 1 1 1 0 1 0 1 1 1 0 0 1 0]\n", - "Running the 174 iteration\n", - "[0 1 0 1 1 0 0 1 1 0 1 0 1 1 0 0 0 1 1 0 1]\n", - "Running the 175 iteration\n", - "[0 1 1 1 1 1 0 0 0 0 1 0 0 0 1 1 0 1 0 1 1]\n", - "Running the 176 iteration\n", - "[0 1 1 1 0 1 0 0 1 1 1 1 0 0 0 1 1 0 0 0 1]\n", - "Running the 177 iteration\n", - "[0 0 0 1 1 0 1 0 0 1 1 0 1 1 1 0 0 1 0 1 1]\n", - "Running the 178 iteration\n", - "[0 1 1 0 1 0 1 1 0 0 1 1 1 0 1 1 0 0 1 0 0]\n", - "Running the 179 iteration\n", - "[0 0 1 1 1 1 1 1 0 0 1 0 1 1 1 0 0 0 0 1 0]\n", - "Running the 180 iteration\n", - "[0 0 0 1 0 0 1 0 0 1 1 1 1 1 0 1 1 0 0 1 1]\n", - "Running the 181 iteration\n", - "[0 1 0 0 0 1 1 1 1 1 1 0 1 0 0 1 0 0 0 1 1]\n", - "Running the 182 iteration\n", - "[1 0 1 1 0 0 0 1 1 1 0 0 1 1 1 0 1 0 0 1 0]\n", - "Running the 183 iteration\n", - "[1 1 1 0 1 1 1 1 1 0 0 0 0 0 0 1 0 0 0 1 1]\n", - "Running the 184 iteration\n", - "[1 1 0 0 0 1 0 1 1 1 0 0 0 0 1 1 1 1 1 0 0]\n", - "Running the 185 iteration\n", - "[0 0 1 0 0 1 0 0 0 1 0 1 0 1 1 1 1 1 1 1 0]\n", - "Running the 186 iteration\n", - "[1 0 0 1 1 0 0 0 1 0 1 1 0 0 1 0 0 1 1 1 1]\n", - "Running the 187 iteration\n", - "[0 0 1 0 1 1 1 0 0 1 1 0 0 0 1 1 0 1 0 1 1]\n", - "Running the 188 iteration\n", - "[1 1 0 0 1 1 1 0 1 1 0 1 1 1 1 0 0 0 0 0 0]\n", - "Running the 189 iteration\n", - "[1 1 0 0 1 1 0 0 0 0 0 1 1 0 1 1 0 1 1 0 1]\n", - "Running the 190 iteration\n", - "[0 1 1 0 0 1 0 1 1 1 1 0 1 0 0 0 0 1 1 1 0]\n", - "Running the 191 iteration\n", - "[1 0 0 0 1 0 0 1 1 1 1 1 1 0 0 1 1 0 0 0 1]\n", - "Running the 192 iteration\n", - "[1 1 0 0 1 0 0 1 0 0 1 0 0 1 1 1 0 1 1 0 1]\n", - "Running the 193 iteration\n", - "[1 1 0 0 0 1 0 0 1 0 1 0 1 1 1 0 0 1 0 1 1]\n", - "Running the 194 iteration\n", - "[0 0 1 1 1 1 0 0 0 1 0 1 1 0 1 1 0 0 1 1 0]\n", - "Running the 195 iteration\n", - "[1 0 1 0 1 0 0 1 1 0 1 0 1 0 0 1 1 1 1 0 0]\n", - "Running the 196 iteration\n", - "[1 0 1 1 1 1 0 1 0 1 0 1 0 1 0 0 0 0 1 0 1]\n", - "Running the 197 iteration\n", - "[0 0 0 0 1 1 1 1 0 1 1 0 1 1 1 0 0 0 1 1 0]\n", - "Running the 198 iteration\n", - "[0 0 0 0 1 0 1 1 0 1 0 0 0 0 1 1 1 1 1 1 1]\n", - "Running the 199 iteration\n", - "[1 1 0 1 0 1 0 1 0 1 0 1 0 1 0 0 1 1 1 0 0]\n", - "Running the 200 iteration\n", - "[1 1 1 1 0 0 0 1 0 0 1 0 1 0 1 1 0 0 0 1 1]\n", - "Running the 201 iteration\n", - "[1 1 1 0 1 0 1 0 1 0 0 1 1 1 1 0 0 0 1 0 0]\n", - "Running the 202 iteration\n", - "[0 1 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 1 0 0 0]\n", - "Running the 203 iteration\n", - "[0 0 0 1 0 1 1 1 0 1 0 0 1 1 1 0 0 0 1 1 1]\n", - "Running the 204 iteration\n", - "[0 1 0 1 0 0 0 1 1 1 0 1 1 0 0 0 1 1 0 1 1]\n", - "Running the 205 iteration\n", - "[0 1 1 0 0 0 1 1 1 0 1 0 1 0 0 0 1 1 1 1 0]\n", - "Running the 206 iteration\n", - "[1 0 1 1 0 0 0 0 1 1 0 0 1 1 1 1 0 0 1 0 1]\n", - "Running the 207 iteration\n", - "[1 0 0 1 1 0 0 1 1 1 0 0 1 0 0 0 1 0 1 1 1]\n", - "Running the 208 iteration\n", - "[0 1 0 1 1 0 1 1 0 1 0 1 1 1 0 1 0 0 0 0 1]\n", - "Running the 209 iteration\n", - "[0 1 1 0 0 0 1 1 0 0 0 1 0 1 1 1 1 1 0 1 0]\n", - "Running the 210 iteration\n", - "[1 1 1 0 1 0 0 0 0 0 1 1 0 1 1 0 0 1 0 1 1]\n", - "Running the 211 iteration\n", - "[1 1 1 1 0 0 1 1 1 0 0 0 0 0 1 0 1 1 0 0 1]\n", - "Running the 212 iteration\n", - "[0 0 0 0 0 1 1 1 0 1 1 1 1 1 0 1 0 1 0 1 0]\n", - "Running the 213 iteration\n", - "[1 1 0 1 1 1 1 0 1 1 0 0 0 0 1 0 1 1 0 0 0]\n", - "Running the 214 iteration\n", - "[1 0 1 0 1 0 0 1 0 0 0 1 1 1 1 1 0 0 1 0 1]\n", - "Running the 215 iteration\n", - "[1 0 1 0 1 0 0 1 0 0 0 1 1 1 0 1 1 0 1 1 0]\n", - "Running the 216 iteration\n", - "[1 1 1 0 1 1 1 0 0 0 1 1 0 0 1 1 0 0 0 1 0]\n", - "Running the 217 iteration\n", - "[1 0 1 0 0 0 0 1 1 1 0 0 1 1 1 0 1 1 1 0 0]\n", - "Running the 218 iteration\n", - "[1 1 1 1 0 0 0 1 0 1 1 1 0 0 0 0 1 1 0 0 1]\n", - "Running the 219 iteration\n", - "[1 0 0 1 0 1 0 1 1 1 0 1 0 1 0 1 1 0 0 1 0]\n", - "Running the 220 iteration\n", - "[1 0 1 1 0 1 0 0 1 0 1 1 0 1 1 0 1 1 0 0 0]\n", - "Running the 221 iteration\n", - "[0 0 0 1 0 1 1 1 1 0 0 1 1 1 0 0 1 0 0 1 1]\n", - "Running the 222 iteration\n", - "[0 1 1 0 0 1 1 1 0 1 1 0 1 0 0 1 0 1 1 0 0]\n", - "Running the 223 iteration\n", - "[0 0 1 1 1 1 0 0 0 1 1 1 0 1 0 1 0 1 1 0 0]\n", - "Running the 224 iteration\n", - "[0 1 1 0 0 1 0 0 1 1 1 0 0 0 1 0 1 0 1 1 1]\n", - "Running the 225 iteration\n", - "[0 1 1 1 1 1 1 0 0 1 0 0 0 0 1 0 0 1 1 1 0]\n", - "Running the 226 iteration\n", - "[1 0 0 0 1 0 1 1 0 0 0 0 0 1 1 1 1 1 1 1 0]\n", - "Running the 227 iteration\n", - "[1 0 1 1 1 0 0 0 1 0 0 1 0 0 1 1 1 1 1 0 0]\n", - "Running the 228 iteration\n", - "[0 0 0 1 0 1 1 0 1 1 1 0 0 1 0 1 1 0 1 0 1]\n", - "Running the 229 iteration\n", - "[1 1 0 1 0 0 1 1 0 1 1 1 1 0 0 1 0 1 0 0 0]\n", - "Running the 230 iteration\n", - "[1 0 0 0 1 1 0 1 0 0 0 1 1 1 0 1 0 1 1 0 1]\n", - "Running the 231 iteration\n", - "[0 1 1 0 1 0 1 1 0 0 0 1 0 1 1 0 1 1 1 0 0]\n", - "Running the 232 iteration\n", - "[0 0 1 1 0 1 0 0 0 1 1 0 1 0 0 0 1 1 1 1 1]\n", - "Running the 233 iteration\n", - "[0 1 1 1 1 0 0 0 1 1 1 0 1 0 0 0 1 1 0 0 1]\n", - "Running the 234 iteration\n", - "[0 1 1 0 0 1 0 1 1 1 0 0 0 1 1 0 0 0 1 1 1]\n", - "Running the 235 iteration\n", - "[1 0 1 0 0 1 1 0 0 1 1 1 0 1 0 0 0 0 1 1 1]\n", - "Running the 236 iteration\n", - "[1 0 0 0 1 0 1 1 1 0 0 0 0 1 0 1 1 0 1 1 1]\n", - "Running the 237 iteration\n", - "[1 1 1 0 0 0 0 1 0 0 0 1 1 1 1 0 1 1 0 0 1]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Running the 238 iteration\n", - "[1 0 1 1 0 0 0 1 1 0 0 0 1 1 0 1 0 0 1 1 1]\n", - "Running the 239 iteration\n", - "[0 1 1 1 1 1 0 0 1 0 0 0 0 1 0 1 1 0 0 1 1]\n", - "Running the 240 iteration\n", - "[0 1 0 0 1 0 1 1 0 0 1 1 0 1 1 1 0 0 0 1 1]\n", - "Running the 241 iteration\n", - "[0 1 0 1 1 0 1 0 1 1 0 1 1 0 0 0 0 1 0 1 1]\n", - "Running the 242 iteration\n", - "[0 0 0 0 1 1 1 0 1 0 0 0 1 1 0 1 0 1 1 1 1]\n", - "Running the 243 iteration\n", - "[0 1 0 0 1 1 1 0 1 0 0 1 0 1 0 1 1 1 0 0 1]\n", - "Running the 244 iteration\n", - "[1 0 0 0 0 1 0 1 1 1 1 1 0 1 1 1 0 0 1 0 0]\n", - "Running the 245 iteration\n", - "[1 0 0 1 0 0 1 0 1 1 1 1 0 0 1 0 0 1 1 0 1]\n", - 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"Running the 258 iteration\n", - "[1 0 0 0 0 1 0 1 1 1 1 0 1 1 0 1 1 1 0 0 0]\n", - "Running the 259 iteration\n", - "[0 0 0 1 0 1 1 0 1 0 1 0 0 0 1 1 1 0 1 1 1]\n", - "Running the 260 iteration\n", - "[0 1 1 1 1 1 0 0 0 1 1 0 1 1 0 0 0 0 1 1 0]\n", - "Running the 261 iteration\n", - "[1 0 0 0 0 1 0 0 1 0 1 1 1 1 1 1 1 0 1 0 0]\n", - "Running the 262 iteration\n", - "[1 0 0 0 1 0 0 0 1 1 1 1 1 0 1 0 0 1 0 1 1]\n", - "Running the 263 iteration\n", - "[0 0 1 0 1 1 0 0 1 1 1 1 1 1 0 0 0 0 1 0 1]\n", - "Running the 264 iteration\n", - "[1 1 0 1 1 0 0 0 0 1 1 0 0 1 1 1 0 0 1 1 0]\n", - "Running the 265 iteration\n", - "[1 1 1 1 0 1 0 0 1 1 0 0 0 1 1 0 0 0 0 1 1]\n", - "Running the 266 iteration\n", - "[0 1 0 1 1 1 1 0 1 1 1 0 0 0 0 0 0 1 1 1 0]\n", - "Running the 267 iteration\n", - "[0 0 0 1 1 1 0 1 0 0 0 1 1 1 1 1 0 1 0 0 1]\n", - "Running the 268 iteration\n", - "[0 0 1 1 1 0 0 0 0 0 0 1 0 1 1 1 1 0 1 1 1]\n", - "Running the 269 iteration\n", - "[1 1 1 1 1 1 0 0 0 0 1 0 0 0 0 1 0 1 1 1 0]\n", - "Running the 270 iteration\n", - "[1 0 1 1 0 1 0 1 0 0 1 1 0 0 1 0 1 0 0 1 1]\n", - "Running the 271 iteration\n", - "[1 0 1 1 0 0 1 0 1 0 1 0 1 1 0 1 0 1 0 0 1]\n", - "Running the 272 iteration\n", - "[1 0 0 0 0 1 1 0 1 0 0 1 1 1 1 0 0 1 0 1 1]\n", - "Running the 273 iteration\n", - "[1 1 1 1 1 0 1 0 0 1 1 0 1 1 1 0 0 0 0 0 0]\n", - "Running the 274 iteration\n", - "[0 0 0 0 0 0 1 1 1 0 0 1 1 1 1 1 1 1 0 0 1]\n", - "Running the 275 iteration\n", - "[0 1 1 0 0 1 0 1 1 0 1 1 1 0 1 0 0 1 0 1 0]\n", - "Running the 276 iteration\n", - "[0 1 0 0 0 0 1 0 0 1 1 0 1 0 0 1 1 1 1 1 1]\n", - "Running the 277 iteration\n", - "[1 0 0 1 0 0 0 1 1 1 0 1 0 1 0 1 1 0 1 1 0]\n", - "Running the 278 iteration\n", - "[0 1 0 1 0 0 1 1 1 0 1 1 0 1 0 1 0 1 0 1 0]\n", - "Running the 279 iteration\n", - "[1 0 1 1 1 0 0 0 1 1 1 0 0 1 0 0 1 1 0 0 1]\n", - "Running the 280 iteration\n", - "[0 1 1 0 1 1 0 0 1 1 0 0 1 1 0 1 0 0 1 1 0]\n", - "Running the 281 iteration\n", - "[1 0 1 0 0 1 0 0 1 1 0 0 0 0 0 1 1 1 1 1 1]\n", - "Running the 282 iteration\n", - "[1 1 1 0 0 1 1 0 1 1 0 0 1 0 0 1 0 1 0 1 0]\n", - "Running the 283 iteration\n", - "[1 0 0 1 0 0 1 1 1 1 0 1 0 1 1 0 1 1 0 0 0]\n", - "Running the 284 iteration\n", - "[0 0 0 1 1 1 1 0 1 1 0 1 1 0 0 0 0 1 1 1 0]\n", - "Running the 285 iteration\n", - "[1 1 1 1 0 0 1 0 1 1 0 0 0 0 1 0 0 0 1 1 1]\n", - "Running the 286 iteration\n", - "[0 1 1 0 1 0 1 0 1 0 0 0 0 1 1 1 0 1 1 0 1]\n", - "Running the 287 iteration\n", - "[1 1 0 0 1 1 1 0 0 0 1 0 0 1 1 1 0 0 0 1 1]\n", - "Running the 288 iteration\n", - "[1 1 0 1 0 1 0 0 0 0 0 1 0 0 1 1 0 1 1 1 1]\n", - "Running the 289 iteration\n", - "[1 1 0 0 1 0 0 1 1 0 1 0 0 0 1 1 1 0 0 1 1]\n", - "Running the 290 iteration\n", - "[0 0 0 1 0 0 1 1 1 0 0 1 1 1 0 1 1 0 0 1 1]\n", - "Running the 291 iteration\n", - "[1 1 1 0 0 0 1 1 0 0 1 1 1 0 1 1 0 0 1 0 0]\n", - "Running the 292 iteration\n", - "[1 1 1 0 1 1 0 0 1 1 0 0 1 0 0 1 0 1 1 0 0]\n", - "Running the 293 iteration\n", - "[0 1 0 0 1 1 1 0 1 0 0 0 1 0 1 0 1 1 1 1 0]\n", - "Running the 294 iteration\n", - "[1 0 0 0 0 1 0 1 0 1 0 1 1 1 0 0 1 1 0 1 1]\n", - "Running the 295 iteration\n", - "[0 0 1 1 0 1 0 0 1 1 1 0 0 1 0 1 1 1 0 1 0]\n", - "Running the 296 iteration\n", - "[0 1 0 1 0 1 0 1 1 0 0 1 1 0 1 1 1 0 0 1 0]\n", - "Running the 297 iteration\n", - "[0 0 1 1 1 1 0 0 1 1 0 1 1 0 0 1 1 0 0 1 0]\n", - "Running the 298 iteration\n", - "[1 1 0 1 1 0 0 0 1 1 1 0 0 1 0 1 1 0 0 0 1]\n", - "Running the 299 iteration\n", - "[0 0 0 0 1 1 1 1 0 0 1 0 1 0 1 1 1 1 0 1 0]\n", - "Running the 300 iteration\n", - "[0 1 0 1 1 1 0 0 1 0 0 1 1 1 1 1 1 0 0 0 0]\n", - "Running the 301 iteration\n", - "[0 0 0 1 0 0 0 1 1 1 1 0 1 1 1 0 1 0 1 1 0]\n", - "Running the 302 iteration\n", - "[1 1 1 0 1 0 0 0 1 1 0 1 1 0 1 0 0 1 0 1 0]\n", - "Running the 303 iteration\n", - "[1 1 0 0 0 0 1 1 0 1 1 1 0 0 0 0 1 1 0 1 1]\n", - "Running the 304 iteration\n", - "[0 0 1 0 1 1 1 0 1 0 0 1 0 0 1 1 0 1 1 1 0]\n", - "Running the 305 iteration\n", - "[0 1 1 1 1 1 1 0 0 0 0 0 1 0 0 1 1 0 1 0 1]\n", - "Running the 306 iteration\n", - "[1 1 1 0 0 1 1 0 1 0 1 1 0 1 0 1 0 1 0 0 0]\n", - "Running the 307 iteration\n", - "[0 1 1 0 0 0 1 1 0 0 1 0 1 1 1 1 0 1 0 1 0]\n", - "Running the 308 iteration\n", - "[1 1 1 0 0 1 1 0 0 0 1 0 1 0 1 0 1 0 1 1 0]\n", - "Running the 309 iteration\n", - "[1 1 1 0 0 1 0 0 0 0 1 0 0 1 1 0 1 1 1 0 1]\n", - "Running the 310 iteration\n", - "[1 0 1 1 0 0 1 1 0 0 0 1 1 1 1 0 1 0 0 0 1]\n", - "Running the 311 iteration\n", - "[1 1 0 1 0 0 0 1 1 0 0 1 1 0 0 1 0 1 1 1 0]\n", - "Running the 312 iteration\n", - "[1 0 1 1 1 0 0 0 0 1 1 1 0 0 1 0 0 0 1 1 1]\n", - "Running the 313 iteration\n", - "[0 1 1 1 0 1 1 0 1 0 0 1 1 0 0 0 0 0 1 1 1]\n", - "Running the 314 iteration\n", - "[0 1 0 1 0 0 0 0 1 1 0 1 0 0 0 1 1 1 1 1 1]\n", - "Running the 315 iteration\n", - "[1 1 1 1 0 0 0 0 1 1 1 0 0 0 0 0 1 1 1 0 1]\n", - "Running the 316 iteration\n", - "[0 1 0 1 0 1 1 1 1 1 1 0 0 0 0 0 1 1 1 0 0]\n", - "Running the 317 iteration\n", - "[1 1 1 0 0 0 0 1 0 0 1 1 1 1 0 0 1 0 1 0 1]\n", - "Running the 318 iteration\n", - "[1 1 0 1 0 0 1 1 1 0 0 0 0 1 0 0 1 1 1 0 1]\n", - "Running the 319 iteration\n", - "[0 1 0 1 0 0 0 0 1 1 1 0 1 1 0 1 1 0 1 1 0]\n", - "Running the 320 iteration\n", - "[0 0 0 0 1 1 0 1 0 1 0 1 1 1 0 1 0 1 1 0 1]\n", - "Running the 321 iteration\n", - "[0 1 1 1 0 0 1 0 0 0 1 1 0 0 1 0 0 1 1 1 1]\n", - "Running the 322 iteration\n", - "[0 0 1 0 1 1 1 1 0 0 0 1 1 0 0 0 1 1 0 1 1]\n", - "Running the 323 iteration\n", - "[1 0 1 0 0 1 1 0 1 0 0 0 1 1 0 0 0 1 1 1 1]\n", - "Running the 324 iteration\n", - "[0 1 1 0 0 0 1 1 0 1 0 1 1 1 0 1 1 0 0 0 1]\n", - "Running the 325 iteration\n", - "[0 0 0 1 1 0 0 0 1 0 0 1 0 1 1 1 1 1 1 1 0]\n", - "Running the 326 iteration\n", - "[1 0 1 1 0 0 1 1 1 0 0 1 0 1 0 1 0 1 1 0 0]\n", - "Running the 327 iteration\n", - "[0 0 1 1 1 0 0 1 1 1 1 1 0 0 0 0 0 1 0 1 1]\n", - "Running the 328 iteration\n", - "[0 1 0 0 0 1 1 0 1 1 0 1 1 0 1 1 1 0 1 0 0]\n", - "Running the 329 iteration\n", - "[0 1 0 0 1 0 1 1 1 1 1 1 0 0 1 1 0 1 0 0 0]\n", - "Running the 330 iteration\n", - "[0 1 1 0 0 1 1 0 1 1 1 0 0 1 0 0 1 1 1 0 0]\n", - "Running the 331 iteration\n", - "[1 1 0 0 0 1 1 1 1 1 1 0 1 0 0 0 0 0 1 1 0]\n", - "Running the 332 iteration\n", - "[1 0 0 1 1 1 1 0 1 1 0 1 0 1 0 0 1 1 0 0 0]\n", - "Running the 333 iteration\n", - "[1 1 1 1 1 0 1 0 1 0 1 0 0 0 0 0 1 1 1 0 0]\n", - "Running the 334 iteration\n", - "[0 0 0 1 1 0 1 1 1 1 1 0 1 0 0 0 1 0 0 1 1]\n", - "Running the 335 iteration\n", - "[0 1 1 1 1 1 1 0 0 0 0 1 0 1 0 0 1 0 0 1 1]\n", - "Running the 336 iteration\n", - "[1 0 0 0 1 1 1 1 1 1 0 0 0 0 0 1 1 1 1 0 0]\n", - "Running the 337 iteration\n", - "[0 1 0 0 1 1 1 0 1 1 1 0 1 1 1 0 0 0 1 0 0]\n", - "Running the 338 iteration\n", - "[0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 1 0 1 1 0]\n", - "Running the 339 iteration\n", - "[1 0 1 1 0 0 0 1 1 0 1 0 1 0 1 1 0 1 0 1 0]\n", - "Running the 340 iteration\n", - "[0 0 1 0 1 1 1 0 1 1 1 0 0 0 0 1 1 1 0 0 1]\n", - "Running the 341 iteration\n", - "[0 0 1 1 1 0 1 0 0 1 1 0 1 0 0 1 0 1 1 1 0]\n", - "Running the 342 iteration\n", - "[0 0 1 1 1 1 1 0 1 1 0 1 0 1 0 1 0 0 0 0 1]\n", - "Running the 343 iteration\n", - "[0 0 1 1 0 0 1 0 1 0 1 0 1 1 0 0 1 1 1 1 0]\n", - "Running the 344 iteration\n", - "[1 1 0 1 1 0 0 1 1 0 0 0 0 1 1 0 0 1 0 1 1]\n", - "Running the 345 iteration\n", - "[0 0 1 0 1 1 1 1 1 0 1 0 0 0 1 0 1 0 1 1 0]\n", - "Running the 346 iteration\n", - "[1 1 0 0 1 0 1 0 0 0 1 0 0 1 1 0 1 1 1 1 0]\n", - "Running the 347 iteration\n", - "[1 1 0 0 1 1 1 0 0 0 1 1 0 0 1 1 1 0 1 0 0]\n", - "Running the 348 iteration\n", - "[1 1 1 0 0 0 0 1 0 0 1 0 1 1 0 1 1 1 0 0 1]\n", - "Running the 349 iteration\n", - "[0 0 1 1 0 0 1 0 1 1 0 1 1 1 0 1 0 0 0 1 1]\n", - "Running the 350 iteration\n", - "[1 0 0 0 0 1 1 1 1 0 0 0 1 0 1 1 1 1 0 0 1]\n", - "Running the 351 iteration\n", - "[0 1 1 0 1 1 1 1 1 0 0 1 0 0 0 1 1 0 1 0 0]\n", - "Running the 352 iteration\n", - "[0 1 0 0 0 0 1 0 1 1 1 0 1 1 1 0 1 1 0 1 0]\n", - "Running the 353 iteration\n", - "[0 0 1 0 1 1 0 0 1 0 1 1 1 1 0 1 0 0 1 0 1]\n", - "Running the 354 iteration\n", - "[1 0 0 0 0 0 1 1 0 1 1 1 1 1 1 1 0 1 0 0 0]\n", - "Running the 355 iteration\n", - "[1 1 1 0 0 0 1 0 0 1 1 1 0 1 1 0 0 1 0 0 1]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Running the 356 iteration\n", - "[1 0 0 0 0 1 0 1 1 1 1 1 1 1 0 0 1 0 0 1 0]\n", - "Running the 357 iteration\n", - "[0 0 1 1 0 0 1 1 1 0 1 0 0 1 0 1 0 1 1 0 1]\n", - "Running the 358 iteration\n", - "[0 0 0 1 0 0 0 0 1 0 1 1 1 0 0 1 1 1 1 1 1]\n", - "Running the 359 iteration\n", - "[1 0 1 0 1 0 1 1 1 1 0 0 1 1 0 0 0 0 0 1 1]\n", - "Running the 360 iteration\n", - "[0 1 1 0 1 1 0 0 0 1 1 1 0 1 1 0 1 0 0 0 1]\n", - "Running the 361 iteration\n", - "[1 1 1 1 0 0 1 1 1 0 0 0 1 0 1 1 0 0 0 0 1]\n", - "Running the 362 iteration\n", - "[0 0 0 0 1 0 1 1 0 1 1 0 0 1 1 1 1 0 1 1 0]\n", - "Running the 363 iteration\n", - "[1 0 1 1 0 1 0 1 0 0 1 1 1 0 1 0 0 1 0 1 0]\n", - "Running the 364 iteration\n", - "[1 1 1 0 0 1 0 1 1 0 0 0 1 1 1 0 0 1 0 0 1]\n", - "Running the 365 iteration\n", - "[1 0 0 0 0 1 0 0 0 1 1 1 1 1 0 0 1 1 0 1 1]\n", - "Running the 366 iteration\n", - "[1 1 1 1 0 0 0 1 1 0 1 1 0 1 1 0 0 0 0 0 1]\n", - "Running the 367 iteration\n", - "[0 0 0 0 1 1 1 0 1 0 0 0 1 1 1 1 0 1 1 0 1]\n", - "Running the 368 iteration\n", - "[1 0 1 0 1 0 1 0 1 0 1 1 0 0 1 1 0 0 1 0 1]\n", - "Running the 369 iteration\n", - "[1 0 1 0 0 1 0 1 1 0 1 1 1 0 1 1 1 0 0 0 0]\n", - "Running the 370 iteration\n", - "[0 1 1 1 0 0 0 1 1 1 0 0 0 1 0 0 1 0 1 1 1]\n", - "Running the 371 iteration\n", - "[1 1 1 1 0 1 1 0 0 0 0 1 1 0 0 1 0 1 0 0 1]\n", - "Running the 372 iteration\n", - "[0 1 1 1 0 1 0 0 0 1 0 1 0 1 1 1 0 1 0 0 1]\n", - "Running the 373 iteration\n", - "[0 0 1 1 1 0 1 1 0 1 1 1 0 0 0 0 1 0 0 1 1]\n", - "Running the 374 iteration\n", - "[1 0 0 1 0 1 1 0 1 0 1 0 1 1 0 0 1 1 0 1 0]\n", - "Running the 375 iteration\n", - "[1 0 1 1 1 0 0 0 1 0 0 1 0 1 0 0 1 1 1 1 0]\n", - "Running the 376 iteration\n", - "[0 1 0 1 1 1 1 1 1 0 0 0 1 0 1 0 0 1 0 0 1]\n", - "Running the 377 iteration\n", - "[0 1 0 1 0 0 1 1 0 0 1 1 1 1 0 1 1 0 0 1 0]\n", - "Running the 378 iteration\n", - "[1 1 1 1 1 0 1 0 1 1 0 0 0 1 0 0 0 1 0 1 0]\n", - "Running the 379 iteration\n", - "[1 0 1 0 1 0 0 0 1 0 0 1 0 1 0 1 1 0 1 1 1]\n", - "Running the 380 iteration\n", - "[1 1 0 1 0 0 0 1 1 0 1 0 1 1 0 1 1 0 1 0 0]\n", - "Running the 381 iteration\n", - "[1 1 1 0 0 1 0 1 1 1 1 0 0 0 1 1 0 0 0 1 0]\n", - "Running the 382 iteration\n", - "[1 1 0 0 0 0 0 0 1 1 1 1 1 0 1 1 0 1 0 1 0]\n", - "Running the 383 iteration\n", - "[1 0 1 1 0 0 1 0 0 1 0 0 1 0 1 0 1 1 1 1 0]\n", - "Running the 384 iteration\n", - "[0 0 1 0 0 1 1 1 0 1 0 1 0 0 1 1 1 0 0 1 1]\n", - "Running the 385 iteration\n", - "[0 1 0 1 0 1 1 1 0 0 0 0 1 0 1 0 1 1 0 1 1]\n", - "Running the 386 iteration\n", - "[1 1 0 1 1 0 0 0 1 1 0 0 0 0 1 0 0 1 1 1 1]\n", - "Running the 387 iteration\n", - "[1 0 0 1 0 1 0 0 1 1 0 1 1 0 1 1 0 1 1 0 0]\n", - "Running the 388 iteration\n", - "[0 0 0 0 1 0 1 0 1 1 1 1 0 1 0 1 1 1 0 0 1]\n", - "Running the 389 iteration\n", - "[1 1 0 1 1 1 1 0 1 0 0 0 0 1 1 0 0 0 1 0 1]\n", - "Running the 390 iteration\n", - "[1 1 0 0 1 0 1 1 0 0 0 0 0 1 1 1 0 1 1 0 1]\n", - "Running the 391 iteration\n", - "[0 1 0 1 1 0 1 0 1 0 0 0 0 1 0 1 1 1 1 1 0]\n", - "Running the 392 iteration\n", - "[1 0 0 0 1 0 1 1 1 0 0 0 0 0 1 0 1 1 1 1 1]\n", - "Running the 393 iteration\n", - "[1 0 1 1 1 0 1 1 0 0 0 1 0 1 1 1 0 0 0 0 1]\n", - "Running the 394 iteration\n", - "[0 1 0 1 0 0 0 1 0 0 1 0 1 1 1 1 0 1 1 1 0]\n", - "Running the 395 iteration\n", - "[0 1 1 1 1 1 0 0 1 0 0 1 1 1 0 0 0 1 0 0 1]\n", - "Running the 396 iteration\n", - "[0 1 1 1 1 0 1 1 1 0 0 0 0 1 1 0 1 1 0 0 0]\n", - "Running the 397 iteration\n", - "[0 1 1 1 1 0 1 0 1 0 1 0 0 1 1 0 0 1 0 1 0]\n", - "Running the 398 iteration\n", - "[1 0 1 0 1 0 1 0 1 0 1 0 0 1 1 1 0 1 0 1 0]\n", - "Running the 399 iteration\n", - "[1 1 0 0 1 1 0 1 0 1 1 1 0 0 0 0 1 1 0 0 1]\n", - "Running the 400 iteration\n", - "[0 1 0 0 0 1 1 1 0 1 1 0 1 0 1 0 1 1 0 1 0]\n", - "Running the 401 iteration\n", - "[0 0 0 0 1 1 0 1 0 0 0 1 1 1 1 1 0 1 1 1 0]\n", - "Running the 402 iteration\n", - "[1 1 1 1 0 0 0 0 0 0 1 1 1 1 1 0 1 0 0 0 1]\n", - "Running the 403 iteration\n", - "[0 0 1 1 1 0 1 1 0 0 1 0 1 0 1 0 1 0 1 1 0]\n", - "Running the 404 iteration\n", - "[1 0 1 1 0 0 0 1 0 1 1 0 1 0 0 0 1 0 1 1 1]\n", - "Running the 405 iteration\n", - "[0 1 1 1 1 0 1 0 0 1 0 1 0 0 1 0 0 1 1 0 1]\n", - "Running the 406 iteration\n", - "[1 0 0 0 0 1 1 1 1 0 1 0 0 1 0 1 0 1 0 1 1]\n", - "Running the 407 iteration\n", - "[1 1 0 0 1 1 0 0 1 0 0 0 0 1 0 1 1 1 0 1 1]\n", - "Running the 408 iteration\n", - "[0 1 0 0 1 1 1 1 0 1 0 0 1 0 1 1 1 0 1 0 0]\n", - "Running the 409 iteration\n", - "[0 1 0 0 1 1 1 0 1 0 0 1 0 1 1 1 1 0 1 0 0]\n", - "Running the 410 iteration\n", - "[1 0 1 1 0 1 1 0 0 1 0 0 0 1 0 1 0 1 0 1 1]\n", - "Running the 411 iteration\n", - "[1 0 1 1 0 0 1 1 0 0 1 0 0 1 1 0 0 0 1 1 1]\n", - "Running the 412 iteration\n", - "[1 1 1 0 0 0 1 0 1 0 1 1 1 0 1 1 0 1 0 0 0]\n", - "Running the 413 iteration\n", - "[1 0 1 0 0 0 0 1 1 0 1 0 1 0 1 0 1 1 0 1 1]\n", - "Running the 414 iteration\n", - "[1 1 0 0 1 0 1 0 0 1 0 1 1 0 1 1 0 0 0 1 1]\n", - "Running the 415 iteration\n", - "[0 1 1 1 1 1 0 0 1 1 0 0 0 0 1 1 0 1 0 1 0]\n", - "Running the 416 iteration\n", - "[0 0 0 1 0 0 1 1 1 0 1 0 1 0 0 1 1 1 0 1 1]\n", - "Running the 417 iteration\n", - "[1 0 0 1 0 1 1 0 0 1 1 0 1 0 0 0 1 1 1 1 0]\n", - "Running the 418 iteration\n", - "[1 0 1 0 1 1 1 0 1 0 1 0 1 1 0 0 0 0 1 1 0]\n", - "Running the 419 iteration\n", - "[1 1 1 0 0 0 0 1 1 1 1 0 0 1 0 0 0 0 1 1 1]\n", - "Running the 420 iteration\n", - "[0 1 1 0 1 1 1 1 1 0 0 0 0 1 1 1 0 0 1 0 0]\n", - "Running the 421 iteration\n", - "[1 0 1 1 0 0 1 1 1 0 0 1 0 0 1 0 1 0 1 0 1]\n", - "Running the 422 iteration\n", - "[1 0 1 1 1 0 1 1 1 0 0 0 0 1 1 1 1 0 0 0 0]\n", - "Running the 423 iteration\n", - "[1 0 0 1 1 1 0 0 1 1 0 0 0 1 0 1 1 1 1 0 0]\n", - "Running the 424 iteration\n", - "[0 1 0 0 0 1 1 1 0 1 0 1 0 1 0 0 1 1 1 1 0]\n", - "Running the 425 iteration\n", - "[1 1 0 1 0 1 0 0 1 0 1 0 0 0 1 1 1 1 0 1 0]\n", - "Running the 426 iteration\n", - "[1 1 1 1 1 0 0 1 0 1 0 1 1 1 0 0 0 0 0 1 0]\n", - "Running the 427 iteration\n", - "[1 0 0 0 1 0 1 0 1 1 0 1 0 1 0 1 1 0 1 1 0]\n", - "Running the 428 iteration\n", - "[0 1 0 1 0 1 1 0 1 1 1 1 0 0 0 1 1 0 1 0 0]\n", - "Running the 429 iteration\n", - "[0 1 1 0 0 0 1 0 1 0 0 1 0 1 0 1 0 1 1 1 1]\n", - "Running the 430 iteration\n", - "[1 1 1 0 0 0 1 0 1 0 1 1 0 0 1 0 1 1 1 0 0]\n", - "Running the 431 iteration\n", - "[1 0 0 0 1 1 1 0 1 0 0 0 1 0 1 0 1 1 1 0 1]\n", - "Running the 432 iteration\n", - "[1 0 1 0 1 0 0 0 1 1 1 0 1 1 0 0 0 1 0 1 1]\n", - "Running the 433 iteration\n", - "[0 1 1 1 1 0 1 1 1 1 0 0 0 1 1 0 1 0 0 0 0]\n", - "Running the 434 iteration\n", - "[0 1 1 0 1 0 1 0 1 0 1 1 1 1 1 1 0 0 0 0 0]\n", - "Running the 435 iteration\n", - "[0 0 1 0 0 0 1 1 1 1 1 0 1 1 0 1 1 1 0 0 0]\n", - "Running the 436 iteration\n", - "[0 1 1 1 1 1 0 0 1 0 1 1 0 0 0 0 0 1 0 1 1]\n", - "Running the 437 iteration\n", - "[1 0 1 0 1 0 0 1 0 0 1 1 0 1 1 0 0 1 1 1 0]\n", - "Running the 438 iteration\n", - "[1 0 1 0 0 1 1 1 1 1 0 0 0 0 0 1 0 1 0 1 1]\n", - "Running the 439 iteration\n", - "[1 0 0 1 0 0 1 1 1 0 1 0 0 0 0 0 1 1 1 1 1]\n", - "Running the 440 iteration\n", - "[0 1 0 1 0 1 0 0 1 1 0 0 1 0 1 1 1 0 1 1 0]\n", - "Running the 441 iteration\n", - "[0 1 0 1 1 0 0 0 1 1 1 0 1 0 1 0 1 1 0 1 0]\n", - "Running the 442 iteration\n", - "[1 0 0 1 0 0 1 1 0 1 1 1 1 0 1 0 0 1 0 0 1]\n", - "Running the 443 iteration\n", - "[0 0 0 1 1 1 1 1 0 0 0 0 1 1 0 1 0 0 1 1 1]\n", - "Running the 444 iteration\n", - "[0 1 1 1 0 0 1 0 1 1 0 0 1 0 1 0 0 1 1 1 0]\n", - "Running the 445 iteration\n", - "[1 0 1 0 1 0 0 1 1 1 0 1 1 0 0 0 0 1 1 0 1]\n", - "Running the 446 iteration\n", - "[0 1 0 0 1 0 1 0 1 0 1 0 1 0 1 1 1 1 1 0 0]\n", - "Running the 447 iteration\n", - "[1 0 1 0 1 1 1 1 0 1 0 0 1 1 0 0 1 1 0 0 0]\n", - "Running the 448 iteration\n", - "[0 0 0 0 1 1 1 1 0 1 1 0 1 0 1 1 1 0 0 0 1]\n", - "Running the 449 iteration\n", - "[0 0 0 1 1 0 1 1 0 0 0 0 1 1 1 0 1 1 1 0 1]\n", - "Running the 450 iteration\n", - "[1 0 0 0 1 1 1 1 1 0 0 1 1 0 1 0 1 0 0 1 0]\n", - "Running the 451 iteration\n", - "[1 0 0 1 0 1 1 0 0 0 1 1 0 1 1 1 0 0 1 0 1]\n", - "Running the 452 iteration\n", - "[0 0 0 1 0 1 0 1 1 1 0 0 1 0 1 0 0 1 1 1 1]\n", - "Running the 453 iteration\n", - "[1 1 1 1 0 0 0 0 1 1 0 1 0 0 1 1 0 1 1 0 0]\n", - "Running the 454 iteration\n", - "[1 0 0 1 0 0 1 1 1 1 0 0 1 1 1 1 0 0 0 0 1]\n", - "Running the 455 iteration\n", - "[0 1 1 1 1 1 0 1 0 1 0 0 0 0 1 1 0 0 1 0 1]\n", - "Running the 456 iteration\n", - "[0 0 1 1 1 1 0 1 1 1 1 1 0 0 1 0 0 1 0 0 0]\n", - "Running the 457 iteration\n", - "[0 0 0 1 1 0 1 0 1 0 0 1 1 0 1 1 0 0 1 1 1]\n", - "Running the 458 iteration\n", - "[0 1 1 0 0 0 1 1 0 1 1 0 1 0 0 1 1 0 1 0 1]\n", - "Running the 459 iteration\n", - "[0 1 0 0 0 1 0 0 1 0 0 1 1 1 1 1 0 1 1 0 1]\n", - "Running the 460 iteration\n", - "[1 0 1 0 0 0 1 1 0 0 1 0 0 0 1 1 0 1 1 1 1]\n", - "Running the 461 iteration\n", - "[0 1 1 1 1 0 0 1 0 0 0 1 0 1 1 1 0 0 1 1 0]\n", - "Running the 462 iteration\n", - "[0 0 1 1 0 1 1 1 1 0 1 0 0 0 1 1 0 1 0 0 1]\n", - "Running the 463 iteration\n", - "[1 0 0 0 1 1 0 0 1 0 0 1 0 1 0 1 1 1 1 1 0]\n", - "Running the 464 iteration\n", - "[1 1 0 1 0 1 0 0 1 1 1 0 0 0 0 1 0 0 1 1 1]\n", - "Running the 465 iteration\n", - "[1 1 1 1 1 0 1 1 0 1 0 1 0 0 1 0 0 0 0 1 0]\n", - "Running the 466 iteration\n", - "[0 1 1 0 1 1 1 0 1 1 1 0 1 1 0 0 0 0 0 0 1]\n", - "Running the 467 iteration\n", - "[1 0 0 0 0 1 1 0 1 1 1 1 0 1 0 1 0 0 1 1 0]\n", - "Running the 468 iteration\n", - "[0 0 1 1 0 0 1 1 1 1 1 0 0 0 1 0 1 1 0 0 1]\n", - "Running the 469 iteration\n", - "[0 1 0 1 1 1 0 0 0 0 1 0 1 0 1 1 1 0 1 0 1]\n", - "Running the 470 iteration\n", - "[1 0 0 0 0 1 0 1 1 1 0 1 0 0 1 1 0 1 0 1 1]\n", - "Running the 471 iteration\n", - "[1 1 1 0 0 0 1 0 1 1 1 1 1 0 1 0 0 0 0 1 0]\n", - "Running the 472 iteration\n", - "[1 1 1 1 0 1 0 1 1 1 0 0 1 0 1 0 0 0 0 0 1]\n", - "Running the 473 iteration\n", - "[0 1 1 1 0 0 0 1 0 1 1 1 0 0 1 1 1 0 1 0 0]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Running the 474 iteration\n", - "[0 0 1 1 0 1 1 0 0 0 1 0 0 0 1 0 1 1 1 1 1]\n", - "Running the 475 iteration\n", - "[0 1 1 0 0 0 1 0 0 1 0 0 1 0 1 1 1 1 1 1 0]\n", - "Running the 476 iteration\n", - "[1 0 0 0 0 0 1 1 0 1 1 0 0 1 0 1 0 1 1 1 1]\n", - "Running the 477 iteration\n", - "[1 1 0 1 0 0 1 0 1 1 0 1 1 1 0 0 1 0 0 0 1]\n", - "Running the 478 iteration\n", - "[0 1 0 0 0 1 0 1 1 1 1 0 1 1 1 0 0 1 1 0 0]\n", - "Running the 479 iteration\n", - "[1 0 1 1 0 1 1 0 1 0 0 1 0 0 1 1 0 1 0 1 0]\n", - "Running the 480 iteration\n", - "[1 0 1 0 0 0 1 0 1 1 0 1 1 1 1 0 0 1 1 0 0]\n", - "Running the 481 iteration\n", - "[1 1 1 1 0 0 0 1 0 1 1 1 0 0 1 0 1 1 0 0 0]\n", - "Running the 482 iteration\n", - "[1 1 1 0 1 0 1 1 1 0 0 0 1 1 0 0 0 0 1 1 0]\n", - "Running the 483 iteration\n", - "[1 1 1 0 0 1 1 0 0 0 1 1 1 1 0 0 1 0 0 1 0]\n", - "Running the 484 iteration\n", - "[1 0 1 1 0 1 1 1 1 1 1 0 0 0 1 0 0 0 0 1 0]\n", - "Running the 485 iteration\n", - "[1 1 1 0 1 1 1 1 0 0 1 0 0 1 1 0 1 0 0 0 0]\n", - "Running the 486 iteration\n", - "[0 0 0 1 0 1 0 1 1 1 1 0 1 0 1 1 1 0 0 0 1]\n", - "Running the 487 iteration\n", - "[0 0 1 1 1 1 0 1 0 0 0 1 0 0 1 1 0 1 1 1 0]\n", - "Running the 488 iteration\n", - "[1 0 0 1 0 1 1 1 0 1 1 0 0 1 0 1 1 1 0 0 0]\n", - "Running the 489 iteration\n", - "[1 0 0 1 1 0 0 0 0 1 1 0 1 1 0 1 1 1 1 0 0]\n", - "Running the 490 iteration\n", - "[1 1 1 1 1 0 0 1 1 0 0 0 1 0 0 0 1 0 0 1 1]\n", - "Running the 491 iteration\n", - "[1 1 1 0 0 0 0 1 1 1 1 0 1 1 1 0 1 0 0 0 0]\n", - "Running the 492 iteration\n", - "[0 0 0 1 1 0 1 1 0 1 0 0 0 1 1 1 1 0 1 1 0]\n", - "Running the 493 iteration\n", - "[1 0 0 0 1 0 0 0 1 1 0 1 0 1 1 1 0 1 0 1 1]\n", - "Running the 494 iteration\n", - "[0 1 0 0 0 1 1 1 1 0 0 1 0 0 1 1 0 1 1 0 1]\n", - "Running the 495 iteration\n", - "[1 1 0 0 0 0 1 0 0 0 1 1 1 1 1 0 0 1 1 0 1]\n", - "Running the 496 iteration\n", - "[0 0 0 0 1 0 1 0 0 1 1 1 1 1 1 1 1 0 1 0 0]\n", - "Running the 497 iteration\n", - "[1 1 0 0 1 0 1 0 0 1 1 0 0 1 0 1 0 1 1 1 0]\n", - "Running the 498 iteration\n", - "[0 1 1 1 0 0 0 1 1 1 1 1 1 1 0 0 0 0 0 1 0]\n", - "Running the 499 iteration\n", - "[1 1 0 0 1 1 0 0 1 0 1 1 0 0 1 1 0 1 0 0 1]\n", - "Running the 500 iteration\n", - "[1 0 1 1 1 0 0 0 0 1 1 0 1 0 0 1 0 1 1 0 1]\n", - "Running the 501 iteration\n", - "[1 0 1 0 1 1 0 0 1 1 0 1 1 1 0 1 0 0 0 0 1]\n", - "Running the 502 iteration\n", - "[1 0 1 1 1 1 0 0 1 0 1 0 0 0 1 1 0 0 0 1 1]\n", - "Running the 503 iteration\n", - "[1 0 1 0 1 0 0 1 1 1 0 0 0 1 0 0 1 1 0 1 1]\n", - "Running the 504 iteration\n", - "[1 0 0 0 1 0 0 0 1 0 1 1 0 1 1 1 0 1 1 0 1]\n", - "Running the 505 iteration\n", - "[1 1 0 1 0 1 1 1 1 1 0 0 1 0 0 0 0 0 1 1 0]\n", - "Running the 506 iteration\n", - "[0 0 0 1 1 0 1 1 1 0 0 0 0 1 1 0 1 1 1 0 1]\n", - "Running the 507 iteration\n", - "[0 0 0 1 1 1 1 0 0 0 0 1 1 1 1 0 1 1 0 1 0]\n", - "Running the 508 iteration\n", - "[0 0 1 1 0 0 1 1 0 1 1 0 1 1 0 0 0 1 1 1 0]\n", - "Running the 509 iteration\n", - "[0 1 0 0 1 1 0 0 0 1 1 1 1 0 1 0 0 1 1 1 0]\n", - "Running the 510 iteration\n", - "[0 1 1 1 1 0 1 0 0 1 0 1 0 1 0 1 1 0 0 1 0]\n", - "Running the 511 iteration\n", - "[1 1 1 1 0 0 0 1 1 0 0 0 0 1 1 0 1 1 0 0 1]\n", - "Running the 512 iteration\n", - "[1 0 0 1 0 0 0 1 1 1 1 0 0 0 0 0 1 1 1 1 1]\n", - "Running the 513 iteration\n", - "[0 1 0 0 1 1 1 0 1 1 0 0 1 1 1 0 0 1 0 0 1]\n", - "Running the 514 iteration\n", - "[0 1 1 1 0 0 0 0 1 0 0 1 0 0 1 1 1 0 1 1 1]\n", - "Running the 515 iteration\n", - "[1 1 1 1 0 0 1 1 0 0 0 0 0 0 0 1 1 1 0 1 1]\n", - "Running the 516 iteration\n", - "[0 0 1 1 0 0 1 0 0 1 0 1 1 1 1 0 0 1 0 1 1]\n", - "Running the 517 iteration\n", - "[0 1 0 1 1 0 0 1 0 1 0 0 1 1 1 1 0 1 0 0 1]\n", - "Running the 518 iteration\n", - "[1 0 0 1 0 1 1 0 0 1 1 1 0 0 1 0 1 1 0 1 0]\n", - "Running the 519 iteration\n", - "[0 0 0 1 0 1 0 1 1 0 1 1 1 1 1 1 0 0 0 0 1]\n", - "Running the 520 iteration\n", - "[0 1 1 0 0 0 1 1 1 1 1 0 0 1 0 0 0 1 1 1 0]\n", - "Running the 521 iteration\n", - "[1 0 0 0 0 1 1 1 0 0 0 1 1 0 1 0 0 1 1 1 1]\n", - "Running the 522 iteration\n", - "[1 0 0 1 0 1 1 1 1 1 0 0 1 0 1 1 0 0 0 0 1]\n", - "Running the 523 iteration\n", - "[1 1 1 1 0 0 1 1 0 1 0 1 1 0 1 0 0 1 0 0 0]\n", - "Running the 524 iteration\n", - "[1 1 0 0 0 1 1 0 1 1 0 1 0 0 0 1 0 0 1 1 1]\n", - "Running the 525 iteration\n", - "[1 1 1 0 1 0 0 1 1 1 0 1 1 0 0 0 1 0 1 0 0]\n", - "Running the 526 iteration\n", - "[1 1 0 0 1 1 0 0 1 1 1 0 0 1 0 0 1 0 1 0 1]\n", - "Running the 527 iteration\n", - "[1 0 0 0 1 0 1 1 0 0 1 0 1 0 1 1 0 0 1 1 1]\n", - "Running the 528 iteration\n", - "[0 1 0 1 1 1 0 1 0 1 0 1 0 1 0 0 1 1 0 0 1]\n", - "Running the 529 iteration\n", - "[0 1 1 1 1 1 0 0 0 1 0 0 0 0 1 0 1 1 1 1 0]\n", - "Running the 530 iteration\n", - "[1 1 0 0 1 1 0 1 0 1 0 1 1 1 0 0 1 0 0 0 1]\n", - "Running the 531 iteration\n", - "[1 0 0 0 1 1 0 1 1 0 1 0 0 1 1 0 1 0 1 0 1]\n", - "Running the 532 iteration\n", - "[1 0 1 1 0 0 0 0 0 1 1 0 1 1 1 1 0 0 0 1 1]\n", - "Running the 533 iteration\n", - "[1 1 1 1 0 1 1 0 0 1 0 0 0 1 0 1 1 1 0 0 0]\n", - "Running the 534 iteration\n", - "[1 1 1 1 0 0 1 0 0 0 1 1 1 0 0 0 1 0 1 0 1]\n", - "Running the 535 iteration\n", - "[1 1 0 0 1 1 1 0 0 1 1 1 0 1 0 0 0 1 0 0 1]\n", - "Running the 536 iteration\n", - "[1 1 1 1 1 1 0 0 1 0 0 0 0 0 0 1 1 1 0 0 1]\n", - "Running the 537 iteration\n", - "[1 1 1 0 1 1 0 0 0 0 1 0 0 1 1 1 0 0 1 1 0]\n", - "Running the 538 iteration\n", - "[1 1 1 1 1 1 1 0 1 1 0 0 0 0 0 0 0 1 1 0 0]\n", - "Running the 539 iteration\n", - "[0 0 0 1 1 0 1 0 0 1 0 1 0 0 1 1 0 1 1 1 1]\n", - "Running the 540 iteration\n", - "[1 0 1 1 0 1 0 0 1 0 0 0 1 1 1 0 0 0 1 1 1]\n", - "Running the 541 iteration\n", - "[0 1 1 0 0 1 1 1 0 1 0 1 0 1 1 1 0 0 0 0 1]\n", - "Running the 542 iteration\n", - "[1 1 0 0 0 0 1 1 1 1 1 1 0 0 0 1 0 1 1 0 0]\n", - "Running the 543 iteration\n", - "[0 1 0 0 1 1 0 0 0 1 0 0 0 1 1 1 1 1 1 1 0]\n", - "Running the 544 iteration\n", - "[1 1 1 0 0 0 0 1 0 1 1 1 1 0 0 0 1 0 1 1 0]\n", - "Running the 545 iteration\n", - "[0 0 1 1 1 0 1 1 1 0 1 0 1 0 1 1 0 1 0 0 0]\n", - "Running the 546 iteration\n", - "[1 0 1 0 0 1 1 1 1 0 0 0 1 0 1 0 0 1 1 0 1]\n", - "Running the 547 iteration\n", - "[0 0 0 0 1 1 0 0 0 1 1 0 1 1 1 1 0 1 1 1 0]\n", - "Running the 548 iteration\n", - "[0 1 1 1 1 1 0 1 1 0 0 1 1 0 0 1 0 1 0 0 0]\n", - "Running the 549 iteration\n", - "[0 0 1 1 1 1 1 0 0 1 0 1 1 0 0 0 0 1 0 1 1]\n", - "Running the 550 iteration\n", - "[1 0 1 1 1 0 0 0 1 0 0 1 0 0 1 0 0 1 1 1 1]\n", - "Running the 551 iteration\n", - "[0 0 0 0 1 0 0 0 0 1 1 1 0 1 1 1 1 1 1 0 1]\n", - "Running the 552 iteration\n", - "[0 1 1 1 1 1 1 1 0 0 0 0 1 1 0 0 1 0 0 1 0]\n", - "Running the 553 iteration\n", - "[1 1 0 1 1 1 0 0 0 1 0 1 0 1 1 0 0 1 1 0 0]\n", - "Running the 554 iteration\n", - "[0 0 1 0 1 1 1 1 0 1 0 1 1 0 1 1 0 0 1 0 0]\n", - "Running the 555 iteration\n", - "[0 1 0 0 1 1 1 1 0 0 1 0 1 0 1 0 1 1 0 1 0]\n", - "Running the 556 iteration\n", - "[1 1 1 1 1 0 0 1 1 0 0 1 0 0 1 1 0 0 0 1 0]\n", - "Running the 557 iteration\n", - "[1 1 0 0 0 1 1 1 0 1 1 0 0 0 0 0 1 1 1 0 1]\n", - "Running the 558 iteration\n", - "[0 0 0 0 1 0 1 1 0 1 1 0 0 1 1 0 1 0 1 1 1]\n", - "Running the 559 iteration\n", - "[0 1 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 1 0]\n", - "Running the 560 iteration\n", - "[0 1 1 0 0 1 1 1 1 0 1 0 0 0 0 1 0 1 1 0 1]\n", - "Running the 561 iteration\n", - "[0 1 0 0 0 1 1 0 1 1 1 1 1 1 0 1 0 1 0 0 0]\n", - "Running the 562 iteration\n", - "[1 0 1 1 0 0 1 0 1 0 1 1 1 1 0 0 1 0 0 0 1]\n", - "Running the 563 iteration\n", - "[0 0 0 1 1 1 0 0 0 1 1 0 1 1 1 1 0 0 1 1 0]\n", - "Running the 564 iteration\n", - "[0 1 1 0 1 0 1 1 1 0 0 0 0 0 1 1 0 1 1 1 0]\n", - "Running the 565 iteration\n", - "[1 1 0 0 1 0 1 0 0 1 1 0 1 1 1 0 1 0 0 1 0]\n", - "Running the 566 iteration\n", - "[1 0 1 1 0 1 0 1 1 1 0 0 1 0 0 0 1 0 1 1 0]\n", - "Running the 567 iteration\n", - "[1 1 0 0 0 1 1 1 0 1 0 1 0 1 0 1 0 0 1 1 0]\n", - "Running the 568 iteration\n", - "[0 0 0 1 1 0 1 0 1 0 1 1 1 1 0 1 1 0 0 1 0]\n", - "Running the 569 iteration\n", - "[0 1 1 1 0 0 1 1 0 0 1 0 1 1 0 0 1 1 0 0 1]\n", - "Running the 570 iteration\n", - "[1 0 1 1 0 0 1 1 1 1 0 0 0 0 0 1 0 0 1 1 1]\n", - "Running the 571 iteration\n", - "[1 1 1 0 0 0 0 1 1 1 0 0 1 0 0 1 0 1 1 0 1]\n", - "Running the 572 iteration\n", - "[0 1 1 1 0 1 0 0 0 1 0 0 0 1 1 0 1 1 0 1 1]\n", - "Running the 573 iteration\n", - "[0 0 1 1 1 0 1 1 0 1 0 1 0 0 1 0 1 0 0 1 1]\n", - "Running the 574 iteration\n", - "[0 0 0 1 1 1 1 1 0 0 0 1 1 0 1 1 0 1 0 0 1]\n", - "Running the 575 iteration\n", - "[0 0 1 1 0 0 1 1 1 0 1 0 1 0 0 1 1 1 1 0 0]\n", - "Running the 576 iteration\n", - "[1 1 1 1 0 1 0 0 0 1 0 1 1 1 1 1 0 0 0 0 0]\n", - "Running the 577 iteration\n", - "[0 1 0 1 0 1 1 0 1 1 1 0 0 0 1 1 1 1 0 0 0]\n", - "Running the 578 iteration\n", - "[1 0 0 1 0 0 1 1 1 0 1 0 0 1 1 0 0 1 0 1 1]\n", - "Running the 579 iteration\n", - "[0 1 1 1 0 1 0 1 1 1 0 0 0 0 0 0 1 1 0 1 1]\n", - "Running the 580 iteration\n", - "[1 1 0 0 0 0 1 1 0 0 1 1 0 1 1 0 1 1 0 0 1]\n", - "Running the 581 iteration\n", - "[0 1 1 1 0 1 0 1 1 0 0 1 0 1 1 0 0 1 0 0 1]\n", - "Running the 582 iteration\n", - "[1 0 0 1 0 0 0 0 1 1 0 0 1 1 1 1 0 1 1 0 1]\n", - "Running the 583 iteration\n", - "[0 1 0 1 0 0 0 0 1 1 1 0 1 1 0 1 1 0 0 1 1]\n", - "Running the 584 iteration\n", - "[1 1 1 0 1 0 0 1 1 0 1 0 0 1 0 0 1 1 0 1 0]\n", - "Running the 585 iteration\n", - "[1 1 0 1 0 1 0 0 1 0 1 1 1 0 0 1 0 1 0 0 1]\n", - "Running the 586 iteration\n", - "[1 0 0 0 0 1 1 1 1 1 0 0 0 1 1 1 0 1 0 0 1]\n", - "Running the 587 iteration\n", - "[0 1 0 0 1 1 1 0 0 1 1 0 0 1 1 0 1 0 1 1 0]\n", - "Running the 588 iteration\n", - "[1 1 0 0 0 1 1 0 1 0 1 0 0 1 1 1 0 0 1 0 1]\n", - "Running the 589 iteration\n", - "[0 0 1 1 0 0 1 1 1 0 1 0 1 1 0 1 0 0 0 1 1]\n", - "Running the 590 iteration\n", - "[1 0 1 1 0 0 0 1 1 0 0 1 1 1 0 1 0 1 1 0 0]\n", - "Running the 591 iteration\n", - "[0 1 0 1 1 1 1 0 1 1 1 1 0 0 0 0 0 0 1 1 0]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Running the 592 iteration\n", - "[1 0 1 1 0 1 1 1 0 1 1 0 0 0 1 1 0 1 0 0 0]\n", - "Running the 593 iteration\n", - "[0 1 0 0 1 1 0 1 1 1 1 0 0 0 1 1 0 1 0 1 0]\n", - "Running the 594 iteration\n", - "[1 1 1 1 1 0 0 0 1 0 1 0 1 0 1 0 1 1 0 0 0]\n", - "Running the 595 iteration\n", - "[0 1 0 1 0 1 1 1 1 0 0 0 0 1 1 0 1 0 0 1 1]\n", - "Running the 596 iteration\n", - "[1 1 0 0 0 0 1 1 0 0 1 1 1 1 1 1 0 0 1 0 0]\n", - "Running the 597 iteration\n", - "[0 1 0 1 0 1 0 0 1 1 1 0 1 0 0 1 1 1 1 0 0]\n", - "Running the 598 iteration\n", - "[1 0 1 0 0 1 1 0 1 0 1 0 0 1 0 1 1 1 0 1 0]\n", - "Running the 599 iteration\n", - "[1 1 0 0 0 0 1 1 1 0 1 1 0 0 0 1 1 0 0 1 1]\n", - "Running the 600 iteration\n", - "[0 0 1 0 1 1 1 0 1 1 0 1 0 1 0 1 0 1 1 0 0]\n", - "Running the 601 iteration\n", - "[1 1 0 0 1 0 0 1 1 0 0 1 1 1 1 0 0 1 0 0 1]\n", - "Running the 602 iteration\n", - "[1 0 1 1 1 1 0 1 0 1 1 0 0 0 1 1 0 0 1 0 0]\n", - "Running the 603 iteration\n", - "[1 1 0 0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0 1 0]\n", - "Running the 604 iteration\n", - "[0 1 1 1 1 0 0 0 0 0 1 1 0 1 1 1 0 1 0 0 1]\n", - "Running the 605 iteration\n", - "[0 0 1 1 0 1 1 1 1 0 1 0 0 0 0 1 1 1 0 1 0]\n", - "Running the 606 iteration\n", - "[0 1 1 0 0 1 0 1 1 1 1 0 0 1 1 1 0 0 0 1 0]\n", - "Running the 607 iteration\n", - "[0 1 0 0 1 1 1 0 0 0 1 0 1 1 1 0 0 0 1 1 1]\n", - "Running the 608 iteration\n", - "[1 1 0 1 1 0 1 1 1 0 0 1 1 0 1 0 0 0 0 1 0]\n", - "Running the 609 iteration\n", - "[1 0 1 1 1 0 0 0 1 0 1 0 0 0 1 1 1 1 0 0 1]\n", - "Running the 610 iteration\n", - "[0 1 1 1 1 1 0 0 0 0 0 0 1 0 1 1 1 0 1 1 0]\n", - "Running the 611 iteration\n", - "[1 0 0 0 0 0 0 0 1 1 1 1 1 1 0 1 1 0 1 1 0]\n", - "Running the 612 iteration\n", - "[0 0 0 1 0 1 1 1 0 1 1 1 1 0 0 1 1 0 0 1 0]\n", - "Running the 613 iteration\n", - "[0 0 1 1 1 1 0 1 0 0 1 1 0 1 1 1 0 0 1 0 0]\n", - "Running the 614 iteration\n", - "[0 0 0 0 0 1 0 1 1 1 0 0 1 0 1 1 1 1 1 0 1]\n", - "Running the 615 iteration\n", - "[1 1 0 1 0 0 1 0 0 0 0 0 0 1 1 0 1 1 1 1 1]\n", - "Running the 616 iteration\n", - "[1 0 1 1 1 1 0 1 0 0 0 1 0 0 1 0 0 1 0 1 1]\n", - "Running the 617 iteration\n", - "[1 1 0 1 1 1 0 1 0 0 1 0 0 1 0 1 0 1 0 0 1]\n", - "Running the 618 iteration\n", - "[0 1 0 1 1 1 0 1 0 1 1 1 0 0 0 1 0 1 0 0 1]\n", - "Running the 619 iteration\n", - "[0 1 1 1 1 1 1 0 0 1 1 0 0 1 0 0 0 0 0 1 1]\n", - "Running the 620 iteration\n", - "[0 0 0 1 0 0 1 1 0 1 0 0 1 0 1 1 1 1 1 0 1]\n", - "Running the 621 iteration\n", - "[1 1 1 0 0 1 0 0 1 0 0 0 1 0 1 0 1 0 1 1 1]\n", - "Running the 622 iteration\n", - "[1 1 1 0 0 0 0 0 0 0 0 1 1 1 1 0 1 1 1 0 1]\n", - "Running the 623 iteration\n", - "[0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 1 0 0 0 1]\n", - "Running the 624 iteration\n", - "[1 0 1 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 0 0 1]\n", - "Running the 625 iteration\n", - "[1 1 0 1 0 0 0 1 1 1 0 0 1 1 1 1 0 0 1 0 0]\n", - "Running the 626 iteration\n", - "[0 0 1 0 1 0 1 0 1 1 1 0 1 1 0 0 1 0 1 0 1]\n", - "Running the 627 iteration\n", - "[1 1 1 1 1 0 0 0 1 0 0 0 1 1 1 0 0 1 0 0 1]\n", - "Running the 628 iteration\n", - "[1 1 0 0 1 1 1 0 0 0 1 1 0 1 0 0 1 1 0 1 0]\n", - "Running the 629 iteration\n", - "[1 1 1 0 0 1 1 1 1 0 1 0 1 0 0 1 1 0 0 0 0]\n", - "Running the 630 iteration\n", - "[1 0 1 1 0 1 1 1 0 0 0 0 0 1 1 0 1 1 0 1 0]\n", - "Running the 631 iteration\n", - "[1 0 0 1 0 1 1 0 0 0 0 1 0 1 1 0 0 1 1 1 1]\n", - "Running the 632 iteration\n", - "[1 1 0 0 1 0 1 1 1 0 0 0 1 0 1 1 1 0 0 0 1]\n", - "Running the 633 iteration\n", - "[0 1 0 1 1 0 0 1 0 0 0 0 1 0 1 1 1 1 1 1 0]\n", - "Running the 634 iteration\n", - "[1 1 1 1 0 0 0 0 0 1 1 1 0 0 0 0 1 1 1 1 0]\n", - "Running the 635 iteration\n", - "[0 1 0 0 1 1 0 1 1 1 0 0 1 0 1 1 0 1 1 0 0]\n", - "Running the 636 iteration\n", - "[0 0 0 0 1 0 1 0 1 0 1 0 1 1 1 1 1 1 0 1 0]\n", - "Running the 637 iteration\n", - "[0 1 1 1 0 0 0 1 1 1 1 1 0 0 1 0 0 0 1 1 0]\n", - "Running the 638 iteration\n", - "[0 1 0 1 0 0 0 1 1 1 1 0 0 0 1 1 1 1 0 1 0]\n", - "Running the 639 iteration\n", - "[1 0 1 0 1 1 0 0 1 1 1 1 0 1 1 0 0 0 0 1 0]\n", - "Running the 640 iteration\n", - "[0 0 0 0 1 1 0 1 1 0 1 0 1 0 1 1 0 0 1 1 1]\n", - "Running the 641 iteration\n", - "[0 0 0 1 0 1 1 1 1 0 1 1 0 0 1 1 0 1 0 1 0]\n", - "Running the 642 iteration\n", - "[0 0 0 0 1 1 1 0 1 1 1 1 0 0 1 1 1 0 1 0 0]\n", - "Running the 643 iteration\n", - "[1 1 0 1 1 1 0 0 0 0 1 1 1 0 0 1 1 0 0 0 1]\n", - "Running the 644 iteration\n", - "[1 0 0 0 1 1 0 0 1 0 1 0 0 1 1 1 1 0 0 1 1]\n", - "Running the 645 iteration\n", - "[1 0 0 1 0 0 1 1 0 0 0 1 1 1 0 0 0 1 1 1 1]\n", - "Running the 646 iteration\n", - "[0 1 0 0 1 1 0 1 1 1 0 1 0 1 0 0 0 1 0 1 1]\n", - "Running the 647 iteration\n", - "[0 1 1 0 0 1 0 0 0 1 1 1 1 0 0 1 1 0 0 1 1]\n", - "Running the 648 iteration\n", - "[1 0 1 0 1 1 0 1 0 1 0 1 0 1 1 0 0 0 1 1 0]\n", - "Running the 649 iteration\n", - "[0 1 1 0 1 0 0 0 1 1 0 1 1 0 1 0 1 0 1 0 1]\n", - "Running the 650 iteration\n", - "[1 0 0 0 1 0 1 0 0 1 1 1 0 1 0 1 1 1 0 0 1]\n", - "Running the 651 iteration\n", - "[1 0 0 1 0 0 1 0 1 0 0 1 0 1 1 1 0 0 1 1 1]\n", - "Running the 652 iteration\n", - "[1 0 1 1 0 0 1 0 1 0 0 1 0 0 0 1 1 0 1 1 1]\n", - "Running the 653 iteration\n", - "[0 1 1 1 1 0 1 0 0 0 1 0 1 1 0 1 0 0 1 1 0]\n", - "Running the 654 iteration\n", - "[0 1 0 1 0 0 1 1 1 1 1 1 1 1 0 0 0 0 1 0 0]\n", - "Running the 655 iteration\n", - "[0 0 0 1 1 0 0 1 1 0 1 1 0 1 0 1 0 1 1 0 1]\n", - "Running the 656 iteration\n", - "[0 0 0 1 0 1 0 1 0 1 1 1 0 1 1 0 0 1 1 0 1]\n", - "Running the 657 iteration\n", - "[0 1 1 0 0 0 1 0 1 0 1 0 1 1 1 1 1 0 1 0 0]\n", - "Running the 658 iteration\n", - "[0 0 1 1 0 1 1 0 1 0 0 0 0 0 0 1 1 1 1 1 1]\n", - "Running the 659 iteration\n", - "[1 1 1 1 1 1 0 0 0 0 0 1 0 0 0 1 0 1 1 1 0]\n", - "Running the 660 iteration\n", - "[0 1 0 1 0 0 1 0 0 1 1 0 0 1 1 0 0 1 1 1 1]\n", - "Running the 661 iteration\n", - "[0 1 1 1 1 0 1 1 0 0 1 0 1 0 1 0 1 0 0 0 1]\n", - "Running the 662 iteration\n", - "[0 0 1 1 0 1 0 0 1 1 1 0 1 1 1 1 0 0 1 0 0]\n", - "Running the 663 iteration\n", - "[1 0 1 0 1 0 1 1 1 0 1 0 0 1 0 0 1 0 1 0 1]\n", - "Running the 664 iteration\n", - "[1 1 1 0 0 0 1 0 0 1 0 1 0 1 0 1 1 0 1 1 0]\n", - "Running the 665 iteration\n", - "[0 1 1 0 1 0 0 0 1 1 1 0 0 1 1 0 1 0 1 1 0]\n", - "Running the 666 iteration\n", - "[0 1 1 0 0 0 1 1 1 0 1 1 1 0 1 1 0 1 0 0 0]\n", - "Running the 667 iteration\n", - "[0 1 0 1 1 1 0 1 1 0 0 1 0 1 0 1 0 1 0 1 0]\n", - "Running the 668 iteration\n", - "[1 0 0 1 1 1 1 1 0 0 0 1 1 0 1 0 0 1 0 1 0]\n", - "Running the 669 iteration\n", - "[0 0 1 0 1 1 1 0 0 1 0 1 0 1 1 0 0 1 1 1 0]\n", - "Running the 670 iteration\n", - "[1 1 0 1 1 0 0 1 0 1 1 0 1 0 1 1 0 0 0 0 1]\n", - "Running the 671 iteration\n", - "[0 1 0 1 1 1 1 1 1 0 1 0 0 0 1 0 0 0 1 1 0]\n", - "Running the 672 iteration\n", - "[0 1 0 0 0 0 0 0 1 1 1 1 0 0 1 1 1 1 1 0 1]\n", - "Running the 673 iteration\n", - "[1 1 0 0 0 1 1 0 0 0 0 0 1 1 1 1 0 1 0 1 1]\n", - "Running the 674 iteration\n", - "[1 0 1 0 0 1 0 0 0 1 1 1 1 0 1 0 1 0 0 1 1]\n", - "Running the 675 iteration\n", - "[0 1 0 1 0 0 1 0 1 0 0 1 1 1 1 0 1 0 1 0 1]\n", - "Running the 676 iteration\n", - "[1 0 0 1 0 1 1 1 0 0 1 0 0 1 0 0 1 1 1 0 1]\n", - "Running the 677 iteration\n", - "[0 1 1 1 0 1 1 0 1 1 1 0 0 0 1 1 0 0 0 0 1]\n", - "Running the 678 iteration\n", - "[1 1 0 1 0 1 1 1 1 0 1 0 0 1 0 1 0 0 0 0 1]\n", - "Running the 679 iteration\n", - "[0 0 1 1 0 1 1 1 0 1 0 1 1 1 0 0 1 1 0 0 0]\n", - "Running the 680 iteration\n", - "[0 1 0 1 0 1 0 1 1 0 1 1 0 0 1 1 0 1 0 0 1]\n", - "Running the 681 iteration\n", - "[1 0 0 0 1 1 0 0 1 1 0 1 0 1 0 1 1 0 1 1 0]\n", - "Running the 682 iteration\n", - "[1 1 1 1 1 1 1 0 0 1 1 0 0 1 0 0 1 0 0 0 0]\n", - "Running the 683 iteration\n", - "[0 1 1 0 1 0 1 0 1 1 0 1 0 1 1 0 0 0 1 1 0]\n", - "Running the 684 iteration\n", - "[0 1 1 0 0 0 1 0 1 1 0 1 0 1 1 1 1 0 1 0 0]\n", - "Running the 685 iteration\n", - "[0 1 1 0 0 0 0 0 1 1 1 0 1 1 1 1 0 0 1 1 0]\n", - "Running the 686 iteration\n", - "[1 0 0 1 1 1 0 1 0 0 1 0 1 0 1 1 1 1 0 0 0]\n", - "Running the 687 iteration\n", - "[1 1 1 0 1 0 1 0 1 0 1 1 0 1 1 0 0 0 0 0 1]\n", - "Running the 688 iteration\n", - "[0 1 1 1 0 1 0 1 0 0 0 1 1 0 1 1 0 1 1 0 0]\n", - "Running the 689 iteration\n", - "[1 0 1 1 1 0 1 0 0 1 1 1 0 0 0 1 1 0 1 0 0]\n", - "Running the 690 iteration\n", - "[1 1 0 0 1 0 1 1 0 1 1 0 0 0 1 1 0 0 1 0 1]\n", - "Running the 691 iteration\n", - "[1 0 1 0 1 0 0 0 1 1 1 1 1 0 0 1 1 0 1 0 0]\n", - "Running the 692 iteration\n", - "[1 0 1 0 0 1 1 0 0 1 1 1 0 1 0 0 1 1 0 1 0]\n", - "Running the 693 iteration\n", - "[1 0 0 1 0 1 1 1 0 1 0 1 1 0 0 1 1 0 0 0 1]\n", - "Running the 694 iteration\n", - "[0 0 1 0 1 1 1 0 1 1 1 1 0 0 1 0 0 1 1 0 0]\n", - "Running the 695 iteration\n", - "[0 0 1 1 1 1 0 0 0 1 0 1 0 1 0 1 0 1 1 0 1]\n", - "Running the 696 iteration\n", - "[1 0 0 0 0 0 1 1 0 1 1 1 0 0 1 0 1 1 1 1 0]\n", - "Running the 697 iteration\n", - "[0 0 1 1 0 0 0 1 0 1 1 1 1 0 1 0 0 0 1 1 1]\n", - "Running the 698 iteration\n", - "[1 0 1 1 1 0 1 1 1 0 1 0 1 1 0 1 0 0 0 0 0]\n", - "Running the 699 iteration\n", - "[0 0 1 1 1 0 0 1 1 1 0 0 1 0 0 1 1 0 1 0 1]\n", - "Running the 700 iteration\n", - "[0 1 0 0 0 1 0 1 1 0 1 1 1 1 0 0 1 0 1 0 1]\n", - "Running the 701 iteration\n", - "[1 1 1 1 0 1 1 0 0 0 0 0 0 1 1 0 1 1 1 0 0]\n", - "Running the 702 iteration\n", - "[1 0 0 1 1 1 1 0 1 1 0 1 0 0 0 1 0 1 0 1 0]\n", - "Running the 703 iteration\n", - "[0 1 0 0 1 1 0 0 1 0 1 0 1 1 1 0 0 0 1 1 1]\n", - "Running the 704 iteration\n", - "[1 0 0 1 1 0 0 1 0 1 1 0 1 0 0 1 1 1 1 0 0]\n", - "Running the 705 iteration\n", - "[1 0 1 0 1 0 0 0 0 0 1 1 1 1 0 0 1 1 0 1 1]\n", - "Running the 706 iteration\n", - "[0 0 0 1 1 1 1 0 0 1 1 0 1 0 0 1 1 0 0 1 1]\n", - "Running the 707 iteration\n", - "[1 0 1 1 1 1 0 0 0 0 0 1 0 0 0 1 1 1 1 0 1]\n", - "Running the 708 iteration\n", - "[0 1 1 1 0 1 1 1 0 0 1 1 0 1 0 0 0 1 0 1 0]\n", - "Running the 709 iteration\n", - "[1 0 0 1 1 0 0 1 1 1 0 1 1 0 0 0 0 0 1 1 1]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Running the 710 iteration\n", - "[0 1 1 1 1 1 0 1 0 0 0 0 1 0 1 0 1 1 0 0 1]\n", - "Running the 711 iteration\n", - "[1 0 0 1 0 1 0 1 0 1 0 0 1 0 0 1 1 1 0 1 1]\n", - "Running the 712 iteration\n", - "[0 1 1 1 1 0 0 0 1 1 0 1 0 1 0 0 1 1 0 0 1]\n", - "Running the 713 iteration\n", - "[0 0 0 1 1 0 0 1 1 1 0 1 1 1 0 0 0 1 1 0 1]\n", - "Running the 714 iteration\n", - "[1 1 1 0 1 0 1 1 1 0 1 0 1 0 0 0 0 1 0 0 1]\n", - "Running the 715 iteration\n", - "[0 1 0 0 1 1 1 1 0 1 1 1 0 1 0 1 0 0 0 1 0]\n", - "Running the 716 iteration\n", - "[0 0 0 1 0 0 1 1 1 0 1 0 1 1 1 0 0 1 0 1 1]\n", - "Running the 717 iteration\n", - "[1 0 0 0 1 1 0 1 1 0 1 1 0 0 1 0 0 1 1 0 1]\n", - "Running the 718 iteration\n", - "[1 0 1 1 1 1 0 1 1 0 0 1 0 1 1 0 0 1 0 0 0]\n", - "Running the 719 iteration\n", - "[1 0 1 0 1 1 0 1 1 1 1 0 0 0 1 0 0 1 0 1 0]\n", - "Running the 720 iteration\n", - "[0 0 1 0 1 1 0 1 1 1 0 0 0 1 1 1 0 1 1 0 0]\n", - "Running the 721 iteration\n", - "[1 1 0 0 1 0 1 1 0 1 0 1 1 0 0 0 0 1 1 0 1]\n", - "Running the 722 iteration\n", - "[1 1 1 0 0 1 0 1 1 0 0 1 0 1 1 0 1 0 0 1 0]\n", - "Running the 723 iteration\n", - "[1 0 0 0 1 0 0 1 1 0 1 0 1 1 1 1 0 1 0 0 1]\n", - "Running the 724 iteration\n", - "[1 1 0 0 0 1 1 1 0 0 0 0 0 1 0 1 1 1 0 1 1]\n", - "Running the 725 iteration\n", - "[0 0 1 1 0 1 1 0 1 0 0 1 1 1 0 1 1 0 0 0 1]\n", - "Running the 726 iteration\n", - "[0 1 1 1 1 0 1 1 0 0 0 0 1 1 0 1 1 0 0 0 1]\n", - "Running the 727 iteration\n", - "[1 0 1 1 1 0 1 0 1 0 0 1 1 0 0 1 0 0 1 0 1]\n", - "Running the 728 iteration\n", - "[0 0 0 1 1 1 1 0 1 0 1 1 0 0 0 1 1 0 1 0 1]\n", - "Running the 729 iteration\n", - "[1 0 0 1 1 0 0 1 0 1 1 0 1 0 0 1 1 1 0 1 0]\n", - "Running the 730 iteration\n", - "[1 0 1 1 0 1 0 1 1 0 0 1 0 0 1 0 1 0 1 0 1]\n", - "Running the 731 iteration\n", - "[1 1 1 0 1 0 0 1 0 0 0 1 1 1 0 0 1 0 1 1 0]\n", - "Running the 732 iteration\n", - "[1 1 0 1 1 1 0 0 1 1 0 1 1 0 0 1 0 0 0 0 1]\n", - "Running the 733 iteration\n", - "[0 0 0 1 1 1 1 0 0 0 1 1 0 1 0 1 1 0 1 1 0]\n", - "Running the 734 iteration\n", - "[1 1 0 0 0 0 0 0 0 1 1 1 1 0 1 1 0 0 1 1 1]\n", - "Running the 735 iteration\n", - "[1 1 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 1 0 1 1]\n", - "Running the 736 iteration\n", - "[1 0 1 1 1 0 1 0 1 0 0 0 1 0 1 0 1 1 0 0 1]\n", - "Running the 737 iteration\n", - "[1 0 1 1 1 1 0 0 1 1 0 0 0 1 1 0 0 0 1 1 0]\n", - "Running the 738 iteration\n", - "[1 1 1 0 1 0 1 0 0 1 0 0 1 0 1 1 1 1 0 0 0]\n", - "Running the 739 iteration\n", - "[1 1 1 0 0 1 0 0 1 0 0 1 0 0 0 1 1 1 0 1 1]\n", - "Running the 740 iteration\n", - "[1 0 1 1 1 0 1 1 0 0 1 1 0 1 1 0 0 0 0 1 0]\n", - "Running the 741 iteration\n", - "[0 0 1 1 0 1 1 1 1 0 0 0 1 0 0 1 1 1 0 0 1]\n", - "Running the 742 iteration\n", - "[1 1 0 0 0 1 0 1 0 1 1 0 1 0 1 0 0 1 0 1 1]\n", - "Running the 743 iteration\n", - "[1 1 1 0 1 0 1 1 0 0 0 1 0 0 0 1 1 1 0 1 0]\n", - "Running the 744 iteration\n", - "[1 1 0 1 1 0 0 1 0 1 0 1 1 0 1 0 0 0 1 0 1]\n", - "Running the 745 iteration\n", - "[1 0 1 1 0 1 1 0 0 0 1 1 1 0 0 0 0 1 1 0 1]\n", - "Running the 746 iteration\n", - "[1 0 1 0 1 1 0 1 0 0 0 0 0 0 0 1 1 1 1 1 1]\n", - "Running the 747 iteration\n", - "[1 0 1 0 0 0 1 1 0 1 0 0 1 0 1 1 0 1 1 1 0]\n", - "Running the 748 iteration\n", - "[1 0 0 0 0 0 1 1 0 1 0 0 1 0 1 0 1 1 1 1 1]\n", - "Running the 749 iteration\n", - "[1 0 0 0 0 0 1 1 1 1 1 0 0 1 0 1 1 1 0 0 1]\n", - "Running the 750 iteration\n", - "[1 1 0 0 0 0 1 1 1 1 1 1 0 0 1 0 1 1 0 0 0]\n", - "Running the 751 iteration\n", - "[0 1 1 1 1 0 0 1 0 1 0 0 0 0 0 1 1 1 1 1 0]\n", - "Running the 752 iteration\n", - "[1 1 1 0 0 1 0 0 0 0 1 1 1 1 1 0 0 1 0 1 0]\n", - "Running the 753 iteration\n", - "[1 1 0 0 0 1 0 0 1 0 1 1 1 1 0 1 1 0 0 0 1]\n", - "Running the 754 iteration\n", - "[0 1 0 0 1 1 1 1 1 1 0 0 1 0 1 0 1 0 1 0 0]\n", - "Running the 755 iteration\n", - "[0 1 0 1 1 0 0 0 0 1 1 0 1 1 0 0 1 1 1 0 1]\n", - "Running the 756 iteration\n", - "[1 0 0 0 0 0 1 1 0 1 1 0 1 0 1 1 1 1 0 1 0]\n", - "Running the 757 iteration\n", - "[1 1 1 1 1 1 0 0 1 0 1 0 1 0 0 0 0 0 1 0 1]\n", - "Running the 758 iteration\n", - "[1 1 1 0 0 1 0 0 1 1 0 1 0 0 0 0 1 0 1 1 1]\n", - "Running the 759 iteration\n", - "[1 1 1 0 0 0 1 1 0 0 0 1 1 1 1 1 0 0 0 1 0]\n", - "Running the 760 iteration\n", - "[1 1 0 1 0 1 0 0 0 1 0 0 1 0 1 1 1 1 0 1 0]\n", - "Running the 761 iteration\n", - "[1 1 1 1 1 0 0 0 0 0 0 1 0 1 0 0 1 0 1 1 1]\n", - "Running the 762 iteration\n", - "[0 1 1 0 0 1 1 1 0 0 1 1 0 1 0 0 0 1 1 1 0]\n", - "Running the 763 iteration\n", - "[0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0 1 1 0 0 1]\n", - "Running the 764 iteration\n", - "[1 0 0 1 0 1 0 1 1 0 1 1 1 0 1 0 0 0 1 1 0]\n", - "Running the 765 iteration\n", - "[0 1 1 1 0 1 0 1 0 0 1 1 0 0 1 0 1 0 1 0 1]\n", - "Running the 766 iteration\n", - "[1 1 1 0 1 1 1 1 0 1 1 0 0 0 0 0 1 0 0 0 1]\n", - "Running the 767 iteration\n", - "[1 0 0 1 0 0 1 1 1 0 1 1 0 0 1 0 0 1 1 0 1]\n", - "Running the 768 iteration\n", - "[1 1 1 1 0 0 0 0 0 1 0 0 1 0 1 1 1 1 0 0 1]\n", - "Running the 769 iteration\n", - "[0 1 0 1 1 0 1 1 0 1 1 1 0 1 0 0 1 0 1 0 0]\n", - "Running the 770 iteration\n", - "[0 0 0 1 0 1 1 1 1 0 1 1 1 1 0 1 0 1 0 0 0]\n", - "Running the 771 iteration\n", - "[1 0 0 1 1 1 0 1 0 0 0 1 0 0 0 1 0 1 1 1 1]\n", - "Running the 772 iteration\n", - "[1 0 0 1 1 1 0 1 1 0 1 0 1 0 0 1 0 1 1 0 0]\n", - "Running the 773 iteration\n", - "[1 1 1 0 1 0 1 0 1 1 0 0 0 0 1 1 0 1 0 0 1]\n", - "Running the 774 iteration\n", - "[0 1 0 0 1 1 0 1 1 0 1 0 0 1 0 1 1 1 0 1 0]\n", - "Running the 775 iteration\n", - "[0 0 1 1 1 0 0 1 1 0 1 1 0 1 0 1 1 0 0 0 1]\n", - "Running the 776 iteration\n", - "[0 0 1 1 0 1 1 0 0 0 1 0 1 1 1 1 0 0 1 0 1]\n", - "Running the 777 iteration\n", - "[0 1 1 0 1 1 0 0 1 0 0 1 0 1 1 1 0 1 0 0 1]\n", - "Running the 778 iteration\n", - "[0 1 0 0 1 1 1 1 0 0 1 0 0 1 0 0 1 0 1 1 1]\n", - "Running the 779 iteration\n", - "[1 0 1 0 0 0 1 0 0 1 1 1 0 1 1 0 1 1 0 0 1]\n", - "Running the 780 iteration\n", - "[0 0 1 1 0 1 0 1 0 1 1 0 1 1 0 0 1 0 1 0 1]\n", - "Running the 781 iteration\n", - "[0 1 1 1 1 1 1 0 0 1 1 0 0 0 1 0 0 0 0 1 1]\n", - "Running the 782 iteration\n", - "[0 1 0 1 0 0 1 1 1 0 1 1 0 1 0 1 0 1 0 0 1]\n", - "Running the 783 iteration\n", - "[1 1 0 0 0 1 0 0 0 1 0 0 1 1 0 1 1 1 1 1 0]\n", - "Running the 784 iteration\n", - "[1 1 1 1 0 1 1 1 0 0 0 0 0 0 1 0 0 0 1 1 1]\n", - "Running the 785 iteration\n", - "[1 1 0 0 0 0 0 1 0 1 1 1 1 0 1 1 0 1 1 0 0]\n", - "Running the 786 iteration\n", - "[1 1 0 0 1 0 1 0 1 1 0 1 1 0 1 0 1 0 0 1 0]\n", - "Running the 787 iteration\n", - "[0 1 1 1 0 0 1 1 1 1 1 1 0 0 0 1 0 1 0 0 0]\n", - "Running the 788 iteration\n", - "[1 1 1 0 0 1 0 1 1 1 1 1 0 0 0 0 0 1 1 0 0]\n", - "Running the 789 iteration\n", - "[0 0 1 1 1 0 1 0 1 0 1 1 0 1 1 0 1 0 0 1 0]\n", - "Running the 790 iteration\n", - "[1 0 1 1 1 0 1 0 0 1 0 1 1 1 0 1 1 0 0 0 0]\n", - "Running the 791 iteration\n", - "[0 1 1 0 1 1 0 1 1 1 0 0 0 1 0 1 1 1 0 0 0]\n", - "Running the 792 iteration\n", - "[1 1 1 0 1 0 0 0 0 1 1 0 1 0 1 0 0 1 0 1 1]\n", - "Running the 793 iteration\n", - "[0 0 0 0 0 1 0 0 0 0 1 1 1 1 1 1 1 1 0 1 1]\n", - "Running the 794 iteration\n", - "[1 0 1 1 1 1 1 0 0 0 1 0 1 0 0 0 1 1 0 1 0]\n", - "Running the 795 iteration\n", - "[1 0 0 1 0 0 0 0 1 1 1 0 0 1 0 1 0 1 1 1 1]\n", - "Running the 796 iteration\n", - "[0 1 1 0 1 1 0 0 1 1 1 1 0 0 1 0 1 0 0 0 1]\n", - "Running the 797 iteration\n", - "[0 0 1 1 1 1 1 1 0 1 0 1 0 0 0 1 0 1 0 0 1]\n", - "Running the 798 iteration\n", - "[0 1 0 1 1 0 0 1 1 0 1 0 1 0 0 1 1 1 1 0 0]\n", - "Running the 799 iteration\n", - "[1 1 1 0 0 1 0 1 0 1 0 1 1 0 1 0 0 0 0 1 1]\n", - "Running the 800 iteration\n", - "[0 1 0 0 1 0 1 0 1 1 1 1 1 0 1 0 1 0 1 0 0]\n", - "Running the 801 iteration\n", - "[1 0 1 1 0 1 1 1 0 0 1 0 0 1 1 0 0 1 1 0 0]\n", - "Running the 802 iteration\n", - "[0 1 0 1 1 1 0 0 1 1 0 1 0 1 1 1 0 0 0 1 0]\n", - "Running the 803 iteration\n", - "[0 1 1 1 1 1 1 0 1 0 1 1 0 1 0 0 1 0 0 0 0]\n", - "Running the 804 iteration\n", - "[1 0 0 0 0 1 1 1 0 1 1 0 0 1 0 1 0 1 1 0 1]\n", - "Running the 805 iteration\n", - "[1 1 1 0 0 0 1 1 1 1 0 0 0 1 0 0 1 1 0 1 0]\n", - "Running the 806 iteration\n", - "[0 1 1 1 1 1 1 1 0 1 0 0 1 0 0 0 0 1 0 0 1]\n", - "Running the 807 iteration\n", - "[1 1 1 0 0 1 1 0 1 1 1 0 0 1 0 0 1 0 0 1 0]\n", - "Running the 808 iteration\n", - "[1 1 1 1 1 1 1 0 0 0 1 0 0 0 0 1 0 0 0 1 1]\n", - "Running the 809 iteration\n", - "[0 0 0 1 1 1 0 1 1 1 0 0 1 1 1 1 0 0 1 0 0]\n", - "Running the 810 iteration\n", - "[1 1 0 0 0 1 1 1 0 1 0 0 1 0 1 1 0 1 0 1 0]\n", - "Running the 811 iteration\n", - "[0 0 0 1 1 1 1 0 0 1 1 0 1 1 1 1 0 1 0 0 0]\n", - "Running the 812 iteration\n", - "[0 0 0 0 1 1 0 1 0 1 1 0 0 1 0 1 1 1 1 0 1]\n", - "Running the 813 iteration\n", - "[1 0 0 1 0 1 0 1 0 1 1 1 1 0 0 0 0 1 1 1 0]\n", - "Running the 814 iteration\n", - "[0 0 0 1 0 0 1 0 1 1 1 1 1 1 1 0 0 1 0 0 1]\n", - "Running the 815 iteration\n", - "[1 1 1 1 0 0 1 0 0 0 0 1 0 1 1 1 0 1 0 1 0]\n", - "Running the 816 iteration\n", - "[0 1 1 0 1 0 0 1 0 0 1 0 0 1 1 1 1 1 0 1 0]\n", - "Running the 817 iteration\n", - "[0 0 0 0 1 1 1 1 0 0 1 0 1 1 1 1 0 1 0 0 1]\n", - "Running the 818 iteration\n", - "[1 1 1 1 1 0 0 1 0 1 0 0 0 1 0 1 1 0 1 0 0]\n", - "Running the 819 iteration\n", - "[0 1 0 1 1 0 1 1 0 0 1 1 0 1 1 1 0 1 0 0 0]\n", - "Running the 820 iteration\n", - "[1 1 1 1 1 0 1 1 0 0 0 0 0 0 1 1 0 0 1 1 0]\n", - "Running the 821 iteration\n", - "[1 0 1 1 1 0 1 0 0 0 0 0 0 0 1 1 0 1 1 1 1]\n", - "Running the 822 iteration\n", - "[1 1 0 1 1 0 1 0 0 1 1 1 0 0 0 0 1 1 0 1 0]\n", - "Running the 823 iteration\n", - "[0 1 1 0 0 0 1 0 1 0 1 1 1 0 1 0 1 0 0 1 1]\n", - "Running the 824 iteration\n", - "[1 0 0 1 0 1 0 0 1 1 1 1 0 1 1 1 0 0 1 0 0]\n", - "Running the 825 iteration\n", - "[0 0 1 1 0 1 0 1 0 1 1 0 0 1 0 0 0 1 1 1 1]\n", - "Running the 826 iteration\n", - "[0 0 1 1 1 0 0 1 1 1 0 0 1 0 0 0 1 0 1 1 1]\n", - "Running the 827 iteration\n", - "[1 0 1 1 0 1 0 1 0 0 1 0 1 1 0 0 1 1 1 0 0]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Running the 828 iteration\n", - "[0 0 1 1 0 0 1 0 0 1 1 0 0 0 1 1 0 1 1 1 1]\n", - "Running the 829 iteration\n", - "[1 1 1 0 0 1 1 1 0 0 0 1 1 0 0 1 0 1 0 0 1]\n", - "Running the 830 iteration\n", - "[0 1 1 0 0 1 1 0 0 0 1 1 0 1 1 1 0 0 1 1 0]\n", - "Running the 831 iteration\n", - "[1 0 1 1 0 1 0 1 0 1 0 1 0 0 0 1 1 0 0 1 1]\n", - "Running the 832 iteration\n", - "[1 1 1 1 1 0 0 1 0 0 1 0 1 0 0 0 0 1 1 1 0]\n", - "Running the 833 iteration\n", - "[1 0 0 1 0 1 1 1 0 1 0 0 1 0 0 1 0 1 1 1 0]\n", - "Running the 834 iteration\n", - "[0 0 1 1 1 1 0 1 1 1 0 1 0 0 0 0 1 0 1 0 1]\n", - "Running the 835 iteration\n", - "[0 0 0 1 0 1 0 1 0 1 0 0 1 1 1 1 0 1 0 1 1]\n", - "Running the 836 iteration\n", - "[0 0 1 0 1 1 1 1 0 1 0 0 0 1 1 1 1 0 0 1 0]\n", - "Running the 837 iteration\n", - "[0 1 1 1 0 1 1 0 1 1 0 0 1 1 1 0 0 0 0 0 1]\n", - "Running the 838 iteration\n", - "[1 1 0 0 0 1 1 0 1 1 1 0 1 0 0 1 0 1 0 1 0]\n", - "Running the 839 iteration\n", - "[1 0 0 0 0 1 1 1 0 0 1 1 0 1 0 1 0 1 0 1 1]\n", - "Running the 840 iteration\n", - "[0 1 1 1 0 0 1 1 0 0 1 0 0 1 0 1 1 1 0 1 0]\n", - "Running the 841 iteration\n", - "[1 1 0 0 1 0 0 1 0 0 1 0 1 1 1 0 1 0 0 1 1]\n", - "Running the 842 iteration\n", - "[0 1 1 1 0 0 0 1 0 1 1 0 1 0 0 1 1 1 1 0 0]\n", - "Running the 843 iteration\n", - "[0 1 0 1 0 1 1 0 1 0 1 0 0 0 0 1 0 1 1 1 1]\n", - "Running the 844 iteration\n", - "[1 1 0 0 1 0 0 1 0 1 0 0 1 0 1 1 1 0 1 1 0]\n", - "Running the 845 iteration\n", - "[1 1 1 1 1 0 0 1 1 1 0 1 0 1 0 0 0 0 0 0 1]\n", - "Running the 846 iteration\n", - "[1 1 1 0 0 0 1 0 1 1 1 1 0 0 1 1 0 1 0 0 0]\n", - "Running the 847 iteration\n", - "[0 1 0 1 1 0 1 1 1 0 0 1 0 0 1 0 0 1 1 0 1]\n", - "Running the 848 iteration\n", - "[0 1 0 1 1 1 0 0 0 1 1 1 1 0 1 0 1 0 1 0 0]\n", - "Running the 849 iteration\n", - "[1 0 0 0 1 1 1 0 1 0 0 1 1 1 0 0 1 0 1 1 0]\n", - "Running the 850 iteration\n", - "[0 1 1 0 1 0 1 1 0 0 0 1 1 1 1 0 0 0 0 1 1]\n", - "Running the 851 iteration\n", - "[0 1 1 0 0 0 1 1 1 0 0 0 0 1 0 1 1 1 0 1 1]\n", - "Running the 852 iteration\n", - "[0 0 0 1 1 0 1 1 1 0 0 0 0 1 0 1 1 1 1 0 1]\n", - "Running the 853 iteration\n", - "[0 0 1 1 0 1 0 1 0 0 1 1 1 1 0 1 0 1 1 0 0]\n", - "Running the 854 iteration\n", - "[0 0 0 1 1 0 1 0 0 1 1 1 1 1 1 0 0 1 1 0 0]\n", - "Running the 855 iteration\n", - "[1 0 1 0 0 1 0 0 0 0 1 1 1 1 0 1 1 0 1 0 1]\n", - "Running the 856 iteration\n", - "[0 1 1 0 0 1 1 0 0 0 1 1 1 1 1 1 0 0 0 0 1]\n", - "Running the 857 iteration\n", - "[0 0 1 1 1 1 1 0 0 1 1 0 1 0 0 0 0 1 1 1 0]\n", - "Running the 858 iteration\n", - "[0 0 1 1 1 0 1 1 0 1 0 0 0 0 1 1 1 1 1 0 0]\n", - "Running the 859 iteration\n", - "[1 1 1 0 1 0 0 0 0 1 0 1 0 1 0 0 1 1 0 1 1]\n", - "Running the 860 iteration\n", - "[1 0 0 1 1 0 0 1 0 0 1 0 1 1 0 1 0 1 0 1 1]\n", - "Running the 861 iteration\n", - "[0 1 0 1 1 1 1 1 1 0 0 1 1 1 1 0 0 0 0 0 0]\n", - "Running the 862 iteration\n", - "[0 1 1 0 1 1 0 1 0 0 1 0 1 0 1 1 1 0 1 0 0]\n", - "Running the 863 iteration\n", - "[0 0 0 1 0 1 0 0 1 1 0 1 1 1 1 1 0 0 1 0 1]\n", - "Running the 864 iteration\n", - "[0 1 0 0 1 1 0 0 1 1 1 1 1 1 0 0 0 0 0 1 1]\n", - "Running the 865 iteration\n", - "[0 0 1 1 0 1 1 0 1 1 0 0 0 0 1 1 1 1 0 1 0]\n", - "Running the 866 iteration\n", - "[0 0 1 1 1 0 1 1 1 0 0 0 1 1 0 0 0 1 0 1 1]\n", - "Running the 867 iteration\n", - "[0 1 1 0 1 0 1 1 0 0 0 0 1 1 1 1 0 0 1 1 0]\n", - "Running the 868 iteration\n", - "[1 0 1 0 1 0 0 1 1 0 1 0 1 0 1 0 0 1 1 0 1]\n", - "Running the 869 iteration\n", - "[0 1 1 0 1 0 1 1 0 0 0 0 1 1 0 0 1 1 1 0 1]\n", - "Running the 870 iteration\n", - "[0 0 0 1 0 1 0 1 0 1 0 0 1 1 1 1 0 1 0 1 1]\n", - "Running the 871 iteration\n", - "[0 0 1 1 1 1 0 1 0 0 1 1 0 0 1 0 1 1 1 0 0]\n", - "Running the 872 iteration\n", - "[0 0 0 1 1 0 1 1 1 1 1 0 0 0 1 1 0 1 0 0 1]\n", - "Running the 873 iteration\n", - "[0 1 0 1 1 0 0 1 0 1 1 0 0 1 1 0 1 0 1 0 1]\n", - "Running the 874 iteration\n", - "[1 0 0 0 0 1 1 0 0 1 1 1 0 0 1 0 1 1 1 0 1]\n", - "Running the 875 iteration\n", - "[0 0 0 1 0 0 1 0 1 1 1 1 1 0 0 1 0 1 1 0 1]\n", - "Running the 876 iteration\n", - "[0 1 1 1 0 0 0 0 1 1 1 0 1 1 1 0 1 0 0 1 0]\n", - "Running the 877 iteration\n", - "[1 0 1 1 1 0 0 0 1 0 0 0 1 1 0 0 0 1 1 1 1]\n", - "Running the 878 iteration\n", - "[0 0 0 1 1 0 1 1 0 1 0 0 0 1 1 1 1 0 1 0 1]\n", - "Running the 879 iteration\n", - "[0 1 1 1 0 0 1 0 1 0 1 1 1 0 0 0 1 0 1 1 0]\n", - "Running the 880 iteration\n", - "[1 1 0 0 0 0 0 1 1 0 1 1 1 0 0 1 0 1 1 1 0]\n", - "Running the 881 iteration\n", - "[0 0 0 0 1 0 0 1 1 1 1 1 1 1 1 0 1 0 0 1 0]\n", - "Running the 882 iteration\n", - "[0 0 1 1 0 1 1 0 1 0 0 0 0 0 0 1 1 1 1 1 1]\n", - "Running the 883 iteration\n", - "[1 0 1 1 1 1 0 0 0 0 0 0 1 1 1 1 0 0 0 1 1]\n", - "Running the 884 iteration\n", - "[1 1 0 0 0 1 1 0 1 1 1 0 1 1 1 0 0 0 0 0 1]\n", - "Running the 885 iteration\n", - "[0 0 0 0 1 1 1 1 0 0 1 1 0 1 1 0 1 1 0 0 1]\n", - "Running the 886 iteration\n", - "[1 1 0 0 0 0 1 1 0 1 1 1 1 1 0 1 1 0 0 0 0]\n", - "Running the 887 iteration\n", - "[1 0 0 1 0 1 1 1 1 1 1 0 0 0 1 0 1 1 0 0 0]\n", - "Running the 888 iteration\n", - "[1 0 0 0 0 1 1 1 0 1 1 0 0 0 1 1 0 1 1 1 0]\n", - "Running the 889 iteration\n", - "[0 0 1 0 1 1 0 1 1 0 1 1 1 0 0 1 0 0 1 1 0]\n", - "Running the 890 iteration\n", - "[0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0 1 0 1 0 1]\n", - "Running the 891 iteration\n", - "[1 0 1 0 0 1 0 1 0 0 1 0 0 0 1 1 0 1 1 1 1]\n", - "Running the 892 iteration\n", - "[0 0 1 0 0 1 1 1 1 1 0 0 0 1 0 0 1 1 0 1 1]\n", - "Running the 893 iteration\n", - "[1 0 1 1 0 0 0 1 1 1 1 0 0 0 1 0 0 1 1 1 0]\n", - "Running the 894 iteration\n", - "[1 0 0 1 1 0 0 1 1 0 0 1 0 1 0 1 0 1 0 1 1]\n", - "Running the 895 iteration\n", - "[0 0 1 1 1 0 1 1 0 0 1 1 1 0 1 0 0 1 0 1 0]\n", - "Running the 896 iteration\n", - "[1 0 1 0 0 1 1 1 1 0 0 1 1 0 0 1 0 0 1 0 1]\n", - "Running the 897 iteration\n", - "[0 0 1 1 1 1 0 0 1 0 0 1 0 1 0 1 1 1 0 0 1]\n", - "Running the 898 iteration\n", - "[0 1 1 1 1 0 0 1 0 0 0 0 0 1 0 1 1 1 0 1 1]\n", - "Running the 899 iteration\n", - "[1 0 0 0 1 1 1 1 0 1 0 1 0 0 1 1 1 0 1 0 0]\n", - "Running the 900 iteration\n", - "[0 1 0 0 1 1 0 1 1 1 1 0 1 1 0 0 0 1 1 0 0]\n", - "Running the 901 iteration\n", - "[0 1 0 1 1 0 1 0 0 0 0 1 0 1 1 1 1 0 1 1 0]\n", - "Running the 902 iteration\n", - "[0 1 1 1 1 0 0 1 1 0 1 1 0 0 0 1 0 1 0 0 1]\n", - "Running the 903 iteration\n", - "[1 0 0 0 0 1 0 1 0 0 0 1 1 1 1 1 0 1 0 1 1]\n", - "Running the 904 iteration\n", - "[0 1 1 1 0 0 0 0 1 1 0 0 1 1 0 1 0 0 1 1 1]\n", - "Running the 905 iteration\n", - "[0 0 1 0 1 1 1 0 0 0 0 1 1 1 0 0 1 1 0 1 1]\n", - "Running the 906 iteration\n", - "[1 0 0 0 1 1 1 0 0 1 0 0 1 1 0 1 1 0 0 1 1]\n", - "Running the 907 iteration\n", - "[0 1 1 0 1 0 1 0 0 1 1 1 0 0 1 0 1 0 0 1 1]\n", - "Running the 908 iteration\n", - "[0 0 1 1 1 0 1 1 1 0 0 0 0 1 1 0 0 1 1 1 0]\n", - "Running the 909 iteration\n", - "[0 0 1 0 0 0 0 1 0 1 0 1 1 1 0 1 1 0 1 1 1]\n", - "Running the 910 iteration\n", - "[1 1 0 1 0 0 0 1 0 0 0 1 0 1 1 1 0 1 1 0 1]\n", - "Running the 911 iteration\n", - "[1 0 1 0 0 1 1 0 1 0 1 1 1 1 1 0 0 1 0 0 0]\n", - "Running the 912 iteration\n", - "[1 0 1 0 1 0 1 1 0 0 0 1 0 1 0 1 1 1 0 1 0]\n", - "Running the 913 iteration\n", - "[0 0 1 1 0 1 0 1 0 1 0 1 0 0 1 0 1 1 1 0 1]\n", - "Running the 914 iteration\n", - "[1 0 0 0 1 1 1 0 0 1 0 1 0 1 0 1 1 1 0 0 1]\n", - "Running the 915 iteration\n", - "[1 1 0 1 0 0 1 1 0 1 0 1 0 1 1 0 0 1 0 1 0]\n", - "Running the 916 iteration\n", - "[1 0 0 0 1 1 0 1 0 1 0 0 0 1 1 1 1 1 1 0 0]\n", - "Running the 917 iteration\n", - "[0 0 0 0 0 1 0 1 0 0 1 1 0 1 1 1 1 1 1 1 0]\n", - "Running the 918 iteration\n", - "[0 0 1 0 0 1 1 0 1 1 0 1 1 1 0 0 1 1 0 0 1]\n", - "Running the 919 iteration\n", - "[1 1 0 0 1 0 0 1 1 1 1 0 1 1 0 1 0 0 1 0 0]\n", - "Running the 920 iteration\n", - "[1 1 0 0 0 1 0 0 1 1 1 1 0 0 1 1 0 1 0 1 0]\n", - "Running the 921 iteration\n", - "[1 0 1 1 1 0 1 0 1 0 1 1 0 0 0 0 0 1 1 0 1]\n", - "Running the 922 iteration\n", - "[0 1 0 0 0 0 0 1 0 1 1 1 1 0 1 1 0 0 1 1 1]\n", - "Running the 923 iteration\n", - "[0 1 1 1 1 0 1 0 1 1 0 0 0 0 0 0 1 1 1 1 0]\n", - "Running the 924 iteration\n", - "[1 0 1 0 0 0 0 0 1 0 1 1 0 1 1 0 1 0 1 1 1]\n", - "Running the 925 iteration\n", - "[0 1 1 1 0 1 0 1 1 0 1 0 0 0 0 0 1 1 1 1 0]\n", - "Running the 926 iteration\n", - "[0 1 0 0 0 1 0 0 1 1 1 1 1 1 1 1 0 1 0 0 0]\n", - "Running the 927 iteration\n", - "[1 0 1 1 1 1 0 1 0 0 0 0 1 1 1 0 1 1 0 0 0]\n", - "Running the 928 iteration\n", - "[1 1 0 1 1 1 0 1 1 0 0 1 0 0 1 0 1 0 0 1 0]\n", - "Running the 929 iteration\n", - "[1 0 1 1 1 1 0 0 1 0 1 1 1 0 0 1 0 0 1 0 0]\n", - "Running the 930 iteration\n", - "[0 1 0 1 0 0 1 1 0 1 1 0 1 0 0 1 0 1 1 0 1]\n", - "Running the 931 iteration\n", - "[1 1 0 0 1 0 0 1 0 0 1 1 0 0 0 1 1 1 0 1 1]\n", - "Running the 932 iteration\n", - "[0 0 0 1 0 1 0 1 1 1 0 0 0 1 1 1 1 0 1 0 1]\n", - "Running the 933 iteration\n", - "[1 1 0 1 1 1 0 0 1 0 0 1 1 1 1 1 0 0 0 0 0]\n", - "Running the 934 iteration\n", - "[0 0 0 1 1 0 0 1 0 0 1 0 0 1 1 1 1 1 1 0 1]\n", - "Running the 935 iteration\n", - "[0 1 0 1 0 0 1 1 0 1 1 0 0 1 0 0 0 1 1 1 1]\n", - "Running the 936 iteration\n", - "[1 0 0 1 1 0 0 1 1 0 1 1 0 1 0 0 0 1 1 1 0]\n", - "Running the 937 iteration\n", - "[0 1 1 0 1 0 1 0 0 1 1 1 0 1 0 1 1 0 0 0 1]\n", - "Running the 938 iteration\n", - "[0 1 0 1 1 1 1 1 1 0 0 0 1 0 1 0 0 1 1 0 0]\n", - "Running the 939 iteration\n", - "[1 0 0 0 0 1 1 1 1 0 0 1 1 0 1 1 0 1 0 1 0]\n", - "Running the 940 iteration\n", - "[0 0 0 1 1 1 1 0 1 1 1 0 1 0 1 1 0 0 0 0 1]\n", - "Running the 941 iteration\n", - "[0 1 0 1 0 1 0 0 0 1 1 0 1 1 0 1 0 1 1 0 1]\n", - "Running the 942 iteration\n", - "[0 1 1 1 0 1 1 0 1 0 0 1 0 1 0 1 0 0 0 1 1]\n", - "Running the 943 iteration\n", - "[1 0 0 1 1 0 0 0 1 1 1 1 0 0 1 1 0 1 0 1 0]\n", - "Running the 944 iteration\n", - "[1 1 1 0 1 1 0 0 0 1 1 1 1 0 1 1 0 0 0 0 0]\n", - "Running the 945 iteration\n", - "[0 1 0 1 0 1 0 0 1 0 1 1 0 0 0 1 1 0 1 1 1]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Running the 946 iteration\n", - "[1 1 0 0 0 1 0 1 0 1 1 1 0 1 0 1 0 0 1 0 1]\n", - "Running the 947 iteration\n", - "[1 1 0 1 1 0 0 0 0 0 1 1 0 1 0 1 0 0 1 1 1]\n", - "Running the 948 iteration\n", - "[1 0 0 1 0 1 0 0 1 1 1 0 0 1 1 1 0 0 1 1 0]\n", - "Running the 949 iteration\n", - "[1 1 1 0 0 1 0 0 0 1 1 1 1 1 0 1 0 0 0 1 0]\n", - "Running the 950 iteration\n", - "[0 0 1 1 0 0 1 0 1 0 1 1 0 1 0 0 1 0 1 1 1]\n", - "Running the 951 iteration\n", - "[1 0 1 1 0 0 1 0 1 0 0 0 1 1 1 1 0 0 1 1 0]\n", - "Running the 952 iteration\n", - "[1 0 0 1 1 0 1 0 0 0 0 0 1 0 1 1 1 1 1 1 0]\n", - "Running the 953 iteration\n", - "[0 0 1 1 1 1 0 0 1 1 0 1 0 0 1 0 0 1 0 1 1]\n", - "Running the 954 iteration\n", - "[0 0 0 0 0 1 1 0 1 1 1 0 1 1 1 1 0 0 1 1 0]\n", - "Running the 955 iteration\n", - "[0 1 1 0 1 0 1 1 1 0 1 1 0 0 0 0 1 0 1 1 0]\n", - "Running the 956 iteration\n", - "[1 1 1 0 1 0 1 1 0 1 0 1 0 0 0 0 1 0 1 0 1]\n", - "Running the 957 iteration\n", - "[1 0 0 0 1 0 1 1 0 0 1 1 1 1 0 1 0 0 1 1 0]\n", - "Running the 958 iteration\n", - "[1 0 1 1 1 0 0 0 0 1 1 1 0 1 1 0 0 1 0 0 1]\n", - "Running the 959 iteration\n", - "[1 0 0 0 0 0 0 1 1 0 1 1 0 1 1 0 1 1 1 1 0]\n", - "Running the 960 iteration\n", - "[1 1 0 0 1 1 0 0 1 0 1 1 0 1 1 0 0 1 0 0 1]\n", - "Running the 961 iteration\n", - "[1 1 1 0 0 1 0 1 0 0 1 0 1 0 1 1 1 1 0 0 0]\n", - "Running the 962 iteration\n", - "[0 0 1 0 1 0 0 1 0 1 0 1 1 0 0 1 0 1 1 1 1]\n", - "Running the 963 iteration\n", - "[1 0 0 0 1 0 1 1 0 1 1 0 1 0 1 0 1 0 1 1 0]\n", - "Running the 964 iteration\n", - "[1 1 1 1 0 1 1 0 1 1 0 0 1 1 0 0 0 1 0 0 0]\n", - "Running the 965 iteration\n", - "[0 0 1 0 1 1 1 0 0 1 1 0 0 1 1 1 0 0 1 0 1]\n", - "Running the 966 iteration\n", - "[0 0 0 1 1 0 0 0 1 0 1 0 0 1 1 1 1 1 1 1 0]\n", - "Running the 967 iteration\n", - "[1 1 0 0 0 1 0 0 1 1 1 1 1 1 0 0 1 1 0 0 0]\n", - "Running the 968 iteration\n", - "[0 0 0 0 1 0 0 1 1 1 1 0 0 1 1 0 1 1 1 0 1]\n", - "Running the 969 iteration\n", - "[0 1 0 1 1 0 1 0 0 0 1 0 0 0 1 1 1 0 1 1 1]\n", - "Running the 970 iteration\n", - "[0 1 1 1 1 0 0 0 0 0 1 1 1 1 1 0 0 1 0 1 0]\n", - "Running the 971 iteration\n", - "[0 1 1 0 1 0 0 1 1 1 0 0 0 0 1 1 0 0 1 1 1]\n", - "Running the 972 iteration\n", - "[1 0 0 1 1 0 1 0 0 1 1 1 1 0 0 1 1 0 1 0 0]\n", - "Running the 973 iteration\n", - "[1 1 0 1 1 1 0 1 1 0 0 0 1 1 1 0 0 0 1 0 0]\n", - "Running the 974 iteration\n", - "[0 1 1 0 1 1 0 1 1 1 0 0 0 0 1 1 1 0 1 0 0]\n", - "Running the 975 iteration\n", - "[0 0 1 1 1 1 1 0 1 0 0 0 1 0 1 0 0 0 1 1 1]\n", - "Running the 976 iteration\n", - "[1 1 1 0 0 0 0 1 1 1 0 1 1 0 0 1 0 1 0 1 0]\n", - "Running the 977 iteration\n", - "[0 1 0 0 1 1 0 0 1 1 0 1 0 1 1 1 1 0 0 1 0]\n", - "Running the 978 iteration\n", - "[1 1 0 0 0 1 1 1 1 1 0 0 1 1 0 0 1 0 0 1 0]\n", - "Running the 979 iteration\n", - "[0 1 1 0 0 1 0 1 1 1 0 1 0 1 0 0 0 1 0 1 1]\n", - "Running the 980 iteration\n", - "[0 0 0 1 1 0 1 1 1 1 0 1 1 1 0 0 1 0 1 0 0]\n", - "Running the 981 iteration\n", - "[0 1 1 1 0 0 0 1 0 1 1 1 0 0 1 0 1 0 1 1 0]\n", - "Running the 982 iteration\n", - "[1 0 0 0 1 1 1 0 1 0 1 0 0 0 1 1 1 1 0 0 1]\n", - "Running the 983 iteration\n", - "[1 0 1 0 0 1 1 0 0 0 1 1 0 0 0 1 1 0 1 1 1]\n", - "Running the 984 iteration\n", - "[1 1 1 0 1 1 0 0 0 1 0 1 0 1 1 1 0 0 0 0 1]\n", - "Running the 985 iteration\n", - "[1 0 1 1 1 1 1 1 0 1 0 0 1 0 1 0 0 0 0 0 1]\n", - "Running the 986 iteration\n", - "[1 1 0 1 0 0 1 0 1 1 1 1 0 0 0 1 1 0 1 0 0]\n", - "Running the 987 iteration\n", - "[1 1 1 1 0 0 1 1 0 1 0 1 0 0 1 0 0 1 1 0 0]\n", - "Running the 988 iteration\n", - "[1 1 1 1 0 0 0 1 1 0 0 0 1 0 1 0 1 1 0 0 1]\n", - "Running the 989 iteration\n", - "[0 0 0 0 0 1 0 1 1 0 0 1 1 0 1 1 0 1 1 1 1]\n", - "Running the 990 iteration\n", - "[0 1 0 0 0 1 1 1 0 0 0 0 1 1 1 1 0 1 0 1 1]\n", - "Running the 991 iteration\n", - "[1 1 1 0 0 1 0 0 0 1 0 0 1 0 1 1 0 0 1 1 1]\n", - "Running the 992 iteration\n", - "[0 0 1 1 1 1 0 0 1 0 1 1 1 1 1 1 0 0 0 0 0]\n", - "Running the 993 iteration\n", - "[0 0 0 1 1 1 1 0 1 0 0 1 1 0 0 1 0 0 1 1 1]\n", - "Running the 994 iteration\n", - "[1 1 0 0 0 1 1 1 0 0 1 0 1 1 0 1 0 1 0 0 1]\n", - "Running the 995 iteration\n", - "[0 1 0 1 1 1 0 1 1 1 0 0 0 0 0 0 1 1 0 1 1]\n", - "Running the 996 iteration\n", - "[1 0 1 0 0 1 0 0 0 1 1 1 1 1 0 1 0 1 0 1 0]\n", - "Running the 997 iteration\n", - "[1 0 0 0 0 1 1 1 1 0 0 1 0 0 1 1 0 1 1 1 0]\n", - "Running the 998 iteration\n", - "[0 0 0 1 1 1 1 1 0 1 0 0 1 1 1 1 1 0 0 0 0]\n", - "Running the 999 iteration\n", - "[0 1 1 1 0 1 0 0 0 1 0 0 1 1 1 0 1 0 1 1 0]\n", - "Running the 1000 iteration\n", - "[0 1 0 1 1 1 0 0 0 1 0 1 1 0 0 1 1 0 1 1 0]\n" - ] - } - ], - "source": [ - "## Lets do permutation tests - shuffling the condition label\n", - "import random\n", - "condPerm = np.array(condition_label)\n", - "permScor = []\n", - "#cv = KFold(n_splits=10)\n", - "for i in range(n_iter):\n", - " print (f'Running the {i+1} iteration')\n", - " random.shuffle(condPerm)\n", - " print(condPerm)\n", - " \n", - " mean_scores = []\n", - " cv_scores = cross_val_score(model,\n", - " X,\n", - " y=condPerm,\n", - " cv=cv,\n", - " groups=condPerm,\n", - " scoring=\"f1\",#\"roc_auc\",\n", - " n_jobs=11, # set number of CPUs\n", - " #verbose = 5 # set some details of the activity \n", - " )\n", - " mean_scores.append(cv_scores.mean())\n", - " permScor.append(mean_scores)" - ] - }, - { - "cell_type": "code", - "execution_count": 450, - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " Mean of permutation score is 0.4956195238095238\n" - ] - }, - { - "data": { - "image/png": "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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# now lets see the mean score\n", - "score = np.array(permScor)\n", - "\n", - "#import matplotlib.pyplot as plt\n", - "plt.hist(score)\n", - "print(f' Mean of permutation score is {np.mean(score)}')" - ] - }, - { - "cell_type": "code", - "execution_count": 451, - "metadata": { - "slideshow": { - "slide_type": "skip" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " Chances of mean permutation score to be random is 0.088\n" - ] - }, - { - "data": { - "image/png": "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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#plot permutation histogram and real one\n", - "plt.hist(score, color=\"blue\")\n", - "plt.hist(rand_score, color=\"red\")\n", - "# chances of getting our score\n", - "print(f' Chances of mean permutation score to be random is {len(score[score>=np.mean(rand_score)])/len(score)}')" - ] - }, - { - "cell_type": "code", - "execution_count": 452, - "metadata": { - "slideshow": { - "slide_type": "subslide" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 452, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "\n", - "sns.distplot(score, hist=True, rug=True)\n", - "sns.distplot(rand_score, hist=True, rug=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 453, - "metadata": { - "slideshow": { - "slide_type": "skip" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "(array([0.001, 0.002, 0.01 , 0.039, 0.086, 0.238, 0.25 , 0.248, 0.09 ,\n", - " 0.036]),\n", - " array([0.23333333, 0.30666667, 0.38 , 0.45333333, 0.52666667,\n", - " 0.6 , 0.67333333, 0.74666667, 0.82 , 0.89333333,\n", - " 0.96666667]),\n", - " )" - ] - }, - "execution_count": 453, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "weights = np.ones_like(score) / len(score)\n", - "weights_real = np.ones_like(rand_score) / len(rand_score)\n", - "plt.hist(score, weights=weights)\n", - "plt.hist(rand_score, weights=weights_real)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, - "source": [ - "## Lets plot each group's array to see the pattern of activation" - ] - }, - { - "cell_type": "code", - "execution_count": 254, - "metadata": { - "slideshow": { - "slide_type": "skip" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "-225.35812" - ] - }, - "execution_count": 254, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "## check maximum and minimum values\n", - "np.min(midArr_reshape)" - ] - }, - { - "cell_type": "code", - "execution_count": 264, - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, - "outputs": [ - { - "data": { - "image/png": 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KNQ7HLnHs+2sfjlJKXaFN0kNeLZ0nrZTqKHrHoVJKbWTak1ZKqY2r02Z3aJJWSnWWTTL/ebU0SSulOovocMdlCd0sGX+RyEkROhmc+jxBt8eWytPYQYtaeRvjyRZuWnwGLJu6W1qqFRjCUO0YjWwPGX8Rr7WIsWxsv8Hc4I2c9YcocY5GupthmWEuKOFKQCPOE4tNYttkkxqZoIrXrpHYLk87r6U3Ps2pxjDDhUVORTvYmp8m267SSuUIE5eJoJc4sRjKzpHCx05CuuI5zsk2+uxppuJBWrGLW7yBGb+Ea8WETorQuMy0isw2Uryu9xhT0SAp18cg5K0aMQ4LYYnYCLEzyrPzPRQzAYeyr8VveTQDhzdHT3O8fDs1sxVHEqLQIk4sulItGkGKhmTw7IiZoEgx1eR4dj8n54rkvJha+q3Mz6UAeLtzkKa7ndlmP43AwbENxkAUCz05n1y6SWA8TuVuZLGVpx64zNccgiGXI9PdxAn849yTmKJFgsVYs5+0ExIbh6qUacceU/UCbvFWqmGOdtMmjC0GcxVORHuQwLDoZ5iquKRcw66eKl99NMs/f2OFn7xtCj9J4cceB84VuOf0NhxHeP+bx4jsNCEeKVq0nSyj7izbF76L1EKOb3sX35p8Fa8fOc0T87uIEqG/4PP0qQyuA1Fs2BP+kDl3CwB2EhIj3Fb5GvbMOMM3vJXiwimOdb+BVpRiQGa4u/o2yklE3guZa+4EloYzb+k5SYKFL1mycY1SqsWAM8l4spV/VHiCbG2S+yrv5tbcQcaibXS5NQTDIwt7ua48ywPj2xjp9il6LXKOR2IsnpoYZP/QOEloU26N43sFpqJe3jB0gmTYIjApIuNwvL6FrBtyqtrLdcVJHh0f4UcGnmFOBmjICLbEBFaauhQZbJ+ix8mQFHbjJAGNJM1N/VN8ffadXN8zy1SzSCnVZKZWYrpZxBLDofky7+5+mOnUVoaaxwEwItQyfQwuHsKKAiIvh1WKWYxKLPg5JhkhQagFaa7PneQHU3s4JX280fo+VhIC0Mz24gV18mkfiRPK6QZ+tFTbczAzR5B4tIICubBCtjmL21gAY5DBvcy18hTzVXoqJ4BdV5xzNktZrNXqrE8D1MLstQ7hmrOD5rUOoWO4sd4vO1HvWpN2YnOVerivpAWWlFJq07Fk9dsKRORfi8gBEXlGRD4lImkR2SEiD4nIMRH5tIh46/px1rNxpZS62sS2V71dsh2REeDXgNuMMTcBNvAzwIeAPzTG7AYWgF9cz8+jSVop1VnWdrjDATIi4gBZYAJ4G/DZ5eMfB35iXT7HMk3SSqnOIrL67RKMMeeAPwDOsJScK8BjwOLyGkYAY8DIOn4aTdJKqQ5zGetJn7/2/fJ253PNiEgZeB+wAxgGcsCPvsQ7mvX8ODpPWinVWS5j1sb5a9+/hHcAJ40xMwAi8nngjUBJRJzl3vQoMH5lAV/aamocvk5EXrv8eJ+I/O8i8t71DEoppV422179dmlngNeLSFZEBHg7cBD4NvBTy+e8n6USg+vmkj1pEfltlrr3joh8A7gd+A7wb0RkvzHmd9YzOKWUumxrdMehMeYhEfks8DhL6+o/wVKv+yvAXSLyn5b3/cWavOFFrDTc8VPALUAKmARGjTFVEfl94CHgJZP08rjOnQC//4F/xy+9751rF7FSSl3KGt5xaIz5beC3X7T7WeB1a/YmK1gpSUfGmBhoisgJY0wVwBjTEpHkYi86f5xn6tBjhnZtzQJWSqlLeoWt3RGISNYY0wRe89xOESkCF03SSil1zWyS271Xa6Uk/RZjlop9G2POT8ouSwPmSim1sXTYAksr1Th8ydVljDGzwOy6RKSUUlfC0kX/lVJq43qFjUkrpdTm8koa7lBKqc3GaE9aKaU2sA6b3SHGrOvaIDx6ZMH02jO0JUNkHGpRlrJbJW2aWCZ+/ry6VSRMXFwrxCUgHy4S2GmcJKTtZHGSgDn6yFotIuNQTOaYkUFyVpNCOE+2Mc146UZ6/HM0UyUMgmCILBcAY4RsVGPaGiJttQkSj6zVoNSapJrpJxcskmnN46fLLKb6CY1L2mohxuAmbRKxaUqexFgYBFtiHCJSSZNsexEjFm7Yop0qUE+VqURFPCvEIiEtLbx4qSTUfNjN9vgoU95WImPTwwx2EpGIRbFyBj/Xi1m+W7+W7uZMY4i0E5J3W7gSMtnqYTQzyXTQy42th5go7iUxFl3JPG7cJrRTdNUniNwMgZsj7VdYzA9zvLmNtBPR7VUQMUy1uhnKzJI2TQxCLlgk3ZzHz3bT9Ipk24u0vC4SsZmMBrDF0OXU6G2dRZKY0M3S8Er0zx7ECnyqfdfhOzkK/ixtN0/h3r9GXvtmolSeeq6fRGwq0k2QuLRjl/lWhsFcjX5rEsvENOwiC2EXA+4Mp5ojzDVTdKUj0k7IszM5PMdw69A5+punOJO+nozl092eYDY1QjGao+6UqMc5PCtkvl2gL73I8cUBujM+z4zl2doXknYiRGC3dxyDcKR9Ha8N7ydy0pxK7yNttclRo2LKxFgYI1iS4EhMYizqUYbEWHhWxLyfoT9bw489yl6VZpxhulHgdvtBTqX3MZycwUpizjo7SVttYmNTsKrMRT1k7RZZ6tgmoiYlCmaRaTNII0zR5TWpBlnSdkSXW2M+KDLkTZEJa8w7A6SlRYzDYlSk4NRxJSAdNfCiFhjDhLeDUf8ok5md1KMcRbfKpN/DUHqW+bBIzvFJyQvzAVwC2qSf/xmyk4i2kyWQNDPtblqRy9bcFOeafQxl5/CTFAYhY/mk8PHJkMInHTVIB1WOODezk2McTm5gNDNJYFJkTINA0iRYlIMpjFiMW1vJ2D6JsfCTFIJBxLB/d+8Vd4Nb3/nUqpNa5o6f3fDd7qv2lSMvWijKi1oXPbdt0heeG79wbmjcF52buuB5Yr3wy8GLSx89l7ABBsMzFxwzL/r2TYl/0fgMF/93dS/xuSxz4dRy6xKLZ734V7ZG9MLfiWuCC46JXNiOny4//7ie7b3gWCt5oR1HwguOhan8Bc/t51djhHpw4d+znP/l/qIv+tLkwQue1+wX4omTC6+8N60CF1NpXfiL3qla//OP28mF8XSFcxdtZ6g7vuC57+Sef/yY+6YLjgVy4c/e+f/Wzovu37LOe160Kxccm7C3XPC8HmUuGt9kMvz844x14c9d1rnwedPkuBg3aFz0WCO5sKycRXyRMyEbVC947vDCz0nBvvDGtBQvxDeT3XbBsbHW4AXPz//Zy9kXlngr2PWLxnO5jGWvetsMdLhDKdVZdExaKaU2MJ3doZRSG5fO7lBKqY2sw2Z3aJJWSnWUzXJBcLU0SSulOsqLZ2ptdpf9aUTkE+sRiFJKrYk1qha+UaxUPuvuF+8CfkRESgDGmP9hvQJTSqmXpcN60isNd4yyVHjxz1kqWy7AbcB/Xue4lFLqZem02R0rfeXcBjwG/CZQMcZ8B2gZY+4zxtx3sReJyJ0i8qiIPPr5T//VmgWrlFIrEmv12yaw0qL/CfCHIvKZ5T+nVnrN8uuer3H46JEFAzNrEatSSq0okVfg7A5jzBjw0yLyY0B1pfOVUuqa2SQ95NW6rCl4xpivAF9Zp1iUUuqKddqYtM6TVkp1lE6bJ61JWinVWbQnrZRSG9cr8sKhUkptFjrcoZRSG1mHDXese43D+w40TdFrkLbaJMZi2i9TStUxCMYIRaeCGEOEi5+kyVgtYmzqUY6JeoHdpUlqUR5jhNgIRbdObzBOI1XirD/EQHqeVpKmJAv4kiU2NqVk9vmSTaFx8eMUffY0oaRoJRmKskBbMnjGp2pKWJKQkjauWSq3FUia3sZpxCTUs30kYuNLltC49IXnqKfKhMYjhY9BCPFImybZoELDK9FdPU071UXbzVGsnKFeGCa0U+RbszTTZUI7Te/8UdqZMm0vj51E5CtjzPTeQP/0M0SpPH6mTGR7lGeO0s73Ejlp0o1Z/Fwvmfo0zcIQdhKQmVsqA7Y4uI/S9BFI4qXHU4dZHNjL6WQ7C60MbzLfArFwanOcG30D+XCB4twJrPoiSaZAo3c7bruOV5+j0b2VlL+IU19AkphW7zacsIXTWCTKdgHQzpSx44D04gQkMVg2VqtOc2g3GEP22Sdo7tyP267h1BeoDu6l8MDdzD36DGLbTP/qn5Kzm3SFc6TbFVrLJb9qTpltx+/FTE/gnzlHZv9+zlz/HmyJGH7w01T3v4sJZys7q49zungL/eEYKb+CnymTbi0w3XUdW49/g7PXvYMtj30GSj08vfWf8KrH/wuTt/80/dPPEGTLjOX20hNP0bV4moPFt9DrzlJqjNNKl5iTAULjkBiLsrNAb+00dtjEz/WSm3mW2eFX0zf2OAvDr6I0fYTDA29DxHD99H080/MOhq2z9Iz/kCcHfoxd5ihiYh4L93NL+gBVt4fDCyMMF6oMc5Z0UGU2u5ViMEPgZLCTiMBOk/fneMrs59XyBCfdGwhih63uGSaTYepBipwb4NkBZZkn589z2LqZLrdBiaUyYqGdwo3bGLFoSh6XgEpcZMiMMWcP0MUiYhJOBttwJKEZuuzNnmAqGaIepiml6mStFumkwazpp8uuYrDIRRUW7V6KyRyR5WEQzgXDzDQyXN89iWA4W+9jMLdIycwxEY+wlWdxoxax5ZFuzVErDHM63s58K8O+4mm6a2eZLWxjrDXIHTdlrjjDTh98dNVJrX/fbRs+o3fW7wVA2rp4jcHLEdvemrQjycVrya2XpnPxuoGXQ+Jw5ZNW005tcU3aad30ppVPWmOLUWlN2sm6a/N3eePUvWvSTp2uVZ97qZqel6Pprf49r4QRWfW2Gehwh1Kqo+iYtFJKbWA6u0MppTawzTKMsVqapJVSHWWtxtA3Ck3SSqmO0mlj0p31aZRSr3gGWfW2EhF5j4gcEZHjIvJvrkL4/53L6kmLyJuA1wHPGGPWZi6QUkqtobXqSYuIDfwJ8E5gDHhERO42xhxckzdYpUt+GhF5+LzHvwz8MVAAfvtafasopdSlJGKvelvB64DjxphnjTEBcBfwvnX/AC+y0leOe97jO4F3GmM+CLwL+J/WLSqllHqZ1nC4YwQ4e97zseV9V9VKSdoSkbKI9LB0C/kMgDGmAUQXe9H5NQ6//JmPrWG4Sil1aZdzx+H5uWp5u/O8pl4qi6/vOhovYaUx6SJLhWgFMCIyaIyZFJE8L/0BgAtrHN53oGmgsVbxKqXUJRmz+il45+eqlzAGbDnv+Sgw/vIje3lWKkS7/SKHEuAn1zwapZS6QmbtJq09AuwWkR3AOeBngJ9bq8ZX62XNkzbGNIGTaxyLUkpdsWSNkrQxJhKRfwl8HbCBjxljDqxJ45dBb2ZRSnWUtbzj0BhzD3DPmjX4MmiSVkp1FL0tXCmlNrDLuXC4GWiSVkp1FO1JK6XUBtZpSdr+wAc+sL5vUDn2AcsSPAJySZWsFzBaPUjaiUhbPg0KGLEoBdPkkyqZsErPwnHyToveXINya4Kc1SRnN8k6Pn2NU1SzA7TJ0O0sMrhwmGpmkJbJsn32EXLtRSyTkI1r1J0y7STFiDlNV32CMJWjzz+L73UR4dIVzDEvvWxv/JBibYzJzHWIBSnTAhHm0qNL7+NPkE6a2FZC1l8Ay6an+izYLk27QG/rLInlMG5tYzroYbR5mCBdIrFswlQBJwmYskfprx0nTBXIBou4rUXmS7vom3iaieI+5jJb6Q6maGfLtNJlErFpOzna2W4a6W5aThcp4zOV2YHjWSx6/eTCRdzGAoeG38O209/m0Oh7GMveQJ+ZolocpWJ1k7JDSqkmQbaLWW8LreIQuajCwWAvw+YM1YHreVDeQsst0ZtM8WTurVTtbnJeQK20lVppKy2vi3FnJwNnHyQpdPNk5s0crG9j38G/wfJc/N5tHC/dTtA7SM+R+3mm/904g70cNTdQyYzg9XRx1tpJTzEhn4Hc/luIe/pIxGE8Huas2cqeyW+Rbi1isnkyi+NIKo27ZRsL229DLKglRQ76u+lPL4BtczC+iX2tRziT2UvF66dtZ+mbOYDrWbhBEyvl4no2E1tvJxSXUt5gHJdDqdeSTQWkaFO1upnJbGM0OQTe2+YAACAASURBVEngZIjtFE4SUozn8OyQ/mCM0XPfx1mc5NToHfRUnyVOF2inupBUmsLMcQ4NvpPR+BRp8TmX34drR0RWilZxgHqcJ3BzeFaI5doMn/wute7tjKSmGPBPkauMIZbFhLud0cmHsS3INGZwJOFM+nq6vSo1pxsEGmGawMpid2WYDnoopRpsqz9DrjHNfHE7JavClulHqOcHKdbHKU8eYKF8HcOnv0+rNEwlLuJKTIUSXVaVmaCHglNnISzSk64y6E1Tqo3RE06wbeFxilKlmS7Tlgx7Dn6Gxf4bCI1Hf+Uo4+4uaqbIkP8stkmwUxYDmUW2jD9EV2sKr5whTYumVWDvkx8n3a7SKG9lTvrpWziCF7focn2GvBn6zj7KxMAtlPwpeu058n3DH7zSnDM51/zAau84HOjJXfH7rbeOWwVvunvPtQ7hmku3K9c6hI7R7hm91iFcc0m5f03auVo93ARZ9bYZ6HCHUqqjdNpwhyZppVRH0dkdSim1gWlPWimlNjDtSSul1AaWmM6aD6FJWinVUZJrHcAaW6l81u0i0rX8OCMiHxSRL4vIh0SkeHVCVEqp1TNGVr1tBiv9XvAxoLn8+I9YKgLwoeV9f7mOcSml1MuyltXCN4IVy2cZY54rk3WbMebXjTHfW65zuPNiLzq/JM3f3PV3axasUkqtpNN60iuNST8jIr9gjPlL4CkRuc0Y86iI7AHCi73o/JI0Z48dNP7axauUUpcUb5Lku1or9aR/CXiriJwA9gEPiMizwJ8tH1NKqQ2l04Y7VqpxWAH+ZxEpsDS84QBjxpipqxGcUkpdrs0yjLFaq5qCZ4ypAU+tcyxKKXXFjLnWEawtnSetlOoom2V1u9XSJK2U6iivyOEOpZTaLBJN0koptXElOiatlFIbV6cNd6x/jcPjD37AlZh8c4ZUUKeZKXMkuZFue4GK1cNI7RD59hxHnZuJ3TRn4y18a/ZV1FODdGUC8q0ZsCxqbg9jrUEOtHbiug62lfDoxCjfHt/FYlBAHJf/8NdpTPdOJq0t3Fj/Ae1iHwEeZ4IRjoS7uE6O85nxf8RCVKIn2+Ij3xhmaCjLf/5Sgb/6lksjs5Ujk12MNfvY2bNImzSB8ZhiiOHmUe6efgMno21MR33ce2YXf/tNi117uvkXH5zi+yd6qVv9jM04/MeP1Xjnuwc5UNuJnXYpB1N84ehenrWup1Sy+NyhPXzs/jLDuwb5d3+d4VS1j+1bPH79dxf43sl+Ds0P860f5jhd66enP8Oh2QFua3yLLzXew+08yP/zvf3ctCPhb57awx9/I8ebX5vlf/l/Xdr57bxh+wS//Hs2p9s72LHF4eBUD+PVAqm0w6Gpbp44U2TR6ueW4jH+4MFbOdEY4abRKjfN/QM/9ZFB9u0fZTi3yJ98c5h5GSaTS9GIcsw1s9xTeT2Hw90Yy8GzDf/hnhG+Xb2F+8+OUDclfKvIU97tNEOPs81ezs2neHYqhVMsERuLI8n1uLt3YmWznEyuI+e06LJr3H+0j/7d3cwWdtHtj/NA/r08bG7ndP7VkMpycH6IUqbNtvQ5PvbQbrYM2jx5Kku7NMozY13c/6TFqfkubtwVspgepF3oYc4ZYiy9hzJzdCWLPC2v4an5UW4qnWYqGeIjX8jz3t1nOdrYxqzpI++1eWhyJyfqQxRKNpZteKK+j3xJaJeHGZ5+kuM9b2TG3ULOanIs3sNXJvfz6oEJ6naJv310O/tH5zlV62ennOCJ6l625qdxJOJsMEzJrZFyhVqqlyPVrZDLsZDbyrPsZndyiG+Yd5EUyixmhznS3kVfukI9yrG98UMGxx7idP7VDKTnOd0a4WbnaQrxAo+Z2+nNNJiTfmJx8bt6ifBIXI9nMm+k5FQ5nb8FzwrJ2C3ONfu47dznyLUXqHaNsH3su8x07aboVInF5bR1HX62TFDs47C5CbGFgWCME12vwbNCstT5gf86rsudYdehL7AwfBMWCdNmkJzVZKGwjSfjW8l4MacbQ+TcgANdd/BAeBvfPd7Hu4qPMtZ7C2fs3RxrbWGBXh5LbmXG7+JLTw2QlIbZO2Jdcc3BYxPJB1Z77u4hW2scXm17R1rXOoRrbsuekWsdQseYDXuvdQjXnC3xmrRzInvzmrSzEq1xqJRSG5jOk1ZKqQ0sTjZHD3m1NEkrpTqK9qSVUmoD2ywLJ62WJmmlVEfRedJKKbWBddpwx0o1Dn9NRLZcrWCUUupKxYmsetsMVpon/R+Bh0TkfhH5FyLSdzWCUkqpl8uY1W+bwUpJ+llglKVk/RrgoIh8TUTev1wI4CWdX+PwY1/82hqGq5RSl3a1krSI3CIiD4rIk8v57nXL+0VEPiIix0XkaRG59UreZ6UxaWOMSYB7gXtFxAV+FPhZ4A+Al+xZn1/jsP7Ql7XGoVLqqrmKFw5/D/igMearIvLe5ed3sJQjdy9vtwN/uvzny7JSkr5g0MYYEwJ3A3eLSOblvqlSSq2Xq7jAkgG6lh8XgfHlx+8DPmGMMcCDIlISkSFjzMTLeZOVkvQ/u2h0xugiGUqpDecqjjX/OvB1EfkDloaO37i8fwQ4e955Y8v71j5JG2OOvpxGlVLqWomT1Z8rIncCd56366PLw7XPHf8mMPgSL/1N4O3AvzbGfE5E/inwF8A74CXvpnnZXx06T1op1VEupyd9/vWzixx/x8WOicgngH+1/PQzwJ8vPx4Dzp+6PMoLQyGXreOWKlVKvbIlZvXbFRoH3rr8+G3AseXHdwM/vzzL4/VA5eWOR4P2pJVSHeYqjkn/MvBHIuIAPi8Mm9wDvBc4DjSBX7iSN9EkrZTqKMlljElfCWPM91i6f+TF+w3wK2v1PpqklVId5Wol6atFzDr/bnDg+ITJSJNU3CQRGzduYxBqbjcJFh5tsmGVTHOOxHZpZrpJBzXabp50u0IzXUYwhFYK20SkwiZGhHqqTP/cYRZL27FMTM0uUwpniC0HL2rRdrLkm7Mklk0zXcbI0vB7rjVHNTuAZWLqUqQcTVN3y7RNip5oEsHgRD5tL48btWl6XcjyhVknCcj4i7S9Ak7cppEq09WaZjxzHXmqpKMGgZ1mkR7yVo18e4GF1AAA5fYURgQ3bNJKlyjUxomdNIGXX2o7bjOV3o4jERYxES6JsegLxjBYnLJ2M2ydpWaXySVV8v4cidikmvOE6S4QIbY9AAIng+/kEGOoJwVEDNsqT9LK9pKITWR7+FaOvtpJQi9LZHk03CK91ZNUCiMEkiaVNGlYXbTiNNfP3Q/AYs8uziVbyTg+jkQMVw5hxKKdLlLzuqkneephFoCSVyMlbQBsIvpnDzLffR1j0SiWJDiSkHOalMNpvKCOlcTMdW2l2JyilSpiJxGBnaYlOWxiLGJ8k2G+XSDjhOTsJjPtEsPpGTJxDcHQsIuU/Qkq6X5sYtJhnVRYx/WrzHRfj2DIt+cZc3dSaefIOgGuHdIM03h2xIA1Qd6fwwkaADRz/cw5gwTGZVftCWaLO+mpnKSdLlFLd2OZhAgXm4ipoI+c4+NZAXPtEmWvSjXKUXardPvjNFMljre2cVv4Per5ARasPjwJ6GmNMZPZSgqfNmki41CPlm5B6HEXOdfqZ2tmnIW4jCUJnoRUwxzdXgWXgCPVrYwW5nEkop14DMZjnGInjiRYktCM0uTcFlONLoZzi5yrl+nP1UhZAXPtLspenYzVIsbGJqZtUlSCPCKGoltHMEy0uhnOzjHtl2m0XQbzVaabBVJ2TGwscm4bWwynFwtEsXB93zxzrTyeEzPXSBNEQm8+oJhqcWymyLbuBik7xLZiTsx341iGvlwL14p53d7iFU9y/pOvrn4mxa/86MZf11R70kqpjnJ5Hc8Nn6M1SSulOstmWThptTRJK6U6SqeNSWuSVkp1FO1JK6XUBnY5t4VvBpqklVIdxVzWrYSb/MKhiHjAzwDjxphvisjPsbTS0yGWFiIJr0KMSim1aq+0QrR/uXxOVkTeD+SBz7O0+tPrgPevb3hKKXV5Xmlj0q8yxty8fG/6OWDYGBOLyCeBp9Y/PKWUujxJh3WlV1oFz1oe8igAWZaqDwCkAPdiLzq/xuFn7vrk2kSqlFKr0GmFaFfqSf8FcBiwWVrk+jMi8izweuCui73o/DVaDxyfMEsLQSml1PqLO6wnvVJllj8UkU8vPx5fXuT6HcCfGWMevhoBKqXU5TCvtCl4xpjx8x4vAp9d14iUUuoKrPeicVebzpNWSnUUvS1cKaU2MO1JK6XUBhbHmqSVUmrD6rCOtCZppVRn6bSbWda9fNbDhyumFqZwrGSpxFHgUUgFDKRmERLG/X7KqTrTrSI136U769OOHPJem+uSQ8ynh5kPipS9KqFxMUbw4xSOFTHbKpByIpqBS8aNmK6l2NFdJW238SQgbZosmG4A8lYdg0XbpIiMTSXIkbFD5v0MjmWo+Q79+RYAthXT5TSwJGGy1YNjJdgSExub3tQCi2GBtB0QG5swsbHFECUWsbHxI4eJxRRvGDlJKmnx7fF9iMBgsU0h5WOLocupERiPRpTGsyIciXEkYtovk3PbLPoZ2rFNb7aBBdTCFO3QxrUTUk5EOVWnFaXpd6aYT3pwrYjYWOStOiKGRpwnQagGWZqhS1eqTTP0SDsRRa9OO/aIjMWAO0PD5BEMI7VD+JkybSdLZLkshGUytk8jyuLHDnvsoziRz1R6O6FxyFlNyq1xLBNTzfRjmZimVaAZZ0hZAWmrRd/CMfxMD7PeMDE2roR84/AIhZzwtpFDRJbHfNRN0amSDxdouQXG/EFK3lL5qhMLPYzP2bx+1zwFu041KlB2F8iEddpOlhibCBdXApwkpGf2CE92vZ3h1CSWiRkLRjg8keOmkQpPnSly+44ZupnlVLCVne5JfDtHhEtoXOphhrQT4EnIgH+KSnaAatxFyVrEMjFHG9vZkR/ncGULnp2wNT/N09PD7O8/ywNj29g/MkVkbI7M9DBaapJzW8z7ebJOQH9qlsWoRI81S2w5GCNYJBgRzjaHMAYWWx4ZL6Y308CPPRIDRydz3Dhc5dPftHjPmz0GcxUeOd3HG7dP4EpIYDw8CRAMlsSExuNkdYAdXVMcmhuiKxMyvpBmR2+D2AhJsrSY0Kfv8fnV/9HniYlBruur0uvOYxOzEJcxCH7kkXYC6mGaqu9hiyHrRUSJxcRiittGztGIsnz8qzb79naxfSBkIFel0s6yI3MWgKopMd8u0AwccqkQz4rIOG3GayWePGaxf0/C9V1nmIt6SFkBM34Xu9Mn2br7hite8eg3PtpadVL70J2ZDb/C0kp3HG4IPd7iqs/tdWYveqxtUqtupxxNr/rcS8ln1uZS83T1ojd4/nfSln/RYzbxqtuphrlVn3spa/V3mbEv/rkuh3UZ/y19Mhc9Nl9d/X+fOLFX/6aX8OOjT65JO45Eqz43nwouemxmbvXt5Kyrc1ObSVa/bQY63KGU6ihJhw1Ka5JWSnWUuMNW/dckrZTqKB3WkdYkrZTqLJdXmWXj0yStlOooOiatlFIb2CuuJy0iu4CfBLYAEXAM+JQxprLOsSml1GXrtCR9yYmeIvJrwH8F0sBrgQxLyfoBEblj3aNTSqnLFMdm1dtmsFJP+peBW5brGn4YuMcYc4eI/DfgS8D+dY9QKaUuQ6etgreaW6aeS+QplmodYow5wyprHH7h7/7qioNUSqnVShKz6m0zWKkn/efAIyLyIPAW4EMAItIHzF/sRefXOFxau2NtglVKqZV0Wk96pRqHfyQi3wRuAD5sjDm8vH+GpaStlFIbSqddOFxNjcMDwIGrEItSSl2xTrstfFOsgqeUUqtlErPq7UqIyE+LyAERSUTkthcdu1lEHlg+/kMRSS/vf83y8+Mi8hERWXFNRk3SSqmOYoxZ9XaFngH+CfDd83eKiAN8EvhfjTE3AncAz12Z+1PgTmD38vaeld5E7zhUSnWUqzVrwxhzCOAlOsPvAp42xjy1fN7c8nlDQJcx5oHl558AfgL46qXeR3vSSqmOcrWGOy5hD2BE5Osi8riI/F/L+0eAsfPOG1ved0nak1ZKdZTLGcYQkTtZGn54zkeXpxA/d/ybwOBLvPQ3jTFfukizDvAmlu7SbgL/ICKPAdWXCnelGNe9J71v8T52ZM8xmplkS3qC0cI8e5OneWh8K4FJsdM9SV80zkBmkZ2lObpTNfqyVSZrOe6rv5a/vn+AD3+2wH+9p0Q9zOBaIWV3kWaU5vb4u/SmKpyYcHh2OkMUC49M7+TIXB9/dm8P/8f/5/KHfx3zzR/2EOMw2Sxz3eEvMF4rEUQ2D53o4tSUx2huhq99q4JrxRTcJqfmu/joozfyWx8J+K1/+zCPnciy6GfYmzyNYPjewQJ7n/4kj57q5qsPZ4mN8LVHMiQGbEmoN+FwZQv3T93A5780ydyiYUt+hmdnu7j3iQKjU49gE/P1R7PsO/1l7jvaxye+3c31zhEW/CyunWAMfOOJHGFiEycWJ8+EfPEbLb50H0w2Snzuux55fw4/9nj07AB7Jr/D987u4M/+YZju1jmmm0VOTOfIeyHdXoU3HfsvdHsVnpkZ5COf9FloZWmYPPcdG2Si2c032nfwjen9fPnoHk7URum3JnGtmJzTpHbLrYR2invm3sAPTg2x2M7TSLJ8q3Y7H37sdXzx4G6mkiGySY0fHO8mNjYPnNvBRGkfXrtKxl+kZOawfuuX+KXcXfxT93P4Vo7j9S2cqRQxCMWZYxzd/+PclDzB0Md/gx1f+31+dPET3L5zgRNzJSb8Xg7ODjDd7uUrZ2+mVD/H3x/YzqlaPydqo/zeFweY6r+JW+fuoXfxOH3/8HFunfkyb99+nE/eA/+s71scm+vhcHMXx6dzPFnfy7HqKHPtEl94qIe77hU+9/0uPv9IH08mt9JTOcUNJ75I8Y//T/rPPsprrEcYfepu9hVP0wxsRmceJ50C17Sp1A2HZ/tohmkOHgtJ2wEPn+zl6Lk0x6a7+P7ZndxQf4CBscfo+cyHyUY18u0F+mcPkXd9dmbOcH33FK+zH2aYs+yLn2CHd5pq3bCTY9x+a47T0x45q8nBcC+Pjw+xGBZ58PQgFjGtJEP/3GEypoExMDrzODvK87xx9nO8aeQ4252T9KYqzNRTbM1N8GPvKHC20c8tQ1N872CBZ+a3cqKxha88VmS6UaAntUjG8vnh6Qzbuua53jrMTD1F1Xf5x4Vv8eTkMO3Y5V1vzuI4woGTNn7s0Y5tjjW20V05yYc+FnLfkw5vju7l1uZ3iI3N1w5v5S0P/nv270kYm3OZaA9gS8yjZ/vZmp3Ct9amXFscxavejDEfNcbcdt720fPbMsa8wxhz00tsF0vQsNRDvs8YM2uMaQL3ALcu7x8977xRYHylz9Nxwx2l7Oprrl1Ksoln8WSqE2vSTtldWJN27Pu+vCbtXAuZ3tKatONOnlyTdq6FyPbWpJ149eU1r8hVvHB4MV8HbhaR7PJFxLcCB40xE0BNRF6/PKvj51laXuOSOi5JK6Ve2a7iFLyfFJEx4A3AV0Tk6wDGmAXgw8AjwJPA48aYryy/7P9v79zj7ZzOPP59EkEieghxXOLSupQg4hZmMKjLYEYpmZnKdEa1U59ixMegMoPR0o7LUNMaZj4xFVVUXUZoTEJIQjuKBLnQxC2IjkkpIm5txVnzx/PsyTrrvHvv9W5755yzz/P7fNZnv+9av/2std71vs+6PM9631PQndwvAC9Sx2gIvibtcDjaDGtqx2EI4S7grippN6FueGn8PGCXMvm4knY4HG2FrtCP1yoL4Era4XC0FQbcuzscDoejP6Grzd7d4Ura4XC0Fbr6s2tWAVxJOxyOtoIvdzgcDkcfRmgzw2G9D9F2iMilIrJERN60sNjiqnr5x5/Pun7qfc0vtcPhcFRBH3h3R1NRbyR9GzALOCiEsBxARDYFTgRuBw4r+lP8+az3Hr0nvN604jocDkdtfLymtjauIdTbcbhNCOGyioIGCCEsDyFcBmzV2qI5HA5HebTbSLqekn5FRL4hIp2VCBHpFJFzgVdbWzSHw+Eoj9DVlR36A+op6b8ANgIeEpG3ROQtYA4wAvizFpfN4XA4SqPdRtL1vhb+NnCuhW4QkZOAKS0ql8PhcDSEAeXdUQffalopHA6Ho0no6grZoT+g5khaRBZWSwI6q6Q5HA5Hr6FrVXt5d9RzwesE/hhI3/4uwCMtKZHD4XB8ArTbckc9JT0NGB5CmJ8miMiclpTI4XA4PgH6i0EwG2U+NdNIAE5uNrfZvP4ic6Dm3W718WuZx/Vg16zlGcC8ZnObzesvMgdq3u1WH7+WeVwPGvwbhw6Hw9GH4Ura4XA4+jDWhJKe3AJus3n9ReZAzbsVMgdq3q2Q2Yq8HQaxdSKHw+Fw9EH4cofD4XD0YbiSdjgcjj4MV9IOh8PRh9H0bxyKyI7AMcAWQABeA+4JISxudl4Oh8PR7mjqSNo+BnAr+m6Px4G5dvxjEZkU8QaJyFdE5F4RWSAiT4jIrSJyUIHMvURktojcJCJbishMEXlHROaKyO7NLH8ORGREJu/UKvE7ish0q/u2InKDiKwQkcdFZKfmlrYw/04R2UNEdo8/5lCFO9J4u4rI8Bq8taLj4dZmIxJO1W9i1inDdiJyvIiMzuTnts/nC+LWaNsUXdMy7eMYIGjmzhjgOWBIQfzawPPR+RTgm8D+wL8AF6HfS3wAOD357+PAkcAJ6Ndgxlv8IcAvEu4GmeVcG/NssfODgbOAIxPe+dHxaKvfS8DLwD5R2t8l4SzgN5XzRObDwNFWn1eAL6Id2dHAgxFvV+BRq/NkYMP4mmTWc1F0PNbkLbbr/ACwxOL2SP432tJfAH4PPGb1vgHoSLhfBt60a3MksBR40Mp9QsRbZTK/WqudgNnAxnb8Vyb3P4BFBfdGbvscl4TjgeWV87JtY9wt0QHJz4B/ILrvgamZ7bOskfYx/rbA2cD3gCuBr6dtE93rfw0caucTgH8FTkvK/F1gv4wyfwEYYccjgRutbX4CjEq4GyfnXwK+D5xM9Px5qHPNmypMb6qtC+K3Bp6Nzhcm6Y/a7zrA4iTtqeh4WbU0O89VBAswpQecg77R73xgJnBJxHsyOr4XU+LAOOCRKO1du0n/EbjQwtuV4xr1eSFJi/P7OXAEsIE9jM8A2xbISBVQrIjeiHjziRRXFL8vsCBtD+CzUV1/aMdfA+5IuIuAjYFPAyujMnbG7Wy8PwVuRpX63agSHJrIezo6ngtsZMfDCu6b3PZZhb4s7Hp0gDDF2mwKcH3ZtrHzmahiHAtcbffQRgVy0g487sjfarB9Jlr+51u+1wLfAX6JfjQ65t6M3ps/BX4E3IV2fjdU2tV4bwDz0M7pcmD3Ks/OL6PjnwBnAqPQznpmjfY5H7iP1R+xvqqePvFg166pwlSpvABMR0d/k4EZFndExHsiepj3AB4uugns/BfA4ejnul4BjrX4A0neA0BjimBeJR1do48VS3yTpR1C/CBuBdwBXAYMs7ilVa5RLP/UGuWan6QdDDxvD21cro/sgZtSEN6NeM8XlcfSUoWUKoU4v7R95kfHr9WoayxjKPDnwH9aO90SX1dgCzueDaxrx4OBZ2qUq1b77I2O7k9h9d6Alxptmyrt8yWsI03K9VvgYlZ33nFY0WD7LAIG2/EwYE50H6bXYWF0b/86+p8k9X3KfrcHLrC6LLFy7hDx4sHWE3WuSdwGTwLr2fEQolmeh9qhqYbDEMIMEdkBHclsYTfCr4C5IYT4TdznALNF5Hd285wAugaKjnhifB3t2bvQd1ufIiJTUIPkyQn3oxDCNGCaiAxFp6lfBK4RkftCCBOMt1JEdgkhPI0uS6wLfGhlidfpPyMi91g9RonIsBDCB5Y2JKr3MmC8iBwDzBSRq2pcpmtEZHgI4b0QwrWVSBHZDp0FRFHSEUJ4x/KYLSLHA3ei35isYCFwhdWlG0Tk0Oh0uojci05PKx8R3hKdCs9I/vqiiFyAKrbj0FEeIjKEnsbmZSJyCbA+sERErkSV76HA/8bFqRyEED4EbgNuE5EO4NiIdyZwv4jciSqKWSIyAziAnp9ry22fuSJyGHC6yTsXNWqnyG0bgCEism4I4beWx00ishwdLa4X8Z5Elz+eSDMTkb+JTsu0D2g7fIzOPte3MiyzNooxSETWtjINAzqAt+x/MTeYjOfRTuViERmDPpv/BWxnvDkichFwiR0fG0KYKiIHA+8keQ81u9EgtHN43/L4SETa6838rURv9Q7og7VxdH5jDe52qGKvrL+dQvH621NV/t8BnBidj0GXPG608CI6FZ4HTIh4ByZhuMV3AqdVyWs94J+JZgcNXp8JwL4F8VsB10XnBwBbVZGxV3J+JPDv6NR3mh0fVfC/DdCOcRo6jV4/uo77JtxPAX8PTAKGA+Ptf9cCm0W8s0vUvcPa+Cp0KeFcYMcCXiPtswXaQRTOdEqU8UzgwIL43Ymm/cBngZFVZHQm50dlts8ZaOc8GR3tnmTxI9P7zsq5FJ2FTkQ73uvQ0fiF9Z6dgryHoPakZRa60KWjW9L7EJ0JxWEzi98IfxteduiVbeE2+knxOWAWQAjh8xF3IrqE8TB6E89H13u/gE5J50Tcs0MIV2SWYTC6jLIDOir5FXBfCGFFnf9tEkJ4PSePXIjIcyGEHZop01EeIjIM+Ft0VHk1Ogs7DlWEF4UQ3uvF4nWDiOwM7IQuwyypw90cIITwmnnZHIradx6POMPL1s9mQWuFEN4s+b/BwDph9azHUQu90TOg6443AQehI6CD0KnxgSSjE0qsv1XJa5NPUM4RBeFlYEPMwm284aiHyjPolO8N1Pj25QKZ76IGtpV2/C46bX0XWBnxBgEnoQaxBeg6/q0khqEq5X6uIK4ib1o9ecCm6Ej4GnTU801rh9uIRsfG3Qsd81YFOQAAB4hJREFUJd2ETs9nAitQo9/uicx/qyczV14rZNr/rrS6P4h6QfwROjP6UZL3Z9DZ17et/a8DnkaNYts0UMa9c+td8h7O8niK+EXeWfGMd0wDZagp00Od69crmarCONNuxLEWV83QtgjtdUGV4xNRWmrMSRXqRnwCpYpO5V5Kwkf2uzTi3Y1at0ehlvsLUAPMD4F/SmRejS6xdEZxLxXUewoZborkK/0secadga7fTkKn1eeineLpwN0JN8tFMldmrrxWyMQMX+hS3HJWGxm7Gdks7mF0SWYSqpzPQpXrV4FZLa73GDLdM8n3eDoYnU2+AdxP944mNoR+jDoCXAyMrvOcZ8n0UEdf9mrmqtRuR0csy6pwyqy/NVWpoq5vM4Bdo7iXCsqYekPMtd9BwJIC/p7o0s5E4/TooAqUQqGbIvlKv1luj7Us+FVdJHNl5sprhczkP9cnvLSNe7PeWe6Zdp7r8TQX2NmOx2OeREX1AXZBbRUvoLOySUQKuKxMD7VDrxfAGuxPSEacSfrO1sg9jEcJr+lKldUdyXdRK3qRQn0E2N+Oj0bXtitpz1Yp6yBUSf+MxHXN0su4KeYo/TLyFkTH307SUmWf5SKZKzNXXitkoptmhhdcu22Bnxdcz4on028wIy3a2S9scb2z3DMtLdf1MX0mdgaeRW0/TxbJs/Nx6LPxKpFvehmZHmqHXi9A0yvUOqV6NDrFXF6Qths6XV2BjnIqG0FGAhML+OOAve34AHQTzFEJ53Oo9byyi26fSOblBTLrKf2KvOdN3r7V5KFLIUXKajt6bmYZi7qdTQd2RD1w3kZHd/uVlWnXsq68JshcYTL/MOKtQ8buPEs7xBTOYnQJ6U67tq8Dx7S43gvoufNzjOX/ZhKf6/E0D9i04FmaT3d/+2ryhJ72pCyZHmqHXi9AyypWW6mOobtS3cHieyhVe2AOQdexhwK7WPwRCW8n1Go+PIlPeRdaueahvqYPokr6YeC8hPsHrFbmo9GlmR4uWcl/Nksf1Cgt2+0x+d/+lvfhGdwD0PXZw5P4fYBP2fFQ4Fuoq9llscIxXkfEuwg1dnbjWfpEYMuMMuXyau3OuyHhro3unqso9L9EDY5FCj13C3euq2mWe6bFZbk+2r27W0F8R3xfErmoNkumh9qhrb/MYhtatg0hPC0iJ4UQpmT85/955v53GjpaGgucEUK429KeDCHsEfFORdfMq/LsfJFx1kGNU6NCCCutrI+FEMYY70LUkLQWamAdBzyE3vj3hRC+Y7wsd8aSbo+PhxDG2fHX7BrchU7HfxpCuLQG91RgasoVkWfQB3aViEwGPkB3aR5i8cdV4b2PjlK78Yz7jqW/CPwYuD2E8EZayRK8hSGEMfbCqP8BNg8hfCwigk7dx0Tcm9G2GYoan9eza3QIanA80XhZLqRlXE0dAwy93UusqUAVw2QtHmp0qWyQ2AYd/Z5h50+V5RX8L02bn8gcjLodrqT7KLTbdmsy3Bkp5/YYl3EuthkDVUSLGuHS3diZrmvOL8uL6jQI7RB+gHoRzEBHuOs3wHsaHSFviHrHVF4ktC49jau5262zXEhzeRbXAVyKDgretLDY4jZolFvjmZjeCA/d6HQJOiuZkKRd24zneiCEpr9PujchIgurJaG70Erx0IfmPYAQwsuir1K9Q0S2JtrmXIIH8Pto+/KeUZk6UO+UClYF3Ur/gYi8GEJYafI/FJGYtxfqAXMecE4IYb6IfBhCeCjJd89MHuhW4g1RxSbBRp0hhPdFZFWD3Hg2s0BE9gohzLPXCHzUAM+yCV2oe9f9tiW64sZ2Bbp8VYb3A1SZDbbrdLuILEUNcrcW1DtnuzXkb+HO5d2GzoAOCiEsBxCRTVn98qLDynJFZA+KIejMjzI8wxR0nfxO4Cv2WoMJIYTfodfUkYPe7iWaGdARzVj0rXtx2IbImFaCNwvz447i1kJd3j4uy7P4daqUfWO6e6U8xuqXNQ2K4jsosIyT4c6Yy0N9y5dirouY8Qddl09Hs1lcK/cN6JLDY6jCXYou4exWlmfcqm5cRC5muTw73xxd5gB1cRsPjCv4X+526ywX0lyexRUat4vScrlo5zCLnlu5ZwMfluUZN71XzgP+G92/4N4dmaHXC9DUyuhIaP8qabc0wBtFYp2O0vYryytZlyxlXpBe052xLC/5zzDg05+Ei44Qd0NH9p01/l+XR/R2tjplyeI10Ea5Cj3XhTSXdz/wDbr7xneiG2UeaISLLvVsXyW/V8vy7Hwx0QDD4k5EPVZeaUWbtGNoa8Ohw9GOsOWlSehn6jax6F8D9wCXhhDeLssVkfGoDeHZgvyODSFMLcOz88uB+0MIDyS8I4CrQwjbN1L/gQZX0g5HGyHXi6kMt9m8styBDlfSDkcbQUSWhRC2aia32byy3IGOtvLucDgGAkp4JzXd46kVeTtqw5W0w9H/0Il+pejtJF7QVx40wm02ryzXUQWupB2O/odp6Oap+WmCiMxpkNtsXlmuowp8TdrhcDj6MAbVpzgcDoejt+BK2uFwOPowXEk7HA5HH4YraYfD4ejDcCXtcDgcfRj/B438tyIklsaFAAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "\n", - "#plt.figure(figsize=(30,10))\n", - "sns.heatmap(ketArr_reshape, cmap=\"coolwarm\", vmax=200, vmin = -200)#,linewidth=0.1)\n", - "plt.show()\n", - "#plt.imshow(ketArr_reshape, axis=0), cmap = \"hot\")" - ] - }, - { - "cell_type": "code", - "execution_count": 265, - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#plt.figure(figsize=(30,10))\n", - "sns.heatmap(midArr_reshape, cmap=\"coolwarm\",vmax=200, vmin = -200)#,linewidth=0.1)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, - "source": [ - "### plot average pattern for each group\n", - "- Ketamin\n" - ] - }, - { - "cell_type": "code", - "execution_count": 205, - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 205, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(50,8))\n", - "sns.heatmap([np.mean(midArr_reshape, axis=0)],cmap=\"coolwarm\",vmax=200, vmin = -200 )" - ] - }, - { - "cell_type": "code", - "execution_count": 207, - "metadata": { - "slideshow": { - "slide_type": "skip" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "-27.613214" - ] - }, - "execution_count": 207, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "deltaKetminusMid = np.mean(ketArr_reshape, axis=0) - np.mean(midArr_reshape, axis=0)\n", - "np.mean(deltaKetminusMid)" - ] - }, - { - "cell_type": "code", - "execution_count": 208, - "metadata": { - "slideshow": { - "slide_type": "skip" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 208, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# t test\n", - "tTestArr = scipy.stats.ttest_ind(ketArr_reshape, midArr_reshape, equal_var=True, nan_policy='propagate')\n", - "plt.figure(figsize=(40,10))\n", - "sns.heatmap([tTestArr[0]], cmap=\"coolwarm\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, - "source": [ - "## show the t-test difference between the groups" - ] - }, - { - "cell_type": "code", - "execution_count": 210, - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 210, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# turn back to brain?\n", - "img = masker.inverse_transform(tTestArr[0])\n", - "nilearn.plotting.plot_stat_map(img, display_mode='y', threshold=0)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, - "source": [ - "## Plot amygdala pattern in each group" - ] - }, - { - "cell_type": "code", - "execution_count": 222, - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 222, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "img_ket = masker.inverse_transform(np.mean(ketArr_reshape, axis=0))\n", - "nilearn.plotting.plot_stat_map(img_ket, threshold=1.5, display_mode='yz', draw_cross=False, \n", - " cut_coords=[-2,-18],colorbar=True, vmax=99) \n", - "nilearn.plotting.plot_glass_brain(img_ket, vmin = -200, vmax = 200, colorbar=True, plot_abs=False)" - ] - }, - { - "cell_type": "code", - "execution_count": 223, - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 223, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "img_mid = masker.inverse_transform(np.mean(midArr_reshape, axis=0))\n", - "nilearn.plotting.plot_stat_map(img_mid, threshold=1.5, display_mode='yz', draw_cross=False, \n", - " cut_coords=[-2,-18],colorbar=True, vmax=99)" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "metadata": { - "slideshow": { - "slide_type": "subslide" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 40, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# another trial of interactive plottive \n", - "view = nilearn.plotting.view_img(img, threshold=2, title=\"Ketamine - Midazolam Amygdala\")\n", - "view" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, - "source": [ - "## Now we do similar thing but with vmPFC \n", - "As it might be involved in regular (no reconsolidated) extinction learning" - ] - }, - { - "cell_type": "code", - "execution_count": 224, - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "mask_file = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", - "mask_file = nilearn.image.math_img(\"a>=4\", a=mask_file)\n", - "%matplotlib inline\n", - "nilearn.plotting.plot_roi(mask_file)\n", - "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", - " sessions=None, smoothing_fwhm=4, standardize=False, detrend=False, verbose=5)" - ] - }, - { - "cell_type": "code", - "execution_count": 225, - "metadata": { - "slideshow": { - "slide_type": "skip" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_008/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", - "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", - "shape=(97, 115, 97, 1),\n", - "affine=array([[ 2. , 0. , 0. , -96.5],\n", - " [ 0. , 2. , 0. , -132.5],\n", - " [ 0. , 0. , 2. , -78.5],\n", - " [ 0. , 0. , 0. , \n", - "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1223/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", - "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", - "shape=(97, 115, 97, 1),\n", - "affine=array([[ 2. , 0. , 0. , -96.5],\n", - " [ 0. , 2. , 0. , -132.5],\n", - " [ 0. , 0. , 2. , -78.5],\n", - " [ 0. , 0. , 0. , \n", - "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1293/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", - "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", - "shape=(97, 115, 97, 1),\n", - "affine=array([[ 2. , 0. , 0. , -96.5],\n", - " [ 0. , 2. , 0. , -132.5],\n", - " [ 0. , 0. , 2. , -78.5],\n", - " [ 0. , 0. , 0. , \n", - "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1307/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", - "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", - "shape=(97, 115, 97, 1),\n", - "affine=array([[ 2. , 0. , 0. , -96.5],\n", - " [ 0. , 2. , 0. , -132.5],\n", - " [ 0. , 0. , 2. , -78.5],\n", - " [ 0. , 0. , 0. , \n", - "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running 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masker.fit_transform(func)\n", - " midazolam.append(beta)\n", - "\n", - "ketArr = np.array(ketamine)\n", - "ketArr_reshape= np.array(ketArr).reshape(ketArr.shape[0], ketArr.shape[2])\n", - "ketArr_reshape.shape\n", - "\n", - "\n", - "midArr = np.array(midazolam)\n", - "midArr_reshape= np.array(midArr).reshape(midArr.shape[0], midArr.shape[2])\n", - "midArr_reshape.shape\n", - "\n", - "\n", - "## Create condition labels (1 = plus, 0 = minus)\n", - "label1 = [1] * ketArr.shape[0]\n", - "label2 = [0] * midArr.shape[0]\n", - "condition_label = np.concatenate([label1, label2])\n", - "condition_label\n", - "\n", - "X = np.concatenate([ketArr, midArr])\n", - "X = X.reshape(X.shape[0], midArr_reshape.shape[1])\n", - "X.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 226, - "metadata": { - "scrolled": true, - "slideshow": { - "slide_type": "skip" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " Running 1 iteration\n", - " Running 2 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+ "## Now we will do similar thing - just shuffling the condition label (Y) so we basically randomizing the lables\n", + "This should generate a chance level prediction" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [], + "source": [ + "## Lets do permutation tests - shuffling the condition label\n", + "import random\n", + "condPerm = np.array(condition_label)\n", + "permScor = []\n", + "#cv = KFold(n_splits=10)\n", + "for i in range(n_iter):\n", + " print (f'Running the {i+1} iteration')\n", + " random.shuffle(condPerm)\n", + " print(condPerm)\n", + " \n", + " mean_scores = []\n", + " cv_scores = cross_val_score(model,\n", + " X,\n", + " y=condPerm,\n", + " cv=cv,\n", + " groups=condPerm,\n", + " scoring=\"f1\",#\"roc_auc\",\n", + " n_jobs=11, # set number of CPUs\n", + " #verbose = 5 # set some details of the activity \n", + " )\n", + " mean_scores.append(cv_scores.mean())\n", + " permScor.append(mean_scores)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "# now lets see the mean score\n", + "score = np.array(permScor)\n", + "\n", + "#import matplotlib.pyplot as plt\n", + "plt.hist(score)\n", + "print(f' Mean of permutation score is {np.mean(score)}')" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'rand_score' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m#plot permutation histogram and real one\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscore\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"blue\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrand_score\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"red\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0;31m# chances of getting our score\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf' Chances of mean permutation score to be random is {len(score[score>=np.mean(rand_score)])/len(score)}'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'rand_score' is not defined" + ] + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#plot permutation histogram and real one\n", + "plt.hist(score, color=\"blue\")\n", + "plt.hist(rand_score, color=\"red\")\n", + "# chances of getting our score\n", + "print(f' Chances of mean permutation score to be random is {len(score[score>=np.mean(rand_score)])/len(score)}')" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "ename": "TypeError", + "evalue": "len() of unsized object", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m 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color, vertical, norm_hist, axlabel, label, ax)\u001b[0m\n\u001b[1;32m 213\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mhist\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 214\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mbins\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 215\u001b[0;31m \u001b[0mbins\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_freedman_diaconis_bins\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m50\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 216\u001b[0m \u001b[0mhist_kws\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msetdefault\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"alpha\"\u001b[0m\u001b[0;34m,\u001b[0m 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TDC41Tcb5eCNiEjcGr6CPMXhVf/qNmN9csObVwP3d2osYXGa5DPg94Eg3FuAO4E+WY9Zu7vQbx5cCXwMuXqqc3bpfZlBIL17svkudc97cFs7Pm8V9ntMAdwLvX+Y51wNru/sXAv8KXLMcsy6Yfx2TfbO4z3P6YuCl8+7/O7BrUllX7KWhqjqV5GbgXgbvzt9eVUeS3NTN31aDyyqfBR5lcD3wQ9Wdrib5F+AhBpdZvsoEv+LdNyvwiSQvB34CvKOq/m+pcnZL3wLcV1U/Ptu+yy0nQJKPM/gjsC7JLPDXVfXhZZj1CuBtwGPd9XeA91TVwWWWcwNwR5JVDK4y3F1VE/tYZt/f//nSM+crGFxig0GhfKyqPjuprP4vJiSpcSv5PQJJ0hhYBJLUOItAkhpnEUhS4ywCSWqcRSBJjbMIJKlx/w96bA2txldfcwAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "sns.distplot(score, hist=True, rug=True)\n", + "sns.distplot(rand_score, hist=True, rug=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "ename": "TypeError", + "evalue": "object of type 'numpy.float64' has no len()", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mweights\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mones_like\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscore\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m 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\u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrand_score\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweights\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mweights_real\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mTypeError\u001b[0m: object of type 'numpy.float64' has no len()" + ] + } + ], + "source": [ + "weights = np.ones_like(score) / len(score)\n", + "weights_real = np.ones_like(rand_score) / len(rand_score)\n", + "plt.hist(score, weights=weights)\n", + "plt.hist(rand_score, weights=weights_real)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## Lets plot each group's array to see the pattern of activation" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "-1187.1151" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "## check maximum and minimum values\n", + "np.min(midArr_reshape)" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "#plt.figure(figsize=(30,10))\n", + "sns.heatmap(ketArr_reshape, cmap=\"coolwarm\", vmax=200, vmin = -200)#,linewidth=0.1)\n", + "plt.show()\n", + "#plt.imshow(ketArr_reshape, axis=0), cmap = \"hot\")" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#plt.figure(figsize=(30,10))\n", + "sns.heatmap(midArr_reshape, cmap=\"coolwarm\",vmax=200, vmin = -200)#,linewidth=0.1)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "### plot average pattern for each group\n", + "- Ketamin\n" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(50,8))\n", + "sns.heatmap([np.mean(ketArr_reshape, axis=0)],cmap=\"coolwarm\",vmax=200, vmin = -200 )" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "- Midazolam" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(50,8))\n", + "sns.heatmap([np.mean(midArr_reshape, axis=0)],cmap=\"coolwarm\",vmax=200, vmin = -200 )" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "-28.281826" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "deltaKetminusMid = np.mean(ketArr_reshape, axis=0) - np.mean(midArr_reshape, axis=0)\n", + "np.mean(deltaKetminusMid)" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# t test\n", + "tTestArr = scipy.stats.ttest_ind(ketArr_reshape, midArr_reshape, equal_var=True, nan_policy='propagate')\n", + "plt.figure(figsize=(40,10))\n", + "sns.heatmap([tTestArr[0]], cmap=\"coolwarm\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## show the t-test difference between the groups" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# turn back to brain?\n", + "img = masker.inverse_transform(tTestArr[0])\n", + "nilearn.plotting.plot_stat_map(img, display_mode='y', threshold=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## Plot amygdala pattern in each group" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "img_ket = masker.inverse_transform(np.mean(ketArr_reshape, axis=0))\n", + "nilearn.plotting.plot_stat_map(img_ket, threshold=1.5, display_mode='yz', draw_cross=False, \n", + " cut_coords=[-2,-18],colorbar=True, vmax=99) \n", + "nilearn.plotting.plot_glass_brain(img_ket, vmin = -200, vmax = 200, colorbar=True, plot_abs=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "img_mid = masker.inverse_transform(np.mean(midArr_reshape, axis=0))\n", + "nilearn.plotting.plot_stat_map(img_mid, threshold=1.5, display_mode='yz', draw_cross=False, \n", + " cut_coords=[-2,-18],colorbar=True, vmax=99)" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# another trial of interactive plottive \n", + "view = nilearn.plotting.view_img(img, threshold=0.5, title=\"Ketamine - Midazolam Amygdala\")\n", + "view" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nilearn.plotting.plot_roi(img)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## Now we do similar thing but with vmPFC \n", + "As it might be involved in regular (no reconsolidated) extinction learning" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_file = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=6\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " smoothing_fwhm=None, standardize=False, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_008/modelestimate/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1223/modelestimate/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1293/modelestimate/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1307/modelestimate/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1315/modelestimate/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses2/modelfit/_subject_id_1322/modelestimate/results/cope2.nii.gz\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "Running 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"[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "data": { + "text/plain": [ + "(23, 1435)" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ketamine = []\n", + "for func in ket_func:\n", + " print(f'Running {func}')\n", + " beta = masker.fit_transform(func)\n", + " ketamine.append(beta)\n", + "\n", + "midazolam = []\n", + "for func in mid_func:\n", + " print(f'Running {func}')\n", + " beta = masker.fit_transform(func)\n", + " midazolam.append(beta)\n", + "\n", + "ketArr = np.array(ketamine)\n", + "ketArr_reshape= np.array(ketArr).reshape(ketArr.shape[0], ketArr.shape[2])\n", + "ketArr_reshape.shape\n", + "\n", + "\n", + "midArr = np.array(midazolam)\n", + "midArr_reshape= np.array(midArr).reshape(midArr.shape[0], midArr.shape[2])\n", + "midArr_reshape.shape\n", + "\n", + "\n", + "## Create condition labels (1 = plus, 0 = minus)\n", + "label1 = [1] * ketArr.shape[0]\n", + "label2 = [0] * midArr.shape[0]\n", + "condition_label = np.concatenate([label1, label2])\n", + "condition_label\n", + "\n", + "X = np.concatenate([ketArr, midArr])\n", + "X = X.reshape(X.shape[0], midArr_reshape.shape[1])\n", + "X.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "skip" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running 1 iteration\n", + " Running 2 iteration\n", + " Running 3 iteration\n", + " Running 4 iteration\n", + " Running 5 iteration\n", + " Running 6 iteration\n", + " Running 7 iteration\n" + ] + }, + { + "ename": "KeyboardInterrupt", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0mgroups\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcondition_label\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mscoring\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0;34m\"accuracy\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;31m#\"roc_auc\",\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m \u001b[0mn_jobs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;31m# set number of CPUs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 13\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 14\u001b[0m )\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36minner_f\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 71\u001b[0m FutureWarning)\n\u001b[1;32m 72\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0marg\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0marg\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparameters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 73\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 74\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0minner_f\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 75\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/sklearn/model_selection/_validation.py\u001b[0m in \u001b[0;36mcross_val_score\u001b[0;34m(estimator, X, y, groups, scoring, cv, n_jobs, verbose, fit_params, pre_dispatch, error_score)\u001b[0m\n\u001b[1;32m 404\u001b[0m \u001b[0mfit_params\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfit_params\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 405\u001b[0m \u001b[0mpre_dispatch\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpre_dispatch\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 406\u001b[0;31m error_score=error_score)\n\u001b[0m\u001b[1;32m 407\u001b[0m \u001b[0;32mreturn\u001b[0m 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step.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 73\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mversion\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0;36m2\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 74\u001b[0;31m \u001b[0mbst\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdtrain\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 75\u001b[0m \u001b[0mbst\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_rabit_checkpoint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 76\u001b[0m \u001b[0mversion\u001b[0m \u001b[0;34m+=\u001b[0m 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\u001b[0mtraining\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " ] } ], @@ -5764,8 +2045,8 @@ " y=condition_label,\n", " cv=cv,\n", " groups=condition_label,\n", - " scoring= \"roc_auc\",\n", - " n_jobs=10, # set number of CPUs\n", + " scoring= \"accuracy\",#\"roc_auc\",\n", + " n_jobs=1, # set number of CPUs\n", " \n", " )\n", " mean_scores.append(scores.mean())\n", @@ -5774,7 +2055,27 @@ }, { "cell_type": "code", - "execution_count": 227, + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(23,)" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "condition_label.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 65, "metadata": { "slideshow": { "slide_type": "slide" @@ -5785,23 +2086,23 @@ "name": "stdout", "output_type": "stream", "text": [ - "Area under curve: 0.70 (+/- 0.22)\n", - "90% CI is [0.51666667 0.86666667]\n" + "Area under curve: 0.43 (+/- 0.11)\n", + "90% CI is [0.34166667 0.47916667]\n" ] }, { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 227, + "execution_count": 65, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -5819,6 +2120,46 @@ "sns.distplot(rand_score)" ] }, + { + "cell_type": "code", + "execution_count": 165, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.\n", + "[Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.3s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.6s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 3 out of 3 | elapsed: 0.9s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 4 out of 4 | elapsed: 1.2s remaining: 0.0s\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Classification score 0.9285714285714286 (pvalue : 0.013972055888223553)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=1)]: Done 500 out of 500 | elapsed: 2.6min finished\n" + ] + } + ], + "source": [ + "## use sklearn permutation test\n", + "from sklearn.model_selection import permutation_test_score\n", + "score, permutation_scores, pvalue = permutation_test_score(\n", + " model, X, condition_label, scoring=\"accuracy\", cv=cv, n_permutations=500, n_jobs=1, verbose=5)\n", + "\n", + "print(\"Classification score %s (pvalue : %s)\" % (score, pvalue))" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -5831,22 +2172,22 @@ }, { "cell_type": "code", - "execution_count": 242, + "execution_count": 168, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 242, + "execution_count": 168, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -5863,22 +2204,22 @@ }, { "cell_type": "code", - "execution_count": 243, + "execution_count": 175, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 243, + "execution_count": 175, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -5889,7 +2230,7 @@ ], "source": [ "img_mid = masker.inverse_transform(np.mean(midArr_reshape, axis=0))\n", - "nilearn.plotting.plot_stat_map(img_mid, threshold=1, display_mode='ortho', draw_cross=False, \n", + "nilearn.plotting.plot_stat_map(img_mid, threshold=1.5, display_mode='ortho', draw_cross=False, \n", " cut_coords=[0,42,-7], colorbar=True, vmax=100)" ] }, @@ -5902,6 +2243,135 @@ "This supports the idea of ketamine as promoting reconsolidation, while midazolam patients recovery is more associated with the typical, yet transient extinction." ] }, + { + "cell_type": "code", + "execution_count": 176, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 176, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# t test\n", + "tTestArr = scipy.stats.ttest_ind(ketArr_reshape, midArr_reshape, equal_var=True, nan_policy='propagate')\n", + "plt.figure(figsize=(40,10))\n", + "sns.heatmap([tTestArr[0]], cmap=\"coolwarm\")" + ] + }, + { + "cell_type": "code", + "execution_count": 180, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 180, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# turn back to brain?\n", + "img = masker.inverse_transform(tTestArr[0])\n", + "nilearn.plotting.plot_stat_map(img, display_mode='ortho',cut_coords=[0,42,-7], threshold=1.5)" + ] + }, + { + "cell_type": "code", + "execution_count": 181, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 181, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "nilearn.plotting.view_img(img, threshold=2, title=\"Ketamine - Midazolam VMpfc\")" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -5911,7 +2381,7 @@ }, { "cell_type": "code", - "execution_count": 277, + "execution_count": 149, "metadata": {}, "outputs": [ { @@ -5936,14 +2406,14 @@ }, { "cell_type": "code", - "execution_count": 278, + "execution_count": 150, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_008/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_008/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -5956,7 +2426,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1223/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1223/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -5969,7 +2439,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1293/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1293/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -5982,7 +2452,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1307/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1307/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -5995,7 +2465,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1315/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1322/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -6008,7 +2478,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1322/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1339/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -6021,7 +2491,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1339/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1343/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -6034,7 +2504,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1343/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1387/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -6047,7 +2517,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1387/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1464/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -6060,7 +2530,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1464/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1499/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -6073,7 +2543,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1499/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1263/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -6086,7 +2556,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1253/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1351/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -6105,59 +2575,7 @@ "output_type": "stream", "text": [ "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1263/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", - "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", - "shape=(97, 115, 97, 1),\n", - "affine=array([[ 2. , 0. , 0. , -96.5],\n", - " [ 0. , 2. , 0. , -132.5],\n", - " [ 0. , 0. , 2. , -78.5],\n", - " [ 0. , 0. , 0. , \n", - "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1351/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", - "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", - "shape=(97, 115, 97, 1),\n", - "affine=array([[ 2. , 0. , 0. , -96.5],\n", - " [ 0. , 2. , 0. , -132.5],\n", - " [ 0. , 0. , 2. , -78.5],\n", - " [ 0. , 0. , 0. , \n", - "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1356/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", - "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", - "shape=(97, 115, 97, 1),\n", - "affine=array([[ 2. , 0. , 0. , -96.5],\n", - " [ 0. , 2. , 0. , -132.5],\n", - " [ 0. , 0. , 2. , -78.5],\n", - " [ 0. , 0. , 0. , \n", - "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1364/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", - "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", - "shape=(97, 115, 97, 1),\n", - "affine=array([[ 2. , 0. , 0. , -96.5],\n", - " [ 0. , 2. , 0. , -132.5],\n", - " [ 0. , 0. , 2. , -78.5],\n", - " [ 0. , 0. , 0. , \n", - "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1369/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1356/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -6170,7 +2588,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1390/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1364/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -6183,7 +2601,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1403/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1369/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -6196,7 +2614,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1468/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1390/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -6209,7 +2627,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1480/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1403/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -6227,10 +2645,10 @@ { "data": { "text/plain": [ - "(10, 1265)" + "(7, 1265)" ] }, - "execution_count": 278, + "execution_count": 150, "metadata": {}, "output_type": "execute_result" } @@ -6257,7 +2675,7 @@ }, { "cell_type": "code", - "execution_count": 279, + "execution_count": 151, "metadata": { "scrolled": true }, @@ -6989,14 +3407,14 @@ " Running 715 iteration\n", " Running 716 iteration\n", " Running 717 iteration\n", - " Running 718 iteration\n" + " Running 718 iteration\n", + " Running 719 iteration\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - " Running 719 iteration\n", " Running 720 iteration\n", " Running 721 iteration\n", " Running 722 iteration\n", @@ -7302,8 +3720,8 @@ " y=condition_label,\n", " cv=cv,\n", " groups=condition_label,\n", - " scoring= \"roc_auc\",\n", - " n_jobs=10, # set number of CPUs\n", + " scoring= \"accuracy\",\n", + " n_jobs=1, # set number of CPUs\n", " #verbose = 5 # set some details of the activity \n", " )\n", " mean_scores.append(scores.mean())\n", @@ -7312,30 +3730,30 @@ }, { "cell_type": "code", - "execution_count": 263, + "execution_count": 153, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Area under curve: 0.73 (+/- 0.19)\n", - "90% CI is [0.56666667 0.86708333]\n" + "Area under curve: 0.64 (+/- 0.15)\n", + "90% CI is [0.52380952 0.76190476]\n" ] }, { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 263, + "execution_count": 153, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -7355,30 +3773,47 @@ }, { "cell_type": "code", - "execution_count": 267, + "execution_count": 155, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.\n", + "[Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.2s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.4s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 3 out of 3 | elapsed: 0.6s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 4 out of 4 | elapsed: 0.7s remaining: 0.0s\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Classification score 0.619047619047619 (pvalue : 0.3069306930693069)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=1)]: Done 100 out of 100 | elapsed: 19.3s finished\n" + ] + } + ], + "source": [ + "score, permutation_scores, pvalue = permutation_test_score(\n", + " model, X, condition_label, scoring=\"accuracy\", cv=cv, n_permutations=100, n_jobs=1, verbose=5)\n", + "\n", + "print(\"Classification score %s (pvalue : %s)\" % (score, pvalue))" + ] + }, + { + "cell_type": "code", + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 267, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "img_ket = masker.inverse_transform(np.mean(ketArr_reshape, axis=0))\n", "nilearn.plotting.plot_stat_map(img_ket, threshold=1, display_mode='ortho', draw_cross=False, \n", @@ -7387,30 +3822,9 @@ }, { "cell_type": "code", - "execution_count": 268, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 268, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "img_mid = masker.inverse_transform(np.mean(midArr_reshape, axis=0))\n", "nilearn.plotting.plot_stat_map(img_mid, threshold=1, display_mode='ortho', draw_cross=False, \n", @@ -7419,34 +3833,9 @@ }, { "cell_type": "code", - "execution_count": 274, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "#plt.figure(figsize=(30,10))\n", "sns.heatmap(ketArr_reshape, cmap=\"coolwarm\", vmax=200, vmin = -200)\n", @@ -7460,32 +3849,9 @@ }, { "cell_type": "code", - "execution_count": 479, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 479, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "tTestArr = scipy.stats.ttest_ind(ketArr_reshape, midArr_reshape, equal_var=True, nan_policy='propagate')\n", "plt.figure(figsize=(40,10))\n", @@ -7494,30 +3860,9 @@ }, { "cell_type": "code", - "execution_count": 480, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 480, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# turn back to brain?\n", "img = masker.inverse_transform(tTestArr[0]) # turn the t array back to brain image\n", @@ -7537,7 +3882,7 @@ }, { "cell_type": "code", - "execution_count": 270, + "execution_count": 188, "metadata": {}, "outputs": [ { @@ -7562,14 +3907,14 @@ }, { "cell_type": "code", - "execution_count": 271, + "execution_count": 189, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_008/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_008/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -7582,7 +3927,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1223/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1223/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -7595,7 +3940,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1293/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1293/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -7608,7 +3953,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1307/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1307/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -7621,7 +3966,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1315/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1322/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -7634,7 +3979,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1322/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1339/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -7647,7 +3992,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1339/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1343/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -7660,7 +4005,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1343/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1387/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -7673,7 +4018,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1387/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1464/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -7686,7 +4031,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1464/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1499/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -7699,7 +4044,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1499/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1263/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -7712,7 +4057,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1253/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1351/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -7731,59 +4076,7 @@ "output_type": "stream", "text": [ "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1263/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", - "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", - "shape=(97, 115, 97, 1),\n", - "affine=array([[ 2. , 0. , 0. , -96.5],\n", - " [ 0. , 2. , 0. , -132.5],\n", - " [ 0. , 0. , 2. , -78.5],\n", - " [ 0. , 0. , 0. , \n", - "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1351/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", - "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", - "shape=(97, 115, 97, 1),\n", - "affine=array([[ 2. , 0. , 0. , -96.5],\n", - " [ 0. , 2. , 0. , -132.5],\n", - " [ 0. , 0. , 2. , -78.5],\n", - " [ 0. , 0. , 0. , \n", - "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1356/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", - "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", - "shape=(97, 115, 97, 1),\n", - "affine=array([[ 2. , 0. , 0. , -96.5],\n", - " [ 0. , 2. , 0. , -132.5],\n", - " [ 0. , 0. , 2. , -78.5],\n", - " [ 0. , 0. , 0. , \n", - "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1364/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", - "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", - "shape=(97, 115, 97, 1),\n", - "affine=array([[ 2. , 0. , 0. , -96.5],\n", - " [ 0. , 2. , 0. , -132.5],\n", - " [ 0. , 0. , 2. , -78.5],\n", - " [ 0. , 0. , 0. , \n", - "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1369/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1356/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -7796,7 +4089,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1390/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1364/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -7809,7 +4102,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1403/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1369/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -7822,7 +4115,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1468/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1390/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -7835,7 +4128,7 @@ "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1480/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", + "Running /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses3/modelfit/_subject_id_1403/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -7853,10 +4146,10 @@ { "data": { "text/plain": [ - "(21, 500)" + "(17, 500)" ] }, - "execution_count": 271, + "execution_count": 189, "metadata": {}, "output_type": "execute_result" } @@ -7897,8 +4190,10 @@ }, { "cell_type": "code", - "execution_count": 272, - "metadata": {}, + "execution_count": 158, + "metadata": { + "scrolled": true + }, "outputs": [ { "name": "stdout", @@ -8264,15 +4559,15 @@ " Running 358 iteration\n", " Running 359 iteration\n", " Running 360 iteration\n", - " Running 361 iteration\n" + " Running 361 iteration\n", + " Running 362 iteration\n", + " Running 363 iteration\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - " Running 362 iteration\n", - " Running 363 iteration\n", " Running 364 iteration\n", " Running 365 iteration\n", " Running 366 iteration\n", @@ -8627,15 +4922,15 @@ " Running 715 iteration\n", " Running 716 iteration\n", " Running 717 iteration\n", - " Running 718 iteration\n" + " Running 718 iteration\n", + " Running 719 iteration\n", + " Running 720 iteration\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - " Running 719 iteration\n", - " Running 720 iteration\n", " Running 721 iteration\n", " Running 722 iteration\n", " Running 723 iteration\n", @@ -8930,8 +5225,8 @@ " y=condition_label,\n", " cv=cv,\n", " groups=condition_label,\n", - " scoring= \"roc_auc\",\n", - " n_jobs=10, # set number of CPUs\n", + " scoring= \"accuracy\",\n", + " n_jobs=1, # set number of CPUs\n", " #verbose = 5 # set some details of the activity \n", " )\n", " mean_scores.append(scores.mean())\n", @@ -8940,30 +5235,30 @@ }, { "cell_type": "code", - "execution_count": 273, + "execution_count": 159, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Area under curve: 0.77 (+/- 0.19)\n", - "90% CI is [0.6 0.9]\n" + "Area under curve: 0.62 (+/- 0.18)\n", + "90% CI is [0.47619048 0.76190476]\n" ] }, { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 273, + "execution_count": 159, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -8983,22 +5278,60 @@ }, { "cell_type": "code", - "execution_count": 275, + "execution_count": 160, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.\n", + "[Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.1s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.2s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 3 out of 3 | elapsed: 0.3s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 4 out of 4 | elapsed: 0.4s remaining: 0.0s\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Classification score 0.6428571428571429 (pvalue : 0.2714570858283433)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=1)]: Done 500 out of 500 | elapsed: 47.0s finished\n" + ] + } + ], + "source": [ + "score, permutation_scores, pvalue = permutation_test_score(\n", + " model, X, condition_label, scoring=\"accuracy\", cv=cv, n_permutations=500, n_jobs=1, verbose=5)\n", + "\n", + "print(\"Classification score %s (pvalue : %s)\" % (score, pvalue))" + ] + }, + { + "cell_type": "code", + "execution_count": 190, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 275, + "execution_count": 190, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -9015,22 +5348,22 @@ }, { "cell_type": "code", - "execution_count": 276, + "execution_count": 191, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 276, + "execution_count": 191, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -9045,6 +5378,71 @@ " cut_coords=[-2,10,-4], colorbar=True, vmax=40)" ] }, + { + "cell_type": "code", + "execution_count": 192, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 192, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "tTestArr = scipy.stats.ttest_ind(ketArr_reshape, midArr_reshape, equal_var=True, nan_policy='propagate')\n", + "plt.figure(figsize=(40,10))\n", + "sns.heatmap([tTestArr[0]], cmap=\"coolwarm\")" + ] + }, + { + "cell_type": "code", + "execution_count": 193, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 193, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "img = masker.inverse_transform(tTestArr[0]) # turn the t array back to brain image\n", + "nilearn.plotting.plot_stat_map(img, display_mode='x', threshold=1.3) # stat plot everything beyond threshold" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -9072,18 +5470,18 @@ }, { "cell_type": "code", - "execution_count": 481, + "execution_count": 182, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Ttest_indResult(statistic=array([ 0.07429292, 1.7787675 , -1.0281352 , ..., 0.53116673,\n", - " -0.3836815 , -0.34552237], dtype=float32), pvalue=array([0.94155392, 0.09128311, 0.316798 , ..., 0.6014582 , 0.70547421,\n", - " 0.73349779]))" + "Ttest_indResult(statistic=array([ 0.41356513, -0.18528277, -2.0933478 , ..., -0.79962456,\n", + " -0.91735995, -1.1412845 ], dtype=float32), pvalue=array([0.6850448 , 0.85548933, 0.05372314, ..., 0.43640887, 0.3734689 ,\n", + " 0.27164508]))" ] }, - "execution_count": 481, + "execution_count": 182, "metadata": {}, "output_type": "execute_result" } @@ -9096,14 +5494,14 @@ }, { "cell_type": "code", - "execution_count": 482, + "execution_count": 184, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Number of significant voxels is 0\n" + "Number of significant voxels is 1\n" ] } ], @@ -9111,14 +5509,14 @@ "# use fdr correction for multiple comparisons\n", "from statsmodels.stats import multitest\n", "# we need to reshape the test p-values array to create 1D array\n", - "alpha = .05 # set p value\n", + "alpha = .1 # set p value\n", "fdr_mat = multitest.multipletests(tTestArr[1], alpha=alpha, method='fdr_bh', is_sorted=False, returnsorted=False)\n", "print(f'Number of significant voxels is {np.sum(fdr_mat[0])}')" ] }, { "cell_type": "code", - "execution_count": 439, + "execution_count": 185, "metadata": {}, "outputs": [], "source": [ @@ -9132,22 +5530,22 @@ }, { "cell_type": "code", - "execution_count": 414, + "execution_count": 187, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 414, + "execution_count": 187, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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ARs5JJ52UZPEMsSmz7B555JFd5/K8sHPOfd7znpdkUYhijvlptpFtcop1xBwwW6oq2gJc0KIqSuSCGCOTxPPQDBezWyqmlkF7zFXmxTXXXLPrGMb84osvnmyjsT6++MUvJkkeffTRJItMA9gZSV00zv6ysuXKts1kmipghM3ZX5qNN8fec4GuCma3jp+5eFxVIIbjqsIxfE+7vqdkkQmBX3nHO96xst+NHbj55puTLLJwfvqnfzrJciEhMOWHbFuwA+2Tbe/eTxicB5OWNSJZZsXant3fqiii56iLitLXcb/EMbZ9F1uq+ubiS57nzsgYM0fw66yTXZRr87jiiiuSJKeeemqSxX6UcR99+UMPPZRksa8km8fPiL0t+1izvv3ssWkzsKeYrxWzuspSAPbh9uWVrY/XwPZY58jqqPZjzDP8MPueT3ziE0kWvy3e8573TPa5cWCCrBXWlfE3IP931ifAtv7iL/4iyWJO3n///UkWrPTOfmw0Go2WHWg0Go1Go9FoNBqNRqPRaDQajb2AJ7Ie83U6aDuF/e6Pr0TYYfcBM3nG/5s9YR0ws0XMluJzovewhMzgIEI/XsMRdfehYpGYyQUc1YcRc+SRR+46hgi5dWMrVhj9hjkA44/IPAyEq666KklyzjnnpLFncO211yZJTj755CQLJhJjboYbn48aavyfaDXP0YxQ273ZhJXdW294jLBbn8yMJEfc6UOlRQVsm1x7ZL7ynRkzwKy/StvZc9Gaz77O+H807pohsD7+8i//MsmC+fTwww8nWTCC/HySWtPS3/s4nq21T4EZoVx7tFvb8MgOTerMAuuuWuPP1/b8Gz9z/ysmeeXrK71NM2pHJhfrHNf82Mc+liQ588wz01jGJz/5ySTJMccck2SxjuK7YCExxuwnxjG3ffMM7IPxSX7e1qLETznbh3Vk27Ztu67FOdbSrDTCvRfh/qzHOqdrP3Uf1Zzz/DX70XPOrEHej2POXpJXslCa6T2PSy+9NEny/Oc/P8liDM1anWL784zIIqn04r2fsSYs7WB/zBkw2pLXfN7DPnUGBKiyF/wbwn51XCvYp7mGhLMZKn1yxoX75n7xM5/61KeSLMaz9+n7Bz7ykY8kWa7JYfg3rtdyfFyysAnXO7Bfxd6ZYxx/zz33JFmwaw3O631vo9E48LGu7MBPrd3ifvfH10aj0Wg0Go1Go9FoNBqNRqPR2PN4KsnfzR61Gew3f3xFfw6NV2t8EbmGTTV+B6zHZCago+FmIk1Vex/bJXo4HsOrq5+aqTX36j4RoYQpOerJucqrK397XDwOVcV57u/GG29MkjzwwANJWvdyd/ChD30oyaIqsBlNZh+ZCQrjOVkwKdD+gvlhxggRdb43k7ti4FmDbYpJ4sq8ZnE44m6Wy5TO5dgXMDLDbN8V+5FrMXZmnFUsF8/ZVVWTYeQzlhdddNHk/RzMgPGKtiuMVxjbZketYsZVGrB+9rxWzDnDDMKp76qK6pWv9muV5eDrTN2nbbZiw1TXrirSg5F14zHDv8DUYT69853vzMEMmJLHHXdckgXrCP9R2Yn97vgd57Kv4Vh8sNt2JXjvP6pK8mMGkRnZFePVsBb4uuz0qXYrvVhnglhfFnvGt1ca5J4HyWItxZ5/6qd2sBc+97nPJUnuu+++JMm55547eV8HM8Z9SLK8R3bmSrLsuxhfa7/yyrNmj+EsGJ45n7OeVCzW8VzsyZr61X6kYmZXmtsjC5d+4VfNWDRjnP5zf5XGuDN06AOZCklnK2wFkCWFBjj786OPPjrJ4vmiPY3t+PdqlaE5rt1mUzt7a+qcJDniiCM2fH/33Xdv6IuzOT7zmc8k2aihzW/wZsU2Go0DA+vKDmybP2Qn9ps/vjYajUaj0Wg0Go1Go9FoNBqNxt7Dk8kT35s/bBPY8n98RRMTHTWihZWO41hVFe0jvnOEmeieI8au1F6xhMy6GDV3YKzQH2uOVawSR9AdvSeiCROE8RivbVaMo/VVxWxHUn0e7RL9pA9XXnnlrms3O2Q1LrvssiQLdo2ZItiL2aY8X2x5iqEGzHYzQ5TjsVEYbWZkmQnFvOD5j9dwdN6wLc3pCFZYpcVpmFlI/4naWx+xep2qXMy883wEsOFgd37gAx9Y2deDATCbGBPbnRlzoy1VOnj2ZdUz97yxtutmKmMDV3k388+sQz63Rnilvzpes2ILVhXA/bl9gbMjpphenqueLzw/qsUfbNW2YQCTvYAP4Hky5mZjMva8juw46/hxTGW3ZjBxLXy7mX28sp7Q/njNp4vKL69ivM615bmCD69Y5dXn2PDIMqxYYd5Hkd1w3nnnrd3/AxVkovE8YL49+OCDSerxTxZZW4cddliSxTNhXWDfXmWeeH/udj1npjSV3dYc47Wy2an7S5azi8ZjfV+e69Ylxs9al7aqF2H/kiz26L0/3/dgL3jKKackWdZD9r4c38yc8v7d84HjYFYnC1vxb17vUfwb1nUd0Clm70amBBmX2N5Yg+L+++9PsvARXJM5gT1feOGFU8PVaDQaWwtPJNmzf3vd+n98bTQajUaj0Wg0Go1Go9FoNBqNvY6nkkzXQdxtbNk/vsKmgfFKlNysEqKHRBPHSDPRPyKDROc4BwYfkTn0q4igEwWkTTOYgNkZySKKWbEP59ghjqQ7Mu8o/3jtuUryvpb75miodeK4Nq8j6xam8rvf/e7Jax7sOPbYY5Msxpwo8EMPPZRkER3GfsyANWvT/x/PqWzM1baJmHMefWD+ADM2kmWWNJhii071aTNM13WOn4JZtmb/mdno8eG8cZyZbzAAqiqy+JSrrroqycFZgfj2229PsrBxbL7SSq3YRyM83q4IXbGBzJitGLBTLECzucxktI6gWVEcP8U6HPs0wiwX98s+2zbszAmPT9XX8Vj3xWxL/AUagweLvqC1+8yuNOu4Yr6O9m49SGuXeo6YLW0GrNeZkaGUbNw3OFMGrOvjK/3lClPzfO5aHhfgPQvfWy/T1b2T5flrTWfWXl4vvfTSJAenrjf7O8bPzFH22tYgHkHWD+NpvwfzFe1I+z727X7W1na3Txzb4hVfXGln+zxgLW7vEab23KPu7XgOr74PM7DpA/s165ObbTveA7aM7ihoXc49i8svv3zX/48//vgNrzx/r/+V/qr9cWW7tIuWfrKYQ/xGq1jW/r3p33jMUfoG85U5OJW1xBrDd+yBmRPMazJHuD/st22y0WhsKTyZZr42Go1Go9FoNBqNRqPRaDQajcYex5NJ/mb2qE1hy/3xFfbMtm07qoYRYbc+jhmlZoiM58D6oCo8kTdAlI9rERV0lXii3VUV45GNYZ3Y6rVieJj5ajaGNdCmqsCvq+VKG2aF+V7criPy4/8//vGPJ+lK2ODmm29OsrBrxonKpkSqYTUQBTabw0yNZJlhZH1hYDYgMFvKkWuYFa7iPWJd9mJlg1UV4ar9qe/mULHOKx1Nj9/ITHB/zTbm+Zih/tGPfjRJ8t73vnetPu/P+JM/+ZMkC8ar2Xi2o8pPjd/Z71sfz99X2pnYtNkmYJUvty/2fDIT0MwVM2Tn2OHjuV57zGAxE9LM1+p1CpXGrdc9s/VZw+nbO97xjvIa+yOYw9u3b0+y8Lc8A/Ybfv7W0p7KWrHuttlwle8ys4nPWU/Y+9g2x/Y8HysGbMV4rfSJK/88tl+xZ6trA/tf+1tncXgfmSzbtRndgDapCH7jjTcmWewnD2QtWPZzjK9Z/GZ98xyxu9HGOQdGHK8GeyPasLY2+3OubR85tZe2vdCXMWNuhH29GdfA+s60P7JdK/a6v6+ugQ17j2Htftodtfn5bcPejv6iR8r+s1mHuwf0oJ///Ofv+ozMCGcI8uosTu9lnIHl32HO0Bx/E8BAZw55ffA64f2r91e+lte8MSuM+eeMAcA5niv4gYMtg6bRaGxxHEyyA41Go9FoNBqNRqPRaDQajUajsc9wIMsOoImIPg5RMLMRgKOAUywLMzP57pFHHkmyHDHmGtYAM0PF1XHNPpk615HEiilYRR6BGb5TVeM9FpVGrc91RN3RUVeZnaoMbs1BIuuw3y6++OKlcw5kXHfddUmSE044IclCM6mqOk6kmsg1rA8izpw/atZZI8wMC1fHNWsFezYzvKqwPTIqKn3ZOe2+ChVbahVDb12mVXVe9bkrwI72bl01j4M1e63rdSBXH/7iF7+YZOFnzdywH7HvM2NwFbw+4Hfsm80gt23zOmW3nldVZoHZt9ab5NrWaAacN35vJqD9v+/TTBSvm9YG9T2On3OsGb5ek4B1zmEOsgbs7wxY2E34A3w3ftQ+wMzJiiE67hts+zwD/H2VUWNmEsd7HbG25Xhtr+dVBkDFrjbrvNrDuP2p+wb2ERX7Fni+c3/WAR3P85zh1ffnzCja4PMDMavh+uuvT7LMTjVTmfFlLOzLR7/Cvptjx73M2DavHI8Ne99i/+T9+cjo9pyDleeMAsNsQxikfO4MA2cqjceCai5yjhnzXguq/R2auiPrlmuxv2Rt4n7YVzbrcHPgdytZEOM8YWyxhUob3nbB8/R+wZkztvdxvcE+qznjNqt9KnaCLXluTe2XbMf8XvD65/HgOObkJz7xiSSLfWSzshuNxjOCg0F2oNFoNBqNRqPRaDQajUaj0Wg09jkORObrZZddliQ55ZRTkiyitkTNiNARySOCSySO6CIYo8OOchO141zaJLpnDZqpaqlju2aOjiwS61pZu839NZPFunpz7KMpfcSKFVyxFc0Aoa+OuK7SrfWY0U+imlS4PPvss3Mgg6qyMLnNmq40e7FNbNHMEesFJnXFXmtHcQ2uzTOBWeJot9kctofx2rapivk6x2a0vc9pJE8dU7FX1mXGep5MaZTC1ql0HStNajPUDsTK2VTdNTuoYrxWjJ4R1bN1te05PT1nMVivFYx9slZnxXC0ZhufV0xBt2MGrfsx3q/Ho2rL9llpM05dG9jvg6pSsp8rfmV/ZcAyR9HwA2Yw27ebXTylkW54ncdPMLZmR9unH3bYYUkWtsczwsfDhLXm5XhNs588Z8zstp2bcVhpJo+2ZrurWPHraBVPodLRnGqrqisAI8s+w5kRB8IeB43Xo48+Osni3qyhW2WLsc7ZJyYL28V+vC8389jal85U87yzLu2Uj7dmpes52J9yH5yHLTi7gePNdhz7M6cJzjnefwGOo89mvMJiHa9tf189J/pNxta73vWuNJZB5hIar9juaGtzGVnVHtFMVmcO2Z9Osax59swVXivdfa6NnbBO8P55z3vehuPogzOGxv44C8O/L3w/1nD2XvlAzCxoNBr7AVrztdFoNBqNRqPRaDQajUaj0Wg09gKeyIHHfD3xxBOTLKK2jlo78kz1Xmstma06/t9sUaJ9MLOI4jsSbwZIFYkGU4xAM5PcTzM7zLozi8RsmymdQOv3VCxC4Mi7WWFmI4IpNmLFOINlCTPnpptuSpK87W1vy4GIo446KsmyxhIRaEeHeb5TlUuTafsGZgmZMeLotKuR0idHvZkPzA/myxjdd5uVNp/1MecqwYNVLNVKJ9ms68re19WGnWLS+n5c8d1ssIpBw7z48Ic/nCR53/vet1aftjKonMw9mxUFKvblKhuvfFHFgLUNYCPWJjTTaYqpZeaq51dlT2ZTeZ56zozXntPD9XpgzUvPBfsK2+3YXpWlUfkZr3Vem/ZXBiy+nLXLfpE9idntXj+d/TLFCrQteN/AtfDZjDH2jE8365Zrec/D+/EYnhe24ewi+ua2wMjASuo1YLQ1763MAF4nA2LqmuvAmUtm+lZ94plUWsfoQZ5zzjlr9+WZBhk7P/uzP5tkWa/Rlcrn/Kx1Wce2nCHAuGNvfI49eV/i85hX7KGmsiUqTWCjyg7zfpY+eL9Gn6aYr1XWmvvrfZvP53v6xG8ofMF4HfyF2e32UYw1be2PNrw3QRbEi170oiSLccLOp3x59R44M82/+XgmZsqCqcwsM1+d3Qn8Gxk/jFZslYHB55w/7hWYG14Hqwwi1izs1vsHxpbPr7322iTJu9/97jQajcZeR2u+NhqNRqPRaDQajUaj0Wg0Go3GXsCBJDtAJUM0c4h+OSrsiKy1MKdYUsDsIDNzeA9zg375vaQAACAASURBVFdHGs3UMFvILNfxGmaBAFfGdjSTKLj1PEGlQzv2o9Lo8/uKJVL1ydcZ+2aWDzCrgfu65ZZbkiRvectbJvuwv+GTn/xkkoVGEuNBBBoQDUYT2JVRzYrzsxqff/W8zSzxPKAPaISZ3cJxzDmzzsf+mblU6VlNsZ7GvlT6rauq0Pv+K03ROQ0uo9KOHVHpeXp+mwXq544vQWvvne985+y1txpgNGIvrtBu1g2wduqU/qizFirN04pNa59fZSRM6ZvajlwVvfLFbnsu88A2lCzswvZUzTezC7kfM1bsV6a0Xq3ZWjGUq/v1/DErfKszYKn8fdJJJyVZ7FFgfD788MNJFkxvM3Qqv1RpsifLtlDtD/DF1vCz1vzUc00Wex2qn4/X5pU1y8wswDhwXMXIMrvQjOmpz+Z0u6vshTmt2FU+n3PHKvHJMlvM1+BZMPYwpPFV+5NPP+GEE5IsGH34DeauNV6tlVrVCRhZeZ4H3tN7z8+8sj3aB5pt6+uNx25GU36EdTbRgTa7z+zpZHlsKgas54AZ9R5zPsc/eU8xtl39pgHW++e+Lr/88iTJhRdeODEqBw+2b9+eZLFnZqw9H8b/V787vc+p7N/7+Kq90c+aec1zxd87WwefZ13WivHq/Rhs1/E+vI44U8Q65dwvr57XzkS94oorkiTnnXdeGgc2eNbj31OqTDLvW9s+Gk8be6Hg1vxfFxqNRqPRaDQajUaj0Wg0Go1GY4vg7rvvzqtf/eqceuqpOe2003bJxIz44z/+4xx22GE5/fTTc/rpp+c//sf/ON8wsgNz/zaBfc58JYL6kpe8JMlytNbMMWCdykoTc2Q2mJFkFol11Hh11UVHxx15d8Ry/H+l+1MxNAwijkQWHWGdino6Ormu/pkZTO6zjzMjajzW91lFaw8//PAk+xc7ZApUOH7BC16QZGGnRHsff/zxJIuIslkQsAStdbyK2Q3mKkBXmsVckwg0bN0KRN7RXhvbciTdcwK7ddS/Yn+s834V+3vqc1+rYsRW50/1w21Xdm4dKzMsGVue//5Y2RX/Wc19UOms+vuRcWYNSzPrfQ0zx0Gl8edrT+kEmr0Mqnk3x6qq2Ozj2mYdSWsMMqerMax0u83gmpqPHospZm5S67PbDoC1crcqA/aYY45Jslij7MNgEaGPxxrtMbe+rv3vqn0D59iGrLtaMQ3pU+UDxznGGmXt12q+mollVrrt2deeyqDwq/vANd0Xv690v1fttzy/rSPt+7H2qPdq7CPZ227lPc4111yTZKH1at1Uxs0a9l73vd7ZD41tmBnHq9uwBiyo2OFzPn689tz3Pq7yn/gI+8apuV3NRVBpgXvsAWww65iP2VbO1vOe0L+7mAMwoHm/P+5L9gTIgqBGifcAjNvoV8w+tea310GPPc+bNtlfzdUySZbZz6wTvForHMztl5yhwPcjw5tr0F9+A7FOYouwh+kDr9izWbj2RdwvrMikWY4HCtAex0a2bduWZOO+3/tSrw/gxhtvTLLYr5177rl7oceNrYBDDz00/+W//Je89KUvzXe+85287GUvy+te97pd+xrwz/7ZP8vv//7vr99wM18bjUaj0Wg0Go1Go9FoNBqNxsGMo48+Oi996UuT7AiCn3rqqfnmN7/59BtG83Xu3yawz5mvaEqhSeZqqHO6eD6+0pgaz6kiIo4cmgFLBI62zYitGF1T/a70JtdpY+zrnG7iOm3NMbDmqsM7YjtVtdjRebOG3CZM0auvvjpJctZZZ032fasCLShrpVkvjygw7NG5cfGzss7NiEoHmT5wTbMIKwasGShEDkdGhfV1Knu2VpwrRldsbY/LyJaqmCOV1uu6jMyqvfF7988MALft+eDnx5i6wviVV16ZZGtHa6+77roky1pfVQVzP1NnMUw9H9uZj7Xvsj43qDQifZ2pcyo98jmY7e1xct9HG68YjdyfNfoq7deKxUi7rHVTzAL6ae3LKVbbeM2KKVvpzKIDnyT/5t/8mzxTQLf75JNPTrLYq5gRyucPPfRQkuSxxx5LsqyzW2XgMA4j+6jKyrEGI98zH2AV8Tl9Y8/iPnEvnJcsfJDt08/doP/eH1Xat1PMRN+3mXh+7zlpJrwzDcBm9knuk1nohvdowHuBrcjUYv8Ca9d1D0Bln86A4dXPc2y7yvIxm5Y1lT2i9xpzPn3E3Fw05hiylXb4Olh3r4/Pt2Y28J6KZzLu09h3mk3I/XFu9fytMX3zzTcnSX791399zbvdvwGzGZu1vTtDIak1wCtmttdoroV/tc83o3a0e84xU7XKxvEejT7O7e+nfo9Y2xUmLL8fGBfWi6m9x1Tf/FvqyCOP3HAvyWIP8UzuHxqbB2siNsBvUDS1/beYZHkO2oatmcyc4PfKu971rr1xK40tgm984xv5y7/8y/z8z//80nd/9md/ln/8j/9xjjnmmPzWb/1WTjvttNWNITuwB/GMFdxqNBqNRqPRaDQajUaj0Wg0Go3dxXe/+928+c1vzgc/+MFdRATw0pe+NHfeeWee/exn59Zbb80b3/jGfOUrX1nd4F6QHdhnf3xFE/PUU09NsojaVZHiSm8OECFxRdQxCubIuKN3rhbKNYjYOfLs6AvnrWIjOno3V53X55nJVLH2Vl0TOOq/rgaVzzframTGEAHmGEeKOdb6XjBGGdOtqgM4Ag23JHnRi16UZMEcMEsK1gbviQY7am12UMXcGaPnZuZUVYCxb9hOZqjRd1fydR/HCtnMKaLdZmZVDCTPXzOAN6tXPN5vxQCu5lqlQ1udP/bLLAXfr6P29jXMB8aRdmBa8EzQ5EuS97znPcUI7FvAEAQ8S+vL2RdUPtAspJEJwbjhm6c01kZYR80aZRXbdOrawGvQFBt7/Nw2ADzvqkyDVf3klX4y5hUT1rqblSbmKuYrr/YHvtZURsR4ntnJvI5MrU9/+tNJkl/7tV/LvsCHPvShXf9/8YtfnGTBHh0r7CYL/8jcpP/41UceeSTJgtlj+/C4jN9j584EwL8yxvSBMeV7+xv6aD1SV69OFpkRnjPW1rQ2Kn2BWVLpDK/KbjIDz5qi7stchsictv6UFieYW3Oq7yvdb1cUZ6+zFcC6gs3TR2tBez/C99gAc5fnZnsdn0+Vrca1zbT2eGIDbmeO1Tf1WbUvX3cPPdfOiDlt+cpGPdddDb7K9hgZsp7DwLU0eJ1iLI99wY989rOfTZK88Y1vLO97f8anPvWpJDvSWZPlscfusdnRl1d1Sfzb1z7K6yLHm81qluroyw877LANbfo3qvfIlYYr98We3/rKq37zVntc1jjgbKZKn7v6XTLOJ+zyYGNm76/g70KsidifdYD9+zBZPHfWGvvLat+G7aLjfOaZZ+6x+2k88/jBD36QN7/5zfm3//bfTv5+GP8Y+4Y3vCHnn39+Hn744V2/uSeB7MAeRDNfG41Go9FoNBqNRqPRaDQajcZ+g6eeeirvfe97c+qpp+aSSy6ZPOb+++/PUUcdlUMOOSR33HFHnnzyyV0BnRJPZP9lvh577LFJlqu6O0pWsdIqRpmZgFOMQF6JUlaVsystKbNr3e5UJNv9rPT9jEqDp4rEV8yPVX2pruWopq/B90QyiTiNEXazFiomC9c0m5iI7f4QwaQSY7K4D7OlKxamK2U7ig0LxIwfMFYXtb1aJ8+6jlzzW9/61obj6CPPgHlBVJJrjpFrGLy0YVa5X810NUtqDlO6q9UxHvtqHoCKFbgO7KfcF/s5V63nPJgn2D/zafRr6CM9U3qBn/vc55Isxslaj/gF69hWerjVcxrB/Zs5DMz29jysmNW2iSltM9voHMO8Yr5W68UqdtWcrZqFWK11ZsvYV0wxAqvqwhWb0Cwg7qOa6x6ncV0e2fX7Asccc8yu/6M3VmmYWrMOWEeVcfAaZ03LqT2LfTasVMbYz5Ox5NpeA6yxj58Z2SGet2ZRe41iLvI6xU4Z73MVPC+tUWtWH2PouQhs1x7XqYwr782qdcBtWcOxYsKDsSr5VVddlSQ555xzlvqzL3DUUUclWd6/eI9r32bmNPfkbCjrCI/nYIt+1r7W3Drv51OxW8dz5l6rvXGlEVvpzE+xu9fdV8xlvblPniPjGunMBu/lrL/J8d7P27Zp75ZbbkmSvOUtb1nr3rY6qLZORpsZ4bYP7Bw/nSyzSXm1rj9t2rfRJmNMH/zbecrW8O/WAeYazpTwbwXWC7I4WFemMkyTjTZd7XOsfc1YeX9oG3VGnrVxR9/ia7S+59bEhz/84SSLvRb2CuyPpmyq0ilmXpn5an+Kb2MN5vv3ve99T+POGs8k/vRP/zTXX399XvKSl+T0009Pkvyn//SfctdddyXZ8WxvueWWXHHFFTn00EPzYz/2Y7npppvm96it+dpoNBqNRqPRaDQajUaj0Wg0Dma88pWvnC2SecEFF+SCCy7YXMP7s+Zro9FoNBqNRqPRaDQajUaj0WhsWayr+bqJv6ju9T++Usji537u55Isi2RXxTmqAkRViuZUSk+V1uSUPIuOA453EYy59P2pflXpSHMpSFX60yr5gip1at0CXFWKqlNzncIyfkcamu/T1H+nCliUHtx4441Jkre//e1L97uvceWVVybZmKrqdPIqTdqpQqT+O0XbKROeJ+P4OCXDqcdOKXKRDMtIkPLhFERSkZAOGc+1lIeLCbjQkVHNKR8/JTtQFSWq0vM8l3xNz8mpAlxzhe/m5jl9dAEHF8YgXWxM/yMN65kCfXHBnUpyg+PtR43K142fOQ12KsUyWU5bsi3bp3kNmIqeruuz52yiSq9dVbzC/fP92h7tT12EZZ3CjVVxL6e6V2nmc+nElfxEsrAZirq99a1vLfv5dHD55ZcnWexPkoXNOL2TV6c/Vn7lscce2/DefhWfyRwf22aO0xekYGjLxbFsm16jfZzlKsb/4+erIj2rCmeN4+D3lWTSVFtV8SqPnddF7+1sazzT8b6dQu+1p7p/F6WyxAfrq9fZ8dpojV199dVJkrPOOiv7AuzLX/KSlySpbb0qduW11n6W9qZkBzxvgNvcLNYtpjXel689x5qZs1OvH1P+tSp2WGFV4c/xe/82GI+zjfu3jeXgvL44/df3SbESitC+853vXHlPWx1HHHFEkuW1wPs1MCV/gl+37I5/69KmfRr+wmn4VeHSES4K7QJa9MkSOF4D+P7RRx+dvG+wSqaJdc+p5fSF30B8jy1WEjzeP462igwav2VYR0lz75TyrQEX+PPv5Er2ZrR5Sw+tWuPHti2HZUmRm266KcnCLttmGmvLDvzk/CGgma+NRqPRaDQajUaj0Wg0Go1Go7Gu7MBW+uMrgv4utmIGj5kLlfB/FfWdYgSadTfHuKreGxUjYtV5Zgv5nHULcFV9WYWKVQeqKJOvYWbC1LXNXDU7xAVxiDq5eAnHE+3Ejj760Y8mSd773veuuuW9CqLi4/0T5TY7jCgu41AVCjGDxxFpHz/Flqrmitvme/rGszIzsbKt0T6q5+b3cyxsULGpVjG959qaY8JWzDXPg9H3VKydufno6CzHu+gCEfyp8eJ5URRi0/o1u4nPfvazSZZZEmZ2mJ32+OOPJ1kuHlaxge2vkmX2dlXUBn9RZSvY31bFTFYVaTEbrPLhVbFEs4YqW5pqy2uaGbFmP5l1anaNmQZTTC3326woZ0ow9hUrzEzBKaYWxzIPbrvttiTJ61//+qX+PR3APBztyVkMLvZpO/d94ledGVKxjUdWO8cyhmao0aYzDugjTB/mJO/x06vWbmC/WTG054qlVu1OvV+3EFLF4LNdV4W5VvW1YiJWjHf7cJ4JrGQXn+KaY+YCjGaez77y6RTRrJj1jJ/3M6Dyp54TnjvJwkdXGSZgqvDi1LVXMaqnvl/nfqrij5VdVu1OocrWM/u2uob75IwT7zXHNszaxlfhX7i2M7A437/TzG4kG+wjH/nIrmufffbZ5VhsVbjoLKj2b4zHmLHGWMH+tg/32uu9fpW9YJb6VOZmtfetinz5eXIfPFfv4cxeH39b07aZqv797YLNLrLp9RP7drHIsV3PBfwc76+99tokybvf/e409j3IuNi2bVuSZWZ55bun9k7eh9rHVUUUDWcXAey4WdONtWUHNoFmvjYajUaj0Wg0Go1Go9FoNBqNxv5YcItogpk6lYadmbDW7bD2H3A0efz/HCttXb2np8NCXbft3cUqjULA2Fb6nI5MVsw09ICmGF9moBHRqvSLYIHwOVFOR3mJdmJPv/3bv50kueSSS5bue28B/cHjjz9+6Tv6zSv354hyxTrG3nllvDieKLD1asZzKu1XR8odHa70MSvGxSpbrVgpFYsFzOkIrsMsreax2zYjsWIi+vvR51Ss2Dk9t4o9zpzkmrAlpjRfzU7YV7BPxsZ9j9wbdmW9Uc43qwQwBqM2Gv+v2FHWBaPtKS22sQ+gso3xs2o+2H7cf0fo3e4qtpR9rJksZidWfTLjyfpzvK5iltsHeU4z5mYxeBxop1rLp46FebOn8dznPjfJxntB64trY8fWMfccNisKVpnZQrCPwJTWLf7ATEIzWp1RZCYbx88x/cb/Vxk9u5u9sDu+fB1t+6RmwvrZ8Cyn7Lxi+M5pkJqF7nnudvBNo9/mXJ4jfn9v4LLLLtv1/1NPPXXDd9/+9reTLOsTg4oBWzFDK3Z4sqwfWrVV2dectqtf5/YeU9eq9gLraryvoxnua8zNl4rha93dKf/sdcMZZ7TFfsPavswfvvd6ap939NFH7/rugx/8YJLkAx/4QLY60Kxlj+911b9juN+pPcscG997Gu/1PcbV7zmeCVkiI6zp6/no3yn0wRkXHOf9qH97jOdUmWRe4+gLzFfvt+ibNWOn/DOf+X7922YrZFAejKiy5datETL6X++Bq8yBOR187Io9Fef7N0TjIMa6mq+bQDNfG41Go9FoNBqNRqPRaDQajcZBj71AfN07f3wlqpQkL3jBC5IsognW4KqYsBXLzuxMV7Ybo2AV28MRkjnN17nqvbvDWt2s9mvFqFvn2mZYrasvWzELiIKipzMyOazjVzGZXV0VxgfMUbOiHMUyM2Nf4Nhjj02yYEtNjX1VfR1wjvWOPE5EmB09dxXT8Vw/J8aWsXIF9IqdYsbIKnuvovE8T/TviMqb0Vtpb3pe0/fxvl391X2aY4xU9zv3OrZZaYbOXbvSDwVmR4zjzPNiDl1zzTVJkve85z3Z0/j0pz+91HdHr61TbLsisgyjEBtwtLvSlh7hDIrqOVTsTLOOKnbU+Ny8JpmVaYaKWSVE1Hm1DrTvaapiMqwQzyMzzcx2tzab/aqPH/2WbbfSqV63GnHF+l/FgORa+JE9hU996lNJkpNPPnlDX8ZrUeGZ50zGh/2nx5r7we+66r0ZsCML2+xaYJuqmCJmjMxlIkwxX6vnjs2xdvl+Ksaox8nM+fE720TFNp9jwvraXm9HW/QabN9sf2e/VOncWy/Tz3A8l++wsSuuuCJJct55503e5+6A/Uuy2LtxXfwKPhpUOrcem3W1tKfaXFfDdW5trfb3q9j8m2XbVlkO1fozXnsuu2eujxXD132wvnOysH/gzA/WGV59f3yOb3QGlpls7JGT5Ljjjlt5n1sJ7FW8htlHMC7MV2c5JMtrl/W68Z8VA3wuA4H2Ya2Pc5fvuB+uRX+dMTH3Owtt9EceeWRD+1Ma2s58cjYfrx5TfBL7JO4f32Tt1yl/TD/M2LXu/OGHH55k7/jZxjJgv/OMq72/1+9qrRjPqf6uYV/MfpW5gP2QTetMQmel7u861o3dx16QfG3ma6PRaDQajUaj0Wg0Go1Go9Fo7DfM11GbxVEHfw7mmA7WxzGLotI2S+Yj65t97z7PHTd1ThXdr6L167IDpj6r9P6qSHrFCHSE1npr47Fmh5n9wntrW9pOHDW1BizVgZO9VyH4lltuSZL8zM/8TJJFVHXsK58R5TbDu9L4tMaWmWnWaSU6N7JnKjbf1PMZj59jWa+j8crzITp9//33J0nuvvvuJMlDDz2UJLn99ts3nHfGGWdseG/mnplLZkwniyjqUUcdlWQRza7YC+tW0pxj4yd1pXZfs2IVA59npi/zg3mULGwAhgDPYG9Uch1ZmGZ2+V7N1rWeIfcEg4HjrBFq/5QsM//BnJ8E9l3Wv7Z27MgMquYXdmZ9ND6vGK5ut9L4G2E/+NhjjyVZzC/YL9yP576ZW5W/GftYsbvclo8HvhbwOExpatEfryP/9b/+1yTJm9/85qVzNgOq7cJ6GO2K8WdM8dHYhH3wnG4e4wKT1qyx0adZR9kMukpXd24e2Jevw3xlnj7wwANJknvuuSfJgv102223JUle8YpXbLh2pftpvffxvmHKwbB63vOet+GYihFrm7M/NbPLrN2k1jJ2hXDgZ+Rrus6BWeqjrXm/42vsSTC2yYKV5jUPhj2v3ANj4LWyWmNXsTxX2eDUOdU+pdozr5OZVrG7q+/X3Zev0oidY8vO/X6obL/K7hjt1pkNrCfMB68fgOOwB/a3XJu1zvuWcf1kfl155ZVJknPPPXflfT4TuPzyy5MsMjWtS88c9n6dscZ/wSxNln+70gZjXWmFs75YX9VrO+/9DJON+8URVYZEpUfMOLDX9pq2ChyDzWBDFYua/ew4hsliPDjeWXWjD3LWice0Yuyih/3+979/9r4amwd+oarz4GyZVZkTYM4nz/0tAt9ln2V/iu2M+5Xf+q3fSpL85m/+5uT9NA4s7AXJ12a+NhqNRqPRaDQajUaj0Wg0Go3Glpcd+NCHPpQkOfHEE3d9ZhYFcMTNzLdKh5HviUK4quGIOQ3TOX0nv5/TSp3CXOXVin06h4oJtqoPlb7kHOauMaXn5QirWUHWP/L9WOuUiBksR+vvJcnv/M7vJEkuvvjizdzeLI488sgky7pWI6Or0v/jGLN+zFziOKK5jIN1Inkd9WmqyrMVo2JdtpQ/51kRwU6WWVGf+cxnsg6+9KUvJUle9apXbbgfj4+ZOeO93nfffRv6QCQTG0HjDiZSpadomH1LH8ZrO5oKqorolX6yr2n2JCyBkcViRqU1OPcEYHuPqCqUAjO97DforzW/PN5TDLEKFfOosnGuySt9ggl5xBFHJNmoKT2nQ7muzzYqHe8R1lakv/i/Y445JsmCVck8hBlrrW0zAq1bOz5Tr6mVXzAT1mxi+6dKt3eKdes2mA+7i+uuuy5JctpppyWZ1h/1OgnTptIk5tyKKe81z1p3U/qjzvSYYpRNYW6v4z5N6Qs//PDDSZK77rorSXLTTTetvOaf/umfTn6ObweMG9d8/PHHd32HXiEZE6x7+HIzlb1++v7MmLFfHucae1PvOdbNJAHWT2aOOiNg3AtbD9jP/dJLL02SXHTRRZPXXAc33HBDkgWrb2zf+oyMH330fqSqRr1uNk1S7zPmNFErDXowx4peda5RZajMtbdOH+bamMtIq9Y6MJWp5udNG9im12T3pbIT3ptpOJUVBpt9KwK/wn04qwG4Yrr1W8d9OefiezgHP8tYsZ/DX+D7vJ5yPn2s1t9keZ5WFeGtCe957n3plDZ8BbOmyZiwdiv36wwp7wvpI+2wTo1sympdmKqVMWJP7p0by2DcmR9zPsyY8r9VhoRrSlTZo85yq/alZk+P/yfzdm9l3Ta2Bp7IfiI70Gg0Go1Go9FoNBqNRqPRaDQa+xO2vOzA0UcfnWSjthTRAyKD1soxe6qKZhCdgBFmvT0wRtgrTak5vdU5BmB1/FSl6CriaMyxa33cXOXXEZtlZs3pKlZ9mjrW7EHrq5lF5Iiq9RJph8jTWF0U3dE9BSpiP//5z0+yXNV5tD3ryQAzna13R5vcjxkwlY7ieK+OWhNBd5R3s+xq+kak+c4770yS3HvvvbuOufXWW9dqy/iX//Jfbugr0W/GwUwNMNoH/7ceF7qzRMZhM27fvj3JMnsKVIyTqcqbtgWzExy19zXMMDC7ivGg3THq6nO4b2zq6quvTpKcddZZ2V3Qz5H5Ya1D9wfbt1aZGWO2dbMOVukE2teuYvKNfeN7rgl7BDYYDLtKk2rEXF/MROZ1qjLw2McpvVlrz9kW+d5rL3MA9qLZNmbi02eP39Q1rftWPYPKz1R6XlP6o644O/r73QG+wAy/ccytGe05XVXFxd/6+fPcuYY176YYS2avYa9o71Ua9xULzq9cm+yBZME6ffDBB5Mkf/zHf5zdAb7d2sdmnIx9dSYB85S1Bm1jnh+Mb+urVnsz7yPHcauyrcxYpU98z9zhvuyX7fu5t5H5yjqOTdAGz3l3WfUj8A2jZp3HxTbN567Ibl9lppnbn9Ilncv2mtOErfa662rFzvVvPNdV0iu7qj4f253LgqtYs3P6xsD7wCl/6kxDV4N3G3zP+faFZik642u8FrqoH/vYx5IkZ555ZrYKmBv4h8reeWXemu0+7v/9m2UqYy5ZtgPvHT2m1W+nce9itp/3EbTlmhtmNPt3tvchq7TD6bf9Hm3g48yKdB0XwNqPTaJxW+nbJot9tJ8r77lP1pGrrroqSXLOOeeUbTbWx1OsL5/8ZJLFePMcWGPN0J7LpBi/8zHYmX2Y9x+uc1BltE31hbZoYyvrWTeePp5KUnuZ3UMzXxuNRqPRaDQajUaj0Wg0Go3GQY8tz3xF04doU7IcSXWUylG+KuLoSoiu4jwVgZuLLFcRZmNO647rjKycivVV6Rsa6/ZtSjNljoWwWQbk02FfOHpUaWISrTJDxdFjMw5HxgZRNbSHzz///N3ud7LQerWWjHX4kmUGme/bUbhxjoznEWkmss41XelzKtLsOeGIeGUXZmJwDVhRX/7yl5NM64Cui3/9r/91kuUq1lXV7s1EQIHnIWMGcxcdTJhAsKcY84qlOjVfHJU3C3JKz3FEpZ1nJhJMxtFv8n8zvbEtGCa7A6rJu8p1UutNVlVFK51Aa5ZZEJvoyAAAIABJREFUZ26Vb/S1rFlW6dByDezt5JNPTrKwAetDTT03zxMzOiotT2u3YZ+82qeN92B/AUMDm+V7648ef/zxSRb2841vfCPJgkloxv2UHnLFSDZjAJg967WPz6s5PbJu/VzNMP/0pz+dJPm1X/u1rIPrr78+SfKiF71ow+f4hPF5M3+wU7MC7WcrbVDbFO1U1azHY53hgQ1x7TlmpMeN99zvV7/61SSLbIZk/cyR1772tUkWtmi9RNuF7aVimkz13zqJ+HL0Ylmj8enMi0qj08y/ZOHjrL9eafW6WrKzuGzffj8y37gGbTKW3i/tjrbctddemyQ5/fTTk2zcc3hPW2mse02d0r8bscp/+hjbeqUjOZeJBirG8apzfO7cNdfFZrRe5/bju6uRu+pa1iW25rfXbvaEnsO0i+9wZuP4f+YL7PWtBDN4bffO6sAX+PfKuF8yW9R+wnPF+yfvJ6ylXmVPjf30OuD+OwvD53lOcX/+XTY1382Odz0Hf84Y2lb53nrDUz4IO7U9OhvQaxJ9GbX+G08fH9nJCD1SzGvvCW1nXiun/IrP4RVbnsokGzGXhW2M/td/n+C7PaHR3th6eDKt+dpoNBqNRqPRaDQajUaj0Wg0GnscW5b5it4FEfYx0kCkg88cSXQ015osMOTMTpvThUrmI8M+Z66aaoWpaD8RRUfviLxVfat0Rzaju+qIztx9Vzpx1o6q+rZuv5LlyJbZmfTdLDNXY53SJrTm3u6C6s6nnnrqhs9dmXiq+qHHzIwyvrcWEfdHdJtxIYLr8RhZSowJ0V36ZwZaBUfFYbz+r//1v5Ikv/d7v7fy/CT5hV/4hSSLeYqGJswk5nHFAAfcv/X1plDpC5thybhQURsdTHQETzzxxCSLitpTLMBkOurqY83sr7RJ/TyratxmAyQL32JmonWsPvjBDyZJPvCBD2QON998c5Ll+Tj6cs9ds8s878zK9HnMV2ssmg2W1CwRM2ANM5LR/YUp5/Vkyveb9QJ7kFdXV8UXcH+8Mudpj+eIdhmvfJ4sbBb9YtrGpmERwYS0FhXXxJfBPP/a17624Vr0cXzePC9rl1ZrFjZT2brZq2Y3jAzQikFu9vC6YI4zbpxPJWbGOVnYJyxExtRztnoFtgd/P1UZ3BqgbtsVoufsl1fY2Tx3mK/jvLG9vuUtb9nwHkYwtmamq5lYXrvpw6psHfsI60SzvvDcYHLz/I499tgki/XHfnVqT+drWOuVfnMfZtRUPt73ZgbXeA2zwtzW7mQzMAauVD72ib6bjWZUWuZT+qLj91P1EIxqf2kbth6w96nWMa10kVdde119WTCXuTZiTp95s9dy3yvW8vid22CsWEfYp2HzrEnOuLLNe38+asWbbYj9byXtV7PjrNde1W4AU5rp+BPu13sUj6XrBrjug5+rWZvj3GX9sM5qxWivalZwPusS/peMGh8/9tfZU87isJ+1L7GfxQfSnjOIxnP4jH5bpx446wj7/8hHPpIkOfvss5fur7E+5rJCqgxRZ0pjK6MP9TP1b0l8V6WjX13bn0/5ZbPZN5Oh2dj/8FSSH8wetTk087XRaDQajUaj0Wg0Go1Go9FoHPTYsrIDRIusWZMsV+8mclYxmKx15gp1jtxV0d9VmKuiOheBXkdrin5Yy9QR0wpzVVRX9anSpK00pqqIj5kFFcbv1x1Ta68xdlXVYyKYjOcU+29O42VdoANpXdZVTD8ztUHFlrI9cL4jfK4wb33MsR/un9kmtgfbEsejmQO76BWveEWSRcR5ZO5wvzDqDj/88CSLeTtXVdhRS87jvh0dH8+fYxrRtll9vKeq9//8n/8zyYLJiB6on//UNaYi/1P9NosQ+BlVmrdT51Svrsa9DnxdV4cd/+/xNfvUmsieA37mtn1nR4xt+FoVe8KfY1cwXjfjI5gPX/nKV5Ik99xzT5LkD/7gDzYc94u/+Isb7hv7gSnIK58zd2BYYn+wXMdrcz/MSfwh5zD/YG9zLTPqYAbCAIUBCQt8HBePkdk91mw0K86VbIE1gadYQxXj3Tqcc/j4xz+eJDnjjDOSLMbDc2S8HmsOz9HzyHsX7NVrkvcwZq3yfrwXxgrfxHe04crXFdO1YjhhL7Q7PmP2ZtiSNV09nz0e1fpi7Vxsd/SFc1k11sK2XiDMV/TJmTcnnHDChj5M7Z/sj5xBY+Z7xUCssnacTTCyWBl/s+LMvNsd5ivnTOkyel3hHugjtmBtPrOEKxb8Ku3zdZmu1qDH7+IfuQeeLfPKrLwp/dGKlT+HzdZLeDptzGm9Vpl7U/B3FcuQ587nzKu5vlhbnXUqWTw/Z/FwrWcSaCmjBe4sDzNCsTH8jjMwRp/G/0cd2GThD5xJ53WmqiNg/W8zS5OFj7WOt5ntzrjj/rg2fcOfYkfsXazfPwLb4FjWR17NgLVWuvWFgTO8+E04wvsE3qMZXmUp+fdoa3g+PThjqWJ/g6pOhPdc42f+HYFfwXext8VenIXsDD2vEVPrvv9e4X1Z48DClpUdaDQajUaj0Wg0Go1Go9FoNBqN/RlPJlmP7rE+9sgfX2FK8Nf/MeoJrPNnfY5KL62qQO7jpiLYczpoz3vHjgj5wx9/aNXtzcKad8kioubIW3XuuhVP/X6VRqGv6fdmz1TXdpTQbOSpqKefR8VOrNiaRFytXeTo6Rh5XqX/uw6uuOKKJMkrX/nKJMv6iWaprKq8WEWtpxic43muQms24FQUrtJRrSJ5FaPZc9SsMO4fJlSyYNjBNjHrrWKIVgwt61lxzSnt0yqqWrGMeYURxFjffffdSZK/+qu/SrKopP1zP/dzG+5xionJmJlRYH1LR+JPPHHH93feuXGcHP0HUwxUR2atF7yKuQtuuOGGJAt2glkH43UrplL17MyuqV7NFJtid9uurIdmzWXrMxIN95hUfmlkI/7v//2/kyxYlBXwUWZEoj0F6wJ2ODp79AmNxpEBAwPS2ns8cxgp1uiD4curny9z+MUvfnGSRdV7XsexsG6mmar2N2YreF4yPmed9Ss7r7TDl1955Rd2XbtiWpktM4fjjz8+yXIVY9/bCOt5Vdp83Bf+gn0Pz8gsQp6BtQDHecVzNMPQGRJVRgXw5zwb2jFrKllkfFjT1SwPj9McE5RXM3/HOWY29RRjcoSZaLxnjv31X/91kgXzC2Yb6+rYZ9uYK187Cwd4nptB6zXMbN3xM+6ftsxuoy+XX355kuTCCy+cGJUdwKe/8IUv3ND2FNPYexmztM12XpWRMfa70socUe3TzNb++te/nmThh7/whR1+4rWvfW2S5eybir07dc25tWmu75upD1HpGVdjOqdDWzHNN1OLwXtBs4nZK9kHVNkMHDeyEb0v8L5yHZveW+D+zDp1Jibf+7cPv0PwDeNvX+YAPgd7dMaHma9mfDK2/u1jPzXuy81cxQ8668QZJK5G7zXb9SHs40dUet1V9ip9ciX56hq21fEcxtK/I3l1TQ7rr3N/45g2Ng/vEeYyd4D1jG2PSZ2x60ws9mfsjWmD/bezOPx3DY4ff+P57xTMo4svvnj1gDT2SzTztdFoNBqNRqPRaDQajUaj0Wg09gK2nObrddddl2RRSZnIwMgQgJnjKK4jTmawbrYS6BTD0pE1R9DuvnJH1fOndkbDHJGuKvP5mlPsPldkrDSwKu0tv99MFdaKTeiopaO2jkYZRBNhxhA1HrWGzNirdGSryLvvodJ4rCLwIz784Q8nSd73vveVx4w48sgjN9yPGQnWMR3h+/PzJjLm10pLzdE4V4weI9ZmhzqCPqcBDPica1u/lkghDL1kmcluG7I9+Fqg0vgz42ZKV9kMAttIxb7m/rZv355kMaawpmgHvUjsfgr2ARUrdfHcTtn5+V9P9tXtjvddVdo0a6ka+xGVzpbfj9fxnLTWq9nffM+9+179vKZYU2a+8h1sCq7NeuM+2U9UrH/aJUqezDNef+mXfinJsnaUx5/7v//++zf0FXYq7PEpBothBizjgs6V/QUMUDOZmL+nnHLKhntIkq997WsbrumKyW9/+68mSW688XMbPvc6WrH+P/rR30+SvPe9r0mykYU656No85prrkmSvOc978kUYBlzv7bBqUrRZplyrKve0zd/zrVcSZr11nq8ow6a2es8H+ttV+ulfb3XyeOOOy7JgjE6aolag9H6nWbR+tqgYrZXa914rLMZrP/stp2twRpFn++6664N72F6w0Yb++f3PP9Kq9Z24PP8rFatYfaF1sZzpfhVsNbrFHOs0kTkvXV6vaZUzM+K2TSFal/CuN53331JlhmvAP/pe8CPTukar6vxOseIrX5bbAZeY71WVX2t1q6qYvh4rer+vN+iL4wl9mAtYs9PjrPO6VQfeL87esZ7CvgB77erbA7vsbF3Z+Yli+fkrDbGyJkxtGWfjx1zDXS7aRe/PcXS5BxsARYg/eccjsPHVXtnrwnL+9rlvZczPfzbp6o+zzWZ5+x5zEQcs5lcI4P+m/EKqswR72EamwNayuxtmWfOYPTvYftR+8Ypv+19p32b5wnsdF4rTeFKsz1Z3vOdf/75U8PQOEDQzNdGo9FoNBqNRqPRaDQajUaj0dgLeCrJekJn6+Np/fEVpiBRjSlNq6oSsNklsNCsaQaqCPQqdpsZV9Z9cWV5R+jM6qs0mcD4ve/LemEVK3VOB8uY02sd++Vjzbbg1ceZ+WMNtJERaCaa2cNz/a7YxmZ+MK7jmJsVR8R0XbhKbsXidKR2vKaZWR4rVxd1X5kX1rJzhH20E7NUphhVybIuqaOMrkILo512GPMpW6yYanMM9oqBUc2D8XOONdOXMfZYV33lvqgEDxMB5h/tv/zlL9/VRsUSswasWZ0v/P+9YMcJOx/FKacQtd+hO/397x+2oW9TDGL66yqxFQvn6quvTpKcddZZuz77nd/5nSQLJlzFzprSNa5YAmYKYvtm/1d60H7mqyraw5bBR8Po+IM/+IMkyate9aoNfTPbf05LHO3IJPkn/+SfJEnuuOOOJAutwSkd4rFPzMtKHw+f8I1vfCPJ4nmOzHL8gO2oymbge+4T9piZgjBezNiGITu29dKXModP2PkKI35jIo6ZjVVWh23s+uu/uPP7Zaa2WQ22wUr79ROf+ESS5Od//ucnz6s0/ZLF8+M7xhJWMe95/ry3Thw+gucNq6iaJ8mCjeH+mVVeMXaqasI8k23btm1of0pD2/uFar77GtUexvN96jgzjaz7V62bvgbPEQYsz4Y5xpw87bTTdp3rddF7jmpd9f6S81xVeR32p9lt3mvZHlYBtje+w2M5tldl6Pg5gEpbuNJDXgXbAeeyF3r00UeTLO+dgX27x25VBoX3l3MM1ypjazOar77vKrvLWYHVedXeyWyxdfo31xZ9Yh7iy/xsprJt5n6jjAz4fQ1nuTnzx3PHrDhgndZkeU4wduzf+N1sv2v2pu2bsa/YuGPbwPORY3nleNpmrePVfbXG77iGYRM8d/wQfpFXjvPYWXfftsbrlC90G34Gzmbw7yt8D+vwutryjY3Axv13Hq8n1h7mWds/T61hc9rBziLFFrBHfufxSh/oO9fy30eSZS3hxoGNLSc70Gg0Go1Go9FoNBqNRqPRaDQaBwK2nOwAEQSiG1PM17nolSNQVaR9LjLtyrPjNYnewWYyU8XVUWFyUj2VSF3F5pxiiPCdq3Ab1sGbi1CbwbNKf9RsvCqabS2/iqHkqDeRoDH6DePEFeWtQ1VpTVkPzjqkwIyvZBEZNvt2XVjXynp52PXUs6y0aRkzazSaLcj9WCOZa5oZM0YAzTao7Bu7thYs4Jowv+jbvffem2Tx3Mf5XdnjKgblqmuv+zrVxhzjznPNTAwYazD6Yb5+5StfSbLQL0qSF7zgBZPXsn3Tp5NOOnbnEd/c+eqIOpXQv5ok+fu/f+FkuzuO2TEXYGoTqbWvxQ6mmCWVPmmlO7cK9oNztm594IrNOLIpOAf/wj3Djvrc5z63oU///b//9yTJL//yLydZzBv0Vl39HcB4uPPOO5eu/ZrXvGbDfTJXXW3Y+lYeH1dOpp177rknyUa/5WdsVpeZsGbA4n8efvjhDddkjleVXpPkpS/duBbDzk52+INbbvmrndfe6E+sC1mxqr3uTOm1V9WWV1VZThbrj32CfcEU095sROyZscfmAG15ffAYm309tWexTqf9vqvsmmUJqgroZguO51VsP2Bfbt/g8+Y086d8i/tZadya1ei2GHP8xde//vUNr6Mvh2lurUGzjumLGa/OoKp0I1etYVzTtuaMmVX++IYbbkiSnH766Rv6a7b0+Bk26rnodaDSGLbPNiPIPn5qPDwnaQufZ+35V7/61Rv65LXWc2fVnnouw26O+boZVCzZuQrglXZ/9Rtoak5UurAV87eyM/tEj7Gf4dgfbIp10Zl2+xKXX355kuRnf/ZnkyyPmVlz1py3nvCULiTrOvsxr4PYNWsVfajWEbPK6QPXGX8H0C9+o1e+2X7ATEVgf1RVhB/76efr5w/cF463Zjrvfb+j5muVWWemL/fL867WZI678sorkyTnnntuGvPw7/6KUe/frtYctp8df8s4W8Z61ZVvd3YHx7OvgwnrjDXmQLLItLvooouWb75xwOGpJHUe5u5hPoep0Wg0Go1Go9FoNBqNRqPRaDT2Q9x222150YtelFNOOSX/+T//55XHwnyd+7cZ7BbzlUp2aOGZdbPhAjujB2YjugpjFWmd0zlyhdSxSjVM1wcffHDD+9tuu23yWm94wxuSLFdRhT3hezArYCoaboZVFa121HtOK7WqMDx+5yiTo97Wv3FbZuH4ez6n+ub43VQlyqk+GJXukaOpZp2M/zeraQ7YM/qAroxJ9NOV7Mcxd8R/VT/HthwFxo6JrDGObmd8/mYagor9BAPWjEPfF+PAXCVSP2VroGJbzz0L28Ucy2rsh+11qpr2eB/V/ZpdCeMXnzKyIdHGdJS10iq+775Hd/bh7zecZ5bxIYfs0Ouznut4/x4rs6bMipyCNSSteTbFjq50ebE7M+LNdKjszaxxM7aTxTNhvB56aAcL8/d+7/fKexzbok8PPPDAhr7i0/n+m9/85ob2k8U4237MpljFcBthe2VeWeswWbBpzVi1BmbF5LSeIlkg3IsZICO+/e0dNo7df+1r/++GNjGvyi+aheK5vUq/dV2ma6UtCeuvYlt6XMZrW2vPzC3ug+fFGsez8rpq5iHPl2cxVrCH6Uzb1vj2Ws6cJ0vHOmVmkGD3U0ytOc3WyqfbL1TsuqqdsT/Vsa6e7udncB7PhnnOmLMnTBaZDvbZrlZu3TrmoNcP+70pjXhQsWS9bzRDawq2P+szjmPleeN7w3a9/niO23djj+xf6O/IIqrGxXsJ7p358S/+xb/YcL4zm8z05fmsw1Jdt8ZE5ePM8JpCxcqrfLVRMYaNqf1vta8yqjntOeCMCcba+qQjzFBzn/YlvGaN2QfJsj1ga2ZjrrPPtS6udSzxbdV+zfsi65gyx8Znit9z5qV9l9n9VeYp+yFnfdhHjv3i1TbiTFLDzHUzff17ZMqWfb9mRVob3+PBbyTP78Z68Brq+TK1/xiP9zo3tWcwS7vy4XN/W7E/MgPW2dpJcsEFF9Q339jyeOKJJ/Lv/t2/y3/7b/8t27dvz8tf/vL86q/+6q5MiKXjs57m67PnD9mF9iiNRqPRaDQajUaj0Wg0Go1G44DDHXfckVNOOSUnnXRSfuRHfiRve9vbVhJ5tgzz1awSV2Qdo+qOnAIiHq4kO8eEdbs+bry2NV+Jxle49dZbkyS/8Au/kGQ5yglDgoib9dbG6FjFIqmYA1UlcN/vXHvj/z02Zs1Yy7Tqu6OjXJMI5Bg1ti5spdlWodLD8rWmolFcE9bQupUqzWj2WDtaN8XUMgOt0t/yWPqZoP9kFqE1qMb79pj42taWdDV2roHeJWNN9NFzeErbeLP6fnN6kHMsufE+K5YGY+y5Zualnzfj4qqYjE+yGHNsx/C4mFFgPSGzI6aqewIzTnmujtTS36lq0Z6PlZ+eYjnb/rEXV2t2RNrrA2PoKtUAf5ssfBS6qFX2gmGNMjNdYHRYw26KyfFnf/ZnG9r+5//8nydZzFWzmavshOrVDNtksXbB/DXzyH7H/pPjrWdsxuuUf6b/rHceOzOZzGQ2fA2zIqqq5uOxZqBdcsklk8fbjiuNdK49zm2zMcwKYs4zhvjsqsJvxerHv46+wbqVHONMCF55/rRJX3gm3Bc2yit9ndIfrRghlY+fY/17vzHFvuN+q/0f57hycWUXZgqjw0yWzvi8acP666Bai+aOsw0yR0ef7kwfnh99Mdtr7LdhxivPmvk6zkuz75wtYjZ/xdp0dpUrr1vDdvy/sy38mwB4DfSzZr0+/PAdWSPMS/8umboPYFuv9Fc3+zp1Dfdljl07Nw89n6ayBOwn5to0Kn1FszL5fGSqe+7apqb2OHsbvo9qLfOzqTS4V7GrnfXo/bpZ5t4P+LmapTuVTWimMm2zD/BzA9yHfxuy5pExgHY+GRfjnHUmLGPK/Xov7H0h164Yr84YmtIBdeYD9o9PdKV7a7zSx2rMG9O47LLLkiTHHHNMkuW/GYx1HJKFXfEMPd+sxTue79/EXsuqDDvgfZ59NrbP3mtVJmFj/8I3v/nNHHfccbveb9++PX/+539eHv9Ulqu0PF3s+1Wv0Wg0Go1Go9FoNBqNRqPRaDT2MtYJjo54MuvJDmwG/cfXRqPRaDQajUaj0Wg0Go1Go3HAYfv27bn77rt3vb/nnnt2sbWn8GQOzXdy+B7tw9OSHahS+0ZquGnmpANAFYd2virddepzp29PFb0izWEqbXgVXJzEacsUxeA4xLlHGvucTICp8Ly3cH9VjGAdYf/qGKe6VyLrTiN0KiTtj7IFljCo0nfWLYYFLDLv9P7xWk6hu/TSS5MkF1100WTbpJpwvFOQXPQCmx5TUVzgpBIWd3qe7Z7PSamp0t/Ga5OOYwF+UiydVsk8cBqoCz44LWrq2a1bVGWuOEtV8GmVrIjTmiyzUBUxcfqz5wnHWdB/lc1WqbdO1wOW7rDd+Pip9GDD6V62nSnYrtyPEZYZwD5cgMp9dxqki7PYn5AaP/pTFkp8+Ste8Yoky8Uqbr/99g3X/pM/+ZMkyWte85oky0VyXMiKtW2qmN5rX/vaJMtp8k6HYxxo08XNnBrHuLpITbJ47qT3ed0jrY4x5/64FmsVY0pac1VIZ/RH/N8pzy6q6OdaFXfx2uZxHNc425/fzxXRqQrgOLXXUivJwga8z2GsGHM+573T1n1tp5ey95lKi+Yzy9B47rkwnn0Xtujz+X7EXBGeOSkZt1P536kCVE4rrNJmvX5OFaCc6ouLZk7tG9ZFVcDD9m55mCmJjzlZGq/t68g3WWbABeOShS1i407drPbj1frt82mXvfE4v1xIB9hPukCPiwXRB+YI89CyaON1qqKRcxJTVWHRCt5DT5079xvHftUyPnPtjDa+zl5gqo9Vn13wsZIsmeqP50VVNHFvAr/oeWAbdGExYMkkHz+2OSXXlSzvi+wDuCbtIC/l31QuZpQs7wHpF3MFf0jfLAXlAmocx3kUr6ZP43rC2Fbzmf2NizJ5D8J9WT6Ee+B1HHPbGG25ADKv9o3+Dej1iLT697///Wkso/rda9/lvS/j7cKalqwY/57k3+22u+p3W/UbrZK9AaM/bTvYv/Hyl788X/nKV/L1r389xx57bG666abceOONK844JMl0gcDdRTNfG41Go9FoNBqNRqPRaDQajcYBh0MPPTS/+7u/m1/6pV/KE088kTPPPDOnnXbaijN+KMmP79k+7M5JFjp2BGKM4FVRbqJ5jsCBqkAGMMvGAttjfyhWAhPwJS95SZIFi4pInPvKtc2gNeuCa8NOmrqfuaINc+yLSggeTBXGmfpubMuC/S7Y4OPM0ptiyVWRLvfFTAP3zezcitU3tu8CaC5aUcGMFTP4HO2nvbHglse8Yu74WlVhERe3sa2NhZ6IOtMvF9MhOg37yUCEn6IkU+LmY3tTzJ2qSMBc1NGMV9uNWRJTMOsYuNDBHCrBdbMGpvpZtVEVNHLBOLNHfd6qgnou+mXB+amCFhUb1YyHcUz5jPF2cQ37MrMQeD/HeKW/9957765rMw4UVeGYo446akNbv/Irv5Ik+fznP7/hfv/oj/5oaQxGUGSR9WOMftM/njnjQNGJO+64I0nyT//pP93Qpgu3MU/niiqN85Q1hTGr1j37KvrP+cxxswJWFRGC3fLlL385yWL9w0/4uQIXDgFm2XidHeeIme/2A3PFD9y2Wf2sZXw+Mi4qNiBwYQezjs2GckFOZxqMrEDawmboF3Oca9in27czPlybezKjh8/H/nnM5tYsn+8CSnPPcqrflU/3vmoV026EWS3j867YpFUBI/s3ru1iaGBXYcSd+9Cj/ma5Lq7Xe+aaixH+zcS5wGNRFdNKlgvLzGWFzO0hgfdQtD/uyz1+VdE0/zag/6wLLpBp2+Gam8n88BydKwS3mYJbc1lfvv+5PT+ossLG61T7lSpTCVT7Wmyc51xlg4z98l6PtvFl+xJVwVsXC6XPLgbp46dYc/5d7LlVrb2ei9gxz5nxsk+YGkfG3gWkXCjLtubnyPP1no9159FHH10aGxdbrrI0qt++LnZFe+w/sL3R1qrfIWY3mk1fFbz2HmezWRIHG6pMgSqj0Vm1zlDx78LxN6kL1/lvD57jVTFnUK0Bbtf/b+yfeMMb3pA3vOENax79rCTL2WJPB818bTQajUaj0Wg0Go1Go9FoNBqNtZmvfzt/yE7s1h9fHbUw02GM/Ftjz9oxFdNt3Yi7mVtTMMsWtpTPNSsGpuyDDz64oT1HomEpjHqnY6R/PMdj5vs202NOo2oqGu42Kv08R3oqtp0j6r72GOWyTmoVgZxjrDha6vNsc+M8KqgJAAAgAElEQVQx1s+d0rcbwX35uZpl5dex747UOdo2xyjwM6pYcVP3ZPt2xI/vrRf40EMPbbhPouFElvmca69iS1UMJdtKFYU0O9O2ZRscz/Xzsiac21rFGh/BGB933HFJkhNPPHHXd9YFmpunZjZZw2iOLTaiskPmHONAG1O+0ext64dNzS9rNgKuP/WMpu4dtgSf44+5JnY5jjGsWM5hXpiNSlswWf/wD/9w6d6nwHGvfOUrk2xkOcMarbQHX/ayl23om5kpvIe96MwJ5hf6o+P4mplh7TLaxp44zowVrmHNN8D5Dz/88K7P7rrrriTLz6PKkLDPN0vX66zvcbR1+wczT+Z0Ap2lAXhP+2b9J8vPeYo5PsJadryaEct9O3No9D/MDbOtzYTlFR9lBizPnedtP8ueZlx3YJVX+4dKR7diU1eM0iqzYmzbew2zUNy3OXDfZEGhhTx+N6fBWWVG8IoNVTURDt85v8c++369B8UnMH/Zk07BrF778HF/6v2zUa2dlZ54tZ9bldllNprP4XPuh/3Jsccem2RRk8H6gfgys77HflSZdsZc5s5c5tpUxkrFMK9YY1Wb1V6Cvo3rZ5VhZlQ1Jsx4xO/Ybq0BnCyv0fhH2/a+RPXcPE726WaSmiE7zjG+s51XrFszwn0e+sm0y1qNrxjrQPga9JvfqrTN+uc1iVfrR3v9tL5ysrw3sY3gJ6vfwM44pT3/psZ+xnWkGjvbrbXQ6WulR8s9fOADH0ijBhqon/zkJ5Ms/+aqavV4f1KtXSMD3f7PbG3PyWr+2efZ1qd05dfNpmwcKDgkyTps5738x9dGo9FoNBqNRqPRaDQajUaj0TiwsC7zdf1A4m798bXSC5xiIZgFYT2OSv+rigI74uA+TFX4rPpbfW99QSLuaOAZRE6IxI33bd0brkHUhahMxeBdVx9qHPtKM2ouWm+mqyOPfO6KmCOzwFpfZhhU91FVizd7YRXT2RFka01VsO6m2SCVxtvYbsV4NWPEkUC3Zaaso3REZscIINFbaxVa54/oL5FBzoNNQ5+IhsPU43i01kaNUeaI78NM7krzFvh5WhdsqjJuxcTiGMbIdgEqFjn3Aovy+OOPT7KRLVXZVMUUYg5ZU9UaeVVGwHjfROl5pe1q/p599tlL/fTctkakGXYj7JurOWk2Lf3l+G3btiVZjCV2iL8dGYdT+l7JYnxgNDC+VcXSOcCMg101tu1nyOe2aY+/mSmuwGt2yagn5YrH9MFzeE6jjGvBlrFdTlWT5Vz8gRl1FQusYtNZx9OMtylmgf0mr//+3//7yWsAWHEVkxsfNuXzPXZmX3pOej9hNocZzjw7mEwjW8rHVlppwNWZsR3sAqZTpTP7ta99bVdbfGZdZd9vpSlq2MdVa+LYL68jZtWvqz3q45irMIFHX07/vr3Tvn/yb6fZC2b/mWlqTefqnkaYyW7NZq9lZo2PsA14TzEy4yrWuu/VTFwzACt94Eovf7ynSlNvlQ51shhnGHSMDWxu7o05NKXVV2UaOWvEDDgzfivW6irNVx9TZbtVe0Jn+FiP1L+xxv/PMcXnNOvNmPSab58+wqxR+v1MVAyvnqc/r7RPq2yz0Q9Zn9vaxaxBnnvVfpTzvR/hGYxjzxjb39Mnfqvab9IGfrLyx9wTtjzOscrPo5HPPs9rl9d8xp5xwvd4fZ7yLfZr1pEG3psyTh6/ubohjY3wXm9uT2W/4fVl6u8JXmuc+ec5zJ6Itmx/wP51Sm/9vPPOmxmBxoGFH0prvjYajUaj0Wg0Go1Go9FoNBqNxh7HIUnqwOLuYLf++OoovHVdx0iCNT7M+nEU3DqFjoBUeqSOTI5tOKrtz6uoNRESooDHHHNMkkVlRzM7xujNyIJNliu3mmnmCGWlaVdFaMcxr7Rcq0i7q1DTd+vHmYVE34mCJwtdHq5tthh9sF5apZHK59YJMltshLWv5qKW1g6qKhlWjITxfittV9o207CqsmrmKywp3o+VTf2cqoie7drMLGzPDB8iz0Ss0YIcrwmLEcwxRCpGt9lBlbbc+H8/L+tf2qaq6sqA9qyHNaWZV7VRsUOBdYhgM5itbP2rZMHAh903Rv7Hc9DqnMJv/uZvJkk+9rGPbbgf++FVmNO7w66YX9Zl5ZoPPPBAkgXjDlsfbdxafVU/GRue3Rvf+MYkyWc/+9mV9/Kv/tW/SrJR19dtAuYFx9p3cd88H9imZovYx03dE2uN9ZmJwjvzwWud/Y+/dx9GVnuljWUmeZUZYP9ilkylrT2eY1SsWgObYsxZP6xXazbNeN/ea5iFCqxjX+mUO8sFfzulC1kxlOzLvE4448bPxn0dq1QzZmYWep/krIS5TBvfm21zhNlhXpvMwJsD7bEvcXbICCyuWqu8V/n+0UfvaHvnumh2MbAdjLZmbVfbvVnD9vUjnFXhuT9lZ147zVazJqIzD4D3WJ5DU/fMtcx8ndOCNDsYXw+bGX/NcaNOrv1cxVL3XpA+Wq94bp+zShuwYvaawew9ofeSnpfOXhm/M6PZ9jbHQnYmhufGlNa21xpnWD0TqLKgrDVtFpx9of3yyI7j/54bZrXjb/l8ikU7vudZkiE0pYcJ/LvY+uS2B54rrzwjZ/fwSjtT/tjrgbN2vIfx3sT7IXyRs1imMgqqeedrVVlH1tqvfq80puG/tXjcvSfkffW7akpL2vq9vqb/PuW/W/nvBMB9xO78N53GwYR1ZQfWRzNfG41Go9FoNBqNRqPRaDQajUZjq8gOEAU3K3WVthVwBWjgSLR181wBtYoOjjADp6rAXulVuto7ETdH2M04SBZMCzTXuG+i0URrzDLk2oyP2ZZV9fdxzIkOzbEIHV1irIlIugKktc1gxoz6aWaswDrglWs5sloxYB1RNRtrjLBbo4X3PIMKF154YZLkf/yP/7Ghb77GKvv22Jr95Ofniti2Vd47ms3xYwSQa9Im9+85Ynt3FNusbCKDfA8DHEZfspgDZn1Z67higJpZARzFdNR/vB+za8yydgTd7AVgxqs1/EZ4LKtIu5lpHnNH2ivWz+hbrKdkn8C8RWNrFazDVkWip/pU6TlZR4u2jjzyyA3X/vrXv55kMc68mtk0fgbsL7gWfcQ30adXv/rVSZLbb799Qzu//Mu/nGTBYuU6sFWThf3A2LVtV7qT1nazVi/zyGvcaG/MZdjmzDPasKaZ5w1z4eyPnZUk+dBvXJEkOf/8/zNJctNNf76hr3P62Emtl2e2tvcHlc77lL57lUmwSvNyBDqCX/jCF5Iss9e9vkzZuTXlzMKwH/XaZP+C3biC9ujjzdZwJkzluys2kPdLAJsc10aYHWhneo7Zl1d9AtWzM1MvWbYJr+Fmj1UMWFd65z4Z+1VsKVa1H9557LN3Ml6AtRl/gr3dTl/D+dt27he9roLxXvABvHo/x/3AvlmljwmLmf2YbX2Ex6/KJLON8r33FhULekqr2NlL1ptet84BfWDMYAJy/+w5R5/hDAJnnlVrnDMuGLepvf/YzsiW8jWxTc/Ras84V8PC15567ow1857+cSx7H36/VFrT1qp3ZfGRIc0Y2X+s0ofd23A2n8ey0vr0Phd47z2eW9Up4Rz3gX2QfVX1DFyjYWyTfpoBW2md4md4/uyjKqY4fRzv23vHX/mVFydJPvOZ/yfJYq/p9R87oQ8eF8bevnxVFoQzDKusV8/BXdkNqgfSWA+MG8/U2U6VP62yZ7z2jp/xrLw2+TcVn/v3k//WZHY4PvKCCy7YxAg0Diw087XRaDQajUaj0Wg0Go1Go9FoNPYCfijJtBzl7mK3/vh6zjnnJEm++MUvJlkdaa1YWWZTVsebFWSdR+shjRGSqvK4r+GoliOTRAlhwDrCDvtvjLATWXb1cu6fSI+ZGRxvhiSwdh1RmvG++b8jgpUOlSteOwrMtegrUVG0GYnUjjB7lmimo/qMaVVl1ZExsxjHezRrhojV+973vqX+TYFnhvakNdpWVVQ2C6iK7FWMCmAtLrNCrGczflfpeFUsMrMyrW/mSuG0g60mC3YlLEZsjzliJt4cS6Ni8E3B87iqHG1mrHUPXbXajINVOoNzjFczuYHtuaoc73tIFmNszSOzls4///zJvo1gXsKeWMV8rWzY1WnNXIAxyr2iLQk8v6xdN/aHY63ZyDPnPjiePp9wwglJkte+9rVJFv4JNi7XflystSQ54ogjkizGu4rWO2rvZ8u8wX8y32AarhpzV1227nalm8b6cO0OUn8+mZ1VWnfK2L7tbTts/TOf+YsN57sfSa1l6XnhOWvGk20bTFWyNWNlswyU++67L8li3XSfVul3O7ukYm1YexF4XphdNMWqqa5Zsaeq7B18GPOEV7NUxzlGv/Dp7G/w5ZV2vu3dbLm5/dbYttkolba7mXb25dbU9hyd8uUnaa8F7tw5X5+/c3yWGM079xnmRVSa+6NuK36Iz8yyZozxEavAMccff/yO/oghNs7LOZ07j7sZZGb+VYzrqb2HWWaVLmBVIdvH+Xlgt1xz1Hzl/mDA4tM5lj2g1xlnfVVsO9vhuH9nvtv/V9r8lZ63/Qn3ZHbYOOb+DQPTmjnPfbHH5/lzvOeu55+f//i7js/MLHsmK8ifffbZSZJbb701yXI2i58B98lzdd2EKT9VaX8705BzvX+lT87AqtblqT1ipVtu1i3Xtg6r9Xm9B/Lv8PG+aPu22/6/nW3+6IZjKx9EH5i3fhZmRY7XrirXr7teOnuHZ9F6n5sDv7mvu+66JMvZQNXvHu/LrIM8Pt9Ky9Xn+hn7twQ2wvG0u47OeuNgQTNfG41Go9FoNBqNRqPRaDQajUZjL2CLaL4CoqcwI1YxGipWlCPJjsCbxeeInKOLq3SEKq1TR9IcubMGCID5CVNy1E+rWC6O+hGB5z4cYbTmF++twTPCVZQdlTZzzZEjRwkddSKqzesYwXT01iwoMwH9vCumY6VxNzKWaAu2LayndQHjZ/v27Ruu4WjdVJV3s/eqis/AzC6zV6215vEcmVCVXlGlj2htTq7l862Vs0ofkbYccZ/TWQauAG522RRDutJEq2zOesuOiK7SgRyvMx5bPd+KZez31TV8T+M8tz60mXfrVoRPkksuuSRJcsMNNySZZklV9zDnH2GVWpN427ZtSRa+DiYsz9jPJVncs3XzXJWaz/HFZuszn+6+++4ky/aGn4XtOrZdrR+VtjYajOi18vkLX/jCJMnRO6ulMy6jljKoWDL0yewhazfeu1On6kU7v/+//u+d//mLna+HHZskedObnrvzg1Hnckd/Pv/5L2+4RsX6MlPr/9/eu0dJVZ3p/w/gJYR2IhflpgJBZfCC/EaMlxHFxBHUqDPBiCh3uSjIRaNoMmtJxhnj0miioGDCVSAYECcYHFGiAuoSg3wTUEBnFEWFRlRAMYmOytTvj+aps+ups7u66aqmG57PWr1OV9W57HPOu/fZVfvZz0sKZb4l4XVUlU+sbhdi4MCBABKFU8zrMSxzbMYM41HLrz56OpNEvdRjmbKB/DjXtphoH0XVpYxr9f9WZU/YpqnynPVTvXpVyRxrN3kdWKeo5OJ2YbwX8vnUvgj3FaqegHwFmiph02I3psYhHQM/w6qUtVBm7LAMLD/LyWvPa8d2jHFcGdddV6FqX758OYCkX16VTN2qeNW40tjQ6679b73e4TkX8jDVul5oPVVpsqw8f/bPgURNp56XLDfrH6+7zmrjenw+6LNBrxefO+E1UZ9MnbXHfepzhWXlefK8tR1J85zWGWiqmlW4HuuoKrKJ3u80T1RVfPPY/O6zL+F91u+hsRkC2p5ouxuqj2MzYvRZrsr4WF3UNq8q/uy8D8zXwPuj3y94v7nU+sHrwHjW9ipsD9T/NtaWxNAZaFSdcn8xn/twW71POmuFbYe2YxqrbC+GDh1aaZlNOrxnjJu0vj0QnzGqvq5hf1f7W0R/G9B2URWwabNJgfzvYg899FD2s6rOpjX7Cw0AFNej3MpXY4wxxhhjjDHGGGOMqWu2A1QWUsmU5tWno1OaQV0VHTElpKot9HMdDQfyfdJi6ruYXxF94lThpb57mhkyvAYctVP1jypa+D6zbHMEUjOiqtJLVYzhtnqNY/5xMZ9RvtaRSI4qqt9R+L9mulbVTCEPzJjSiZ+nKaBYbsZlVdQiIYMGDQKQeBmrqlpVnOFIGf/nNqrqSlNYAYU932Ij7+H+VTFB1FNQRxsZM5oJlWVSj9S0cyukGtXYi/m4sQy8d/yc58sR6NB7iUoAVTdqO8R98BhUJBKuz/W4H6oh1N8rJHZfY8rW2Paq4tF6lKa61ayxXJdqnepAhYsq7sMY17LqyDPLQ8WRqiqohOV15v3jPaUKRTPNAomPn5aP14n7Yll4jXR9xgqPQRURy6DKiXBfRFXuel0Yq5s2bQKQtOmMEVVwqDdV2D7HvNjU30r9R3nt7qT4f/We5e17lmv3LI/dszx3z5Saw4OpNRsq7tcll1SovJ588uWc6xBTbavXaSGfVr1+4fnoc/+WW26pdF8xLrroIgCJAlaVTaFvuX6mz4FYRniqhPS8tf3kfU/L4MttuG8eU73xVU3FdljbEZZNFU3cPu05qj70Wn4tq7b53CeVbeXl5Tn7437CmSm8ZjxPzipiW6JtBq8P27pYVnpeY+2jhfVbn1Gkum24vlbljM7WAvLVxernWVkm7xibN28GkFzDUH2pFPJk13sfUwdrP4CkKaxj+4555Ma8XhnbfG7w2vFZxvWo+gMSxSq30XqhmdXVA5VtOz3uqarlfVTldXjeWre1j6R9Zu0Ds8w6w4R1Qj1+07yFtW+vbV3s2R7zXlZVY9rsBz1vznQZMGAA9jXsC/I+E43nWFug7XPYrvA+ai6KmJ+3zjzUZx+fL3q/Y97BYXl5HtxGv0cwPng92C9iWXls7ZezfQ3zQKgaWlXWsdwjWu9Zp/iadZWvVW0dHoNLzWMRm5nI14xztiFsS83eQYXonDlzAOTPolTldMzrP83zX5+nMT9m/X6ks0j12aRlYmwzHs2BSB2zHTDGGGOMMcYYY4wxxpj9gzqmfGXGyCeeeAJA/igTkD9iGPORjGUu16zV6oEZ80gM3yOxLKI6+hvLbMrRMFUnqIIQSBQWHHWnsirmqaXeWBxpjI12qsIlVKipZ6tmBUzL8Jx2HjqyyNFhvs/jcEQy7fxUAaDKZqIjXKrCVWWCeoQCyajtmDFjUBPefPNNAPkjXzEFXPi/KghU8a0qP1WCa6ZGVUfpfQ/fi3l/qbeU1j09L1V4c8lYTEPVG6rwLuRrxX1rHdV6wxF5IMnuzLrGLM9US6lfLJfcN+/vd392XsUON+3ZMa0I94ToO2sqPgjVcepFRFSpFFPvqMKI14N1iUqEtIzAekxV9A4ZMiRvm0Jcv8cblN6vVEuF6gRVw/AztgscGeY5UJVG1aoqPHmteP8YA9xfeGzGAdVcqjhW72RVhajHF++fqjHow5qWrTmm7mFZ+HygKoqvV65ciZCWLVvmlIll5jUP20aWl/H/8su56tPu3bsDyJ9BkW2bZu9ZkUrXDXuWX+2Jq7Z71PLt97wfDu6zWX+z4ppfdFFF/Xrqqc05561tHMsaU4MTLWv4uT67i5VxlgrYxx57DEC+sjgsD+s720tVjzEm+VrVHDojQb3YtR6E5VEVtPaTtM/CMqoKSp/dVGGzrUhTG6d5uaeVKdamxZTs2paHHvms+/q8U3U41+O23FdM2aTPMm1jgPy+VWzGiz7DSKyPE/PUD++3zmLQPlX4vKsq/fr1A5D0y48++mgAuddW62ZM/RN7ThXyWde2sTJi/RZd6ud8bmicqko17COyP85teU14nXmvGCfqE0/lLOsPVd36LNNnBZCvbOU1Y7ui3z/U21J9nrmexq/OCgmPrfdP/Zy5jX6/UiU934+pzkK4LfsDV155Zd46+4qRI0cCAObPnw8gvz1V/1ztf6uHZVivYnkN9LuworOOwhlA4Wu2EWnqU/XejSl2udQZQTwvnbmpszt47Mr6xnyt31XT1OFpr1k2xh5zc3D7sC1n35990ZiPsuZL4PmwHaBP/9ixY2FqTv/+/QEkCliiinN9xmoulDA29N7qzBttL2OKV33e6zMrzaf2/vvvB+D4OHBoACD/2VYTrHw1xhhjjDHGGGOMMcaYuqZ8Jd///vcBJFlWw1E2HVnV0eyYt5BmX9SMw6oESRtpVpWIjrDr6J96uqmyi8emoomjgDoqGJ4HR+C45Cg8zyvmhxfLuqi+iZVlf1Y/TXot8Xw4WqmeOjoaGls/Ldugji7p/YyNSqlvHpf7Iqvg4MGDAQCPPPIIgEQ5ohkbw2uvakD1BdR4ZvyrT2ma/2F4zDT1TcynTbNzq5InlslYR9J5D+nhl5aVnaOPeh/VW0qzOMdUH6qQ5utwdF+9pLhPHWmPZYrPKg+YxHLNnuXre5ZbKhZU2IbHZl1geVX1r2pi9WbWehLzWstTMiK/7nC0nortmkDVFJWBYVuu6m5eA1Um6PXierGs8VyP++V9ZFsXoqpB3RfhfVEPacIYYSxTEcVlqEpRlaHWQZb33XffBZCoC1966aW88gOJWooKjvHjxwMAJk2aBCBR9wJJ+0D1MF8//fTTAPIVSnmqGnq9ssq24es9o7hbpHBHBP9TDJoV4uaq1VX1lub3l1a2WGbwsM7wvbTZFcWgd+/eOa8XLlyY/V8VrSSWhV09p4n61Wsspp03r43Gtc5a0DZfVVTqa69tHu9h6H+t/ST1ctZ962wlnWHAsvL6qEIlvL78n9uwTVBFrCrP9PzU+5afd//u2RUH+opxlMTTn/60JecYOuNHr10svmP+mJV5IOu+uA/eF/rQ7w3sl9PnOHx+qa9dLDM7y8P6pzOWYsRUfSGxHAQxxauqhGOe2ernGiqsVdlJpRyX7GcT3jN99lHhqn0PjcPw/qrilUtV6FJdy2Non5L75nOV7Q6PndYv1zZL67AqzNT7ks+q/TXru35/1PvOWIr5rGqsAvl1m6+5rcZ/zANWZ8fxc53JGH7/ZGxwybqSNtsCSOo92zzOzuH5qjJcYzjsX3EbHpPxqs+u2CzImKc+v0Ozn0nVchq//vWvASSezKwjmvdC47xPnz7RfZqaQwXsrFmzct7Xfo/2/1SlCuR/j9VcPDojR+NK22iNR12Gfa6qzOgw+xONYM9XY4wxxhhjjDHGGGOMKToNABxccK3qUNQfX3v06AEAWLp0afY9jkqroi/mAamjDKooVD+kqmSD1dETjnapOkSVKao+5Yge1VEcwVQfnHAb+hzxvFRZRZWNegqpwovXgyN0HAVU1W54PoT7UK819fnhksor9ZRSX8q0ESFVf3BUn6pbjk6NGzcOdZ2+ffvmvKaCREfcgHyPU413zb6s6hod1dbRYB2tqwxVv8WUryyb3n+ivldcP1SSqJ8dR6U5Uq5KE8a7Zi5lLKqSiWXndaJCJTwWy6N+Tupbyn2qn+6qHa9UHOuoimOdcfjpAICXy/64p0y5iviw/JpVVUf7dVRV1biqJNC2SpUpQFKH2BZcccUVAICePXuiWKgysDIWL14MIFFrsaxUT/B6836p/xaXbNPYZrDtDD9T71ZeZ94H9YGKZdtWj0WqjDTuwvIVyoyryt4YbE/Vm3r06NF561J9z+dG27ZtAQDHHXccAOD11ytk2qoczPo7frRnRwwfFo2h/Nae5bt7lqHyleLAv60HACxYUKGsppVgLFtx2iwUIP9Zpe1o2jOM9/XWW29FKbn88suz/zOe+Vxn+8f7xnYl5t8ci0FVpqmfa3isQv0BbatVaa99AO6PZWN9Cj1F9ZnF+NZjqRch21/OjOB+2I9QxSLb+vC8NaO7eoBr/0+fp2xj9Pmb5Ud7lvQm/GuoYqhQvupsA77W+xlT56i/rCrC0/xR1R+W509v4mJQ2b44wyHmoa2qf1UoqS9yzNc5JOa7qPVC7wdRf2PWS/U31rIASezq7B32K8JZB0C+ElIVjnxu8J7r81w9jAHg3HNPBgA899yanHVUOa59IS5V1ah5ItKUr/r9SrPXc8lnNPtp1113XV7590e0r0+WLFkCIP+68N5o+xM++/W+aR9R+yaxmSQxlbLW2bB/qv1J1g2tO9q3Uc9b9jtYx7T/rnEfHjt23qq+1eeL9hv0HEIFf4zhw4cXXMfsOzijY+LEiQCS9le9ilmveM/T8gnFvIT1u5R+99bvZvrbhS5D7/D68PuFKSZ11HbAGGOMMcYYY4wxxhhj6jcNUS9sBy644IK89xYsWAAgGV3QrO46qhXz4VA/mZjCA8hXTcR8atTniKN6fM1jcXRPy8AR6LSRdu6DI4Y8L44ociSHn8c8/FR9qv5P4bFjCkYqAngsjv5z9J5L3gveG80IqcqONEUgVWv7k0eUKkjmzZuX/Z/3i6O8VEepp6uqarjUkWlV9MW8/ypDVVQkNuKs+9R6oyOHYfljCk/1vmVcME7UV0+PwRhU9TmQxCuVklyq+oRqlpg6NS8jbCZ3/2nqclXv6fnHfBFjPrSaSV092MJs7FSY1pXR10suuQRA4lmqKj0u1TM6dg3pbxr676kKT1UU2h5yX9rm835QXaSKOr2PQH67zm0Ym+3atQOQeEMztqlSZTvRvXt3ALnq7ULwvFle1p9jjz0WAHDUUUcBADZu3JhTVl6fR0dUeJmqClOfgX36fKfigO8mbcBvf/uinH/ubJWYh2vfvhXn+cgjLwDIb2dis1/SPLXCjN21BeOO9Z/xmJbJG8j3ueZ5qRclqcwvTJWt6sUZ8w1UxaeqkPXYac8A9QGN+W4zvtkO0eOY90ozGBP1sQ2fI2zXqZ7dsqVCjcpryGvbunVrAPn9J71up8zuUrFjKrlP2bOk53FwK1levXaq/jz66Io6+M47TXKuh3ozqmJGr1/YX+JzkfWbfvO1hbaTqk7Wdlb7grz+vE8xDxo8l+4AACAASURBVNuwPS3kB6t9HH2G8tjsx/IasgyqgmbbHsLysO5yG9Z5ttHaRumsOe1b6/MmTdX+wgvr95xXriKcx2K/nOuz/dHz4zmwvWLZtI8JJPWH9Yvb3HjjjXnXxiRceOGFAIDf/e53APL9VqlUT+uXs03T3Bkan9rOEG2rVdFX2XdfrTN8rV75OgtM0f6EKt55/qyLQP5sN56n9re1/6f9wNj7VfGTNvUDnf1FHnqoIhGH9pUZr0D+DM6Y4lVn9MR+B9JnG5eqejcHInXcdsAYY4wxxhhjjDHGGGPqJ/VE+ZoGR610NJAjGZo9MpaFU72XYt41QL4iR9fhax0ZV4UnlR76vvrPhiNyfE/9fDiKop5RHN2OeUfpqIxmEA5HXNVTiyORPBbPR5U6qhpTzy2uz1FzKl+uvfZaHIhw9BdI7jO99FTBTTQGeY1VLaUxxXuosRyiyp1YBuyYz5OqrXQEkXUw3C8z0nOEUjPvqtpHy5SmjAnLSlQBBuT7Af3oRz/K2eZXv/oVgHxVo3p28n1e8zWN1+4pU1yxpvVaPfFiPkKsv6yDqkIfNmwY6hvMLKvqVFU9qweYqljZzvC+hv57qh7juqrkIKqm5Gsqf5555hkAwNlnn51TBhLGmdanmGKaZePnrAsDBgwAAHz44Yc521UFemNRPbt161YASVbeF16oUJfedNNNOdv98pe/BJBcN5aFzw3WCcbxokVrc15X/F+5F5u+5r149NGVAICGDXOVoqr2Z1xodngguabjx49HbcP4pLqS7by2m6pA4vmE3mBAviel+tmG7YrGs6qi1HNS2/SYVyzRtpx9AiBpy7lkuVV5pM8mbU9jbb9et7Bs3Pdtt92WU96f/exnOcdgn0O9wLUf+fIPK/y6z5hV4d+dVcAejtzXAHZ/mtuGE/X0fe21ivKyrY7Fs/YbqQ4bMWIE6ho8N2YFZ/ugzzVVffOc1btdPfv4OqzbqkgqpIzXPhGXvM4sC/vWXKpaLzwffU5zX+rFz345t1OvdxKbZRSiHq46o4jtDOMr5h2sPvvsQ+gMoAPFr7WUzJ07N+e1eqHqDIO0/BecrcL7xHZVnwva5mv8qoqVaPscbqNlieUS4fvqh6nPD76vHrehIpHxx/PVmQCx7x2x3BOx2Rtm/0V/U+B3jPA7gX7XjH3vJfobTOy7mn5H4+8eY8eO3evzMfWchgC+UXCtamHlqzHGGGOMMcYYY4wxxhRf+Fr6H185cqjZyjnqp5lNVfnBz7k+R+o4OqH+YeGoh/qA6Qih+snpyKOqSVTJpaPl4eifjuqpIoXbcrSG10eVHKrw4naqGkjzQuG2qjCjykEVrmHm4/BzHpMKDr4+UBWvJPTUUl+nmGJJ75v6dKmnmCoxVCkb7otodmmivrFEswnHfEr5Pn0mgUTpG/OxSvP3A5L6y1HFbdu25bxW1ZWOUob7UMUrYZxu2rQpZx+avVw9nHX0n6T5t8WUaKqGUhXU/pSNlef64osVHqHnnXcegHz1Ray9peJHlRFhzOi+GLOqvFB1EJfl5eUAEu82oj7AqsqobJ1CXuKMiVatWgFIYltVU5Vx7733AkgUWBrrMd/fG264IfV9+vIecUSF9E/rWZqiXjNiqxJFVemqBmJ86MwJKhAmTJiQWtbaJFQ4tWzZEkByHqy72j5on0Ofp9pf0PZG23og38M0pjxSZZIuNcZU3cH6ErblVJWoj7zOFNIY4flR6UR1qs4Q0v5XGEeMhXvuuSfnPNg28HxYj+kJy8/Zp1GV8uMXbss5Jt6rWBy8NWlPysVnXZ+nMb9u9fq95pprUF+gkp6xzue49ld57qqAZQyr4k+93DW7eoj2O9R/Vtub2DNA65/enzDONAYZ29ofISw3v7ewDNy3lpUxot89wv/Zbui6VFPqeVA5yWPq5yyz+sWbvWf27NkAkv484137fTrzMmyvtU/P9lA9JNVnWfMg6PdR7X/oDE8gfVZF+Fo/1+8Esbqmz35eh3AWoM7GVAWsznZTpa8qGXW2k+P7wCPt+9LkyZMBJP0WxmCsD6VttM4y1lmKMT9acwBSfMtXK1+NMcYYY4wxxhhjjDGmXipfjTHGGGOMMcYYY4wxps7TEMA3i7vLkv/4ymm2haY56lQ0na7N9zldjlMRdCpr2rQPPZaahWsCCJ3uwCXLTnk7p1PwHLkE8qeOxJKzcJoWJfCa1IVLHrt9+/Y510unQIbHoIyen3GqCcvPfXDaEsvCaTFEp9VWZ9rs/kyYWIVTxmK2EDqlRqfl6dR+nb7O9ZkgJYzztGRUITHzfMIy8Ng6pY5lV8uQquxbp3zEEneMHj0aAHDfffcBiJumh9vzfKdMmZJ6TN6LH//4x6n74rSVNm3a5Kz//e9/P3X9ynjggQcA5E/JZVlGjhxZ7X3WVThFOzYVTROlaBKXWEIFnWYXxlRs+jWvN+sPE1J98MEHAIAnnnii0nNhvdWp0WEZWS6N5ZjtgJZR235tX5WlS5dm/z/11FMBJFO5Z82aBSBJxFVdWM8UJjQIk0+y3qclswzR66HWD0wgU5encYUxzHglOq1X22BNjKLTKzXxJdfjVO+0tjM2tTSWiDCWWEv7SSwrrTDC6aKxaax633UKulrq3HzzzTnr/+IXv8jZjssw1rS/xH2xrmjSPm3TZ86cCSBpy7ndBRdcgOrC54lOW6yLCbP2Ft5bxrJOFea5a99Y44owrnjdK+uXqy0SX2tiNk0wxH2oJZlalrH+8nVop0XLE00ArM8wnp/221hf+H4s6VpaMjHt8+m0a/1eotNj2T9XWxNuz/Pm9o8//nj22JdddhlM1eH95pTmsM8L5N8brh/av2lfnwmCNEEcvzd+/PHHAPITQWuiRrWb4H7C6fiMCT5j+P2b9T2WlFntOPR7uR5bbQHD8+QxeU3YD9AE1ppMVfuJWs+5vTmwiX2nmj59OoB8qzu1wWIcOZHW/sFvfvMb3HXXXQAqnoVTpkzBKaeckrfeoEGDsGLFimzbOGvWLHTt2rXynVfVdqAauQCtfDXGGGOMMcYYY4wxxtQLOnTogBUrVqBp06ZYsmQJhg8fjj/+8Y+p6/785z/H5ZdfXvWdV9V24C+FVyEl//GVoxPLly8HkK/o5AgcR850pF3RBD6q8gzVRxw50xE1VU3pCIkqmNTgW4/N/TBpEJCY5Kv6S5P7ED1fVevqSKQmBQpVJJowg6P1quxVZRbLylFQHVnn9lT8HuiEKkyO9jJ2OCIeM4ePKWI1kVzsXoVqJFWGxEz2lZiqivHDUf/KFIkxhZZ+TlQhogmENBmWKsXTEiGFagMguYY8Dyo1+/Xrl7NeMdWo119/fdH2VdfhdaTaTBOTaXIfwvvEGOF9iiV9SEtWou0h2yoqMZiIZ8mSJVU6F6oztM0ME05oAqmYGkzXjz2bYgo6qlp79uyZfY/H2Lx5c84+nn76aQBJMrmaqvKqkgCO6m7eR20PNPnOddddV6My1SZpsaYxp4k2tV+hyYgYQ5okMZbQM/w/1qZrXdE6o5/zGHw+aVKKNHV5TPkaq+dUXt14441IgwoDVVuFswRU9acJt7gPLpXBgwenvr831Ke43VsYk7E2TWeeqcqZy3D2D5A/My0tUaYek/dclfaaOJbrs2w6i4bHUmV2GDN85rCvTjUeFYGcCcH+OvehSRd1hguvBxO/aSJd/R9I+td6HnrN2Z7EEsPo+0zOeOmll8LsHZr4WJO6afyn9fd1H1qH9P5yH1Rqc7aL3u+aKPWohj7yyCMB5H8PZR1jbGq/SNdj2x+qUfk/610sCbE+ozRBpT4v+L1zf5pFZopPfUp8aYrHWWedlf3/jDPOyH5nKgpVtR2oxo+vDQuvYowxxhhjjDHGGGOMMXWL6dOn48ILL4x+/q//+q/o0qULbrjhhjyLpFQaoUL5WuivGtSa7QBH79QriqPaOgoWG3FW1Qk/T/Oj05E2VXSoUoejfKp44X60rCwT90t1CQB89NFHAOKjdFTjcXRQ/W10lF+XOuodBhBH7zniqkocjsjG/NR4bF4fjkjG/LwOVEL1g6owVcmqPrm8xowpbkeljyo9VR2RpiSJqaOIvo55Nar6T5V/oVIrFp96DMYM/a1i9UKvo+4vVCSqypbb0JtWvdVMcVFPbX2falS2R2zjWBdUYa/3PrzXJOYLyDIce+yxAIBLLrkEALB48eLUsp933nkAkva3MgW3toexJVFvS7avbAuU+++/H0Dy/OB1A4DWrVsDSNRMPF9e03DdUqPqbnp5attU3z3BtS+i91NjRL2P+b569hFVkKapT3VfSqH3eQ4xj/001bbGcQyuRyVS6KkZQqU0Y1X7V6FPoNYxrqv+nfU9tuoKeu/YNulsMG2z2Tarqo/bM+5YJzTWQ9TLUfMdqIq2kAcs39cYD+sKyzNu3LhouYBkFoJ6fsb6JYRlSJuhpN9teA15fvoc1X3ynqh3IWfZ8bUVrzVH23r1FWbM8ZnNuAiV4KpI1lluMSUs44Ixt3HjRgDF8aak9++jjz4KIOlfqK+sPvP0+aHfDcLvhJobhEteK9Yp9cDndeB1o4KW+2acG2NMjGXLlmH69Ol48cUXUz+/88470apVK3z55ZcYPnw47rrrLtx2222V77Sqnq/VwMpXY4wxxhhjjDHGGGNMneXBBx9E165d0bVrV5SXl+PVV1/F0KFD8fjjj2cFK0rr1q3RoEEDHHrooRg8eDBWrVpV+ED0fK2Pylf616jXqyr7+JqjZbFs76qo4zJUucX80WJefaqQY1nVc0nVV2mZ2dXLUqFv4sSJEwEARx11VM6xdOQ8lm02TVnJa8Hg44ijKgt4Tbm+Zs3UkUvem5jS5UAjVLKp4kEVEqrKUNWcquJ4z1QNkeaJXMi3TUex9X1VWauiK83rlei+FcYOFa+FRq+1HdD2IVSRaaZhXgfGMa9ptYy1TZWh6pJt1ne/+10A+T6svD+qBOWS23OpGc+BuJJKVVDcR4cOHQAgO/VEPWDZNqq3sO43/D/mx0li+6DKLOYlyfaYdeMPf/hD9rPjjz8eQNKeUD3D2O7du3fqPmuDmMdnfST0MVfPd1579aAkhbxv1TdQlbJhrOmMiEJteaE+TiG/4rQ2vdAsBtbbDz/8EABw7bXX5u0DSPpq2qYzhjnLA8ifyaPnx7pxxRVXpB7LVA+q6JYtWwYg3jbzHqlftyph2Y7y+VzI8z48pirNdakzzHRGls6g4Odp/Zaq9l0HDRqU83r27NkAkpkS6ntNdPZQqAjUa0pVN5eqbCWq/NXvHyyLczEUD15z9TjWmYl8rTM0gfz41P6qKqH1WOwXlGJ2yw9/+EMAwJw5cwAAbdu2BZDEoj5vtI5qWcN6rnkv9BnE7zZ8PvBzrq/9Jvoyjx49uianbIzZzxg1ahRGjRoFAHjvvffwgx/8AHPmzMl+b0pj69ataN26NTKZDBYtWoSTTjqp8IGq6vlaDWrtx1djjDHGGGOMMcYYY4ypCbfffju2b9+etTQ86KCDsHr1agDARRddhGnTpqFNmza4+uqr8dFHHyGTyaBr16546KGHCu+8BLYDtfbjK0exWrZsCSAZHdNMwBzF5VJHudUPSv1xQlWKKpRUFaLE1KUc/dOs6hzR5DH3RhE6ZswYAInvX8eOHXPOK6Z8rCzjNr1ydASV5aQykHDklSOSup4qYu2hWcHOnTuz/6uKKabkJjqSriPLpJBva9pnnS89AQCw4fH1OccgMc9BXU9fq1q9svIwRjhq/8EHHwCIZ2WfNGkSgCTuqYBS77nKPORUaWCFdmm54YYbAACTJ08GkLQzvA+898wsraoKKoBiav801RTvv6qbNCN2WqZroCILJpBk++UxVbFUWT2LoVncGcNUfRfi5ptvrvYxTXEI26Xnn38eQH5sqe9jzOtXPbNVgRd7He5TfStJTJGk28cUeUqaz2Ssf8R6TT97tukKO7M6s4Z1Mi2DNteh+ol9GB7Tqr7SwraZbbLOHuH94b3jc1n9LLk9VW2qFAzRGI2ptonO0InNumEMMXbC2TbDhw/PP/kqMGDAAADAjBkzACTPFZ53rL6F9U5n8/EzzdHA9fR5om2CKihVkW/2HrY32p/gtS6UPyHchkudEaHxwLhlLLH9ZF+lFPTv3x9AEtfHHHMMgPj3DvaXGPdchvVbvyfyPNmWnHx2hdLszdVvAUjaFLYxvIZ8HcsPYYwxZNq0aZg2bVrqZ08++WT2/+eee676O6ftQBGx8tUYY4wxxhhjjDHGGGPqs+3AsGHDACCbgYwqEo6OqS8OlQ8cBVQVJ9fjqKL6BYbb6CheTOmnmVq55Cio+pERetKoT1R1oAfXzJkzASQKAo5+qkKLo4mqhA3PS5WAXFKxyfNTD1heQ81AzGse83g70KBqGQCeffZZAImChNee15Sq4ljMxTJsxxR5aerT7L4rwjF7H3WbmKoqpnjSY4f1KeZJTNXj5s2bAQB9+/ZN3TdRP6e7774bQKKU19FwIO5Jq96CprRQmTBlyhQA+T5gVCCzTVPVkKrA1e8SiCuetV2M+XmffvrpABJFFsugyqy042j9idUbVSjxuRDzbKPa215mdQvet6OPPhpAcn91RgnbV/V/LKTc03Y4XE/b/ULPC21/C8WmEq4fK7dmVX///fcBxOOW9XfgwIEAgHvvvRcAcMQRR+ScY6jUU1Wjnles/KZmsG1me8i+INtJ7Qsr2n/na/Z7tB8bom2vekPGPLZjr1VByHq8ZcuWSq5A9RgyZAgAYOHChQDinqBp9VH75WxPeG147TWPgyp89dnG1zFPcVN9qAh9+umnAST3Rtsj3pM0NX+sTdYZAIx/xi/vf+z7ZilgXM+dOzfnmPos0O+jfB22D6rMZhxzm//33J8AAH/720E5n3PJ+vvxxx8X4cyMMaaGWPlqjDHGGGOMMcYYY4wxJaA+e74SHe3VLJGaCTimxiPqT5q2vipgYxmCYyPM9DbbunUrgETdyNHP8vLySstYHQYPHgwAWLRoEYBkdFQzY8Z8hID8TJ2x0Xj1xuK+VMXAEcwdO3YU5Rz3R6gGOvnkkwHkj5RzFJvo/SSaGV5HntN8V5VNr7wDIKncGvexjNcxb1gtS9rovvqrvffeewD2Pjv1+PHjAQAPP/xwzjFDhbcqJHmNqTS0V1TtQuXNAw88ACA/47POXohlYk9TmMYyyqsXmfqpqXqkadOmAPJ9O9WTMHytzwN9NrFO6qwMZoO//vrrkUahZ5vZN1x66aUAklk6Cvsu2q5q30X9MfW5nNaWq5KbxNSAOvNF64nOBqiKikr7AYzjTZs2AQCGDh2aut19990HABg3blzO++xnqGI4nMWg/vnchn7J9Jc2xYV926OOOirnfe1namyTmEc241Fnp1RGLI9BTP3N9dkv5ywbzScRa39rgnr4q5o97RkW84hmedXrXD3PdWaeKmhN8Xn33XcBJPeVinD11k6bOVPIm1j9vdVXlveZHtu1Qb9+/QAk3z9jzxP2n1jmUNmu30m1PhJVePM7PL9P63PEGGP2CfXZdsAYY4wxxhhjjDHGGGPqLI1Q/20HOErdrFkzAMkoGVURHFEjOvodUwJWJRt6dTMHq+JJlXV8vxQj6xzF5/Vg2VUprNknw3VjI6+qvKHKRBU7HLGkmpEebiYf+v0+88wzABKFnaqK9X5pRlC+VmUe7wXf5z0C8r0mY/GsI8yh8ijcp8aJxkuo4KAyib5qrN/0eK4pbCeoNqdHXXge9Hajb7LZt2hmbCoe6J1N/2NFlT1p6PMg5vvHmGCMsCzNmzcHEM8QnaYCjyleVXXL11QK0ls7RugZbeoeVAUyAzRjSGc1MMbUQ53Pan7O9pdtvyqfgKR9j6ljtS/CGKP6jcekQku3q6yfxHrLNn3btm0Akra9UD8nplRiNvdWrVoBSFRSbA+ApE9F70FTO9C/nxmA6f3KWGasqq+xon3MyrwwY76+sdcK+0iMGba3fM3nC/NAlALWEZ0Fp7MgWN+AuBpdZw/pDCXeC33N+nPVVVcV8cxMyPDhwwEkM7C0XlSmbtW2Vj2+VcGtMw3Vu7g24bNP+/wai3zehOet38l1FpL2p3ie/O7Aa26MMXWC/cF2wBhjjDHGGGOMMcYYY+oc+0PCLVUIcpRaVSGaVZHERhpjo+RAMlqnWd45elcoeyozrnOUj0pQjriXApZVMz6qb1Qa6kMU899S5StH0vk51TQjRozYy7M48Dj//PMBAM8//zyAJJ65DBWrQHLteW/UA1b9d3nPQv8kHWlWb019nzHEOOZrHjvmEcsyhv613EfMB7CmXHLJJQCAlStXAkhUZICV2HWVH/3oRwCSLOeMO3qXUZWnCtiYSi98L+avyZikIolqEa1XMTVUTOGh5UjbhuVmW03PMqrKTP3k8ssvBwAsW7YMQL4qUNvmmDKWbbU+u9XfO0SVRVyqbyrbasa7qokY76qqSvM65qwCersXK35VMbt8+XIASV0FrHjd19Cj/cQTT8x5X/uMOjtGVXzaVrJfn6aMK6Si1X1rv5x9D35O31o+V7p3717ZKdcI9okXLlwIILkuPF9VwgLx/pWqCbkPbWfY92E95XcpU3rY16QXKttV7bOE/QbeN/WHVcWzxnnMP7k2Yds/ceJEAMmsBfbdeG78XhPWZfVu5mt+n2SdYJz36dOnRGdhjDFFwJ6vxhhjjDHGGGOMMcYYUwL2B+UroY/YCSecACA/0yOVTDGfVs0knDbyGPM+rUwlG26nikB6lxFVpRYTzRzOshx55JE562kG5RC9Jvqa6hiOpPOYpuYwM3Tnzp0B5CvrOHLM0V9VNKnaNObfmvaeqlBiXq4cvWccqzch6yDjZF8q+c4888ycpan7UAHLLOiMK2YQplKpSZOKp5p6ooVKQVXqMVYZo6oSUtWFemVrXSBUVdE/MNyWvoc6g4JKV3pkhl6Wpv7zxhtvAABOPvlkAEk8MJ7V41VnJ3A9fq6xHKqGYmo47ksVsPScZB2iapVtOrdnvWBs7ku/4R49euyzY5t0qKJ89tlnAQBHHHEEgCQ2GT/sCxCdRcUZa5X1X1TNrUrQmJ+3zrzRNlxV37UB1dt6Lqyvad7hqvhl+8BtuFSlq2f67HvoS8p+BHM7aB8biMezfq6vWdcY5+Fsr9pGnxOTJ08GkHwPpco8PG9VqPOZw2dTKXKkGGNMybDnqzHGGGOMMcYYY4wxxpSAEtgONMjo8Fst89RTTwFIRtpJ6GkJ5GcR1WyTXD/0x1HFa9roJBAfmdQRdy7pXfPaa68BqN2RvFmzZgEAWrRoASA92yTREUiOqLL8AwYMKGlZDfDoo48CANq1a5fzPu+JKl4Zoxz15j1TtUjou8q6wNiPKb01zqm4oF8gFRbqPUZ1h0esTU2gip9KDrbp6gFL9VTolxdT8Wu7p96vjGn6dnft2hVAvgqRMPZD9SozyuusC9Ybtqcsm7P17p/MmDEDANCxY0cASZzG+hU6e0f9hqnQY/sNJHHJdp/ovtUfUDNGM365Hz5vPLvFVAbb6FNPPRVAvsqbsN/C2QA6A039LsMZBtyG76lKlsdShbgu1RuV7TS9xWuzHZ40aRIA4LjjjgOQtAnh95GY121MIejnSN1l6tSpAIBjjjkGQDIrMmzLC/W/Gd+MY8624f1nPAwePLhEZ1E8qIgFkvMZO3bsviqOMcYUjQZduwHPri643qk9u2H16sLrAVa+GmOMMcYYY4wxxhhjTElsB/a58pUwozDVIRwV5Gixep2prxqXobeUZoHXTPM8hmbS1vdVdcUR9l69eu3l2dYcZqGkiiBUCrO8+9LXzeQyf/58AEDbtm0BJPctlvmUqineS6qsSKiM4r40jtUnNhbXXFKRSL9Aqgedtd0UE6qERo8eXel6bOOAJNM8vS35PCBs/6h05ZLvd+rUCQBw7LHHAsj3YNa2P6xf77zzDgDg/fffBwDcdNNNBc/R7L/MnDkTQBJLaRmfgaQNZ6yyDVfvSrbf4b50Jo+25bFZDGyzqZ6iOtuKV1Md5syZAyBfyamzyBjbjEP1Odb+O5DEuMauzjDTWQ6xryp8n3kk3n77bQDAzTffXJ1TLgpsGzp06AAgdwYFFbl6fiNHjqzNIpoiQqX40UcfDSDxgAXyZyVqf5txz3432272PTwz0Rhj9j0NunUD/lgF5evpVr4aY4wxxhhjjDHGGGNMlWkIoHGjgqtVizrz46tmFKbCSZWBOnrIUUIqREJvKfVFI5pJOLZvHWnnSGVapvnaxqrW+kWfPn0AJJ693/72twEkChLN9K7xzPdVDQLEvYoVVUupioWwLFa8mlJQSPFK0vzytD7orAT1uKTKisrZ2PZEnzdA4sVmxasBEg++X/3qVwASD9iysrKc9TRmtb+RpuRTv25uU2h2DtfjzCHWg+3bt+/VOZoDm/79+wMAHnvsMQBA+/btAcT70to31jgO/btV8RpTvsZm8mgZqBzkflq1alW9ky0i9cGf0xQPzYNAX3AAaN68OYBkZoP2OTjzgcsrr7yytIU1xhhTbRoBOLzI+6wzP74aY4wxxhhjjDHGGGPMvqIBgEMLrlU96syPr/QkmzZtGgDg7//+7wHkZ3LXrKqh1ymQq+JTD7bYyHpMVRJTmYQebcZUh0GDBuW8XrRoEYBklFzVHVSMMGYrs2jWbXVdVaNoNlYeS5WwxuxrVOGnCnEq/TRL/GGHHQYgfyaFonWDaiog8WIzJmTEiBE5r6kSbNasGYB8j9dY7IXqa8azKgZVNUsYt+GMHyBRwIaKQ2OqS+/evQEksX3UUUcByFejsh/OWKbfpapUgSSWtT9O5arGuvZTVDnIY7Pe1ZE0FuYAZMiQIXnv3X///QDy6wTbbLbVxhhj6h4HwcpXY4wxxhhjjDHGGGOMKTpVtR34tBr7rHM/vg4dOhRAkkWSGYUPP7zi1FWFStQzM23dop5k4wAAEEFJREFUmLKVS1VRqSeV+gkaU1P++Z//GUCS2b1ly5YA8uNdVVOhuoPKEY6kp/lWhu/r54x7VaQYsy+54YYbsv//+te/BpDvn8m2+K9//WvO+/R4paKcMyZUPaUKLr7PbPFaDmNiUCU4adIkAIlKkG15zPsv9DbWtjzmURxuE8LPY7MfjNkbGNuzZ88GAHTo0AFAEtOMM8arzp4J+8za/4gttU/P/venn1Z8xfn8888BJHWmb9++NTpHY0rB2LFj93URjDHG7CUNAFRlvnu9/vHVGGOMMcYYY4wxxhhjapuq2g5sq+Y+jTHGGGOMMcYYY4wx5oCmEYBvFXmfdfbH1+uvvz7n9dy5cwEkU/loXs4pTJpwAkimI2mSFqJJu3bu3AkA2L59O4B083RjSsGYMWNS33/ooYcAJNOomTgoLembTtdTqwKdiqo2Azqtz5i6wmeffQYgiVm297SEYYIs1otvf/vbAJL6otO31W6AdYXJtT766KNSnYrZzxk9enTq+zNnzgQANG3aFABQVlaWt472URi3OgVb41jbdE7JHjly5F6ehTH5DBgwIOf17373OwDAEUccASCJ15jlV7hOzBaJMcw2nRYwH374IYAkOa8xxhhjTCmpqudrdaizP74q/fr1A1DxQ+lLL720j0tjjDHGGGOMMcYYY4zZn2iIqnm+VocGmX2QkWHZsmUYM2YM3n//fTRq1AjnnHMOHnjgAbRt2xZAhQLvuuuuw8KFC/HNb34T48ePx4033pizD6pIOOJ+2GGHAUgUIiGaaIsKv08++QQAsG1bhVNDTLFiTHXZunUrRowYgdWrV2Pr1q1455130L59+7z1duzYgU6dOqFTp0548cUXq7x/JqQDgDZt2gBIFFVMLlRILUWFyRdffAEgqQdXXnlllcthDiyq0jbXBnfffTcAYPz48TnvMyHMSSedlPM+FbGsE1TMKhs3bgQAXHbZZcUrrKlXLFiwAPfddx/WrFmD73znO1i+fHnqeg8//DAGDRqEqVOnZhOF7g3z58/P/t+qVSsAccU2UcUrZy9Q8free+8BSAatjVFuuukmPP744/jggw/Qtm1b/OQnP8lRtj733HO46aab8NZbb6FFixa49dZbMXz48NR9MWEoZ6Y1a9YMQNIXCWfhaD+E/XHOOvj4448BAIMGDSrKeRoT62cvWLAAEyZMwObNm3H00UfjZz/7WTYJrjH1iWeeeQbjx4/Hf//3f6NZs2a49957ccUVVwCo+K43YcIEzJgxA5999hmOPfZYLFu2LJsM1BgT55hu3XDT6tUF15vdrRtWV2E9oOIH3VrnhBNOwNNPP41PPvkE5eXlOO6443KmEv30pz/Fm2++iXfffRfLli3D3XffjaeeempfFNWYvaJhw4bo1asXHnvssUrXu+WWW9C5c+daKpUxNcNts9nfadasGcaNG4dbb701us7OnTtx55134sQTT6zFkhlTPJo0aYLFixfj008/xcMPP4yxY8dmZ5V99dVX+Jd/+ReMGDECn376KebPn48bb7wRa9eu3celNqb6pPWzt2zZgn79+uEXv/gFdu3ahZ///Oe46qqrsvYWxtQXNmzYgKuuugp33HEHPv30U6xZswannnpq9vMJEybgpZdewsqVK7Fr1y7MmTMn1brOGJMPPV8L/VWHgrYDGzduxGmnnYZnnnkG//AP/4Dy8nJ06dIFCxcuRI8ePap5uApatmyZ87pRo0Z46623sq9nz56NmTNnomnTpmjatCmGDRuGWbNmoVevXtl1Bg8eXPA4oToQyPeRNQYoXYyPHDkyq0hKY+XKlVi3bh2GDx+O6dOnV2v/abHMfbB+qXqKqC8gPY7prWb2T4oR51Vpm2sDVbySxo0bA0g8wbX+cfYDoRKWdaC8vLyo5TS1SzFi/PzzzwcATJs2LbrOj3/8Y4wZMwYLFiyocZn79OmT/X/y5MkAgA4dOgBIFITahutsHp29YMXr/k0x4vzf/u3fsv+ffvrp6N69O1auXImzzjoLO3bswK5du9C/f380aNAAp512Gjp37owNGzbglFNOydtXzLOeTJkyJfs/21zmWnC/3KRRrH55rJ+9efNmHH744bjwwgsBABdffDGaNGmCjRs34sgjjyz26RiTSjHi/D/+4z8wYsSIbCw3b94czZs3B1AxUHzfffdh7dq1aNeuHYD8mWHGmDilsB0oqHzt2LEj7rrrLlx99dX429/+hsGDB2PQoEHo0aMHRo4cicMPPzz1r0uXLpXu97333sPhhx+Oxo0b45577sl+md65cyfKy8tzOninnHIK1q9fX8NTNSadUsV4ZezevRujRo3CAw88kDel1JhSUNM4d9ts6jq10ZavWrUKq1evxrXXXlvCMzEmTrHj/PPPP8crr7ySVXK3bNkSffv2xcyZM7F7926sXLkS7777Ls4+++zaPE1zAFOMGK+sn92tWzd07twZv//977F7924sWrQIhx56aI369cZUl2LE+csvvwwAOPnkk9G6dWv069cvK6Z57bXXcNBBB2HhwoVo1aoVjj/+eDz44IP75FyNqY8w4Vahv+pQZc/XSy+9FO+88w4aNGiAV155JevlVFN27NiBqVOn4txzz8UZZ5yB999/H8cccww+//zzrCz+D3/4A4YNG4ZNmzYV5ZjGpFGKGP/6669x8MEH53m+/vKXv8T//M//YMqUKZg1axamTZtWLc/X6jBnzhwAidca/S6roh43+x97G+f1oW1evHgxgIoOLZCoq6gcpPcgFYOsC2+88QYAoG/fvrVXWFMyitGWT5s2DXPnzs3xfN29ezdOP/10TJo0CWeeeSZ69OiBfv361cjztTLmzZsHAFlvNp4Hu22cvbBz504A+dnozf5NsfosAwcOxLZt27BkyZJsP2Hx4sUYOnRodlbAlClTMGzYsKKV3ZiqUJMYL9TPnj59OsaOHYsvvvgChxxyCB599FFcfPHFpTgNYyqlJnF+yCGHoE2bNli6dCnatGmDgQMH4hvf+AZ+85vfYN68ebj66qsxZMgQPPDAA3jzzTfxve99D/PmzcM//dM/lfCMjNk/6NytG2ZVwct1VCk8X4cNG4Z169Zh9OjR1WoUXnjhBZSVlaGsrCzVH61Zs2YYOHAgLrvsMnz99dcoKysDkJjv838m1DKmVJQqxpXy8nJMnDgRd9xxR02Ka8xesbdx7rbZ1Bf2NsYLMXnyZHTp0gVnnnlm0fZpzN5SjDi/+eabsW7dOixYsCD7w+sbb7yBPn36YPbs2fjyyy+xfv163H333fiv//qvYhbfmILsbYwX6mczQdHy5cvx5ZdfYsWKFRg6dCjWrFlTrKIbU2Vq0pY3btwYgwcPxvHHH4+ysjL85Cc/wZNPPpn9DABuu+02NG7cGF26dMGVV16Z/dyYA4nly5fjW9/6Frp27YquXbvi9ttvL7gNbQcK/VWHgp6vAPCXv/wF48aNwzXXXIOf/vSn6N27N5o1a4Zrr70Wc+fOTd2mXbt2WL9+Pbp3746//OUvle7/66+/xocffohdu3ahWbNmaN26NdauXZsdlVm7dq0TW5iSUuoYD1m1ahW2bt2KE044AUCFeunzzz9Hq1atsGXLlqwnWrHo379/Ufdn6i81ifOmTZvW+bZZs2uHWbbTYHINK173H2oS44V49tlnsWLFiuwXlx07duDPf/4z1qxZk+cxXwyuuuqqou/T7B8UI84nTJiAJUuWYMWKFfi7v/u77Pvr1q1Dp06d0LNnTwBAp06dcPHFF2PJkiVWBppaoyYxXqifvWbNGpxzzjno1q0bAOC0007D6aefjmeeeQZdu3attXM0pqZteZcuXaL2dbQnsL2dMRV0794dTzzxRJXXZ8KtYlIl24FrrrkGn332GRYsWIDhw4fjk08+qVGiif/8z//EiSeeiOOOOw7bt2/HqFGj8NZbb+FPf/oTAODWW2/FypUrsWjRImzbtg3nnXceZs6cWetJXcyBQ7FjHKhIgrJ7926UlZXhjTfeQLt27fCNb3wD//u//5udJgoA8+fPx7x58/D444+jVatWNT0VY6LUNM7retu8dOlSAMAxxxwDILEd0B9jaTuwZcsWAMj+yGDqPzWN8d27d+Orr77CrFmzMG/ePCxduhSNGjXCwQcfjE8++SSb3AoAfvCDH+Dyyy/HNddcg299q9jdM2Pi1DTO77zzTsyYMQPPP/88WrdunfPZxo0bccopp+D3v/89zjvvPLz99tvo2bMnbrnlFlsPmFqjJjFeqJ+9YsUK9O7dO/tj65///Gecf/75eOSRR3DBBReU6pSMyaOmbfmMGTPw7//+73j22WfRqlUrDBo0CIceemjWcu6cc85B586dMXHiRLz99ts499xz8cgjj+B73/teqU7JmDrJ8uXLcc8991Trx9f/r1s3LKuCncD51bAdQKYAixYtyrRp0yazffv2TCaTyXz22WeZjh07ZubOnVto0ygTJ07MtG/fPvPNb34z07Jly0yfPn0ymzZtyn7+xRdfZAYPHpw57LDDMkceeWTm3nvv3etjGVOIUsR4JpPJAMj7S2PmzJmZf/zHf6zRsYwpRDHivK63zStWrMisWLEi8/rrr2def/31zKuvvpp59dVXM+vXr8+sX78+s2HDhsyGDRsyq1atyqxatSozffr0zPTp0/d1sU2RKEaMz5w5M6/dHjhwYOq65557bmbq1KnFKLoxVaYYcQ4gc8ghh2SaNGmS/bvjjjuyn8+fPz9z4oknZsrKyjJt27bNjB8/PrN79+6in4sxaRS7X57Wz540aVKmY8eOmbKyskyHDh0y99xzT43LbUx1KFac33bbbZkWLVpkWrRokenXr19mx44d2c82b96c6dmzZ6ZJkyaZDh06ZB566KGinoMx9YVly5ZlmjVrlunSpUumV69emXXr1hXc5tRTT63Svqu6XiaTyVQ54ZYxxhhTl3n++ecBAEceeSSAJKEWrTw49Yo2Ia+99hoAYMiQIbVaTmOMMcYYY4wxpWfXrl1o2LAhysrK8OSTT2Ls2LF48803K92mV69e+Pjjjwvuu0WLFnjqqaeqVA7/+GqMMWa/4KWXXgIANG3aFEDFFHIg326gvLwcADy90BhjjDHGGGP2Mx588EFMnToVAPDkk0+iTZs22c/at2+P1atXo0WLFrVapsqzkRhjjDHGGGOMMcYYY0w9YNSoUVizZg3WrFmDhg0bgprTVatW4f/+7//QvHnzWi/TQbV+RGOMMaYEnHXWWVVa76STTipxSYwxxhhjjDHG7GsWLlyIKVOm4KCDDkLjxo3x29/+NmtHV5vYdsAYY4wxxhhjjDHGGGNKgG0HjDHGGGOMMcYYY4wxpgT4x1djjDHGGGOMMcYYY4wpAf7x1RhjjDHGGGOMMcYYY0qAf3w1xhhjjDHGGGOMMcaYEuAfX40xxhhjjDHGGGOMMaYE+MdXY4wxxhhjjDHGGGOMKQH+8dUYY4wxxhhjjDHGGGNKgH98NcYYY4wxxhhjjDHGmBLgH1+NMcYYY4wxxhhjjDGmBPjHV2OMMcYYY4wxxhhjjCkB/z8E1qQFjQMylwAAAABJRU5ErkJggg==\n", + "image/png": 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"text/plain": [ "
" ] @@ -9157,7 +5555,7 @@ } ], "source": [ - "plotting.plot_stat_map(fdr_img, display_mode='x')" + "nilearn.plotting.plot_stat_map(fdr_img, display_mode='x')" ] } ], diff --git a/task_based_analysis/amygdalaReactivity.pdf b/task_based_analysis/amygdalaReactivity.pdf new file mode 100644 index 0000000..7594d59 Binary files /dev/null and b/task_based_analysis/amygdalaReactivity.pdf differ diff --git a/task_based_analysis/amygdalaReactivity.png b/task_based_analysis/amygdalaReactivity.png new file mode 100644 index 0000000..2215bb6 Binary files /dev/null and b/task_based_analysis/amygdalaReactivity.png differ diff --git a/task_based_analysis/average_Comp_ROIs.ipynb b/task_based_analysis/average_Comp_ROIs.ipynb index 41e637c..944d410 100644 --- a/task_based_analysis/average_Comp_ROIs.ipynb +++ b/task_based_analysis/average_Comp_ROIs.ipynb @@ -13,7 +13,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 26, "metadata": {}, "outputs": [], "source": [ @@ -27,240 +27,150 @@ "import nilearn.input_data\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", - "import pandas as pd" + "import pandas as pd\n", + "import pymc3 as pm\n", + "import arviz as az\n", + "import dask\n", + "import statsmodels.api as sm\n", + "import statsmodels.formula.api as smf" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 25, "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "['/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_008/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz',\n", - " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1223/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz',\n", - " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses2/modelfit/_subject_id_1253/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz',\n", 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pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", - "\n", - "func_files = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/work/fsl_analysis_ses%s/modelfit/_subject_id_*/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz' %(ses))\n", - "func_files.sort()\n", - "func_files" + "## Check mean FD for each subject\n", + "# session 1 - \n", + "regFiles = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-*/ses-1/func/sub-*_ses-1_task-Memory_desc-confounds_regressors.tsv')\n", + "#df.columns.values.tolist()\n", + "for file in regFiles:\n", + " df = pd.read_csv(file, sep=\"\\t\")\n", + " print(file)\n", + " print(df['framewise_displacement'].mean())" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 68, "metadata": {}, "outputs": [ { "data": { - "text/html": [ - "
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'/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1390/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1403/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1419/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1464/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1468/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1480/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1499/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1561/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1573/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses1/modelfit/_subject_id_1578/modelestimate/results/cope7.nii.gz']" ] }, - "execution_count": 3, + "execution_count": 68, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "medication_cond" + "# Set session\n", + "ses = 1\n", + "## Grab group\n", + "# compare between groups\n", + "\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "\n", + "func_files = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses%s/modelfit/_subject_id_*/modelestimate/results/cope7.nii.gz' %(ses))\n", + "#func_files = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/allScript_ses%s/modelfit_ses_%s/_subject_id_*/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz' %(ses, ses))\n", + "\n", + "func_files.sort()\n", + "func_files" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 49, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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YwkknnSRJuummm1rfsXKAHjb3A3fOC1kjO7OVYiMWNHn55Zc7PHHejtm9t0Otd3o761QZI/GSchzlGFkRwH4GkXeBIijUnnDnNlbQkP37e3ohJhOT8pJesmSJJGnevHmSqslkF6HU2ZXEJy9KoKD7j+4PX5w1a9a0TQi2DIwaFEQNDSihWLqK6F6mLmyTS50lLry5vD0mdESuVJ47uj99zsvyAp8XNzQ58cQTta7AzTLmzJkjqT2c4HNkaUo/oMpwhdSZRGXQ7U3ZT3928xO65Vj6wYQ0lprQLU+1qSgcUya4sByFc53uZ5bO0D1uRPrIUSjA557iKJzPLM3ytbnhhhskSYcddpgSiQ0NyaQTiURimuLpp59u/d9GjQ05G0E2cvy3bJwhdariOV5b9iovlfW8nkkUiRCz/UlChtOXj5g0DUcbdCQeNABJZLw+VReZU+IxWcGSEqbU7HeP9KnApLykd911V0lVkwyeOKmzQH+41ntSdZLZ6IDJVhtttJEGBwc1ODiotWvXdjBwg0lUUQJDN+MjM4kmbeQlIKP2vihF6WNgS0EypojheH2XwkjVje59mJ2uC+UwFipxwljJpHmz+bPPqR9IFM/xwyLqS8trGCWERUlT9Mx4HF6Pbr8ocYwP5PLY+GCKmC8ZNJNtou5InK+cl+x37P3ag8NjjsrLklEnNkQkk04kEolpig9/+MOt/7tzm40bh1ZsTEUqXFFoz9n4q1ev1sDAgAYHB/Xiiy926C5QDY9/o/p7o64zm8ExMxPd+zahY0VBFE5iBQ1V00i+zKipYLlq1SpJVY7AVGBCX9IWKzHDMYMezmKmlU8Gy9gwJyJdMa+88kobUyCbJZtg/IyTgAIjZXlBlGxAWVDKfzL2x7GR2bD0IWq/GTEmo+x8Y3By77bbbprusAjGdtttJ6lTDlXqjOX65vvNb34jqZpnFOIo55FUza8oaYbXIuqfy8+8Ft4/ZUqb8hvKEka6RUv3Zrlvg3HtyBPDey8SgIlENvg9H5jRMfm6ujTrmWeekSSdccYZSiTWVySTTiQSiXUAzkhmki2NcRtj1IKw0VbXu7y3t1cDAwNas2ZNRz00DUYSFSMKU9TVSUfGqrdpkuRt2mvA7G+OwccYqToypEMCZaPdxvhUxqKNCXlJ2y2zxx57SKosYE6uumYAFD6gCIVBBsIeq6WVXu4nYtCMQZauIKmTYfv3MuHA/2eyQ1Tkz2QIMhQeG7PFyYyMKFuXmcgsUyj35bFsueWWkqTly5dLkg4//HBNFyxbtkxSJd7g+VUn/8qMdt/0TqJhExPmTfhhQI9LlKvQlETD5erKVaQ4dyL6XK7Ph2uTZ4XXnjkM3GcUH6f4hbfn5wBFd3wuWeXge81/fX95+/Z6lF3aptItmUhMBJJJJxKJxDoAGmxRfJXGf1ROWq7f29urwcFB9fX1dRAlhnwYPolCkRxnuWxTdjdj09w3FcPY08FGNpMn68KU5TmjHnnUDXEyMSEv6W233VZSZz0va0PLE0DmzL88qQatetaG9vX1tVpVum2lFLMFNhewFc+YtNcvY4bOXvU22eqNTDbKEGbNLN1OvMl47sigKRLv7fr6ML5abtuT3td0OsDSpY6XmxVTWrOujajPCeOckQQm3WaU62x66IwWTes3MXepmme8vpRSZGY55yPvDd4DUbtYNgeJpFU9nog583p6nBT3kKRrr71WkrRgwYKO3xKJdRHJpBOJRGKa4aKLLpLUHopivwKGMWgcRaWgNt5soL7yyistJr3RRht1hHBIlCKt7iiLvAyXkEhw21QAY+Iukw4NGoJMHiXjjsJQTGquIzCTjXF9Sbs1oBlOlEhQp2TEiRU1oSBzYFMLJgLMmjWrxaBLNaZIQJ2JC7bmGRfmuKVqYnhbjluTaZDtc0w+FpdaeEzR+Yzqo5tcQHWlG6y5Jhv7+te/Lkn60z/909qxTAasKOaYJFtskvFJna471orTLebffW7Kh2X5fcSo6/Iu6hDFh6PPEXOvq71nTgPbdBq+xv49KqVhwhCFJOgWjdyskaIeBSVYBcFmCXXjtVfFcpqHHnpo7bEkEusKkkknEonENMHSpUslSTvssIOkdlJA9kkN7qY+0ww7luGvvr4+DQ4Oavbs2R2JfRGTjvpLk0zUMekoUTjqTkWiQ/EeZnUzHEnyYcOVoRsyeh+Tr4tUne/JEnga15c0LXReCFrYJUv2yWUct6lemgyaVntvb2+bzjYZNMEJydpmw5OpZHGM6ZHRkXEYdfFEqfNmovsocunQyxDlBPCY646fLeK22morSVXb0dNOO02TBWdzu9UpdbTJfku2GVUNGJw/UeYzPTtNyTJN8y1i3E31/E2iEHVjiLxT9OAQvNcYW/a8dh6HPUjRMUZuWeZMUFedzRPqmDRbz04Hz08iMRYkk04kEokpxpe+9CVJVTmhDZXSAGFpmo0hf7YhzXAWDVAmTZYywxtvvHFHAxSyUCMyfFmmWJKSSM6WRIYGZiT6489k0FYQ4/YMjjFqZmRDsPQO+Hy79G+iy/7G5SXtwVqbmyeAHaPq3CJUO6qrdS0RMZimGs8oYYAp+GRp/szM2HL/HpMvLFXQIhUqjs3gzcHzSJZbl9Vcbjeqn65bli4rdixy/fRkwt3TeING5RTl9ywbiZhvJHEYsVCjiTHzXEfVCmNFuZ/oHonGFGl0R/F23jN+2Puza9BZGcEHMLtfUY+f4/BylIqUquvssXie2gtz1FFH1Z6LRGK6Ipl0IpFITDEsaWsDnwmqUmcpphmd5VHdhtWs0ttiAxOKyGy++eYtyeT+/v4OEkWyZeMvqllmjXOpChYZhix1pSHIz/Q0eGxm0FYOiwgJFc5sUNqA9LnzfkrSMtw1mgiMy0vaWbZRNmbT3zpEcdroe8a5+D0RxRydUc1OU96fWTGZmRT3yfUENOhCaTofZB7M5o7OSZTRHCmf1R0vv6erbDJgbe6ddtpJUmeMPsomLo+LGfWRSEGTAETTvOR2os/8vonVRjHo4WLTTey+CU0MPKq08D3kc+4HoB/aPMfsLEaNeoKekvIlQD1wP5OciHX99ddLko444ojwuBOJ6YRk0olEIjFFuPrqqyVJO+64o6ROA78M1zUlnDLpMwr9+XMp3LR27Vr19fW1/pa/WzOcMeY6I6ncDxMKy+9sPJF98xjJtClp7GP0+mbQjtd731HdtY/Rx8yQGkMx5ba87+uuu06S9MEPflATgTG9pL/yla9Iqlw1ZGFkNNSkLtEUD2uqO4069ZRuip6enkYNcLuG7OagKlKkWFaOgbFpbzOK99IL0OQtaNKHZtYtdacjF1L5/6b6XrMd18YvXrx42OXHAt847PlMD4FRV9NO1kbGFcW1o6oBomledrt8t9rc0XJ1+4vmSdNyTWiq1fb1IkM2s2Z+AJejW5WeE3abK7fNhCL2DfCza+HChV0dayIxVUgmnUgkElMEG/KMA9tQobKW1MkKGTOm+hZDd0Zded+aNWta7NIGD0WZzGqZGBu1OC2Ztg0qHze3SSlYGqWUK6ZATtT2lJnxjl17PYdoeB18TDY4y+PxWBzunSiM6SVthlPKy5WI4nrDIWLU0XIGJ1w5hp6enjAezuXJ/v17lPVdZqFT7Sw6bjKDcqzlsUQx6yh724hqy6P2bOUxsCQiimv7+DfbbDNNFJyR+6Y3valtvDwvkdhCXaydXh0eJxXGIn11oymfYKI1vEeyLh94EcOOvEVN92TdvSd1zjPqpVNlMJK95EvJn62ZL1UPYSuPRRnpfihffPHFkqRTTz112GNLJKYKyaQTiURikmExIAvzGMMZZZF4DHWp/ZnxVra6LWPZg4ODGhwc1CuvvNLRZCjq2Rxpg0dGVrktGlqU6fVfanYbNsIorMNSXpIphi9pZJOJszlR+Z0NQhuhV1xxhSRp0aJFGk+M6iV92WWXSZL22msvSXH3oW7/loiK3SPrPsp8rlt/OCYQaYfbLeK/lKcrj4EZ4IyLRfsYaQZ7E+j2oguHpRh12t1RkT+PzW6riVAgo6Iax2809UmWOm9W33T0EPCaMUGlKRs7ukYjjfM2Xetu9tNtDNqI7p3oc1O+CO8RNi3wA5bKhH74+dp4zjHHwsuV9yAFOOyy5UPaY5hO3d0SiTokk04kEolJBhNTIwJTF4piOMuIWKKNGkoul2MYGBjQ4OCgXnjhhY7wGOWEGRKjkUWjqjTe/Bvj2lQS876jlsVRtrbBMuAmMDZOgag6Q5fEcKLKUkf1kt56660ldRaURxZwlM1coklhjOs21VyPNIbIMgZOPLt+fEz+W04Of7dq1aq2dXlsI1WCIqL1IldP07mp67tMBs3EDjLO8UyesKfGLCeSCmQXLwoXlMfJmCTjpVyHWd0RmuYTl4vW53pN7LTbz3VjaWL13S4/0u1GlRfRy8fXnQ9iNj+w67P8jQlXvCecCOR1b775ZknSIYccMuwxJBKTjWTSiUQiMUm48sorJVXGAZnhSJIfGQZijTWbFJlouJbYy2+66aZas2aNent79eyzz7YMVIrUGMykphHlRD5nhXv58jsvw0RNhqUYpiDDZu02jTSGRhz+iPTIo25bdaSPBrXPt0nGiSee2LHOaDCql7QzepkBzXR4n5iI1ZYshawvylg2RhIbLL/zxWFyBOXmvH/Weno9exPKcVHDmJObbiJPVN8s1C5uOkaCDL3J5VOXGxCJ5keZu+xVPB7YfvvtJVXXwjcWb2R2KIvGWjfuKB+A55DnLtp2NMejeHm37HSkXpVy+Sg7m/drtK/o3HB9xpwNumOjORTpKnBcfBjWeTn40Gf8m54U9rBOje/EdEMy6UQikZhguB+xDVAj6iDl70ulKyZ8MsbssjKTKH/vbdnYtdZ3qc61evVq9fb26tFHH+1Q27IxZCPLSbQUSTKYqf1P//RPrd/e9a53SaoInPXGSVBIjiKhJsam+ZcGZbQ9g2WzdcY8DW8fr8+Xxb0uv/xySdIJJ5ygsWBUL+ly4kidrgeeQB5wXfw5yp5tUt2KMkzrakFLxTFL3d1///1tn+fOnSup0on2pGF3rm5if4bPw69+9au2fT7xxBOSpF122UWStPPOO0uq3FUsC2jaT7dJEt2UeXAZutY4uTknRgPL6/k8+Iayi8zXyGOwyzDyXIymxjiqQY/mVZN6XNQHejSxZanZO1LOjejeiI4pGkPUbYxjitaLwAco48Usg4n01kuwvp0vtqiLmRm3O/ll/XRiuiCZdCKRSEwwGMKxgUI1r0gxS+rUk7Yx7+/NpJ3EaePH+zAozPTss8+qr69PAwMDWrNmTYtpmyk7lOXtm4GbmZu5uxe2t/v4449LkubPn9/a9xZbbCGpMqKcZPv000+3jc3L+VhpsDFz/YILHm/7/eyz39g2NjZ/cpjTXgEfS9R+tTTGo3g4Cd14EBdplC9p1kUzIYEt1QzW79ZpK0e1nZE+dZOqkksL/H+yAU8GT8x//dd/lST9z//8jyRp3rx5kqpM47rWZQY7LJn5Pfzww5KkBx98UFLl6rFbhMw5UhjrNns2YlvdZCJH7IfXh/HfiKGMBD7HZlKeHz7XvpF8Xnmto7hjuQznDR+KfBjU9T6v27cxXK12+T2z58kSWc/dxNjr2G4UQ+5WfzxiyFFsO0rG6bbSgsIRvjd9z/k5Q9dwOX+juDgTieiq9Bj9UHfXrERiqpFMOpFIJCYIy5cvl1QZoMxOpjwtRYRKRh0xNdY9+3eWrHGf5533iKQhg+XRR1/R4KB02WW/7iAbxx03tH+TCxtLNiQdnjLpcDKew3xlUqkNL7PyrbbaSpL0s5/9TFIVEjTDZc/qK64Y2neUJOsxfeELK1/9/slXP/9+2zniuWIStLfDpNRyLAzr+nrQsP7mN78pSfqTP/kTjQYjekk7tXzvvfduG5zdKR60B+uYoa1Tf/YJGq6PcV1MuQ4RO6wTaF+7dm1oOXuieQLeeuuttfs78sgjJVVyfr6IkvToo49Kkn7xi18Mu433v//9kiqW3hSDJmPhOWnK0jUi9leuH5V3RFnPZXnFaOGM2t12261tnx6Lz4/HYEZtz43B8zEck6YmORkty088hijzmOD+fGPbC7By5cq2Y/BY+fBinMq0ZYsAACAASURBVD2aG3XelijrOopNc551m+1NdLudJs9QlCjFl0DpPYhUyughiTLK/WzydbjkkkskSaeccsqwY00kJgrJpBOJRGKcsWTJEklVc5gytCd1JtUyOY5ZylJlKNqQ8DYYR2UZJZNdP/rR/7tt325C1NMzNE6GsK6+emhMRx7Zvl2zYm/H4Tz/TolWqTKebKTaGHI/bRuxzog+77zzJFUEb+bM9vPW22syUR/KiQxQn0sa617O5MteCnsRpE4GTUOPNd7OEbj00kslSSeffLJGghG9pDnR6E5hgoFPrL+n5FudJc2TSuZAltSUqeqYtDO7GevziXYctEnL92tf+5ok6b3vfa8kacstt2z9dtVVVw27rjFnzhxJ1URoypw2mmLVUWYxt0+U14FNzqlA5olI5lmX6NItnFFL8QUfD6UDmQthTw67ew3Xt5xutDoFuXJbLEeJqg98PpwQ41wHf3bJybe+9a229Q4++GBJ1b0SqXERUe1xuW40X6LubFEMm3+j5ZpqvSM9/mh5KukZfnCWLzLPBV5P//W2eO9Rx94Pcc/NRGKqkEw6kUgkxhk29snIWL9LJS2GR2yIShWDtiEXSdlGocKPf/zetuWNoeV7JA2RGf4+c+bQdjfbbMhwcdzYRtL+++/ftrzDomUPZsPGk7fhMZvY+Xx97nOfk1SFfS6/fCgsVNU52zBsCp20C+Aw5uzvKQ9sI83bLa9DZMg3tcMdbTOXEb2ko36vHqTjuz7hvkhkQnVgrNAWMWXcfPKibQ+nTFb+ZqbIRI1SB7gbjIRBHnrooZI6mR7ZWlQXHTEVJjI4zslWaj42dpeq65xk1sLECTJP9mMeCb70pS9Jkvbcc8+246NAAcshyLQYd6yLE3er3EVvQ3TO+dljfuyxxyRJ9913n6SKOf/oRz8adv8Gk4O6zTfo5vememjma5B5Mz+hKYu7KeZMjJRRUz2wBMfKXAtvI+rINdrnQSIx3kgmnUgkEqPEvvvuW/u9wxs0DhjGi8IYdSEJGm6R8A7h5f7rv4bYa6cdN6jnnx/K9P7JT5ZU3w5Wv0vSmWcO/d1226H9u0ztxhtvrN2v4YTacp0IjzwyNA4aZD5/Dz30AtYwkx52szr++M3atktEpZdGyZ6jEGzUOIZ11RdddFHH/u+6665w7CN6SZPtGrY2HSC3dWowwF43mShdZ3eIP1MOzttgDI8orfGBgYGOi2BW6RPpY1i4cKGkatJ4ObNdK5KV2bcHHXSQpIrB/sM//IMkab/99pNUJVp4rLbemb1MRhjFAA12qjKT9l8fs70T9nRQMKDcp/+ScTBG3Y1edgTWiRvsNGaw0Tu1nLvRdCaz4jq8AZuUqnyePNamzP4I1CFnk4Nov8Mp9I2021WU48As7aZ6foNsNho7v28aNzuw1R2T7wXGsSnkwUoTuzWpjjjeTRMSiW6RTDqRSCRGCTIgl2ztvvvukiqD2Iao2RTLVqNwUala5ZgmY9JNpXI21hct+l7t8oOD0ooVzkb/SBgy+au/GpIvdjLkRDQhcVa8j9WJuZ/85H++Or6h5ZqSDw0bW1dd9UeSOmPTBgmQjWWTRIexpM7sdUpGk3S55tvE00JZRx99dHAW2jGilzTrEpnI4MFGNadUGitPrJmIT4otWm+DbJJjIcMrL4Kzu0uQJTADnfWSFI33JCoZlo/bccjDDjtMUsVYqajFftxGpOrFpIeoXzQTGDw5uD0vV/aC9jK+DkbZ1q5uX6Nh0t4WhQQYa+R4ef54UwxXNUAvBb07Tck3kXKZz5dvyJHCx0T5QiKqde8mDs+ckmi5bvXLo/KWbnT0h/vdaIrHs5ymPEafxygDPVImi5T06O1JJCYLyaQTiURinOBsZMZSGZsmSWACJo3I8v9NxpBhouOa5NNOGyon+9znftG2vaakSCaTUu45wvnnny+p3eizEXzGGWfUrsMmK17+nHN+W1J1jGefvWLYfXu5888fEt6KyviaDMO69Siuw/PivyR2lLvtFiN6SZspeqdmMh4UM6XZQJsunfKEeEI5lsQ2aEyZ5wRjPWSdprSL9qVORkVr3oza7NfuKY/Pn0tmSbZpUX2WF0QZ6VH9KuPwETNhvI3C7z7H7C5VsgSfP7vI6DXxsnS51WXYRnB8781vfrOkTtEFlm54TGarvDnoUaiLkUZZ6FHtb+R5oVfD2/X5Kmt2u4GbD7C9oNHUg7kpI7pExGSNKBciKhNqqo+OGHm3jLuJadd9z4cwvTO+Xr6PI3U05o34Hk4kJhvJpBOJRGKcwOYwDE1F/YpJbGw81PWTphFPw5F9o5lE9xd/MVeSdM45DxbbGFRPj40ZZykP7eezn91LUmXU2+C55pprJFWGjcNqNNhLY81GspXEbJz6OG38R0JMPk+f/vSb2pajypqXe/LJJ9vO2TbbbCOpIh00HOnpsNFc6o972ySOPgaWkpJJ19WPD4cRvaStX/v973+/bRBmaIwTMwOYMnalK4fqQeykRak1xjHJ2suLNzg4WEjf1SccMGYZ9br1/t1arSxy9zH4Itj6ZjZylOjBm48N4clkGPNn3bXPpSck2SQl8cp1eD59PSKFpqb63RJOBmG9K9mL9+F9R+pbkUpd3XHx5m/S4iZ7Y/Y39+XtuzSHzNjL+Rjt+rL3pSnDv0m9q/y9ScOdrlWfo8hTwwcZX0RRbDrq1NWUuR6Nm6jLh/A2/GKhEhnnnL1NzPq352is0o6JxGiRTDqRSCTGCQzHkVRQljjqWGUjo2TSTLhl8qKZrPs4cxtlMyBJOv/8LVrbOeOMTTQ4OKhPf/pNHcYyhYvMRm24+NjMWn/6059Kkr73ve91nJ+3v/3tkqoGRW5s5PNmL8Avf/lLSZXhSPYZtYSNejmT5TuMyd7bNFDrEmYpMcuwG0NqNGp9rFdccYUkadGiRRoOo3pJm0WSZTJDkpnZPgFmnCVz9MUwM/WJ8MmO9IcjlamSGQ8ODrYUx7rtdUvW75uLbNR11FKn64YKYlFGMRFlIkdjjJgMvQ/RuSwZJ9m7P0fxcKqcdQPrITO7nX/9O2/QSNSBWeEW65eqm97HSl35KPM58m50q39NFS8/KP1w8Dj8fdP+m+Kz3YDu0ciLRFCsgXOEzJpMvKmbW3SMTWU2dcfusflZ44c/8zt83vlQptfA8yazvBOTjWTSiUQiMc6gARx1rKIsaSQIU/6fRosNkieeeEJSZZhQ7IXGT2mIOBQ4e/bsDsPEho1JiDPY2TCJYbU6Jr311ltL6qwjNxh2MCH0GPw7CaARhcJM+rw9Xw9vj16GqIWpVOqH14eayLBJJrzNbiVnR/WSNivx5GDPW8Y86Xqos4wpvM5JS2bNfRnDZYqWy3LCRxmqDP5zQjrWJXVOMErNRTcZY4IRIm8B/5KBc/8+l9RJL9dl/2NmvRtmKK4NHw4WenjnO98pqZOVcJz0YjDphsfrG7duTC5D4blhfgTzKqJ90A3m80K3nZf3A84qa45Fs1E8b/SmMpsmllkiuleIqP7ZiLwF0dh8jqNjGumxNJUMlfukYh5Lo3zPRt4vjonPukRiopFMOpFIJMYI6zHvuuuukjrLUQ0bNkyIpUE6nCAPjRuWlUWGRERgSiNscHCwtT0TJ2/PhiaFYBiCNDt+97vfLUm68847W8vaqKXyF40hG1X+6zBolJTIY4zKU30sVHwjO+Z+ynMUJXEytBUJ6NBAbMKoXtLU6mZCgwfLxuVmF4zrSXGiQGTRGrzIvGj9/f1tvzE7N2JpkcLZcDFDXjxmEpMpMlWfLhzGmqM6YDIbPiB4Dhn/L+GxsJMW49tRosVwiDqXkb2zNp5sJ6pZjhq4S53eDd+kVMHjNuiujOaf74VddhmSTqSXwIkqfDj7IdRNr+9yf1G8ti6eHMWYOdcjBbsoZhz9jbY/0i5ZkRJaU0y7PBZ2TqOnwqD+Pe8l5tskEpOFZNKJRCIxRrBGlrFQGpJkcIxND4coTBG1cuV6jI8zJMhYtGPQZOg0WHyMbHPrjG6pInhRaSeNfi9v44mCTFyPpXUEjeeI+EShnrp1acBFZIEGdrehk3gEiUQikUgkphSjYtKOTTj2QHe3LQzGNmwFsSuIVFlUttpsKUX+/EjWs06soqenp1WGFbnYmKxE9yZdynVlPqy5oyu9STEo0pFl+VfkBqRFZ0uYFh6vQ2ldMkbmbExbxRTn8Pdl8lkErktWYWuZgh88D1HiEbMmy/257CvSRqZFHo2NiWWeB97XjjvuKKkSbKECkkM+LEP0PRUhcm8P5zJuEgXhulECaMQyjEikhPHAiJ10I/c5HOqWi5Iy6b5mOMPfM4ZJkaVEYrKQ7u5EIpEYI+iuZrUAq0TYa8CgkVyHqEzLhp6NcOayRA06mDi2atWqtrHZUGeOTKmvUG7Py1n0pDSWTWQ4Np+fSNXORpKJHclDlEDGHASqGdKA5LmqMxhZcUQhGl7zppyNJozqJU3NUicE8YA9+EjkoGTSHjC1b70s4y1RIg9La8qTXC5LVkrLOZqIlBssmTRvOLJzxoDIyiKGzbpFJoKRFURSlfRo+HPZlMDeET50WGLECdpNfIXekSgBKJKdbGrfyHKqMr4XeVyIqJzNx0n1JcbWmAnr9V0Oxvnre8CiKmSlUdlZJCxSHhfPc+SBISg/G/U6jrbjc8TEwOjFE2XkRuiGaXNO0LvHuKv/UjbU67MPdCIxWUgmnUgkEmMEhSsYNosMaQpckPCU4DZoiDjM0yQ1SrGNvr4+zZgxQwMDA9pkk01ajTlskNioJ7ukpj5DDJQPlTpDdwZL06gbwFAYVRRpUDL0QrnQSMqT56iuMoGkh2PjNTciXf4mjOolzYnGQZA5kmX54pYqLj5QMgfqnZLZeNuRdW1ZUC9DJkVGzjFHcTkzaMd1peqiRXWIZEm06in6EMWqI9dOpBkbyYB6wjoPQKoYoN1IbEfKWG0Up6xD1AGIAhKUBY2ySptkLcsxRW0TOabIlUiPQiShGa3Pek/D85jNUJoYf/QQKR8mkehHU0nfSCRG67Zj1JXC1a3XJE4ykng8H7I+n+wqxRgzyxb9gvL97fv9Ix/5SO2xJBIThWTSiUQiMUY01YiTPZEkROyqNHCYiBsZkEZdyK9crww/Whp00003bSU9WruiDOmV60dxX5ZileG06Pgi49ZGEsvBrNhHI4wdGb0dhtro+aCxTNJWGoQMnbCDIxN1SUpGWnM/qpc0B8U2cGwmEAlglFY/GXJUL9jUBIATs5wUg4OD4c1CFsF4KU8sY1fl/8nsyPajxAIy54jRcMy84TkxGdena61UvnGmN9WFfM193BRKaZI0LccZHYfB2DLPR5SZy0zqckyRi5C9YJkLwdhldGNRmIaeHp9Xb88PPh+7s77Z1pQCL8xGN+rYZeSBaWK2nOtRJQXXixSYIsYeyYSOJpPd4LJRD98m17Gvl8dUeswSiclEMulEIpEYI6gWGKmsRYy7ySCVKoPNbJEJvIYN6aipR10vdSfW9vf3d4S6bFDakHTsmwmGUciojoWS1fN7b8NNQ6jsZ6OLZI7xeJanUnufxjhLIymaUo61iSww/MjE6qaEzNZ6XS0FRG3fONE8GGeu+uJTkUaqLFXGsfw5qmNm8oJRMp+BgQH19PRozZo1IUtlbLqpdpPMS4rjiVEMuokpk4nw4kcsIIq3MmeATQXKY/Ayvi50I5GtenIPB8ax6x5E5fijTGvvy2Mja62TyGSdLPVz/T3nKMfkbXp7vNGiLGy2xjT8APQx2cUYzSWPi9nHdZKerAIwOJ8iZhwlwDTJgXI+8uHdVFfdFBMfTgK1rqxI6tQs4AOWTWc4R7vJuUgkJgLJpBOJRGKMoAFqMEubRh3jtlH/A6mz7DHKaGbziChR00b6xhtv3EqqXbNmTcswscv/ySeflCTdf//9kip9+ojQDFf/G4U2GLv/+c9/3vaX5IHr8bz7nNir4L8GGTjj/d6uz0FdiWkTkYsSIKOSyAijekm7+YJrPFnbzIJ8nwC7Dswqygnok0PGY/jieV+RkpO37X2vXr26xaRffPHFRtUv3kS8+PQClBfb39FaZwKBEcUMedMxI9UlEszO9jH7Jo0abzDjuPRo+PiY3Urm6M9mgt24brxspNfL82Cw5MOs3mP0cbEEpQTrYP058lLw4RoxK56PiJVSUc9j9RzwefZf32NMdDET5z1WF6/l+WLZidm7x+h5QJ3kKBucf5kL4fnVlDkfMXUy/agZTonIq+e/TDTyNqMymtFmvCcS44Vk0olEIjFG0JglGWAiG9W5omzjUjyFBgNd9GThTDokvM+XXnqprRd71F7zoYceklQZb3vssUfbMUQJgaVxFmWGe9lHH31UkvSf//mfbb+bnHlsjB37e3bvY/iU3fCYqU2jm41QSkSJjQwr8thpADZhVC/p8uKWOyvdJ+Wg2AvUbKBky/6/WaInvZelnBtVqfzZilkle+zp6dH99/9ap5zyT8VRDJ3QL37xnW3b5Ymja4lWfHkhODnJyiLGGNWds3E9yxLoweA54fY94czi6uKkHjPrwJnVzUnv8z4cTjjhBEnS3XffLamTGTFGyYxpsmDmI/Ca1KlvkaXRTUmPQBR35fLRg43b80OEymT+7N+pr25Pke8tyyJS/KJMcOF58QPfy5xxxj2SpPvv/3XbueC1bnLjsaWoXYQUmohauTLOTxENg9v1dkqPHGP1frhSJIOVDh4727gy/yGRmGwkk04kEokx4vTTT5ckfetb35LUyZgNJvpFhqUNpZJJR3rWUdIje2PTcCwZ3dq1a9XT06Pnn3++Q+DF8GdL3HpsNtAZaqhLTGTog96Bp59+WlJlJPmYvK0oaZRGVZSMyr9RGIsGaxkS5LWLynVp3DL8yTh5hFG9pF1IztpP1sryRHiQZnBl5x9qI5s5UIWKjIZlCN7nokXfkyStWbNW99//aw0ODo2DF+PDH75TkrR06R+27cf798WPYn/lZ7qZ+Nfni8zGf//iL/697fdIsczHcPnl+7bt1+CNwA5OvqnqYrjOLmaM1Ov6fNNb0q1YvFR5SzwO1pGzBpgZuHRh8drXeTkYw41yD5q6HPE4+dDlmMm0Ob99rJ4bvhZk3IZLUvzX69WVinhM9pScffaK2mPxeV+48DttY/7c536nbTs8hxFLjbK36ZXguYjyHyI5Sro+y+8MCn2QjXusnGPscnfyyScrkZgKJJNOJBKJcYJf7jYGaNxHDNKgWFJJfLwNCg0xRGejjGWSDNmVGeSlQc9wBzOraVR5PGSMNp5Kw8nEgMYuE4B9/ry8wXAEQ19MSo3KT6MQJMs960pMzaoZjmRYh+SJTLrbZi2jekn7orGWk1mhHhRrUf19KbxuVsUUeJYo0IXAGOPxx/+DpPImGNDQIoMaGBiU5IvQHq899tjvSpK+9KV3S6pOoN0vPlZmDpfMxdtiHJcTzhPx4YcfbhsrmUPEQPz9hz98lyTp8svf9eoxrW1bn8krPgaPxzdz6Xbh2NmdjIkuVMbqBk4Oce9ltveLmDTrdqMEjeE6QkXLRkp2kdhEk2gFHxJ8mJgpe7+e/2al9lYx38B/H3/88bbfnTVePhjssaCmvFHdI2obm8d6xhn/Kkm64ILfazv2qJsVqxgi9yddlszSjzK0mSBVp23PPAa6P+lqJJNm1cIDDzxQe6yJxGQhmXQikUiME/jyZ+ZzJDBj0FgsjS4bGDZqzWApjmQj3OtSiIik4KWXXlJPT4/Wrl2r559/viNW6v3YyHdIzH2nbeyzPNbZ4GXS3bx58yRVhMXLOnxjA3Dbbbdt+2yjlrXfZMRRW2DK87Jhk8HwEglouU0byD4vVC+LMsjr8g2Gw6he0kxgiGqOIyu2bqKaOZhd82Sz+JwW8wkn3NW27/qyg+q7vj5b+0OfffHvvffetu14IvrimrF47GVmtE++1zGTsWC992FxAB/DkiVPtH3uGPWrw47k9ng+2eDcYzeYEeybrjwGnz8qqzE7luzpwgsvlCSddtpptcciVfE9JtlE88kgq+X3kXpUeVzMNeA2GRenezLS7mZCCpkvz1eko01G7fkVMXnW/5bnjvON7jgi0u42q/S8ibwJEcNmOREfuHTDMgbOKoC6THaDLz8+GPmZcW6PzV6uU045pfaYEonJQjLpRCKRGCdEMsY0ymgcRuWYJdlg2aDhbdjQoGiUPzNsVBoqPT09Ghwc1MDAQOt3ih2xYZLJiA0aG5g+NhuH5XhXrlzZtm8LYnls2223Xdu+fB5MFqggRuEcCvZQg9tGr7+3sR6VE/tYy3BeFN9mp60om97H1G3b0zH1kzbK9PRycFFGdl2hvieULzS3GQnVNzGToeUGO9aLhO5tSXdrQV988cWt/x911FHDLvuFL3xBUnUxd9hhB0nSpz/9JknSX/3V/zfs+tWQB9s++xwwXu5zyM5ePsdMUpE6lZjIcpkQY1eW1xuOQRMHHXSQJOnOO4cy7O2lIAuNJAR93L7RokSZEt4mlekY/49YO11X/L7uAVjuhzdupHttjxIfQgQfWiWTtJuyYrjtLQeJykM2tM/Vq4e26ZIbPpT4IOQ58Dny9WGyj0HmHGWLG3zYlQ9Q1lr7JcCaa9ZYn3TSSZ0nJJGYBhj2Jb3vvvvWfm8Lim4nugQjRZU6EfyofIPrEF7uv/5r6Gbs9HIP6vnnH5EkrVhxYfVtxwtv6O+FFw7t/4YbbqjdH+EkKEm68cYbh132kUeGxsGkOJ+/hx56AWvYhTr8GI499oq27RJ0h9MtWT7konKuKJmHjQrKZMBu4QdppNIU1TJGLRAjQ6zcZrftD5vmHdHUdCL6PrLOIwGQblSLeI0efPCFV79vX+7554fm8L//+5JX99Vu8J57bvtLM8qcjbSMm54Lkfu8qdlN3bnmvprOk79fvnx5x2977bWXlixZUrteBEqt0tjj51K+uFyfilnlugblUlk3TaPH+6wTA/K/GTNmdMRaachSwMjbd5Ktt282WhIu3+sOodhYtoHukAoN88gbwHCcx+zlSTaYI8CyTo+d92E5f9goieEYGuC8D2jgN2FUTJqqPnyAG9EDjhegRFQTTDSVMnSPoTG84Q1DF7fb9mGG2fBIMFxMrR2+yD1tn6OXd5NMXcREy3MXrcuHTDcvxG7hm93GX1R7zWvOMQxXw07jIkK3xmFTU4HIcBjp75FwAudO3Xb4oogPfXjDgfuIDAcaIk1zpMlgipTJGDsv71n/fzT3ZSIxHTHsS/quu+6q/d6M0fEDP2T94GBiiMGbrnTPvu51r5PU2covutFtAdki+7M/u7vt9wo9WrFiyBp+85tPK8bQvtwnPznU2cVJVAsWLKg99rHAVrnPm1mnH3p2d0cPr0ie8ZJL/i9Jnc0X+EJlXZ9d1Y4TSbEVzvgUxR6cJDd//vzuTwhw++23S6qsae+b15wu3qj0p5xfdNMbnFfMlCV7pBAHY1gG3d5Rr1lvz8fqY/e1JFsxmIRVp7TEF/r/+l//76v7HPrd78Sf/GRoXr7lLae3HZPH+Gd/1p7USVc8zxET+CIRGpYKkv2wvI9MkS7t8v9TlfDlpMh//Md/lNQ5j3hvcm6TpZVGY+Rp4n3OJDkaNdxH2fmqp6en47pG5a/+azbs3x1aoBJZ+ZuvpZNqOVeZvOjvGZuOmhZFTDhiuZHhx/Afz1u5j4g5857vVmnMGFM/ae7cD3K7LqIkCL40pM6gezQB+RKuJqLalqsmUvvYq4k29NnxYKpXTQSoAEWlLcJf2/1Yjd2sqn15PuyaanlZliB1xreZNBK5Lkc68epwwAEHtH12yIHzh6pnzFavUw9jSQwfkgwJRH2i+RCI1M84b1lX7pcqVecid63jy75WzNg3yjwPPqTPP39vSdLHPvb/vLqvevZuTw3V0Lxtxsejl2mTy5nH6jlEVy8NwcWLF9ceeyKxPiKzuxOJRGKcYYOG2cRR2CWKw5feoKg9KRP0/DnKFWDCnZl0T0+P+vr6OkSqaBzTkGVCqpl1XTiPxj7zTqjW5X0wrs7ffSw8NzYYWS/N7fEcMX5cXgca+FHMmd4Aj9Xer24xqpc00+aptUtFsijWVDK7KIs2ckfS2j733N+WVLr0OtmpJ2I5JtbYjjSoPxJEmsaeWOec89tty1NrOfIO8OaNGDSZtG8Yd1Qqx8YMa8rk0YtitjOe8I3hG9CuLkoLkqXyxpRikQkmlnhfUQIjNQKMiGkzqTJKaKEb0Dcy56X/2ntgllun1kYlL/+1gpgVxYje3qFjOOecvSRVYRFfY4+NJTeRdn00Z5gFTsbt77NWObEhI5l0IpFIjDPsmmf8PkoWjbL2y5Ag49relgkLeyAzg5zMu2R8JjD9/f2tsbIjVCQqw0xr5m+UiOLnkQQs657JbMmkIwlZb5/Z35FwDvXHy/AXDfQoREUS67/HHXdcx3kZDqN6SbsW9tZbb5VUHXC3cUkqYpXfRXrVrMF0XJyxvL/+690kVUlYg4ODr647VKz/mc/s2ba8WYFZgi/ApZdeKml8u9+Y/VCmj4lS/v5//+//o219H5O7E5GVGZEbJor3l+tzHap38a9/P/roo7s4AyOD5xN7KDfVNlM1TOr0wPAc+brzQcOeytx21IecjJu61EziYzN6z0u27iM7tTvVXhEr95XbJqP2Puy5OfjgtqF3PNhYHukx+VywnSBjyCOpnU8kEu1IJp1IJBLjjIULF0qS7rjjDkmdilg0MOvixFK7AR2Fd/h7VG8eMb4yBNjb29thvFP4hVLN7HY1XPlsFPr0ttg8x2MotbOlzioTslfuO+pYRUOURrAN3DKhOGqARAITNdUZKcb0krZFbWueiQsR+/LBlUXuZgBmlQZrJH2CqGnsfVe9mee2tnH22bPU19enT31q99bFZ7Nwx9mZ6HHRRRdJ6l7CrQ4uvfK26f6YM2eOpM7YssdYiUq8RVKn7B9745INTy5iNAAAF7pJREFUMy5KbwRvACmuXeUkLstfxhuOhbo8LxLT4GfqM5fLMD7K+cBs7EigIKoh5v6irmlk1GT03p4bD7g00NfM94uPkU0OpE5ZSK/Lcp+5c4deIJ///P/ZNibG9j3PvB2PjW7XZM6JxPghmXQikUhMEGzQOMmORl63DVukzhCLQdZJNmpEbVn7+vpaimP9/f0tI45lmOxx7e/tJTBBooZAacAyoZKNYbhvlvNRLppxcZZSRloTFORiTJosuAydcR9RrTvrokdLaMb0knYA/JZbbpHUeaLpgmBhejlBfXLICslwKIDgk8yM8lL4oL+/Xz09Pdp000076lq9H8b2nDXr7SxdurTtmJhEUf7GsbpgP2IonMw+BzwXbDbe1H+Xn719M1THDEsmzQcBHwjUy/7FL36hiYLHFSW80J3HOVSyWGpb80HG79nwnjroUdyf156yhgTV3+gq87jpyXHOhK+l51jpPeCcdq01O4DxQcWHOJm0GTrFZTz2888/X1LF6k888cTaY08kEs1IJp1IJBITBBvCTnpkJykjkrgtmXRU9xz93qSmZZhJ9/b2aubMmR2GKkkCw3U2ZG0U2mir8xJEhqHX8edIo5sEL6pvjrwJXI4GfpMOd/n/6LzSY+HzOFoRnnF5Sb/vfe+TJN18882SYnUqsovyBPOA/Zn10J4QPnC7EMh8PGEsGj84OKiZM2d2bM/7Mzvw+p40pWpVeUyMr5e/8Ubzhafko1kQ2T1dO5THdAKCGRHbqjEGzYkdnYPyuMhW6dlwY5FTTz1VEwXXx373u9+V1HnuyZwNxnelzmbvPndRj+WIpTf1Yo6+j/SrPUZnRFOqNcqFcNWBO6vRPSdV15DzyA9Ifx+przHO7rGakVMpzGPw9nwv+blwyCGH1B5LIpGIkUw6kUgkJgjHH3+8pMrQtOHCzGka6EYda2Y2ccS+mekcJfCWIbve3t5Qp54SwawDbjo2b1+qDD4SOMZ1WWYaiU6xbjoKQxlReSqzwOsaLvF8Rp4L1pmPFuP6knZ80g0kyPCifrTlMszQZX1opEzGZIVyuwMDAxoYGNALL7wQFr97Mvizt2dmEyUFlOOJWu75r9mcmbS3wfZ0Pi9OxGBcnueENbac+Lwh6Cqqi6tzWR+3O1U19c4eT7DJB9v6kTHW3WBcxmyQiSnMeYhq0ImmDk58kFIhjP25u1VwO+OMMyRVFQTlOHxM9uCwJptxeJ4Ljj3y1ERJN1E5TCKR6B7JpBOJRGKC8eSTT0qqDPTIUKK0b51CGVkkM8aZWBo1OKkLwQwODnaITbHrHLtkcTtk1MNld5Nw+DwwNOPfbZhHtdxRFjfPQZQcyVg5SyTLbbFu3KCBbsN7tBjXl7Tjk8uWLZNUTciovrXMeGV9KF0pniA+IWalUW1xWWBv2bvVq1e3vvfkIHMigz/ppJNGdzIKXHjhhZKqyev4N8sHfDE5MSKtY4+dmcMRw65LGCl/r9u39+VSkiOOOKLr4x4v+HjMfqkORi9KndeF55BZ/E2xZrLBzm5r9Uyaf/kQ4fKe72bI3eL000/v+O6KK65o26bPl+dh1DWMY2Z8nu5QPqS8Pc+ZRYsWjehYEolEhWTSiUQiMcFweMg90w0ah8xiLn+PQnWRwpjRFHIpjbLSkLfxRdlnht+iXup1mdFNIkDeFtufkkEzmdaIwkwR0WG3MYZuGMIpx8SkUiY9eznnJYwWE/KSZu0mXRMskpc6rfoo6cHWOXsKk3mXWs1r167VwMCAVq1a1YrzMjOa7qWxuihKWIHpK1/5Stsx+tg8JorD2xPBeDlvHp9H1q362Oge401dxl2ZaOF1RytpNx5gswIyaXoMhqseMKISD6LbhJPodyPKU+D5Hc95Zwbreedt+3pTc9u/R3H5yFtg0JWZSCTGjmTSiUQiMUmwlCqznJnFXNdJKsrOjtqiRpnjXG/GjBnq6elpMWlmmJMUUFo3qouuy1hvEiKKwp1k0JFiG4+dJI+hMMbxo1a2ZWlj1HGLIUJL+Y4VE/KSdhz3hhtukNTZpo2JB1LnAUaZoRQrd5ySmtulxvTg4KDWrl2rF154oTWh7D5hRrAvcl2Mb6yI4phkdVFvYta7UuecHcHIMCM1sTqXmtexx8ENA6YCjoP/8z//s6TOB5y9KcxIL0EGywQRgwzYIIskW+R6dEVG8oT2DDmbeyJYqLUEnAvhe4B18r5n2KqQ84fgA5H67olEYvRIJp1IJBKThGOOOUaSdOONN0rqTFyk4NNwYAyUGc1EVE9d/u3v7+9QFCNZMCLBp7qEVILEhCyfRIMhPxrkJHNRQqf3S+8Dk3EZqy5j9Ww1TGlfk6Xxat87oS/pxx57TFJn7LCOwUWNwnmRqAvOhuTM0u7t7W1J3vX393fEf81GzVK7rU8dDTiZvW9K43GCMkZIDW8yI55fZnWzbKHOlePz+vjjj4/8QCcILmOZO3eupM6yCiqQkSVLccZyxKCJiBHzd4LuNj7gzHJ9rV0hMR716PYKXXXVVZI6NQnq6uVL0G0aac57zvgeGs9e7InEhopk0olEIjHJcLguCocYdaWBNKYYqzaiEMxwv5eGLUWDSA7MMh2yceLhcPrZkTiQDWt2uaIB2RQO9b6Y2Bl1BGOWd1SnTi+C1Klt7vM1XrFoY0Jf0tYdvuyyyyRVfZNZEyp11jtHDc5Zx8saT07YgYGBNjcP9+OMYbsw3vve947xqGO4G5Bj9TvssIOkKq4exaQjFTDelFSUMpjxbrC8QapcNdbmHq0o/ETA2s8/+MEPJHX2aqayWtkRigklPFcUJoi6VlGEInqo+q/PrW9czzPD8XSPx5rdE6Ho5nPAGD5/r5NClGK3qo/R/eXHQ1sgkUgMIZl0IpFITDKOPfZYSdL1118vqTPR0CiZJ+OlXJZZ31HcluGKV155RYODg+rp6dHatWtbBiMZIstWvZyTdr09G/osq5WqUIi3scUWW0jqZNAmEJFmN48lAhlxU49tIwq/lt/ZOGXYcLyTbCflJc1+st/4xjckVXE4Kdb3bmrLFrUFMzbaaKOOrjwl9t9//xEcyfjgsMMOa/v8tre9TZL01a9+VVJnP2kW9pNhM8ZIN5XBm9Pbs7tKkh555BFJ0oc//OHRHt6E48EHH5Qk7bHHHpI6Fe0Y/5WqG4kJKEwCoZvM55IdxRj3ppuN59iuQF8T1vf7+9E2hu8GzGj3g5EPsEj4wSCD9vxJBp1IjD+SSScSicQUwSEZallH4ZRyWcZrGa6IwhmMRZessU5xLDL+SRKcqU6U+7Nx66RZG81s8sIM8ah1btRWlYZnpM4WNWzidsvzwjGx8dF4o16wOJFIJBKJxJRjSpj0Bz7wgY7vrrnmGkmVNcakIIPlSIy/0B350ksvtWItzz777KS2WBwpXFfnxgg+ls0337xtOZbvMM5CkYqovtFym+taAwTXmn7rW9+SJG2//faS6hPGDAro0JXL0ixa1JHFbjCGRWvb89rfO7vXv9vNfcIJJwx/8GOAz5vh8ApL/nz+HD80u3EiaGL84PilQ4BU8arL7o7anRKRNC3Z4YwZM1ox6Z6enrBRjZ+pZL0eq5/JDmPW3Sscq1l59KxiS2Ay6Og+pnchqg0nOOa65FqK9Hid4447rnabY0Uy6UQikUgkpimmTUz6Qx/60IiWv/TSSyVVlpett2233VZSZe088MADevHFF7X99ttPaxZdgsz22muvlSS9/vWvl1RZdRaLoTXphh7rOw466CBJ0ne/+11J1RyoaxzC+kyW7EXtFll2FDUgicrjmHDmTFjv/6GHHpIknXLKKd0e9rjBnpsrr7xSUlV2N5FsPlEPZ0S7JNTzpy7OGcVZmxqgcE4yu9vyyRRR4tz2705+ZKw6qjkux+BESi/rbTG5lQyaNdiRpyuqk46yvSOtbx9TyaSpjjaRyZ5SMulEIpFIJKYtegbrCsHWM+y7776SpLvuumtKx5GYWHznO9+RVLVILeNfjFWxc49j1hQxoVRrXQeh8nta8lEnIgt/HHjggaM82vFD3h/TB2xKVGZos6EMBXnIfOlho+RvGXM+++yz1dfXp/POO69Dxjlqx2qwURBLRcvlXa7nbbIxkkGGyzg6tb8jBm0PGnNSKJJFzxhLI8tyTi9rBj1RsWgjmXQikUgkEtMU0yYmnUiMFfPnz5dUZX2bUUudWaWMK0W9eJmtHYmWGBGTZub5U089NapjTKzfsNDRrbfeKql93lKwidnd9Pbw+6i9quPRAwMDbZnLZOoRs+ZcJwsua4w9BgvpMI5OZssqCYpVGWxBy/7c9DZEDDrSQS+P2d6AiWbQrX1Pyl4SiUQikUiMGMmkE+sdnPXtOmCpau7CLFLWN7PRBpkw2QK/J5P2787SdQY1a5YTiRJu9GOvkNQ55xj7ZX4EvUH+vq4TVW9vb4tNe67yXojyMDweM0xnqtf1eqaeNxk17zfGoFnTzxbFUbvablXZoq5kpYdhsquEkkknEolEIjFNkUw6sd7CdcAlrrvuOknS6173OkmVEhjrnY2oB29Un+nt2PK2apdbUJ566qmjPp5EIrHhIV/SiQ0KH/zgByUNvUTvvvvuKR5NIjE8LPohVX3no252LD8y6Ob239L129fXp4GBAc2aNavDtUz5T7qk+Tu7ppWGrv/vZe3uppuZSXGUg6a720luLLWKZEYZIuDvPqf+WydlPVnIl3Rig8RGG22kP/zDP9RVV10lSdpqq60kVQ8NtqAkc3bczjex43B+qB5//PETfgyJRGL9x5S8pO+880595CMf0S9+8Qv19fVpn3320SWXXKIddthhKoaTWEfxd3/3dzr33HO1YsUKzZo1SwcffLAuuOCClkDCRz/6Ud1yyy1auXKldthhB5111lm1LvBEYrrCnh+pEjpxm0ejSfKSLJUlU/39/a1lZs2a1WKXkWBIJMHp9Zy05VBSyaSdXEbGyiYeFBdiQyXu08a1GXRUJmZEDJpJeY8//rimGlPykt5jjz30ne98R9tvv71Wr16tv/zLv9RJJ53Uqg1MJLrBr3/9a33iE5/QPvvso9WrV2vBggX62Mc+pssuu0zS0EPitttu06677qp77rlHBxxwgObNm6e3v/3trW0ce+yxUzX8RCKRaETjS/q8887Tj3/8Y914442t70499VT19fVpyZIlo9rpNtts0/a5r69PDzzwwKi2lVg38N///d/6vd/7PX3ve9/T7/7u7+qxxx7TW97yFt1www0tWcqRYsGCBa3/b7zxxlq8eLE++clPtr771Kc+1fr/W9/6Vr3zne/Uj370o7aXdCKxrsBCJzfddJOkqpyQIiURoybKcsKenh719vZq5syZHdtjqVWd3Ge5H7NeM+lyOZZAMV7uY4rESLytSNCF+2GYKmqsEYkNnXjiiZpqNJZgHXXUUbr99ttbOqVr1qzR8uXL9aEPfUgnn3yyNt9889p/b3nLW4bd7s9//nNtvvnmmj17ts4//3x9/OMfH58jSkxL7LzzzvrsZz+rI488Ui+88IKOPfZYLVy4UPvuu++Y5lGJH/zgB3rTm95U+9uLL76oe+65J/w9kUgkpiMamfR2222nffbZR9/4xje0ePFi3X777dpqq6209957a++99261jBwp5syZo1/96ldatWqVvvzlL2v33Xcf1Xa6wV577TVh2050j8WLF+u2227TW9/6VvX09LTCG5deeumo55Fxxx136Oqrr9a//Mu/1P5+4oknas8992xJhyYq5P2xbuHQQw+VFMeoI0SCIZYFJSgAwu0wE5twc4pSYtP/9zqOITumTCYdNdqIfo8abvDYWTJpBv3MM89Iml5iQ12JmRxzzDFatmyZJGnZsmUj6v38wx/+UJtssok22WSTWhazxRZb6JhjjtH73ve+Dr3U8cKSJUtG7ZpPjC8WL16sFStW6NRTT+3oODUchptHP/7xj7VgwQLdcMMN2nXXXTvW/djHPqYVK1bo61//ekfdcyLvj0RiOqOrVpUvvfSStttuO/3whz/UH/zBH+inP/2p5syZoxNPPLH18iZ22mkn/cd//EdXg3jkkUe044476plnntEWW2wxsiNIrDN47rnntOeee+rd7363vv3tb+snP/mJtthiizHNo3vvvVfz58/XFVdcoYMPPrjj909+8pO68cYb9f3vf7+t4UYisb7g2muvlSRtvvnmkjprhVlOaLi+ee3atTr99NMlSRdeeGGYvU15UX9mFjhrjMtXjNclc3b8mrFog3K8zM6OjG++3lj77VLKJ554QpJ0+OGH125nKtEVk541a5YOO+wwLViwQL//+7/f0kG+7LLL9Nxzz9X+G+7BetNNN+lnP/uZBgYG9NRTT+nMM8/U7/zO7+QLej3Haaedpr333ltLly7VH//xH7eSMkY7j1asWKEDDjhAF198ce0L+txzz9W1116rO+64I1/QiURinUTXJVjHHHOMli5dqiuvvHLMO3300Uf153/+53ryySf12te+Vvvuu6+++c1vjnm7iemLW265Rbfffrt+8pOfSJIuuOAC7bXXXvra176mI488clTb/PznP6+nnnpKixYt0qJFiyS1M++zzjpLM2fO1C677NJa56yzztJZZ501xqNJJKYPXOXw5S9/WVIleWu2amZM9kmmPDAwoJdeeqlDwcwslVnjjO8yk9ooWW5Uw22QhVNJLGryQSbN5iJk+b/5zW8kSY899pikegnh6YKu3N3SUDb27rvvrpUrV2rTTTed6HElEolEYgSIXtKRRGb5Uj3zzDM1MDCg8847b8QvaXaq8vp8WZfrWrTE7u6ov/R4v6SdzGZN/XXhJd0Vkx4YGNAFF1ygI444Il/QiUQiMQ2xePHits/O82CsmvHeEgMDAx2sky9p12sbbqdJVbConlrqzAjnC93bovKYX840GMrxS53M2bHnVatWSRrSbZCkU045pWNs0w2NL+nnn39e22yzjXbaaSfdfvvtkzGmRCKRSCQS6uIl/ZrXvKalt5pIJBKJdQNHHXWUpKGMbalSerQ31K5kqZ7tsgaZDNo46KCDJEl///d/L6nT/V2yXe+TKmZe1m5wu7/JnFmzbUR1z449W4O71EJfV9BVdncikUgkEonJR7aqTCQSiWmEl19+WQsWLNC//du/6eGHH9add97Zpm//nve8Rz/84Q/blt9tt91alRPEaaedVvu9Y9avec1rtHbtWvX09Gjt2rUdyVl15Y11OPDAAxuXcWtYs3nvw0zYTLspY5xZ4WbQbhX79NNPS5Le//73dzX26Yxk0olEIjHN8I53vEPLli3Ttttu2/Hbt7/97TYtgbe//e36wAc+MAWjTEwGui7BSiQSiUQnli9f3qrTl4ZY3dve9jbdddddY97261//ei1btizsFPfQQw9p55131gMPPKA3vOENo96Ptz8eYx4JzKytOGYdcpdmsWwsUk0zc3ZJVeQ9WBeRTDqRSCTGgMMPP7zFah977DG98Y1v1Ac/+EF95jOfCbu7uSxqrPjqV7+qd77znWN6QUtDTVay0cr0RDLpRCKRGAcMDAzove99r3bccUd98YtfHJdtNjHpefPm6ROf+IQWLlw4LvubalxyySWSKkbt+mhng1OUhLXh6yOSSScSicQ44Oyzz9azzz6riy66qOt1fv7zn7e6u3XbctK4++67tXLlyrA0KrF+ILO7E4lEYoy4/vrrdd111+mee+5pqWWdc845Ouecc8J1nnvuOc2ZM2fUOhRXX321Dj300BG/3Kcz1gUFsMlGursTiURiDLj33nv1R3/0R7rjjjvGLa67evVqDQ4Oat68ebryyiu1zz77aKONNmq5fV988UVtt912uummm7TffvuNyz4T0xPp7k4kEokx4JZbbtEvf/lLveMd72i5rd/znveMaZu77babZs+erUcffVTz58/X7Nmz9fDDD7d+v/nmm7XZZpvp3e9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" ] @@ -272,24 +182,47 @@ "source": [ "## Amygdala as mask\n", "mask_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", - "mask_file = nilearn.image.math_img(\"a>=20\", a=mask_file)\n", + "mask_file = nilearn.image.math_img(\"a>=25\", a=mask_file)\n", "%matplotlib inline\n", "nilearn.plotting.plot_roi(mask_file)\n", "\n", "\n", "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", - " sessions=None, smoothing_fwhm=2, standardize=True, detrend=False, verbose=9)" + " smoothing_fwhm=None, standardize=True,\n", + " detrend=False, verbose=9)" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 69, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "\n", + "[NiftiMasker.fit] Resampling mask\n", + "\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Resampling mask\n", + "\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", @@ -299,27 +232,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -327,11 +239,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -339,11 +246,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -351,27 +253,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -379,39 +260,19 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", " [ 0. , 2. , 0. , -132.5],\n", " [ 0. , 0. , 2. , -78.5],\n", - " [ 0. , 0. , 0. , \n", + " [ 0. , 0. , 0. , [NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "\n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -419,51 +280,51 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", " [ 0. , 2. , 0. , -132.5],\n", " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Resampling mask\n", + "\n", + "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", " [ 0. , 2. , 0. , -132.5],\n", " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , [NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -471,27 +332,8 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -499,11 +341,11 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -511,24 +353,14 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals[NiftiMasker.fit] Loading data from None[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "\n", + "[NiftiMasker.fit] Resampling mask\n", + "\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", @@ -539,27 +371,10 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -567,11 +382,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -579,11 +389,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -591,27 +396,19 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -619,39 +416,25 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", " [ 0. , 2. , 0. , -132.5],\n", " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", + "\n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -659,11 +442,15 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -671,27 +458,15 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -699,152 +474,1492 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] } ], "source": [ + "## using dask to pararelize fit transform\n", + "t_arr = []\n", "mean_act = []\n", "scr_id = []\n", + "#delayed_get_data = dask.delayed(masker.fit_transform)\n", "for func in func_files:\n", " # get subject number\n", " scr_id.append('KPE' + func.split('id_')[1].split('/')[0])\n", " # get average activation\n", - " t_map = masker.fit_transform(func)\n", + " t_map = dask.delayed(masker.fit_transform)(func)\n", + " t_arr.append(dask.delayed(np.mean)(t_map))\n", " \n", - " average = np.mean(np.array(t_map))\n", - " mean_act.append(average)\n" + "average = dask.compute(t_arr)\n", + " #mean_act.append(t_map)\n", + " \n", + " #h = np.mean(t_map)" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 64, "metadata": {}, "outputs": [], "source": [ - "df = []\n", - "df = pd.DataFrame({'scr_id': scr_id, 'meanAct': mean_act})\n", - "df['group'] = medication_cond['med_cond']\n" + "df_ses3 = []\n", + "df_ses3 = pd.DataFrame({'scr_id': scr_id, 'amg3': average[0]})\n", + "df_ses3 = pd.merge(medication_cond, df_ses3)\n", + "df_ses3 = df_ses3.rename(columns={'med_cond': 'group'})\n", + "#df['group'] = medication_cond['med_cond']\n", + "df_ses3 = df_ses3.replace(to_replace={'group': {0.0:'midazolam', 1.0:'ketamine'}})" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 76, "metadata": {}, "outputs": [ { "data": { + "text/html": [ + "
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" + ], "text/plain": [ - "Ttest_indResult(statistic=-2.705978131239815, pvalue=0.014007413085524702)" + " amg3 \\\n", + " count mean std min 2.5% 50% \n", + "group \n", + "ketamine 11.0 -10.821569 25.109403 -51.072002 -50.816131 -9.722885 \n", + "midazolam 9.0 11.689874 30.076048 -17.359652 -17.306857 -1.437943 \n", + "\n", + " \n", + " 97.5% max \n", + "group \n", + "ketamine 27.381773 30.116594 \n", + "midazolam 62.401079 63.315742 " ] }, - "execution_count": 7, + "execution_count": 76, "metadata": {}, "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" } ], "source": [ - "# plot\n", - "sns.barplot(x='group',y='meanAct', data=df, ci=68)\n", - "#sns.boxplot(x='group',y='meanAct', data=df)\n", - "scipy.stats.ttest_ind(df.meanAct[df['group']==1], df['meanAct'][df['group']==0])" + "df_ses3.groupby('group').describe(percentiles=[.025, 0.975])\n", + "#df_ses3.groupby('group').median()" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 67, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "# now lets do the same with vmPFC\n", - "mask_file = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", - "mask_file = nilearn.image.math_img(\"a>=6\", a=mask_file)\n", - "%matplotlib inline\n", - "nilearn.plotting.plot_roi(mask_file)\n", - "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", - " sessions=None, smoothing_fwhm=4, standardize=True, detrend=False, verbose=5)" + "df_ses2 = []\n", + "df_ses2 = pd.DataFrame({'scr_id': scr_id, 'amg2': average[0]})\n", + "df_ses2 = pd.merge(medication_cond, df_ses2)\n", + "df_ses2 = df_ses2.rename(columns={'med_cond': 'group'})\n", + "#df['goup'] = medication_cond['med_cond']\n", + "df_ses2 = df_ses2.replace(to_replace={'group': {0.0:'midazolam', 1.0:'ketamine'}})" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 77, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", - "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", - "shape=(97, 115, 97, 1),\n", - "affine=array([[ 2. , 0. , 0. , -96.5],\n", - " [ 0. , 2. , 0. , -132.5],\n", - " [ 0. , 0. , 2. , -78.5],\n", - " [ 0. , 0. , 0. , \n", - "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", - "shape=(97, 115, 97, 1),\n", - "affine=array([[ 2. , 0. , 0. , -96.5],\n", - " [ 0. , 2. , 0. , -132.5],\n", - " [ 0. , 0. , 2. , -78.5],\n", - " [ 0. , 0. , 0. , \n", - "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "data": { + "text/html": [ + "
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scr_idgroupamg1
0KPE008ketamine28.970097
1KPE1223ketamine13.012181
2KPE1253midazolam0.108282
3KPE1263midazolam-21.872662
4KPE1293ketamine-7.580429
5KPE1307ketamine-38.789413
6KPE1315ketamine-21.045033
7KPE1322ketamine40.718792
8KPE1339ketamine-2.454142
9KPE1343ketamine-90.909035
10KPE1351midazolam-28.428524
11KPE1356midazolam-17.781033
12KPE1364midazolam-13.385894
13KPE1369midazolam110.843590
14KPE1387ketamine-16.330170
15KPE1390midazolam-12.436435
16KPE1403midazolam24.746063
17KPE1419ketamine-16.783064
18KPE1464ketamine26.202894
19KPE1468midazolam-2.376417
20KPE1480midazolam80.050438
21KPE1499ketamine48.258152
22KPE1561midazolam15.476287
23KPE1573ketamine17.051298
24KPE1578midazolam33.940796
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" + ], + "text/plain": [ + " scr_id group amg1\n", + "0 KPE008 ketamine 28.970097\n", + "1 KPE1223 ketamine 13.012181\n", + "2 KPE1253 midazolam 0.108282\n", + "3 KPE1263 midazolam -21.872662\n", + "4 KPE1293 ketamine -7.580429\n", + "5 KPE1307 ketamine -38.789413\n", + "6 KPE1315 ketamine -21.045033\n", + "7 KPE1322 ketamine 40.718792\n", + "8 KPE1339 ketamine -2.454142\n", + "9 KPE1343 ketamine -90.909035\n", + "10 KPE1351 midazolam -28.428524\n", + "11 KPE1356 midazolam -17.781033\n", + "12 KPE1364 midazolam -13.385894\n", + "13 KPE1369 midazolam 110.843590\n", + "14 KPE1387 ketamine -16.330170\n", + "15 KPE1390 midazolam -12.436435\n", + "16 KPE1403 midazolam 24.746063\n", + "17 KPE1419 ketamine -16.783064\n", + "18 KPE1464 ketamine 26.202894\n", + "19 KPE1468 midazolam -2.376417\n", + "20 KPE1480 midazolam 80.050438\n", + "21 KPE1499 ketamine 48.258152\n", + "22 KPE1561 midazolam 15.476287\n", + "23 KPE1573 ketamine 17.051298\n", + "24 KPE1578 midazolam 33.940796" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_ses1" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [], + "source": [ + "df_ses1 = pd.merge(df, df_ses1)\n", + "df_ses1['amg_change'] = df_ses1.meanAct - df_ses1.amg1" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# this is in case we need to show the lowering of amygdala reactivation before and after treatment\n", + "sns.boxplot(y='amg1', x= 'group', data = df_ses1)\n", + "sns.stripplot(y='amg1', x= 'group', data = df_ses1)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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scr_idgroupmeanActgroupIdxvmPFChippostriatumAcamg3
0KPE008ketamine3.1901201-0.072546-5.5291552.483448-6.452068
1KPE1223ketamine12.91250219.66234818.528749-10.181743-25.161104
2KPE1263midazolam12.12987208.88953821.97941029.35497958.742424
3KPE1293ketamine-20.2331181-7.122487-19.774799-12.404725-17.078924
4KPE1307ketamine-52.2213101-29.786623-28.613234-9.516820-11.628900
5KPE1322ketamine13.528724133.13494111.50446113.141923-50.048515
6KPE1339ketamine-3.3691651-1.105649-3.718665-32.740704-0.137346
7KPE1343ketamine-65.0852201-11.860424-50.98640128.125856-51.072002
8KPE1351midazolam-18.5520020-25.503946-44.4484714.393234-1.437943
9KPE1356midazolam30.8837200-14.83609713.315349-1.926483-1.711294
10KPE1364midazolam56.474892016.96603445.53267345.82691263.315742
11KPE1369midazolam26.3963910-45.5105096.881987-45.61096613.279358
12KPE1387ketamine-13.5788521-11.315875-3.810227-4.811108-9.722885
13KPE1390midazolam7.84772801.090048-3.209616-25.851357-6.360809
14KPE1403midazolam2.05465807.03655725.67226611.806690-17.095680
15KPE1419ketamine-22.49930415.8007159.04819222.4217112.970581
16KPE1464ketamine-31.1857321-23.971344-56.4882518.19493119.177311
17KPE1499ketamine-53.8379101-47.302711-29.856201-18.45126230.116594
18KPE1561midazolam23.159636010.8377893.59905016.30591613.836721
\n", + "
" + ], + "text/plain": [ + " scr_id group meanAct groupIdx vmPFC hippo striatumAc \\\n", + "0 KPE008 ketamine 3.190120 1 -0.072546 -5.529155 2.483448 \n", + "1 KPE1223 ketamine 12.912502 1 9.662348 18.528749 -10.181743 \n", + "2 KPE1263 midazolam 12.129872 0 8.889538 21.979410 29.354979 \n", + "3 KPE1293 ketamine -20.233118 1 -7.122487 -19.774799 -12.404725 \n", + "4 KPE1307 ketamine -52.221310 1 -29.786623 -28.613234 -9.516820 \n", + "5 KPE1322 ketamine 13.528724 1 33.134941 11.504461 13.141923 \n", + "6 KPE1339 ketamine -3.369165 1 -1.105649 -3.718665 -32.740704 \n", + "7 KPE1343 ketamine -65.085220 1 -11.860424 -50.986401 28.125856 \n", + "8 KPE1351 midazolam -18.552002 0 -25.503946 -44.448471 4.393234 \n", + "9 KPE1356 midazolam 30.883720 0 -14.836097 13.315349 -1.926483 \n", + "10 KPE1364 midazolam 56.474892 0 16.966034 45.532673 45.826912 \n", + "11 KPE1369 midazolam 26.396391 0 -45.510509 6.881987 -45.610966 \n", + "12 KPE1387 ketamine -13.578852 1 -11.315875 -3.810227 -4.811108 \n", + "13 KPE1390 midazolam 7.847728 0 1.090048 -3.209616 -25.851357 \n", + "14 KPE1403 midazolam 2.054658 0 7.036557 25.672266 11.806690 \n", + "15 KPE1419 ketamine -22.499304 1 5.800715 9.048192 22.421711 \n", + "16 KPE1464 ketamine -31.185732 1 -23.971344 -56.488251 8.194931 \n", + "17 KPE1499 ketamine -53.837910 1 -47.302711 -29.856201 -18.451262 \n", + "18 KPE1561 midazolam 23.159636 0 10.837789 3.599050 16.305916 \n", + "\n", + " amg3 \n", + "0 -6.452068 \n", + "1 -25.161104 \n", + "2 58.742424 \n", + "3 -17.078924 \n", + "4 -11.628900 \n", + "5 -50.048515 \n", + "6 -0.137346 \n", + "7 -51.072002 \n", + "8 -1.437943 \n", + "9 -1.711294 \n", + "10 63.315742 \n", + "11 13.279358 \n", + "12 -9.722885 \n", + "13 -6.360809 \n", + "14 -17.095680 \n", + "15 2.970581 \n", + "16 19.177311 \n", + "17 30.116594 \n", + "18 13.836721 " + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_ses3 = pd.merge(df, df_ses3)\n", + "df_ses3" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ttest_indResult(statistic=-2.0672394809544707, pvalue=0.05428628326311834)" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot\n", + "sns.barplot(x='group',y='meanAct', data=df, ci=95)\n", + "#sns.boxplot(x='group',y='meanAct', data=df)\n", + "scipy.stats.ttest_ind(df.meanAct[df['group']=='ketamine'], df['meanAct'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# test changes betwen sessions\n", + "df2ses = pd.merge(df, df_ses1)\n", + "df2ses['amg2_1'] = df2ses.meanAct - df2ses.meanAct_ses1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'df2ses' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbarplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'group'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'amg2_1'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdf2ses\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mci\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m68\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0;31m#sns.boxplot(x='group',y='meanAct', data=df)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m scipy.stats.ttest_ind(df2ses.amg2_1[df2ses['group']=='ketamine'], \n\u001b[1;32m 4\u001b[0m df2ses['amg2_1'][df2ses['group']=='midazolam'])\n", + "\u001b[0;31mNameError\u001b[0m: name 'df2ses' is not defined" + ] + } + ], + "source": [ + "sns.barplot(x='group',y='amg2_1', data=df2ses, ci=68)\n", + "#sns.boxplot(x='group',y='meanAct', data=df)\n", + "scipy.stats.ttest_ind(df2ses.amg2_1[df2ses['group']=='ketamine'], \n", + " df2ses['amg2_1'][df2ses['group']=='midazolam'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Use PyMC3 for bayesian based analysis " + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [], + "source": [ + "import pymc3 as pm\n", + "# first code new variable for group index (1=ketamine, 0= midazolam)\n", + "group = {'ketamine': 1,'midazolam': 0} \n", + "df['groupIdx'] =[group[item] for item in df.group] " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Full model\n", + "with pm.Model() as model_1:\n", + " # Data\n", + " group = pm.Data('group', df.groupIdx)\n", + " amg = pm.Data('amg', df.meanAct)\n", + " #ketamine = pm.Data('ketamine', df.meanAct[df['group']=='ketamine'].values)\n", + " #midazolam = pm.Data('midazolam', df.meanAct[df['group']=='midazolam'].values)\n", + " \n", + " # Priors\n", + " alpha = pm.Normal('alpha', mu=0, sd=50)\n", + " beta = pm.Normal('beta', mu=0, sd=50)\n", + " sigma = pm.Uniform('sigma', lower=0, upper=50)\n", + " \n", + " # Regression\n", + " mu = alpha + beta * group\n", + " diff_group = pm.Normal('diff_group', mu=mu, sd=sigma, observed=amg)\n", + " \n", + " # Prior sampling, trace definition and posterior sampling\n", + " prior = pm.sample_prior_predictive()\n", + " posterior_1 = pm.sample(draws=2000, tune=2000) # this is the trace sampling\n", + " posterior_pred_1 = pm.sample_posterior_predictive(posterior_1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#az.summary(posterior_1, credible_interval=.95).round(2) # adding round to make shorted floats\n", + "pm.summary(posterior_1)#, alpha=.05).round(2)# also possible" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (4 chains in 4 jobs)\n", + "NUTS: [sd, groupIdx, Intercept]\n", + "Sampling 4 chains, 0 divergences: 100%|██████████| 20000/20000 [00:04<00:00, 4844.57draws/s]\n" + ] + } + ], + "source": [ + "# play with glm module of pymc3\n", + "from pymc3.glm import GLM\n", + "\n", + "with pm.Model() as model_glm:\n", + " GLM.from_formula('meanAct ~ groupIdx', df)\n", + " trace = pm.sample(draws=2000, tune=3000)" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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meansdhpd_2.5%hpd_97.5%mcse_meanmcse_sdess_meaness_sdess_bulkess_tailr_hat
Intercept14.647.69-0.1030.080.130.093752.03719.03778.04351.01.0
groupIdx-31.6410.41-52.65-11.240.170.123857.03823.03860.04294.01.0
sd25.184.0418.1133.060.070.053477.03379.03573.03428.01.0
\n", + "
" + ], + "text/plain": [ + " mean sd hpd_2.5% hpd_97.5% mcse_mean mcse_sd ess_mean \\\n", + "Intercept 14.64 7.69 -0.10 30.08 0.13 0.09 3752.0 \n", + "groupIdx -31.64 10.41 -52.65 -11.24 0.17 0.12 3857.0 \n", + "sd 25.18 4.04 18.11 33.06 0.07 0.05 3477.0 \n", + "\n", + " ess_sd ess_bulk ess_tail r_hat \n", + "Intercept 3719.0 3778.0 4351.0 1.0 \n", + "groupIdx 3823.0 3860.0 4294.0 1.0 \n", + "sd 3379.0 3573.0 3428.0 1.0 " + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pm.summary(trace, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.distplot(trace.groupIdx)\n", + "sum(trace['groupIdx']>0) / len(trace['groupIdx'])" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# set variables\n", + "y = 'meanAct'\n", + "dfPlot = df\n", + "ci = np.quantile(trace.groupIdx, [.025,.975])\n", + "fig, (ax1, ax2) = plt.subplots(1,2, figsize=(3, 5),gridspec_kw={'width_ratios': [1, .2],\n", + " 'wspace':.1})\n", + "g1 = sns.stripplot(y= y, x='group', data=dfPlot, size = 8, ax=ax1)\n", + "sns.boxplot(y= y, x='group', data=dfPlot, ax=ax1,\n", + " boxprops=dict(alpha=.3))\n", + "g2 = sns.distplot(trace['groupIdx'], ax = ax2, vertical=True)\n", + "ax2.vlines(x=0.001,ymin=ci[0], ymax=ci[1], color='black', \n", + " linewidth = 2, linestyle = \"-\")\n", + "\n", + "#g3.set_ylim(-.7, .7)\n", + "#ax1.set_ylim(-.7,.7)\n", + "ax2.set_ylim(g1.get_ylim()) # use first graph's limits to get the relevant for this one\n", + "ax2.yaxis.tick_right()\n", + "ax2.set_xticks([])\n", + "ax2.set_ylabel(\"Difference between groups\", fontsize=14) \n", + "ax2.yaxis.set_label_position(\"right\")\n", + "ax1.set_ylabel(\"Amg reactivity to traumatic script\", fontsize=12)\n", + "ax1.set_xlabel(\"Group\", fontsize=14)\n", + "fig.savefig('amygdalaReactivity.png', dpi=300, bbox_inches='tight')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# run GLM but define priors first\n", + "# with pm.Model() as model_glm:\n", + " \n", + " \n", + "# GLM.from_formula('meanAct ~ groupIdx',data = df, \n", + "# priors = {'Intercept': pm.Normal.dist(mu=0, sd=50),\n", + "# 'Sigma': pm.Uniform('sigma', lower=0, upper=50)\n", + "# })\n", + "# trace = pm.sample(draws=2000, tune=2500)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# now lets do the same with vmPFC\n", + "mask_file = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=5\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None,\n", + " standardize=True, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -856,7 +1971,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -868,24 +1982,7 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", @@ -896,27 +1993,10 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -924,7 +2004,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -936,7 +2015,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -948,24 +2026,7 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", @@ -976,27 +2037,10 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -1004,7 +2048,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1016,7 +2059,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1028,24 +2070,7 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", @@ -1056,27 +2081,32 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -1084,7 +2114,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1096,7 +2125,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1108,20 +2136,9 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n" ] }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, { "name": "stdout", "output_type": "stream", @@ -1136,27 +2153,32 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", "shape=(97, 115, 97, 1),\n", "affine=array([[ 2. , 0. , 0. , -96.5],\n", @@ -1164,7 +2186,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1176,7 +2197,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1188,24 +2208,7 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n", - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", - " warnings.warn('Standardization of 3D signal has been requested but '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", @@ -1216,18 +2219,9 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. 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" - ], - "text/plain": [ - " scr_id meanAct group\n", - "0 KPE008 -6.946251 1.0\n", - "1 KPE1223 8.529267 1.0\n", - "2 KPE1253 -3.683595 0.0\n", - "3 KPE1263 12.874712 0.0\n", - "4 KPE1293 -16.982929 1.0\n", - "5 KPE1307 -26.965698 1.0\n", - "6 KPE1315 4.907678 1.0\n", - "7 KPE1322 14.401104 1.0\n", - "8 KPE1339 13.274624 1.0\n", - "9 KPE1343 -75.193253 1.0\n", - "10 KPE1351 -4.254865 0.0\n", - "11 KPE1356 37.194920 0.0\n", - "12 KPE1364 37.733135 0.0\n", - "13 KPE1369 12.817131 0.0\n", - "14 KPE1387 -7.577533 1.0\n", - "15 KPE1390 9.533126 0.0\n", - "16 KPE1403 8.639864 0.0\n", - "17 KPE1464 -6.269195 1.0\n", - "18 KPE1468 10.638014 0.0\n", - "19 KPE1480 10.782543 0.0\n", - "20 KPE1499 -59.420677 1.0" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df" - ] - }, - { - "cell_type": "code", - "execution_count": 11, + "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Ttest_indResult(statistic=-0.41402609967959914, pvalue=0.6834913628886718)" + "Ttest_indResult(statistic=-0.6388758996578112, pvalue=0.529499641388856)" ] }, - "execution_count": 11, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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gCBMi/RYAAAAASUVORK5CYII=\n", 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\n", 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" ] @@ -1468,21 +2266,50 @@ } ], "source": [ - "#df = pd.DataFrame({'scr_id': scr_id, 'meanAct': mean_act})\n", + "#df_vmpfc = pd.DataFrame({'scr_id': scr_id, 'meanAct': mean_act})\n", "df['vmPFC'] = mean_act_vmpfc\n", "#sns.boxplot(x='group',y='vmPFC', data=df)\n", "sns.barplot(x='group',y='vmPFC', data=df, ci=68)\n", - "scipy.stats.ttest_ind(df.vmPFC[df['group']==1], df['vmPFC'][df['group']==0])" + "scipy.stats.ttest_ind(df.vmPFC[df['group']=='ketamine'], df['vmPFC'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "len(mean_act_vmpfc)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "with pm.Model() as model_glm:\n", + " GLM.from_formula('vmPFC ~ groupIdx', df)\n", + " trace_vmpfc = pm.sample(draws=4000, tune=3000)" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pm.summary(trace_vmpfc, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -1498,12 +2325,13 @@ "%matplotlib inline\n", "nilearn.plotting.plot_roi(mask_file)\n", "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", - " sessions=None, smoothing_fwhm=2, standardize=False, detrend=False, verbose=5)" + " sessions=None, smoothing_fwhm=None,\n", + " standardize=True, detrend=False, verbose=5)" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 45, "metadata": {}, "outputs": [ { @@ -1519,7 +2347,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1531,7 +2358,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1543,7 +2369,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1555,7 +2380,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1567,7 +2391,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1579,7 +2402,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1591,7 +2413,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1603,7 +2424,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1615,7 +2435,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1627,7 +2446,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1639,7 +2457,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1651,7 +2468,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1663,7 +2479,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1675,25 +2490,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", - "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", - "[NiftiMasker.fit] Loading data from None\n", - "[NiftiMasker.fit] Resampling mask\n", - "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", - "shape=(97, 115, 97, 1),\n", - "affine=array([[ 2. , 0. , 0. , -96.5],\n", - " [ 0. , 2. , 0. , -132.5],\n", - " [ 0. , 0. , 2. , -78.5],\n", - " [ 0. , 0. , 0. , \n", - "[NiftiMasker.transform_single_imgs] Resampling images\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1705,7 +2501,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1717,7 +2512,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1729,8 +2523,13 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", - "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", "[NiftiMasker.fit] Resampling mask\n", @@ -1741,7 +2540,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1753,7 +2551,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1765,7 +2562,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" ] @@ -1786,53 +2582,207 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "Length of values (20) does not match length of index (24)", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'hippo'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmean_act_hippo\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0msns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbarplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'group'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'hippo'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mci\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m68\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mscipy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mttest_ind\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhippo\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'group'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m'ketamine'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'hippo'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'group'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m'midazolam'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__setitem__\u001b[0;34m(self, key, value)\u001b[0m\n\u001b[1;32m 3035\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3036\u001b[0m \u001b[0;31m# set column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3037\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_set_item\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3038\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3039\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_setitem_slice\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mslice\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_set_item\u001b[0;34m(self, key, value)\u001b[0m\n\u001b[1;32m 3111\u001b[0m \"\"\"\n\u001b[1;32m 3112\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_ensure_valid_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3113\u001b[0;31m \u001b[0mvalue\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sanitize_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3114\u001b[0m \u001b[0mNDFrame\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_set_item\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3115\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_sanitize_column\u001b[0;34m(self, key, value, broadcast)\u001b[0m\n\u001b[1;32m 3756\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3757\u001b[0m \u001b[0;31m# turn me into an ndarray\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3758\u001b[0;31m \u001b[0mvalue\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msanitize_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3759\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndarray\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mIndex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3760\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/internals/construction.py\u001b[0m in \u001b[0;36msanitize_index\u001b[0;34m(data, index)\u001b[0m\n\u001b[1;32m 746\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 747\u001b[0m raise ValueError(\n\u001b[0;32m--> 748\u001b[0;31m \u001b[0;34m\"Length of values \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 749\u001b[0m \u001b[0;34mf\"({len(data)}) \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 750\u001b[0m \u001b[0;34m\"does not match length of index \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mValueError\u001b[0m: Length of values (20) does not match length of index (24)" + ] + } + ], + "source": [ + "df['hippo'] = mean_act_hippo\n", + "sns.barplot(x='group',y='hippo', data=df, ci=68)\n", + "scipy.stats.ttest_ind(df.hippo[df['group']=='ketamine'], df['hippo'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df['hippo_21'] = df.hippo - df.hippo1\n", + "sns.barplot(x='group',y='hippo_21', data=df, ci=68)\n", + "scipy.stats.ttest_ind(df.hippo_21[df['group']=='ketamine'], df['hippo_21'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": 19, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (4 chains in 4 jobs)\n", + "NUTS: [sd, groupIdx, Intercept]\n", + "Sampling 4 chains, 0 divergences: 100%|██████████| 28000/28000 [00:05<00:00, 5140.47draws/s]\n", + "The acceptance probability does not match the target. It is 0.6948570225703795, but should be close to 0.8. Try to increase the number of tuning steps.\n" + ] + }, { "data": { + "text/html": [ + "
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meansdhpd_2.5%hpd_97.5%mcse_meanmcse_sdess_meaness_sdess_bulkess_tailr_hat
Intercept7.007.31-6.5722.430.120.093506.03355.03513.03728.01.0
groupIdx-19.3610.02-38.640.960.170.123538.03489.03548.04080.01.0
sd23.963.7617.5231.760.060.043817.03817.03658.03645.01.0
\n", + "
" + ], "text/plain": [ - "Ttest_indResult(statistic=-2.399270760779392, pvalue=0.026845745096531853)" + " mean sd hpd_2.5% hpd_97.5% mcse_mean mcse_sd ess_mean \\\n", + "Intercept 7.00 7.31 -6.57 22.43 0.12 0.09 3506.0 \n", + "groupIdx -19.36 10.02 -38.64 0.96 0.17 0.12 3538.0 \n", + "sd 23.96 3.76 17.52 31.76 0.06 0.04 3817.0 \n", + "\n", + " ess_sd ess_bulk ess_tail r_hat \n", + "Intercept 3355.0 3513.0 3728.0 1.0 \n", + "groupIdx 3489.0 3548.0 4080.0 1.0 \n", + "sd 3817.0 3658.0 3645.0 1.0 " ] }, - "execution_count": 14, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" } ], "source": [ - "df['hippo'] = mean_act_hippo\n", - "sns.barplot(x='group',y='hippo', data=df, ci=68)\n", - "scipy.stats.ttest_ind(df.hippo[df['group']==1], df['hippo'][df['group']==0])" + "with pm.Model() as model_glm:\n", + " GLM.from_formula('hippo ~ groupIdx', df)\n", + " trace_hippo = pm.sample(draws=2000, tune=5000)\n", + "pm.summary(trace_hippo, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.set_style(\"whitegrid\")\n", + "\n", + "grid = plt.GridSpec(2, 20, wspace=.1, hspace=0.0) # building a grid to put the graphs in\n", + "plt.subplot(grid[:, :10])\n", + "#fig.add_subplot(grid[0,0])\n", + "g1= sns.stripplot(x='group',y='hippo',hue = 'group', data=df, s=8)\n", + "#g1 = sns.boxplot(x='group',y='meanAct',hue = 'group', data=df)\n", + "g1.set_ylim(-80,80)\n", + "g1.legend_.remove()\n", + "\n", + "plt.subplot(grid[:, 10])\n", + "g3 = sns.boxplot(trace_hippo.groupIdx, orient='v')\n", + "g3.set_ylim(-80,80)\n", + "g3.set_yticks([])\n", + "\n", + "plt.subplot(grid[:, 11:13])\n", + "g2 = sns.distplot(trace_hippo.groupIdx, vertical=True, color=\"Green\")\n", + "g2.set_ylim(-80,80)\n", + "#g2.set_yticks([])\n", + "g2.yaxis.tick_right()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Striatum" + "## Caudate" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 20, "metadata": {}, "outputs": [ { "data": { - "image/png": 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gLltxKMHpv/v7+9Xd3a2BgQH19PRUjkcm7fvD19yf7GvElDuljRF11iCpNVc91z33fO+UsSO85/2OGi8kk04kEolEYopiyjBp5z9bNIP+D0bTmkl4BWQfgvf3Cs2s1MzGKzkzKG/PVSV1tksG5UT99evXV1ZYjBjnJ/tAZTF/mu15xeZ8aI8JGUmpAFXuR3ZH5uRa2psrozZ7llorYha497WoY6IlyD583Rm1XaaelOf1PPT5PO/oeyMbZcyFrTCsejVc2o3ni1f8nEcRIi3vstKX/Y99fX1tedVURaP1iwy71Mcv28ksBzPrzYFRs9DEcDEM9EEzJoXqc0Yn+c+Rip7QjxvFBa1evbpyzvJ4tEhSC4LWAbL1iDF3+p1/8/y+P82gyaTL4/Bep/V1rJFMOpFIJBKJKYopw6QTiUTipQazMlohmEVQbsv4Gmr/k1HTF83MBLLQyO/LqHLWITfrLGN1BgcHK9ZGMuPoXBS8iraPrASdGLTH12229ZL6BlTbK/sbxTGNNSb1Je2yklK7+XG4gBipXf7TZgsHltksyAAclvijGAXN27y4AwMDlUldtovnoLmbZqZIPMJtsEmeNwPNLRSRYJ8YMOSb2cF5myvKqkEeM/edaSsU+jA6Bap4P5qdowAypxlFZnemQdG06flNFwfbV/6fx2BaWWQGNfhyKB90vgfWrFnTnOesARzpL0cBSry3vZ0fhg6otNBRip4kNmckk04kEolJQuR7ZcyD1K7ZwJoArBdOMhBFg3Ohx2h/koAo46Fsh33RAwMDbfn55TmitpGkkfCwjjsJTsSsqeDHEpXMZKiL+YgyQcYLk/KStoJVaSYgk/DFcNAIJ6QHjUyagWF1FVpKRJqvBoO0pk+f3iwqMGPGjIqmazTZOdE6VWahGYUpV1FKS3Q8ns/MxsFLZVGJE088UZs67rjjDknVm4cMmqkdkdmM14ymP0pm8qameM7y5cslSc8880ylzVEgGIOFeO2JusC36AHYKU3Fn2bvFJ6gBCmlSznGUZAPg3gMPgzZdx+/tMj5GMmuE5sLkkknEonEJCNaqJcLF7ojyHDJEunXZnWyTgzQ+3uhymIXXCzV+bgHBwcrRIZg9g6PQf34yEVIJm0fM1k89QX4SZ813Vdlv+tquI8HJvQl7dQJJqxL7eYLTjD/zonDlCzKLNKpTyZkRAya5+/u7m5K3k2fPr3SBxbOoN8wSpPhxWbKCo9DQQt/T6ENm25owiFDL+FUuNNPP722rVMZZtD0P0vtflFeXz7oaJ3gw8D7cz5GrI9pMmab3s8xFLYA8dpGcQZRQEz5f6aZGZFJkffecFaI7u5uNRoNzZw5sznPIjOoP2kFoGhKVB6U8pSsaCS1fP621p199tlKJDZlJJNOJBKJSQJ9qFxElovFiGDQf+3FjomKF2NcrHth2Clf2gsfL7qcb+92sJrfihUrmi7Bnp6eWqbJBRcV+LzQY9441RoNVp97+umnm20p22q3kxeeUaVCVq8rF5ad3IljjQl9STM6ua6utAeFE4YTkZKDHGQy7JEmyTNogpHaLLBRdxMxoIAh+wZZnCcs/ZNk4hRFocCGJ5gnLM1NZCieuFLrBhxv0fjxgG9sSshKsZmsU/3ZSBiCRQY6iaD4mpkpu218GJH9Mt0mKoPqdvihJLXmgeeTmTDnFRk0TX2Rv91WJf/mBx99y5Rc5L3n7+vqEpfbGYxHKS1C3tc+/2TUiU0dyaQTiURikkDFLbo3StDlwpRParWzZgCrN9FtwPQ/wkGPZMFeNJWpft3d3bUuQRK1qF67++RzdgpC9CKV0dr+9PG8IPTfVPrjdWBEfQm6dcYLE/KSjnzRJUuJfH5RUnpkJmKOJSUQyUh4XE98MxsmtVMWtLxAnYTtI580Bex97ihHl8zc20UMukzjGK7v5bFLFjrVYT86WepwgTG0lBiUVOUDjDEKTEfh/ob3t7kusqqQzXou+OHD4/uzrj+M42BpQVqNPF/8Nxl4nR+8bA+tBbQo8TwO7nH7nG0QtY9Wi7qUotIqVB4jGXViU0Uy6UQikZgkkA2TMZZuGorFkDHTBeh9qbnORRsXUf70wpDbm926pgDZcG9vb6UNXuSV/aMLhQsy67RHKbgkKIzuNrxg5wLRfna6gOjWjHLLhzvnWGNCX9JkuSXTobmD6CT7Rh8do3kjEw0nuNmoV/m+qGUE6sDAgPr7+/X8889XGBMngkFfM1kQo7pdkrJUzJJiXzRNOdHNGLG8OsEEb3vVVVdJks4//3xNNdx4442S2n2odQE2nUra8Tr7+6g4BBk2WV7EpBkPwLnAwjFkkcz7H66wRqRixr77HD43C74wEr28txqNhrq6uirjGpVU5AM18oXTd82XzEhiW/xwNjv3uZJRJzY1JJNOJBKJSQKZHRlc6b4ggfC2Dva0qZ+CUFzYEVw8ccHKBaODE88557uSpNtvP1pSnC9c55NmqqKP7b6ZSTP3m/t3qvzHBZzb4j66L4zijioWlm2i/vd4YVxf0vZFM/Lak6n0H0VSc/6M/FT0TzG3OEpaN+gLpOA6dYj7+/srLKa8iWweclvpVzST9ureq32yM4+LGQvHgBOvkznLiEpWln51js94J+pvDKyQRvNepJEuxcUEeFP6e/qCDZojvT+tGDQBdoqx4DjzIcNAm05FEkp0ytM3osCkKNZhxowZzVKVa9euDbXkOb99j9p3TUbs47MdLGlZd0/zYU11PR/zuuuukyTNnz9/2DFJJCYbyaQTiURikuCF5VNPPSWpRQ68oC/ZLyOTd9ppJ0mtYEQuIMkO6fLz3yQmXGRFLp1PfWp/SdLxx39VkvSlL71bUnWh2Gg0KqSCymKGz21/d11+cvm9F8/0GTNlkQv2KBV32bJlkloWDQfxmkiVhMfHdJufe+45jSfG5SXtHNvIj+cBLCOIaVaItJOjEmZ18m3l750KnXu1zhB++uFmzZrVvLBbb711M2m+3DcStmfFpE7VgciiODaRVcHHY/WsiIGX0nn0+3kbW0XOPfdcTRasKGaYidUJ/EtVtbmobJ9BZuxPm8N8bWlSJFtkoEsUxR1FaXNeDudn74QojiNi1tEYUM3PL4tVq1ZVAn08n6MIax7f2zEDg3ECfG5EanBlG/3JzAkf23nU1v2eN2+eEompiGTSiUQiMUlgSqkXQFx4S63Fp33QXngwIDcqwsJiLz6nmSDdCpQPJpNuuQCHFkTve989zd9//vPntfvuszQ4OFjrC6cKmhksF7mRwI0Xz5TV5UKRqmsG3UQeUx/XjN6L83IsvQA0udkkFcfs//HFZeBCXcg6cyojRkx2GjET7hf5/ujPpJmFmsuNRkPd3d0aHBzUtGnTKtYAX2jmpzJVwn3kOEWJ+pEvkX2iiSbyh1L8oPSrRzfocCL5EwWPH3Wufc1cZ9g3Wh2T7sRw6Tf1mPpmLf2x5fZ8ePBaExGjj+Znp7/rfNLclj7n6FhsW1R9aubMmert7dXAwIB6enra/Pe05LCPjAPoFA8RBUSVcpf+P+M7+FD2vemXwy233CJJOvnkk5VITCUkk04kEolJAtPfKMRTLqC9iKHuNH+npCzdBd7OqXVMO6SrwOz0Ax/4fqXNXBj29VnSWU3Bp/7+/soiym0wHMXtbf7mb34gSbr88jdKal8YkmB4wem+REG5kewzx8wLf+qclwtGuro2qTxpr0Z32WUXSe1mEpsHPNB2vEtxdCorS0X5rkTEGjpNbFb6YSDCqlWrKhe+rgqWGZz7zQkVVSPi31HBcoMRypEvkNHfnOilT9rbepJ7HLzvZPjw7It2m7bZZpvK3xwns6OS2fGBZXBsOca2inhsIwlAPgg76bXXmTPL80W+52g+D8ek+RlpDRDR/uVDyvr1W221VVs8h+cSSyNG/njGXER+f0bg+wFd/uY5QjOpr4+vJyPXE4mphmTSiUQiMcH47Gc/K6mqdy21u/vKhVSndFQvvikmY3jRQ8ljgi6B887798p5o0XewEBVdvZXv1qtj3zkES1YsEPbOf7H//i3F49VXfR6MWXW/rnPHVr5ntK1FHQy8WN6X1SgiQtGL948Rh7L0nVGvfWSbI4HxvQlveOOO0pq+WYp7O4VNVMJpJYvzxeBk7eulm3590gr5xj83azMUneUzPPfzz//fMWUUzIrH5M+YZY9YwpEp0jfyGdH9kdzFaOdo7zXkkXQv83+U+t6PHHbbbdJal17ijbwIWRTF7WhpVZ/GJASjSEZNqOrqZZl+OHAOAMjMrtFVbg6RXNHc6WuzZ3U/KI2jsQq1dPT0xbI5HnlwCTey1F8ANvPvrE95TyIqoYRjDnwvP785z8vSTrjjDNq90skJhrJpBOJRGKCYClbkwEGw3VKyZPaWSHdEFz4MWDXi6do8e+/L7jge5XjjrTMb1l4hcf/6Ef/j6SYoBgM4CSDrju21CIgdDdFbeVxfD76tOsWkhTVWbRokSTpzDPPbNt2NBiTl/RNN90kSdp3330ltTrIC8E84ZKVUYrOv3lCUUOZ1ZoYRRtN8iiy1cej1q9R6gl3dQ0VNI/8mz6Wo5Dpf3RfIn8l+0DQHFWnilb+7k/6oOtSCOiLZn1u+/quvfZaSdI555xT28axgMfXbSKDJiumz9oCBVJrHtXJ/JVoTy+pRvtTKIKFEej77pR1ECmGjeRhXdeu4fzMEaPuFEFO7e+6GAlnPUgtS5HHhPOND9KIYbOdfNnwgSrFWgC8Jwy3lTKRX/ziFyVJc+fO1XA45JBDhv2dePLJJ2vbGaG8nlH1L/r0I8lMWoEiC4rxi1+8UDm+5M/hX3iStGrVUknST35ytS65pGXpWLq0D8f0vp7nqvz93vfeUOl7ZA1q7oWXahSHEVmwogyk8nkRWXT8vRURNwQPPvhg+Fsy6UQikRhn/O53v5PUvhAxopfQaHJwue9IAwaj40Qv604oF32t/5KQcJ+hz5/9bMhV8qpXvazjscu20k0VEaCNGd9oUWRY4GqHHdp98RuDMXlJb7vttpLaI1sNJsFHGtQl6Ff1SpcMz2A+ZCcWGkVMG2T73n7GjBlNJt3b21tpB/XDyRSiNnFcIvbEtpsV2PfqtpLlmbkwL5pRtOV3ZP+0XJitjge8ErUlwn5DWiBYH9njz7rcUotJM+/d4Aqb+uecq/6dQhJ8KNAkGWnKR4j8slG76wKNIuYUIXoI1amfdXUNVcCq6wevR1Rli6yF+uSRjn+dAhmtBSxKYXge0FrDMpCdMBwDKuFqcnvttZekVuyC2+nzel5Rt1xqjRNjM5hyxXrehvvqvnXy9S9Y8FBlOz7X168feo44YKy0Uv74x1eq0ZD22+88XXjhjs19rrjiqcox/cLv6fE8dw599T657LI3VMYg0hmgNdPX1XONmQH+ZCaOU8OMstwmx4nPBmc5HH/88RoLJJNOJBKJcYZZlReelFrlg78uApspnnRF0ZVDlx1fcEYnURt/Xn/9IZKk97//QUmlW6I+LbGra2jff/iH3za/u+KKgyRJH/zgwy9+U2Xpvb1VU32n0sRRm+muGqnoFc3dvj7l9iSKdO948TRWAjlj8pJmVKfhCUapuzpEDIHMLooujhhJJzZqRJPBObf+HBgYaAZG9Pf3V1gAQ/I90XxjRr7ASGVqpBPVY+IVXGTyYV1rjm15LLaVogJerY8HfA4+jKJxIaP29mYcUkur2Q8/MtoIrEbl8fGYRT7uTpHUUV+4Ha1QTCGJ8qyl9oc6MyTYZrIJ6hr4nAwgcnzGSINyaGGipYfPCbJLz726uILIImJwDEoLmdQaqzL3OpGYTCSTTiQSiXGGA1K9SKDrhgtrugSkdsZGRhf5uaO/uUCka+W6694qSTrnnP9HUrvbxCbqwUFGUFfP0dvbMpO3FpHVQLGWC6V6LLeBzDYKsDSYjkpw8R0F5XmxVo4tCxZx0enrsf3229eee0Mxqpe0I3xf97rXSWpPAaB93yvzuvxI+r3oB2GSv30NZPGdco0jv1y0HVnH2rVrm6Lx69evrzBpTwj3l2pVPFcnv3kn+KbtJBNI0CpR+m75cIj8f2Vy/1jB5iH3J9J85sMkitgt2+hrYH8cbyhGFHfKc4605Y0odYPza6SSgjwv84HJlss+RIMq1zcAACAASURBVHWdO81D+kUd+ez5vW7dumY96b6+vraoYradLwlG6ZNBez/GUgx3fzCWhSIVUQUtmip9T2TedGKykUw6kUgkxgk333yzpFbAmBdVjPLmwoP62SXod2VQlBciUU5xdE6yS+O6695S2b7FYquFUsyCBwcHinP1NnW4y3P/7//9p5LaNbO9nxdJkURsFExoRL9zQcoAZPfN16fORctAPcYEULxr4cKFkqSzzz677Vgjwahe0syHpo+Uyk/2PbF+rBT71sgYfE5fVLLISBWJEztSmGJffB63ee3atZo5c6YGBwf1mte8ptJu5soygtSgKYYTiEptBvvi81gYgfrSURCEmVHdBKfvNarP6zaOZZ1pTnqDQTVRPihrYZfzi9G7/mRkOK//cHEUZZs6md+ivGrPL7ePZtCRsl6jfPCSwdJaVBetXX5Pc57nl+fbCy+8oBkzZqi/v18zZ85sWik4ppG/nvm7kfCE76PhxDMMXy/GHtAixvx33nM+Jyt7JRITjWTSiUQiMU54xSteIandF93Jj1xXsteLIPtJmdpJnzUDKiPhG3/fKZjS23/2s39W2f7007/54u8t1tvV1aV99tlGN930FxWXDmWGzzrr2y+2cagNn//8YbVtNEhkKC4U9ZFj4XFmUCQXw3UuS/8/cjkxAHO06aqjeklzkkTMjatTR92WSkFR0rkHwIyZOZdRdGykuey2mtXbv+ZaxA7wMFtg7ve0adPU09Ojnp4ezZkzp3ZcIj+mV/dWHfIqfeedd5bUYlXsW+S35ISlb4+KZIySNcoHgW8ism1fSz5UonrJGwIr1vmBFvkPI6uHP1nzufTP+v+eP/avuj/+PVIi65RfHwXfsAKc+/bKV76y0p6RnpcPHR/X1qoyHziKzjbYd7eN+ek0zXq+bbfddpo2bZp6e3u11157NTW6rfTm6xApZNHiE1kN+GDn2FTFMuqfRUYnjQbGYPjFaDnP0047rXa/RGK8kEw6kUgkxglccDJoNhLJIbmQWoVKvI+JBCOU+dlJJrSTwA4jpOkmcf60Gf706dN12mkv1/r16/X73/9eTz31VHPf/fbbT1Jr8XPllX8sqUXceGyyfaNTACcJTiRpy7KqXjh6wU9Xj9QuY0uBJC5OvdjdWIzqJc0I2EitivmrTCGQ4jq8jFrlatzopMhkuG3M4V6+fLkk6Te/+Y2kFqN2bWwyax+7bAcngJmMJ6mP7ZvNZhCH6nOCRdWH2GcjCo6gPzny/ZX7cjzJqCO1nY2BbwB/smJVJ9Utpq0YdWkTPrZvSl9/srZOiB6Iho/nNvm4nk8MlIliJDin3F5bAvxg9GfJpP2gYR7yd7/73WH7Zj1qz0+z/p122klSS2GwjB6fPn16U7DDY2xGbY0BzhkGOEXWr+iFVhflzRcPmTRfAhS9iCLMRxqFn0iMNZJJJxKJxBjDUd177723pPYUPy926aOOGLfUXriHJW99rCgfOvK31tWultrVuiLfNgnV2rVr1Wg0tGbNGv3yl7/UE0880TymyY4XgHSZdhIFoggNEcnw0uUTKYzZ/WnSRhdk+X+TCvchGvfRpquO6iXdKQeUPiP6qksziicp/WMjVYaKzs1Iaps3GGVr/7KVqSyI/9hjj0lq+Ut32WUXrVq1StOnT9fy5csrfnVf4N///veS1Jyc9nf74pqRmKHQT07/aDQhI4m7KOiB2r2snlVuY9SpkpWIagGPBNdff70kadddd5XUXtEsij6OKtzwYVUHb+Obj4w6Es3vpFTHwBXOO88vX4vIKmDQcsHqcO6HLT60EEgt5kz9aj8gzXDJrCM96sMOGwrq2W233SQNvYDWr1+vadOmNT/LPvrh5JeKLUpuTydGzfkdVceqG0O3hbXT+SJjvAbHfUN1zxOJsUYy6UQikRhj2McapfTRpxq5dkqXIF2BTIf0JyOVDX8fMWi2kW3gJ11hZTDj4OCgBgYGtHLlyopYkkmQF26E++aFelT8gws29oVuOS7oyf55PBOuunROanb7N5Ief++FoQNkTz311Nq+RxiTl3QnFsvt6vw/VP4ZaSm3TkLrnEhRSL/Zq/1q/v4nP/mJJGnx4sXNfZYuXartt99e//Ef/9GMzC63vf/++yvneOtbh6Tt9thjD0ktHzQZHyc7FbeMqI6pwZuYKmGMDB6JTzqyjkRRySOBGR2jiKMAFzJsjhf7OVwevo/lcztOwOzT14bjwOMwkt7nZByAH0qdSuf5eG6PzW5k0FH+bzlnPJ4eZ/q1fWy/UO655x4NhwceeKDy9+GHH67nnntOs2bN0n/913/pVa96VeV4biOj9p3d4D4akYXEGIk+P61IHmdbs2ytofWKljW+oBjvkEhMFJJJJxKJxBjD7hS+9LnA5uKAvuly0UWSE5VtjBbQkbvIiFIzyfajYFIvZFyAyAGFdX51upkiPWwKFXUKpo3U1qIFHxk7I7britFERXfYRpKLjc2XHtVLOgprj5gefYtlxzk5eQxPAEes+nuvjCP1M7aBE46mHf/uAY0Kdy9btkx33nmnjj322OZ3ZNDGnnvuKanFoDtpKndirZ7gjvD1J8fE7I3ni/SLy/9HqlHRuG4M3D5eu6gtHB/Wz6ZaV4lIfYsSf6xgxvlIv2lUjcpts8+YD4MonsDn/9GPfiRJuv322yu/H3rooZV2UVChLsCFOvf+fscdh+r8muF6Lt95550aCe6//349++yzevbZZ7Vw4cLm/n/0R38kqZX/z9q+9mn776efflpS+/U2Oj1X6sA5QzMn02h4PWgJ8Ry78sorJUkXXHBBeO5EYiyRTDqRSCTGCNddd50k6Q//8A8lxYGVZMVeRFDbu8yx9WKcwjiRfzbyc0dM2ogW6FyQMn/ai7G+vj51dQ2VL505c2Zl4Uh9a44Do9opLsMAv05WAxJEkgwu9Jlqx8JC/H/ZpigafrTlfUf1kmYHO9U/prmlzEmlr4jR2I5E9UT1ds7ZpFkiKmnmAfa5OfE40X38TmNQh8MPP1xSK+2ANwfHgz5oThhv5++dG+ux8ffum29mWwU8xpHyU/l/Mo8o2rmTtnUdHEDhogORrnIUac34Aga01EWk8+YmmNdseMw63dSMs+CNOtLxsp+YDNrwefzwNlNnOk557rKCW9kH3gvO4T766KMlSUuWLBm2rYQZuK0Bro7nNCTqJJjJ+3tnQ1BTPjJt0npRtw/TYKiRzmNRPIPxDhnlnZhoJJNOJBKJMYJdOFHqaBTIyoBFL8LKRaMJixdB9Gd3Curk93TlGFFFqchVU8e4ywViST68IItSbDuletIvXuc6rQMX/FE6MN1ddYs6/z9K14vO6b5vqMTsqF7SZmpcbUaNpAmjZNLU57Xv2aHwZtDUZeYK2L+zyhEjg7l/JLBe5kFvKBzVSi1ufjJHnMES/ozKqvFvMyYjimyu0z0ni4lqBHOCbggc/UsVOZaX6/Q7WRKtMGXqB2tOR/1gQAsZGSPKOd/oH6faVxTd7b9tFTnooIMkSQ899JCkVo6yH25m0Dah1RVsiEQsGOfhPpHhvv3tb5ck3XvvvdoQfP3rX6/87bbtvvvulb/dPt8nHgNrFLAfZLNRPED5G+dIp7z+6LqMtApZIjHWSCadSCQSY4SyqIsUl87lYo3ysSYH5eKSjM37MG2VftRIGjWSFY5SaCP3A91UfX19zQjv/v7+2lTbSFc8WgRFxWHoZ4/cEZ2Cc5lK6evIwOTyXHQfRUV32NcN9U2PCZNmHd9IRo4avJzQUsukY+bMWtRMVSC79MQlw3ObuKLuJAQQ5Sobw5lZqM/MbevSLMq2k525be4DI+LpH6WKFlMB6nS3eQNGTNrniBjqcKjzn0qxj5k3UlTM3m3xHChv2LoAkPJYTGdxxLGZLS0q1NB2ZP/BBx8sqTVunr9W27LaHNvh+AJv5/OZzfKeYunDulSRKEqaJkafmxYMs/WNhRm14zrMmH1cPmj9u61ozm2OzLTD+YfdF0bvG4xZoUmXVqz0RScmC8mkE4lEYowQBT9GkdeGf/eigGV9y228wLArkIyaBCMqDkJ3QRSd3KmIznDiVQMDAxWGGbkqOvmUIzGqiEFThIj504wq9xh6P6aHlvrbPoYJZaeFHF0mdeR0OIzqJT1//nxJLaUi+l7JVhlNWjJID5KZh1fTHghfTHeQx+QEjqoHeaCYV8qL5uN4+yOOOEKSdN9991XGYLjJRfF43jzsC33KZKmR8IH/5mTx3x4jjyXzkssHRpTOQTOUr9e5554b9j9CVPCejL+TWhwrmtHvW94MUTF4I8qjNcukVcMMmjrX1sH+sz/7M0mtMf/tb38rqTWv7Vv2NbXeu/vgwCFKDdoK4v15H5TzMQpaiiKfPY4eA5/jXe96l6TOimQR3AePRfniKdvhTzNtK5JF1p06FULGqNAUTH88ny8GrTLD+b8TifFEMulEIpEYI5AUUMc5KtfL4EgvEkozvRc3Ub5yVN2KZCmKkDYifXEjkgouF9nd3d1NxbFy/6gNnRg1BYwicCHnRRbHIGLSzE/3Z9kHFmnaUFlst+XSSy+VJF100UXD9mlMXtJutDvEiRhFdZedIHP26tuf9CVHymE07XASMDCAzOn0078pSerrGzrOxz/+B5XtjBdemKWHHtpL731vXH+Y+5BJ00/KGtdkEJxYkYSewRvenx5T97kuyj4yz/EYG4JrrrlGkrT//vvX9ovjFeUe88ZiTAQj+cv/R/nOPgYj430sM2fP03/7t38btq/f/va3JbUYNfXSGS3OB6ItSm6XGbRz7kdSP32kDw0yWY+NLS5m1I899kZJ0t57/4ck6aGH9tILL/xn8/8HHfTLyvHdd1d7c4xG9CCmlYtjFFkGSosT77Eox97X2dczKhEZyUwmEhOFZNKJRCIxSlx77bWSWoGBnRZ9Jh1RPek6luttvWDzgsTEhpHhZJV1i/LyXAYXR5EOdvR7b29vU3FsxowZFbfTcOmfZZv5NxdqXETxeD6PrwMJIt1fLLjjT49lOUZRui4JIf/mgnykvumNL2GUSCQSiURiXDEmTNpRhl512HdCvwsDx0o1HZq7fUwjyqdjNGVk0qO5259u8ymn3Fc5Xnf30PH/5//80YvtGmrfk08OmfimT5+mOXPmVNJU3vSmN0lqN9ddeOH3JUnXXvvmyjjQFOc20e9C/41/j1Kx6I9hnz3GLNIgtWsJe5z9vff154YgksiMxiGS3oz0dRndWgfmmDLX0d/702ZuB5B5XP70T/9U0sjN3oTFSSImwOA3F2dx33y/UJSnHEuu9CNRE4+nTeweT6dOUTDll78cElrZZpt+vfBCr+bM6dJZZ+2gnp4hFul7wqUr/clynWynwUDASKrTroOyz0zvi+5/n4MKXwxE9fZ+HqWYSWKikebuRCKRGCW8kKFqoEHtAsbGRGbvcsHOcziv3N9TzMQLUhORyMwdaULQ508zLs28dQp3vb29leNGWRZR3AmPGQXcRWIozACgLCkD9LxY44KyJJQUL4nM/yQ8DPhj7n6EMXlJuwMWYnDjzKhZQrCOMXpV7LQLb8NKLyOVCOykXOPz+WLfeus7JUknnHB3ZX8fxufddttt9cILvc0KL2XU36677iopXnWfd96/V9p+221HVfrqNkU3QeTbYAAZi4f4wWD2y+CYOm1dXiOzLIt8nHHGGdpQdGLEkbUjKp9ZFyAWgcdmgCIDyDwP3X8/GH1uS2e6KIVFT77xjW90bIskPfDAA5W/3/rWt0pqMUE+7H0PUXhkOKWmqNoRH4QcZz/0fe+1hISq/jxrNC9bJn35y73q7R2aR9df/wZJrTHyS4KpmWT0nmNMV+NLh37e8mEXWSZoCfLv7iutX7TI+R5ZsGCBEomJRDLpRCKRGCW8oGEwEJXP+H0k9enFRsngvNAwgyYLN+gK5IKFTC+qbU5EKVckE+VnJGbCthpRFT7qNTDgjK4zuov4O60PPh7FS3x9vGCU2nPnOZ4s2sG2+pylQMpwGJOXtBvh1aY7YTbC4vN1sn5mn2TQTL1idCBZJVlXVCjeDGr+/O9U2kQwmnDWrFkvHrtLXV1dTWYjSVddtUyS9Fd/NZRyYn/2lVcO+fD++q//v8qx3VdPAIqXRBMyMjt5nCPlIPfZflajzidN2UszRbKYDcH5558vSfra174mqX2yM+WKEZlkSZGKUN24UWrVY042WV5PqcUGaX6039Xj4bl96KGHSpK+9a1vdR6QAr537AfmvWIzHIuIMPq17HNU0IVmTPfB57D/2/jIR378YlscG9FixF1d3erqGppDPL7HkhG2Bv29Tz75pKTWnOt0r/vZUFqCojREX29aC1icxRgutS2RmEgkk04kEolRgguGyO1G32qUy07pyfKYZodcYHTyMUeL/ihQNSpKEamu1bHkadOm1aYauX9kyDwnmTHdF2wz9R0iFwuDbhmcSDJXZ9HgAt/bkCTRvUj/dyeM6Uua0aAeMPqb6R+U2v3YDHZwxyi1yQCDKFeN3y9Y8FDlOO3FCKr7lZOpu7tbno/lZPGxLr/8SX8jSfrAB77/4u/VNp588lAJwMsuG/LhRaINBplxFBRBxkGzlJkLI4Trjul+s/jBaOD5ECkikUUaUfUeMm9+X57Tfk/eYO6XbxyPiXNSqS5Ec5q/d8DJSHH44YdLkvbdd19JLYZOhkxLksHt6qom0bpEnz8Lt9Aywwdgee6uLqnRaJk2JemZZ56RJC1fvryyvdtDBk8LEq1nnIssrlNXftLnMiv331GAF02XUQnTRGKiMexL+pBDDhnRQVz/lSpeRp3GLv/myzBazUXBMHXHLMFV3i9+UTVr+gXa2r76ki+xatVSSdIjj1ytSy5pPTSXLq2vCBWtpv0SP/30l9WeKzLBRb4mIzLxR6vQOgWoyE/lh9fChQvb9hkpli0bcgtE9cc7la0zyAyGM1lGEZdkLmxDlMpDJmR4Ne0XVSc88sgjktoXJhE76iTiX/7eaVwinWsG5P30p//94nbNIzSPVd4LxkUX1ddg53l5foPXwIjYVt08iSJqo2jguvHba6+9RhwgSfVA3mvs60jnenmvUmkvktKMnpHRuegXj1LiOsmPlte30Wiot7dXW221VWVhGUmMRkGxJCB85kXjyfeFEfmHObcYzFu6+bjY5AKezJmfhl26nTAmTHrnnXeW1CotF+Uyc+KWEzCatBF7MiK2ONKXdfHLi7+r8jk8oo26Kr/HgRlD3//850PMdu+9q6Uto7aO9AEeLQ78ySAVqT2nfTzyQvkw2NBrbnR6YZVMmg9rRjiTqY40mCaqemTLA9kkEZXQjJSYIqnZ4V7SHKdIMYnWqcceWzls24k99phVOV+nl3EU4BRd/6i9dVKofNhHD8qordLQOPABnEhMNIZ9SbPCTye4QpRN1qxz7NWIg5AcKCK1VhWW1aOPxw9PRjT6JqJACitC8Wa88ML/ePHMXhVWfRFcARtdXV360Y+uUKPR0B/8wXnNIDGpZeZumen8oB/6vcXOplW+97ls9u70kGJKCx9MHANGG3oxZQtIaaJ10BB12D0Ofum4MtLG4Oabb66cl3KH7F8ELvpo+i1N86xm5TGy6d/9daAYU694TI+Tr7VdOdT47lQ56uSTT5Yk7b777sP2iZKOnYLByr5yfjBozsfwfes+/c3f/ODF/fyS9Yus0fz7kUeuUqMh7bffefrYx15T6YPHkEyML86oKhxZbycpyLJP1D5nICq3j0zvnV7OV1xxhSTp9a9/faWNZGgkJhtaFKNEnXlfar9fKAZDjf8oVTPK7+X3kYuxXAT29PRUAlOjEpWsTkafdWT5iOZGJ2sC3wscU87dslYBZVDpdolYPS0OHs+rrx6yQp133nmqw5j6pHkT+uL4xuAAlSYEVo3plNxOfVoGVfCFxYty6aUHSpIuuug/K9u3o55J7bHHbH30o6/WRz/6f5rftQdqVPdpTeYqk/nHf/y/K32IXs6Rr47R2w424Q3BF4DHas6cOc1zMbe9Lpl/tPALLaqIY3SynhB84JaR2lSx8mLDx3K/mQ/N+UV1M/os7fP0fgcffLCkVglL47jjjpMk7bDDDpLaH4Ten/7XyEVg0Gdd9pGLNe9L071f4p/4xB9Kkj70of+q/P6JT+zXPM5FF83Wr361So1Go21+Mf+az4NOghSdTMJ1sS1+OXs8GWPgPlBxjuZwXvcssJGYLGR0dyKRSGwkyMCiKlr0J5NRk5zQglj+31YBLl4omxqltUYFOHw8ih950UZW6YWtrZ9ln4eCCrua/+f4RIpsPhfHkSyeAk5cXDGQktaEKNaEgYR1AYOdmDMXmWT3tDR1ypce05e0L6rNmGQXBgvYS62i9zYXRkEJjFj1CpmTnQn+DLbw5z/8w+sktecw+3yf/vT/Jal1cR2pbeZQmrsZ3e6L8ld/9f9Wju1zX375Gyttph+UVgPqNDMvnWwxyg33zevr5ONLrQnj72jhoDlwY3DBBRdIkm666abKsTuZ0wyab6nl7DlUWmo8JpHmOG80jwPnC60ZfqgwMtq/mym/+c1Duu2+wa1O52vIXGI+pDsFUfF7qd0KRa12zjPeQ97PZuy669RoNLT77rP0t3+7d9tYUS2NLquIQXeKSaDFpLzOPqbnNi0LDASKUnKYmdKpjnEiMV5IJp1IJBIbCS4oWBaSPulIdjdaIJWIXB5RZLIXpHQvMgWPizWmJTobw4tfL1wsEexFWFlsSBpa6Kxdu7aysOeiyb/98pe/lNSKl/Eii5+2BkTkjQt9uz+Ygue2RnEvXGCW20U+Z86BTvEJ7kOnkpVj+pK2D9CRraxmZHZmVlM2zitZXyR3gBfe+3rwORCc5P7e52YAhy+yWa0Dyj7zmddX2mH8r/+1rz7wgdkaGBhQf39/xVdF5uI+XXHFkOKYJ4794Ax6YBoa/aNkKJ54vhnpA2SgkNOCqLpU3jg0hXHyU61sNPA1tN/QD5E6v2rZ7kiPmcFCZbCHt91uu+0qf/tB430931hRi2Y2xg/4Wvse8N8+Hlm+/fK+V+gTjVJHItEFzr2yTx5Xt4X+WeZL+3uPq+eNH5Tc3+D+fMBFKYBGu1ZBdR4zv5rKY2XbaCallcnXkVWzIr/3vHnzatucSIw3kkknEonERoIBZWRTzDlnUB0ZNZlguVhj0CLPaXghQtEgLxC5KGOQIjMKvLijtKoXgY8++qikqgunr69P69ev1+9///uKO4Ln8gJw6dKhfPvIR8xURbfdi2ISI7oC/Uk3KBdzPr/b54VpXeBslHMdZSGwb5GQFjGmL2mvNp124otMhmS2VvoH/Z2jbl1Riz4mwxfHk5vqSGQWVFHy+RgBvXDhWyp/15lN7I9eu3btsHJxnDi+GNdff0jlb15UgzWOGRThm5CVnAyapfy3/aRuVzlxfY1Gqm09Gpx77rmSpC996UuVc3heMKKfjIq++GhcpBZjddwAZRfdX/ePCmK0MPCmJ6tklLf3t6XIlZ587R2EE5k0I6lBMvvS0hFpYfu6U1WL6S0eC6dMGuVDpdFoNNXGPCbRg5XBU9yeL5uotnmUslVuwxcV2X0kRxm98BKJyUIy6UQikdhIOAjyO9/5Tu3vzIP2goLlN1lcpo5JR3rTXFx5wWli4f2i3OBIi8K/2x3FCHQvlu+6665Knw877DCtWrVKzz77bHMBblgG17j//vslSW9605sktRazZu/WI6AvnzndhhecnSLW6Q41ODa8TmUbIsEsHjMKgI2UOIlxeUl75e4B56q/TljAE8O/efVuxsHIaW/PqFiei+HvvAki9SUylzJlwsxhxYoVtdYAn7NkciWiqj6eEGRnTNegiYwX2+NvJuWb1WPL4IvyOtBPSXYbJdyPBraeuB2M2uW1ilSgGLlbRq2TdfnTTNnzjZXEfEzPO+bZ+jjUQedx3BY+EBloRHPccKI65e+sWia1rpn7ZvEaP/i8LUvnRczXpkl/P2PGjIpFovy+Dp0kGnk9eQ9H93QJBmLRMsEYg+g5MB6Wo0RiY5BMOpFIJEaJKI0yypkdTs61bv/yGDwnF/1esHlxTh8z/2b+NCt5+dO/2zUTpWM+8MADbS4Sw8yZ+Pd//3dJLZGfV75yKLXV5MwLMrq46F+PNPk9Fv7dC1WmIxpRpLbUHggZyRuTzUfiUp3S+8blJU3mxlB1r27L/GkzFlYdYoSpV7Y0zbBaFqto0UREUQEOsM/PUP+BgYGmH87BEQYjeyP/Llk9c7ttXmIOLeUVqapmZmRmSr8po3tZWaw8F81vY1H9KoJ90zfeeKOkVgQ2ffJuC9mR5whZbxnHwAAf78t8cPffbSAiX7DnByPyqe7la8tqb1EkdCe9akrtlsyPlpff/OY3kqQnnnhCknThhRdW+nbrrbdKaj3ArMnvPns/+9W32GIL9ff3q7u7W+vXr2+7B6OAmUi6caSfBo9bftfJt29ED1I/w0ZaYCORGC8kk04kEolRgi6Y4URmpJEXE6nzV/I7LjDoQqFvmQtDRnVT+McLP0qtllHbo8Whhx5aaRsZrImPP5lm6U8uxk0u6MYje42KFjGGQIqrD0Z50dQlJxHqRIDG5SXtDvki0kzj1W2pOGZmwUhTd4D+VxaL8DE9gWhyoKmB/jZeFLc9ypctvzMioXlGSPumiGph84aP8p7NnpgfbJC1mUn7RjDTLPtBhaWo8MB44LTTThvRdl/96lcltdrqh4jH0f0qLTVMP/E18PW1Wc1j6+0ZNENZQR+PEce8Zp6HPg+tSrzxec90yiH2Z+mTtrKc4QecLRfEiSeeKEm65pprJLWKfrjWtTXef/azn0mqFjmYNm1ac15FGvM07W6oVnun/ctz0gQZ5ZdHFjQ/VxKJyUYy6UQikRgl6NIiy6L7IpIAjuRfy334NxccXqSyFjPdW6yKZebsBQrVugxGqo8FuEilhre/twuVLjsuplnFzvtx7oZoLAAAHIxJREFU0WxECz/KBJfnjKKyWfglkm32Z7RoNsblJW0G44tIPw/TEqT2iUXdajIH+uLMIHyT0EzRKWGclaM8wM6v9UXq6+urmKjqxONpPmLYP7enSAHZUVQ9zKpV9Gl7/P3JaHr3yd+X7IsR0oySnQo46qijJEnXX3+9pFZb6csvHyKeX7QIRAIEvmb0WTIqm/n3lFakr5oR1VEFsCiamw9Waq2Xfabi2EgrOfmhcdlll0lqzQkz6n322UeS9POf/1xdXV1N3QDOf/YtCu4ZjhmXiMQfynswCuJh9Dbb4OvlF1QqjCWmCpJJJxKJxChhsuCKUFzc0s3GCF9GXLO6U7kNWSeP4cW3wd+jqHC7R/xJ+WZ/svzvWIALOaZfMrDYLjy6PykkxYBNEiNaNozhirxw8clr67bQX85AzqjYDzEuL2lPMJoYqF9cx0Lts/Mgmg14YjBaNir95v2Ym82JylxSt9ESd/40nnvuuWae9MqVK3XRRRc1f3PxbjNYK3uZ8f70pz+V1Lqo7mtUPo3Mh2YSw2Pl4zGK25+e4G6fx6hk0gy04DWcCvjc5z4nqd1CQVNZybjMON0fsj5WbKOZjTe/rxWtJpEZ00UKHCHNyOnoYcHc4Mg37XaUtcHd1kceeURSS3hjpPjABz5Q+XvhwoWSWmO0du1aDQ4OamBgQMuXL297+PjB6E+aCUfqm4581XUm4kh7m38z5sL3/0knnVR7rkRispBMOpFIJEYJp2p9+9vfltQeUEimxzRKkgcGwEpx/WIGNVIwh6w0EnSJ9LLpRmLb/+Iv/qJy3K9//evDjNQQrDzGYxr+nsVeooBLkyvmTTM6nG6hyAcdpTyWYKAvRZhILHntRyqUMy4vaZpTGCHtAS1Dz7mt2aAHty4PVGpPJ6D8m/OrbcJhmsH8+fMlSZdccomklu/S7XCda2uJn3jiibr88sslqcKipXY1rq997WuSWszDbfz1r39d6YsZrs9NxSfmQ3sicnvmjPtvM2xvT53qOmU0MsROPv2JgPN4mQHgtg2X2+19PAaeV0wn8bHMuKMHG2szM17AVgoXDnBEuuFI6qjsIJm6QRYaPWCl9tiD0eLss89u++7OO++UNDxLd/67WT6tGRs6xyJmLbWr9EV64Z4bJ5xwwojOmUhMFpJJJxKJxBiBqXv0X0bVrljdaST+XpasZWBqZPqPtKVLGd0SLMjCBaIXXV4AH3PMMfrZz36mwcFBvfOd76wcy+TH4+Nj2CUY5XgzJ5tup6gaGRevVHxjn8ik665DlMYbiU1F+7nPnTAuL2n6TBmRygjYch8zXupY09HPBH3mOfoieyDMbMwaP/jBD1baaMbiCWfda7fxnHPOGVnnC7zjHe+QJN10002S2tkRFZ8M+7bpj/TN4qCJqKIPI39LH6LUGmOa5Mq2cTwnIk+6E9wWmvWoDkf/cwk+NCPJRIJjy3PbYmMryZIlS4btix9ofGCy6EEUAR2J89eZR4djniXuuOMOSS0rliOd/bkx94DUnv/uPGxbeJh9QP97p/aXD0MG7diiNnfu3I1qeyIx2UgmnUgkEmMEu8XswqJ8LH2mUQUqukGkdqZM0sOyvNEiLVI/o5Qyt2c9acN9KF1I06dPV6PR0C677FLZluNh4sCFGVNomZvNdFUWWIpyu6PI7EhTvQ68llGhIyMqf9opP7rZ9hFttYEwU7NPzI1kXeWSRdAU4JWwJ60ZM3WsuT9X3xx8D+hVV10lqaXR/NrXvlZSi3E7GpcRrhuDU089VVIrr9cR4/ax2jdspuK+m2n4kwXNozrUnthma55w9uubXdCvWoL54h6XyYTbwmpj9FGTjUpVfXKpXUaQvmcKP9Bf6rZ4TB25P5KgGallDWE6TSQpSNNZJD9ZYqRWkEWLFklqlQv0fet7wPPFfbMG+MbmEnd6ODGKnFY0BuCUljs/F0b6AEwkpjqSSScSicQYwQuX++67T1J70KwXV5SR5YKkrkISy+cypzoKIowqbkWMmq6WyN8b6YuX550+fXrlPFyMMtiTbiWPB6Vm6Y/n4pbHi0qVRqI37EuJTi6oqAKasaGa5+PykvZEdXSzBzhixVJc19kge2Lhba+mGf1NpuKLar+bzTHez77FsWDQxPvf/35J0he/+MXKuY1bbrlFUmt8WEObpjEK5PuT6QbUrTbqxOMNsydPqFNOOWXkHR0nePxcSJ6VjqjUVoKBOxQaoOgBH3xRfr5/t0Xm4IMPliR997vfre3De97zHkmtaxTlDEdl7YwoRaS8b2yejFilYx98/T1PGIXNVJzxrrFcF0UuSZ///Ocr7am73smgE5sbkkknEonEGMOLfZat5acXPly0eUFdLqzpk/a2DEKMcn8jZswiRHSTcAFJSVsv6L0oNAGibHLZFpbXJeNlPjSFniKfsxHVg47qfft4DEIlA687B923PAfTAkca1d3s2wZtvYFwVGgkhl76CckozGSYqsBAAQYUcEJ5MphV+pNKUNaDnggw0vSee+6R1OqDmTNNPKxexTQFfvJmpEWjruYuE/LHmzVtDDwn3B/PKwbl8KFWbmMfu8fcY+q5aXgcqEBGS45rMHteRUza2zGAxuCDtJOJkvdN+TurYBG+/r7GBx10kCTpn//5nyW1R1/7YfyXf/mXwx53vJC1nRMvRSSTTiQSiTGGxWq+8Y1vSGpfUJJh021HuWOp3SVIlwxZKP2/XGBGkrOscxwxaLfdbNiLwoGBgeYxli9fXhspTWEmlo6N3JTMQWaQKDW7o3Q+9pWBsRQpqgOj6+sCoss+us9nnnlmeMw6jOtL2hP17rvvltQePl8mzzPAwqAesJkNLwZZolf/3o7ycBHbnAww+IG+ZveJYgNmQEy9iNIXzNA58croWPpqnS8+leCHAgvEM/ijLiLdY80IeB6LuuB8mDKFhAFA7373uyW15v5hhx0mqT3jIXoIRIXloxrmVNKTWpHnxBVXXFFpM5XzjjnmmNr9EonExCOZdCKRSIwTzC6dche55+hmYiR3iYix0Q9r0F/L1DWKLEWCRoxiJrEq3XJ1dZjr+hC1weB4kEGzLGqUN82ocOZ++zqxRjbdSeV3nfLP6YveWNfhhLykGURRaiobzIU0zKS9jxkOo20ZucwJx4AAMvHJBP3trE3sPvii29fPXF+mdZA1cowZ6Sy1bgqfYypGyzqf3EputpqMJNWBfn3GKDBghw8smhb9yfJ93v6P//iPJbUqovl8nXzNBoN++KDkdqUfmkpfBmtmJxKJqYtk0olEIjFOcJDdgw8+KKlFVMhOvciLAmPL7yhiFPlbfWyqbZG107XCdERvxwWlf7dbpexDo9FQT0+PZs6cWVmAmhzZZeVx8ELb5+BiOVI5M/HoZFWIKoeZ/Jmo0HVYR+Y65Xb7d7fdx3aZ2g3FhLykvaJfvHixpHp/HH3HBp3uDKig2cjbR2YOJsFPhehlRsFHYAk0X3yaxNjnOmEEqV3dTWqNx/HHH7+BvZh4WMnNVZbMUuuECRirwNzwTukmFNM3OP980zMC3b5ozu+RKIeV2/FhRRlEV20bDh6X8dACSCQSY4tk0olEIjHO8OLJi0UurBmJ7cVfyaQjn3PkOiExseuGrhlqUBs+NwvVkCg5WNK65c8884z6+vrUaDT0/PPPV/zMXsQ6VzjS3I78vdQJ97GZqmtEvmjmgjNd04TIC9ryOpD0cEHPY7ivw5VzHQ4T+pI+7rjjJLXX1pXaB4PmhmgiMbKXEy8q/ebfzzrrrI3uz1jBCm033HCDpHa1qUhGjsES1NuOyq8Z3t6mJ0l6/PHHR9GTyYEtNVakqiskH/Wd8yP6mzcz55vPZT+vv7fvm1rdkTBFFJQSFQQwHIX/9NNPqxM29mGRSCQmHsmkE4lEYpxxwgknSJLuuusuSS2hGOpvD1eNKdKlrmN75e+RHjYVsiI3Glkri9B4AWpX2Zo1a9RoNNRoNNTX11fx59K/7UUstcsNslT7wcnuWVM78klHeuNRlSz6n8tjdCof6766IM3GYlJe0lb3uv3225vf+WKNlEnTF0gThPerG2Rpaka2uk3UNo8CQjihWCEsEnincMKm4H8eCaxI5XrFJTw2HtvIZNjJ7EWLTMTI+VBhhL7Ba8rgHZ6HliMr5vlBcP7557f1PZFIbLpIJp1IJBIThCOPPFJSS4ksSvGLFmslGDxLta4I9O/yk4pjVChjbjILAtn1MjAwoJUrV9aKJZkJs4gQNbpZ8YtuIxITkzTW5Y7cR/6dZZTp7ipdZ7RcUNHN/XXq8YUXXqjRYFJf0nUM7sorr5TUbqZg8jrzTZkHzVB7/+7958+fP5ZdGRM4J9nayb7IntBM9GffqMrmz5cau/I4Xn755c3v/HBYunSppNbYUcWNpkQyV4LWCm7naxZJCDJHPoriNvw7GfTpp59eu30ikdi0kUw6kUgkJhiO9qZwEZlcCbJLlq41e4xcKP5kuqvb4AUrF4he/NP9RvEkuyxXr16t3t5edXV1aauttqr4mb2vK2VRVIiKX+4LiwmZmJiIUMyKLDfyI1PgiX5+BiBLrfGj69VwNPd73/tejQUmX24rkUgkEolELaYck97Q9BCbx+knMRhEdd555422ieOOLHAwNih9QTZ9e5XrtDO7EiJWYF8V3SgEfVhmI5HcbSfzuVfrZAoWvrHKU5k+l9h0cMopp0iS7rzzzsr3rGxVx6g7pZtGdaUNb2ffKQseUf2LvmrmcpNRWru7rn61n9P0ARtRnjgZLsWt2AYel/szL50R71QaqxPeoriUr4PjDsYKyaQTiUQikZiimHJMekORwgyJkWCkEZZXX321pPZULVpoGPDl1bT9d16Zm5V08o0Z3s4M+ZFHHpG04TVoE5sGrNK1zTbbSGrPmy79w1QUi9IICW9PVsrIaP/Omtf0UZPBU8Fs9uzZ6unp0bp167RixYqKv3jOnDmVtjNvmlHXUQAwU2wj4SZarHjfRmPEwM4yNZNFeWzd+t3vfqfxQDLpRCKRSCSmKDZ5Jp1IjCUcs2DpWkbdElQX8go9KoUZKR5FIiXJoDdvuOzq3XffLamVB0zlrTowLbVTvIQRxT2w/CojpCNhKf9tK8DLXvYy9fT0qLu7W7Nmzaqc31HdthQ4NZIR41GeMn3R9JtHsSNk0D4efdNRym+dlcLH8DHPPvvstm3GAsmkE4lEIpGYokgmnUjUgFGgZL6UoTUbMXN2aUoqSkUVi7xyt0/bvsrESwMubGPfNPWypXbhnEgBjHON+9Hf7U/6mN0GM2TPcfqBWS2rp6dHPT096u3t1dZbb13RFPc29DVHlbuYr8z60lRLo08/UhCL+h75tksm7f97PEZSHnY0SCadSCQSicQURTLpRKIG1i1m/V/WozXz9Yp8l112kdTyLdLXxYIcZD+WgnX50sRLA46FWLx4saSWRaZk0mSN9L8ykjli3NTDjtilP72fWTCtSqyu1Wg01NXVpa6uLk2bNq3iX+/UdvebfnDD39Nvzoh0+umjvGjWhKZymVH22fe879XxlphOJp1IJBKJxBRFMulEogYnnXSSJOlLX/qSpPYobfujrGBmhrDDDjtIal/JRwpj/t2r8/HKtUwkEpsm8iWdSCQSUwTHHXecJOn++++XVC3ewAUfXSZMH+L3LOZBOGCMkqTenhXjyoAwqbUwLU3GNn2Xf5dtc5t8LKZgRWU1jZFWq+P5vB2D4SLhlrJUpV1hxx57bO25xhr5kk4khsEJJ5wgSbr++usltSslOc9z5513ltS5qhEjYg3X4LWmcyKRSEgT5JO+44479KY3vUmzZ8/WIYcc0vb7ww8/rAMPPFCzZ8/WgQceqIcffngimpXYxPEv//IvevOb36ytt95aO+64o+bNm5cFJxKbBR599FE9+uijeu6555r/Vq9erdWrV2vt2rVau3at1q1bp3Xr1mnVqlVatWqVVqxYUfnn7/v6+tTX11cJ5po2bVrz78HBwQqDHBgY0MDAgPr7+9Xf39/8vbe3V729vZo9e7Zmz56tLbfcUltuuaVmzZqlWbNmqbu7u1JYo9FoaGBgoHme8lw8tn9vNBqVfz7mjBkzNGPGDM2cOVMzZ85s9sFt8naG9yc4Bu6L+zB9+nRNnz69eVzDY7527Vo98cQTeuKJJ8bx6lcxIUx622231YIFC/TTn/5U3/rWtyq/rV+/XkcddZQWLFigc845R9dff72OOuoo/fznP69ENiYSxPPPP6+//du/1Vve8hatW7dOc+fO1V//9V/ruuuuG/Nzvf/97x/29y9/+cuSYh80HxjeztWsfv3rX49JOxOJxOaFji/pz3zmM/re975XKal23nnnqaenR1dcccWITnL44YdLkhYtWtT224MPPqj+/n4tWLBAXV1dOv/883XppZfqW9/6lo444oiR9iMxxfHYY4/pDW94g+6//369/vWv1xNPPKH9999fixcvrrWujARz585t/n/27NmaN2+ePvaxj41RixOJyYPlQr/whS80v6NAh10vTKHi9v6dxV78vYMWKW3rFC36tvlJyc2BgYHmonRwcLCSgsWAyk6FZvh3JHHKMeHxKWnK41LohQVznn766eY+J554oiYSHc3dJ554ou67775mFGt/f79uv/12nXTSSTrnnHO09dZb1/7bf//9R9SARx55RPvvv3+Feey///7N6j+JzQN77723Pv3pT+t973ufVq9erdNOO02nnnqqDjnkkDGZR5L0r//6r9pvv/3GsRcxrLJklCa+cm7bLGdT5eOPP67HH39cZ511ls4666zJaHoikZjC6Mikd9ppJ73lLW/Rl7/8Zc2bN0/33XeftttuOx144IE68MADde21146qAStXrmwKPxhbbbXVlPYtHnDAAZPdhE0S8+bN0913362DDjpIXV1duuuuuyRJ11577ajn0Te/+U3dfPPNeuihh8aiqYkRIu+F8YVTASU1rZleDFq4g2yREphk2mbUJdsttzPbJLsk6zS8H89vn7QZeV1beQy6ixi1zU+yejJwSp1SvCSS/3RAqMtQvvvd79ZkYUQ+6VNOOUULFy7UvHnzdOutt1Ymzmix5ZZb6oUXXqh898ILL+hlL3vZmJ1jrDFSM3+iHfPmzdORRx6pz372syOq9GN897vf1dvf/nZJ0u67716xtHzve9/T3LlztXjxYr3mNa8Z8zaPBIzWNphK4r+tzX388cdPQOvGD3kvJBLjixFFdx999NH64Q9/qB//+Me655579L73vU/SkByaI/z4b6Rmx/32208//OEPK76GH/7wh5NmtkyMH1auXKkFCxbojDPO0MUXX9xcpY5kHh188MFauXKlVq5cWXlB/+AHP9CRRx6pG264QYcddtik9CuRmAgce+yxOvbYY5vRxY7eZqS04b8ZBe6/GTm9xRZbaIsttmhGODPK21Hi/p5wRLV90o1GQ319fc3zOPK7/Mdo7/Xr12v9+vVt5+L2diPZzcTobu/n47nPPg/75t/9jHnmmWf0zDPP6Cc/+Yl+8pOfTMj1jTCil/TMmTN13HHHae7cuXrjG9+o3XbbTZJ03XXXNTvFf+WDdGBgQGvXrm1OpLVr1zbNDocccoh6enp01VVXad26dbrmmmskSYceeuhY9zUxybjgggt04IEHatGiRXrnO9/Z1Lwd6TwifvzjH+uII47Q1VdfPanmKEltaS3lg6m7u7v5/Zo1a7RmzRr99re/1W9/+9tJbXMikZj6GHEK1imnnKJFixbphhtu2OCTfOELX9Bpp53W/HvWrFk65ZRTdNNNN2n69OlasmSJzjzzTH3oQx/SvvvuqyVLlmT61WaGr371q7rvvvv0ox/9SJJ02WWX6YADDtA//dM/NS0zG4p//Md/1LJly3TGGWfojDPOkNRuCk8kNjccddRRkqQlS5ZIkubMmSOp5aOOFMUY8Wz/rZXETJwoVWt/rhGlE9ql09/f32S9ZuzcNyr9Sl+0/ef+3tvZvUR1NG7H40btcB+XL18uaYgASNKCBQs02RjxS3q33XbTrFmzNkoK7dRTT9Wpp54a/v66171O//mf/7nBx01sOjjqqKOaDxdpKBbhF7/4xaiOeeONN+rGG28cbdPGBPRJM7XED4Nly5ZJUmXRmkgkEhFG9JIeHBzUZZddpve+9716+ctfPt5tSiQSiUQHHH300ZKkr3zlK5KkXXfdVVJ7PnSnHGKWtHQ0t62ZZtT+pLQtF6SrV69u+o6de00wkpw+brN7B5eydCUj1/1JrW8unt1XR2/702UnHZxqbY+pgI4v6VWrVmnOnDnafffddd99901EmxKJTQ5//ud/PqLt9tlnn3FuSSKR2JzQ8SW9xRZbaOXKlRPRlkQikUhsIN7znvdIkhYvXixpSDhIUjONlWzUbNMs1t+bdTIH2d+bddp1U+Y/S63qUMuXL1dfX58ajYb6+/ub+0ktvzkVvczCfcwoh9v7+W/GLjHV0b+7D2TwLg1rq8RUxIQU2EgkEolEIrHhyFKViUQiMUVxySWX6OKLL9Y3v/nNjn5S16K++eabJUn77ruvJOkVr3iFJLWJB1GZzKy1U3S42az9zf7b0tHOa+7q6tL06dMrllgzaZ+LLJ6lXlk7m4phZsSM+ia8//PPPy9J+tWvfiVp4mpCjwbJpBOJRGIK4rHHHtPixYu10047TXZTEpOIZNKJRCIxCtx+++3NPH1piO39yZ/8iR588MFRHffcc8/Vpz/96WZFrJHilFNOqfx9//33S5J23nlnSa3I6TKvWWqxUvqwzWrt3/V+Tif0p3/fYost1NPTo0ajoRkzZlTyrM2EHYFO5svobLfB+/l3t5H+dWqAk+X/7Gc/k6TK9ZrqSCadSCQSo8Dxxx/fVMh74okntNdee+mEE07Q3//934fV3bbeeuthj/nlL39Z06dP1zve8Y4J6sXYYq+99tLuu+8+2c3YLNDVoHxMIpFIJDYYg4ODOvLII7Xrrrtq4cKFG32clStX6nWve52+8Y1vaM8999Qee+yhRYsWjTp395ZbbpEkvepVr5IkbbPNNpJabNV+XbNYf/p7M277oh0Z7YqF9okbd9xxh6SqYpnV0bbffvvKOQgzZTNtH4OR5WbMbpsjzP355JNPSpKOOeaY2vNsCkgmnUgkEmOAj3zkI1qxYoWuuuqqEe/zm9/8plJQRpI+9rGP6aSTTtKee+45Xk1NbEJIJp1IJBKjxG233aYPfehD+v73v99kiZ/85Cf1yU9+Mtwn0p844IADtHTp0iaLXLZsmbbaait98IMf1Ac/+MExa7OjwHfZZRdJ0lZbbSWpxVLtYyZbffbZZyW1WKrztCNceumlzf974WF1NPvH3Vd/si60fdJugxm4X19mzmb373rXu4Zt06aEDBxLJBKJUeAHP/iBzjvvPH3zm99svqAl6cMf/rA+/OEPb/DxHnjggeZLSZLe8IY36LLLLmtKViZeWkgmnUgkEqPAxRdfrI9//OMVBa6DDz5Y995775gcf6x80iOFfddWLDO7tTrY8ccfP+pz3HrrrZKkV77ylZJaLJ6R5cyHtj/cn2b1ndj8poxk0olEIjEKXHzxxbr44ovH7fiPP/74uB07MfWRTDqRSCQSUwI33HCDpPZ60db/PvvssyenYZOIjO5OJBKJRGKKIpl0IpFIJBJTFMmkE4lEIpGYosiXdCKRSCQSUxT5kk4kEolEYooiX9KJRCKRSExR5Es6kUgkEokpinxJJxKJRCIxRZEv6UQikUgkpijyJZ1IJBKJxBTF/w+p8VA7CFVnTAAAAABJRU5ErkJggg==\n", 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" ] @@ -1842,18 +2792,20 @@ } ], "source": [ - "mask_file = '/media/Data/work/KPE_ROI/binConjunc_PvNxDECxRECxMONxPRI_striatum.nii.gz'\n", - "mask_file = nilearn.image.math_img(\"a>=0.001\", a=mask_file)\n", + "mask_file = '/media/Data/work/caudate_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", "%matplotlib inline\n", "nilearn.plotting.plot_roi(mask_file)\n", "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", - " sessions=None, smoothing_fwhm=4, standardize=False, detrend=False, verbose=5)" + " sessions=None, smoothing_fwhm=None, standardize=False, detrend=False, verbose=5)" ] }, { "cell_type": "code", - "execution_count": 16, - "metadata": {}, + "execution_count": 21, + "metadata": { + "scrolled": true + }, "outputs": [ { "name": "stdout", @@ -1868,7 +2820,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1880,7 +2831,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1892,7 +2842,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1904,7 +2853,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1916,7 +2864,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1928,7 +2875,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1940,7 +2886,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1952,7 +2897,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1964,7 +2908,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1976,7 +2919,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -1988,7 +2930,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -2000,7 +2941,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -2012,7 +2952,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -2024,7 +2963,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -2036,7 +2974,28 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n" ] }, @@ -2054,7 +3013,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -2066,7 +3024,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -2078,7 +3035,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -2090,7 +3046,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -2102,7 +3057,6 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", "[NiftiMasker.fit] Loading data from None\n", @@ -2114,7 +3068,17 @@ " [ 0. , 0. , 2. , -78.5],\n", " [ 0. , 0. , 0. , \n", "[NiftiMasker.transform_single_imgs] Resampling images\n", - "[NiftiMasker.transform_single_imgs] Smoothing images\n", + "[NiftiMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(97, 115, 97, 1),\n", + "affine=array([[ 2. , 0. , 0. , -96.5],\n", + " [ 0. , 2. , 0. , -132.5],\n", + " [ 0. , 0. , 2. , -78.5],\n", + " [ 0. , 0. , 0. , \n", + "[NiftiMasker.transform_single_imgs] Resampling images\n", "[NiftiMasker.transform_single_imgs] Extracting region signals\n", "[NiftiMasker.transform_single_imgs] Cleaning extracted signals\n" ] @@ -2135,22 +3099,22 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Ttest_indResult(statistic=0.6821943858213649, pvalue=0.5033486619831957)" + "Ttest_indResult(statistic=0.18593831440195263, pvalue=0.8541968951546848)" ] }, - "execution_count": 17, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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+ "image/png": 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\n", "text/plain": [ "
" ] @@ -2164,7 +3128,19 @@ "source": [ "df['striatumAc'] = mean_act_st\n", "sns.barplot(x='group',y='striatumAc', data=df, ci=68)\n", - "scipy.stats.ttest_ind(df.striatumAc[df['group']==1], df['striatumAc'][df['group']==0])" + "scipy.stats.ttest_ind(df.striatumAc[df['group']=='ketamine'], df['striatumAc'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "with pm.Model() as model_glm:\n", + " GLM.from_formula('striatumAc ~ groupIdx', df)\n", + " trace_striat = pm.sample()\n", + "pm.summary(trace_striat, credible_interval=.95).round(2)" ] }, { @@ -2176,7 +3152,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 24, "metadata": {}, "outputs": [ { @@ -2254,24 +3230,43 @@ " 'scid_subindmood_feat',\n", " 'scid_ppsy_lifetime',\n", " 'scid_ppsy_pm',\n", + " 'scid_substance_version',\n", " 'scid_alcohol_lifetime',\n", + " 'scid5_alcohol_lifetime',\n", " 'scid_alcohol_pm',\n", + " 'scid5_alcohol_pm',\n", " 'scid_sedative_lifetime',\n", + " 'scid5_sedative_lifetime',\n", " 'scid_sedative_pm',\n", + " 'scid5_sedative_pm',\n", " 'scid_cannabis_lifetime',\n", + " 'scid5_cannabis_lifetime',\n", " 'scid_cannabis_pm',\n", + " 'scid5_cannabis_pm',\n", " 'scid_stimulants_lifetime',\n", + " 'scid5_stimulants_lifetime',\n", " 'scid_stimulants_pm',\n", + " 'scid5_stimulants_pm',\n", " 'scid_opioid_lifetime',\n", + " 'scid5_opioid_lifetime',\n", " 'scid_opioid_pm',\n", + " 'scid5_opioid_pm',\n", " 'scid_cocaine_lifetime',\n", + " 'scid5_cocaine_lifetime',\n", " 'scid_cocaine_pm',\n", + " 'scid5_cocaine_pm',\n", " 'scid_halpcp_lifetime',\n", + " 'scid5_halpcp_lifetime',\n", " 'scid_halpcp_pm',\n", + " 'scid5_halpcp_pm',\n", " 'scid_poly_lifetime',\n", + " 'scid5_poly_lifetime',\n", " 'scid_poly_pm',\n", + " 'scid5_poly_pm',\n", " 'scid_other_lifetime',\n", + " 'scid5_other_lifetime',\n", " 'scid_other_pm',\n", + " 'scid5_other_pm',\n", " 'scid_pd_lifetime',\n", " 'scid_pd_agorap',\n", " 'scid_pd_pm',\n", @@ -2321,8 +3316,10 @@ " 'caps5_b3',\n", " 'caps5_b4',\n", " 'caps5_b5',\n", + " 'caps_sum_btotal',\n", " 'caps5_c1',\n", " 'caps5_c2',\n", + " 'caps_sum_ctotal',\n", " 'caps5_d1',\n", " 'caps5_d2',\n", " 'caps5_d3',\n", @@ -2330,23 +3327,27 @@ " 'caps5_d5',\n", " 'caps5_d6',\n", " 'caps5_d7',\n", + " 'caps_sum_dtotal',\n", " 'caps5_e1',\n", " 'caps5_e2',\n", " 'caps5_e3',\n", " 'caps5_e4',\n", " 'caps5_e5',\n", " 'caps5_e6',\n", + " 'caps_sum_etotal',\n", " 'caps5_ptsd_totals',\n", " 'caps5_total_sx',\n", " 'caps5_duration',\n", " 'caps5_subj_distress',\n", " 'caps5_impair_func',\n", " 'caps5_impair_occup',\n", + " 'caps_sum_gtotal',\n", " 'caps5_gv',\n", " 'caps5_gs',\n", " 'caps5_gi',\n", " 'caps5_deperson',\n", " 'caps5_dereal',\n", + " 'caps_sum_diss',\n", " 'caps5_ptsd',\n", " 'caps5_disssymp',\n", " 'caps5_delayed_onset',\n", @@ -2857,6 +3858,8 @@ " 'rapa_consentdate',\n", " 'rapa_complete',\n", " 'referral_tracking_complete',\n", + " 'appt_date',\n", + " 'appt_age',\n", " 'staix1_1',\n", " 'staix1_2',\n", " 'staix1_3',\n", @@ -2920,6 +3923,7 @@ " 'bdi_19_concentrationdiff',\n", " 'bdi_20_tirednessfatigue',\n", " 'bdi_21_interestinsex',\n", + " 'bdi_total',\n", " 'bdiii_complete',\n", " 'pcl5_1',\n", " 'pcl5_2',\n", @@ -3154,45 +4158,17 @@ " 'ces_4',\n", " 'ces_5',\n", " 'ces_6',\n", - " 'ces_7',\n", - " 'ces_score',\n", - " 'ces_score_auto',\n", - " 'ces_combat_experiences_scale_complete',\n", - " 'scr_pswq_id',\n", - " 'pswq_date',\n", - " 'pswq_1',\n", - " 'pswq_2',\n", - " 'pswq_3',\n", - " 'pswq_4',\n", - " 'pswq_5',\n", - " 'pswq_6',\n", - " 'pswq_7',\n", - " 'pswq_8',\n", - " 'pswq_9',\n", - " 'pswq_10',\n", - " 'pswq_11',\n", - " 'pswq_12',\n", - " 'pswq_13',\n", - " 'pswq_14',\n", - " 'pswq_15',\n", - " 'pswq_16',\n", - " 'pswq_score',\n", - " 'pswq_penn_state_worry_questionnaire_complete',\n", - " 'scr_atrq_id',\n", - " 'scr_atrq_date',\n", - " 'scr_atrq_adep',\n", - " 'scr_atrq_1',\n", " ...]" ] }, - "execution_count": 18, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "## read pcl scores\n", - "pclDf = pd.read_csv('/home/or/Documents/kpe_analyses/KPEIHR0009_DATA_2019-10-07_1121.csv')\n", + "pclDf = pd.read_csv('/home/or/Documents/kpe_analyses/KPEIHR0009_DATA_2020-08-13_1339.csv')\n", "# take only KPE patients\n", "pclDf = pclDf[pclDf['scr_id'].str.startswith('KPE')]\n", "list(pclDf.columns)" @@ -3200,22 +4176,22 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 19, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -3244,7 +4220,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 26, "metadata": {}, "outputs": [ { @@ -3285,135 +4261,821 @@ " \n", " \n", " \n", - " KPE 1560\n", - " NaN\n", - " NaN\n", - " 77.0\n", + " KPE 1237\n", + " NaN\n", + " NaN\n", + " 60.0\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " KPE 1419\n", + " 20.0\n", + " NaN\n", + " 23.0\n", + " 36.0\n", + " 41.0\n", + " \n", + " \n", + " KPE 1560\n", + " NaN\n", + " NaN\n", + " 77.0\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " KPE 1573\n", + " 21.0\n", + " 53.0\n", + " 39.0\n", + " 48.0\n", + " 16.0\n", + " \n", + " \n", + " KPE 1574\n", + " NaN\n", + " NaN\n", + " 37.0\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " \n", + " \n", + " KPE1611\n", + " NaN\n", + " NaN\n", + " 28.0\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " KPE1612\n", + " NaN\n", + " NaN\n", + " 47.0\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " KPE1613\n", + " NaN\n", + " NaN\n", + " 57.0\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " KPE1615\n", + " NaN\n", + " NaN\n", + " 51.0\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " KPE1616\n", + " NaN\n", + " NaN\n", + " 23.0\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + "\n", + "

87 rows × 5 columns

\n", + "" + ], + "text/plain": [ + "redcap_event_name 30Days 90Days Screening Visit1 Visit7\n", + "scr_id \n", + "KPE 1237 NaN NaN 60.0 NaN NaN\n", + "KPE 1419 20.0 NaN 23.0 36.0 41.0\n", + "KPE 1560 NaN NaN 77.0 NaN NaN\n", + "KPE 1573 21.0 53.0 39.0 48.0 16.0\n", + "KPE 1574 NaN NaN 37.0 NaN NaN\n", + "... ... ... ... ... ...\n", + "KPE1611 NaN NaN 28.0 NaN NaN\n", + "KPE1612 NaN NaN 47.0 NaN NaN\n", + "KPE1613 NaN NaN 57.0 NaN NaN\n", + "KPE1615 NaN NaN 51.0 NaN NaN\n", + "KPE1616 NaN NaN 23.0 NaN NaN\n", + "\n", + "[87 rows x 5 columns]" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# reshape it to wide\n", + "df2=dfP_PCL.pivot(index = 'scr_id',columns='redcap_event_name', values='pclTotal')\n", + "list(df2)\n", + "df2 = df2.rename(columns={\"30_day_follow_up_s_arm_1\": \"30Days\", \"90_day_follow_up_s_arm_1\": \"90Days\",\n", + " \"screening_selfrepo_arm_1\": \"Screening\", \"visit_1_arm_1\": \"Visit1\", \n", + " \"visit_7_week_follo_arm_1\": \"Visit7\"})\n", + "#df2['scr_id'] = dfP_PCL['scr_id']\n", + "df2" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Nan\n", + "68.0\n", + "Nan\n", + "32.0\n", + "Nan\n", + "38.0\n", + "Nan\n", + "35.0\n" + ] + }, + { + "data": { + "text/html": [ + "
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scr_idgroupmeanActgroupIdxvmPFChippostriatumAc30Days90DaysScreeningVisit1Visit7days30_1days30_sVisit7_1
0KPE008ketamine3.1901201-0.072546-5.5291552.48344856.049.0NaN58.061.0-2.0NaN3.0
KPE 1565NaN1KPE1223ketamine12.91250219.66234818.528749-10.18174342.049.039.041.050.01.03.09.0
2KPE1253midazolam-17.4411030-7.129313-1.235472-26.71046833.0NaN60.058.063.058.0-30.0-25.0-5.0
3KPE1263midazolam12.12987208.88953821.97941029.35497937.034.021.054.056.0-17.016.02.0
4KPE1293ketamine-20.2331181-7.122487-19.774799-12.4047258.03.033.036.06.0-28.0-25.0-30.0
5KPE1307ketamine-52.2213101-29.786623-28.613234-9.51682045.020.0NaN49.041.0-4.0NaN-8.0
KPE0066KPE1315ketamine5.8963841-1.910045-2.230514-5.855117NaNNaN36.040.038.08.0NaNNaN-30.0
KPE0087KPE1322ketamine13.528724133.13494111.50446113.14192338.027.0NaN56.049.022.0-18.0NaN58.061.0-34.0
KPE1205NaNNaN43.0NaNNaN8KPE1339ketamine-3.3691651-1.105649-3.718665-32.74070446.067.068.068.065.0-22.0-22.0-3.0
..................9KPE1343ketamine-65.0852201-11.860424-50.98640128.12585620.019.032.038.020.0-18.0-12.0-18.0
KPE1548NaN10KPE1351midazolam-18.5520020-25.503946-44.4484714.39323433.025.0NaN43.026.0-10.0NaNNaN-17.0
KPE1549NaN11KPE1356midazolam30.8837200-14.83609713.315349-1.92648352.0NaN61.063.056.0-11.0-9.0-7.0
12KPE1364midazolam56.474892016.96603445.53267345.82691249.052.048.051.042.0-2.01.0-9.0
13KPE1369midazolam26.3963910-45.5105096.881987-45.61096648.049.055.052.031.0-4.0-7.0-21.0
14KPE1387ketamine-13.5788521-11.315875-3.810227-4.81110848.039.032.032.046.016.016.014.0
15KPE1390midazolam7.84772801.090048-3.209616-25.8513576.025.038.038.021.0-32.0-32.0-17.0
16KPE1403midazolam2.05465807.03655725.67226611.8066904.08.017.012.0NaNNaN3.0-8.0-13.0-9.0
KPE1556NaN17KPE1464ketamine-31.1857321-23.971344-56.4882518.19493121.031.035.035.014.0-14.0-14.0-21.0
18KPE1468midazolam27.22140100.56069622.786213-65.921585NaN0.09.028.029.029.0NaNNaN0.0
KPE1561NaN19KPE1480midazolam12.215979025.966124-12.630979-19.501911NaN57.027.031.030.034.0NaNNaN4.0
KPE1563NaN20KPE1499ketamine-53.8379101-47.302711-29.856201-18.45126241.0NaN50.044.064.0NaN-23.0-3.0NaN
21KPE1561midazolam23.159636010.8377893.59905016.30591618.013.057.048.018.0-30.0-39.0-30.0
\n", - "

65 rows × 5 columns

\n", "
" ], "text/plain": [ - "redcap_event_name 30Days 90Days Screening Visit1 Visit7\n", - "scr_id \n", - "KPE 1560 NaN NaN 77.0 NaN NaN\n", - "KPE 1565 NaN NaN 60.0 NaN NaN\n", - "KPE006 NaN NaN 36.0 NaN NaN\n", - "KPE008 56.0 49.0 NaN 58.0 61.0\n", - "KPE1205 NaN NaN 43.0 NaN NaN\n", - "... ... ... ... ... ...\n", - "KPE1548 NaN NaN 43.0 NaN NaN\n", - "KPE1549 NaN NaN 12.0 NaN NaN\n", - "KPE1556 NaN NaN 0.0 NaN NaN\n", - "KPE1561 NaN NaN 57.0 NaN NaN\n", - "KPE1563 NaN NaN 50.0 NaN NaN\n", - "\n", - "[65 rows x 5 columns]" + " scr_id group meanAct groupIdx vmPFC hippo striatumAc \\\n", + "0 KPE008 ketamine 3.190120 1 -0.072546 -5.529155 2.483448 \n", + "1 KPE1223 ketamine 12.912502 1 9.662348 18.528749 -10.181743 \n", + "2 KPE1253 midazolam -17.441103 0 -7.129313 -1.235472 -26.710468 \n", + "3 KPE1263 midazolam 12.129872 0 8.889538 21.979410 29.354979 \n", + "4 KPE1293 ketamine -20.233118 1 -7.122487 -19.774799 -12.404725 \n", + "5 KPE1307 ketamine -52.221310 1 -29.786623 -28.613234 -9.516820 \n", + "6 KPE1315 ketamine 5.896384 1 -1.910045 -2.230514 -5.855117 \n", + "7 KPE1322 ketamine 13.528724 1 33.134941 11.504461 13.141923 \n", + "8 KPE1339 ketamine -3.369165 1 -1.105649 -3.718665 -32.740704 \n", + "9 KPE1343 ketamine -65.085220 1 -11.860424 -50.986401 28.125856 \n", + "10 KPE1351 midazolam -18.552002 0 -25.503946 -44.448471 4.393234 \n", + "11 KPE1356 midazolam 30.883720 0 -14.836097 13.315349 -1.926483 \n", + "12 KPE1364 midazolam 56.474892 0 16.966034 45.532673 45.826912 \n", + "13 KPE1369 midazolam 26.396391 0 -45.510509 6.881987 -45.610966 \n", + "14 KPE1387 ketamine -13.578852 1 -11.315875 -3.810227 -4.811108 \n", + "15 KPE1390 midazolam 7.847728 0 1.090048 -3.209616 -25.851357 \n", + "16 KPE1403 midazolam 2.054658 0 7.036557 25.672266 11.806690 \n", + "17 KPE1464 ketamine -31.185732 1 -23.971344 -56.488251 8.194931 \n", + "18 KPE1468 midazolam 27.221401 0 0.560696 22.786213 -65.921585 \n", + "19 KPE1480 midazolam 12.215979 0 25.966124 -12.630979 -19.501911 \n", + "20 KPE1499 ketamine -53.837910 1 -47.302711 -29.856201 -18.451262 \n", + "21 KPE1561 midazolam 23.159636 0 10.837789 3.599050 16.305916 \n", + "\n", + " 30Days 90Days Screening Visit1 Visit7 days30_1 days30_s Visit7_1 \n", + "0 56.0 49.0 NaN 58.0 61.0 -2.0 NaN 3.0 \n", + "1 42.0 49.0 39.0 41.0 50.0 1.0 3.0 9.0 \n", + "2 33.0 NaN 58.0 63.0 58.0 -30.0 -25.0 -5.0 \n", + "3 37.0 34.0 21.0 54.0 56.0 -17.0 16.0 2.0 \n", + "4 8.0 3.0 33.0 36.0 6.0 -28.0 -25.0 -30.0 \n", + "5 45.0 20.0 NaN 49.0 41.0 -4.0 NaN -8.0 \n", + "6 NaN NaN 40.0 38.0 8.0 NaN NaN -30.0 \n", + "7 38.0 27.0 NaN 56.0 22.0 -18.0 NaN -34.0 \n", + "8 46.0 67.0 68.0 68.0 65.0 -22.0 -22.0 -3.0 \n", + "9 20.0 19.0 32.0 38.0 20.0 -18.0 -12.0 -18.0 \n", + "10 33.0 25.0 NaN 43.0 26.0 -10.0 NaN -17.0 \n", + "11 52.0 NaN 61.0 63.0 56.0 -11.0 -9.0 -7.0 \n", + "12 49.0 52.0 48.0 51.0 42.0 -2.0 1.0 -9.0 \n", + "13 48.0 49.0 55.0 52.0 31.0 -4.0 -7.0 -21.0 \n", + "14 48.0 39.0 32.0 32.0 46.0 16.0 16.0 14.0 \n", + "15 6.0 25.0 38.0 38.0 21.0 -32.0 -32.0 -17.0 \n", + "16 4.0 8.0 17.0 12.0 3.0 -8.0 -13.0 -9.0 \n", + "17 21.0 31.0 35.0 35.0 14.0 -14.0 -14.0 -21.0 \n", + "18 NaN 9.0 28.0 29.0 29.0 NaN NaN 0.0 \n", + "19 NaN 27.0 31.0 30.0 34.0 NaN NaN 4.0 \n", + "20 41.0 NaN 44.0 64.0 NaN -23.0 -3.0 NaN \n", + "21 18.0 13.0 57.0 48.0 18.0 -30.0 -39.0 -30.0 " + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# merging two data frames toghether\n", + "dfTest = pd.merge(df, df2, on = 'scr_id')\n", + "# change visit1 missing values with screening values\n", + "for i in dfTest.iterrows():\n", + " if np.isnan(i[1].Visit1):\n", + " print(\"Nan\")\n", + " print(i[1].Screening)\n", + " dfTest.at[i[0], 'Visit1']= i[1].Screening\n", + "\n", + "# create difference pcl score\n", + "dfTest['days30_1'] = dfTest['30Days'] - dfTest.Visit1\n", + "dfTest['days30_s'] = dfTest['30Days'] - dfTest.Screening\n", + "dfTest['Visit7_1'] = dfTest['Visit7'] - dfTest.Visit1\n", + "dfTest" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(0.16719689115364295, 0.4688204670021354)" ] }, - "execution_count": 20, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" } ], "source": [ - "# reshape it to wide\n", - "df2=dfP_PCL.pivot(index = 'scr_id',columns='redcap_event_name', values='pclTotal')\n", - "list(df2)\n", - "df2 = df2.rename(columns={\"30_day_follow_up_s_arm_1\": \"30Days\", \"90_day_follow_up_s_arm_1\": \"90Days\",\n", - " \"screening_selfrepo_arm_1\": \"Screening\", \"visit_1_arm_1\": \"Visit1\", \n", - " \"visit_7_week_follo_arm_1\": \"Visit7\"})\n", - "#df2['scr_id'] = dfP_PCL['scr_id']\n", - "df2" + "sns.lmplot(x='Visit7', y='meanAct',hue='group', data=dfTest)\n", + "xMask = np.isnan(dfTest['Visit7'])\n", + "yMask = np.isnan(dfTest['meanAct'])\n", + "nas = np.logical_or(xMask, yMask)\n", + "scipy.stats.pearsonr(dfTest['Visit7'][~nas],dfTest['meanAct'][~nas])" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Test difference in amygdala activation between 1st and2nd session and see if it correlates to symtpoms\n", + "dfTest['amg_ses2_ses1'] = dfTest.meanAct - df_ses1.meanAct_ses1" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "ename": "KeyError", + "evalue": "\"['amg_ses2_ses1'] not in index\"", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlmplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'amg_ses2_ses1'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Visit7_1'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mhue\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'group'\u001b[0m\u001b[0;34m,\u001b[0m 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\u001b[0;36mlmplot\u001b[0;34m(x, y, data, hue, col, row, palette, col_wrap, height, aspect, markers, sharex, sharey, hue_order, col_order, row_order, legend, legend_out, x_estimator, x_bins, x_ci, scatter, fit_reg, ci, n_boot, units, order, logistic, lowess, robust, logx, x_partial, y_partial, truncate, x_jitter, y_jitter, scatter_kws, line_kws, size)\u001b[0m\n\u001b[1;32m 549\u001b[0m \u001b[0mneed_cols\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcol\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrow\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0munits\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx_partial\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_partial\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 550\u001b[0m \u001b[0mcols\u001b[0m \u001b[0;34m=\u001b[0m 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"\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2903\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_iterator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2904\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2905\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_listlike_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mraise_missing\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2906\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2907\u001b[0m \u001b[0;31m# take() does not accept boolean indexers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_get_listlike_indexer\u001b[0;34m(self, key, axis, raise_missing)\u001b[0m\n\u001b[1;32m 1252\u001b[0m \u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnew_indexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reindex_non_unique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1253\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1254\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_read_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mraise_missing\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mraise_missing\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1255\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1256\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_validate_read_indexer\u001b[0;34m(self, key, indexer, axis, raise_missing)\u001b[0m\n\u001b[1;32m 1302\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mraise_missing\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1303\u001b[0m \u001b[0mnot_found\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1304\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"{not_found} not in index\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1305\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1306\u001b[0m \u001b[0;31m# we skip the warning on Categorical\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mKeyError\u001b[0m: \"['amg_ses2_ses1'] not in index\"" + ] + } + ], + "source": [ + "sns.lmplot(x='amg_ses2_ses1', y='Visit7_1',hue='group', data=dfTest)\n", + "xMask = np.isnan(dfTest['Visit7_1'])\n", + "yMask = np.isnan(dfTest['amg_ses2_ses1'])\n", + "nas = np.logical_or(xMask, yMask)\n", + "scipy.stats.pearsonr(dfTest['Visit7_1'][~nas],dfTest['amg_ses2_ses1'][~nas])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "### So - change in Hippocampus reactivation to trauma script (vs. relax) is correlated to changes symptoms at end of treatment\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "dfTest" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# lets test correlation per group (although this is a very ver\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "dfTest.corr()\n", + "#sns.heatmap(dfTest)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.figure(figsize=(20,10))\n", + "sns.heatmap(dfTest[dfTest.group==0].corr(), annot=True, cmap=\"coolwarm\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "X = dfTest[['meanAct','hippo', 'group']]\n", + "y = dfTest['days30_1']\n", + "\n", + "X = sm.add_constant(X)\n", + "est = sm.OLS(y, X, missing='drop').fit()\n", + "est.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "smOLS = smf.ols(formula='days30_1 ~ group * meanAct', data=dfTest).fit()\n", + "\n", + "smOLS.summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Check correlation with SCR" + ] + }, + { + "cell_type": "code", + "execution_count": 61, "metadata": {}, "outputs": [ { @@ -3438,471 +5100,379 @@ " \n", " \n", " scr_id\n", - " meanAct\n", - " group\n", - " vmPFC\n", - " hippo\n", - " striatumAc\n", - " 30Days\n", - " 90Days\n", - " Screening\n", - " Visit1\n", - " Visit7\n", - " days30_1\n", - " days30_s\n", + " peakTrauma1\n", + " T_R1\n", + " T_R2\n", + " T_R3\n", + " peakTrauma1_ses2\n", + " T_R1_ses2\n", + " T_R2_ses2\n", + " T_R3_ses2\n", + " TR1_2vs1\n", + " Trauma_2vs1\n", " \n", " \n", " \n", " \n", " 0\n", " KPE008\n", - " -6.946251\n", - " 1.0\n", - " -2.846219\n", - " -4.206524\n", - " -17.900854\n", - " 56.0\n", - " 49.0\n", - " NaN\n", - " 58.0\n", - " 61.0\n", - " -2.0\n", - " NaN\n", + " 0.008409\n", + " 0.001438\n", + " 0.001053\n", + " 0.001252\n", + " 0.029288\n", + " 0.000477\n", + " -0.001506\n", + " -0.001410\n", + " -0.000961\n", + " 0.020879\n", " \n", " \n", " 1\n", " KPE1223\n", - " 8.529267\n", - " 1.0\n", - " -2.804725\n", - " 14.248498\n", - " -0.737637\n", - " 42.0\n", - " 49.0\n", - " 39.0\n", - " 41.0\n", - " 50.0\n", - " 1.0\n", - " 3.0\n", + " 0.780029\n", + " 0.717968\n", + " 0.384221\n", + " 0.100718\n", + " 0.583972\n", + " 0.259239\n", + " 0.458151\n", + " 0.007750\n", + " -0.458729\n", + " -0.196057\n", " \n", " \n", " 2\n", " KPE1253\n", - " -3.683595\n", - " 0.0\n", - " -4.532005\n", - " 15.681519\n", - " -31.282396\n", - " 33.0\n", - " NaN\n", - " 58.0\n", - " 63.0\n", - " 58.0\n", - " -30.0\n", - " -25.0\n", + " 0.265186\n", + " 0.241093\n", + " 0.003840\n", + " 0.003628\n", + " 0.035520\n", + " 0.000500\n", + " -0.136277\n", + " -0.029247\n", + " -0.240594\n", + " -0.229666\n", " \n", " \n", " 3\n", " KPE1263\n", - " 12.874712\n", - " 0.0\n", - " 17.630823\n", - " 23.427145\n", - " 17.346642\n", - " 37.0\n", - " 34.0\n", - " 21.0\n", - " 54.0\n", - " 56.0\n", - " -17.0\n", - " 16.0\n", + " 0.086110\n", + " -0.004309\n", + " 0.013307\n", + " 0.020422\n", + " 0.215977\n", + " 0.002232\n", + " 0.003547\n", + " 0.003662\n", + " 0.006541\n", + " 0.129867\n", " \n", " \n", " 4\n", " KPE1293\n", - " -16.982929\n", - " 1.0\n", - " -5.291761\n", - " -12.896251\n", - " -10.877463\n", - " 8.0\n", - " 3.0\n", - " 33.0\n", - " 36.0\n", - " 6.0\n", - " -28.0\n", - " -25.0\n", + " 0.126689\n", + " 0.110741\n", + " -0.071293\n", + " -0.014922\n", + " 0.266611\n", + " 0.082697\n", + " -0.064094\n", + " -0.000251\n", + " -0.028044\n", + " 0.139922\n", " \n", " \n", " 5\n", " KPE1307\n", - " -26.965698\n", - " 1.0\n", - " -31.102919\n", - " -14.611773\n", - " -6.422866\n", - " 45.0\n", - " 20.0\n", - " NaN\n", - " 49.0\n", - " 41.0\n", - " -4.0\n", - " NaN\n", + " 0.004207\n", + " 0.002910\n", + " 0.000029\n", + " 0.000145\n", + " 0.001569\n", + " 0.000222\n", + " 0.000491\n", + " 0.000080\n", + " -0.002688\n", + " -0.002638\n", " \n", " \n", " 6\n", " KPE1315\n", - " 4.907678\n", - " 1.0\n", - " 0.741474\n", - " -4.181294\n", - " 15.014778\n", - " NaN\n", - " NaN\n", - " 40.0\n", - " 38.0\n", - " 8.0\n", - " NaN\n", - " NaN\n", + " 0.138220\n", + " 0.126930\n", + " -0.123548\n", + " 0.014124\n", + " 0.036497\n", + " -0.007158\n", + " 0.068810\n", + " -0.036000\n", + " -0.134087\n", + " -0.101723\n", " \n", " \n", " 7\n", " KPE1322\n", - " 14.401104\n", - " 1.0\n", - " 41.637451\n", - " 7.759628\n", - " 22.561092\n", - " 38.0\n", - " 27.0\n", - " NaN\n", - " 56.0\n", - " 22.0\n", - " -18.0\n", - " NaN\n", + " 0.001624\n", + " -0.000776\n", + " 0.002179\n", + " 0.000628\n", + " 0.001706\n", + " -0.000454\n", + " -0.002171\n", + " 0.000696\n", + " 0.000323\n", + " 0.000082\n", " \n", " \n", " 8\n", " KPE1339\n", - " 13.274624\n", - " 1.0\n", - " 8.444402\n", - " 9.774380\n", - " -18.798775\n", - " 46.0\n", - " 67.0\n", - " 68.0\n", - " NaN\n", - " 65.0\n", - " NaN\n", - " -22.0\n", + " 0.407656\n", + " 0.299639\n", + " -1.047222\n", + " -0.054400\n", + " 0.059600\n", + " 0.060571\n", + " -0.000934\n", + " -0.017752\n", + " -0.239068\n", + " -0.348056\n", " \n", " \n", " 9\n", " KPE1343\n", - " -75.193253\n", - " 1.0\n", - " -13.703897\n", - " -53.993622\n", - " 31.429287\n", - " 20.0\n", - " 19.0\n", - " 28.0\n", - " 38.0\n", - " 20.0\n", - " -18.0\n", - " -8.0\n", + " 0.280073\n", + " -0.357724\n", + " 0.212229\n", + " 0.084777\n", + " 0.011259\n", + " 0.013012\n", + " -0.129134\n", + " -0.101347\n", + " 0.370736\n", + " -0.268814\n", " \n", " \n", " 10\n", " KPE1351\n", - " -4.254865\n", - " 0.0\n", - " -37.893764\n", - " -37.880573\n", - " 20.151730\n", - " 33.0\n", - " 25.0\n", - " NaN\n", - " NaN\n", - " 26.0\n", - " NaN\n", - " NaN\n", + " 0.001234\n", + " 0.000289\n", + " 0.000949\n", + " 0.000056\n", + " 0.001306\n", + " 0.000073\n", + " -0.000262\n", + " -0.000178\n", + " -0.000216\n", + " 0.000071\n", " \n", " \n", " 11\n", " KPE1356\n", - " 37.194920\n", - " 0.0\n", - " -19.185541\n", - " 15.918907\n", - " 5.486425\n", - " 52.0\n", - " NaN\n", - " 61.0\n", - " 63.0\n", - " 56.0\n", - " -11.0\n", - " -9.0\n", + " 0.052688\n", + " 0.136233\n", + " 0.036890\n", + " 0.105237\n", + " 2.110562\n", + " 1.131081\n", + " 0.127063\n", + " -1.512681\n", + " 0.994849\n", + " 2.057874\n", " \n", " \n", " 12\n", " KPE1364\n", - " 37.733135\n", - " 0.0\n", - " 22.610329\n", - " 32.815807\n", - " 51.587872\n", - " 49.0\n", - " 52.0\n", - " 48.0\n", - " 51.0\n", - " 42.0\n", - " -2.0\n", - " 1.0\n", + " 0.915233\n", + " 0.426590\n", + " -0.516820\n", + " 0.566176\n", + " 2.048961\n", + " 0.781841\n", + " 1.786441\n", + " 1.369894\n", + " 0.355251\n", + " 1.133728\n", " \n", " \n", " 13\n", " KPE1369\n", - " 12.817131\n", - " 0.0\n", - " -64.223045\n", - " 17.741920\n", - " -58.815681\n", - " 48.0\n", - " 49.0\n", - " 55.0\n", - " 52.0\n", - " 31.0\n", - " -4.0\n", - " -7.0\n", + " 0.001491\n", + " -0.000369\n", + " 0.000148\n", + " 0.000289\n", + " 0.007637\n", + " 0.006719\n", + " -0.001052\n", + " 0.003752\n", + " 0.007088\n", + " 0.006146\n", " \n", " \n", " 14\n", " KPE1387\n", - " -7.577533\n", - " 1.0\n", - " -25.509872\n", - " -2.993752\n", - " 8.455001\n", - " 48.0\n", - " 39.0\n", - " 32.0\n", - " NaN\n", - " 46.0\n", - " NaN\n", - " 16.0\n", + " 0.087918\n", + " 0.077212\n", + " 0.024198\n", + " -0.004463\n", + " 0.005663\n", + " -0.007924\n", + " 0.008943\n", + " 0.004053\n", + " -0.085136\n", + " -0.082256\n", " \n", " \n", " 15\n", " KPE1390\n", - " 9.533126\n", - " 0.0\n", - " 0.539426\n", - " -3.722745\n", - " -18.217686\n", - " 6.0\n", - " 25.0\n", - " 38.0\n", - " NaN\n", - " 21.0\n", - " NaN\n", - " -32.0\n", + " 0.298818\n", + " 0.018293\n", + " 0.026366\n", + " 0.086684\n", + " 0.499008\n", + " 0.372015\n", + " 0.033121\n", + " -0.204080\n", + " 0.353721\n", + " 0.200190\n", " \n", " \n", " 16\n", " KPE1403\n", - " 8.639864\n", - " 0.0\n", - " 12.316640\n", - " 32.002499\n", - " -11.029285\n", - " 4.0\n", - " 8.0\n", - " 17.0\n", - " 12.0\n", - " 3.0\n", - " -8.0\n", - " -13.0\n", + " -0.001133\n", + " -0.012253\n", + " -0.004849\n", + " -0.005090\n", + " 0.360719\n", + " 0.327673\n", + " -0.007846\n", + " -0.002575\n", + " 0.339926\n", + " 0.361852\n", " \n", " \n", " 17\n", " KPE1464\n", - " -6.269195\n", - " 1.0\n", - " -31.559772\n", - " -31.806927\n", - " 1.430042\n", - " 21.0\n", - " 31.0\n", - " 35.0\n", - " NaN\n", - " 14.0\n", - " NaN\n", - " -14.0\n", + " 0.946752\n", + " 0.773722\n", + " -0.055203\n", + " -0.007144\n", + " 0.571820\n", + " 0.290042\n", + " -0.471218\n", + " -1.376700\n", + " -0.483680\n", + " -0.374932\n", " \n", " \n", " 18\n", " KPE1468\n", - " 10.638014\n", - " 0.0\n", - " -14.457576\n", - " 16.002533\n", - " -28.563894\n", - " NaN\n", - " 9.0\n", - " 28.0\n", - " 29.0\n", - " 29.0\n", - " NaN\n", - " NaN\n", + " 0.002584\n", + " 0.001163\n", + " 0.000599\n", + " 0.000526\n", + " 0.000673\n", + " -0.002864\n", + " -0.000847\n", + " 0.001938\n", + " -0.004027\n", + " -0.001911\n", " \n", " \n", " 19\n", " KPE1480\n", - " 10.782543\n", - " 0.0\n", - " 23.216175\n", - " -7.493195\n", - " -4.965089\n", - " NaN\n", - " 27.0\n", - " 31.0\n", - " 30.0\n", - " 34.0\n", - " NaN\n", - " NaN\n", + " 0.527992\n", + " 0.548514\n", + " -0.026175\n", + " 0.168836\n", + " 0.080483\n", + " -0.129895\n", + " -0.005818\n", + " -2.657530\n", + " -0.678408\n", + " -0.447508\n", " \n", " \n", " 20\n", " KPE1499\n", - " -59.420677\n", - " 1.0\n", - " -63.349010\n", - " -45.548290\n", - " -7.772642\n", - " 41.0\n", - " NaN\n", - " 44.0\n", - " 64.0\n", - " NaN\n", - " -23.0\n", - " -3.0\n", + " 0.065899\n", + " 0.043608\n", + " -0.002630\n", + " -0.002066\n", + " 0.000996\n", + " -0.000095\n", + " 0.000229\n", + " 0.001317\n", + " -0.043703\n", + " -0.064903\n", " \n", " \n", "\n", "" ], "text/plain": [ - " scr_id meanAct group vmPFC hippo striatumAc 30Days \\\n", - "0 KPE008 -6.946251 1.0 -2.846219 -4.206524 -17.900854 56.0 \n", - "1 KPE1223 8.529267 1.0 -2.804725 14.248498 -0.737637 42.0 \n", - "2 KPE1253 -3.683595 0.0 -4.532005 15.681519 -31.282396 33.0 \n", - "3 KPE1263 12.874712 0.0 17.630823 23.427145 17.346642 37.0 \n", - "4 KPE1293 -16.982929 1.0 -5.291761 -12.896251 -10.877463 8.0 \n", - "5 KPE1307 -26.965698 1.0 -31.102919 -14.611773 -6.422866 45.0 \n", - "6 KPE1315 4.907678 1.0 0.741474 -4.181294 15.014778 NaN \n", - "7 KPE1322 14.401104 1.0 41.637451 7.759628 22.561092 38.0 \n", - "8 KPE1339 13.274624 1.0 8.444402 9.774380 -18.798775 46.0 \n", - "9 KPE1343 -75.193253 1.0 -13.703897 -53.993622 31.429287 20.0 \n", - "10 KPE1351 -4.254865 0.0 -37.893764 -37.880573 20.151730 33.0 \n", - "11 KPE1356 37.194920 0.0 -19.185541 15.918907 5.486425 52.0 \n", - "12 KPE1364 37.733135 0.0 22.610329 32.815807 51.587872 49.0 \n", - "13 KPE1369 12.817131 0.0 -64.223045 17.741920 -58.815681 48.0 \n", - "14 KPE1387 -7.577533 1.0 -25.509872 -2.993752 8.455001 48.0 \n", - "15 KPE1390 9.533126 0.0 0.539426 -3.722745 -18.217686 6.0 \n", - "16 KPE1403 8.639864 0.0 12.316640 32.002499 -11.029285 4.0 \n", - "17 KPE1464 -6.269195 1.0 -31.559772 -31.806927 1.430042 21.0 \n", - "18 KPE1468 10.638014 0.0 -14.457576 16.002533 -28.563894 NaN \n", - "19 KPE1480 10.782543 0.0 23.216175 -7.493195 -4.965089 NaN \n", - "20 KPE1499 -59.420677 1.0 -63.349010 -45.548290 -7.772642 41.0 \n", + " scr_id peakTrauma1 T_R1 T_R2 T_R3 peakTrauma1_ses2 \\\n", + "0 KPE008 0.008409 0.001438 0.001053 0.001252 0.029288 \n", + "1 KPE1223 0.780029 0.717968 0.384221 0.100718 0.583972 \n", + "2 KPE1253 0.265186 0.241093 0.003840 0.003628 0.035520 \n", + "3 KPE1263 0.086110 -0.004309 0.013307 0.020422 0.215977 \n", + "4 KPE1293 0.126689 0.110741 -0.071293 -0.014922 0.266611 \n", + "5 KPE1307 0.004207 0.002910 0.000029 0.000145 0.001569 \n", + "6 KPE1315 0.138220 0.126930 -0.123548 0.014124 0.036497 \n", + "7 KPE1322 0.001624 -0.000776 0.002179 0.000628 0.001706 \n", + "8 KPE1339 0.407656 0.299639 -1.047222 -0.054400 0.059600 \n", + "9 KPE1343 0.280073 -0.357724 0.212229 0.084777 0.011259 \n", + "10 KPE1351 0.001234 0.000289 0.000949 0.000056 0.001306 \n", + "11 KPE1356 0.052688 0.136233 0.036890 0.105237 2.110562 \n", + "12 KPE1364 0.915233 0.426590 -0.516820 0.566176 2.048961 \n", + "13 KPE1369 0.001491 -0.000369 0.000148 0.000289 0.007637 \n", + "14 KPE1387 0.087918 0.077212 0.024198 -0.004463 0.005663 \n", + "15 KPE1390 0.298818 0.018293 0.026366 0.086684 0.499008 \n", + "16 KPE1403 -0.001133 -0.012253 -0.004849 -0.005090 0.360719 \n", + "17 KPE1464 0.946752 0.773722 -0.055203 -0.007144 0.571820 \n", + "18 KPE1468 0.002584 0.001163 0.000599 0.000526 0.000673 \n", + "19 KPE1480 0.527992 0.548514 -0.026175 0.168836 0.080483 \n", + "20 KPE1499 0.065899 0.043608 -0.002630 -0.002066 0.000996 \n", "\n", - " 90Days Screening Visit1 Visit7 days30_1 days30_s \n", - "0 49.0 NaN 58.0 61.0 -2.0 NaN \n", - "1 49.0 39.0 41.0 50.0 1.0 3.0 \n", - "2 NaN 58.0 63.0 58.0 -30.0 -25.0 \n", - "3 34.0 21.0 54.0 56.0 -17.0 16.0 \n", - "4 3.0 33.0 36.0 6.0 -28.0 -25.0 \n", - "5 20.0 NaN 49.0 41.0 -4.0 NaN \n", - "6 NaN 40.0 38.0 8.0 NaN NaN \n", - "7 27.0 NaN 56.0 22.0 -18.0 NaN \n", - "8 67.0 68.0 NaN 65.0 NaN -22.0 \n", - "9 19.0 28.0 38.0 20.0 -18.0 -8.0 \n", - "10 25.0 NaN NaN 26.0 NaN NaN \n", - "11 NaN 61.0 63.0 56.0 -11.0 -9.0 \n", - "12 52.0 48.0 51.0 42.0 -2.0 1.0 \n", - "13 49.0 55.0 52.0 31.0 -4.0 -7.0 \n", - "14 39.0 32.0 NaN 46.0 NaN 16.0 \n", - "15 25.0 38.0 NaN 21.0 NaN -32.0 \n", - "16 8.0 17.0 12.0 3.0 -8.0 -13.0 \n", - "17 31.0 35.0 NaN 14.0 NaN -14.0 \n", - "18 9.0 28.0 29.0 29.0 NaN NaN \n", - "19 27.0 31.0 30.0 34.0 NaN NaN \n", - "20 NaN 44.0 64.0 NaN -23.0 -3.0 " - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# merging two data frames toghether\n", - "dfTest = pd.merge(df, df2, on = 'scr_id')\n", - "# create difference pcl score\n", - "dfTest['days30_1'] = dfTest['30Days'] - dfTest.Visit1\n", - "dfTest['days30_s'] = dfTest['30Days'] - dfTest.Screening\n", - "dfTest" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(-0.0654497646561909, 0.8240838887819125)" + " T_R1_ses2 T_R2_ses2 T_R3_ses2 TR1_2vs1 Trauma_2vs1 \n", + "0 0.000477 -0.001506 -0.001410 -0.000961 0.020879 \n", + "1 0.259239 0.458151 0.007750 -0.458729 -0.196057 \n", + "2 0.000500 -0.136277 -0.029247 -0.240594 -0.229666 \n", + "3 0.002232 0.003547 0.003662 0.006541 0.129867 \n", + "4 0.082697 -0.064094 -0.000251 -0.028044 0.139922 \n", + "5 0.000222 0.000491 0.000080 -0.002688 -0.002638 \n", + "6 -0.007158 0.068810 -0.036000 -0.134087 -0.101723 \n", + "7 -0.000454 -0.002171 0.000696 0.000323 0.000082 \n", + "8 0.060571 -0.000934 -0.017752 -0.239068 -0.348056 \n", + "9 0.013012 -0.129134 -0.101347 0.370736 -0.268814 \n", + "10 0.000073 -0.000262 -0.000178 -0.000216 0.000071 \n", + "11 1.131081 0.127063 -1.512681 0.994849 2.057874 \n", + "12 0.781841 1.786441 1.369894 0.355251 1.133728 \n", + "13 0.006719 -0.001052 0.003752 0.007088 0.006146 \n", + "14 -0.007924 0.008943 0.004053 -0.085136 -0.082256 \n", + "15 0.372015 0.033121 -0.204080 0.353721 0.200190 \n", + "16 0.327673 -0.007846 -0.002575 0.339926 0.361852 \n", + "17 0.290042 -0.471218 -1.376700 -0.483680 -0.374932 \n", + "18 -0.002864 -0.000847 0.001938 -0.004027 -0.001911 \n", + "19 -0.129895 -0.005818 -2.657530 -0.678408 -0.447508 \n", + "20 -0.000095 0.000229 0.001317 -0.043703 -0.064903 " ] }, - "execution_count": 22, + "execution_count": 61, "metadata": {}, "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" } ], "source": [ - "sns.lmplot(x='days30_s', y='vmPFC',hue='group', data=dfTest)\n", - "xMask = np.isnan(dfTest['days30_s'])\n", - "yMask = np.isnan(dfTest['vmPFC'])\n", - "nas = np.logical_or(xMask, yMask)\n", - "scipy.stats.pearsonr(dfTest['days30_s'][~nas],dfTest['vmPFC'][~nas])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# lets test correlation per group (although this is a very very small number)" + "scr = pd.read_csv('/home/or/kpe_task_analysis/scr_deltas.csv')\n", + "scr1 = scr.drop(columns = ['med_cond', 'groupIdx'])\n", + "scr1" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 62, "metadata": {}, "outputs": [ { @@ -3926,264 +5496,485 @@ " \n", " \n", " \n", - " meanAct\n", + " scr_id\n", " group\n", - " vmPFC\n", - " hippo\n", - " striatumAc\n", - " 30Days\n", - " 90Days\n", - " Screening\n", - " Visit1\n", - " Visit7\n", - " days30_1\n", - " days30_s\n", + " meanAct\n", + " groupIdx\n", + " peakTrauma1\n", + " T_R1\n", + " T_R2\n", + " T_R3\n", + " peakTrauma1_ses2\n", + " T_R1_ses2\n", + " T_R2_ses2\n", + " T_R3_ses2\n", + " TR1_2vs1\n", + " Trauma_2vs1\n", " \n", " \n", " \n", " \n", - " meanAct\n", - " 1.000000\n", - " -0.527427\n", - " 0.449946\n", - " 0.818602\n", - " -0.029120\n", - " 0.234423\n", - " 0.383298\n", - " 0.266594\n", - " -0.016831\n", - " 0.259557\n", - " 0.388989\n", - " 0.024823\n", + " 0\n", + " KPE008\n", + " ketamine\n", + " 3.190120\n", + " 1\n", + " 0.008409\n", + " 0.001438\n", + " 0.001053\n", + " 0.001252\n", + " 0.029288\n", + " 0.000477\n", + " -0.001506\n", + " -0.001410\n", + " -0.000961\n", + " 0.020879\n", " \n", " \n", - " group\n", - " -0.527427\n", - " 1.000000\n", - " -0.094559\n", - " -0.482208\n", - " 0.154624\n", - " 0.117299\n", - " 0.150786\n", - " 0.007515\n", - " 0.114304\n", - " -0.060733\n", - " -0.056819\n", - " 0.081032\n", + " 1\n", + " KPE1223\n", + " ketamine\n", + " 12.912502\n", + " 1\n", + " 0.780029\n", + " 0.717968\n", + " 0.384221\n", + " 0.100718\n", + " 0.583972\n", + " 0.259239\n", + " 0.458151\n", + " 0.007750\n", + " -0.458729\n", + " -0.196057\n", " \n", " \n", - " vmPFC\n", - " 0.449946\n", - " -0.094559\n", - " 1.000000\n", - " 0.480782\n", - " 0.396810\n", - " -0.160152\n", - " 0.008088\n", - " -0.238895\n", - " -0.278640\n", - " 0.037655\n", - " -0.008648\n", - " -0.065450\n", + " 2\n", + " KPE1253\n", + " midazolam\n", + " -17.441103\n", + " 0\n", + " 0.265186\n", + " 0.241093\n", + " 0.003840\n", + " 0.003628\n", + " 0.035520\n", + " 0.000500\n", + " -0.136277\n", + " -0.029247\n", + " -0.240594\n", + " -0.229666\n", " \n", " \n", - " hippo\n", - " 0.818602\n", - " -0.482208\n", - " 0.480782\n", - " 1.000000\n", - " -0.174749\n", - " 0.199591\n", - " 0.282015\n", - " 0.146814\n", - " -0.100687\n", - " 0.328689\n", - " 0.361380\n", - " 0.125439\n", + " 3\n", + " KPE1263\n", + " midazolam\n", + " 12.129872\n", + " 0\n", + " 0.086110\n", + " -0.004309\n", + " 0.013307\n", + " 0.020422\n", + " 0.215977\n", + " 0.002232\n", + " 0.003547\n", + " 0.003662\n", + " 0.006541\n", + " 0.129867\n", " \n", " \n", - " striatumAc\n", - " -0.029120\n", - " 0.154624\n", - " 0.396810\n", - " -0.174749\n", - " 1.000000\n", - " 0.036574\n", - " -0.008536\n", - " -0.261465\n", - " 0.022821\n", - " -0.101539\n", - " 0.047667\n", - " 0.471450\n", + " 4\n", + " KPE1293\n", + " ketamine\n", + " -20.233118\n", + " 1\n", + " 0.126689\n", + " 0.110741\n", + " -0.071293\n", + " -0.014922\n", + " 0.266611\n", + " 0.082697\n", + " -0.064094\n", + " -0.000251\n", + " -0.028044\n", + " 0.139922\n", " \n", " \n", - " 30Days\n", - " 0.234423\n", - " 0.117299\n", - " -0.160152\n", - " 0.199591\n", - " 0.036574\n", - " 1.000000\n", - " 0.772183\n", - " 0.602115\n", - " 0.776027\n", - " 0.797502\n", - " 0.486560\n", - " 0.557607\n", + " 5\n", + " KPE1307\n", + " ketamine\n", + " -52.221310\n", + " 1\n", + " 0.004207\n", + " 0.002910\n", + " 0.000029\n", + " 0.000145\n", + " 0.001569\n", + " 0.000222\n", + " 0.000491\n", + " 0.000080\n", + " -0.002688\n", + " -0.002638\n", " \n", " \n", - " 90Days\n", - " 0.383298\n", - " 0.150786\n", - " 0.008088\n", - " 0.282015\n", - " -0.008536\n", - " 0.772183\n", - " 1.000000\n", - " 0.787455\n", - " 0.664047\n", - " 0.779806\n", - " 0.707697\n", - " 0.288786\n", + " 6\n", + " KPE1315\n", + " ketamine\n", + " 5.896384\n", + " 1\n", + " 0.138220\n", + " 0.126930\n", + " -0.123548\n", + " 0.014124\n", + " 0.036497\n", + " -0.007158\n", + " 0.068810\n", + " -0.036000\n", + " -0.134087\n", + " -0.101723\n", " \n", " \n", - " Screening\n", - " 0.266594\n", - " 0.007515\n", - " -0.238895\n", - " 0.146814\n", - " -0.261465\n", - " 0.602115\n", - " 0.787455\n", - " 1.000000\n", - " 0.753638\n", - " 0.561272\n", - " 0.023041\n", - " -0.327020\n", + " 7\n", + " KPE1322\n", + " ketamine\n", + " 13.528724\n", + " 1\n", + " 0.001624\n", + " -0.000776\n", + " 0.002179\n", + " 0.000628\n", + " 0.001706\n", + " -0.000454\n", + " -0.002171\n", + " 0.000696\n", + " 0.000323\n", + " 0.000082\n", " \n", " \n", - " Visit1\n", - " -0.016831\n", - " 0.114304\n", - " -0.278640\n", - " -0.100687\n", - " 0.022821\n", - " 0.776027\n", - " 0.664047\n", - " 0.753638\n", - " 1.000000\n", - " 0.725921\n", - " -0.173426\n", - " 0.164326\n", + " 8\n", + " KPE1339\n", + " ketamine\n", + " -3.369165\n", + " 1\n", + " 0.407656\n", + " 0.299639\n", + " -1.047222\n", + " -0.054400\n", + " 0.059600\n", + " 0.060571\n", + " -0.000934\n", + " -0.017752\n", + " -0.239068\n", + " -0.348056\n", " \n", " \n", - " Visit7\n", - " 0.259557\n", - " -0.060733\n", - " 0.037655\n", - " 0.328689\n", - " -0.101539\n", - " 0.797502\n", - " 0.779806\n", - " 0.561272\n", - " 0.725921\n", - " 1.000000\n", - " 0.230600\n", - " 0.333663\n", + " 9\n", + " KPE1343\n", + " ketamine\n", + " -65.085220\n", + " 1\n", + " 0.280073\n", + " -0.357724\n", + " 0.212229\n", + " 0.084777\n", + " 0.011259\n", + " 0.013012\n", + " -0.129134\n", + " -0.101347\n", + " 0.370736\n", + " -0.268814\n", " \n", " \n", - " days30_1\n", - " 0.388989\n", - " -0.056819\n", - " -0.008648\n", - " 0.361380\n", - " 0.047667\n", - " 0.486560\n", - " 0.707697\n", - " 0.023041\n", - " -0.173426\n", - " 0.230600\n", - " 1.000000\n", - " 0.525243\n", + " 10\n", + " KPE1351\n", + " midazolam\n", + " -18.552002\n", + " 0\n", + " 0.001234\n", + " 0.000289\n", + " 0.000949\n", + " 0.000056\n", + " 0.001306\n", + " 0.000073\n", + " -0.000262\n", + " -0.000178\n", + " -0.000216\n", + " 0.000071\n", " \n", " \n", - " days30_s\n", - " 0.024823\n", - " 0.081032\n", - " -0.065450\n", - " 0.125439\n", - " 0.471450\n", - " 0.557607\n", - " 0.288786\n", - " -0.327020\n", - " 0.164326\n", - " 0.333663\n", - " 0.525243\n", - " 1.000000\n", + " 11\n", + " KPE1356\n", + " midazolam\n", + " 30.883720\n", + " 0\n", + " 0.052688\n", + " 0.136233\n", + " 0.036890\n", + " 0.105237\n", + " 2.110562\n", + " 1.131081\n", + " 0.127063\n", + " -1.512681\n", + " 0.994849\n", + " 2.057874\n", + " \n", + " \n", + " 12\n", + " KPE1364\n", + " midazolam\n", + " 56.474892\n", + " 0\n", + " 0.915233\n", + " 0.426590\n", + " -0.516820\n", + " 0.566176\n", + " 2.048961\n", + " 0.781841\n", + " 1.786441\n", + " 1.369894\n", + " 0.355251\n", + " 1.133728\n", + " \n", + " \n", + " 13\n", + " KPE1369\n", + " midazolam\n", + " 26.396391\n", + " 0\n", + " 0.001491\n", + " -0.000369\n", + " 0.000148\n", + " 0.000289\n", + " 0.007637\n", + " 0.006719\n", + " -0.001052\n", + " 0.003752\n", + " 0.007088\n", + " 0.006146\n", + " \n", + " \n", + " 14\n", + " KPE1387\n", + " ketamine\n", + " -13.578852\n", + " 1\n", + " 0.087918\n", + " 0.077212\n", + " 0.024198\n", + " -0.004463\n", + " 0.005663\n", + " -0.007924\n", + " 0.008943\n", + " 0.004053\n", + " -0.085136\n", + " -0.082256\n", + " \n", + " \n", + " 15\n", + " KPE1390\n", + " midazolam\n", + " 7.847728\n", + " 0\n", + " 0.298818\n", + " 0.018293\n", + " 0.026366\n", + " 0.086684\n", + " 0.499008\n", + " 0.372015\n", + " 0.033121\n", + " -0.204080\n", + " 0.353721\n", + " 0.200190\n", + " \n", + " \n", + " 16\n", + " KPE1403\n", + " midazolam\n", + " 2.054658\n", + " 0\n", + " -0.001133\n", + " -0.012253\n", + " -0.004849\n", + " -0.005090\n", + " 0.360719\n", + " 0.327673\n", + " -0.007846\n", + " -0.002575\n", + " 0.339926\n", + " 0.361852\n", + " \n", + " \n", + " 17\n", + " KPE1464\n", + " ketamine\n", + " -31.185732\n", + " 1\n", + " 0.946752\n", + " 0.773722\n", + " -0.055203\n", + " -0.007144\n", + " 0.571820\n", + " 0.290042\n", + " -0.471218\n", + " -1.376700\n", + " -0.483680\n", + " -0.374932\n", + " \n", + " \n", + " 18\n", + " KPE1468\n", + " midazolam\n", + " 27.221401\n", + " 0\n", + " 0.002584\n", + " 0.001163\n", + " 0.000599\n", + " 0.000526\n", + " 0.000673\n", + " -0.002864\n", + " -0.000847\n", + " 0.001938\n", + " -0.004027\n", + " -0.001911\n", + " \n", + " \n", + " 19\n", + " KPE1480\n", + " midazolam\n", + " 12.215979\n", + " 0\n", + " 0.527992\n", + " 0.548514\n", + " -0.026175\n", + " 0.168836\n", + " 0.080483\n", + " -0.129895\n", + " -0.005818\n", + " -2.657530\n", + " -0.678408\n", + " -0.447508\n", + " \n", + " \n", + " 20\n", + " KPE1499\n", + " ketamine\n", + " -53.837910\n", + " 1\n", + " 0.065899\n", + " 0.043608\n", + " -0.002630\n", + " -0.002066\n", + " 0.000996\n", + " -0.000095\n", + " 0.000229\n", + " 0.001317\n", + " -0.043703\n", + " -0.064903\n", " \n", " \n", "\n", "" ], "text/plain": [ - " meanAct group vmPFC hippo striatumAc 30Days \\\n", - "meanAct 1.000000 -0.527427 0.449946 0.818602 -0.029120 0.234423 \n", - "group -0.527427 1.000000 -0.094559 -0.482208 0.154624 0.117299 \n", - "vmPFC 0.449946 -0.094559 1.000000 0.480782 0.396810 -0.160152 \n", - "hippo 0.818602 -0.482208 0.480782 1.000000 -0.174749 0.199591 \n", - "striatumAc -0.029120 0.154624 0.396810 -0.174749 1.000000 0.036574 \n", - "30Days 0.234423 0.117299 -0.160152 0.199591 0.036574 1.000000 \n", - "90Days 0.383298 0.150786 0.008088 0.282015 -0.008536 0.772183 \n", - "Screening 0.266594 0.007515 -0.238895 0.146814 -0.261465 0.602115 \n", - "Visit1 -0.016831 0.114304 -0.278640 -0.100687 0.022821 0.776027 \n", - "Visit7 0.259557 -0.060733 0.037655 0.328689 -0.101539 0.797502 \n", - "days30_1 0.388989 -0.056819 -0.008648 0.361380 0.047667 0.486560 \n", - "days30_s 0.024823 0.081032 -0.065450 0.125439 0.471450 0.557607 \n", + " scr_id group meanAct groupIdx peakTrauma1 T_R1 T_R2 \\\n", + "0 KPE008 ketamine 3.190120 1 0.008409 0.001438 0.001053 \n", + "1 KPE1223 ketamine 12.912502 1 0.780029 0.717968 0.384221 \n", + "2 KPE1253 midazolam -17.441103 0 0.265186 0.241093 0.003840 \n", + "3 KPE1263 midazolam 12.129872 0 0.086110 -0.004309 0.013307 \n", + "4 KPE1293 ketamine -20.233118 1 0.126689 0.110741 -0.071293 \n", + "5 KPE1307 ketamine -52.221310 1 0.004207 0.002910 0.000029 \n", + "6 KPE1315 ketamine 5.896384 1 0.138220 0.126930 -0.123548 \n", + "7 KPE1322 ketamine 13.528724 1 0.001624 -0.000776 0.002179 \n", + "8 KPE1339 ketamine -3.369165 1 0.407656 0.299639 -1.047222 \n", + "9 KPE1343 ketamine -65.085220 1 0.280073 -0.357724 0.212229 \n", + "10 KPE1351 midazolam -18.552002 0 0.001234 0.000289 0.000949 \n", + "11 KPE1356 midazolam 30.883720 0 0.052688 0.136233 0.036890 \n", + "12 KPE1364 midazolam 56.474892 0 0.915233 0.426590 -0.516820 \n", + "13 KPE1369 midazolam 26.396391 0 0.001491 -0.000369 0.000148 \n", + "14 KPE1387 ketamine -13.578852 1 0.087918 0.077212 0.024198 \n", + "15 KPE1390 midazolam 7.847728 0 0.298818 0.018293 0.026366 \n", + "16 KPE1403 midazolam 2.054658 0 -0.001133 -0.012253 -0.004849 \n", + "17 KPE1464 ketamine -31.185732 1 0.946752 0.773722 -0.055203 \n", + "18 KPE1468 midazolam 27.221401 0 0.002584 0.001163 0.000599 \n", + "19 KPE1480 midazolam 12.215979 0 0.527992 0.548514 -0.026175 \n", + "20 KPE1499 ketamine -53.837910 1 0.065899 0.043608 -0.002630 \n", "\n", - " 90Days Screening Visit1 Visit7 days30_1 days30_s \n", - "meanAct 0.383298 0.266594 -0.016831 0.259557 0.388989 0.024823 \n", - "group 0.150786 0.007515 0.114304 -0.060733 -0.056819 0.081032 \n", - "vmPFC 0.008088 -0.238895 -0.278640 0.037655 -0.008648 -0.065450 \n", - "hippo 0.282015 0.146814 -0.100687 0.328689 0.361380 0.125439 \n", - "striatumAc -0.008536 -0.261465 0.022821 -0.101539 0.047667 0.471450 \n", - "30Days 0.772183 0.602115 0.776027 0.797502 0.486560 0.557607 \n", - "90Days 1.000000 0.787455 0.664047 0.779806 0.707697 0.288786 \n", - "Screening 0.787455 1.000000 0.753638 0.561272 0.023041 -0.327020 \n", - "Visit1 0.664047 0.753638 1.000000 0.725921 -0.173426 0.164326 \n", - "Visit7 0.779806 0.561272 0.725921 1.000000 0.230600 0.333663 \n", - "days30_1 0.707697 0.023041 -0.173426 0.230600 1.000000 0.525243 \n", - "days30_s 0.288786 -0.327020 0.164326 0.333663 0.525243 1.000000 " + " T_R3 peakTrauma1_ses2 T_R1_ses2 T_R2_ses2 T_R3_ses2 TR1_2vs1 \\\n", + "0 0.001252 0.029288 0.000477 -0.001506 -0.001410 -0.000961 \n", + "1 0.100718 0.583972 0.259239 0.458151 0.007750 -0.458729 \n", + "2 0.003628 0.035520 0.000500 -0.136277 -0.029247 -0.240594 \n", + "3 0.020422 0.215977 0.002232 0.003547 0.003662 0.006541 \n", + "4 -0.014922 0.266611 0.082697 -0.064094 -0.000251 -0.028044 \n", + "5 0.000145 0.001569 0.000222 0.000491 0.000080 -0.002688 \n", + "6 0.014124 0.036497 -0.007158 0.068810 -0.036000 -0.134087 \n", + "7 0.000628 0.001706 -0.000454 -0.002171 0.000696 0.000323 \n", + "8 -0.054400 0.059600 0.060571 -0.000934 -0.017752 -0.239068 \n", + "9 0.084777 0.011259 0.013012 -0.129134 -0.101347 0.370736 \n", + "10 0.000056 0.001306 0.000073 -0.000262 -0.000178 -0.000216 \n", + "11 0.105237 2.110562 1.131081 0.127063 -1.512681 0.994849 \n", + "12 0.566176 2.048961 0.781841 1.786441 1.369894 0.355251 \n", + "13 0.000289 0.007637 0.006719 -0.001052 0.003752 0.007088 \n", + "14 -0.004463 0.005663 -0.007924 0.008943 0.004053 -0.085136 \n", + "15 0.086684 0.499008 0.372015 0.033121 -0.204080 0.353721 \n", + "16 -0.005090 0.360719 0.327673 -0.007846 -0.002575 0.339926 \n", + "17 -0.007144 0.571820 0.290042 -0.471218 -1.376700 -0.483680 \n", + "18 0.000526 0.000673 -0.002864 -0.000847 0.001938 -0.004027 \n", + "19 0.168836 0.080483 -0.129895 -0.005818 -2.657530 -0.678408 \n", + "20 -0.002066 0.000996 -0.000095 0.000229 0.001317 -0.043703 \n", + "\n", + " Trauma_2vs1 \n", + "0 0.020879 \n", + "1 -0.196057 \n", + "2 -0.229666 \n", + "3 0.129867 \n", + "4 0.139922 \n", + "5 -0.002638 \n", + "6 -0.101723 \n", + "7 0.000082 \n", + "8 -0.348056 \n", + "9 -0.268814 \n", + "10 0.000071 \n", + "11 2.057874 \n", + "12 1.133728 \n", + "13 0.006146 \n", + "14 -0.082256 \n", + "15 0.200190 \n", + "16 0.361852 \n", + "17 -0.374932 \n", + "18 -0.001911 \n", + "19 -0.447508 \n", + "20 -0.064903 " ] }, - "execution_count": 23, + "execution_count": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "dfTest.corr()" + "dfMerge = pd.merge(df, scr1)\n", + "dfMerge" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 63, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 24, + "execution_count": 63, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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" ] }, "metadata": { @@ -4193,247 +5984,64 @@ } ], "source": [ - "plt.figure(figsize=(20,10))\n", - "sns.heatmap(dfTest[dfTest.group==0].corr(), annot=True, cmap=\"coolwarm\")" + "sns.lmplot(x = 'Trauma_2vs1', y= 'meanAct',hue = 'group', data=dfMerge)" ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/scipy/stats/stats.py:1535: UserWarning: kurtosistest only valid for n>=20 ... continuing anyway, n=13\n", - " \"anyway, n=%i\" % int(n))\n" - ] - }, - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - " \n", - "\n", - "\n", - " \n", - "\n", - "\n", - " \n", - "\n", - "\n", - " \n", - "\n", - "\n", - " \n", - "\n", - "\n", - " \n", - "\n", - "\n", - " \n", - "\n", - "\n", - " \n", - "\n", - "\n", - " \n", - "\n", - "
OLS Regression Results
Dep. Variable: days30_1 R-squared: 0.228
Model: OLS Adj. R-squared: -0.029
Method: Least Squares F-statistic: 0.8871
Date: Wed, 27 May 2020 Prob (F-statistic): 0.484
Time: 20:38:34 Log-Likelihood: -46.731
No. Observations: 13 AIC: 101.5
Df Residuals: 9 BIC: 103.7
Df Model: 3
Covariance Type: nonrobust
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coef std err t P>|t| [0.025 0.975]
const -17.1182 6.371 -2.687 0.025 -31.529 -2.707
meanAct 0.0757 0.264 0.287 0.780 -0.521 0.672
hippo 0.1651 0.364 0.453 0.661 -0.659 0.989
group 8.3105 8.779 0.947 0.369 -11.549 28.170
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Omnibus: 2.218 Durbin-Watson: 2.178
Prob(Omnibus): 0.330 Jarque-Bera (JB): 1.572
Skew: -0.695 Prob(JB): 0.456
Kurtosis: 2.014 Cond. No. 146.


Warnings:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified." - ], - "text/plain": [ - "\n", - "\"\"\"\n", - " OLS Regression Results \n", - "==============================================================================\n", - "Dep. Variable: days30_1 R-squared: 0.228\n", - "Model: OLS Adj. R-squared: -0.029\n", - "Method: Least Squares F-statistic: 0.8871\n", - "Date: Wed, 27 May 2020 Prob (F-statistic): 0.484\n", - "Time: 20:38:34 Log-Likelihood: -46.731\n", - "No. Observations: 13 AIC: 101.5\n", - "Df Residuals: 9 BIC: 103.7\n", - "Df Model: 3 \n", - "Covariance Type: nonrobust \n", - "==============================================================================\n", - " coef std err t P>|t| [0.025 0.975]\n", - "------------------------------------------------------------------------------\n", - "const -17.1182 6.371 -2.687 0.025 -31.529 -2.707\n", - "meanAct 0.0757 0.264 0.287 0.780 -0.521 0.672\n", - "hippo 0.1651 0.364 0.453 0.661 -0.659 0.989\n", - "group 8.3105 8.779 0.947 0.369 -11.549 28.170\n", - "==============================================================================\n", - "Omnibus: 2.218 Durbin-Watson: 2.178\n", - "Prob(Omnibus): 0.330 Jarque-Bera (JB): 1.572\n", - "Skew: -0.695 Prob(JB): 0.456\n", - "Kurtosis: 2.014 Cond. No. 146.\n", - "==============================================================================\n", - "\n", - "Warnings:\n", - "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n", - "\"\"\"" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "import statsmodels.api as sm\n", - "import statsmodels.formula.api as smf\n", - "X = dfTest[['meanAct','hippo', 'group']]\n", - "y = dfTest['days30_1']\n", + "smOLS = smf.ols(formula='Trauma_2vs1 ~ group * meanAct', data=dfMerge).fit()\n", "\n", - "X = sm.add_constant(X)\n", - "est = sm.OLS(y, X, missing='drop').fit()\n", - "est.summary()" + "smOLS.summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Check changes in amg activation and SCR / PCL" ] }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 64, "metadata": {}, "outputs": [ { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - " \n", - "\n", - "\n", - " \n", - "\n", - "\n", - " \n", - "\n", - "\n", - " \n", - "\n", - "\n", - " \n", - "\n", - "\n", - " \n", - "\n", - "\n", - " \n", - "\n", - "\n", - " \n", - "\n", - "\n", - " \n", - "\n", - "
OLS Regression Results
Dep. Variable: days30_1 R-squared: 0.273
Model: OLS Adj. R-squared: 0.030
Method: Least Squares F-statistic: 1.124
Date: Thu, 28 May 2020 Prob (F-statistic): 0.390
Time: 14:31:26 Log-Likelihood: -46.346
No. Observations: 13 AIC: 100.7
Df Residuals: 9 BIC: 103.0
Df Model: 3
Covariance Type: nonrobust
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coef std err t P>|t| [0.025 0.975]
Intercept -19.1213 6.444 -2.967 0.016 -33.698 -4.545
group 9.1770 8.065 1.138 0.285 -9.068 27.422
meanAct 0.4047 0.278 1.456 0.179 -0.224 1.033
group:meanAct -0.2670 0.305 -0.876 0.404 -0.956 0.422
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Omnibus: 2.247 Durbin-Watson: 2.251
Prob(Omnibus): 0.325 Jarque-Bera (JB): 1.058
Skew: -0.273 Prob(JB): 0.589
Kurtosis: 1.714 Cond. No. 144.


Warnings:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified." - ], - "text/plain": [ - "\n", - "\"\"\"\n", - " OLS Regression Results \n", - "==============================================================================\n", - "Dep. Variable: days30_1 R-squared: 0.273\n", - "Model: OLS Adj. R-squared: 0.030\n", - "Method: Least Squares F-statistic: 1.124\n", - "Date: Thu, 28 May 2020 Prob (F-statistic): 0.390\n", - "Time: 14:31:26 Log-Likelihood: -46.346\n", - "No. Observations: 13 AIC: 100.7\n", - "Df Residuals: 9 BIC: 103.0\n", - "Df Model: 3 \n", - "Covariance Type: nonrobust \n", - "=================================================================================\n", - " coef std err t P>|t| [0.025 0.975]\n", - "---------------------------------------------------------------------------------\n", - "Intercept -19.1213 6.444 -2.967 0.016 -33.698 -4.545\n", - "group 9.1770 8.065 1.138 0.285 -9.068 27.422\n", - "meanAct 0.4047 0.278 1.456 0.179 -0.224 1.033\n", - "group:meanAct -0.2670 0.305 -0.876 0.404 -0.956 0.422\n", - "==============================================================================\n", - "Omnibus: 2.247 Durbin-Watson: 2.251\n", - "Prob(Omnibus): 0.325 Jarque-Bera (JB): 1.058\n", - "Skew: -0.273 Prob(JB): 0.589\n", - "Kurtosis: 1.714 Cond. No. 144.\n", - "==============================================================================\n", - "\n", - "Warnings:\n", - "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n", - "\"\"\"" - ] - }, - "execution_count": 36, - "metadata": {}, - "output_type": "execute_result" + "ename": "NameError", + "evalue": "name 'df_ses1' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdfMerge\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'amg_2_1'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdfMerge\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmeanAct\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mdf_ses1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmeanAct_ses1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;31mNameError\u001b[0m: name 'df_ses1' is not defined" + ] } ], "source": [ - "smOLS = smf.ols(formula='days30_1 ~ group * meanAct', data=dfTest).fit()\n", + "dfMerge['amg_2_1'] = dfMerge.meanAct - df_ses1.meanAct_ses1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.lmplot(x='Trauma_2vs1', y = 'amg_2_1', hue='group', data=dfMerge)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "smOLS = smf.ols(formula='Trauma_2vs1 ~ group * amg_2_1', data=dfMerge).fit()\n", "\n", "smOLS.summary()" ] diff --git a/task_based_analysis/average_Comp_ROIs_DiFuMo.ipynb b/task_based_analysis/average_Comp_ROIs_DiFuMo.ipynb new file mode 100644 index 0000000..09e8ce3 --- /dev/null +++ b/task_based_analysis/average_Comp_ROIs_DiFuMo.ipynb @@ -0,0 +1,2352 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Comparing Ketamine and Midazolam after treatment in ROIs\n", + "- focus on end of treatment\n", + "- Amygdala\n", + "- vmPFC\n", + "- Hippocampus" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# import relevant packages\n", + "import glob\n", + "import numpy as np\n", + "import scipy\n", + "import nilearn\n", + "import nilearn.image\n", + "import nilearn.plotting\n", + "import nilearn.input_data\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import pandas as pd\n", + "import pymc3 as pm\n", + "import arviz as az\n", + "import dask\n", + "import statsmodels.api as sm\n", + "import statsmodels.formula.api as smf" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_008/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1223/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1263/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1293/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1307/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1322/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1339/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1343/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1351/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1356/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1364/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1369/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1387/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1390/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1403/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1419/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1464/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1499/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1561/modelestimate/results/cope7.nii.gz',\n", + " '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_1578/modelestimate/results/cope7.nii.gz']" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Set session\n", + "ses = 3\n", + "## Grab group\n", + "# compare between groups\n", + "\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "scr_id = medication_cond.scr_id\n", + "func_files = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses%s/modelfit/_subject_id_*/modelestimate/results/cope7.nii.gz' %(ses))\n", + "#func_files = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/allScript_ses%s/modelfit_ses_%s/_subject_id_*/modelestimate/mapflow/_modelestimate0/results/cope2.nii.gz' %(ses, ses))\n", + "\n", + "func_files.sort()\n", + "func_files" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 KPE008\n", + "1 KPE1223\n", + "2 KPE1253\n", + "3 KPE1263\n", + "4 KPE1293\n", + "5 KPE1307\n", + "6 KPE1315\n", + "7 KPE1322\n", + "8 KPE1339\n", + "9 KPE1343\n", + "10 KPE1351\n", + "11 KPE1356\n", + "12 KPE1364\n", + "13 KPE1369\n", + "14 KPE1387\n", + "15 KPE1390\n", + "16 KPE1403\n", + "17 KPE1419\n", + "18 KPE1464\n", + "19 KPE1468\n", + "20 KPE1480\n", + "21 KPE1499\n", + "22 KPE1561\n", + "23 KPE1573\n", + "24 KPE1578\n", + "Name: scr_id, dtype: object" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "scr_id" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nilearn/plotting/displays.py:99: UserWarning: No contour levels were found within the data range.\n", + " **kwargs)\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "maps_img = '/media/Data/work/DiFuMo_atlas/256/maps.nii.gz'\n", + "labels = pd.read_csv('/media/Data/work/DiFuMo_atlas/256/labels_256_dictionary.csv')\n", + "#coords = nilearn.plotting.find_parcellation_cut_coords(labels_img=maps_img)\n", + "#coords = nilearn.plotting.find_probabilistic_atlas_cut_coords(maps_img)\n", + "# plot atlas (only if we want)\n", + "nilearn.plotting.plot_prob_atlas(maps_img, draw_cross=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMapsMasker.fit] loading regions from /media/Data/work/DiFuMo_atlas/256/maps.nii.gz\n" + ] + } + ], + "source": [ + "masker = nilearn.input_data.NiftiMapsMasker(maps_img=maps_img, \n", + " verbose=2, standardize=True).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMapsMasker.transform_single_imgs] Loading data from [/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_results/fsl_analysis_ses3/modelfit/_subject_id_008/modelestimate/results/cope7.nii.gz, /media/Data/Lab_Projects/KPE_PTSD_Project/neuroimagin\n", + "[NiftiMapsMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiMapsMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + } + ], + "source": [ + "t_maps3 = masker.transform(func_files)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(24, 256)" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "t_maps2.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "# extract relevant ROIs (vmpfc, hippo, amygdala)\n", + "labels_list = list(labels.Difumo_names)\n", + "amg = labels_list.index('Amygdala')\n", + "hippo_post = labels_list.index('Hippocampus posterior')\n", + "hippo_ant = labels_list.index('Hippocampus anterior')\n", + "vmPFC_ant = labels_list.index('Ventromedial prefrontal cortex anterior')\n", + "vmPFC = labels_list.index('Ventromedial prefrontal cortex')\n", + "index_list = np.array([amg, hippo_post, hippo_ant, vmPFC_ant, vmPFC])" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(25, 5)" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ses1_ROIs = t_maps1[: ,index_list]\n", + "ses1_ROIs.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(20, 5)" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ses3_ROIs = t_maps3[: ,index_list]\n", + "ses3_ROIs.shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(24, 5)" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ses2_ROIs = t_maps2[: ,index_list]\n", + "ses2_ROIs.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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scr_idgroupamghippoposthippoAntvmPFC_antvmPFC
0KPE008ketamine-0.465222-0.6887740.5386160.3373280.128000
1KPE1223ketamine0.8566790.5219090.6139980.7743750.589104
2KPE1253midazolam1.023002-0.386011-0.834792-1.1725101.470069
3KPE1263midazolam0.603694-0.5065580.7636010.7461350.560564
4KPE1293ketamine-0.553164-0.309508-0.3972730.297633-0.358259
5KPE1307ketamine-2.318977-0.597950-0.118689-0.990741-1.934913
6KPE1315ketamine0.1948920.001936-0.1152150.2535060.504973
7KPE1322ketamine0.2993611.2671630.4924071.5401141.670747
8KPE1339ketamine-0.516204-0.0038740.5185290.939097-0.079983
9KPE1343ketamine-2.330085-0.823191-1.347205-0.5243860.089253
10KPE1351midazolam-0.763579-0.965045-2.526727-1.078393-0.504770
11KPE1356midazolam1.3543951.352217-0.1055370.108860-1.305680
12KPE1364midazolam1.6132862.6619802.2642930.5482051.331228
13KPE1369midazolam0.865586-0.6417400.360260-2.478017-0.350239
14KPE1387ketamine-0.381962-0.1857510.033346-0.316837-0.620232
15KPE1390midazolam0.392622-0.536858-0.1362770.1161900.767498
16KPE1403midazolam0.5527691.0974040.7765530.2078381.031879
17KPE1419ketamine0.123481-0.3213270.3033590.106221-0.418346
18KPE1464ketamine-1.576694-0.691025-2.1825030.854975-2.496906
19KPE1468midazolam0.764399-0.3322941.141317-0.9329770.284373
20KPE1480midazolam0.293831-0.661676-0.6528751.6646560.426620
21KPE1499ketamine-0.6034001.900897-0.288752-1.550560-1.120646
22KPE1561midazolam0.4553220.6323900.1381341.269623-0.250904
23KPE1573ketamine0.115967-1.7843140.761430-0.7203310.586571
\n", + "
" + ], + "text/plain": [ + " scr_id group amg hippopost hippoAnt vmPFC_ant vmPFC\n", + "0 KPE008 ketamine -0.465222 -0.688774 0.538616 0.337328 0.128000\n", + "1 KPE1223 ketamine 0.856679 0.521909 0.613998 0.774375 0.589104\n", + "2 KPE1253 midazolam 1.023002 -0.386011 -0.834792 -1.172510 1.470069\n", + "3 KPE1263 midazolam 0.603694 -0.506558 0.763601 0.746135 0.560564\n", + "4 KPE1293 ketamine -0.553164 -0.309508 -0.397273 0.297633 -0.358259\n", + "5 KPE1307 ketamine -2.318977 -0.597950 -0.118689 -0.990741 -1.934913\n", + "6 KPE1315 ketamine 0.194892 0.001936 -0.115215 0.253506 0.504973\n", + "7 KPE1322 ketamine 0.299361 1.267163 0.492407 1.540114 1.670747\n", + "8 KPE1339 ketamine -0.516204 -0.003874 0.518529 0.939097 -0.079983\n", + "9 KPE1343 ketamine -2.330085 -0.823191 -1.347205 -0.524386 0.089253\n", + "10 KPE1351 midazolam -0.763579 -0.965045 -2.526727 -1.078393 -0.504770\n", + "11 KPE1356 midazolam 1.354395 1.352217 -0.105537 0.108860 -1.305680\n", + "12 KPE1364 midazolam 1.613286 2.661980 2.264293 0.548205 1.331228\n", + "13 KPE1369 midazolam 0.865586 -0.641740 0.360260 -2.478017 -0.350239\n", + "14 KPE1387 ketamine -0.381962 -0.185751 0.033346 -0.316837 -0.620232\n", + "15 KPE1390 midazolam 0.392622 -0.536858 -0.136277 0.116190 0.767498\n", + "16 KPE1403 midazolam 0.552769 1.097404 0.776553 0.207838 1.031879\n", + "17 KPE1419 ketamine 0.123481 -0.321327 0.303359 0.106221 -0.418346\n", + "18 KPE1464 ketamine -1.576694 -0.691025 -2.182503 0.854975 -2.496906\n", + "19 KPE1468 midazolam 0.764399 -0.332294 1.141317 -0.932977 0.284373\n", + "20 KPE1480 midazolam 0.293831 -0.661676 -0.652875 1.664656 0.426620\n", + "21 KPE1499 ketamine -0.603400 1.900897 -0.288752 -1.550560 -1.120646\n", + "22 KPE1561 midazolam 0.455322 0.632390 0.138134 1.269623 -0.250904\n", + "23 KPE1573 ketamine 0.115967 -1.784314 0.761430 -0.720331 0.586571" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.DataFrame({'scr_id': scr_id[0:24], 'amg': ses2_ROIs[:,0], 'hippopost': ses2_ROIs[:,1], \n", + " 'hippoAnt': ses2_ROIs[:,2], 'vmPFC_ant': ses2_ROIs[:,3], 'vmPFC': ses2_ROIs[:,4]})\n", + "df = pd.merge(medication_cond, df)\n", + "df = df.rename(columns={'med_cond': 'group'})\n", + "df = df.replace(to_replace={'group': {0.0:'midazolam', 1.0:'ketamine'}})\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ttest_indResult(statistic=-1.4180515886707268, pvalue=0.17018571435391172)" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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scr_idgroupamg1hippopost1hippoAnt1vmPFC_ant1vmPFC1
0KPE008ketamine0.9007020.1308181.4155080.1312550.722584
1KPE1223ketamine-0.0003830.077618-0.7728210.5757790.384614
2KPE1253midazolam-0.0228060.185740-0.7948910.294901-0.295044
3KPE1263midazolam-0.821198-1.733423-1.369823-0.584887-0.734617
4KPE1293ketamine-0.5796050.0407200.967307-0.0508510.375149
5KPE1307ketamine-2.235922-0.6462150.460168-1.842212-1.463576
6KPE1315ketamine0.015740-0.469739-0.366420-0.984387-0.386665
7KPE1322ketamine0.6697432.3488031.2455762.6984681.399117
8KPE1339ketamine0.629622-0.045620-1.649392-0.590417-0.581334
9KPE1343ketamine-1.827200-2.167584-0.802191-1.813836-2.091250
10KPE1351midazolam-0.5931470.678353-1.1192290.2164840.486913
11KPE1356midazolam-0.444151-0.4055000.074420-0.316062-0.147327
12KPE1364midazolam-0.488994-0.2173000.325527-0.566040-0.248948
13KPE1369midazolam2.6730960.4533280.535578-0.0671620.916625
14KPE1387ketamine-0.763182-0.395722-1.506574-1.378497-1.390060
15KPE1390midazolam0.221027-0.142072-0.075633-0.1484710.111280
16KPE1403midazolam0.1792130.7197930.4305280.6391861.137717
17KPE1419ketamine0.0042170.725436-0.153304-0.331571-0.721480
18KPE1464ketamine0.7048081.0417851.838457-0.3095790.472867
19KPE1468midazolam-0.611402-1.494585-1.0889211.140707-1.455404
20KPE1480midazolam0.2101711.3609781.9556710.5698260.721975
21KPE1499ketamine1.6135560.3658080.0977911.4125021.903666
22KPE1561midazolam-0.279547-1.245863-0.467781-0.641542-1.016617
23KPE1573ketamine1.272405-0.525214-0.1388690.9475411.372057
24KPE1578midazolam-0.4267631.3596570.9593180.9988640.527759
\n", + "
" + ], + "text/plain": [ + " scr_id group amg1 hippopost1 hippoAnt1 vmPFC_ant1 vmPFC1\n", + "0 KPE008 ketamine 0.900702 0.130818 1.415508 0.131255 0.722584\n", + "1 KPE1223 ketamine -0.000383 0.077618 -0.772821 0.575779 0.384614\n", + "2 KPE1253 midazolam -0.022806 0.185740 -0.794891 0.294901 -0.295044\n", + "3 KPE1263 midazolam -0.821198 -1.733423 -1.369823 -0.584887 -0.734617\n", + "4 KPE1293 ketamine -0.579605 0.040720 0.967307 -0.050851 0.375149\n", + "5 KPE1307 ketamine -2.235922 -0.646215 0.460168 -1.842212 -1.463576\n", + "6 KPE1315 ketamine 0.015740 -0.469739 -0.366420 -0.984387 -0.386665\n", + "7 KPE1322 ketamine 0.669743 2.348803 1.245576 2.698468 1.399117\n", + "8 KPE1339 ketamine 0.629622 -0.045620 -1.649392 -0.590417 -0.581334\n", + "9 KPE1343 ketamine -1.827200 -2.167584 -0.802191 -1.813836 -2.091250\n", + "10 KPE1351 midazolam -0.593147 0.678353 -1.119229 0.216484 0.486913\n", + "11 KPE1356 midazolam -0.444151 -0.405500 0.074420 -0.316062 -0.147327\n", + "12 KPE1364 midazolam -0.488994 -0.217300 0.325527 -0.566040 -0.248948\n", + "13 KPE1369 midazolam 2.673096 0.453328 0.535578 -0.067162 0.916625\n", + "14 KPE1387 ketamine -0.763182 -0.395722 -1.506574 -1.378497 -1.390060\n", + "15 KPE1390 midazolam 0.221027 -0.142072 -0.075633 -0.148471 0.111280\n", + "16 KPE1403 midazolam 0.179213 0.719793 0.430528 0.639186 1.137717\n", + "17 KPE1419 ketamine 0.004217 0.725436 -0.153304 -0.331571 -0.721480\n", + "18 KPE1464 ketamine 0.704808 1.041785 1.838457 -0.309579 0.472867\n", + "19 KPE1468 midazolam -0.611402 -1.494585 -1.088921 1.140707 -1.455404\n", + "20 KPE1480 midazolam 0.210171 1.360978 1.955671 0.569826 0.721975\n", + "21 KPE1499 ketamine 1.613556 0.365808 0.097791 1.412502 1.903666\n", + "22 KPE1561 midazolam -0.279547 -1.245863 -0.467781 -0.641542 -1.016617\n", + "23 KPE1573 ketamine 1.272405 -0.525214 -0.138869 0.947541 1.372057\n", + "24 KPE1578 midazolam -0.426763 1.359657 0.959318 0.998864 0.527759" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df1 = pd.DataFrame({'scr_id': scr_id, 'amg1': ses1_ROIs[:,0], 'hippopost1': ses1_ROIs[:,1], \n", + " 'hippoAnt1': ses1_ROIs[:,2], 'vmPFC_ant1': ses1_ROIs[:,3],\n", + " 'vmPFC1': ses1_ROIs[:,4]})\n", + "df1 = pd.merge(medication_cond, df1)\n", + "df1 = df1.rename(columns={'med_cond': 'group'})\n", + "df1 = df1.replace(to_replace={'group': {0.0:'midazolam', 1.0:'ketamine'}})\n", + "df1" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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scr_idgroupamghippoposthippoAntvmPFC_antvmPFChippAvgamg1hippopost1hippoAnt1vmPFC_ant1vmPFC1amg2_1hippost2_1hippAnt2_1
0KPE008ketamine-0.465222-0.6887740.5386160.3373280.128000-0.0750790.9007020.1308181.4155080.1312550.722584-1.365924-0.819593-0.876891
1KPE1223ketamine0.8566790.5219090.6139980.7743750.5891040.567954-0.0003830.077618-0.7728210.5757790.3846140.8570620.4442921.386819
2KPE1253midazolam1.023002-0.386011-0.834792-1.1725101.470069-0.610401-0.0228060.185740-0.7948910.294901-0.2950441.045808-0.571751-0.039900
3KPE1263midazolam0.603694-0.5065580.7636010.7461350.5605640.128521-0.821198-1.733423-1.369823-0.584887-0.7346171.4248921.2268652.133425
4KPE1293ketamine-0.553164-0.309508-0.3972730.297633-0.358259-0.353390-0.5796050.0407200.967307-0.0508510.3751490.026441-0.350228-1.364580
5KPE1307ketamine-2.318977-0.597950-0.118689-0.990741-1.934913-0.358319-2.235922-0.6462150.460168-1.842212-1.463576-0.0830550.048266-0.578857
6KPE1315ketamine0.1948920.001936-0.1152150.2535060.504973-0.0566400.015740-0.469739-0.366420-0.984387-0.3866650.1791520.4716750.251204
7KPE1322ketamine0.2993611.2671630.4924071.5401141.6707470.8797850.6697432.3488031.2455762.6984681.399117-0.370382-1.081640-0.753169
8KPE1339ketamine-0.516204-0.0038740.5185290.939097-0.0799830.2573280.629622-0.045620-1.649392-0.590417-0.581334-1.1458260.0417472.167922
9KPE1343ketamine-2.330085-0.823191-1.347205-0.5243860.089253-1.085198-1.827200-2.167584-0.802191-1.813836-2.091250-0.5028841.344393-0.545014
10KPE1351midazolam-0.763579-0.965045-2.526727-1.078393-0.504770-1.745886-0.5931470.678353-1.1192290.2164840.486913-0.170433-1.643398-1.407498
11KPE1356midazolam1.3543951.352217-0.1055370.108860-1.3056800.623340-0.444151-0.4055000.074420-0.316062-0.1473271.7985461.757717-0.179956
12KPE1364midazolam1.6132862.6619802.2642930.5482051.3312282.463137-0.488994-0.2173000.325527-0.566040-0.2489482.1022812.8792791.938767
13KPE1369midazolam0.865586-0.6417400.360260-2.478017-0.350239-0.1407402.6730960.4533280.535578-0.0671620.916625-1.807510-1.095068-0.175318
14KPE1387ketamine-0.381962-0.1857510.033346-0.316837-0.620232-0.076203-0.763182-0.395722-1.506574-1.378497-1.3900600.3812200.2099701.539920
15KPE1390midazolam0.392622-0.536858-0.1362770.1161900.767498-0.3365670.221027-0.142072-0.075633-0.1484710.1112800.171595-0.394786-0.060644
16KPE1403midazolam0.5527691.0974040.7765530.2078381.0318790.9369780.1792130.7197930.4305280.6391861.1377170.3735560.3776110.346025
17KPE1419ketamine0.123481-0.3213270.3033590.106221-0.418346-0.0089840.0042170.725436-0.153304-0.331571-0.7214800.119264-1.0467640.456663
18KPE1464ketamine-1.576694-0.691025-2.1825030.854975-2.496906-1.4367640.7048081.0417851.838457-0.3095790.472867-2.281502-1.732810-4.020960
19KPE1468midazolam0.764399-0.3322941.141317-0.9329770.2843730.404512-0.611402-1.494585-1.0889211.140707-1.4554041.3758011.1622912.230237
20KPE1480midazolam0.293831-0.661676-0.6528751.6646560.426620-0.6572760.2101711.3609781.9556710.5698260.7219750.083661-2.022653-2.608546
21KPE1499ketamine-0.6034001.900897-0.288752-1.550560-1.1206460.8060731.6135560.3658080.0977911.4125021.903666-2.2169551.535089-0.386543
22KPE1561midazolam0.4553220.6323900.1381341.269623-0.2509040.385262-0.279547-1.245863-0.467781-0.641542-1.0166170.7348691.8782530.605914
23KPE1573ketamine0.115967-1.7843140.761430-0.7203310.586571-0.5114421.272405-0.525214-0.1388690.9475411.372057-1.156439-1.2591010.900299
\n", + "
" + ], + "text/plain": [ + " scr_id group amg hippopost hippoAnt vmPFC_ant vmPFC \\\n", + "0 KPE008 ketamine -0.465222 -0.688774 0.538616 0.337328 0.128000 \n", + "1 KPE1223 ketamine 0.856679 0.521909 0.613998 0.774375 0.589104 \n", + "2 KPE1253 midazolam 1.023002 -0.386011 -0.834792 -1.172510 1.470069 \n", + "3 KPE1263 midazolam 0.603694 -0.506558 0.763601 0.746135 0.560564 \n", + "4 KPE1293 ketamine -0.553164 -0.309508 -0.397273 0.297633 -0.358259 \n", + "5 KPE1307 ketamine -2.318977 -0.597950 -0.118689 -0.990741 -1.934913 \n", + "6 KPE1315 ketamine 0.194892 0.001936 -0.115215 0.253506 0.504973 \n", + "7 KPE1322 ketamine 0.299361 1.267163 0.492407 1.540114 1.670747 \n", + "8 KPE1339 ketamine -0.516204 -0.003874 0.518529 0.939097 -0.079983 \n", + "9 KPE1343 ketamine -2.330085 -0.823191 -1.347205 -0.524386 0.089253 \n", + "10 KPE1351 midazolam -0.763579 -0.965045 -2.526727 -1.078393 -0.504770 \n", + "11 KPE1356 midazolam 1.354395 1.352217 -0.105537 0.108860 -1.305680 \n", + "12 KPE1364 midazolam 1.613286 2.661980 2.264293 0.548205 1.331228 \n", + "13 KPE1369 midazolam 0.865586 -0.641740 0.360260 -2.478017 -0.350239 \n", + "14 KPE1387 ketamine -0.381962 -0.185751 0.033346 -0.316837 -0.620232 \n", + "15 KPE1390 midazolam 0.392622 -0.536858 -0.136277 0.116190 0.767498 \n", + "16 KPE1403 midazolam 0.552769 1.097404 0.776553 0.207838 1.031879 \n", + "17 KPE1419 ketamine 0.123481 -0.321327 0.303359 0.106221 -0.418346 \n", + "18 KPE1464 ketamine -1.576694 -0.691025 -2.182503 0.854975 -2.496906 \n", + "19 KPE1468 midazolam 0.764399 -0.332294 1.141317 -0.932977 0.284373 \n", + "20 KPE1480 midazolam 0.293831 -0.661676 -0.652875 1.664656 0.426620 \n", + "21 KPE1499 ketamine -0.603400 1.900897 -0.288752 -1.550560 -1.120646 \n", + "22 KPE1561 midazolam 0.455322 0.632390 0.138134 1.269623 -0.250904 \n", + "23 KPE1573 ketamine 0.115967 -1.784314 0.761430 -0.720331 0.586571 \n", + "\n", + " hippAvg amg1 hippopost1 hippoAnt1 vmPFC_ant1 vmPFC1 amg2_1 \\\n", + "0 -0.075079 0.900702 0.130818 1.415508 0.131255 0.722584 -1.365924 \n", + "1 0.567954 -0.000383 0.077618 -0.772821 0.575779 0.384614 0.857062 \n", + "2 -0.610401 -0.022806 0.185740 -0.794891 0.294901 -0.295044 1.045808 \n", + "3 0.128521 -0.821198 -1.733423 -1.369823 -0.584887 -0.734617 1.424892 \n", + "4 -0.353390 -0.579605 0.040720 0.967307 -0.050851 0.375149 0.026441 \n", + "5 -0.358319 -2.235922 -0.646215 0.460168 -1.842212 -1.463576 -0.083055 \n", + "6 -0.056640 0.015740 -0.469739 -0.366420 -0.984387 -0.386665 0.179152 \n", + "7 0.879785 0.669743 2.348803 1.245576 2.698468 1.399117 -0.370382 \n", + "8 0.257328 0.629622 -0.045620 -1.649392 -0.590417 -0.581334 -1.145826 \n", + "9 -1.085198 -1.827200 -2.167584 -0.802191 -1.813836 -2.091250 -0.502884 \n", + "10 -1.745886 -0.593147 0.678353 -1.119229 0.216484 0.486913 -0.170433 \n", + "11 0.623340 -0.444151 -0.405500 0.074420 -0.316062 -0.147327 1.798546 \n", + "12 2.463137 -0.488994 -0.217300 0.325527 -0.566040 -0.248948 2.102281 \n", + "13 -0.140740 2.673096 0.453328 0.535578 -0.067162 0.916625 -1.807510 \n", + "14 -0.076203 -0.763182 -0.395722 -1.506574 -1.378497 -1.390060 0.381220 \n", + "15 -0.336567 0.221027 -0.142072 -0.075633 -0.148471 0.111280 0.171595 \n", + "16 0.936978 0.179213 0.719793 0.430528 0.639186 1.137717 0.373556 \n", + "17 -0.008984 0.004217 0.725436 -0.153304 -0.331571 -0.721480 0.119264 \n", + "18 -1.436764 0.704808 1.041785 1.838457 -0.309579 0.472867 -2.281502 \n", + "19 0.404512 -0.611402 -1.494585 -1.088921 1.140707 -1.455404 1.375801 \n", + "20 -0.657276 0.210171 1.360978 1.955671 0.569826 0.721975 0.083661 \n", + "21 0.806073 1.613556 0.365808 0.097791 1.412502 1.903666 -2.216955 \n", + "22 0.385262 -0.279547 -1.245863 -0.467781 -0.641542 -1.016617 0.734869 \n", + "23 -0.511442 1.272405 -0.525214 -0.138869 0.947541 1.372057 -1.156439 \n", + "\n", + " hippost2_1 hippAnt2_1 \n", + "0 -0.819593 -0.876891 \n", + "1 0.444292 1.386819 \n", + "2 -0.571751 -0.039900 \n", + "3 1.226865 2.133425 \n", + "4 -0.350228 -1.364580 \n", + "5 0.048266 -0.578857 \n", + "6 0.471675 0.251204 \n", + "7 -1.081640 -0.753169 \n", + "8 0.041747 2.167922 \n", + "9 1.344393 -0.545014 \n", + "10 -1.643398 -1.407498 \n", + "11 1.757717 -0.179956 \n", + "12 2.879279 1.938767 \n", + "13 -1.095068 -0.175318 \n", + "14 0.209970 1.539920 \n", + "15 -0.394786 -0.060644 \n", + "16 0.377611 0.346025 \n", + "17 -1.046764 0.456663 \n", + "18 -1.732810 -4.020960 \n", + "19 1.162291 2.230237 \n", + "20 -2.022653 -2.608546 \n", + "21 1.535089 -0.386543 \n", + "22 1.878253 0.605914 \n", + "23 -1.259101 0.900299 " + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "col = df.loc[: , [\"hippoAnt\",\"hippopost\"]]\n", + "df['hippAvg'] = col.mean(axis=1)\n", + "\n", + "dfTot = pd.merge(df, df1)\n", + "dfTot['amg2_1'] = dfTot.amg - dfTot.amg1\n", + "dfTot['hippost2_1'] = dfTot.hippopost - dfTot.hippopost1\n", + "dfTot['hippAnt2_1'] = dfTot.hippoAnt - dfTot.hippoAnt1\n", + "dfTot" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'dfTot' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mboxplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'group'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'amg1'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdfTot\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msaturation\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m.4\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m scipy.stats.ttest_ind(dfTot.amg2_1[dfTot['group']=='ketamine'],\n\u001b[1;32m 3\u001b[0m dfTot['amg2_1'][dfTot['group']=='midazolam'])\n", + "\u001b[0;31mNameError\u001b[0m: name 'dfTot' is not defined" + ] + } + ], + "source": [ + "sns.boxplot(x='group',y='amg1', data=dfTot, saturation=.4)\n", + "scipy.stats.ttest_ind(dfTot.amg2_1[dfTot['group']=='ketamine'],\n", + " dfTot['amg2_1'][dfTot['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ttest_indResult(statistic=-2.8974675362889157, pvalue=0.008353808055991145)" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(x='group',y='amg2_1', data=dfTot, saturation=.4)\n", + "scipy.stats.ttest_ind(dfTot.amg2_1[dfTot['group']=='ketamine'],\n", + " dfTot['amg2_1'][dfTot['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df.groupby(['group']).count()" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ttest_indResult(statistic=-3.502808955912397, pvalue=0.002010504076813303)" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot\n", + "sns.boxplot(x='group',y='amg', data=df, saturation=.4)\n", + "sns.stripplot(x='group',y='amg', data=df)\n", + "#sns.boxplot(x='group',y='meanAct', data=df)\n", + "scipy.stats.ttest_ind(df.amg[df['group']=='ketamine'], df['amg'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ttest_indResult(statistic=0.3937659771165316, pvalue=0.6975443224592655)" + ] + }, + "execution_count": 58, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(x='group',y='vmPFC_ant', data=df, saturation=.4)\n", + "sns.stripplot(x='group',y='vmPFC_ant', data=df)\n", + "#sns.boxplot(x='group',y='meanAct', data=df)\n", + "scipy.stats.ttest_ind(df.vmPFC_ant[df['group']=='ketamine'], df['vmPFC_ant'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "array length 20 does not match index length 25", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m## add session 3\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m df3 = pd.DataFrame({'scr_id': scr_id, 'amg': ses3_ROIs[:,0], 'hippopost': ses3_ROIs[:,1], \n\u001b[0;32m----> 3\u001b[0;31m 'hippoAnt': ses3_ROIs[:,2], 'vmPFC_ant': ses3_ROIs[:,3], 'vmPFC': ses3_ROIs[:,4]})\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0mdf3\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmerge\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmedication_cond\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdf3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mdf3\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf3\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrename\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m'med_cond'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'group'\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, data, index, columns, dtype, copy)\u001b[0m\n\u001b[1;32m 465\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 466\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 467\u001b[0;31m \u001b[0mmgr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0minit_dict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolumns\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 468\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mMaskedArray\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 469\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmrecords\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mmrecords\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/internals/construction.py\u001b[0m in \u001b[0;36minit_dict\u001b[0;34m(data, index, columns, dtype)\u001b[0m\n\u001b[1;32m 281\u001b[0m \u001b[0marr\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mis_datetime64tz_dtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marr\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0marr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0marr\u001b[0m \u001b[0;32min\u001b[0m \u001b[0marrays\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 282\u001b[0m ]\n\u001b[0;32m--> 283\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0marrays_to_mgr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marrays\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata_names\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolumns\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 284\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 285\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/internals/construction.py\u001b[0m in \u001b[0;36marrays_to_mgr\u001b[0;34m(arrays, arr_names, index, columns, dtype, verify_integrity)\u001b[0m\n\u001b[1;32m 76\u001b[0m \u001b[0;31m# figure out the index, if necessary\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 77\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mindex\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 78\u001b[0;31m \u001b[0mindex\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mextract_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marrays\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 79\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 80\u001b[0m \u001b[0mindex\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mensure_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/pandas/core/internals/construction.py\u001b[0m in \u001b[0;36mextract_index\u001b[0;34m(data)\u001b[0m\n\u001b[1;32m 409\u001b[0m \u001b[0;34mf\"length {len(index)}\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 410\u001b[0m )\n\u001b[0;32m--> 411\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 412\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 413\u001b[0m \u001b[0mindex\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mibase\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdefault_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlengths\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mValueError\u001b[0m: array length 20 does not match index length 25" + ] + } + ], + "source": [ + "## add session 3\n", + "df3 = pd.DataFrame({'scr_id': scr_id, 'amg': ses3_ROIs[:,0], 'hippopost': ses3_ROIs[:,1], \n", + " 'hippoAnt': ses3_ROIs[:,2], 'vmPFC_ant': ses3_ROIs[:,3], 'vmPFC': ses3_ROIs[:,4]})\n", + "df3 = pd.merge(medication_cond, df3)\n", + "df3 = df3.rename(columns={'med_cond': 'group'})\n", + "df3 = df3.replace(to_replace={'group': {0.0:'midazolam', 1.0:'ketamine'}})\n", + "df3" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Use PyMC3 for bayesian based analysis " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pymc3 as pm\n", + "# first code new variable for group index (1=ketamine, 2= midazolam)\n", + "group = {'ketamine': 1,'midazolam': 2} \n", + "df['groupIdx'] =[group[item] for item in df.group] " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#az.summary(posterior_1, credible_interval=.95).round(2) # adding round to make shorted floats\n", + "pm.summary(posterior_1)#, alpha=.05).round(2)# also possible" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# play with glm module of pymc3\n", + "from pymc3.glm import GLM\n", + "\n", + "with pm.Model() as model_glm:\n", + " GLM.from_formula('amg ~ groupIdx', df)\n", + " trace = pm.sample(draws=4000, tune=3000)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pm.summary(trace, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.distplot(trace.groupIdx)\n", + "sum(trace['groupIdx']>0) / len(trace['groupIdx'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Presenting differences between the groups using scatter plot for each group + \n", + "## The resulting Bayesian analyses plots (density of differences and boxplot)\n", + "\n", + "sns.set_style(\"whitegrid\")\n", + "plt.figure(figsize=(5,5))\n", + "grid = plt.GridSpec(2, 20, wspace=.1, hspace=0.0) # building a grid to put the graphs in\n", + "plt.subplot(grid[:, :10])\n", + "#fig.add_subplot(grid[0,0])\n", + "g1= sns.stripplot(x='group',y='meanAct',hue = 'group', data=df, s=8)\n", + "#g1 = sns.boxplot(x='group',y='meanAct',hue = 'group', data=df)\n", + "g1.set_ylim(-80,80)\n", + "g1.legend_.remove()\n", + "\n", + "plt.subplot(grid[:, 10])\n", + "g3 = sns.boxplot(trace.groupIdx, orient='v')\n", + "g3.set_ylim(-80,80)\n", + "g3.set_yticks([])\n", + "\n", + "plt.subplot(grid[:, 11:13])\n", + "g2 = sns.distplot(trace.groupIdx, vertical=True, color=\"Green\")\n", + "g2.set_ylim(-80,80)\n", + "#g2.set_yticks([])\n", + "g2.yaxis.tick_right()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#df_vmpfc = pd.DataFrame({'scr_id': scr_id, 'meanAct': mean_act})\n", + "#df['vmPFC'] = mean_act_vmpfc\n", + "#sns.boxplot(x='group',y='vmPFC', data=df)\n", + "sns.barplot(x='group',y='vmPFC', data=df, ci=68)\n", + "scipy.stats.ttest_ind(df.vmPFC[df['group']=='ketamine'], df['vmPFC'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "len(mean_act_vmpfc)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "with pm.Model() as model_glm:\n", + " GLM.from_formula('vmPFC ~ groupIdx', df)\n", + " trace_vmpfc = pm.sample(draws=4000, tune=3000)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pm.summary(trace_vmpfc, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Hippocampus\n", + "mask_file = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=15\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None, standardize=False, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mean_act_hippo = []\n", + "scr_id = []\n", + "for func in func_files:\n", + " # get subject number\n", + " scr_id.append('KPE' + func.split('id_')[1].split('/')[0])\n", + " # get average activation\n", + " t_map = masker.fit_transform(func)\n", + " \n", + " average = np.mean(np.array(t_map))\n", + " mean_act_hippo.append(average)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df['hippo'] = mean_act_hippo\n", + "sns.barplot(x='group',y='hippo', data=df, ci=68)\n", + "scipy.stats.ttest_ind(df.hippo[df['group']=='ketamine'], df['hippo'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "with pm.Model() as model_glm:\n", + " GLM.from_formula('hippo ~ groupIdx', df)\n", + " trace_hippo = pm.sample(draws=2000, tune=5000)\n", + "pm.summary(trace_hippo, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.set_style(\"whitegrid\")\n", + "\n", + "grid = plt.GridSpec(2, 20, wspace=.1, hspace=0.0) # building a grid to put the graphs in\n", + "plt.subplot(grid[:, :10])\n", + "#fig.add_subplot(grid[0,0])\n", + "g1= sns.stripplot(x='group',y='hippo',hue = 'group', data=df, s=8)\n", + "#g1 = sns.boxplot(x='group',y='meanAct',hue = 'group', data=df)\n", + "g1.set_ylim(-80,80)\n", + "g1.legend_.remove()\n", + "\n", + "plt.subplot(grid[:, 10])\n", + "g3 = sns.boxplot(trace_hippo.groupIdx, orient='v')\n", + "g3.set_ylim(-80,80)\n", + "g3.set_yticks([])\n", + "\n", + "plt.subplot(grid[:, 11:13])\n", + "g2 = sns.distplot(trace_hippo.groupIdx, vertical=True, color=\"Green\")\n", + "g2.set_ylim(-80,80)\n", + "#g2.set_yticks([])\n", + "g2.yaxis.tick_right()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Caudate" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mask_file = '/media/Data/work/caudate_association-test_z_FDR_0.01.nii.gz'\n", + "mask_file = nilearn.image.math_img(\"a>=12\", a=mask_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(mask_file)\n", + "masker = nilearn.input_data.NiftiMasker(mask_img=mask_file, \n", + " sessions=None, smoothing_fwhm=None, standardize=False, detrend=False, verbose=5)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "mean_act_st = []\n", + "scr_id = []\n", + "for func in func_files:\n", + " # get subject number\n", + " scr_id.append('KPE' + func.split('id_')[1].split('/')[0])\n", + " # get average activation\n", + " t_map = masker.fit_transform(func)\n", + " \n", + " average = np.mean(np.array(t_map))\n", + " mean_act_st.append(average)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df['striatumAc'] = mean_act_st\n", + "sns.barplot(x='group',y='striatumAc', data=df, ci=68)\n", + "scipy.stats.ttest_ind(df.striatumAc[df['group']=='ketamine'], df['striatumAc'][df['group']=='midazolam'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "with pm.Model() as model_glm:\n", + " GLM.from_formula('striatumAc ~ groupIdx', df)\n", + " trace_striat = pm.sample()\n", + "pm.summary(trace_striat, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Correlation between PCL scores and average activation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## read pcl scores\n", + "pclDf = pd.read_csv('/home/or/Documents/kpe_analyses/KPEIHR0009_DATA_2019-10-07_1121.csv')\n", + "# take only KPE patients\n", + "pclDf = pclDf[pclDf['scr_id'].str.startswith('KPE')]\n", + "list(pclDf.columns)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "dfP = pd.DataFrame({'subject': pclDf['scr_id']})\n", + "dfP_PCL = pclDf[['scr_id','redcap_event_name','pcl5_1', 'pcl5_2', 'pcl5_3', 'pcl5_4', 'pcl5_5', 'pcl5_6', 'pcl5_7',\n", + " 'pcl5_8', 'pcl5_9', 'pcl5_10', 'pcl5_11', 'pcl5_12', 'pcl5_13', 'pcl5_14', 'pcl5_15', 'pcl5_16', 'pcl5_17',\n", + " 'pcl5_18', 'pcl5_19', 'pcl5_20']]\n", + "# remove NAs\n", + "dfP_PCL = dfP_PCL.dropna()\n", + "# set list of columns for analysis\n", + "colList = list(dfP_PCL)\n", + "colList.remove('scr_id')\n", + "colList.remove('redcap_event_name')\n", + "# set total pcl scores \n", + "dfP_PCL['pclTotal'] = dfP_PCL[colList].sum(axis=1)\n", + "sns.distplot(dfP_PCL.pclTotal)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# reshape it to wide\n", + "df2=dfP_PCL.pivot(index = 'scr_id',columns='redcap_event_name', values='pclTotal')\n", + "list(df2)\n", + "df2 = df2.rename(columns={\"30_day_follow_up_s_arm_1\": \"30Days\", \"90_day_follow_up_s_arm_1\": \"90Days\",\n", + " \"screening_selfrepo_arm_1\": \"Screening\", \"visit_1_arm_1\": \"Visit1\", \n", + " \"visit_7_week_follo_arm_1\": \"Visit7\"})\n", + "#df2['scr_id'] = dfP_PCL['scr_id']\n", + "df2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# merging two data frames toghether\n", + "dfTest = pd.merge(df, df2, on = 'scr_id')\n", + "# change visit1 missing values with screening values\n", + "for i in dfTest.iterrows():\n", + " if np.isnan(i[1].Visit1):\n", + " print(\"Nan\")\n", + " print(i[1].Screening)\n", + " dfTest.at[i[0], 'Visit1']= i[1].Screening\n", + "\n", + "# create difference pcl score\n", + "dfTest['days30_1'] = dfTest['30Days'] - dfTest.Visit1\n", + "dfTest['days30_s'] = dfTest['30Days'] - dfTest.Screening\n", + "dfTest['Visit7_1'] = dfTest['Visit7'] - dfTest.Visit1\n", + "dfTest" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.lmplot(x='Visit7', y='meanAct',hue='group', data=dfTest)\n", + "xMask = np.isnan(dfTest['Visit7'])\n", + "yMask = np.isnan(dfTest['meanAct'])\n", + "nas = np.logical_or(xMask, yMask)\n", + "scipy.stats.pearsonr(dfTest['Visit7'][~nas],dfTest['meanAct'][~nas])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Test difference in amygdala activation between 1st and2nd session and see if it correlates to symtpoms\n", + "dfTest['amg_ses2_ses1'] = dfTest.meanAct - df_ses1.meanAct_ses1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.lmplot(x='amg_ses2_ses1', y='Visit7_1',hue='group', data=dfTest)\n", + "xMask = np.isnan(dfTest['Visit7_1'])\n", + "yMask = np.isnan(dfTest['amg_ses2_ses1'])\n", + "nas = np.logical_or(xMask, yMask)\n", + "scipy.stats.pearsonr(dfTest['Visit7_1'][~nas],dfTest['amg_ses2_ses1'][~nas])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "### So - change in Hippocampus reactivation to trauma script (vs. relax) is correlated to changes symptoms at end of treatment\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "dfTest" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# lets test correlation per group (although this is a very ver\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "dfTest.corr()\n", + "#sns.heatmap(dfTest)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.figure(figsize=(20,10))\n", + "sns.heatmap(dfTest[dfTest.group==0].corr(), annot=True, cmap=\"coolwarm\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "X = dfTest[['meanAct','hippo', 'group']]\n", + "y = dfTest['days30_1']\n", + "\n", + "X = sm.add_constant(X)\n", + "est = sm.OLS(y, X, missing='drop').fit()\n", + "est.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "smOLS = smf.ols(formula='days30_1 ~ group * meanAct', data=dfTest).fit()\n", + "\n", + "smOLS.summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Check correlation with SCR" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "scr = pd.read_csv('/home/or/kpe_task_analysis/scr_deltas.csv')\n", + "scr1 = scr.drop(columns = ['med_cond', 'groupIdx'])\n", + "scr1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "dfMerge = pd.merge(df, scr1)\n", + "dfMerge" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.lmplot(x = 'Trauma_2vs1', y= 'meanAct',hue = 'group', data=dfMerge)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "smOLS = smf.ols(formula='Trauma_2vs1 ~ group * meanAct', data=dfMerge).fit()\n", + "\n", + "smOLS.summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Check changes in amg activation and SCR / PCL" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "dfMerge['amg_2_1'] = dfMerge.meanAct - df_ses1.meanAct_ses1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.lmplot(x='Trauma_2vs1', y = 'amg_2_1', hue='group', data=dfMerge)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/averagedMat_acrossSessions.mat b/task_based_analysis/averagedMat_acrossSessions.mat new file mode 100644 index 0000000..5f461c9 Binary files /dev/null and b/task_based_analysis/averagedMat_acrossSessions.mat differ diff --git a/task_based_analysis/averagedMat_session1.mat b/task_based_analysis/averagedMat_session1.mat new file mode 100644 index 0000000..0dd42f3 Binary files /dev/null and b/task_based_analysis/averagedMat_session1.mat differ diff --git a/task_based_analysis/averagedMat_session2.mat b/task_based_analysis/averagedMat_session2.mat new file mode 100644 index 0000000..6f7869b Binary files /dev/null and b/task_based_analysis/averagedMat_session2.mat differ diff --git a/task_based_analysis/conAmg_Hippo/.ipynb_checkpoints/corr_computation_onlyamgHippo-checkpoint.ipynb b/task_based_analysis/conAmg_Hippo/.ipynb_checkpoints/corr_computation_onlyamgHippo-checkpoint.ipynb new file mode 100644 index 0000000..a2b9b78 --- /dev/null +++ b/task_based_analysis/conAmg_Hippo/.ipynb_checkpoints/corr_computation_onlyamgHippo-checkpoint.ipynb @@ -0,0 +1,1734 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Mask amygdala hippocampus and correlate the trauma script" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import scipy\n", + "import nilearn.plotting\n", + "import nilearn.input_data\n", + "import os\n", + "import nipype.pipeline.engine as pe # pypeline engine\n", + "import nipype.interfaces.utility as util # utility" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "output_dir = '/media/Data/work/kpe_connAnalysis'\n", + "ses = '1'" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "## set parameters for the maskers\n", + "mask_params = {\n", + " 'detrend': True, 'standardize': True,\n", + " 'high_pass': 0.01, 'low_pass': 0.1, 't_r': 1,\n", + " 'smoothing_fwhm': 4,\n", + " 'verbose': 5}\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Amygdala as mask\n", + "amg_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "amg_file = nilearn.image.math_img(\"a>=25\", a=amg_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(amg_file)\n", + "\n", + "\n", + "masker_amg = nilearn.input_data.NiftiMasker(mask_img= amg_file, **mask_params).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# now lets do the same with vmPFC\n", + "vmpfc_mask = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", + "vmpfc_mask = nilearn.image.math_img(\"a>=5\", a=vmpfc_mask)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(vmpfc_mask)\n", + "masker_vmpfc = nilearn.input_data.NiftiMasker(mask_img= vmpfc_mask, **mask_params).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'mask_file' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_line_magic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'matplotlib'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'inline'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mnilearn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplotting\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot_roi\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhipp_mask\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mmasker_hipp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnilearn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minput_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mNiftiMasker\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmask_img\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0mmask_file\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mmask_params\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;31mNameError\u001b[0m: name 'mask_file' is not defined" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Hippocampus\n", + "hipp_mask = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "hipp_mask = nilearn.image.math_img(\"a>=15\", a=hipp_mask)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(hipp_mask)\n", + "masker_hipp = nilearn.input_data.NiftiMasker(mask_img= mask_file, **mask_params).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "def removeVars (sub, ses):\n", + " \n", + " # this method takes the csv regressors file (from fmriPrep) and chooses a few to confound. You can change those few\n", + " import pandas as pd\n", + " import numpy as np\n", + " subject = sub.split('KPE')[1]\n", + " confound_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_desc-confounds_regressors.tsv'\n", + " confoundFile = confound_template.format(sub=subject, ses=ses)\n", + " confound = pd.read_csv(confoundFile,sep=\"\\t\", na_values=\"n/a\")\n", + " finalConf = confound[['csf', 'white_matter', 'framewise_displacement', \n", + " 'a_comp_cor_00', 'a_comp_cor_01',\t'a_comp_cor_02', 'a_comp_cor_03', \n", + " 'a_comp_cor_04', 'a_comp_cor_05', 'trans_x', 'trans_y', 'trans_z', \n", + " 'rot_x', 'rot_y', 'rot_z']] # can add 'global_signal' also ,,\n", + " # \n", + " # change NaN of FD to zero\n", + " finalConf = finalConf.fillna(0)\n", + " return np.array(finalConf)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "# method to generate subject array of timeseries\n", + "def pooledTS(sub, ses, confounds, output_dir):\n", + " import os\n", + " import numpy as np\n", + " import nilearn.input_data\n", + " import nilearn.image\n", + " \n", + " event_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/sub-{sub}_ses-{ses}_30sec_window.csv'\n", + " func_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz'\n", + " # set mask params\n", + " mask_params = {\n", + " 'detrend': True, 'standardize': True,\n", + " 'high_pass': 0.01, 'low_pass': 0.1, 't_r': 1,\n", + " 'smoothing_fwhm': 4,\n", + " 'verbose': 5}\n", + "\n", + " amg_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + " amg_file = nilearn.image.math_img(\"a>=25\", a=amg_file)\n", + " hipp_mask = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + " hipp_mask = nilearn.image.math_img(\"a>=15\", a=hipp_mask)\n", + " vmpfc_mask = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", + " vmpfc_mask = nilearn.image.math_img(\"a>=5\", a=vmpfc_mask)\n", + "\n", + " \n", + " # fit maskers\n", + " masker_amg = nilearn.input_data.NiftiMasker(mask_img= amg_file, **mask_params).fit()\n", + " masker_vmpfc = nilearn.input_data.NiftiMasker(mask_img= vmpfc_mask, **mask_params).fit()\n", + " masker_hipp = nilearn.input_data.NiftiMasker(mask_img= hipp_mask, **mask_params).fit()\n", + " # set output dir\n", + " if not os.path.exists(output_dir):\n", + " os.makedirs(output_dir)\n", + " duration = 120 #set duration of event in seconds \n", + " #sub_tsAmg = []\n", + " #sub_tsHipp = []\n", + " #sub_tsvmPFC = []\n", + " #for sub in subject_list:\n", + " subject = sub.split('KPE')[1]\n", + "\n", + " # load the npy file (timeseries)\n", + " tsAmg = masker_amg.transform(func_template.format(sub=subject, ses=ses), confounds)\n", + " tsHipp = masker_hipp.transform(func_template.format(sub=subject, ses=ses),confounds)\n", + " tsvmPFC = masker_vmpfc.transform(func_template.format(sub=subject, ses=ses),confounds)\n", + " event = event_template.format(sub=subject, ses=ses)\n", + " events = pd.read_csv(event, sep='\\t')\n", + " onset = int(events.onset[events.trial_type_30=='trauma1_0']) # take onset of trauma first script\n", + " tsAmg_script = tsAmg[onset:onset+duration, :]\n", + " tsHipp_script = tsHipp[onset:onset+duration, :]\n", + " tsvmPFC_script = tsvmPFC[onset:onset+duration, :]\n", + " tsAmg_mean = np.mean(tsAmg_script, axis=1)\n", + " tsHipp_mean = np.mean(tsHipp_script, axis=1)\n", + " tsvmPFC_mean = np.mean(tsvmPFC_script, axis=1)\n", + " np.save(output_dir + 'sub-' + subject + 'amygdalaMeanTS' + 'ses-' + ses, tsAmg_mean)\n", + " np.save(output_dir + 'sub-' + subject + 'hippoMeanTS' + 'ses-' + ses, tsHipp_mean)\n", + " np.save(output_dir + 'sub-' + subject + 'vmPFCMeanTS' + 'ses-' + ses, tsvmPFC_mean)\n", + "# sub_tsAmg.append(tsAmg_mean)\n", + "# sub_tsHipp.append(tsHipp_mean)\n", + "# sub_tsvmPFC.append(tsvmPFC_mean)\n", + " return tsAmg_mean, tsHipp_mean , tsvmPFC_mean" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "## condition labels (ketamine , midazolam)\n", + "# read file\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "subject_list = np.array(medication_cond.scr_id)\n", + "condition_label = np.array(medication_cond.med_cond)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "subject_list = subject_list[0:24] # removing 1578 \n", + "condition_label = condition_label[0:24]\n", + "subject_list" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "infosource = pe.Node(util.IdentityInterface(fields=['subject_id'\n", + " ],\n", + " ),\n", + " name=\"infosource\")\n", + "infosource.iterables = [('subject_id', subject_list)]\n", + "\n", + "removeVars = pe.Node(util.Function(\n", + " input_names=['sub','ses'],\n", + " output_names=['finalConf'],\n", + " function=removeVars),\n", + " name=\"removeVars\")\n", + "\n", + "removeVars.inputs.ses = ses\n", + "\n", + "runTimeSeries = pe.Node(util.Function(\n", + " input_names=['sub','ses','confounds', 'output_dir'],\n", + " output_names=['tsAmg_mean', 'tsHipp_mean', 'tsvmPFC_mean'],\n", + " function=pooledTS),\n", + " name=\"runTimeSeries\")\n", + "\n", + "\n", + "runTimeSeries.inputs.output_dir = output_dir\n", + "runTimeSeries.inputs.ses = ses\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "amg_file" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "runTS = pe.Workflow(name='hippAmgTS', base_dir = output_dir)\n", + "runTS.connect([\n", + " (infosource, removeVars, [('subject_id', 'sub')]),\n", + " (infosource, runTimeSeries, [('subject_id', 'sub')]),\n", + " (removeVars, runTimeSeries, [('finalConf', 'confounds')])\n", + "])" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "200821-08:07:55,993 nipype.workflow INFO:\n", + "\t Workflow hippAmgTS settings: ['check', 'execution', 'logging', 'monitoring']\n", + "200821-08:07:56,114 nipype.workflow INFO:\n", + "\t Running in parallel.\n", + "200821-08:07:56,121 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 25 jobs ready. Free memory (GB): 56.23/56.23, Free processors: 10/10.\n", + "200821-08:07:56,223 nipype.workflow INFO:\n", + "\t [Job 0] Cached (hippAmgTS.removeVars).\n", + "200821-08:07:56,225 nipype.workflow INFO:\n", + "\t [Job 2] Cached (hippAmgTS.removeVars).\n", + "200821-08:07:56,228 nipype.workflow INFO:\n", + "\t [Job 4] Cached (hippAmgTS.removeVars).\n", + "200821-08:07:56,230 nipype.workflow INFO:\n", + "\t [Job 6] Cached (hippAmgTS.removeVars).\n", + "200821-08:07:56,232 nipype.workflow INFO:\n", + "\t [Job 8] Cached (hippAmgTS.removeVars).\n", + "200821-08:07:56,234 nipype.workflow INFO:\n", + "\t [Job 10] Cached (hippAmgTS.removeVars).\n", + "200821-08:07:56,237 nipype.workflow INFO:\n", + "\t [Job 12] Cached (hippAmgTS.removeVars).\n", + "200821-08:07:56,239 nipype.workflow INFO:\n", + "\t [Job 14] Cached (hippAmgTS.removeVars).\n", + "200821-08:07:56,241 nipype.workflow INFO:\n", + "\t [Job 16] Cached (hippAmgTS.removeVars).\n", + "200821-08:07:56,244 nipype.workflow INFO:\n", + "\t [Job 18] Cached (hippAmgTS.removeVars).\n", + "200821-08:07:58,357 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1578/runTimeSeries\".\n", + "200821-08:07:58,372 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1573/runTimeSeries\".\n", + "200821-08:07:58,400 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1561/runTimeSeries\".\n", + "200821-08:07:58,446 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1499/runTimeSeries\".\n", + "200821-08:07:58,472 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1480/runTimeSeries\".\n", + "200821-08:07:58,507 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1468/runTimeSeries\".\n", + "200821-08:07:58,539 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1464/runTimeSeries\".\n", + "200821-08:07:58,571 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1419/runTimeSeries\".\n", + "200821-08:07:58,600 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1403/runTimeSeries\".\n", + "200821-08:07:58,607 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:07:58,615 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:07:58,626 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:07:58,641 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1390/runTimeSeries\".\n", + "200821-08:07:58,667 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:07:58,702 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:07:58,727 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:07:58,782 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:07:58,788 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:07:58,808 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:07:58,813 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Resampling mask200821-08:07:59,368 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "\n", + "\n", + "\n", + "\n", + "[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Loading data from None\n", + "\n", + "\n", + "[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Resampling mask200821-08:07:59,386 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "\n", + "[NiftiMasker.fit] Loading data from None\n", + "\n", + "\n", + "[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Resampling mask200821-08:07:59,393 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "\n", + "[NiftiMasker.fit] Loading data from None\n", + "200821-08:07:59,396 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "[NiftiMasker.fit] Resampling mask\n", + "200821-08:07:59,401 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None200821-08:07:59,413 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1480/runTimeSeries)\n", + "\n", + "\n", + "[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "\n", + "[NiftiMasker.fit] Resampling mask\n", + "200821-08:07:59,436 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "200821-08:07:59,434 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "200821-08:07:59,439 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1499/runTimeSeries)\n", + "200821-08:07:59,441 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1578/runTimeSeries)\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask200821-08:07:59,459 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1561/runTimeSeries)\n", + "\n", + "200821-08:07:59,460 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1573/runTimeSeries)\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Loading data from None\n", + "\n", + "[NiftiMasker.fit] Resampling mask\n", + "200821-08:07:59,473 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "200821-08:07:59,481 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1464/runTimeSeries)\n", + "200821-08:07:59,481 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "200821-08:07:59,487 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1468/runTimeSeries)\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "200821-08:07:59,515 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "200821-08:07:59,515 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1390/runTimeSeries)\n", + "200821-08:07:59,522 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1403/runTimeSeries)\n", + "200821-08:07:59,554 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1419/runTimeSeries)\n", + "200821-08:08:00,154 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a24 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:00,156 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a24-6f26a6f6-9af2-4b90-8273-9b949fd5235f.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:00,230 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a23 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:00,232 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a23-66df5956-6ab1-498b-b586-218afa97109e.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:00,298 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a22 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:00,299 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a22-748aaf96-52c4-45b7-8cd2-ca6203483242.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:00,364 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a21 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:00,365 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a21-164d73b4-87a3-42ec-b294-9b825f553128.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:00,429 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a20 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:00,430 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a20-3e4b6b1d-bed5-4a5c-b49e-30b74aa47ff6.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "200821-08:08:00,493 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a19 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:00,494 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a19-39869b72-c45a-4cfb-92ee-a62cb9509935.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:00,557 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a18 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:00,558 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a18-0e359fb3-d9f6-4ec3-87bb-b630f2b06743.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:00,632 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a17 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:00,633 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a17-904b002a-17af-4213-83e1-5c52a6e0d5c9.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:00,698 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a16 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:00,699 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a16-062ac9e3-a5d1-40d2-834e-ea99266d837d.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:00,771 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a15 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:00,772 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a15-0f52afac-c2c5-4546-a634-fe3a9da9eb87.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:00,828 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 15 jobs ready. Free memory (GB): 56.23/56.23, Free processors: 10/10.\n", + "200821-08:08:00,929 nipype.workflow INFO:\n", + "\t [Job 20] Cached (hippAmgTS.removeVars).\n", + "200821-08:08:00,933 nipype.workflow INFO:\n", + "\t [Job 22] Cached (hippAmgTS.removeVars).\n", + "200821-08:08:00,935 nipype.workflow INFO:\n", + "\t [Job 24] Cached (hippAmgTS.removeVars).\n", + "200821-08:08:00,938 nipype.workflow INFO:\n", + "\t [Job 26] Cached (hippAmgTS.removeVars).\n", + "200821-08:08:00,941 nipype.workflow INFO:\n", + "\t [Job 28] Cached (hippAmgTS.removeVars).\n", + "200821-08:08:00,944 nipype.workflow INFO:\n", + "\t [Job 30] Cached (hippAmgTS.removeVars).\n", + "200821-08:08:00,947 nipype.workflow INFO:\n", + "\t [Job 32] Cached (hippAmgTS.removeVars).\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "200821-08:08:00,950 nipype.workflow INFO:\n", + "\t [Job 34] Cached (hippAmgTS.removeVars).\n", + "200821-08:08:00,953 nipype.workflow INFO:\n", + "\t [Job 36] Cached (hippAmgTS.removeVars).\n", + "200821-08:08:00,956 nipype.workflow INFO:\n", + "\t [Job 38] Cached (hippAmgTS.removeVars).\n", + "200821-08:08:02,256 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1387/runTimeSeries\".\n", + "200821-08:08:02,270 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1369/runTimeSeries\".\n", + "200821-08:08:02,309 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1364/runTimeSeries\".\n", + "200821-08:08:02,344 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1356/runTimeSeries\".\n", + "200821-08:08:02,366 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1351/runTimeSeries\".\n", + "200821-08:08:02,412 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1343/runTimeSeries\".\n", + "200821-08:08:02,431 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1339/runTimeSeries\".\n", + "200821-08:08:02,493 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1322/runTimeSeries\".\n", + "200821-08:08:02,515 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1315/runTimeSeries\".\n", + "200821-08:08:02,539 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:08:02,554 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:08:02,556 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1307/runTimeSeries\".\n", + "200821-08:08:02,556 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:08:02,608 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:08:02,615 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:08:02,654 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:08:02,659 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:08:02,704 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:08:02,713 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:08:02,717 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Resampling mask\n", + "\n", + "[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Resampling mask\n", + "\n", + "\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Loading data from None\n", + "\n", + "200821-08:08:03,184 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Resampling mask\n", + "\n", + "[NiftiMasker.fit] Loading data from None200821-08:08:03,197 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Resampling mask\n", + "200821-08:08:03,208 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None200821-08:08:03,223 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "200821-08:08:03,225 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "\n", + "200821-08:08:03,227 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1356/runTimeSeries)\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask200821-08:08:03,252 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1387/runTimeSeries)\n", + "200821-08:08:03,253 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1364/runTimeSeries)\n", + "\n", + "[NiftiMasker.fit] Loading data from None200821-08:08:03,255 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Resampling mask\n", + "\n", + "[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Loading data from None\n", + "\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask200821-08:08:03,263 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1351/runTimeSeries)\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None200821-08:08:03,272 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1369/runTimeSeries)\n", + "\n", + "\n", + "[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Loading data from None\n", + "\n", + "[NiftiMasker.fit] Resampling mask\n", + "200821-08:08:03,276 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "200821-08:08:03,283 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "200821-08:08:03,293 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1307/runTimeSeries)\n", + "200821-08:08:03,319 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1343/runTimeSeries)\n", + "200821-08:08:03,320 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1339/runTimeSeries)\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None200821-08:08:03,339 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask\n", + "200821-08:08:03,351 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "200821-08:08:03,371 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1322/runTimeSeries)\n", + "200821-08:08:03,401 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1315/runTimeSeries)\n", + "200821-08:08:04,153 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a14 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:04,155 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a14-c2c9e0d2-59da-454a-b42e-0d14a5c180b6.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "200821-08:08:04,243 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a13 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:04,245 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a13-c0245223-cfe7-4ecd-a330-41ec6df42370.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:04,313 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a12 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:04,314 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a12-dad6c511-4874-459b-bece-133839a8abd5.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:04,377 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a11 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:04,378 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a11-d4ce083b-2278-4a8c-bd76-f7ca8337c1f1.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:04,442 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a10 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:04,443 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a10-a0c3c35a-442a-44a4-989b-e3dae23f3665.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:04,515 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a09 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:04,516 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a09-e6600ed7-bd56-4cae-817e-531153284749.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:04,582 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a08 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:04,583 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a08-d6c04300-1ba3-4cdf-9c50-ad10892b4681.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "200821-08:08:04,655 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a07 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:04,656 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a07-29ed4b7c-40d5-4dc5-b435-c40322f9e6e1.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:04,722 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a06 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:04,723 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a06-4be87bd6-ba36-418c-8d4d-cc6ba902c5ed.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:04,787 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a05 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:04,788 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a05-d4a1be5e-8fa8-4dfd-9ef1-4c6d93786383.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:04,840 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 5 jobs ready. Free memory (GB): 56.23/56.23, Free processors: 10/10.\n", + "200821-08:08:04,927 nipype.workflow INFO:\n", + "\t [Job 40] Cached (hippAmgTS.removeVars).\n", + "200821-08:08:04,930 nipype.workflow INFO:\n", + "\t [Job 42] Cached (hippAmgTS.removeVars).\n", + "200821-08:08:04,933 nipype.workflow INFO:\n", + "\t [Job 44] Cached (hippAmgTS.removeVars).\n", + "200821-08:08:04,936 nipype.workflow INFO:\n", + "\t [Job 46] Cached (hippAmgTS.removeVars).\n", + "200821-08:08:04,939 nipype.workflow INFO:\n", + "\t [Job 48] Cached (hippAmgTS.removeVars).\n", + "200821-08:08:06,246 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1293/runTimeSeries\".\n", + "200821-08:08:06,256 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1263/runTimeSeries\".\n", + "200821-08:08:06,296 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1253/runTimeSeries\".\n", + "200821-08:08:06,325 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1223/runTimeSeries\".\n", + "200821-08:08:06,354 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"hippAmgTS.runTimeSeries\" in \"/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE008/runTimeSeries\".\n", + "200821-08:08:06,442 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:08:06,479 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:08:06,498 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:08:06,512 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "200821-08:08:06,513 nipype.workflow INFO:\n", + "\t [Node] Running \"runTimeSeries\" (\"nipype.interfaces.utility.wrappers.Function\")\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Loading data from None\n", + "\n", + "\n", + "[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Resampling mask\n", + "\n", + "\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Loading data from None\n", + "\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Resampling mask\n", + "\n", + "[NiftiMasker.fit] Loading data from None200821-08:08:06,939 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "\n", + "\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Loading data from None\n", + "\n", + "[NiftiMasker.fit] Loading data from None\n", + "\n", + "[NiftiMasker.fit] Resampling mask200821-08:08:06,942 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "[NiftiMasker.fit] Resampling mask\n", + "[NiftiMasker.fit] Resampling mask\n", + "\n", + "[NiftiMasker.fit] Loading data from None\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Resampling mask\n", + "200821-08:08:06,945 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "\n", + "[NiftiMasker.fit] Resampling mask[NiftiMasker.fit] Loading data from None\n", + "\n", + "[NiftiMasker.fit] Loading data from None[NiftiMasker.fit] Resampling mask\n", + "\n", + "[NiftiMasker.fit] Resampling mask\n", + "200821-08:08:06,949 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "200821-08:08:06,950 nipype.workflow WARNING:\n", + "\t Storing result file without outputs\n", + "200821-08:08:06,980 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1263/runTimeSeries)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "200821-08:08:06,981 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1293/runTimeSeries)\n", + "200821-08:08:06,994 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE008/runTimeSeries)\n", + "200821-08:08:07,2 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1223/runTimeSeries)\n", + "200821-08:08:07,3 nipype.workflow WARNING:\n", + "\t [Node] Error on \"hippAmgTS.runTimeSeries\" (/media/Data/work/kpe_connAnalysis/hippAmgTS/_subject_id_KPE1253/runTimeSeries)\n", + "200821-08:08:08,158 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a04 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:08,159 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080808-or-runTimeSeries.a04-04542912-03f2-4a66-bf54-c7059447622c.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:08,227 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a03 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:08,228 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080808-or-runTimeSeries.a03-aa67bd06-9d43-41c4-8488-756a59f3aeed.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:08,293 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a02 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:08,294 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080808-or-runTimeSeries.a02-1df5baab-c871-42bd-8107-efe96057f769.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:08,357 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a01 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:08,358 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080808-or-runTimeSeries.a01-fbfac736-1985-4501-8111-dbf8c6dd03c0.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n", + "200821-08:08:08,421 nipype.workflow ERROR:\n", + "\t Node runTimeSeries.a00 failed to run on host or-ThinkStation-P520.\n", + "200821-08:08:08,422 nipype.workflow ERROR:\n", + "\t Saving crash info to /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080808-or-runTimeSeries.a00-f7f11014-5ed5-4cfa-ab5c-fb1d2fb3ef1c.pklz\n", + "Traceback (most recent call last):\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py\", line 67, in run_node\n", + " result[\"result\"] = node.run(updatehash=updatehash)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 516, in run\n", + " result = self._run_interface(execute=True)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 635, in _run_interface\n", + " return self._run_command(execute)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py\", line 741, in _run_command\n", + " result = self._interface.run(cwd=outdir)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/base/core.py\", line 397, in run\n", + " runtime = self._run_interface(runtime)\n", + " File \"/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/interfaces/utility/wrappers.py\", line 142, in _run_interface\n", + " out = function_handle(**args)\n", + " File \"\", line 29, in pooledTS\n", + "NameError: name 'output_dir' is not defined\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "200821-08:08:08,474 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 0 jobs ready. Free memory (GB): 56.23/56.23, Free processors: 10/10.\n", + "200821-08:08:10,130 nipype.workflow INFO:\n", + "\t ***********************************\n", + "200821-08:08:10,131 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a24\n", + "200821-08:08:10,133 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a24-6f26a6f6-9af2-4b90-8273-9b949fd5235f.pklz\n", + "200821-08:08:10,134 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a23\n", + "200821-08:08:10,135 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a23-66df5956-6ab1-498b-b586-218afa97109e.pklz\n", + "200821-08:08:10,136 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a22\n", + "200821-08:08:10,137 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a22-748aaf96-52c4-45b7-8cd2-ca6203483242.pklz\n", + "200821-08:08:10,139 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a21\n", + "200821-08:08:10,140 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a21-164d73b4-87a3-42ec-b294-9b825f553128.pklz\n", + "200821-08:08:10,141 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a20\n", + "200821-08:08:10,142 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a20-3e4b6b1d-bed5-4a5c-b49e-30b74aa47ff6.pklz\n", + "200821-08:08:10,143 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a19\n", + "200821-08:08:10,144 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a19-39869b72-c45a-4cfb-92ee-a62cb9509935.pklz\n", + "200821-08:08:10,145 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a18\n", + "200821-08:08:10,146 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a18-0e359fb3-d9f6-4ec3-87bb-b630f2b06743.pklz\n", + "200821-08:08:10,147 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a17\n", + "200821-08:08:10,148 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a17-904b002a-17af-4213-83e1-5c52a6e0d5c9.pklz\n", + "200821-08:08:10,148 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a16\n", + "200821-08:08:10,149 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a16-062ac9e3-a5d1-40d2-834e-ea99266d837d.pklz\n", + "200821-08:08:10,151 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a15\n", + "200821-08:08:10,152 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080800-or-runTimeSeries.a15-0f52afac-c2c5-4546-a634-fe3a9da9eb87.pklz\n", + "200821-08:08:10,153 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a14\n", + "200821-08:08:10,154 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a14-c2c9e0d2-59da-454a-b42e-0d14a5c180b6.pklz\n", + "200821-08:08:10,154 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a13\n", + "200821-08:08:10,155 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a13-c0245223-cfe7-4ecd-a330-41ec6df42370.pklz\n", + "200821-08:08:10,156 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a12\n", + "200821-08:08:10,157 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a12-dad6c511-4874-459b-bece-133839a8abd5.pklz\n", + "200821-08:08:10,157 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a11\n", + "200821-08:08:10,158 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a11-d4ce083b-2278-4a8c-bd76-f7ca8337c1f1.pklz\n", + "200821-08:08:10,158 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a10\n", + "200821-08:08:10,159 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a10-a0c3c35a-442a-44a4-989b-e3dae23f3665.pklz\n", + "200821-08:08:10,159 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a09\n", + "200821-08:08:10,160 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a09-e6600ed7-bd56-4cae-817e-531153284749.pklz\n", + "200821-08:08:10,160 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a08\n", + "200821-08:08:10,161 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a08-d6c04300-1ba3-4cdf-9c50-ad10892b4681.pklz\n", + "200821-08:08:10,161 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a07\n", + "200821-08:08:10,161 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a07-29ed4b7c-40d5-4dc5-b435-c40322f9e6e1.pklz\n", + "200821-08:08:10,162 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a06\n", + "200821-08:08:10,162 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a06-4be87bd6-ba36-418c-8d4d-cc6ba902c5ed.pklz\n", + "200821-08:08:10,163 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a05\n", + "200821-08:08:10,163 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080804-or-runTimeSeries.a05-d4a1be5e-8fa8-4dfd-9ef1-4c6d93786383.pklz\n", + "200821-08:08:10,164 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a04\n", + "200821-08:08:10,164 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080808-or-runTimeSeries.a04-04542912-03f2-4a66-bf54-c7059447622c.pklz\n", + "200821-08:08:10,165 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a03\n", + "200821-08:08:10,165 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080808-or-runTimeSeries.a03-aa67bd06-9d43-41c4-8488-756a59f3aeed.pklz\n", + "200821-08:08:10,166 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a02\n", + "200821-08:08:10,166 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080808-or-runTimeSeries.a02-1df5baab-c871-42bd-8107-efe96057f769.pklz\n", + "200821-08:08:10,167 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a01\n", + "200821-08:08:10,167 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080808-or-runTimeSeries.a01-fbfac736-1985-4501-8111-dbf8c6dd03c0.pklz\n", + "200821-08:08:10,167 nipype.workflow ERROR:\n", + "\t could not run node: hippAmgTS.runTimeSeries.a00\n", + "200821-08:08:10,168 nipype.workflow INFO:\n", + "\t crashfile: /home/or/kpe_task_analysis/task_based_analysis/conAmg_Hippo/crash-20200821-080808-or-runTimeSeries.a00-f7f11014-5ed5-4cfa-ab5c-fb1d2fb3ef1c.pklz\n", + "200821-08:08:10,168 nipype.workflow INFO:\n", + "\t ***********************************\n" + ] + }, + { + "ename": "RuntimeError", + "evalue": "Workflow did not execute cleanly. Check log for details", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mrunTS\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'MultiProc'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mplugin_args\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m'n_procs'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;36m10\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/engine/workflows.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, plugin, plugin_args, updatehash)\u001b[0m\n\u001b[1;32m 630\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mstr2bool\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"execution\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"create_report\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 631\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_write_report_info\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbase_dir\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexecgraph\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 632\u001b[0;31m \u001b[0mrunner\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexecgraph\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mupdatehash\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mupdatehash\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 633\u001b[0m \u001b[0mdatestr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdatetime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mutcnow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstrftime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"%Y%m%dT%H%M%S\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 634\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mstr2bool\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"execution\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"write_provenance\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/base.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, graph, config, updatehash)\u001b[0m\n\u001b[1;32m 190\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 191\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_remove_node_dirs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 192\u001b[0;31m \u001b[0mreport_nodes_not_run\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnotrun\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 193\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 194\u001b[0m \u001b[0;31m# close any open resources\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/nipype/pipeline/plugins/tools.py\u001b[0m in \u001b[0;36mreport_nodes_not_run\u001b[0;34m(notrun)\u001b[0m\n\u001b[1;32m 96\u001b[0m \u001b[0mlogger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"***********************************\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 97\u001b[0m raise RuntimeError(\n\u001b[0;32m---> 98\u001b[0;31m \u001b[0;34m(\u001b[0m\u001b[0;34m\"Workflow did not execute cleanly. \"\u001b[0m \u001b[0;34m\"Check log for details\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 99\u001b[0m )\n\u001b[1;32m 100\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mRuntimeError\u001b[0m: Workflow did not execute cleanly. Check log for details" + ] + } + ], + "source": [ + "runTS.run('MultiProc', plugin_args={'n_procs': 10})" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "#subject_list = ['KPE008']\n", + "subAmg, subHipp, subVMPFC = pooledTS(subject_list, '1')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "subAmg_2, subHipp_2 , subVMPFC_2= pooledTS(subject_list, '2')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.plot(subAmg[1])\n", + "plt.plot(subHipp[1])\n", + "plt.plot(subVMPFC[1])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "np.array(subAmg_2).shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#add both to same array\n", + "both1 = np.dstack([subAmg, subHipp, subVMPFC])\n", + "both1.shape\n", + "both2 = np.dstack([subAmg_2, subHipp_2, subVMPFC_2])\n", + "both2.shape\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from nilearn import connectome\n", + "connectome = connectome.ConnectivityMeasure(\n", + " kind='correlation', vectorize=False)\n", + "\n", + "mat_ses1 = connectome.fit_transform(both1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.heatmap(np.mean(mat_ses1, axis=0), annot=True, cmap='coolwarm')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mat_ses2 = connectome.fit_transform(both2)\n", + "sns.heatmap(np.mean(mat_ses2, axis=0), annot=True, cmap=\"coolwarm\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket1 = mat_ses1[condition_label==1]\n", + "mid1 = mat_ses1[condition_label==0]\n", + "ket2 = mat_ses2[condition_label==1]\n", + "mid2 = mat_ses2[condition_label==0]\n", + "sns.heatmap(np.mean(ket2, axis=0), cmap='coolwarm', annot=True)\n", + "plt.show()\n", + "sns.heatmap(np.mean(mid2, axis=0), cmap='coolwarm', annot=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "t, p =scipy.stats.ttest_ind(ket2, mid2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "p" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket2_1 = np.subtract(ket2, ket1)\n", + "mid2_1 = np.subtract(mid2, mid1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "t, p =scipy.stats.ttest_ind(ket2_1, mid2_1)\n", + "p" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.heatmap(t, cmap='coolwarm', annot=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mat2_1 = np.subtract(mat_ses2, mat_ses1)\n", + "dfDelta = pd.DataFrame({'scr_id':subject_list, 'group':condition_label,\n", + " 'amg_hippo': mat2_1[:,0,1],\n", + " 'amg_vpmfc': mat2_1[:,0,2]})" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.boxplot( y= 'amg_vpmfc',x= 'group', data= dfDelta, saturation=0.2)\n", + "sns.stripplot( y= 'amg_vpmfc',x= 'group', data= dfDelta)\n", + "scipy.stats.ttest_ind(dfDelta.amg_vpmfc[dfDelta.group==1], \n", + " dfDelta.amg_vpmfc[dfDelta.group==0])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pymc3 as pm\n", + "from pymc3.glm import GLM\n", + "\n", + "with pm.Model() as model_glm:\n", + " GLM.from_formula('amg_vpmfc ~ group', dfDelta)\n", + " trace = pm.sample(draws=4000, tune=3000)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pm.summary(trace, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ci = np.quantile(trace.group, [.025,.975]) # take credible intervals from the trace" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "fig, (ax1, ax2) = plt.subplots(1,2, figsize=(4, 5),gridspec_kw={'width_ratios': [1, .2],\n", + " 'wspace':.1})\n", + "g1 = sns.stripplot(y= 'amg_vpmfc', x='group', data=dfDelta, size = 8, ax=ax1)\n", + "sns.boxplot(y= 'amg_vpmfc', x='group', data=dfDelta, ax=ax1,\n", + " boxprops=dict(alpha=.3))\n", + "g2 = sns.distplot(trace['group'], ax = ax2, vertical=True)\n", + "ax2.vlines(x=0.2,ymin=ci[0], ymax=ci[1], color='black', \n", + " linewidth = 1.5, linestyle = \"-\")\n", + "\n", + "#g3.set_ylim(-.7, .7)\n", + "ax1.set_ylim(-.7,.7)\n", + "ax2.set_ylim(-.7,.7)\n", + "ax2.set_ylabel(\"Difference between groups\", fontsize=14) \n", + "ax2.yaxis.set_label_position(\"right\")\n", + "ax2.yaxis.tick_right()\n", + "ax2.set_xticks([])\n", + "ax1.set_ylabel(\"Amg-vmPFC change in connectivity\", fontsize=14)\n", + "ax1.set_xlabel(\"Group\", fontsize=14)\n", + "ax1.set_xticklabels(['Midazolam', 'Ketamine'])\n", + "fig.savefig(\"amgvmPFC.png\", dpi=300, bbox_inches='tight')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# only first 30sec\n", + "both1_30 = both1[:, 0:120, :]\n", + "both2_30 = both2[:, 0:120, :]\n", + "\n", + "mat_ses1_30 = connectome.fit_transform(both1_30)\n", + "mat_ses2_30 = connectome.fit_transform(both2_30)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket1 = mat_ses1_30[condition_label==1]\n", + "mid1 = mat_ses1_30[condition_label==0]\n", + "ket2 = mat_ses2_30[condition_label==1]\n", + "mid2 = mat_ses2_30[condition_label==0]\n", + "\n", + "ket2_1 = np.subtract(ket2, ket1)\n", + "mid2_1 = np.subtract(mid2, mid1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "t, p =scipy.stats.ttest_ind(ket2, mid2)\n", + "p" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## test for different time frames (30,60,90,120) sec\n", + "ses = '2'\n", + "duration = 60\n", + "for sub in subject_list:\n", + " subject = sub.split('KPE')[1]\n", + " amgTS = np.load(output_dir + 'sub-' + subject + 'amygdalaMeanTS' + 'ses-' + ses + '.npy')\n", + " hippTS = np.load(output_dir + 'sub-' + subject + 'hippoMeanTS' + 'ses-' + ses + '.npy')\n", + " vmpfcTS = np.load(output_dir + 'sub-' + subject + 'vmPFCMeanTS' + 'ses-' + ses + '.npy')\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.7.7 64-bit ('neuroAnalysis': conda)", + "language": "python", + "name": "python37764bitneuroanalysiscondaa23731adadc74dd9881a406adec17ad1" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/conAmg_Hippo/amgvmPFC.png b/task_based_analysis/conAmg_Hippo/amgvmPFC.png new file mode 100644 index 0000000..093eb8f Binary files /dev/null and b/task_based_analysis/conAmg_Hippo/amgvmPFC.png differ diff --git a/task_based_analysis/conAmg_Hippo/corr_computation_onlyamgHippo.ipynb b/task_based_analysis/conAmg_Hippo/corr_computation_onlyamgHippo.ipynb new file mode 100644 index 0000000..ebf2718 --- /dev/null +++ b/task_based_analysis/conAmg_Hippo/corr_computation_onlyamgHippo.ipynb @@ -0,0 +1,595 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Mask amygdala hippocampus and correlate the trauma script" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import scipy\n", + "import nilearn.plotting\n", + "import nilearn.input_data\n", + "import os\n", + "import nipype.pipeline.engine as pe # pypeline engine\n", + "import nipype.interfaces.utility as util # utility" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "output_dir = '/media/Data/work/kpe_connAnalysis'\n", + "ses = '1'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## set parameters for the maskers\n", + "mask_params = {\n", + " 'detrend': True, 'standardize': True,\n", + " 'high_pass': 0.01, 'low_pass': 0.1, 't_r': 1,\n", + " 'smoothing_fwhm': 4,\n", + " 'verbose': 5}\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Amygdala as mask\n", + "amg_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + "amg_file = nilearn.image.math_img(\"a>=25\", a=amg_file)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(amg_file)\n", + "\n", + "\n", + "masker_amg = nilearn.input_data.NiftiMasker(mask_img= amg_file, **mask_params).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# now lets do the same with vmPFC\n", + "vmpfc_mask = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", + "vmpfc_mask = nilearn.image.math_img(\"a>=5\", a=vmpfc_mask)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(vmpfc_mask)\n", + "masker_vmpfc = nilearn.input_data.NiftiMasker(mask_img= vmpfc_mask, **mask_params).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Hippocampus\n", + "hipp_mask = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + "hipp_mask = nilearn.image.math_img(\"a>=15\", a=hipp_mask)\n", + "%matplotlib inline\n", + "nilearn.plotting.plot_roi(hipp_mask)\n", + "masker_hipp = nilearn.input_data.NiftiMasker(mask_img= mask_file, **mask_params).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def removeVars (sub, ses):\n", + " \n", + " # this method takes the csv regressors file (from fmriPrep) and chooses a few to confound. You can change those few\n", + " import pandas as pd\n", + " import numpy as np\n", + " subject = sub.split('KPE')[1]\n", + " confound_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_desc-confounds_regressors.tsv'\n", + " confoundFile = confound_template.format(sub=subject, ses=ses)\n", + " confound = pd.read_csv(confoundFile,sep=\"\\t\", na_values=\"n/a\")\n", + " finalConf = confound[['csf', 'white_matter', 'framewise_displacement', \n", + " 'a_comp_cor_00', 'a_comp_cor_01',\t'a_comp_cor_02', 'a_comp_cor_03', \n", + " 'a_comp_cor_04', 'a_comp_cor_05', 'trans_x', 'trans_y', 'trans_z', \n", + " 'rot_x', 'rot_y', 'rot_z']] # can add 'global_signal' also ,,\n", + " # \n", + " # change NaN of FD to zero\n", + " finalConf = finalConf.fillna(0)\n", + " return np.array(finalConf)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# method to generate subject array of timeseries\n", + "def pooledTS(sub, ses, confounds, output_dir):\n", + " import os\n", + " import numpy as np\n", + " import nilearn.input_data\n", + " import nilearn.image\n", + " \n", + " event_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/sub-{sub}_ses-{ses}_30sec_window.csv'\n", + " func_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz'\n", + " # set mask params\n", + " mask_params = {\n", + " 'detrend': True, 'standardize': True,\n", + " 'high_pass': 0.01, 'low_pass': 0.1, 't_r': 1,\n", + " 'smoothing_fwhm': 4,\n", + " 'verbose': 5}\n", + "\n", + " amg_file = '/media/Data/work/KPE_ROI/amygdala_association-test_z_FDR_0.01.nii.gz'\n", + " amg_file = nilearn.image.math_img(\"a>=25\", a=amg_file)\n", + " hipp_mask = '/media/Data/work/KPE_ROI/hippocampus_association-test_z_FDR_0.01.nii.gz'\n", + " hipp_mask = nilearn.image.math_img(\"a>=15\", a=hipp_mask)\n", + " vmpfc_mask = '/media/Data/work/RCF_or/vmpfc_association-test_z_FDR_0.01.nii.gz'\n", + " vmpfc_mask = nilearn.image.math_img(\"a>=5\", a=vmpfc_mask)\n", + "\n", + " \n", + " # fit maskers\n", + " masker_amg = nilearn.input_data.NiftiMasker(mask_img= amg_file, **mask_params).fit()\n", + " masker_vmpfc = nilearn.input_data.NiftiMasker(mask_img= vmpfc_mask, **mask_params).fit()\n", + " masker_hipp = nilearn.input_data.NiftiMasker(mask_img= hipp_mask, **mask_params).fit()\n", + " # set output dir\n", + " if not os.path.exists(output_dir):\n", + " os.makedirs(output_dir)\n", + " duration = 120 #set duration of event in seconds \n", + " #sub_tsAmg = []\n", + " #sub_tsHipp = []\n", + " #sub_tsvmPFC = []\n", + " #for sub in subject_list:\n", + " subject = sub.split('KPE')[1]\n", + "\n", + " # load the npy file (timeseries)\n", + " tsAmg = masker_amg.transform(func_template.format(sub=subject, ses=ses), confounds)\n", + " tsHipp = masker_hipp.transform(func_template.format(sub=subject, ses=ses),confounds)\n", + " tsvmPFC = masker_vmpfc.transform(func_template.format(sub=subject, ses=ses),confounds)\n", + " event = event_template.format(sub=subject, ses=ses)\n", + " events = pd.read_csv(event, sep='\\t')\n", + " onset = int(events.onset[events.trial_type_30=='trauma1_0']) # take onset of trauma first script\n", + " tsAmg_script = tsAmg[onset:onset+duration, :]\n", + " tsHipp_script = tsHipp[onset:onset+duration, :]\n", + " tsvmPFC_script = tsvmPFC[onset:onset+duration, :]\n", + " tsAmg_mean = np.mean(tsAmg_script, axis=1)\n", + " tsHipp_mean = np.mean(tsHipp_script, axis=1)\n", + " tsvmPFC_mean = np.mean(tsvmPFC_script, axis=1)\n", + " np.save(output_dir + 'sub-' + subject + 'amygdalaMeanTS' + 'ses-' + ses, tsAmg_mean)\n", + " np.save(output_dir + 'sub-' + subject + 'hippoMeanTS' + 'ses-' + ses, tsHipp_mean)\n", + " np.save(output_dir + 'sub-' + subject + 'vmPFCMeanTS' + 'ses-' + ses, tsvmPFC_mean)\n", + "# sub_tsAmg.append(tsAmg_mean)\n", + "# sub_tsHipp.append(tsHipp_mean)\n", + "# sub_tsvmPFC.append(tsvmPFC_mean)\n", + " return tsAmg_mean, tsHipp_mean , tsvmPFC_mean" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## condition labels (ketamine , midazolam)\n", + "# read file\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "subject_list = np.array(medication_cond.scr_id)\n", + "condition_label = np.array(medication_cond.med_cond)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "subject_list = subject_list[0:24] # removing 1578 \n", + "condition_label = condition_label[0:24]\n", + "subject_list" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "infosource = pe.Node(util.IdentityInterface(fields=['subject_id'\n", + " ],\n", + " ),\n", + " name=\"infosource\")\n", + "infosource.iterables = [('subject_id', subject_list)]\n", + "\n", + "removeVars = pe.Node(util.Function(\n", + " input_names=['sub','ses'],\n", + " output_names=['finalConf'],\n", + " function=removeVars),\n", + " name=\"removeVars\")\n", + "\n", + "removeVars.inputs.ses = ses\n", + "\n", + "runTimeSeries = pe.Node(util.Function(\n", + " input_names=['sub','ses','confounds', 'output_dir'],\n", + " output_names=['tsAmg_mean', 'tsHipp_mean', 'tsvmPFC_mean'],\n", + " function=pooledTS),\n", + " name=\"runTimeSeries\")\n", + "\n", + "\n", + "runTimeSeries.inputs.output_dir = output_dir\n", + "runTimeSeries.inputs.ses = ses\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "amg_file" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "runTS = pe.Workflow(name='hippAmgTS', base_dir = output_dir)\n", + "runTS.connect([\n", + " (infosource, removeVars, [('subject_id', 'sub')]),\n", + " (infosource, runTimeSeries, [('subject_id', 'sub')]),\n", + " (removeVars, runTimeSeries, [('finalConf', 'confounds')])\n", + "])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "runTS.run('MultiProc', plugin_args={'n_procs': 10})" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "#subject_list = ['KPE008']\n", + "subAmg, subHipp, subVMPFC = pooledTS(subject_list, '1')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "subAmg_2, subHipp_2 , subVMPFC_2= pooledTS(subject_list, '2')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.plot(subAmg[1])\n", + "plt.plot(subHipp[1])\n", + "plt.plot(subVMPFC[1])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "np.array(subAmg_2).shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#add both to same array\n", + "both1 = np.dstack([subAmg, subHipp, subVMPFC])\n", + "both1.shape\n", + "both2 = np.dstack([subAmg_2, subHipp_2, subVMPFC_2])\n", + "both2.shape\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from nilearn import connectome\n", + "connectome = connectome.ConnectivityMeasure(\n", + " kind='correlation', vectorize=False)\n", + "\n", + "mat_ses1 = connectome.fit_transform(both1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.heatmap(np.mean(mat_ses1, axis=0), annot=True, cmap='coolwarm')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mat_ses2 = connectome.fit_transform(both2)\n", + "sns.heatmap(np.mean(mat_ses2, axis=0), annot=True, cmap=\"coolwarm\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket1 = mat_ses1[condition_label==1]\n", + "mid1 = mat_ses1[condition_label==0]\n", + "ket2 = mat_ses2[condition_label==1]\n", + "mid2 = mat_ses2[condition_label==0]\n", + "sns.heatmap(np.mean(ket2, axis=0), cmap='coolwarm', annot=True)\n", + "plt.show()\n", + "sns.heatmap(np.mean(mid2, axis=0), cmap='coolwarm', annot=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "t, p =scipy.stats.ttest_ind(ket2, mid2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "p" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket2_1 = np.subtract(ket2, ket1)\n", + "mid2_1 = np.subtract(mid2, mid1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "t, p =scipy.stats.ttest_ind(ket2_1, mid2_1)\n", + "p" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.heatmap(t, cmap='coolwarm', annot=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mat2_1 = np.subtract(mat_ses2, mat_ses1)\n", + "dfDelta = pd.DataFrame({'scr_id':subject_list, 'group':condition_label,\n", + " 'amg_hippo': mat2_1[:,0,1],\n", + " 'amg_vpmfc': mat2_1[:,0,2]})" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.boxplot( y= 'amg_vpmfc',x= 'group', data= dfDelta, saturation=0.2)\n", + "sns.stripplot( y= 'amg_vpmfc',x= 'group', data= dfDelta)\n", + "scipy.stats.ttest_ind(dfDelta.amg_vpmfc[dfDelta.group==1], \n", + " dfDelta.amg_vpmfc[dfDelta.group==0])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pymc3 as pm\n", + "from pymc3.glm import GLM\n", + "\n", + "with pm.Model() as model_glm:\n", + " GLM.from_formula('amg_vpmfc ~ group', dfDelta)\n", + " trace = pm.sample(draws=4000, tune=3000)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pm.summary(trace, credible_interval=.95).round(2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ci = np.quantile(trace.group, [.025,.975]) # take credible intervals from the trace" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "fig, (ax1, ax2) = plt.subplots(1,2, figsize=(4, 5),gridspec_kw={'width_ratios': [1, .2],\n", + " 'wspace':.1})\n", + "g1 = sns.stripplot(y= 'amg_vpmfc', x='group', data=dfDelta, size = 8, ax=ax1)\n", + "sns.boxplot(y= 'amg_vpmfc', x='group', data=dfDelta, ax=ax1,\n", + " boxprops=dict(alpha=.3))\n", + "g2 = sns.distplot(trace['group'], ax = ax2, vertical=True)\n", + "ax2.vlines(x=0.2,ymin=ci[0], ymax=ci[1], color='black', \n", + " linewidth = 1.5, linestyle = \"-\")\n", + "\n", + "#g3.set_ylim(-.7, .7)\n", + "ax1.set_ylim(-.7,.7)\n", + "ax2.set_ylim(-.7,.7)\n", + "ax2.set_ylabel(\"Difference between groups\", fontsize=14) \n", + "ax2.yaxis.set_label_position(\"right\")\n", + "ax2.yaxis.tick_right()\n", + "ax2.set_xticks([])\n", + "ax1.set_ylabel(\"Amg-vmPFC change in connectivity\", fontsize=14)\n", + "ax1.set_xlabel(\"Group\", fontsize=14)\n", + "ax1.set_xticklabels(['Midazolam', 'Ketamine'])\n", + "fig.savefig(\"amgvmPFC.png\", dpi=300, bbox_inches='tight')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# only first 30sec\n", + "both1_30 = both1[:, 0:120, :]\n", + "both2_30 = both2[:, 0:120, :]\n", + "\n", + "mat_ses1_30 = connectome.fit_transform(both1_30)\n", + "mat_ses2_30 = connectome.fit_transform(both2_30)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ket1 = mat_ses1_30[condition_label==1]\n", + "mid1 = mat_ses1_30[condition_label==0]\n", + "ket2 = mat_ses2_30[condition_label==1]\n", + "mid2 = mat_ses2_30[condition_label==0]\n", + "\n", + "ket2_1 = np.subtract(ket2, ket1)\n", + "mid2_1 = np.subtract(mid2, mid1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "t, p =scipy.stats.ttest_ind(ket2, mid2)\n", + "p" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## test for different time frames (30,60,90,120) sec\n", + "ses = '2'\n", + "duration = 60\n", + "for sub in subject_list:\n", + " subject = sub.split('KPE')[1]\n", + " amgTS = np.load(output_dir + 'sub-' + subject + 'amygdalaMeanTS' + 'ses-' + ses + '.npy')\n", + " hippTS = np.load(output_dir + 'sub-' + subject + 'hippoMeanTS' + 'ses-' + ses + '.npy')\n", + " vmpfcTS = np.load(output_dir + 'sub-' + subject + 'vmPFCMeanTS' + 'ses-' + ses + '.npy')\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.7.7 64-bit ('neuroAnalysis': conda)", + "language": "python", + "name": "python37764bitneuroanalysiscondaa23731adadc74dd9881a406adec17ad1" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/connUtils.py b/task_based_analysis/connUtils.py new file mode 100644 index 0000000..86e9f76 --- /dev/null +++ b/task_based_analysis/connUtils.py @@ -0,0 +1,261 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +Created on Mon Dec 9 15:14:01 2019 + +@author: Or Duek +This file should contain all connectivity analysis functions so we could load from it to other files +""" +import numpy as np +import scipy + +def removeVars (confoundFile): + # this method takes the csv regressors file (from fmriPrep) and chooses a few to confound. You can change those few + import pandas as pd + confound = pd.read_csv(confoundFile,sep="\t", na_values="n/a") + finalConf = confound[['csf', 'white_matter', 'framewise_displacement', + 'a_comp_cor_00', 'a_comp_cor_01', 'a_comp_cor_02', 'a_comp_cor_03', 'a_comp_cor_04', + 'a_comp_cor_05', 'trans_x', 'trans_y', 'trans_z', 'rot_x', 'rot_y', 'rot_z']] # can add 'global_signal' also + # change NaN of FD to zero + finalConf = np.array(finalConf) + finalConf[0,2] = 0 # if removing FD than should remove this one also + return finalConf + +# build method for creating time series for subjects +def timeSeries(func_files, confound_files, atlas_filename): + # This function receives a list of funcional files and a list of matching confound files + # and outputs an array + from nilearn.input_data import NiftiLabelsMasker + # define masker here + masker = NiftiLabelsMasker(labels_img=atlas_filename, standardize=True, smoothing_fwhm = 6, + memory="nilearn_cashe",t_r=1, verbose=5, high_pass=.01 , low_pass = .1) # As it is task based we dont' bandpassing high_pass=.01 , low_pass = .1) + total_subjects = [] # creating an empty array that will hold all subjects matrix + # This function needs a masker object that will be defined outside the function + for func_file, confound_file in zip(func_files, confound_files): + print(f"proccessing file {func_file}") # print file name + confoundClean = removeVars(confound_file) + confoundArray = confoundClean#confoundClean.values + time_series = masker.fit_transform(func_file, confounds=confoundArray) + #time_series = extractor.fit_transform(func_file, confounds=confoundArray) + #masker.fit_transform(func_file, confoundArray) + total_subjects.append(time_series) + return total_subjects + +def timeSeriesSingle(func_file, confound_file, atlas_filename): + # this function receives one functional and one confound file and returns one time-series + from connUtils import removeVars + from nilearn.input_data import NiftiLabelsMasker + # define masker here + masker = NiftiLabelsMasker(labels_img=atlas_filename, standardize=True, smoothing_fwhm = 6, + memory="nilearn_cashe",t_r=1, verbose=5, high_pass=.01 , low_pass = .1) # As it is task based we dont' bandpassing high_pass=.01 , low_pass = .1) + # This function needs a masker object that will be defined outside the function + confoundClean = removeVars(confound_file) + confoundArray = confoundClean#confoundClean.values + time_series = masker.fit_transform(func_file, confounds=confoundArray) + return time_series + +# contrasting two timePoints +def contFuncs(time_series1, time_series2): + twoMinusOneMat = [] + for scanMatrix, scanMatrix2 in zip(time_series1, time_series2): + a = scanMatrix2 - scanMatrix + twoMinusOneMat.append(a) + return np.array(twoMinusOneMat) + +# create correlation matrix per subject +def createCorMat(time_series): + from nilearn.connectome import ConnectivityMeasure + correlation_measure = ConnectivityMeasure(kind='correlation') # can choose partial - it might be better + # create correlation matrix for each subject + fullMatrix = [] + for time_s in time_series: + correlation_matrix = correlation_measure.fit_transform([time_s])[0] + fullMatrix.append(correlation_matrix) + return fullMatrix + +# ############################################################################# +# # Seed based functions + +def createSeedVoxelSeries(roi_file, func_filename, confound_filename, mask_file, subject): + from nilearn import input_data + seed_masker = input_data.NiftiMasker(mask_img = roi_file, + smoothing_fwhm=6, + detrend=True, standardize=True, + low_pass=0.1, high_pass=0.01, t_r=1., + memory='/media/Data/nilearn', memory_level=1, verbose=2) + + brain_masker = input_data.NiftiMasker(mask_img = mask_file, + smoothing_fwhm=6, + detrend=True, standardize=True, + low_pass=0.1, high_pass=0.01, t_r=1., + memory='/media/Data/nilearn', memory_level=1, verbose=2) + + seed_time_series = seed_masker.fit_transform(func_filename, + confounds=removeVars(confound_filename)) + + #seed_time_series = np.mean(seed_time_series, axis=0) + + brain_time_series = brain_masker.fit_transform(func_filename, + confounds=removeVars(confound_filename)) + + + return seed_time_series, brain_time_series, brain_masker + + +# stratify to events +def seedVoxelCor(spec_seed_timeseries, spec_brain_timeseries, scriptName, subject, brain_masker, func_file, session, seedName): + import numpy as np + + seed_to_voxel_correlations = (np.dot(spec_brain_timeseries.T, spec_seed_timeseries) / + spec_seed_timeseries.shape[0] + ) + + + from nilearn import plotting + + seed_to_voxel_correlations_img = brain_masker.inverse_transform( + seed_to_voxel_correlations.T) + + + seed_to_voxel_correlations_fisher_z = np.arctanh(seed_to_voxel_correlations) + print("Seed-to-voxel correlation Fisher-z transformed: min = %.3f; max = %.3f" + % (seed_to_voxel_correlations_fisher_z.min(), + seed_to_voxel_correlations_fisher_z.max() + ) + ) + + # Finally, we can tranform the correlation array back to a Nifti image + # object, that we can save. + seed_to_voxel_correlations_fisher_z_img = brain_masker.inverse_transform( + seed_to_voxel_correlations_fisher_z.T) + seed_to_voxel_correlations_fisher_z_img.to_filename( + '%s_seed_%s_sub-%s_ses-%s_z.nii.gz' %(scriptName,seedName,subject, session)) + + return seed_to_voxel_correlations, seed_to_voxel_correlations_fisher_z +# this function returns the regular correlation matrix, the fishr-z transformation of correlation matrix and the brain masker (for inverse transform the brain back to nifti image) + +def createDelta(func_files1, func_files2, mask_img): + from nilearn.input_data import NiftiMasker + + # here I use a masked image so all will have same size + nifti_masker = NiftiMasker( + mask_img= mask_img, + smoothing_fwhm=6, + memory='nilearn_cache', memory_level=1, verbose=2) # cache options + fmri_masked_ses1 = nifti_masker.fit_transform(func_files1) + fmri_masked_ses2 = nifti_masker.fit_transform(func_files2) + ### + from nilearn import input_data + brainMasker = input_data.NiftiMasker( + smoothing_fwhm=6, + detrend=True, standardize=True, + t_r=1., + memory='nilearn_cashe', memory_level=1, verbose=2) + brainMasker.fit(func_files1) + + #### + deltaCor_a = fmri_masked_ses2 - fmri_masked_ses1 + print (f'Shape is: {deltaCor_a.shape}') + + # run paired t-test + testDelta = scipy.stats.ttest_rel(fmri_masked_ses1, fmri_masked_ses2) + print (f'Sum of p values < 0.005 is {np.sum(testDelta[1]<0.005)}') + + + return deltaCor_a, testDelta # return the delta correlation and the t-test array + +def createZimg(deltaCor, scriptName, seedName): + from nilearn import input_data + brainMasker = input_data.NiftiMasker( + smoothing_fwhm=6, + detrend=True, standardize=True, + t_r=1., + memory='nilearn_cashe', memory_level=1, verbose=2) + # mean across subjects + mean_zcor_Delta = np.mean(deltaCor,0) + mean_zcor_img_delta = brainMasker.inverse_transform(mean_zcor_Delta.T) + # save it as file + mean_zcor_img_delta.to_filename( + '%s_seed_%s_delta_z.nii.gz' %(scriptName,seedName)) + + return mean_zcor_img_delta, mean_zcor_Delta # returns the image and the array + +## now create a function to do FDR thresholding +def fdrThr(testDelta, mean_zcor_Delta, alpha, brain_masker): + from statsmodels.stats import multitest + # we need to reshape the test p-values array to create 1D array + #b = np.reshape(np.array(testDelta[1]), -1) + fdr_mat = multitest.multipletests(testDelta[1], alpha=alpha, method='fdr_bh', is_sorted=False, returnsorted=False) + #fdr_mat = multitest.fdrcorrection(testDelta[1], alpha=0.7, method='indep', is_sorted=False) + np.sum(fdr_mat[1]<0.05) + corr_mat_thrFDR = np.array(mean_zcor_Delta) + corr_mat_thrFDR = np.reshape(corr_mat_thrFDR, -1) + corr_mat_thrFDR[fdr_mat[0]==False] = 0 + + # now I can treshold the mean matrix + numNonZeroDelta = np.count_nonzero(corr_mat_thrFDR) + print (f'Number of voxels crossed the FDR thr is {numNonZeroDelta}') + # transofrm it back to nifti + nifti_fdr_thr = brain_masker.inverse_transform(corr_mat_thrFDR.T) + return corr_mat_thrFDR, nifti_fdr_thr # return matrix after FDR and nifti file + +#%% KPE specific functions +# need to build a function that will read the event file - take onset and duration of each line and stratify the timeseries accordingly +def stratifyTimeseries (events_file, subject_timeseries, subject_id, trial_line): + #trial_line is a parameter - if 0 then will create each line as file. If 1 then each task + import pandas as pd + import numpy as np + import os + # grab subject events file + events = pd.read_csv(events_file, sep=r'\s+') + timeSeries = subject_timeseries #np.array(np.load(subject_timeseries, allow_pickle = True)) + + # create a subject folder + try: + # check if already there + os.makedirs('subject_%s' %(subject_id)) + except: + print ("Dir already preset") + + # read line by line and create matrix per line + if trial_line==0: + for line in events.iterrows(): + print (f' Proccessing line {line}') + numberRow = line[0] # take row number to add to matrix name later + onset = round(line[1].onset) # take onset and round it + duration = round(line[1].duration) + trial_type = line[1].trial_type + specTimeline = timeSeries[onset:(onset+duration),:] + np.save('subject_%s/speficTrial_%s_%s' %(subject_id,numberRow, trial_type), specTimeline) + elif trial_line==1: # read by trial type and create specific timeline for each script + traumaOnset = [] + sadOnset = [] + relaxOnset = [] + traumaDuration = [] + sadDuration = [] + relaxDuration = [] + for line in events.iterrows(): # runs trhough the events file, takes the specific files and create timeseries per each + print (line) + if line[1]['trial_type'].find('trauma')!= -1: + print('trauma') + traumaOnset.append(round(line[1].onset)) + traumaDuration.append(round(line[1].duration)) + elif line[1]['trial_type'].find('sad')!= -1: + print('sad') + sadOnset.append(round(line[1].onset)) + sadDuration.append(round(line[1].duration)) + elif line[1]['trial_type'].find('relax')!= -1: + print('relax') + relaxOnset.append(round(line[1].onset)) + relaxDuration.append(round(line[1].duration)) + trauma_timeline = np.concatenate([timeSeries[traumaOnset[0]:traumaOnset[0] + traumaDuration[0],:], timeSeries[traumaOnset[1]:traumaOnset[1]+ traumaDuration[1],:], timeSeries[traumaOnset[2]:traumaOnset[2]+traumaDuration[2],:]]) + sad_timeline = np.concatenate([timeSeries[sadOnset[0]:sadOnset[0] + sadDuration[0],:], timeSeries[traumaOnset[1]:sadOnset[1]+ sadDuration[1],:], timeSeries[sadOnset[2]:sadOnset[2]+sadDuration[2],:]]) + relax_timeline = np.concatenate([timeSeries[relaxOnset[0]:relaxOnset[0] + relaxDuration[0],:], timeSeries[relaxOnset[1]:relaxOnset[1]+ relaxDuration[1],:], timeSeries[relaxOnset[2]:relaxOnset[2]+relaxDuration[2],:]]) + np.save('subject_%s/traumaTrials' %(subject_id), trauma_timeline) + np.save('subject_%s/sadTrials' %(subject_id), sad_timeline) + np.save('subject_%s/relaxTrials' %(subject_id), relax_timeline) + + # or read by trial type and create matrix per trial type + else: + print ("Need to run by task") + # extract subject specific timeseries from 3D array diff --git a/task_based_analysis/consort_graphviz.ipynb b/task_based_analysis/consort_graphviz.ipynb new file mode 100644 index 0000000..f8e4a2d --- /dev/null +++ b/task_based_analysis/consort_graphviz.ipynb @@ -0,0 +1,184 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from graphviz import Digraph" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "dot = Digraph(comment='KPE CONSORT', node_attr={'shape': 'rectangle', 'color':'lightblue', 'style':'filled'})" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "dot.node('A', 'Total Screened\\n N=119')\n", + "dot.node('B', 'Total Eligible\\n N=30')\n", + "dot.node('C','Total Randomized\\n N=25\\n Ketamine=13 Midazolam=12')\n", + "dot.node('D', 'Participated in 1st visit\\n N=25')\n", + "dot.node('E', 'Participated in 2nd visit')\n", + "dot.node('F', 'Participated in 3rd visit')\n", + "dot.node('G', 'Participated in 4th visit')\n", + "dot.edges(['AB', 'BC', 'CD','DE','EF', 'FG'])" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "%3\n", + "\n", + "\n", + "\n", + "A\n", + "\n", + "Total Screened\n", + " N=119\n", + "\n", + "\n", + "\n", + "B\n", + "\n", + "Total Eligible\n", + " N=30\n", + "\n", + "\n", + "\n", + "A->B\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "C\n", + "\n", + "Total Randomized\n", + " N=25\n", + " Ketamine=13 Midazolam=12\n", + "\n", + "\n", + "\n", + "B->C\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "D\n", + "\n", + "Participated in 1st visit\n", + " N=25\n", + "\n", + "\n", + "\n", + "C->D\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "E\n", + "\n", + "Participated in 2nd visit\n", + "\n", + "\n", + "\n", + "D->E\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "F\n", + "\n", + "Participated in 3rd visit\n", + "\n", + "\n", + "\n", + "E->F\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "G\n", + "\n", + "Participated in 4th visit\n", + "\n", + "\n", + "\n", + "F->G\n", + "\n", + "\n", + "\n", + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dot" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.7.7 64-bit ('neuroAnalysis': conda)", + "language": "python", + "name": "python37764bitneuroanalysiscondaa23731adadc74dd9881a406adec17ad1" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/corrstats.py b/task_based_analysis/corrstats.py new file mode 100644 index 0000000..62a9a71 --- /dev/null +++ b/task_based_analysis/corrstats.py @@ -0,0 +1,114 @@ +""" +Functions for calculating the statistical significant differences between two dependent or independent correlation +coefficients. +The Fisher and Steiger method is adopted from the R package http://personality-project.org/r/html/paired.r.html +and is described in detail in the book 'Statistical Methods for Psychology' +The Zou method is adopted from http://seriousstats.wordpress.com/2012/02/05/comparing-correlations/ +Credit goes to the authors of above mentioned packages! + +Author: Philipp Singer (www.philippsinger.info) +""" + +from __future__ import division + +__author__ = 'psinger' + +import numpy as np +from scipy.stats import t, norm +from math import atanh, pow +from numpy import tanh + +def rz_ci(r, n, conf_level = 0.95): + zr_se = pow(1/(n - 3), .5) + moe = norm.ppf(1 - (1 - conf_level)/float(2)) * zr_se + zu = atanh(r) + moe + zl = atanh(r) - moe + return tanh((zl, zu)) + +def rho_rxy_rxz(rxy, rxz, ryz): + num = (ryz-1/2.*rxy*rxz)*(1-pow(rxy,2)-pow(rxz,2)-pow(ryz,2))+pow(ryz,3) + den = (1 - pow(rxy,2)) * (1 - pow(rxz,2)) + return num/float(den) + +def dependent_corr(xy, xz, yz, n, twotailed=True, conf_level=0.95, method='steiger'): + """ + Calculates the statistic significance between two dependent correlation coefficients + @param xy: correlation coefficient between x and y + @param xz: correlation coefficient between x and z + @param yz: correlation coefficient between y and z + @param n: number of elements in x, y and z + @param twotailed: whether to calculate a one or two tailed test, only works for 'steiger' method + @param conf_level: confidence level, only works for 'zou' method + @param method: defines the method uses, 'steiger' or 'zou' + @return: t and p-val + """ + if method == 'steiger': + d = xy - xz + determin = 1 - xy * xy - xz * xz - yz * yz + 2 * xy * xz * yz + av = (xy + xz)/2 + cube = (1 - yz) * (1 - yz) * (1 - yz) + + t2 = d * np.sqrt((n - 1) * (1 + yz)/(((2 * (n - 1)/(n - 3)) * determin + av * av * cube))) + p = 1 - t.cdf(abs(t2), n - 3) + + if twotailed: + p *= 2 + + return t2, p + elif method == 'zou': + L1 = rz_ci(xy, n, conf_level=conf_level)[0] + U1 = rz_ci(xy, n, conf_level=conf_level)[1] + L2 = rz_ci(xz, n, conf_level=conf_level)[0] + U2 = rz_ci(xz, n, conf_level=conf_level)[1] + rho_r12_r13 = rho_rxy_rxz(xy, xz, yz) + lower = xy - xz - pow((pow((xy - L1), 2) + pow((U2 - xz), 2) - 2 * rho_r12_r13 * (xy - L1) * (U2 - xz)), 0.5) + upper = xy - xz + pow((pow((U1 - xy), 2) + pow((xz - L2), 2) - 2 * rho_r12_r13 * (U1 - xy) * (xz - L2)), 0.5) + return lower, upper + else: + raise Exception('Wrong method!') + +def independent_corr(xy, ab, n, n2 = None, twotailed=True, conf_level=0.95, method='fisher'): + """ + Calculates the statistic significance between two independent correlation coefficients + @param xy: correlation coefficient between x and y + @param xz: correlation coefficient between a and b + @param n: number of elements in xy + @param n2: number of elements in ab (if distinct from n) + @param twotailed: whether to calculate a one or two tailed test, only works for 'fisher' method + @param conf_level: confidence level, only works for 'zou' method + @param method: defines the method uses, 'fisher' or 'zou' + @return: z and p-val + """ + + if method == 'fisher': + xy_z = 0.5 * np.log((1 + xy)/(1 - xy)) + ab_z = 0.5 * np.log((1 + ab)/(1 - ab)) + if n2 is None: + n2 = n + + se_diff_r = np.sqrt(1/(n - 3) + 1/(n2 - 3)) + diff = xy_z - ab_z + z = abs(diff / se_diff_r) + p = (1 - norm.cdf(z)) + if twotailed: + p *= 2 + + return z, p + elif method == 'zou': + L1 = rz_ci(xy, n, conf_level=conf_level)[0] + U1 = rz_ci(xy, n, conf_level=conf_level)[1] + L2 = rz_ci(ab, n2, conf_level=conf_level)[0] + U2 = rz_ci(ab, n2, conf_level=conf_level)[1] + lower = xy - ab - pow((pow((xy - L1), 2) + pow((U2 - ab), 2)), 0.5) + upper = xy - ab + pow((pow((U1 - xy), 2) + pow((ab - L2), 2)), 0.5) + return lower, upper + else: + raise Exception('Wrong method!') + +# + +#print dependent_corr(.40, .50, .10, 103, method='steiger') +#print independent_corr(0.5 , 0.6, 103, 103, method='fisher') +# - + +# print dependent_corr(.396, .179, .088, 200, method='zou') +# print independent_corr(.560, .588, 100, 353, method='zou') diff --git a/task_based_analysis/difumo_conn_analysis.py b/task_based_analysis/difumo_conn_analysis.py index 15c3a40..72fb3ab 100644 --- a/task_based_analysis/difumo_conn_analysis.py +++ b/task_based_analysis/difumo_conn_analysis.py @@ -1,10 +1,9 @@ -``` +''' @author: Or Duek @date: Jul 16 2020 This is a sciprt that uses the nee DiFuMo dictionary atlas (https://www.sciencedirect.com/science/article/pii/S1053811920306121#appsec7) - -``` +''' #%% import libraries import pandas as pd from nilearn.input_data import NiftiMapsMasker @@ -13,18 +12,21 @@ import numpy as np import nilearn.plotting from sklearn.model_selection import StratifiedShuffleSplit +import os +import glob #%% Functions # extract RS data and create vector for each subject def removeVars (confoundFile): # this method takes the csv regressors file (from fmriPrep) and chooses a few to confound. You can change those few import pandas as pd confound = pd.read_csv(confoundFile,sep="\t", na_values="n/a") - finalConf = confound[['csf','white_matter', 'framewise_displacement', 'dvars', 'std_dvars', - 'trans_x', 'trans_y', 'trans_z', 'rot_x', 'rot_y', 'rot_z', - ]] # can add 'global_signal' also , + finalConf = confound[['csf', 'white_matter', 'framewise_displacement', + 'a_comp_cor_00', 'a_comp_cor_01', 'a_comp_cor_02', 'a_comp_cor_03', + 'a_comp_cor_04', 'a_comp_cor_05', 'trans_x', 'trans_y', 'trans_z', + 'rot_x', 'rot_y', 'rot_z']] # can add 'global_signal' also ,, + # # change NaN of FD to zero finalConf = np.array(finalConf.fillna(0.0)) - #finalConf[0,2] = 0 # if removing FD than should remove this one also return finalConf @@ -41,18 +43,32 @@ def removeVars (confoundFile): subject_list = np.array(medication_cond.scr_id) condition_label = np.array(medication_cond.med_cond) +group_label = list(map(int, condition_label)) #%% # Fetch grey matter mask from nilearn shipped with # ICBM templates - should consider changing it to mean image # of our dataset -#gm_mask = datasets.fetch_icbm152_brain_gm_mask(threshold=0.2) - +gm_mask = datasets.fetch_icbm152_brain_gm_mask(threshold=0.2) +#%% # condition (medication condition) +# create a mean mask of all subjects +# load mask of brain +ses= '2' +brainmasks = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-*/ses-%s/func/sub-*_ses-%s_task-rest_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz' %(ses,ses)) +print(brainmasks) +%matplotlib inline +#for mask in brainmasks: + # nilearn.plotting.plot_roi(mask) + +mean_mask = nilearn.image.mean_img(brainmasks) +nilearn.plotting.plot_stat_map(mean_mask) +group_mask = nilearn.image.math_img("a>=0.95", a=mean_mask) +nilearn.plotting.plot_roi(group_mask) #%% fetch atlas maps_img = '/media/Data/work/DiFuMo_atlas/256/maps.nii.gz' -labes = pd.read_csv('/media/Data/work/DiFuMo_atlas/256/labels_256_dictionary.csv') +labels = pd.read_csv('/media/Data/work/DiFuMo_atlas/256/labels_256_dictionary.csv') #coords = nilearn.plotting.find_parcellation_cut_coords(labels_img=maps_img) # generate time series @@ -65,8 +81,10 @@ def removeVars (confoundFile): masker = NiftiMapsMasker(maps_img=maps_img, **mask_params) #%% +#subject_list = ['KPE1223'] subject_ts = [] ses = '2' + for sub in subject_list: print(f' Analysing subject {sub}') subject = sub.split('KPE')[1] @@ -87,9 +105,7 @@ def removeVars (confoundFile): - # %% -group_label = list(map(str, condition_label)) -len(group_label) + # %% XGboost from xgboost import XGBClassifier @@ -111,10 +127,80 @@ def removeVars (confoundFile): #%% permutation scores from sklearn.model_selection import permutation_test_score score, permutation_scores, pvalue = permutation_test_score( - model, vec, group_label, scoring="accuracy", cv=cv, n_permutations=500, + model, vec, condition_label, scoring="roc_auc", cv=cv, n_permutations=100, n_jobs=8, verbose=5) print("Classification score %s (pvalue : %s)" % (score, pvalue)) +#%% test the same, but on session 1 +subject_list_1 = list(subject_list) +subject_list_1.remove('KPE1315') +subject_ts_1 = [] +ses = '1' +for sub in subject_list_1: + print(f' Analysing subject {sub}') + subject = sub.split('KPE')[1] + func = func_template.format(sub=subject, session=ses) + confound = confound_template.format(sub=subject, session=ses) + signals = masker.fit_transform(imgs=func, confounds=removeVars(confound)) + subject_ts_1.append(signals) + +#%% +vec_1 = connectome_measure.fit_transform(subject_ts_1) + + +# %% removing sbject 1315 from condition label +subject_list[6] +condition_label_1 = list(condition_label) +del(condition_label_1[6]) +condition_label_1 + +#%% run ML CV +scores_1 = cross_val_score(model, vec_1, condition_label_1, + scoring='roc_auc', cv=cv) + +#%% +scores_1 + +#%% Run NBS to compare the two networks +# first we want to change the vectors to matrices for each session +# session 2: +connectome = connectome.ConnectivityMeasure( + + kind='correlation', vectorize=False) + +# Vectorized connectomes across subject-specific timeseries +mat_2 = connectome.fit_transform(subject_ts) +#mat_1 = connectome.fit_transform(subject_ts_1) #%% -score \ No newline at end of file +mat_2.shape +# using the condition labels to seperate midazolam and ketamine +ketamine_mat = [] +midazolam_mat = [] +for i,x in enumerate(condition_label): + print(i) + print(x) + if x==1: + # ketamine + ketamine_mat.append(mat_2[i]) + else: + midazolam_mat.append(mat_2[i]) + +#%% now reshape and NBS +ketamine = np.moveaxis(np.array(ketamine_mat),0,-1) +midazolam = np.moveaxis(np.array(midazolam_mat),0,-1) +#%% +from bct import nbs +# we compare ket1 and ket3 +pval, adj, _ = nbs.nbs_bct(ketamine, midazolam, thresh=2.5, tail='both',k=500, paired=False, + verbose = True) +# no difference in RS across groups + +# %% +nilearn.plotting.plot_matrix(mat_2[0], labels=np.array(labels.Yeo_networks7) , + colorbar=True) + +#%% +np.array(labels.Difumo_names) + + diff --git a/task_based_analysis/difumo_conn_analysis_original.py b/task_based_analysis/difumo_conn_analysis_original.py new file mode 100644 index 0000000..e0f17d8 --- /dev/null +++ b/task_based_analysis/difumo_conn_analysis_original.py @@ -0,0 +1,175 @@ +``` +@author: Or Duek +@date: Jul 16 2020 + +This is a sciprt that uses the nee DiFuMo dictionary atlas (https://www.sciencedirect.com/science/article/pii/S1053811920306121#appsec7) + +``` +#%% import libraries +import pandas as pd +from nilearn.input_data import NiftiMapsMasker +from nilearn import connectome +from nilearn import datasets +import numpy as np +import nilearn.plotting +from sklearn.model_selection import StratifiedShuffleSplit +#%% Functions +# extract RS data and create vector for each subject +def removeVars (confoundFile): + # this method takes the csv regressors file (from fmriPrep) and chooses a few to confound. You can change those few + import pandas as pd + confound = pd.read_csv(confoundFile,sep="\t", na_values="n/a") + finalConf = confound[['csf', 'white_matter', 'framewise_displacement', + 'a_comp_cor_00', 'a_comp_cor_01', 'a_comp_cor_02', 'a_comp_cor_03', + 'a_comp_cor_04', 'a_comp_cor_05']] # can add 'global_signal' also ,, + # 'trans_x', 'trans_y', 'trans_z', + #'rot_x', 'rot_y', 'rot_z' + # change NaN of FD to zero + finalConf = np.array(finalConf.fillna(0.0)) + return finalConf + + +#%% functional files +# subject_list = ['008','1223','1253','1263','1293','1307','1315','1322','1339','1343','1351','1356','1364','1369' +# ,'1387','1390','1403','1464', '1468', '1480', '1499'] + +func_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{session}/func/sub-{sub}_ses-{session}_task-rest_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz' +confound_template = '/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{session}/func/sub-{sub}_ses-{session}_task-rest_desc-confounds_regressors.tsv' + +## condition labels (ketamine , midazolam) +# read file +medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv') +subject_list = np.array(medication_cond.scr_id) +condition_label = np.array(medication_cond.med_cond) + +#%% +# Fetch grey matter mask from nilearn shipped with +# ICBM templates - should consider changing it to mean image +# of our dataset +gm_mask = datasets.fetch_icbm152_brain_gm_mask(threshold=0.2) + +# condition (medication condition) + + +#%% fetch atlas +maps_img = '/media/Data/work/DiFuMo_atlas/256/maps.nii.gz' +labels = pd.read_csv('/media/Data/work/DiFuMo_atlas/256/labels_256_dictionary.csv') +#coords = nilearn.plotting.find_parcellation_cut_coords(labels_img=maps_img) + +# generate time series +# +mask_params = { 'mask_img': gm_mask, + 'detrend': True, 'standardize': True, + 'high_pass': 0.01, 'low_pass': 0.1, 't_r': 1, + 'smoothing_fwhm': 6., 'verbose': 5} + +masker = NiftiMapsMasker(maps_img=maps_img, **mask_params) + +#%% +subject_list = ['KPE1223'] +subject_ts = [] +ses = '2' +for sub in subject_list: + print(f' Analysing subject {sub}') + subject = sub.split('KPE')[1] + func = func_template.format(sub=subject, session=ses) + confound = confound_template.format(sub=subject, session=ses) + signals = masker.fit_transform(imgs=func, confounds=removeVars(confound)) + subject_ts.append(signals) + +#%% generate connectivity matrix +from sklearn.covariance import LedoitWolf +connectome_measure = connectome.ConnectivityMeasure( + cov_estimator=LedoitWolf(assume_centered=True), + kind='partial correlation', vectorize=True) + +# Vectorized connectomes across subject-specific timeseries +vec = connectome_measure.fit_transform(subject_ts) + + + + + # %% +group_label = list(map(str, condition_label)) +len(group_label) +# %% XGboost + +from xgboost import XGBClassifier +from sklearn.model_selection import train_test_split +from sklearn.metrics import accuracy_score +from sklearn.model_selection import StratifiedKFold +from sklearn.model_selection import cross_val_score + +model = XGBClassifier(n_jobs=8, + verbose = 9, random_state=None) + + +#%% Run cross validation +cv = StratifiedShuffleSplit(n_splits=20, test_size=0.25, + random_state=0) +scores = cross_val_score(model, vec, group_label, + scoring='roc_auc', cv=cv) + +#%% permutation scores +from sklearn.model_selection import permutation_test_score +score, permutation_scores, pvalue = permutation_test_score( + model, vec, group_label, scoring="roc_auc", cv=cv, n_permutations=500, + n_jobs=8, verbose=5) + +print("Classification score %s (pvalue : %s)" % (score, pvalue)) + +#%% test the same, but on session 1 +subject_list_1 = list(subject_list) +subject_list_1.remove('KPE1315') +subject_ts_1 = [] +ses = '1' +for sub in subject_list_1: + print(f' Analysing subject {sub}') + subject = sub.split('KPE')[1] + func = func_template.format(sub=subject, session=ses) + confound = confound_template.format(sub=subject, session=ses) + signals = masker.fit_transform(imgs=func, confounds=removeVars(confound)) + subject_ts_1.append(signals) + +#%% +vec_1 = connectome_measure.fit_transform(subject_ts_1) + + +# %% removing sbject 1315 from condition label +subject_list[6] +condition_label_1 = list(condition_label) +del(condition_label_1[6]) +condition_label_1 + +#%% run ML CV +scores_1 = cross_val_score(model, vec_1, condition_label_1, + scoring='roc_auc', cv=cv) + +#%% +scores_1 + +#%% Run NBS to compare the two networks +# first we want to change the vectors to matrices for each session +# session 2: +connectome = connectome.ConnectivityMeasure( + + kind='correlation', vectorize=False) + +# Vectorized connectomes across subject-specific timeseries +mat_2 = connectome.fit_transform(subject_ts) +mat_1 = connectome.fit_transform(subject_ts_1) +#%% +mat_2.shape + +# %% +nilearn.plotting.plot_matrix(mat_2[0], labels=np.array(labels.Difumo_names) , + colorbar=True, vmin = -.8, vmax = .8) + +#%% +np.array(labels.Difumo_names) + +#%% +import seaborn as sns +sns.heatmap(mat_2[0]) + +# %% diff --git a/task_based_analysis/extractingKPE_taskdata.py b/task_based_analysis/extractingKPE_taskdata.py index 93b9a35..8aa04ed 100755 --- a/task_based_analysis/extractingKPE_taskdata.py +++ b/task_based_analysis/extractingKPE_taskdata.py @@ -1,5 +1,6 @@ #!/usr/bin/env python3 # -*- coding: utf-8 -*- +# %% """ Created on Wed Mar 6 16:02:52 2019 @@ -20,7 +21,7 @@ # choose scripts channel #b = a.channels[7].raw_data -#%% +# %% # create loop that will look for changes between zero and back to zero as on and off set time points. def lookZero(b, offSet): # take Channel data and if we need to adjust timings time_onset = [] @@ -35,8 +36,8 @@ def lookZero(b, offSet): # take Channel data and if we need to adjust timings look_for_zero = True time_onset.append(i/1000 - offSet) return (time_onset, time_offset) - -#%% Function to extract actual data from subjects + +# %% Function to extract actual data from subjects def kpeTaskDat(filename): # takes filename and returns data frame of onsets and duration. Needs to attach condition and subject number import pandas as pd @@ -76,8 +77,8 @@ def orderSize(folder): pairs.sort(key=lambda s: s[0], reverse = True) # Display pairs. return pairs[0][1] # return only file name -#%% This part takes the scan sheet and create a data frame with condition and sessions. -totalScanData = pd.read_excel('/media/Data/PTSD_KPE/kpe_scan_table.xls', sheet_name = 'kpe_scan_table') +# %% This part takes the scan sheet and create a data frame with condition and sessions. +totalScanData = pd.read_excel('/media/Data/Lab_Projects/KPE_PTSD_Project/other/kpe_scan_table.xls', sheet_name = 'kpe_scan_table') # short loop to fill in subject numebrs and sessions totalScanData["subject_id"] = totalScanData["subject_id"].fillna('noSub') # filling all NaNs with noSub. # create a session column @@ -93,7 +94,7 @@ def orderSize(folder): trialOrder = pd.DataFrame({'subject_id': totalScanData["subject_id"], "scriptOrder":totalScanData["Script Order"], "session":totalScanData["scan_num"]}) # read subject id and pick the right line from the data frame -#%% +# %% def getCondition(subNum): # use scanSheet (from top lines), subjectNumber and session to return a list of condition by order of appereance @@ -137,12 +138,12 @@ def getCondition(subNum): #conditionTotal.append(conditionDat) #events= pd.DataFrame({'onset':scriptTime[0], 'duration':duration, 'condition':condition}) # now we should create a data frame - -#%% + +# %% # this function takes subject and session number and returns the specific acq file def getFile(subNum, session): - data_dir = '/media/Data/PTSD_KPE/physio_data/raw/' + data_dir = '/media/Data/Lab_Projects/KPE_PTSD_Project/behavioral/physio_data/raw/' folder = data_dir + "kpe" + str(subNum) + "/" + "Scan_" + str(session) + "/" try: fullFile = orderSize(folder) @@ -152,12 +153,12 @@ def getFile(subNum, session): return 99 -#%% +# %% # now we can iterate through subjects and sessions and create subject data for each # for now - lets create tsv files for each subject per each session -subList = ['008','1223','1253','1263','1293','1307','1315','1322','1339','1343','1351','1356','1364','1369','1387','1390','1403','1464'] -subList = ['1499'] -sessionList = [1,2,3] +#subList = ['008','1223','1253','1263','1293','1307','1315','1322','1339','1343','1351','1356','1364','1369','1387','1390','1403','1464'] +subList = ['008']#['1561','1573','1578','1419'] +sessionList = [1,2,3,4] for sub in subList: subNum = sub @@ -181,15 +182,16 @@ def getFile(subNum, session): onsetsDat['trial_type'] = conditionSession['condition'].tolist() # save as tsv file in specifi location BIDS compatible name (i.e. sub-subNum_ses_session_task_.tsv) # save filename in folder - onsetsDat.to_csv(r'/media/Data/PTSD_KPE/condition_files/'+'sub-' + str(subNum)+ '_' + 'ses-' +str(session)+'.csv', index = False, sep = '\t') + onsetsDat.to_csv(r'/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/'+'sub-' + str(subNum)+ '_' + 'ses-' +str(session)+'.csv', index = False, sep = '\t') -#%% Addind trialType numbe (trauma1/2/3, sad1/2/3 etc.) -events_file = '/media/Data/PTSD_KPE/condition_files/sub-1403_ses-1.csv' +# %% Addind trialType number (trauma1/2/3, sad1/2/3 etc.) + # first read csv file import glob -file_list = glob.glob('/media/Data/PTSD_KPE/condition_files/sub-*_ses-*.csv') +#file_list = glob.glob('/media/Data/PTSD_KPE/condition_files/sub-*_ses-*.csv') +file_list = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/sub-008_ses-*.csv') for file in file_list: events = pd.read_csv(file, sep=r'\t') # for every line add number @@ -214,5 +216,50 @@ def getFile(subNum, session): r_i = r_i +1 events["trial_type_N"] = trial_typeN # save refined csv file - events.to_csv(r'/media/Data/PTSD_KPE/condition_files/withNumbers/'+'sub-' + str(subNum)+ '_' + 'ses-' +str(session)+'.csv', index = False, sep = '\t') - \ No newline at end of file + events.to_csv(r'/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/'+'sub-' + str(subNum)+ '_' + 'ses-' +str(session)+'.csv', index = False, sep = '\t') + +# %% Create 30sec window for each script +#file_list = glob.glob('/media/Data/PTSD_KPE/condition_files/withNumbers/sub-*_ses-*.csv') +file_list = glob.glob('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/sub-*_ses-4.csv') +for file in file_list: + events = pd.read_csv(file, sep=r'\t') + + # for every line add number + subNum = file.split('sub-')[1].split('_')[0] + session = file.split('ses-')[1].split('.')[0] + # set index for each script and index (n) for each window + duration = [] + onset = [] + trial_typeN_60 = [] + for line in events.iterrows(): + #print(line) + newDuration = 60#round(line[1][1] / 4) + startOnset = line[1][0] + # print(startOnset) + for i in range(2): + print(line[1][3]) + trial_typeN_60.append(line[1][3] + '_' + str(i)) + duration.append(newDuration) + onset.append(startOnset) + startOnset = startOnset + newDuration + df = pd.DataFrame({'onset':onset, 'duration': duration, 'trial_type_60': trial_typeN_60}) + + + # save refined csv file + df.to_csv(r'/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/'+'sub-' + str(subNum)+ '_' + 'ses-' +str(session)+ '_60sec_window' + '.csv', index = False, sep = '\t') + +# %% +for line in events.iterrows(): + #print(line) + newDuration = 60#round(line[1][1] / 4) + startOnset = line[1][0] + # print(startOnset) + for i in range(1): + print(line[1])#[3]) + trial_typeN_60.append(line[1][3] + '_' + str(i)) + duration.append(newDuration) + onset.append(startOnset) + startOnset = startOnset + newDuration + +# %% +pd.read_csv('/media/Data/Lab_Projects/KPE_PTSD_Project/neuroimaging/KPE_BIDS/condition_files/withNumbers/sub-008_ses-1_60sec_window.csv', sep='\t') diff --git a/task_based_analysis/fmri_fsl_cluster.py b/task_based_analysis/fmri_fsl_cluster.py index 246d8e7..765fe3c 100644 --- a/task_based_analysis/fmri_fsl_cluster.py +++ b/task_based_analysis/fmri_fsl_cluster.py @@ -1,4 +1,5 @@ #!/usr/bin/env python +# %% # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*- # vi: set ft=python sts=4 ts=4 sw=4 et: """ @@ -114,7 +115,7 @@ def _bids2nipypeinfo(in_file, events_file, regressors_file, removeTR = 4, selectfiles = pe.Node(nio.SelectFiles(templates, ), name="selectfiles") -#%% +# %% # Extract motion parameters from regressors file runinfo = pe.Node(util.Function( @@ -126,7 +127,7 @@ def _bids2nipypeinfo(in_file, events_file, regressors_file, removeTR = 4, # Set the column names to be used from the confounds file runinfo.inputs.regressors_names = ['dvars', 'framewise_displacement'] + \ ['a_comp_cor_%02d' % i for i in range(6)] + ['cosine%02d' % i for i in range(4)] -#%% +# %% @@ -135,14 +136,14 @@ def _bids2nipypeinfo(in_file, events_file, regressors_file, removeTR = 4, skip.inputs.t_min = removeTR skip.inputs.t_size = -1 -#%% +# %% susan = pe.Node(interface=fsl.SUSAN(), name = 'susan') #create_susan_smooth() susan.inputs.fwhm = fwhm susan.inputs.brightness_threshold = 1000.0 -#%% +# %% modelfit = pe.Workflow(name='modelfit', base_dir= output_dir) """ Use :class:`nipype.algorithms.modelgen.SpecifyModel` to generate design information. @@ -197,7 +198,7 @@ def _bids2nipypeinfo(in_file, events_file, regressors_file, removeTR = 4, ) -#%% +# %% modelfit.connect([ (infosource, selectfiles, [('subject_id', 'subject_id')]), (selectfiles, runinfo, [('events','events_file'),('regressors','regressors_file')]), diff --git a/task_based_analysis/fmri_fsl_local.py b/task_based_analysis/fmri_fsl_local.py index d5982c8..2bbfc10 100755 --- a/task_based_analysis/fmri_fsl_local.py +++ b/task_based_analysis/fmri_fsl_local.py @@ -8,7 +8,7 @@ 1st level analysis using FSL output In this one we smooth using SUSAN, which takes longer. """ - +#%% from __future__ import print_function from __future__ import division from builtins import str @@ -47,7 +47,7 @@ fwhm = 6 tr = 1 removeTR = 4#Number of TR's to remove before initiating the analysis -#%% + #%% Methods def _bids2nipypeinfo(in_file, events_file, regressors_file, regressors_names=None, diff --git a/task_based_analysis/fsl_twosample/dsmat.con b/task_based_analysis/fsl_twosample/dsmat.con new file mode 100644 index 0000000..3e770c3 --- /dev/null +++ b/task_based_analysis/fsl_twosample/dsmat.con @@ -0,0 +1,10 @@ +/ContrastName1 ket>mid +/ContrastName2 mid > ket +/NumWaves 2 +/NumContrasts 2 +/PPheights 1.000000e+00 1.000000e+00 +/RequiredEffect 2.636 2.636 + +/Matrix +1.000000e+00 -1.000000e+00 +-1.000000e+00 1.000000e+00 diff --git a/task_based_analysis/fsl_twosample/dsmat.fsf b/task_based_analysis/fsl_twosample/dsmat.fsf new file mode 100644 index 0000000..b973eeb --- /dev/null +++ b/task_based_analysis/fsl_twosample/dsmat.fsf @@ -0,0 +1,591 @@ + +# FEAT version number +set fmri(version) 6.00 + +# Are we in MELODIC? +set fmri(inmelodic) 0 + +# Analysis level +# 1 : First-level analysis +# 2 : Higher-level analysis +set fmri(level) 2 + +# Which stages to run +# 0 : No first-level analysis (registration and/or group stats only) +# 7 : Full first-level analysis +# 1 : Pre-processing +# 2 : Statistics +set fmri(analysis) 2 + +# Use relative filenames +set fmri(relative_yn) 0 + +# Balloon help +set fmri(help_yn) 1 + +# Run Featwatcher +set fmri(featwatcher_yn) 1 + +# Cleanup first-level standard-space images +set fmri(sscleanup_yn) 0 + +# Output directory +set fmri(outputdir) "" + +# TR(s) +set fmri(tr) 3 + +# Total volumes +set fmri(npts) 19 + +# Delete volumes +set fmri(ndelete) 0 + +# Perfusion tag/control order +set fmri(tagfirst) 1 + +# Number of first-level analyses +set fmri(multiple) 19 + +# Higher-level input type +# 1 : Inputs are lower-level FEAT directories +# 2 : Inputs are cope images from FEAT directories +set fmri(inputtype) 1 + +# Carry out pre-stats processing? +set fmri(filtering_yn) 0 + +# Brain/background threshold, % +set fmri(brain_thresh) 10 + +# Critical z for design efficiency calculation +set fmri(critical_z) 5.3 + +# Noise level +set fmri(noise) 0.66 + +# Noise AR(1) +set fmri(noisear) 0.34 + +# Motion correction +# 0 : None +# 1 : MCFLIRT +set fmri(mc) 1 + +# Spin-history (currently obsolete) +set fmri(sh_yn) 0 + +# B0 fieldmap unwarping? +set fmri(regunwarp_yn) 0 + +# GDC Test +set fmri(gdc) "" + +# EPI dwell time (ms) +set fmri(dwell) 0.7 + +# EPI TE (ms) +set fmri(te) 35 + +# % Signal loss threshold +set fmri(signallossthresh) 10 + +# Unwarp direction +set fmri(unwarp_dir) y- + +# Slice timing correction +# 0 : None +# 1 : Regular up (0, 1, 2, 3, ...) +# 2 : Regular down +# 3 : Use slice order file +# 4 : Use slice timings file +# 5 : Interleaved (0, 2, 4 ... 1, 3, 5 ... ) +set fmri(st) 0 + +# Slice timings file +set fmri(st_file) "" + +# BET brain extraction +set fmri(bet_yn) 1 + +# Spatial smoothing FWHM (mm) +set fmri(smooth) 5 + +# Intensity normalization +set fmri(norm_yn) 0 + +# Perfusion subtraction +set fmri(perfsub_yn) 0 + +# Highpass temporal filtering +set fmri(temphp_yn) 1 + +# Lowpass temporal filtering +set fmri(templp_yn) 0 + +# MELODIC ICA data exploration +set fmri(melodic_yn) 0 + +# Carry out main stats? +set fmri(stats_yn) 1 + +# Carry out prewhitening? +set fmri(prewhiten_yn) 1 + +# Add motion parameters to model +# 0 : No +# 1 : Yes +set fmri(motionevs) 0 +set fmri(motionevsbeta) "" +set fmri(scriptevsbeta) "" + +# Robust outlier detection in FLAME? +set fmri(robust_yn) 0 + +# Higher-level modelling +# 3 : Fixed effects +# 0 : Mixed Effects: Simple OLS +# 2 : Mixed Effects: FLAME 1 +# 1 : Mixed Effects: FLAME 1+2 +set fmri(mixed_yn) 2 + +# Higher-level permutations +set fmri(randomisePermutations) 5000 + +# Number of EVs +set fmri(evs_orig) 2 +set fmri(evs_real) 2 +set fmri(evs_vox) 0 + +# Number of contrasts +set fmri(ncon_orig) 1 +set fmri(ncon_real) 2 + +# Number of F-tests +set fmri(nftests_orig) 0 +set fmri(nftests_real) 0 + +# Add constant column to design matrix? (obsolete) +set fmri(constcol) 0 + +# Carry out post-stats steps? +set fmri(poststats_yn) 0 + +# Pre-threshold masking? +set fmri(threshmask) "" + +# Thresholding +# 0 : None +# 1 : Uncorrected +# 2 : Voxel +# 3 : Cluster +set fmri(thresh) 3 + +# P threshold +set fmri(prob_thresh) 0.05 + +# Z threshold +set fmri(z_thresh) 3.1 + +# Z min/max for colour rendering +# 0 : Use actual Z min/max +# 1 : Use preset Z min/max +set fmri(zdisplay) 0 + +# Z min in colour rendering +set fmri(zmin) 2 + +# Z max in colour rendering +set fmri(zmax) 8 + +# Colour rendering type +# 0 : Solid blobs +# 1 : Transparent blobs +set fmri(rendertype) 1 + +# Background image for higher-level stats overlays +# 1 : Mean highres +# 2 : First highres +# 3 : Mean functional +# 4 : First functional +# 5 : Standard space template +set fmri(bgimage) 1 + +# Create time series plots +set fmri(tsplot_yn) 1 + +# Registration to initial structural +set fmri(reginitial_highres_yn) 0 + +# Search space for registration to initial structural +# 0 : No search +# 90 : Normal search +# 180 : Full search +set fmri(reginitial_highres_search) 90 + +# Degrees of Freedom for registration to initial structural +set fmri(reginitial_highres_dof) 3 + +# Registration to main structural +set fmri(reghighres_yn) 0 + +# Search space for registration to main structural +# 0 : No search +# 90 : Normal search +# 180 : Full search +set fmri(reghighres_search) 90 + +# Degrees of Freedom for registration to main structural +set fmri(reghighres_dof) BBR + +# Registration to standard image? +set fmri(regstandard_yn) 1 + +# Use alternate reference images? +set fmri(alternateReference_yn) 0 + +# Standard image +set fmri(regstandard) "/usr/local/fsl/data/standard/MNI152_T1_2mm_brain" + +# Search space for registration to standard space +# 0 : No search +# 90 : Normal search +# 180 : Full search +set fmri(regstandard_search) 90 + +# Degrees of Freedom for registration to standard space +set fmri(regstandard_dof) 12 + +# Do nonlinear registration from structural to standard space? +set fmri(regstandard_nonlinear_yn) 0 + +# Control nonlinear warp field resolution +set fmri(regstandard_nonlinear_warpres) 10 + +# High pass filter cutoff +set fmri(paradigm_hp) 60 + +# Number of lower-level copes feeding into higher-level analysis +set fmri(ncopeinputs) 0 + +# EV 1 title +set fmri(evtitle1) "Ket" + +# Basic waveform shape (EV 1) +# 0 : Square +# 1 : Sinusoid +# 2 : Custom (1 entry per volume) +# 3 : Custom (3 column format) +# 4 : Interaction +# 10 : Empty (all zeros) +set fmri(shape1) 2 + +# Convolution (EV 1) +# 0 : None +# 1 : Gaussian +# 2 : Gamma +# 3 : Double-Gamma HRF +# 4 : Gamma basis functions +# 5 : Sine basis functions +# 6 : FIR basis functions +# 8 : Alternate Double-Gamma +set fmri(convolve1) 0 + +# Convolve phase (EV 1) +set fmri(convolve_phase1) 0 + +# Apply temporal filtering (EV 1) +set fmri(tempfilt_yn1) 0 + +# Add temporal derivative (EV 1) +set fmri(deriv_yn1) 0 + +# Custom EV file (EV 1) +set fmri(custom1) "dummy" + +# Orthogonalise EV 1 wrt EV 0 +set fmri(ortho1.0) 0 + +# Orthogonalise EV 1 wrt EV 1 +set fmri(ortho1.1) 0 + +# Orthogonalise EV 1 wrt EV 2 +set fmri(ortho1.2) 0 + +# Higher-level EV value for EV 1 and input 1 +set fmri(evg1.1) 1 + +# Higher-level EV value for EV 1 and input 2 +set fmri(evg2.1) 0.0 + +# Higher-level EV value for EV 1 and input 3 +set fmri(evg3.1) 0.0 + +# Higher-level EV value for EV 1 and input 4 +set fmri(evg4.1) 1 + +# Higher-level EV value for EV 1 and input 5 +set fmri(evg5.1) 1 + +# Higher-level EV value for EV 1 and input 6 +set fmri(evg6.1) 1 + +# Higher-level EV value for EV 1 and input 7 +set fmri(evg7.1) 1 + +# Higher-level EV value for EV 1 and input 8 +set fmri(evg8.1) 1 + +# Higher-level EV value for EV 1 and input 9 +set fmri(evg9.1) 1 + +# Higher-level EV value for EV 1 and input 10 +set fmri(evg10.1) 0.0 + +# Higher-level EV value for EV 1 and input 11 +set fmri(evg11.1) 0.0 + +# Higher-level EV value for EV 1 and input 12 +set fmri(evg12.1) 0.0 + +# Higher-level EV value for EV 1 and input 13 +set fmri(evg13.1) 0.0 + +# Higher-level EV value for EV 1 and input 14 +set fmri(evg14.1) 1 + +# Higher-level EV value for EV 1 and input 15 +set fmri(evg15.1) 0.0 + +# Higher-level EV value for EV 1 and input 16 +set fmri(evg16.1) 0.0 + +# Higher-level EV value for EV 1 and input 17 +set fmri(evg17.1) 1 + +# Higher-level EV value for EV 1 and input 18 +set fmri(evg18.1) 0.0 + +# Higher-level EV value for EV 1 and input 19 +set fmri(evg19.1) 1 + +# EV 2 title +set fmri(evtitle2) "Mid" + +# Basic waveform shape (EV 2) +# 0 : Square +# 1 : Sinusoid +# 2 : Custom (1 entry per volume) +# 3 : Custom (3 column format) +# 4 : Interaction +# 10 : Empty (all zeros) +set fmri(shape2) 2 + +# Convolution (EV 2) +# 0 : None +# 1 : Gaussian +# 2 : Gamma +# 3 : Double-Gamma HRF +# 4 : Gamma basis functions +# 5 : Sine basis functions +# 6 : FIR basis functions +# 8 : Alternate Double-Gamma +set fmri(convolve2) 0 + +# Convolve phase (EV 2) +set fmri(convolve_phase2) 0 + +# Apply temporal filtering (EV 2) +set fmri(tempfilt_yn2) 0 + +# Add temporal derivative (EV 2) +set fmri(deriv_yn2) 0 + +# Custom EV file (EV 2) +set fmri(custom2) "dummy" + +# Orthogonalise EV 2 wrt EV 0 +set fmri(ortho2.0) 0 + +# Orthogonalise EV 2 wrt EV 1 +set fmri(ortho2.1) 0 + +# Orthogonalise EV 2 wrt EV 2 +set fmri(ortho2.2) 0 + +# Higher-level EV value for EV 2 and input 1 +set fmri(evg1.2) 0 + +# Higher-level EV value for EV 2 and input 2 +set fmri(evg2.2) 1.0 + +# Higher-level EV value for EV 2 and input 3 +set fmri(evg3.2) 1.0 + +# Higher-level EV value for EV 2 and input 4 +set fmri(evg4.2) 0 + +# Higher-level EV value for EV 2 and input 5 +set fmri(evg5.2) 0 + +# Higher-level EV value for EV 2 and input 6 +set fmri(evg6.2) 0 + +# Higher-level EV value for EV 2 and input 7 +set fmri(evg7.2) 0 + +# Higher-level EV value for EV 2 and input 8 +set fmri(evg8.2) 0 + +# Higher-level EV value for EV 2 and input 9 +set fmri(evg9.2) 0 + +# Higher-level EV value for EV 2 and input 10 +set fmri(evg10.2) 1.0 + +# Higher-level EV value for EV 2 and input 11 +set fmri(evg11.2) 1.0 + +# Higher-level EV value for EV 2 and input 12 +set fmri(evg12.2) 1.0 + +# Higher-level EV value for EV 2 and input 13 +set fmri(evg13.2) 1.0 + +# Higher-level EV value for EV 2 and input 14 +set fmri(evg14.2) 0 + +# Higher-level EV value for EV 2 and input 15 +set fmri(evg15.2) 1.0 + +# Higher-level EV value for EV 2 and input 16 +set fmri(evg16.2) 1.0 + +# Higher-level EV value for EV 2 and input 17 +set fmri(evg17.2) 0 + +# Higher-level EV value for EV 2 and input 18 +set fmri(evg18.2) 1.0 + +# Higher-level EV value for EV 2 and input 19 +set fmri(evg19.2) 0 + +# Setup Orthogonalisation at higher level? +set fmri(level2orth) 0 + +# Group membership for input 1 +set fmri(groupmem.1) 1 + +# Group membership for input 2 +set fmri(groupmem.2) 1 + +# Group membership for input 3 +set fmri(groupmem.3) 1 + +# Group membership for input 4 +set fmri(groupmem.4) 1 + +# Group membership for input 5 +set fmri(groupmem.5) 1 + +# Group membership for input 6 +set fmri(groupmem.6) 1 + +# Group membership for input 7 +set fmri(groupmem.7) 1 + +# Group membership for input 8 +set fmri(groupmem.8) 1 + +# Group membership for input 9 +set fmri(groupmem.9) 1 + +# Group membership for input 10 +set fmri(groupmem.10) 1 + +# Group membership for input 11 +set fmri(groupmem.11) 1 + +# Group membership for input 12 +set fmri(groupmem.12) 1 + +# Group membership for input 13 +set fmri(groupmem.13) 1 + +# Group membership for input 14 +set fmri(groupmem.14) 1 + +# Group membership for input 15 +set fmri(groupmem.15) 1 + +# Group membership for input 16 +set fmri(groupmem.16) 1 + +# Group membership for input 17 +set fmri(groupmem.17) 1 + +# Group membership for input 18 +set fmri(groupmem.18) 1 + +# Group membership for input 19 +set fmri(groupmem.19) 1 + +# Contrast & F-tests mode +# real : control real EVs +# orig : control original EVs +set fmri(con_mode_old) real +set fmri(con_mode) real + +# Display images for contrast_real 1 +set fmri(conpic_real.1) 1 + +# Title for contrast_real 1 +set fmri(conname_real.1) "ket>mid" + +# Real contrast_real vector 1 element 1 +set fmri(con_real1.1) 1 + +# Real contrast_real vector 1 element 2 +set fmri(con_real1.2) -1.0 + +# Display images for contrast_real 2 +set fmri(conpic_real.2) 1 + +# Title for contrast_real 2 +set fmri(conname_real.2) "mid > ket" + +# Real contrast_real vector 2 element 1 +set fmri(con_real2.1) -1.0 + +# Real contrast_real vector 2 element 2 +set fmri(con_real2.2) 1.0 + +# Contrast masking - use >0 instead of thresholding? +set fmri(conmask_zerothresh_yn) 0 + +# Mask real contrast/F-test 1 with real contrast/F-test 2? +set fmri(conmask1_2) 0 + +# Mask real contrast/F-test 2 with real contrast/F-test 1? +set fmri(conmask2_1) 0 + +# Do contrast masking at all? +set fmri(conmask1_1) 0 + +########################################################## +# Now options that don't appear in the GUI + +# Alternative (to BETting) mask image +set fmri(alternative_mask) "" + +# Initial structural space registration initialisation transform +set fmri(init_initial_highres) "" + +# Structural space registration initialisation transform +set fmri(init_highres) "" + +# Standard space registration initialisation transform +set fmri(init_standard) "" + +# For full FEAT analysis: overwrite existing .feat output dir? +set fmri(overwrite_yn) 0 diff --git a/task_based_analysis/fsl_twosample/dsmat.grp b/task_based_analysis/fsl_twosample/dsmat.grp new file mode 100644 index 0000000..b94d734 --- /dev/null +++ b/task_based_analysis/fsl_twosample/dsmat.grp @@ -0,0 +1,23 @@ +/NumWaves 1 +/NumPoints 19 + +/Matrix +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 diff --git a/task_based_analysis/fsl_twosample/dsmat.mat b/task_based_analysis/fsl_twosample/dsmat.mat new file mode 100644 index 0000000..53f8b3a --- /dev/null +++ b/task_based_analysis/fsl_twosample/dsmat.mat @@ -0,0 +1,24 @@ +/NumWaves 2 +/NumPoints 19 +/PPheights 1.000000e+00 1.000000e+00 + +/Matrix +1.000000e+00 0.000000e+00 +0.000000e+00 1.000000e+00 +0.000000e+00 1.000000e+00 +1.000000e+00 0.000000e+00 +1.000000e+00 0.000000e+00 +1.000000e+00 0.000000e+00 +1.000000e+00 0.000000e+00 +1.000000e+00 0.000000e+00 +1.000000e+00 0.000000e+00 +0.000000e+00 1.000000e+00 +0.000000e+00 1.000000e+00 +0.000000e+00 1.000000e+00 +0.000000e+00 1.000000e+00 +1.000000e+00 0.000000e+00 +0.000000e+00 1.000000e+00 +0.000000e+00 1.000000e+00 +1.000000e+00 0.000000e+00 +0.000000e+00 1.000000e+00 +1.000000e+00 0.000000e+00 diff --git a/task_based_analysis/fsl_twosample/dsmat.png b/task_based_analysis/fsl_twosample/dsmat.png new file mode 100644 index 0000000..6bf9e2e Binary files /dev/null and b/task_based_analysis/fsl_twosample/dsmat.png differ diff --git a/task_based_analysis/fsl_twosample/dsmat.ppm b/task_based_analysis/fsl_twosample/dsmat.ppm new file mode 100644 index 0000000..6697239 Binary files /dev/null and b/task_based_analysis/fsl_twosample/dsmat.ppm differ diff --git a/task_based_analysis/fsl_twosample/dsmat_cov.png b/task_based_analysis/fsl_twosample/dsmat_cov.png new file mode 100644 index 0000000..53813e4 Binary files /dev/null and b/task_based_analysis/fsl_twosample/dsmat_cov.png differ diff --git a/task_based_analysis/fsl_twosample/dsmat_cov.ppm b/task_based_analysis/fsl_twosample/dsmat_cov.ppm new file mode 100644 index 0000000..8d86350 Binary files /dev/null and b/task_based_analysis/fsl_twosample/dsmat_cov.ppm differ diff --git a/task_based_analysis/kpe_sub_condition.csv b/task_based_analysis/kpe_sub_condition.csv new file mode 100644 index 0000000..0f6c475 --- /dev/null +++ b/task_based_analysis/kpe_sub_condition.csv @@ -0,0 +1,26 @@ +scr_id,med_cond +KPE008,1 +KPE1223,1 +KPE1253,0 +KPE1263,0 +KPE1293,1 +KPE1307,1 +KPE1315,1 +KPE1322,1 +KPE1339,1 +KPE1343,1 +KPE1351,0 +KPE1356,0 +KPE1364,0 +KPE1369,0 +KPE1387,1 +KPE1390,0 +KPE1403,0 +KPE1419,1 +KPE1464,1 +KPE1468,0 +KPE1480,0 +KPE1499,1 +KPE1561,0 +KPE1573,1 +KPE1578,0 diff --git a/task_based_analysis/matFiles.zip b/task_based_analysis/matFiles.zip new file mode 100644 index 0000000..fcc583c Binary files /dev/null and b/task_based_analysis/matFiles.zip differ diff --git a/task_based_analysis/mydask.png b/task_based_analysis/mydask.png new file mode 100644 index 0000000..ccb9fb5 Binary files /dev/null and b/task_based_analysis/mydask.png differ diff --git a/task_based_analysis/rdm/.ipynb_checkpoints/rdm_analysis-checkpoint.py b/task_based_analysis/rdm/.ipynb_checkpoints/rdm_analysis-checkpoint.py new file mode 100755 index 0000000..71cd1cc --- /dev/null +++ b/task_based_analysis/rdm/.ipynb_checkpoints/rdm_analysis-checkpoint.py @@ -0,0 +1,110 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +# %% +""" +Created on Wed Mar 11 12:19:37 2020 + +@author: Ruonan Jia, Or Duek + +Using Ruonan's code to generate dissimilarity matrix +""" + +# %% Compute ROI RDM + +def compute_roi_rdm(in_file, + stims, + all_masks): + + from pathlib import Path + from nilearn.input_data import NiftiMasker + import numpy as np + import nibabel as nib + + rdm_out = Path('roi_rdm.npy').resolve() + stim_num = len(stims) + + # dictionary to store rdms for all rois + rdm_dict = {} + + # loop over all rois + for mask_name in all_masks.keys(): + mask = all_masks[mask_name] + masker = NiftiMasker(mask_img=mask) + + # initiate matrix + spmt_allstims_roi= np.zeros((stim_num, np.sum(mask.get_data()))) + + for (stim_idx, spmt_file) in enumerate(in_file): + spmt = nib.load(spmt_file) + + # get each condition's beta + spmt_roi = masker.fit_transform(spmt) + spmt_allstims_roi[stim_idx, :] = spmt_roi + + # create rdm + rdm_roi = 1 - np.corrcoef(spmt_allstims_roi) + + rdm_dict[mask_name] = rdm_roi + + # save + np.save(rdm_out, rdm_dict) + + return str(rdm_out) + + + +get_roi_rdm = Node(util.Function( + input_names=['in_file', 'stims', 'all_masks'], + function=compute_roi_rdm, + output_names=['rdm_out']), + name='get_roi_rdm', + ) + +get_roi_rdm.inputs.stims = {'01': 'Med_amb_0', '02': 'Med_amb_1', '03': 'Med_amb_2', '04': 'Med_amb_3', + '05': 'Med_risk_0', '06': 'Med_risk_1', '07': 'Med_risk_2', '08': 'Med_risk_3', + '09': 'Mon_amb_0', '10': 'Mon_amb_1', '11': 'Mon_amb_2', '12': 'Mon_amb_3', + '13': 'Mon_risk_0', '14': 'Mon_risk_1', '15': 'Mon_risk_2', '16': 'Mon_risk_3'} + +# Masker files +maskfile_vmpfc = os.path.join(output_dir, 'binConjunc_PvNxDECxRECxMONxPRI_vmpfc.nii.gz') +maskfile_vstr = os.path.join(output_dir, 'binConjunc_PvNxDECxRECxMONxPRI_striatum.nii.gz') +maskfile_roi1 = os.path.join(output_dir, 'none_glm_Med_Mon_TFCE_p005_roi1.nii.gz') +maskfile_roi2 = os.path.join(output_dir, 'none_glm_Med_Mon_TFCE_p005_roi2.nii.gz') +maskfile_roi3 = os.path.join(output_dir, 'none_glm_Med_Mon_TFCE_p005_roi3.nii.gz') + +maskfiles = {'vmpfc': maskfile_vmpfc, + 'vstr': maskfile_vstr, + 'med_mon_1': maskfile_roi1, + 'med_mon_2': maskfile_roi2, + 'med_mon_3': maskfile_roi3} + +# roi inputs are loaded images +get_roi_rdm.inputs.all_masks = {key_name: nib.load(maskfiles[key_name]) for key_name in maskfiles.keys()} + + +wfSPM_rsa.connect([ + (contrastestimate, get_roi_rdm, [('spmT_images', 'in_file')]), + ]) + +# %% data sink rdm +# Datasink +datasink_rdm = Node(nio.DataSink(base_directory=os.path.join(output_dir, 'Sink_resp_rsa_nosmooth')), + name="datasink_rdm") + + +wfSPM_rsa.connect([ + (get_roi_rdm, datasink_rdm, [('rdm_out', 'rdm.@rdm')]), + ]) + +# %% +wfSPM_rsa.write_graph(graph2use = 'flat') + +# # wfSPM.write_graph("workflow_graph.dot", graph2use='colored', format='png', simple_form=True) +# # wfSPM.write_graph(graph2use='orig', dotfilename='./graph_orig.dot') +# %matplotlib inline +# from IPython.display import Image +# %matplotlib qt +# Image(filename = '/home/rj299/project/mdm_analysis/work/l1spm/graph.png') + +# %% run +wfSPM_rsa.run('MultiProc', plugin_args={'n_procs': 4}) diff --git a/task_based_analysis/rdm/rdm_analysis.py b/task_based_analysis/rdm/rdm_analysis.py new file mode 100755 index 0000000..71cd1cc --- /dev/null +++ b/task_based_analysis/rdm/rdm_analysis.py @@ -0,0 +1,110 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +# %% +""" +Created on Wed Mar 11 12:19:37 2020 + +@author: Ruonan Jia, Or Duek + +Using Ruonan's code to generate dissimilarity matrix +""" + +# %% Compute ROI RDM + +def compute_roi_rdm(in_file, + stims, + all_masks): + + from pathlib import Path + from nilearn.input_data import NiftiMasker + import numpy as np + import nibabel as nib + + rdm_out = Path('roi_rdm.npy').resolve() + stim_num = len(stims) + + # dictionary to store rdms for all rois + rdm_dict = {} + + # loop over all rois + for mask_name in all_masks.keys(): + mask = all_masks[mask_name] + masker = NiftiMasker(mask_img=mask) + + # initiate matrix + spmt_allstims_roi= np.zeros((stim_num, np.sum(mask.get_data()))) + + for (stim_idx, spmt_file) in enumerate(in_file): + spmt = nib.load(spmt_file) + + # get each condition's beta + spmt_roi = masker.fit_transform(spmt) + spmt_allstims_roi[stim_idx, :] = spmt_roi + + # create rdm + rdm_roi = 1 - np.corrcoef(spmt_allstims_roi) + + rdm_dict[mask_name] = rdm_roi + + # save + np.save(rdm_out, rdm_dict) + + return str(rdm_out) + + + +get_roi_rdm = Node(util.Function( + input_names=['in_file', 'stims', 'all_masks'], + function=compute_roi_rdm, + output_names=['rdm_out']), + name='get_roi_rdm', + ) + +get_roi_rdm.inputs.stims = {'01': 'Med_amb_0', '02': 'Med_amb_1', '03': 'Med_amb_2', '04': 'Med_amb_3', + '05': 'Med_risk_0', '06': 'Med_risk_1', '07': 'Med_risk_2', '08': 'Med_risk_3', + '09': 'Mon_amb_0', '10': 'Mon_amb_1', '11': 'Mon_amb_2', '12': 'Mon_amb_3', + '13': 'Mon_risk_0', '14': 'Mon_risk_1', '15': 'Mon_risk_2', '16': 'Mon_risk_3'} + +# Masker files +maskfile_vmpfc = os.path.join(output_dir, 'binConjunc_PvNxDECxRECxMONxPRI_vmpfc.nii.gz') +maskfile_vstr = os.path.join(output_dir, 'binConjunc_PvNxDECxRECxMONxPRI_striatum.nii.gz') +maskfile_roi1 = os.path.join(output_dir, 'none_glm_Med_Mon_TFCE_p005_roi1.nii.gz') +maskfile_roi2 = os.path.join(output_dir, 'none_glm_Med_Mon_TFCE_p005_roi2.nii.gz') +maskfile_roi3 = os.path.join(output_dir, 'none_glm_Med_Mon_TFCE_p005_roi3.nii.gz') + +maskfiles = {'vmpfc': maskfile_vmpfc, + 'vstr': maskfile_vstr, + 'med_mon_1': maskfile_roi1, + 'med_mon_2': maskfile_roi2, + 'med_mon_3': maskfile_roi3} + +# roi inputs are loaded images +get_roi_rdm.inputs.all_masks = {key_name: nib.load(maskfiles[key_name]) for key_name in maskfiles.keys()} + + +wfSPM_rsa.connect([ + (contrastestimate, get_roi_rdm, [('spmT_images', 'in_file')]), + ]) + +# %% data sink rdm +# Datasink +datasink_rdm = Node(nio.DataSink(base_directory=os.path.join(output_dir, 'Sink_resp_rsa_nosmooth')), + name="datasink_rdm") + + +wfSPM_rsa.connect([ + (get_roi_rdm, datasink_rdm, [('rdm_out', 'rdm.@rdm')]), + ]) + +# %% +wfSPM_rsa.write_graph(graph2use = 'flat') + +# # wfSPM.write_graph("workflow_graph.dot", graph2use='colored', format='png', simple_form=True) +# # wfSPM.write_graph(graph2use='orig', dotfilename='./graph_orig.dot') +# %matplotlib inline +# from IPython.display import Image +# %matplotlib qt +# Image(filename = '/home/rj299/project/mdm_analysis/work/l1spm/graph.png') + +# %% run +wfSPM_rsa.run('MultiProc', plugin_args={'n_procs': 4}) diff --git a/task_based_analysis/secondLevel_fsl.py b/task_based_analysis/secondLevel_fsl.py index f3df5c8..fe2d565 100644 --- a/task_based_analysis/secondLevel_fsl.py +++ b/task_based_analysis/secondLevel_fsl.py @@ -1,5 +1,6 @@ #!/usr/bin/env python3 # -*- coding: utf-8 -*- +# %% """ Created on Wed Dec 4 14:29:06 2019 @@ -7,15 +8,9 @@ 2nd level analysis using FSL output """ -#%% -#%% Load packages -from nipype.pipeline import engine as pe -from nipype.interfaces import fsl, utility as niu, io as nio - - - -import os -#%% Set variables +# %% +# %% Load packages +# %% Set variables # set number of contrasts (cope) cope_list = ['1','2','3', '4', '5'] # setting working directory (same as first level) @@ -23,7 +18,7 @@ # set input directory (where original files are) mask_dir = '/media/Data/KPE_BIDS/' -#%% Now run second level +# %% Now run second level workflow2nd = pe.Workflow(name="2nd_level", base_dir=work_dir) copeInput = pe.Node(niu.IdentityInterface( @@ -48,7 +43,7 @@ base_directory=work_dir), name="selectCopes") -#%% +# %% copemerge = pe.Node(interface=fsl.Merge(dimension='t'), name="copemerge") @@ -117,7 +112,7 @@ def _len(inlist): (maskemerge, fdr_ztop, [('merged_file','mask_file')]), (flameo_ols, fdr_ztop, [('zstats','in_file')]), ]) -#%% +# %% workflow2nd.run('MultiProc', plugin_args={'n_procs': 3}) diff --git a/task_based_analysis/spm1.log b/task_based_analysis/spm1.log new file mode 100644 index 0000000..3b91db2 --- /dev/null +++ b/task_based_analysis/spm1.log @@ -0,0 +1,3103 @@ +200223-21:16:43,5 nipype.workflow INFO: + Workflow l1spm settings: ['check', 'execution', 'logging', 'monitoring'] +200223-21:16:43,209 nipype.workflow INFO: + Running in parallel. +200223-21:16:43,217 nipype.workflow INFO: + [MultiProc] Running 0 tasks, and 21 jobs ready. Free memory (GB): 56.32/56.32, Free processors: 5/5. +200223-21:16:43,269 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1499/selectfiles". +200223-21:16:43,272 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1480/selectfiles". +200223-21:16:43,275 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1468/selectfiles". +200223-21:16:43,280 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1464/selectfiles". +200223-21:16:43,285 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1403/selectfiles". +200223-21:16:43,370 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200223-21:16:43,372 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200223-21:16:43,375 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200223-21:16:43,376 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200223-21:16:43,377 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200223-21:16:43,443 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200223-21:16:43,444 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200223-21:16:43,446 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200223-21:16:43,447 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200223-21:16:43,447 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200223-21:16:45,220 nipype.workflow INFO: + [Job 0] Completed (l1spm.selectfiles). +200223-21:16:45,223 nipype.workflow INFO: + [Job 9] Completed (l1spm.selectfiles). +200223-21:16:45,224 nipype.workflow INFO: + [Job 18] Completed (l1spm.selectfiles). +200223-21:16:45,226 nipype.workflow INFO: + [Job 27] Completed (l1spm.selectfiles). +200223-21:16:45,228 nipype.workflow INFO: + [Job 36] Completed (l1spm.selectfiles). +200223-21:16:45,231 nipype.workflow INFO: + [MultiProc] Running 0 tasks, and 21 jobs ready. Free memory (GB): 56.32/56.32, Free processors: 5/5. +200223-21:16:45,288 nipype.workflow INFO: + [Job 1] Cached (l1spm.gunzip). +200223-21:16:45,294 nipype.workflow INFO: + [Job 10] Cached (l1spm.gunzip). +200223-21:16:45,302 nipype.workflow INFO: + [Job 19] Cached (l1spm.gunzip). +200223-21:16:45,310 nipype.workflow INFO: + [Job 28] Cached (l1spm.gunzip). +200223-21:16:45,319 nipype.workflow INFO: + [Job 37] Cached (l1spm.gunzip). +200223-21:16:47,269 nipype.workflow INFO: + [Job 2] Cached (l1spm.smooth). +200223-21:16:47,275 nipype.workflow INFO: + [Job 11] Cached (l1spm.smooth). +200223-21:16:47,281 nipype.workflow INFO: + [Job 20] Cached (l1spm.smooth). +200223-21:16:47,288 nipype.workflow INFO: + [Job 29] Cached (l1spm.smooth). +200223-21:16:47,294 nipype.workflow INFO: + [Job 38] Cached (l1spm.smooth). +200223-21:16:49,288 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1499/runinfo". +200223-21:16:49,306 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1480/runinfo". +200223-21:16:49,330 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1468/runinfo". +200223-21:16:49,342 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200223-21:16:49,356 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1464/runinfo". +200223-21:16:49,368 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200223-21:16:49,383 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1403/runinfo". +200223-21:16:49,391 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200223-21:16:49,409 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200223-21:16:49,419 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200223-21:16:50,17 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200223-21:16:50,357 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200223-21:16:50,357 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200223-21:16:50,423 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200223-21:16:50,454 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200223-21:16:51,226 nipype.workflow INFO: + [Job 3] Completed (l1spm.runinfo). +200223-21:16:51,228 nipype.workflow INFO: + [Job 12] Completed (l1spm.runinfo). +200223-21:16:51,230 nipype.workflow INFO: + [Job 21] Completed (l1spm.runinfo). +200223-21:16:51,231 nipype.workflow INFO: + [Job 30] Completed (l1spm.runinfo). +200223-21:16:51,233 nipype.workflow INFO: + [Job 39] Completed (l1spm.runinfo). +200223-21:16:51,236 nipype.workflow INFO: + [MultiProc] Running 0 tasks, and 21 jobs ready. Free memory (GB): 56.32/56.32, Free processors: 5/5. +200223-21:16:51,317 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1499/modelspec". +200223-21:16:51,355 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1480/modelspec". +200223-21:16:51,397 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1468/modelspec". +200223-21:16:51,453 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1464/modelspec". +200223-21:16:51,753 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1403/modelspec". +200223-21:16:53,228 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 16 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.modelspec + * l1spm.modelspec + * l1spm.modelspec +200223-21:41:32,987 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200223-21:41:33,154 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200223-21:41:38,192 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200223-21:41:38,413 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200223-21:41:38,780 nipype.workflow INFO: + [Job 4] Completed (l1spm.modelspec). +200223-21:41:38,782 nipype.workflow INFO: + [Job 40] Completed (l1spm.modelspec). +200223-21:41:38,786 nipype.workflow INFO: + [MultiProc] Running 3 tasks, and 18 jobs ready. Free memory (GB): 55.72/56.32, Free processors: 2/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.modelspec +200223-21:41:38,876 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200223-21:41:39,198 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1499/level1design". +200223-21:41:41,241 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 16 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.modelspec +200223-21:41:41,290 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1403/level1design". +200223-21:41:44,2 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200223-21:41:44,21 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200223-21:41:44,153 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200223-21:41:44,784 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200223-21:41:45,245 nipype.workflow INFO: + [Job 13] Completed (l1spm.modelspec). +200223-21:41:45,249 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 17 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200223-21:41:47,829 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200223-21:41:47,919 nipype.workflow INFO: + [Job 31] Completed (l1spm.modelspec). +200223-21:41:47,943 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 17 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design + * l1spm.modelspec +200223-21:41:47,952 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200223-21:41:48,20 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1480/level1design". +200223-21:41:48,261 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1464/level1design". +200223-21:41:48,933 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200223-21:41:49,6 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200223-21:41:49,326 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200223-21:41:49,922 nipype.workflow INFO: + [Job 22] Completed (l1spm.modelspec). +200223-21:41:49,927 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 17 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200223-21:41:50,212 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1468/level1design". +200223-21:41:50,869 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200223-21:41:51,926 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 16 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200223-21:52:34,67 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200223-21:52:34,513 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200223-21:52:34,579 nipype.workflow INFO: + [Job 5] Completed (l1spm.level1design). +200223-21:52:34,580 nipype.workflow INFO: + [Job 41] Completed (l1spm.level1design). +200223-21:52:34,584 nipype.workflow INFO: + [MultiProc] Running 3 tasks, and 18 jobs ready. Free memory (GB): 55.72/56.32, Free processors: 2/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200223-21:52:34,679 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1499/level1estimate". +200223-21:52:34,767 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1403/level1estimate". +200223-21:52:35,402 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200223-21:52:35,913 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200223-21:52:35,916 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200223-21:52:36,580 nipype.workflow INFO: + [Job 14] Completed (l1spm.level1design). +200223-21:52:36,583 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 17 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1design +200223-21:52:36,690 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1480/level1estimate". +200223-21:52:36,961 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200223-21:52:37,301 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200223-21:52:37,946 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200223-21:52:38,582 nipype.workflow INFO: + [Job 32] Completed (l1spm.level1design). +200223-21:52:38,583 nipype.workflow INFO: + [Job 23] Completed (l1spm.level1design). +200223-21:52:38,584 nipype.workflow INFO: + [MultiProc] Running 3 tasks, and 18 jobs ready. Free memory (GB): 55.72/56.32, Free processors: 2/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200223-21:52:38,639 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1468/level1estimate". +200223-21:52:39,245 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1464/level1estimate". +200223-21:52:39,803 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200223-21:52:40,63 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200223-21:52:40,584 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 16 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-00:36:38,716 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200224-00:36:40,674 nipype.workflow INFO: + [Job 42] Completed (l1spm.level1estimate). +200224-00:36:40,678 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 17 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-00:36:45,945 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 16 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.contrastestimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-00:36:46,861 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1403/contrastestimate". +200224-00:38:25,488 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200224-00:41:24,1 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200224-00:41:24,221 nipype.workflow INFO: + [Job 43] Completed (l1spm.contrastestimate). +200224-00:41:24,225 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 17 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-00:41:25,372 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1403/datasink". +200224-00:41:26,224 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 16 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.datasink + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-00:41:26,701 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200224-00:41:32,529 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200224-00:41:34,230 nipype.workflow INFO: + [Job 44] Completed (l1spm.datasink). +200224-00:41:34,235 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 16 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-00:41:34,680 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1390/selectfiles". +200224-00:41:36,91 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200224-00:41:36,234 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 15 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.selectfiles + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-00:41:37,84 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200224-00:41:38,234 nipype.workflow INFO: + [Job 45] Completed (l1spm.selectfiles). +200224-00:41:38,238 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 16 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-00:41:38,770 nipype.workflow INFO: + [Job 46] Cached (l1spm.gunzip). +200224-00:41:41,21 nipype.workflow INFO: + [Job 47] Cached (l1spm.smooth). +200224-00:41:43,479 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1390/runinfo". +200224-00:41:44,240 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 15 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.runinfo + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-00:41:44,748 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200224-00:41:54,218 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200224-00:41:54,249 nipype.workflow INFO: + [Job 48] Completed (l1spm.runinfo). +200224-00:41:54,253 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 16 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-00:41:54,901 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1390/modelspec". +200224-00:41:56,252 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 15 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-00:53:12,890 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200224-00:53:16,962 nipype.workflow INFO: + [Job 33] Completed (l1spm.level1estimate). +200224-00:53:16,967 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 16 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-00:53:48,809 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 15 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-00:53:52,251 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1464/contrastestimate". +200224-00:56:44,128 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200224-00:56:50,994 nipype.workflow INFO: + [Job 15] Completed (l1spm.level1estimate). +200224-00:56:50,998 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 16 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-00:57:20,160 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 15 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.contrastestimate + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-00:57:23,544 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200224-00:57:24,536 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1480/contrastestimate". +200224-01:01:04,784 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200224-01:04:28,526 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200224-01:04:30,604 nipype.workflow INFO: + [Job 34] Completed (l1spm.contrastestimate). +200224-01:04:30,608 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 16 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:04:56,109 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1464/datasink". +200224-01:04:56,110 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 15 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.datasink + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:05:00,977 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200224-01:05:48,843 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200224-01:05:50,163 nipype.workflow INFO: + [Job 35] Completed (l1spm.datasink). +200224-01:05:50,167 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 15 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:05:52,271 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 14 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.selectfiles + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:05:52,273 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1387/selectfiles". +200224-01:05:59,684 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200224-01:06:05,806 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200224-01:06:06,284 nipype.workflow INFO: + [Job 54] Completed (l1spm.selectfiles). +200224-01:06:06,288 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 15 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:06:08,126 nipype.workflow INFO: + [Job 55] Cached (l1spm.gunzip). +200224-01:06:10,400 nipype.workflow INFO: + [Job 56] Cached (l1spm.smooth). +200224-01:06:12,417 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 14 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.runinfo + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:06:12,419 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1387/runinfo". +200224-01:06:20,222 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200224-01:06:29,336 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200224-01:06:30,434 nipype.workflow INFO: + [Job 57] Completed (l1spm.runinfo). +200224-01:06:30,439 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 15 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:06:35,124 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 14 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.modelspec + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:06:35,127 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1387/modelspec". +200224-01:08:57,635 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200224-01:09:01,273 nipype.workflow INFO: + [Job 16] Completed (l1spm.contrastestimate). +200224-01:09:01,277 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 15 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:09:17,326 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 14 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.datasink + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:09:17,328 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1480/datasink". +200224-01:09:27,749 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200224-01:09:54,978 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200224-01:09:55,363 nipype.workflow INFO: + [Job 17] Completed (l1spm.datasink). +200224-01:09:55,367 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 14 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:09:58,751 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1369/selectfiles". +200224-01:09:58,754 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 13 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.selectfiles + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:10:09,508 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200224-01:10:13,475 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200224-01:10:14,769 nipype.workflow INFO: + [Job 63] Completed (l1spm.selectfiles). +200224-01:10:14,773 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 14 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:10:15,852 nipype.workflow INFO: + [Job 64] Cached (l1spm.gunzip). +200224-01:10:18,414 nipype.workflow INFO: + [Job 65] Cached (l1spm.smooth). +200224-01:10:20,919 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 13 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.runinfo + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:10:20,920 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1369/runinfo". +200224-01:10:25,431 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200224-01:10:33,366 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200224-01:10:34,931 nipype.workflow INFO: + [Job 66] Completed (l1spm.runinfo). +200224-01:10:34,936 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 14 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:10:42,310 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 13 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:10:42,314 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1369/modelspec". +200224-01:19:36,42 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200224-01:19:40,663 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200224-01:19:40,869 nipype.workflow INFO: + [Job 49] Completed (l1spm.modelspec). +200224-01:19:40,872 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 14 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:19:42,44 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1390/level1design". +200224-01:19:42,873 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 13 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-01:19:47,50 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200224-01:22:23,136 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200224-01:22:27,42 nipype.workflow INFO: + [Job 6] Completed (l1spm.level1estimate). +200224-01:22:27,46 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 14 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate +200224-01:23:02,897 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 13 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.contrastestimate + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate +200224-01:23:05,673 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1499/contrastestimate". +200224-01:25:46,975 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200224-01:25:55,79 nipype.workflow INFO: + [Job 24] Completed (l1spm.level1estimate). +200224-01:25:55,83 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 14 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:26:32,407 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 13 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.contrastestimate + * l1spm.contrastestimate + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:26:37,184 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1468/contrastestimate". +200224-01:26:53,760 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200224-01:30:22,293 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200224-01:34:07,514 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200224-01:34:08,883 nipype.workflow INFO: + [Job 7] Completed (l1spm.contrastestimate). +200224-01:34:08,887 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 14 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:34:18,130 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 13 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.datasink + * l1spm.contrastestimate + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:34:18,132 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1499/datasink". +200224-01:34:21,247 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200224-01:34:48,522 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200224-01:34:50,160 nipype.workflow INFO: + [Job 8] Completed (l1spm.datasink). +200224-01:34:50,164 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 13 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:34:50,939 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1364/selectfiles". +200224-01:34:52,163 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 12 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.selectfiles + * l1spm.contrastestimate + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:34:54,281 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200224-01:34:55,547 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200224-01:34:56,165 nipype.workflow INFO: + [Job 72] Completed (l1spm.selectfiles). +200224-01:34:56,169 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 13 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:34:57,485 nipype.workflow INFO: + [Job 73] Cached (l1spm.gunzip). +200224-01:35:00,94 nipype.workflow INFO: + [Job 74] Cached (l1spm.smooth). +200224-01:35:02,363 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 12 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.runinfo + * l1spm.contrastestimate + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:35:02,364 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1364/runinfo". +200224-01:35:05,612 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200224-01:35:09,272 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200224-01:35:10,368 nipype.workflow INFO: + [Job 75] Completed (l1spm.runinfo). +200224-01:35:10,372 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 13 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:35:14,862 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 12 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.modelspec + * l1spm.contrastestimate + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:35:14,864 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1364/modelspec". +200224-01:37:27,66 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200224-01:37:29,3 nipype.workflow INFO: + [Job 25] Completed (l1spm.contrastestimate). +200224-01:37:29,7 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 13 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:37:52,765 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 12 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.datasink + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:37:52,767 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1468/datasink". +200224-01:37:56,887 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200224-01:38:33,136 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200224-01:38:34,808 nipype.workflow INFO: + [Job 26] Completed (l1spm.datasink). +200224-01:38:34,812 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 12 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:38:35,520 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1356/selectfiles". +200224-01:38:36,812 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 11 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.selectfiles + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:38:40,346 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200224-01:38:43,175 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200224-01:38:44,818 nipype.workflow INFO: + [Job 81] Completed (l1spm.selectfiles). +200224-01:38:44,822 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 12 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:38:46,850 nipype.workflow INFO: + [Job 82] Cached (l1spm.gunzip). +200224-01:38:47,932 nipype.workflow INFO: + [Job 83] Cached (l1spm.smooth). +200224-01:38:51,536 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 11 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.runinfo + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:38:51,537 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1356/runinfo". +200224-01:39:07,61 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200224-01:39:14,537 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200224-01:39:15,559 nipype.workflow INFO: + [Job 84] Completed (l1spm.runinfo). +200224-01:39:15,564 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 12 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:39:20,205 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 11 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-01:39:20,207 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1356/modelspec". +200224-01:45:22,338 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200224-01:45:30,80 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200224-01:45:30,593 nipype.workflow INFO: + [Job 58] Completed (l1spm.modelspec). +200224-01:45:30,597 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 12 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec +200224-01:45:32,800 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 11 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec +200224-01:45:32,838 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1387/level1design". +200224-01:45:39,174 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200224-01:49:39,324 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200224-01:49:43,204 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200224-01:49:45,65 nipype.workflow INFO: + [Job 67] Completed (l1spm.modelspec). +200224-01:49:45,70 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 12 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1design +200224-01:49:45,976 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1369/level1design". +200224-01:49:47,70 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 11 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1design +200224-01:49:49,604 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200224-02:09:14,402 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200224-02:09:27,43 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200224-02:09:28,283 nipype.workflow INFO: + [Job 76] Completed (l1spm.modelspec). +200224-02:09:28,289 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 12 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design +200224-02:09:32,802 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 11 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design +200224-02:09:32,837 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1364/level1design". +200224-02:09:41,960 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200224-02:12:51,819 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200224-02:12:52,935 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200224-02:12:53,2 nipype.workflow INFO: + [Job 85] Completed (l1spm.modelspec). +200224-02:12:53,7 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 12 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200224-02:12:53,393 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1356/level1design". +200224-02:12:54,344 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200224-02:12:55,7 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 11 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200224-02:15:58,760 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200224-02:15:59,187 nipype.workflow INFO: + [Job 50] Completed (l1spm.level1design). +200224-02:15:59,191 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 12 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200224-02:15:59,511 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1390/level1estimate". +200224-02:16:01,191 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 11 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200224-02:16:01,888 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200224-02:20:26,734 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200224-02:20:27,454 nipype.workflow INFO: + [Job 59] Completed (l1spm.level1design). +200224-02:20:27,459 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 12 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200224-02:20:27,679 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1387/level1estimate". +200224-02:20:29,458 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 11 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200224-02:20:30,658 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200224-02:20:31,427 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200224-02:20:31,458 nipype.workflow INFO: + [Job 68] Completed (l1spm.level1design). +200224-02:20:31,462 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 12 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1design +200224-02:20:31,795 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1369/level1estimate". +200224-02:20:33,463 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 11 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1design +200224-02:20:34,171 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200224-02:28:03,139 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200224-02:28:03,918 nipype.workflow INFO: + [Job 77] Completed (l1spm.level1design). +200224-02:28:03,922 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 12 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1design +200224-02:28:04,806 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1364/level1estimate". +200224-02:28:05,922 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 11 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1design +200224-02:28:11,573 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200224-02:29:44,774 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200224-02:29:46,20 nipype.workflow INFO: + [Job 86] Completed (l1spm.level1design). +200224-02:29:46,24 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 12 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-02:29:46,623 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1356/level1estimate". +200224-02:29:48,23 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 11 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-02:29:53,404 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200224-06:07:09,666 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200224-06:07:11,352 nipype.workflow INFO: + [Job 60] Completed (l1spm.level1estimate). +200224-06:07:11,356 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 12 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:07:16,85 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 11 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.contrastestimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:07:16,88 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1387/contrastestimate". +200224-06:08:38,543 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200224-06:11:23,506 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200224-06:11:24,338 nipype.workflow INFO: + [Job 61] Completed (l1spm.contrastestimate). +200224-06:11:24,343 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 12 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:11:25,147 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1387/datasink". +200224-06:11:26,110 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200224-06:11:26,342 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 11 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.datasink + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:11:29,116 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200224-06:11:30,344 nipype.workflow INFO: + [Job 62] Completed (l1spm.datasink). +200224-06:11:30,347 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 11 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:11:30,976 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1351/selectfiles". +200224-06:11:31,912 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200224-06:11:32,347 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 10 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.selectfiles + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:11:32,349 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200224-06:11:34,347 nipype.workflow INFO: + [Job 90] Completed (l1spm.selectfiles). +200224-06:11:34,351 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 11 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:11:34,653 nipype.workflow INFO: + [Job 91] Cached (l1spm.gunzip). +200224-06:11:36,844 nipype.workflow INFO: + [Job 92] Cached (l1spm.smooth). +200224-06:11:38,816 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1351/runinfo". +200224-06:11:39,756 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200224-06:11:40,355 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 10 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.runinfo + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:11:48,271 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200224-06:11:48,361 nipype.workflow INFO: + [Job 93] Completed (l1spm.runinfo). +200224-06:11:48,365 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 11 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:11:48,606 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1351/modelspec". +200224-06:11:50,365 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 10 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:12:08,503 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200224-06:12:10,383 nipype.workflow INFO: + [Job 51] Completed (l1spm.level1estimate). +200224-06:12:10,388 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 11 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:12:11,765 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200224-06:12:12,954 nipype.workflow INFO: + [Job 69] Completed (l1spm.level1estimate). +200224-06:12:12,957 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1390/contrastestimate". +200224-06:12:12,959 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 11 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:12:13,952 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1369/contrastestimate". +200224-06:12:14,957 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 10 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.contrastestimate + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:14:18,288 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200224-06:14:21,371 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200224-06:19:02,338 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200224-06:19:03,373 nipype.workflow INFO: + [Job 52] Completed (l1spm.contrastestimate). +200224-06:19:03,377 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 11 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:19:04,54 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200224-06:19:09,164 nipype.workflow INFO: + [Job 70] Completed (l1spm.contrastestimate). +200224-06:19:09,168 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1390/datasink". +200224-06:19:09,170 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 11 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.datasink + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:19:12,362 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200224-06:19:13,106 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 10 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.datasink + * l1spm.datasink + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:19:13,108 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1369/datasink". +200224-06:19:15,19 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200224-06:19:25,247 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200224-06:19:27,119 nipype.workflow INFO: + [Job 53] Completed (l1spm.datasink). +200224-06:19:27,123 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 10 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.datasink + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:19:28,446 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1343/selectfiles". +200224-06:19:29,96 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200224-06:19:29,119 nipype.workflow INFO: + [Job 71] Completed (l1spm.datasink). +200224-06:19:29,123 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 9 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.selectfiles + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:19:29,680 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1339/selectfiles". +200224-06:19:31,123 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 8 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.selectfiles + * l1spm.selectfiles + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:19:35,535 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200224-06:19:37,823 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200224-06:19:38,698 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200224-06:19:39,130 nipype.workflow INFO: + [Job 99] Completed (l1spm.selectfiles). +200224-06:19:39,134 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 9 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.selectfiles + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:19:40,421 nipype.workflow INFO: + [Job 100] Cached (l1spm.gunzip). +200224-06:19:40,510 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200224-06:19:41,131 nipype.workflow INFO: + [Job 108] Completed (l1spm.selectfiles). +200224-06:19:41,135 nipype.workflow INFO: + [MultiProc] Running 3 tasks, and 10 jobs ready. Free memory (GB): 55.72/56.32, Free processors: 2/5. + Currently running: + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:19:42,314 nipype.workflow INFO: + [Job 101] Cached (l1spm.smooth). +200224-06:19:43,135 nipype.workflow INFO: + [Job 109] Cached (l1spm.gunzip). +200224-06:19:44,835 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1343/runinfo". +200224-06:19:45,647 nipype.workflow INFO: + [Job 110] Cached (l1spm.smooth). +200224-06:19:45,654 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 9 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.runinfo + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:19:46,652 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1339/runinfo". +200224-06:19:47,258 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200224-06:19:47,655 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 8 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.runinfo + * l1spm.runinfo + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:19:49,804 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200224-06:19:51,339 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200224-06:19:51,657 nipype.workflow INFO: + [Job 102] Completed (l1spm.runinfo). +200224-06:19:51,662 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 9 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.runinfo + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:19:52,239 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200224-06:19:52,719 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1343/modelspec". +200224-06:19:53,659 nipype.workflow INFO: + [Job 111] Completed (l1spm.runinfo). +200224-06:19:53,663 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 9 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:19:54,918 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1339/modelspec". +200224-06:19:55,661 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 8 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-06:29:09,349 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200224-06:29:22,252 nipype.workflow INFO: + [Job 78] Completed (l1spm.level1estimate). +200224-06:29:22,256 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 9 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate +200224-06:29:47,641 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 8 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate +200224-06:29:59,728 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1364/contrastestimate". +200224-06:33:35,412 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200224-06:34:25,500 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200224-06:34:27,936 nipype.workflow INFO: + [Job 87] Completed (l1spm.level1estimate). +200224-06:34:27,940 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 9 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.modelspec + * l1spm.modelspec +200224-06:34:52,556 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 8 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.contrastestimate + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.modelspec + * l1spm.modelspec +200224-06:34:54,368 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1356/contrastestimate". +200224-06:37:08,928 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200224-06:37:11,409 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200224-06:37:12,701 nipype.workflow INFO: + [Job 94] Completed (l1spm.modelspec). +200224-06:37:12,705 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 9 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.modelspec +200224-06:37:14,167 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1351/level1design". +200224-06:37:14,706 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 8 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1design + * l1spm.contrastestimate + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.modelspec +200224-06:37:16,515 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200224-06:37:32,710 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200224-06:39:06,191 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200224-06:39:06,815 nipype.workflow INFO: + [Job 79] Completed (l1spm.contrastestimate). +200224-06:39:06,819 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 9 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.modelspec +200224-06:39:10,420 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 8 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.datasink + * l1spm.level1design + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.modelspec +200224-06:39:10,423 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1364/datasink". +200224-06:39:11,809 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200224-06:39:27,822 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200224-06:39:28,437 nipype.workflow INFO: + [Job 80] Completed (l1spm.datasink). +200224-06:39:28,441 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 8 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.modelspec +200224-06:39:29,19 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1322/selectfiles". +200224-06:39:30,440 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 7 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.selectfiles + * l1spm.level1design + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.modelspec +200224-06:39:31,161 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200224-06:39:31,852 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200224-06:39:32,440 nipype.workflow INFO: + [Job 117] Completed (l1spm.selectfiles). +200224-06:39:32,444 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 8 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.modelspec +200224-06:39:33,40 nipype.workflow INFO: + [Job 118] Cached (l1spm.gunzip). +200224-06:39:36,403 nipype.workflow INFO: + [Job 119] Cached (l1spm.smooth). +200224-06:39:36,919 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1322/runinfo". +200224-06:39:38,446 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 7 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.runinfo + * l1spm.level1design + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.modelspec +200224-06:39:39,282 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200224-06:39:41,911 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200224-06:39:42,448 nipype.workflow INFO: + [Job 120] Completed (l1spm.runinfo). +200224-06:39:42,452 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 8 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.modelspec +200224-06:39:45,892 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 7 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.modelspec + * l1spm.level1design + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.modelspec +200224-06:39:45,895 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1322/modelspec". +200224-06:43:20,575 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200224-06:43:22,119 nipype.workflow INFO: + [Job 88] Completed (l1spm.contrastestimate). +200224-06:43:22,123 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 8 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-06:43:31,153 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 7 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.datasink + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-06:43:31,155 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1356/datasink". +200224-06:43:34,796 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200224-06:43:58,660 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200224-06:43:59,181 nipype.workflow INFO: + [Job 89] Completed (l1spm.datasink). +200224-06:43:59,185 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 7 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-06:44:00,78 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1315/selectfiles". +200224-06:44:01,184 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 6 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.selectfiles + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-06:44:02,540 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200224-06:44:04,179 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200224-06:44:05,187 nipype.workflow INFO: + [Job 126] Completed (l1spm.selectfiles). +200224-06:44:05,190 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 7 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-06:44:06,656 nipype.workflow INFO: + [Job 127] Cached (l1spm.gunzip). +200224-06:44:08,272 nipype.workflow INFO: + [Job 128] Cached (l1spm.smooth). +200224-06:44:11,276 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 6 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.runinfo + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-06:44:11,278 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1315/runinfo". +200224-06:44:19,959 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200224-06:44:30,955 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200224-06:44:31,294 nipype.workflow INFO: + [Job 129] Completed (l1spm.runinfo). +200224-06:44:31,298 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 7 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-06:44:33,302 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 6 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec +200224-06:44:33,306 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1315/modelspec". +200224-06:47:12,351 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200224-06:47:18,962 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200224-06:47:19,479 nipype.workflow INFO: + [Job 112] Completed (l1spm.modelspec). +200224-06:47:19,483 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 7 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec +200224-06:47:21,490 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 6 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec +200224-06:47:21,538 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1339/level1design". +200224-06:47:26,514 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200224-06:47:37,669 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200224-06:47:42,290 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200224-06:47:43,507 nipype.workflow INFO: + [Job 103] Completed (l1spm.modelspec). +200224-06:47:43,511 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 7 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1design +200224-06:47:44,799 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1343/level1design". +200224-06:47:45,511 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 6 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1design +200224-06:47:48,119 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200224-06:59:56,726 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200224-07:00:00,105 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200224-07:00:00,266 nipype.workflow INFO: + [Job 121] Completed (l1spm.modelspec). +200224-07:00:00,270 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 7 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design +200224-07:00:01,330 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1322/level1design". +200224-07:00:02,269 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 6 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design +200224-07:00:04,848 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200224-07:02:31,544 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200224-07:02:33,843 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200224-07:02:34,422 nipype.workflow INFO: + [Job 130] Completed (l1spm.modelspec). +200224-07:02:34,426 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 7 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200224-07:02:35,82 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1315/level1design". +200224-07:02:36,429 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 6 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200224-07:02:36,452 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200224-07:07:51,10 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200224-07:07:52,734 nipype.workflow INFO: + [Job 95] Completed (l1spm.level1design). +200224-07:07:52,739 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 7 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200224-07:07:53,240 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1351/level1estimate". +200224-07:07:54,738 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 6 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200224-07:07:56,157 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200224-07:08:40,563 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200224-07:08:40,783 nipype.workflow INFO: + [Job 113] Completed (l1spm.level1design). +200224-07:08:40,788 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 7 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200224-07:08:40,984 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1339/level1estimate". +200224-07:08:42,788 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 6 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200224-07:08:45,61 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200224-07:08:50,811 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200224-07:08:52,796 nipype.workflow INFO: + [Job 104] Completed (l1spm.level1design). +200224-07:08:52,800 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 7 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1design +200224-07:08:53,102 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1343/level1estimate". +200224-07:08:54,800 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 6 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1design +200224-07:08:56,885 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200224-07:15:53,999 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200224-07:15:55,238 nipype.workflow INFO: + [Job 122] Completed (l1spm.level1design). +200224-07:15:55,242 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 7 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1design +200224-07:15:55,656 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1322/level1estimate". +200224-07:15:57,242 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 6 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1design +200224-07:16:02,397 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200224-07:17:56,629 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200224-07:17:57,359 nipype.workflow INFO: + [Job 131] Completed (l1spm.level1design). +200224-07:17:57,363 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 7 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-07:17:57,965 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1315/level1estimate". +200224-07:17:59,363 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 6 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-07:18:04,14 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200224-10:30:32,38 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200224-10:30:35,207 nipype.workflow INFO: + [Job 114] Completed (l1spm.level1estimate). +200224-10:30:35,211 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 7 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-10:30:37,549 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 6 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.contrastestimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-10:30:37,616 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1339/contrastestimate". +200224-10:32:53,720 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200224-10:36:44,385 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200224-10:36:45,929 nipype.workflow INFO: + [Job 115] Completed (l1spm.contrastestimate). +200224-10:36:45,933 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 7 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-10:36:50,865 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 6 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.datasink + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-10:36:50,868 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1339/datasink". +200224-10:36:52,521 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200224-10:37:06,22 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200224-10:37:06,880 nipype.workflow INFO: + [Job 116] Completed (l1spm.datasink). +200224-10:37:06,884 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 6 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-10:37:07,363 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1307/selectfiles". +200224-10:37:08,884 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 5 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.selectfiles + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-10:37:10,432 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200224-10:37:12,264 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200224-10:37:12,884 nipype.workflow INFO: + [Job 135] Completed (l1spm.selectfiles). +200224-10:37:12,888 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 6 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-10:37:14,483 nipype.workflow INFO: + [Job 136] Cached (l1spm.gunzip). +200224-10:37:15,768 nipype.workflow INFO: + [Job 137] Cached (l1spm.smooth). +200224-10:37:18,89 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1307/runinfo". +200224-10:37:18,889 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 5 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.runinfo + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-10:37:21,626 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200224-10:37:31,213 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200224-10:37:32,902 nipype.workflow INFO: + [Job 138] Completed (l1spm.runinfo). +200224-10:37:32,906 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 6 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-10:37:34,801 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1307/modelspec". +200224-10:37:34,904 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 5 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-10:45:16,179 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200224-10:45:25,385 nipype.workflow INFO: + [Job 123] Completed (l1spm.level1estimate). +200224-10:45:25,389 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 6 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-10:46:44,191 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 5 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-10:46:54,720 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1322/contrastestimate". +200224-10:51:59,818 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200224-11:00:26,516 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200224-11:00:29,35 nipype.workflow INFO: + [Job 124] Completed (l1spm.contrastestimate). +200224-11:00:29,39 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 6 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:00:44,685 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 5 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.datasink + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:00:44,687 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1322/datasink". +200224-11:00:50,260 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200224-11:01:23,304 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200224-11:01:24,724 nipype.workflow INFO: + [Job 125] Completed (l1spm.datasink). +200224-11:01:24,728 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 5 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:01:25,229 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1293/selectfiles". +200224-11:01:26,728 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 4 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.selectfiles + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:01:30,410 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200224-11:01:32,657 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200224-11:01:35,718 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200224-11:01:38,739 nipype.workflow INFO: + [Job 105] Completed (l1spm.level1estimate). +200224-11:01:38,741 nipype.workflow INFO: + [Job 144] Completed (l1spm.selectfiles). +200224-11:01:38,745 nipype.workflow INFO: + [MultiProc] Running 3 tasks, and 6 jobs ready. Free memory (GB): 55.72/56.32, Free processors: 2/5. + Currently running: + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:02:00,273 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1343/contrastestimate". +200224-11:02:01,165 nipype.workflow INFO: + [Job 145] Cached (l1spm.gunzip). +200224-11:02:01,172 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 5 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:02:02,814 nipype.workflow INFO: + [Job 146] Cached (l1spm.smooth). +200224-11:02:06,41 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 4 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.runinfo + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:02:06,43 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1293/runinfo". +200224-11:02:09,175 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200224-11:02:13,639 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200224-11:02:14,46 nipype.workflow INFO: + [Job 147] Completed (l1spm.runinfo). +200224-11:02:14,51 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 5 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:02:15,794 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1293/modelspec". +200224-11:02:16,49 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 4 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.modelspec + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:04:58,818 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200224-11:10:57,917 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200224-11:11:00,590 nipype.workflow INFO: + [Job 106] Completed (l1spm.contrastestimate). +200224-11:11:00,592 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 5 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:11:17,371 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 4 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.datasink + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:11:17,373 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1343/datasink". +200224-11:11:21,684 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200224-11:11:48,324 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200224-11:11:49,402 nipype.workflow INFO: + [Job 107] Completed (l1spm.datasink). +200224-11:11:49,406 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 4 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:11:51,184 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1263/selectfiles". +200224-11:11:51,405 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 3 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.selectfiles + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:11:56,653 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200224-11:12:01,194 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200224-11:12:01,412 nipype.workflow INFO: + [Job 153] Completed (l1spm.selectfiles). +200224-11:12:01,416 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 4 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:12:02,428 nipype.workflow INFO: + [Job 154] Cached (l1spm.gunzip). +200224-11:12:06,417 nipype.workflow INFO: + [Job 155] Cached (l1spm.smooth). +200224-11:12:08,908 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 3 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.runinfo + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:12:08,910 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1263/runinfo". +200224-11:12:14,12 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200224-11:12:20,425 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200224-11:12:20,918 nipype.workflow INFO: + [Job 156] Completed (l1spm.runinfo). +200224-11:12:20,922 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 4 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:12:23,418 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 3 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:12:23,422 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1263/modelspec". +200224-11:16:37,826 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200224-11:16:41,820 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200224-11:16:43,684 nipype.workflow INFO: + [Job 139] Completed (l1spm.modelspec). +200224-11:16:43,688 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 4 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:16:45,892 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 3 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200224-11:16:45,938 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1307/level1design". +200224-11:16:48,506 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200224-11:16:50,353 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200224-11:16:51,896 nipype.workflow INFO: + [Job 132] Completed (l1spm.level1estimate). +200224-11:16:51,900 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 4 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate +200224-11:17:43,298 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 3 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.contrastestimate + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate +200224-11:17:46,147 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1315/contrastestimate". +200224-11:20:43,366 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200224-11:25:51,878 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200224-11:25:53,780 nipype.workflow INFO: + [Job 133] Completed (l1spm.contrastestimate). +200224-11:25:53,784 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 4 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate +200224-11:26:01,479 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1315/datasink". +200224-11:26:01,482 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 3 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.datasink + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate +200224-11:26:04,460 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200224-11:26:27,463 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200224-11:26:27,506 nipype.workflow INFO: + [Job 134] Completed (l1spm.datasink). +200224-11:26:27,510 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 3 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate +200224-11:26:27,970 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1253/selectfiles". +200224-11:26:29,510 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 2 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.selectfiles + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate +200224-11:26:31,776 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200224-11:26:34,877 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200224-11:26:35,514 nipype.workflow INFO: + [Job 162] Completed (l1spm.selectfiles). +200224-11:26:35,518 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 3 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate +200224-11:26:36,255 nipype.workflow INFO: + [Job 163] Cached (l1spm.gunzip). +200224-11:26:40,214 nipype.workflow INFO: + [Job 164] Cached (l1spm.smooth). +200224-11:26:44,289 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1253/runinfo". +200224-11:26:44,290 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 2 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.runinfo + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate +200224-11:26:48,97 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200224-11:26:53,6 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200224-11:26:54,297 nipype.workflow INFO: + [Job 165] Completed (l1spm.runinfo). +200224-11:26:54,301 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 3 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate +200224-11:26:55,823 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1253/modelspec". +200224-11:26:56,299 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 2 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.modelspec + * l1spm.level1estimate +200224-11:31:39,981 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200224-11:31:44,372 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200224-11:31:44,592 nipype.workflow INFO: + [Job 148] Completed (l1spm.modelspec). +200224-11:31:44,596 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 3 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1estimate +200224-11:31:46,188 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1293/level1design". +200224-11:31:46,596 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 2 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1estimate +200224-11:31:50,125 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200224-11:36:06,9 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200224-11:36:10,859 nipype.workflow INFO: + [Job 96] Completed (l1spm.level1estimate). +200224-11:36:10,863 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 3 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec +200224-11:36:48,619 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 2 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.contrastestimate + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design + * l1spm.modelspec +200224-11:36:51,76 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1351/contrastestimate". +200224-11:40:53,463 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200224-11:44:51,894 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200224-11:45:03,817 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200224-11:45:05,121 nipype.workflow INFO: + [Job 157] Completed (l1spm.modelspec). +200224-11:45:05,125 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 3 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design +200224-11:45:07,142 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 2 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1design + * l1spm.contrastestimate + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design +200224-11:45:07,174 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1263/level1design". +200224-11:45:15,911 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200224-11:48:10,285 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200224-11:48:11,316 nipype.workflow INFO: + [Job 97] Completed (l1spm.contrastestimate). +200224-11:48:11,320 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 3 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design +200224-11:48:24,697 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 2 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.datasink + * l1spm.level1design + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design +200224-11:48:24,700 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1351/datasink". +200224-11:48:28,183 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200224-11:48:52,945 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200224-11:48:54,723 nipype.workflow INFO: + [Job 98] Completed (l1spm.datasink). +200224-11:48:54,729 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 2 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design +200224-11:48:56,963 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.selectfiles + * l1spm.level1design + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design +200224-11:48:56,964 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1223/selectfiles". +200224-11:49:04,789 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200224-11:49:07,747 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200224-11:49:08,971 nipype.workflow INFO: + [Job 171] Completed (l1spm.selectfiles). +200224-11:49:08,975 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 2 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design +200224-11:49:10,656 nipype.workflow INFO: + [Job 172] Cached (l1spm.gunzip). +200224-11:49:12,919 nipype.workflow INFO: + [Job 173] Cached (l1spm.smooth). +200224-11:49:15,706 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.runinfo + * l1spm.level1design + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design +200224-11:49:15,708 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1223/runinfo". +200224-11:49:20,175 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200224-11:49:26,19 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200224-11:49:27,714 nipype.workflow INFO: + [Job 174] Completed (l1spm.runinfo). +200224-11:49:27,719 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 2 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design +200224-11:49:30,347 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.modelspec + * l1spm.level1design + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design +200224-11:49:30,351 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1223/modelspec". +200224-12:03:08,42 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200224-12:03:17,376 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200224-12:03:19,199 nipype.workflow INFO: + [Job 166] Completed (l1spm.modelspec). +200224-12:03:19,203 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 2 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200224-12:03:22,973 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200224-12:03:23,6 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1253/level1design". +200224-12:03:33,504 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200224-12:27:32,272 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200224-12:27:32,415 nipype.workflow INFO: + [Job 140] Completed (l1spm.level1design). +200224-12:27:32,419 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 2 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design + * l1spm.level1design +200224-12:27:34,395 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1307/level1estimate". +200224-12:27:34,417 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1design + * l1spm.modelspec + * l1spm.level1design + * l1spm.level1design +200224-12:27:58,225 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200224-12:37:29,697 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200224-12:37:36,556 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200224-12:37:37,7 nipype.workflow INFO: + [Job 175] Completed (l1spm.modelspec). +200224-12:37:37,9 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 2 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200224-12:37:48,288 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1design + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1design + * l1spm.level1design +200224-12:37:48,321 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1223/level1design". +200224-12:37:53,447 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200224-12:49:41,305 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200224-12:49:42,971 nipype.workflow INFO: + [Job 149] Completed (l1spm.level1design). +200224-12:49:42,975 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 2 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1design + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1design +200224-12:49:46,377 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1293/level1estimate". +200224-12:49:46,378 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1design +200224-12:50:10,896 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200224-13:06:10,426 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200224-13:06:13,361 nipype.workflow INFO: + [Job 158] Completed (l1spm.level1design). +200224-13:06:13,365 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 2 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1estimate + * l1spm.level1design +200224-13:06:15,172 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1263/level1estimate". +200224-13:06:15,363 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1estimate + * l1spm.level1design +200224-13:06:27,142 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200224-13:42:14,427 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200224-13:42:15,590 nipype.workflow INFO: + [Job 167] Completed (l1spm.level1design). +200224-13:42:15,594 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 2 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1estimate +200224-13:42:16,231 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1253/level1estimate". +200224-13:42:17,594 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1design + * l1spm.level1estimate +200224-13:42:24,824 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200224-13:52:15,520 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200224-13:52:16,186 nipype.workflow INFO: + [Job 176] Completed (l1spm.level1design). +200224-13:52:16,190 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 2 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-13:52:16,796 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1223/level1estimate". +200224-13:52:18,189 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200224-13:52:25,325 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200225-02:41:03,203 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200225-02:41:05,56 nipype.workflow INFO: + [Job 150] Completed (l1spm.level1estimate). +200225-02:41:05,60 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 2 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200225-02:42:10,915 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.contrastestimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200225-02:42:10,917 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1293/contrastestimate". +200225-02:48:06,678 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200225-03:00:47,390 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200225-03:00:50,65 nipype.workflow INFO: + [Job 151] Completed (l1spm.contrastestimate). +200225-03:00:50,71 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 2 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200225-03:00:52,270 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.datasink + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200225-03:00:52,272 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1293/datasink". +200225-03:01:02,707 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200225-03:02:40,812 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200225-03:02:42,384 nipype.workflow INFO: + [Job 152] Completed (l1spm.datasink). +200225-03:02:42,388 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 1 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200225-03:02:53,891 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 0 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.selectfiles + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200225-03:02:53,892 nipype.workflow INFO: + [Node] Setting-up "l1spm.selectfiles" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_008/selectfiles". +200225-03:03:00,918 nipype.workflow INFO: + [Node] Running "selectfiles" ("nipype.interfaces.io.SelectFiles") +200225-03:03:08,223 nipype.workflow INFO: + [Node] Finished "l1spm.selectfiles". +200225-03:03:09,904 nipype.workflow INFO: + [Job 180] Completed (l1spm.selectfiles). +200225-03:03:09,908 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 1 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200225-03:03:10,353 nipype.workflow INFO: + [Job 181] Cached (l1spm.gunzip). +200225-03:03:12,876 nipype.workflow INFO: + [Job 182] Cached (l1spm.smooth). +200225-03:03:16,367 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 0 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.runinfo + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200225-03:03:16,368 nipype.workflow INFO: + [Node] Setting-up "l1spm.runinfo" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_008/runinfo". +200225-03:03:21,375 nipype.workflow INFO: + [Node] Running "runinfo" ("nipype.interfaces.utility.wrappers.Function") +200225-03:03:25,389 nipype.workflow INFO: + [Node] Finished "l1spm.runinfo". +200225-03:03:26,375 nipype.workflow INFO: + [Job 183] Completed (l1spm.runinfo). +200225-03:03:26,379 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 1 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200225-03:03:29,80 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 0 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200225-03:03:29,83 nipype.workflow INFO: + [Node] Setting-up "l1spm.modelspec" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_008/modelspec". +200225-03:04:03,777 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200225-03:04:05,116 nipype.workflow INFO: + [Job 141] Completed (l1spm.level1estimate). +200225-03:04:05,120 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 1 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200225-03:04:24,529 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 0 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200225-03:04:24,532 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1307/contrastestimate". +200225-03:15:38,594 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200225-03:28:18,402 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200225-03:28:20,14 nipype.workflow INFO: + [Job 142] Completed (l1spm.contrastestimate). +200225-03:28:20,18 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 1 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200225-03:29:44,430 nipype.workflow INFO: + [MultiProc] Running 5 tasks, and 0 jobs ready. Free memory (GB): 55.32/56.32, Free processors: 0/5. + Currently running: + * l1spm.datasink + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200225-03:29:44,433 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1307/datasink". +200225-03:29:55,201 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200225-03:30:18,618 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200225-03:30:20,467 nipype.workflow INFO: + [Job 143] Completed (l1spm.datasink). +200225-03:30:20,471 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 0 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate + * l1spm.level1estimate +200225-03:30:23,895 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200225-03:30:32,480 nipype.workflow INFO: + [Job 177] Completed (l1spm.level1estimate). +200225-03:30:32,485 nipype.workflow INFO: + [MultiProc] Running 3 tasks, and 1 jobs ready. Free memory (GB): 55.72/56.32, Free processors: 2/5. + Currently running: + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200225-03:30:58,510 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 0 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate + * l1spm.level1estimate +200225-03:31:04,397 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1223/contrastestimate". +200225-03:40:34,35 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200225-03:40:37,828 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200225-03:40:39,98 nipype.workflow INFO: + [Job 159] Completed (l1spm.level1estimate). +200225-03:40:39,100 nipype.workflow INFO: + [MultiProc] Running 3 tasks, and 1 jobs ready. Free memory (GB): 55.72/56.32, Free processors: 2/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate +200225-03:40:40,365 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1263/contrastestimate". +200225-03:40:41,101 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 0 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.contrastestimate + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate +200225-03:51:57,483 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200225-03:57:58,190 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200225-03:58:00,139 nipype.workflow INFO: + [Job 178] Completed (l1spm.contrastestimate). +200225-03:58:00,143 nipype.workflow INFO: + [MultiProc] Running 3 tasks, and 1 jobs ready. Free memory (GB): 55.72/56.32, Free processors: 2/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate +200225-03:58:13,309 nipype.workflow INFO: + [MultiProc] Running 4 tasks, and 0 jobs ready. Free memory (GB): 55.52/56.32, Free processors: 1/5. + Currently running: + * l1spm.datasink + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate +200225-03:58:13,376 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1223/datasink". +200225-03:58:23,115 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200225-03:59:15,720 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200225-03:59:17,372 nipype.workflow INFO: + [Job 179] Completed (l1spm.datasink). +200225-03:59:17,376 nipype.workflow INFO: + [MultiProc] Running 3 tasks, and 0 jobs ready. Free memory (GB): 55.72/56.32, Free processors: 2/5. + Currently running: + * l1spm.contrastestimate + * l1spm.modelspec + * l1spm.level1estimate +200225-04:07:22,525 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200225-04:07:23,867 nipype.workflow INFO: + [Job 160] Completed (l1spm.contrastestimate). +200225-04:07:23,871 nipype.workflow INFO: + [MultiProc] Running 2 tasks, and 1 jobs ready. Free memory (GB): 55.92/56.32, Free processors: 3/5. + Currently running: + * l1spm.modelspec + * l1spm.level1estimate +200225-04:07:25,909 nipype.workflow INFO: + [MultiProc] Running 3 tasks, and 0 jobs ready. Free memory (GB): 55.72/56.32, Free processors: 2/5. + Currently running: + * l1spm.datasink + * l1spm.modelspec + * l1spm.level1estimate +200225-04:07:25,983 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1263/datasink". +200225-04:07:27,143 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200225-04:07:55,809 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200225-04:07:55,936 nipype.workflow INFO: + [Job 161] Completed (l1spm.datasink). +200225-04:07:55,940 nipype.workflow INFO: + [MultiProc] Running 2 tasks, and 0 jobs ready. Free memory (GB): 55.92/56.32, Free processors: 3/5. + Currently running: + * l1spm.modelspec + * l1spm.level1estimate +200225-04:12:54,450 nipype.workflow INFO: + [Node] Running "modelspec" ("nipype.algorithms.modelgen.SpecifySPMModel") +200225-04:13:38,559 nipype.workflow INFO: + [Node] Finished "l1spm.modelspec". +200225-04:13:40,288 nipype.workflow INFO: + [Job 184] Completed (l1spm.modelspec). +200225-04:13:40,292 nipype.workflow INFO: + [MultiProc] Running 1 tasks, and 1 jobs ready. Free memory (GB): 56.12/56.32, Free processors: 4/5. + Currently running: + * l1spm.level1estimate +200225-04:13:40,962 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1design" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_008/level1design". +200225-04:13:42,293 nipype.workflow INFO: + [MultiProc] Running 2 tasks, and 0 jobs ready. Free memory (GB): 55.92/56.32, Free processors: 3/5. + Currently running: + * l1spm.level1design + * l1spm.level1estimate +200225-04:13:42,557 nipype.workflow INFO: + [Node] Running "level1design" ("nipype.interfaces.spm.model.Level1Design") +200225-05:18:37,312 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200225-05:18:38,222 nipype.workflow INFO: + [Job 168] Completed (l1spm.level1estimate). +200225-05:18:38,226 nipype.workflow INFO: + [MultiProc] Running 1 tasks, and 1 jobs ready. Free memory (GB): 56.12/56.32, Free processors: 4/5. + Currently running: + * l1spm.level1design +200225-05:18:38,600 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1253/contrastestimate". +200225-05:18:40,226 nipype.workflow INFO: + [MultiProc] Running 2 tasks, and 0 jobs ready. Free memory (GB): 55.92/56.32, Free processors: 3/5. + Currently running: + * l1spm.contrastestimate + * l1spm.level1design +200225-05:23:34,74 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200225-05:25:57,461 nipype.workflow INFO: + [Node] Finished "l1spm.level1design". +200225-05:26:00,657 nipype.workflow INFO: + [Job 185] Completed (l1spm.level1design). +200225-05:26:00,661 nipype.workflow INFO: + [MultiProc] Running 1 tasks, and 1 jobs ready. Free memory (GB): 56.12/56.32, Free processors: 4/5. + Currently running: + * l1spm.contrastestimate +200225-05:26:12,516 nipype.workflow INFO: + [MultiProc] Running 2 tasks, and 0 jobs ready. Free memory (GB): 55.92/56.32, Free processors: 3/5. + Currently running: + * l1spm.level1estimate + * l1spm.contrastestimate +200225-05:26:15,669 nipype.workflow INFO: + [Node] Setting-up "l1spm.level1estimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_008/level1estimate". +200225-05:27:05,369 nipype.workflow INFO: + [Node] Running "level1estimate" ("nipype.interfaces.spm.model.EstimateModel") +200225-05:30:49,395 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200225-05:30:50,796 nipype.workflow INFO: + [Job 169] Completed (l1spm.contrastestimate). +200225-05:30:50,799 nipype.workflow INFO: + [MultiProc] Running 1 tasks, and 1 jobs ready. Free memory (GB): 56.12/56.32, Free processors: 4/5. + Currently running: + * l1spm.level1estimate +200225-05:30:53,37 nipype.workflow INFO: + [MultiProc] Running 2 tasks, and 0 jobs ready. Free memory (GB): 55.92/56.32, Free processors: 3/5. + Currently running: + * l1spm.datasink + * l1spm.level1estimate +200225-05:30:53,109 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_1253/datasink". +200225-05:30:53,714 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200225-05:31:52,579 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200225-05:31:53,97 nipype.workflow INFO: + [Job 170] Completed (l1spm.datasink). +200225-05:31:53,101 nipype.workflow INFO: + [MultiProc] Running 1 tasks, and 0 jobs ready. Free memory (GB): 56.12/56.32, Free processors: 4/5. + Currently running: + * l1spm.level1estimate +200225-09:56:02,579 nipype.workflow INFO: + [Node] Finished "l1spm.level1estimate". +200225-09:56:03,113 nipype.workflow INFO: + [Job 186] Completed (l1spm.level1estimate). +200225-09:56:03,118 nipype.workflow INFO: + [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 56.32/56.32, Free processors: 5/5. +200225-09:56:03,295 nipype.workflow INFO: + [Node] Setting-up "l1spm.contrastestimate" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_008/contrastestimate". +200225-09:56:05,117 nipype.workflow INFO: + [MultiProc] Running 1 tasks, and 0 jobs ready. Free memory (GB): 56.12/56.32, Free processors: 4/5. + Currently running: + * l1spm.contrastestimate +200225-09:58:23,52 nipype.workflow INFO: + [Node] Running "contrastestimate" ("nipype.interfaces.spm.model.EstimateContrast") +200225-10:00:56,100 nipype.workflow INFO: + [Node] Finished "l1spm.contrastestimate". +200225-10:00:57,404 nipype.workflow INFO: + [Job 187] Completed (l1spm.contrastestimate). +200225-10:00:57,409 nipype.workflow INFO: + [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 56.32/56.32, Free processors: 5/5. +200225-10:00:57,617 nipype.workflow INFO: + [Node] Setting-up "l1spm.datasink" in "/media/Drobo/work/KPE_SPM_ses-1/l1spm/_subject_id_008/datasink". +200225-10:00:57,728 nipype.workflow INFO: + [Node] Running "datasink" ("nipype.interfaces.io.DataSink") +200225-10:00:59,288 nipype.workflow INFO: + [Node] Finished "l1spm.datasink". +200225-10:00:59,405 nipype.workflow INFO: + [Job 188] Completed (l1spm.datasink). +200225-10:00:59,410 nipype.workflow INFO: + [MultiProc] Running 0 tasks, and 0 jobs ready. Free memory (GB): 56.32/56.32, Free processors: 5/5. diff --git a/task_based_analysis/spm_2nd_level.ipynb b/task_based_analysis/spm_2nd_level.ipynb index e343a87..2775fb8 100644 --- a/task_based_analysis/spm_2nd_level.ipynb +++ b/task_based_analysis/spm_2nd_level.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -32,12 +32,12 @@ { "data": { "text/plain": [ - "['/media/Data/work/KPE_SPM/spm_l2analysisWorking/_contrast_id_con_0001/level2thresh/spmT_0001_thr.nii',\n", - " '/media/Data/work/KPE_SPM/spm_l2analysisWorking/_contrast_id_con_0003/level2thresh/spmT_0001_thr.nii',\n", - " '/media/Data/work/KPE_SPM/spm_l2analysisWorking/_contrast_id_con_0006/level2thresh/spmT_0001_thr.nii',\n", - " '/media/Data/work/KPE_SPM/spm_l2analysisWorking/_contrast_id_con_0004/level2thresh/spmT_0001_thr.nii',\n", - " '/media/Data/work/KPE_SPM/spm_l2analysisWorking/_contrast_id_con_0005/level2thresh/spmT_0001_thr.nii',\n", - " '/media/Data/work/KPE_SPM/spm_l2analysisWorking/_contrast_id_con_0002/level2thresh/spmT_0001_thr.nii']" + "['/media/Drobo/work/KPE_SPM_ses1/Sink_ses-1/2ndLevel/_contrast_id_con_0004/spmT_0001_thr.nii',\n", + " '/media/Drobo/work/KPE_SPM_ses1/Sink_ses-1/2ndLevel/_contrast_id_con_0002/spmT_0001_thr.nii',\n", + " '/media/Drobo/work/KPE_SPM_ses1/Sink_ses-1/2ndLevel/_contrast_id_con_0006/spmT_0001_thr.nii',\n", + " '/media/Drobo/work/KPE_SPM_ses1/Sink_ses-1/2ndLevel/_contrast_id_con_0003/spmT_0001_thr.nii',\n", + " '/media/Drobo/work/KPE_SPM_ses1/Sink_ses-1/2ndLevel/_contrast_id_con_0005/spmT_0001_thr.nii',\n", + " '/media/Drobo/work/KPE_SPM_ses1/Sink_ses-1/2ndLevel/_contrast_id_con_0001/spmT_0001_thr.nii']" ] }, "execution_count": 3, @@ -46,18 +46,18 @@ } ], "source": [ - "stat_files = glob.glob('/media/Data/work/KPE_SPM/spm_l2analysisWorking/_contrast_id_con_000*/level2thresh/spmT_0001_thr.nii')\n", + "stat_files = glob.glob('/media/Drobo/work/KPE_SPM_ses1/Sink_ses-1/2ndLevel/_contrast_id_con_000*/spmT_0001_thr.nii')\n", "stat_files" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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\n", + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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GzZo1w8GDB5GUlITBgwfD19cXI0eOxLZt21TXuGrVKly6dAkDBgyQ/Wr0adWqFU6cOIE9e/ZgzJgx8odLgwYN0KxZM9VQFnd3d+zfvx/BwcEYOnQoCgsLy7zP9vb2qFatmurjxNzcXLWYyj///IMRI0Zg8uTJ5fYzcXNzQ15eHlJSUhTbN2/erPjYGTFiBPbs2WN0SJeXl5fciXfu3Bn+/v7YuHEj+vbti7fffhunT59WvXAuXLgQOTk5GDJkCFasWAFfX1+FGR3QdTzLly/HkiVLMGLECNSrVw8bNmzA5s2bcerUKQwaNAgxMTHYunWrwXHCFeXll1+GnZ0d/v33X3mbi4sLwsPD8f7778PLywsrVqzAN998g5kzZ6qOX7FiBS5duoQ33ngDJ06cwC+//IK2bdvK++vXr4/g4GCMHz8e/fv3x/bt27FmzRrFPedZuXIlhg4dqnhptLOzw+DBg+WXvM8//xxvvvkmvv76a/Ts2RPTpk1Denq6UXkaNWoUvvjiCyxevBi9e/fGpEmTcPPmTfkcNCSNPmocHBzQtGlTnDlzBmfOnFF97Jw+fVper1GjBk6cOAFbW1uMHDkSH3zwATw9PREYGKjwEwOARYsWITMzE0OHDlUNn6T7dfLkSdy8eRP9+vVTDfnUx8fHB6+//jomTpyImTNnol+/fooybWxscOjQIdjY2GDEiBGYO3culixZgnr16qnKKk8fCgC7du3CpEmT8PPPP8PLywu+vr4KRcLs2bPx5ZdfYvny5RgwYACCg4OxadMmVbvXq1cPCxcuxLfffosRI0bAyclJ8bJAH/dz5syR+179YbGG7qcp/xu7d+9GUVER3nrrLQwYMABLly6Vh62+//77uH79ujwsrX379hUefrxr1y689NJLeOedd/Dxxx9j6tSpqheAsvjtt9/wzTff4M8//0S/fv3wySefKJ6N8ePHY9myZdi9ezf69++PrVu34vvvv1c9r7a2tli3bh1+++03DB48GHl5eQgICDC5P2natKnBYUnXr1+XfTMaNWoEKysrVb7r16/D3NwcL774osllEc2bN0d6ejq0Wi2CgoJUL+CAri+2sLDAiRMnjNZ/27ZtGDt2LL777jv0798fISEh2L17t+zTsGXLFrRr1071fuHj44N9+/bJ/wmmvPOYgoeHBxITE+VhPaW9ZwDAJ598AmdnZ7z11ltYuHAh3n33XUydOlVV7ubNm7F37154eXlh7969Jl17w4YNsW3bNhw7dgz9+/fHm2++ib1796p8qEypA98WixcvRqdOnfDRRx+hd+/e+OKLL1Qv8ra2tti4cSP8/f0xdOhQpKWlKZRRxPDhw9GuXTuMGzcOCxYswCeffILFixdjzpw5+Prrr/Hee+/B09NT8UL9MDAkrwUFBbh165Ysr5Qakv3q1avL/aMpZT0Myuo7FyxYgKysLAwZMgQbN26Er68vhgwZoiiD+oyVK1eiT58+OHfunNHz2dvbY82aNfj1118xePBgFBYWIiAgANbW1g9+MRUdxnb+/Hn20Ucfyetr1qxhBQUFrGHDhvK2+fPnM8YYGzVqlLytb9++jDHGmjZtygCwRo0asaKiItUQmHXr1rFz584xQDcsKCYmhv3yyy+KPIcPH1YMEyrLtKbRaJi5uTm7fv06+/rrr0u9HmPD2Gi5f/++qj60mJmZMWdnZ5WJ3ZRhbGZmZqxSpUosIyNDcd80Gg2Lj49nb7zxhrwtJiaGffLJJwwAGzduHDt//jw7ffo0e/fddxkA9sEHH7D4+Hg5/+bNm9mNGzcUw8eGDh3KGGOsffv2DNANM2OMscWLFxs0BU6ePJm1a9eOpaSkGDQxT5kyhV26dEll7mSMsejoaKPDRGjIQJUqVZi5uTlzdXVlW7ZsYQUFBfLwH8pjCE9PT5PMma6uruzixYvycbdu3WLff/89q1WrliLfnTt32KJFi5i5uTmzsbFh3t7eLC0tTTGsgIYO1ahRg+Xn5zN3d3dmaWnJUlJS2MCBAw0Os3zppZdYYWEhq1GjBgPAPvnkE3b+/Hmj9aX7d+jQIcX25cuXs+joaNlM7evryxhjrEuXLnKeSZMmMcaYQtabNWvGGGOsT58+Jt2vsoZyaDQaduzYMRYeHs4sLCyMlmNubs4+//xzduvWLXkbydo333wjb7OwsGAJCQls3rx5pZbl7++vGObC17Ny5cosKyuLjR07Vs4zbtw4ptVqWbVq1RgAtmfPHrZo0SKTr33p0qVs27Ztpd6vO3fuyEMQ+vTpwxISEhgANmTIEPnabW1tWX5+vvzsAmDz5s1jqamprHLlyvI2GpIzfPhwhSzs2LHD4HkXLlzIGjVqxO7evcu2bdvGLC0tVXKk3zfeuXOH3bx5UzEsccmSJSw2NlZef//991leXh5zdnZW1YsfosX3oaUtvXr1Yowx1r9/f4P7q1atyrKystisWbMU2/ft28fCwsLkdfrf0R+6MXDgQMYYY02aNGFA2UMxDN1PXsb5/43q1aszxhh76aWXjB5XkWFsvMzR/2W7du3kPPXq1WMFBQUmD6Vp0qQJY4yxDz74wOj1RUdHs9WrVyu2//zzzywtLU0edkJ9TLdu3eQ8LVu2ZIwx1rt3b5PqcvjwYRYQEKDavmHDBhYcHMwAMA8PD8YYUwz7BHTvCowx1rNnT5PLAsA+/PBD9t5777EuXbqwwYMHs9OnT7O8vDzWtm1bxXGLFi1iu3btMtoW3bt3V/WxANhff/3F/vzzTwbo+qbExEQ2c+ZMeb+zszMrKipigwcPlq+jrHceQD2MjV+aNWvGcnJyVO8UpQ1j++uvvxTbAgIC2JkzZ1TX/OGHHyrymXLtgwcPZklJSaW2vyl1MNQWV65cYVOmTDFaLsnmiBEj5G12dnYsOTlZ8V9y584dlQvC33//zQoKChRDwubPn8/i4uIMnquiw9hu3LjBlixZotoeFBTEfv/9dwaAjRw5kjHGmIODgyLP66+/zhhjrHHjxiaXpb88qmFs69atU2y/ePEi27x5s6pdBgwYUOa55syZwxhTvjO3adOGMaYclhoVFaVo0w0bNqjkx5DcVciyU7t2bbRu3VqlqYqMjMTt27fl9Zs3bwIAjh07ptrm4uICQBdhpLi4GAEBAQpN/dGjR9GqVSuYmZmhbt26cHZ2Vjl67tixo8y6Nm3aFDt27EBcXByKi4tRWFiIpk2bytqh0q6nNPRNdQDQp08fBAcHIy0tDUVFRYiJiQEAxXmM8dprr+Hw4cNISkpCUVERcnNzUblyZcWx7dq1g6Ojo2KIyKlTp9C5c2cAQJcuXXDy5EmcPHlSse3UqVOKMgICAhTDx7Zv346CggLVUARj96Jjx44IDAzE8uXL8eGHH6r2GxvCdujQIbi4uODzzz8v9V6kp6ejsLAQUVFR6N69O95++22VY1znzp3h7u6uWGhoUllER0ejTZs2eP3117Fo0SKkpKTg448/xuXLl2WZJD755BMUFhYiJycHe/fuxcmTJw1GkklKSsKxY8cwfPhw9OnTBxqNBgcOHDB4fm9vb5w7d07WxIWGhqJ169ZYvHgxOnfurNLiEwEBAYr1HTt2wMXFBa6urvK2vLw8xZAOU56/B2XevHno0KEDRo0apbDWWVtbw8/PDxEREcjLy0NhYSG+++47NGzYUGU5OXz4sPy7sLAQERERiutydHTEjz/+iMjISBQUFKCwsBDvvvtuqc9WZmamrIkkxo4di927d8uWudDQUIwdOxYzZsxQDa01RGhoKLy8vODn54e2bduqoiABOusOWXA8PDxk8/rZs2fRsGFD1KpVC+3atYOlpaXCstOuXTscPnxYYRUJCQnBnTt3TH42mzRpgpMnT+LUqVMYNmwYCgoKyrym48ePK4Yl/vvvv3BycpLlsG3btrhw4QLu37+vqBdvbS1vH9q9e3ckJycbHYb30ksvwc7OThGNCihxSK9Zs6a8LTIyUpZrugYAChkqDUN1Lut/IyUlBffu3YO/vz98fHwU9XmYtGvXDnFxcQpt6L1790zu74AS7ezatWsN7nd1dYWLi4vBe+3g4KB4NvLz8xWWj/LeawAGh9ZoNBrVdn6d/nP1t5tS1k8//QR/f3+cPHkS27dvR/fu3RETE6OKollW8J8ePXogNjYWwcHBqncVd3d3AEBRURF27NiBYcOGyccNHToU2dnZctmmvPOUhaOjI7Zv347Lly8btO4aQ7+vBXTtZ6jt+PtgyrVfuXIFDg4OWLt2LXr27AlbW9sK14Fvi9DQUMyYMQOTJk1C48aNjV6f/v9kdnY2AgMD0a5dO0WeEydOKN6Bbt68icjISMWQsJs3b6JmzZpG/48ryuOW/UeNKW1ZXFxs9H2IJzc3V/EOU5H+xRgV+tjx8vLC7du3cePGDcX2tLQ0xXp+fr5qO22j6Ak1atSAhYUFMjIyUFhYKC/r1q2DpaUl6tSpI0f0SkhIUJTPr/PY29vj8OHDqFu3Lj7++GN06tQJ7u7uCA0NVURvMHY9xrC2tkb16tURHx8PQDdEa/fu3YiOjsaoUaPQvn17OZJLWVEi6tati8OHD0Oj0eDdd9+Fh4cH3N3dER8frzjW29sbJ0+elMdQArqhbPQi1LlzZwQFBSEoKEj+2OnUqZNCcOrUqSPXmSguLkZycrLK1MznI3r16gULCwusX79etc/W1hZdu3Y1+IexdOlSLFiwALNmzVL5ZOjTuXNntGnTBvXr10etWrWwYcMGVZ6LFy/iwoULikX/vpRFcXExjh07hhkzZqBt27bo1asXqlWrhk8++USRb8OGDXB3d8fLL7+MypUrY8CAAUZlbsuWLfDx8cHIkSPlsbOG4Dvxo0ePYty4cejSpQtOnDiBpKQk/Pzzz6o/CmOyrz8ULzMzU9HRGXr+6AXYpOglZTBp0iTMmDEDY8aMUZmm58+fj+nTp2P58uXw8vKCu7s75syZY/DchvoN/Txr167FsGHDsHDhQvTq1Qvu7u5YtWpVmdewatUqdO7cGQ0bNkTDhg3RpUsXhR/P3Llz8fPPP+P999/H5cuXERUVZfADnli9ejW++OIL+Pj44Ny5c4iPj8fs2bMVLyenT59G06ZNUa1aNXTo0EH+oImOjkZ0dDQ8PDzg4eEBrVareGE19GwCuufQ1GfTw8MDzs7OWLlypcqvyhiG7r2ZmZk8hr527doGIw3x28rbh1avXr3UENUk1/y10nrVqlVLvQbAdBnnz2HK/waT/Brj4uKwevVqxMXF4eTJk2jVqpVJ5zSV2rVrG+xzyvrv06d69erIysoyOrywrHutL38ZGRmKPqa8/UlqaqpBXwhHR0e5HVNTU+VtfB4AinxllWUIrVaL/fv3y0PAAd0QrKZNm5YaSbBGjRqoU6eO4j2lsLAQ33zzDerWrSvn27JlC1q3bi2/lA8bNgy7d++GVquVyynrnac0rK2tsWvXLlhbW2PAgAEmKTWIsvpagpcFU679xo0bGDhwIBo2bIj9+/cjKSkJv//+u2Joqil1MNQWU6ZMwc6dOzFr1izcuHEDN27cUHxQArr/P7rHREJCgup+Gjp/Wf3gw+BpkP2HjSnylJqaarKMpqenq8oDHs77SoVCTz/M8McpKSkoKChAx44dDTqsJyQkyE74+s66htZ5OnTogLp166Jnz54IDw+Xt/P+EOW9nm7dusHS0lLW2r7xxhtITExUPHyGxrQbok+fPrC1tcXAgQPlcKPm5uaqFxxvb2/Vi39QUBCqV6+Onj17okGDBggKCkJBQQFcXFzQs2dP1K5dW/GxExsbq7pnZmZmqF69usoPxZh2YO7cuejRowcCAwPRuXNnhSXv9ddfR05OjlFnsZkzZ6JWrVpYunQpEhMTDfoKXbx48bGHLw4MDMSlS5dUY13j4+NN1qDu2LFDHitsbNy1o6MjOnTooHqhXr9+PdavX48aNWpg0KBBWLJkCTIyMhRWMGOy/6TmNBk0aBCWLl2KTz/9VOVIDOi0mUuXLlXM/VKRmPzW1tbw9vbGlClTFHPSmKL9DAoKQkREBMaMGQONRoOYmBiFJiovLw++vr7w9fXFCy+8gPfeew8//vgjwsPDcejQIVV5jDH88MMP+OGHH+Dq6oo333wT3377LeDtwhYAACAASURBVGJiYuS60cdNp06d0K5dO/kDD4Dst9OsWTOcP39e8UFs6NkEgFq1aqlk0NizuWbNGlSpUgU7d+5Ejx49EBISUuY9Kou4uDiD85Hwlozy9qHJycmlvtSRXDs5OSn6Jhp/z/dXDwJ/P0393wgPD5f9UDt37oz58+dj3759cHV1fWja1bi4OINy4eTkVKovlj7Jycmwt7dH5cqVDX7w6N9rfR7FvQ4LC5OVcfo0bdoUO3fuBADcunUL+fn5aNq0KU6ePKnIU1RUJH9Qm1JWaei3kbe3Ny5duoTo6Gij+VNSUhAdHY3/+7//K7XcEydOIDY2FsOGDcP69evx2muvKfw/THnnMYaZmRk2bdqEFi1awMPDo1wfveWBl19Tr33//v3Yv38/qlSpAm9vb/zwww9YunSpKrBIaRhqi/T0dEydOhVTp07Fyy+/jE8//RS///47Ll++jOvXrwMAKleujEqVKik+eJycnJ6aeb/CwsJU7xiWlpZo2LChHNqa/HCaNm2Ke/fuyfmaNm2K5ORkeUSIKWU9LTxOS1NplNuyY2lpiR49ejy0j51jx47B3NwcDg4OKm39hQsXUFBQgKioKMTGxqomaBs0aFCpZZPTZF5enrytQ4cOCufB8l6Pg4MD5s+fj4iICBw5ckQ+D//l+uabb6qONfTVa2NjIw+TIHx8fBTm0zp16uDVV19V1fHKlStITU3Fl19+ibCwMCQlJcmTZH755ZfIzMxEaGionP/vv//GG2+8oXhRHDRoECwtLRXD3UqjoKAAQ4YMQXh4OI4cOQJnZ2d5n7e3Nw4ePFhqlLV33nkHBw8exIYNG9C1a1eTzvkwMTTcxNraGq6urkY15qaQkZGB+fPnY/v27bJc8PTp0wfx8fGKNtEnKSkJy5cvV0WTAnQf1PoMGjQI9+/fL/XP+VHh6emJ33//HcuWLcP3339vMI+NjY3iuTMzMys1oIAxrK2tYWFhoSjL3t4eAwYMMOn41atXY8yYMRg9ejTWr19vVDZv3ryJ6dOnQ6vVqu69IaKjozF//nzcvHlTkf/y5cvIyMjAxIkTYWNjo/jgOHPmDDp27Ij27dsrhrABumezd+/esLe3l7e5u7ujQYMGJj+bAPDee+9h7969OHDgAF566SWTjzNGSEgI3N3dFc9527ZtFfNnVeQ/4ejRo6hevbrRD+CrV68iOztbFbnHx8cH4eHhinkWyqK82kFT/jf0KSwsxPHjx7F48WI4OzvLGldjWvPyEBISgtq1ayuG4tStW1dhlSgLGsZqLNpXdHQ0YmJiDN7r9PR0XLlypQI1N8yBAwdQp04dRZSsNm3aoFGjRvJQl/z8fBw/flxVn2HDhuHMmTPIyMgwuSxDVKpUCX379lUoEUz5WD969Chq166NrKwsg+8qBGMM27Ztw7Bhw+Dj44OMjAwcPHhQ3m/KO48xfvnlF/Tp0wf9+/c3akV9GHLHY+q1ExkZGdi8eTMCAgJM6k/1Kastrly5ghkzZsDc3Fz1wq//P2lnZ4eePXuW6hD/ODlw4ADatm2rUIQPGDAA1tbWsnzcuXMH4eHhCtnXaDQYOnSoQqZNKeth8DAtK0+aclt2unTpAjMzs4c2YdWNGzfg7++PLVu2YMGCBTh//jwqVaqEFi1a4MUXX8SECRNQXFyMBQsWYNGiRUhKSkJQUBAGDx6sCPFqiLNnzyIzMxMrVqzAggUL4OrqCj8/P8ULYmnXY2FhIQ9Hq1y5Mtq0aYNJkybB1tYWffr0kV+cAgMD8dFHH2HJkiXYs2cPPDw88NZbb6nKCwsLkz8IsrKyEB4eLnd8a9aswapVq9CiRQtMnz5dNmcCuiEiERERiIiIUJTHGENwcDD69eun+JoPCgrClClTcPjwYcVwlrlz5+LixYvYuXMnfv31V7i6umL+/Pk4ePAgzp49W+q91Eer1aJ///44cuQIjhw5gi5duiApKQleXl747LPPSj22qKgIQ4cOxZEjR7Bz50507drV6Mu/Mdq2bavSaiYkJODOnTtlHnvo0CGEhYVhz549iIqKQu3atTFlyhRUrVr1gWez9/X1LXW/oQkX/fz8UK1aNXkIW+vWreHp6am6jy1atIC/vz+2b9+OLl264J133sHUqVMfu9aEtKZhYWH4448/FBPvJSYmypa+wMBATJ48GTdv3kRKSgomT55coYgqGRkZOHfuHGbNmoWMjAwUFxfjs88+Q3p6uipaoSHWrVuHuXPnwtLSUuWzsGPHDly4cAEXL15Ebm6urKXX1ybr4+/vL4dTTU9PR7du3dC4cWNFxKri4mKcO3cOffv2lcslzpw5g0WLFsHMzEw1mejixYsxadIkHDp0CPPnz4e9vT3+97//4fLly9i+fbvJ94sxhtGjR2Pbtm04fPgwunTpovBnKS9r1qzBV199hb179+Kbb76BjY0NvvnmGyQkJMj9X0X+EwIDA3Hw4EFs2rQJs2fPxj///IM6deqgS5cueO+995CamooffvgBX331FQoLC3H+/HkMGjQI3t7e5f5oLigowO3bt+Hj44OrV69Cq9Xi8uXLRvOb8r/x8ssvY9GiRfjjjz9w+/ZtVK1aFTNnzkRoaKjcd4eFhaF3797o1asXkpOTcefOnXJbSfbv34/Q0FBs3boVM2fOhFarxezZs8ul0b9x4wZ+++03fP/993BycsLJkyfh6OiIIUOGYMSIEWCMwc/PD7/99huSk5MRGBgIT09PTJo0CV988YXio+9BOXv2LA4ePIj169dj+vTp8kSgQUFBOHr0qJxvzpw5OHHiBJYsWYKdO3fCy8sLXl5eirC6ppRVpUoV7N27Fxs3bsTNmzdRo0YNfPTRR3BxcYGPjw8A3fBrT09PzJ49u9S6BwYG4tChQwgMDMT8+fNx7do1VKlSBa1atUKlSpUUPkB//PEHPvjgA3z00UcICAhQfMCY8s5jiM8//xzvvvsuvvvuOxQXFyv63n///Ve22hl6zyjPMO+KXvvEiRPRoUMHHDx4EPfv30fjxo0xdOhQg0PejWGsLYKCghAQEICrV6+CMYYJEyYgKytL8SGTk5ODb7/9Fvb29rh//z6mT58OKysr/Pjjjw907Q+Lbdu24csvv8SOHTvw9ddfw8HBAUuWLMGmTZsUfbSfnx82btyIyMhIBAcHY8yYMWjcuLFiugVTy2rWrBmaN28uf6y4u7sjKysLiYmJRv/n9Clv32kqZmZmyMvLw6xZsx561DujsDIAF9Vg8eLFBiOgGJq4y1AkJ2MR06ZOncquXr3KtFotS0hIYCdOnFBEIwPAZs+ezRISElhGRgbbuHEjGzFiBGOs9GhsvXv3ZleuXGE5OTns0qVLrG/fvoooJ8auh6JIMMZYUVERS01NZSEhIWzu3LmqyF0A2IwZM9i9e/dYVlYWCwwMZC+88AJjTDmB1quvvsrOnDnDsrKyGGMlEcRGjRrFbt68yXJyctiZM2dYu3btFJME7tixw2DkDQDs008/VUUh8fHxYYwxVcQ5QBdV5ezZsyw3N5fFx8ezn3/+WdE+FCFLf5JMWvjrcXR0ZBcvXmQXLlxgr7zyCissLJQjXZXV3lWrVmVXr15lsbGxrGHDhiZN4FZaNLYVK1aYFF1k+PDhbOfOnezevXtMq9WyqKgotmvXLlVkHlMmaSwrj340No1GwxITE9nAgQNVeY4cOcISEhJYbm4uCwsLU0Tyofs3cuRItmnTJpaRkcESEhKYn5+fSl756IHG2pJvx9IWvl1KawP9yFNOTk5sx44dLD09ncXFxbH58+ez8ePHK8oyVj8+ClGjRo3Y0aNHWVZWFrt79y6bMWOG6npLk5+goCDFZIS0TJ8+nYWEhLC0tDSWkZHBzp49q4gaY+jaT506xZKTk1l2dja7dOkSe/vtt1Xl+vn5McYYW7p0qWK7lZUV02q1jDEmR+PTX1q1asWOHj3KsrOzWWpqKvv999+Zk5NTmc+SIVm0srJihw4dYpGRkczV1dVoNDZefg3dx1deeYUFBwczrVbLwsLC2MCBA1l4eLjcJxnrQ8taKlWqxBYuXMiioqKYVqtlt2/fZnPnzpX3m5mZMT8/P3bv3j2Wl5fHrl27xkaOHKkow9D/jqFr7dmzJ7t06RLLzc2Vn8nS7mdZ/xs1a9Zk69evZ7du3WK5ubksNjaWbdq0idWtW1cuo0GDBiwwMJClpaUxxkyLhGTo/tetW5cdOHCA5eTksMjISDZx4sRyR4QyMzOToyHm5eWxqKgoVfS1yZMns4iICJaXl8du3brFpk2bVmYfU97+BNBNTLx69WqWmprK0tPT2e+//25wwsyBAweyK1euMK1Wy65fv86GDRtW7rKsra3Z9u3b5f4+LS2NHThwgL322mtyngEDBrCkpCTVJOGG2sLKyor5+fnJ9yk2NpYdOHCAeXl5qep29+5dxhhjvXr1Mngfynrn4fvB48ePG+179aORGnvPMNRO5elHy7r29u3bs71797KYmBiWm5vLbt++zf73v/8pJjwtqw7G2mLBggXs8uXLLCMjg6WmprJjx46xTp06qcro1KkTu3jxItNqtSw0NFQR2Qsw3OeZ+u5Ky4NM6Ovi4sICAgJYZmYmS0pKYsuWLWM2NjaqfOPHj2cRERFMq9WyCxcusO7du1eoLP33WH3KU//y9J38vTTWZ5ibmzPGGPvyyy/lbXPmzFFEAtXPRxGGgYpHYyv3x054eDgbP358hRr6aVye9uuxtLRkGRkZrEePHk+8LqUtn3/+OTt16tQTr8fTunTo0IFptdpyz8b9IDMVi0X3UZ2Tk2Pwo0QsFVvc3NxYfn6+HNb7ae9DxSKW0pbffvuNbdy48YnXQywVb4uypgoRy397YYwxjfRBYxQ+xLJAIHh81K9fH5GRkejXr99D85P7L2Bvb4/mzZtj6tSp6NGjB9zc3Ex26BYo+eyzz3D//n3cvXsX9erVw+effy5PmGrqBKICgUDwqPD19cWUKVMeWQh4wbMNY6xi0dgEgqcRjUZTapQuU8Px/pfg57zR51m+X23atMGJEycQGRmJ0aNHiw+dB4AxBl9fXzg7O8tzOU2fPr3UD53S5Kq4uPipidDzuHkUz1tpZTLGSg0Y87B5XvsTgaA0ntV3j6ep73jklHcYm1jE8rQuxsanEvrjmsVSuv8NY+WfbVksYgFKhl4aQ9+367+0PKrnrTQq6lvwNF2fWMTytC/P6rvH09J3PI7rFMPYBM8NderUUYTI5XkYUWmeJ6pVq2Y0nC6ACkWPEggsLS3xyiuvGN2flJSEu3fvPsYaPR08quetTZs2RvdlZmaaPNHrgyL6E8F/lWf13eNp6TseNYwxiI8dgUAgEAgEAoFA8NzBGCv/pKICgUAgEAgEAoFA8CwgPnYEAoFAIBAIBALBc0mZHzu1atV6HPUQCAQCgUAgEAgEgocCfcOU6bMjEPxXOSH5qzWW1h2lNFFKo4OC4Oio20ohHLVaLQAgPj5esb1+/fq6MqT8FNIxKSkJABAVFQVA59wNAK6urgAAW1tbxXbyocvLywMA5OTkAIAc9pL203YqPzk5WbG/cuXKAAAbGxsAkEMBU/3JmTI7OxsA5NDNkyZNMnyzBE+UH3/8EQDg4uICoKSDr1KlCoASOaL2z8/PBwA5fHRGRgaAErmg4yil7YWFhahWo4aurC7SyV2kNFtKI3RJ6nVdGn/9OqpVq6aoR+/evQEAGzduVFwH7Sd5zM7ORsoLLwAA2jpImTyl1E5KY6T0pi5h93UpPadO4i/ugXB3fwHnz39fyv45OH/+/GOskUAgEJQPMc/OY2DatGkAgB9++OEJ10RQFqKtBAKBQB8GQPukKyEQCAQV5j/5sbNs2TIAJVpt0poTo0ePfqjnO3DgAACgSZMmAEommKJ06tSpD/V8gooTGhoKANiwYQOwfj2Ki4vhPHYsgBLFdfzJk3ByckJNANbW1gBKLDVkcSHNuZ2dTv3MTzhGlpOYGJ1auqCgAIAuhCWglk1KSeNNGnoLC90jbGVlpSifzk/1Iw19pUqVAAD29vaK46g8kkmy8FA5ZNn5448/AADp6emK6/3ggw8gePyQRYfCnjo5OQEoaW+SP7KYkBxSu5HcUkryQnLCy29ubi40NaST02TlZHEhJItLValbvdmsGTIB1I+Ply2dVB7JNZ2f5JCeh+LiYjjeuIGMjAzEuLsDAFz+lc7jJqU5hu8N9eqRUpluwsJTQYohPnYEAsGzjAhQIBAIBAKBQCAQCJ5LHqllx83NDStXrkSPHj0e5WmM8uuvvwIAHBx0qkfSZpOFhbTapGUkbeKuXbsAlIxnf+uttyp0/q1btyrOU7duXcX5SJu5e/duACXaVjrv22+/XaHzVhQ3NzfES9pXe3t79OnTB8uWLZPv2/PM5s2bAZT4uJDPQ2FhIW7u2ydbOOrWrQtblFheSBNOPjIkQ5QSpLHW90UASiwoJKNULmnAKaXjeU087ScNOVlmaDvJHpVP66S5p3WyEBUWFirW6Ty8Lwf5YJCFKlSq31npmXvvvfcgeHSQRad69eoAStqXLDjUviQH1LdQu9J2Wqc+ieST35+fn4/bkq+OKz93Hol6tjLNVz4CyM3NleWb9x2j54u3kNJzlZGRIdsWakq+OVZk0SETDp1fgmydZHgSFp6KUgwg70lXQiAQCCqMsOwIFOzZswdZWVkIDQ3FxYsXMW/evCddJYFAIBA8Mchnx9giEAgETzfPlc8O+eKQtrBmzZqKdUp5rTZpNUmrTZYM0pavW7cOADBmzBiT6rFjxw7F+Uk7SpG4eEibSlp5yrd3714AJdpzsjpMmTLFpHo8CLVr10bv3r1lH5bnjVWrVgEoudc1JK01WWrIskNWNmoD0kgT1LaEMcsOQceT5px8IniZ430bCJIRXgNPKWnG6ThexnlLEF2vpaUlYqRIXjWh04rbSuekoFcAYEdadErJb0My3rbaLkVr+0mXMikil0Zo0x8KZK2uV68eAHWfxssNyQtZSEj+qN15HzBK+eh/ubm5qBMVhfv37yP7tdcAAHZnpEqR6YQsLVw0tOKzZ2FnZ4fMzEyVfyRZevR9ggAj0eJ27oS1tTUi+/YFALhI5yGZZNwjZ6tclUU2RLqmtkImTUT47AgEgmcbYdkRGCQ6OhoHDhzAC1LYV4FAIBAIBAKB4FnjmbbsLF26FECJdtOY5YTXppO221iEIspfvXp11GrfHgDgZglgwlisW7FWZeHZsmULXh4xAgBwfetW1K5d22D5dH7SthJ8JCLS9tM4fPKPoPH5W7ZsAQAMHz7c8I15AP7v//4PGo0GWVlZ6N69O7755puHfo4nxTXp/l5Yt06OWkUyw7cVaaBJVnhNOFkBCd4Pi6C25tuY91XgfWeM+erwssNr8imlcvjrImg/XaeZmZlspKHUjlTj+j4a9JvMPZbcOodG0vbnS9dBgbRaCa16uSCLToMGDQCofbD4dud9xMjSSJYTaneyCJF8k6WFUkJfjq+cOSOXo9VqUcfLC0DJPFT5UpoupVqtVq4f+apRvXgLJJ2Hl0/9+qRDiZ1k0eEtkVaSbNpyFp80CMqHCD0tEAiebYRlR6Bg586dyMzMxIkTJxAWFiYPnRMIBALBfxEaxiZ8dgQCwbPJM2PZ0R9nTT40NG6dtNs8pCUkLTxp0UmbyWsV9SNdZTVvDjMAbjQe3U2XjFkyFlgyVh6Qzu4DwwDclbJVrVpVpU0nLSb5ffDaedpP2lV+dnsqh/w6aHtAQAAAID4+HsDDjYDl6emJsWPHYvr06di5c+dDK/eJYKWTHdI8N5Isc2anT8tWNLr3/DwfJDO85pwgmeE11SSTtJ23+PAzxVPK++zw/lwky/w8O3z96Hp4TT8fxU3/PORjIWvISSOu72Yhm32klA6KkFJSm+co91NR1AbBUn06CgtPqVDUtUaNGgEo8S0j+eHbl7dek9zQOvnukC8MHUeWIoq2x/vWULl0Xn3fr6ygIKSmpiIKQEpKCoASf8UqVarAHGrLJy/3VB7fB/I+aGlpaUg7fBjFxcXI7tMHQIkoktySjDlLQqfhLDwkwsJ3x1SEz45AIHi2eeQfOwUFBXJ4XUD358y/MAqeTqZNmwY3NzeEhoaiVatWT7o6AoFAIBAIBAJBuXjkXx1e0nhu4ssvv8TcuXNNPp5J2jfSxm3fvh1ubm4A1FpGfhZ4Gh9Ovji8/wRpC+k4fe24PCk47waUz6UcdnZ2irkp9M+bkZGhOF9Zfhr8XBf8OPzCwkLU7NYNLwJoDCB/0iSs8ffHu+++a7hy5aRmzZoYPXo05syZg+3btz+UMh8rdsrIabzmt9jeXmUhoXU+GpSxmd95jTXvm8MYQ/W+fZEB3TQgsQCaxsbK1kWy1pGM8NZA2s7LEl9fwlTLEn89BQUFcImJQU5ODjKg87PIefllAIDbXb0Da0IJWXIidUmqNOqRDD68fwXvV0FzWqWn63KOHj0aghKcnXVOUmR5IcuHsXmSeCs39X10HKW0nbcoUrkE7aftVA/y2SH5IfkkxRZZTI3N+8PLJS+39FyQJZP3pywoKEDBnj2ws7NDFnSWoFzpuEzpvBH16wMAakoWHZI5vksnXz6S2a7C0sMhfHYEAsGzzSP92ImMjHyUxQseMobaixyjBQKBQPBfRAxjEwgEzzZP33iyVpKmWtIY03hrGvRft25dWVvI+yXoa6n195OFh/bzPjukLde3/ORSfaS5HGQNtlQPlqPcTJN3k6ZVvx78OHXyueF9c3itLGlJjVl2gBJ3CitJZf7upveATe9h5agV8vGPY16ep4ls6T6RFYFkiFqGNLz51tayhpp8Gfh5R0izTPeSUsZpf41Fv8rLy1MFLMvPz1f55hiLukYac0oJ3ippzLeHNOJULj+ElNew03GFhYVIu3gRVlZW+Bclvhx2desCAKryEcklEw5pxy1u3QIAOHLWVKpfQYsWAEoiDFLEwYMHDwIo8UMzdW6r543169cDKLkvhL5cAWrfF14OKD8fPZD32eItRDy0nfpOOg89D/oWT5c33tCdOzhYLtdY+bwllKDy9OeB0l/n62MouqBtVBQAXd+cn5+P+5LfE+92RpaexlJK/YedsPBIMAB5T7oSAoFAUGFENDaBQCAQCAQCgUDwXPL0WHaGSJo9UrtJphKaFZs0xpUrV1ZFKeO1gKQtpHWyBBF0PB+hSDEXxT//wNzcHDEtW+rK4JwPKLpUDpdamZurtOR8tDXSktP4dxrfTpBvD6UEb7nKzMyUfSLI0qSRKjb+ygTdj/oAFn+AtdXWYOzYsXjeWbduHQZIv8miYlnArUtpoZmZ3EZk4eF9CEhzTD4lFFGP2o6XRd7SkpmZiasbNqBhw4YAdJaM3Nxclaa6LMsMrfOabYLPT9dDssL7pRG8rPKWA97CVSBZXK7VqgUAaEHObdIjZicJpEa6b7yfHJWfKh2m6dwZAFA5NFR3vPQskM/GCen81GbPe/Q2f39/ACVR16id6T7yljo+wiTlp/28PGi1Wph7esIKQNFff8nH8REkeR8v3nKkb62u+uqrcETJFEzUNyZ27AgAyLl2Ta6XMcsin5bVd9J26sN5XyDeElpcXAzriAgUFBTgbvPmAHRdIwA4kXBJF2BleLq2/zBiGJtAIHi2eXo+dgQCgUAgEDxliI8dgUDwbPPkPnamSpYc0qqRRYeb24MsJgXBwahataqiCN6vgbfw8PPnELSdH3dOWmfy8bG3t5dddkiBXeKRo4MPylZcXGw0MhdZAUh7TT47pFWlepA2Ni1NOdc3Ha+v/YzesQNarRbOI0cCAFzIBEaHStrKsdpxgP84bK+5DYMHD8bzSL5GgxEGtnMTqMsid7+xbpS+VWioym+LZInairewkMzx89aQppzaliZlpZT3v+KjUBG87xDvY8FHbaP6kewamx+I9xHiLTr8Oh1H2+n+OCUk6M7n5KS7T5IPj4t0c1NdXACUWGQJen5cpJTENEsKbU5tRbZOeymlNguV6k0+cs+Lpeenn34CALi6ugJQR18jSyClxnzEeDmmPiUnJwe2XbvCBiVdbaKnJ3IBOEVGyuXy/oXGLIZ5eXnIa94cGpRYdKxqSCk1omTli2nRAvkArCMjjfqo8fJM8kvnpz7b0dFRcTztJ+s870NE59O/rkqXL6OwsBD3X30VAOAkVVe+MeS8M0b6j1r3fMhYxRHR2AQCwbONsOwIBAKBQCAwgrDsCASCZ5vH/7EzXdKWOXDb+dnaJRUwWU60Wq2stePHZ5PWkbSbZCnhx3Pz/gp8BB8+IhBvEdKvHqXkDUQa6xhJW2h17pxcP95KQPXjZ0Hn/SVIO0taXkp5i5GFhYWsQXfhosbxDL47BFgM7H1xD/r162c40zPIli1bMFzSLJeYA7lMUqPVzFFmK7Szk+89Dz8fDt+m1BYka5SPrJD8HEu8DJJskiWI13zzGnA+8iBvieHn4TEWzYqPREjwliCCtxgQEVLaim6m5O9QlVI+FB2ZZKS5eyKl4+ju03NEhxF861BxNEcKnb7tM2rpqU9zwtTUmRfK6sP46HbG5mfSl4vMo0dha2uLtA4dAACVr1+XfYOM9X3U59J8U7Sen58PhIRAq9UiTfK7qinNsUTRD3mjfaKbG/IA2EZFqaIZEsZ8g/joa3RdZNGhlK6bnweL0PfzJL8x8gvVkK8OOfOQkE2S7s2vz6ZsCQQCwX8dYdkRCAQCgUBghLKGsWlK2ScQCARPnsf/sVPApaSSTePyUXQnyl5QII8X5/0eDEUcAtSzdvPj0vn5esgnprCwEGjdGgDgKp2flH6krdQoA7zJ0dBof2S7drAEoAkOVll2KOVnM+etCzQHCY1T5/1H9CNuGTHklMDd736B/YFAlJjOnmWtZSsNhgMlKmSSKXnyIymV2oz+mt0k60Jo48awAGAfEaHyjSEZ4jXpJHt8NCyy7JAM8lY4wlV7QwAAIABJREFU0pDzlhZjM9jzvge8Zp+36NB5qBxjc1HxGnQ6jn9G+IiHBJ3P7sYNAEDMiy8CKPHf0DSTfpD/Az1A1CaSPNre1KW8JQfKbLKYUn9ATc1HALshXceLz4iFZ9u2bQB084cBJc86b/Xl243anY86xvva6Ft/AZ2lqPjCBdmiQ+1t7HjyASO5pT5H3yeIrHvUhdsZiX4o9+WFhSrLDW9F533YeB83Y/eBtzzyUeD0LackkhoaZUCpM5eSxfg/S1nD2GweV0UEAoGgQgjLjkAgEAgEAiOIjx2BQPBs8/g+dmgeHVLvkRqQNL2kjSeLiaS6pQg/FhYWqlnnKeWjqNH4bX1tJlBiuaHjaJ3y2djYIEGKItWK1JE0fpvUgLyTjqRY1UiRh1widamltB4hzTVh2batykJD2krSRvJzSlA+mluC9+0hNBqNXC2V0wNvSaP7nc9tJ1+qRc+GRhwA0FyqM10zHyqPVymTOcBWub3xJV0a2rgxigBYtWsnW0b4+UsKCgpgLs3TQSJBEfsc79wx6uPDa6ZJRnlLDx8VjbfUUD5+fiCSfd4iYyz6mrEobCSLvCWJf+Z4y1AklLjQBFD8NPVcm9Bm3tWMt+hUuXxZV79XXgGgtiBJjzhe/FeXhkjX+zT68KRKdbMC0BclEetyrl1TWX15ny1C37odK1mF6NZWu3tXbkfe54f6PJInY5Y+xZxjUFvN9X2CUvfsQWpqKm5L9WkyahSAkseM6kVdvL2eZYf3OTIWPZCXSz5KIe+jw2/Xvw+apk0BAC9RxdyktCaXtpJS6jOXSv3NB0+fTAkEAoHAOGZlZxEIBAKBQPC0U1RUhNatWxsMPnPv3j1069YNrVu3xiuvvIL9+/ebWCoDkFfKIhAIBE83j96y48XNp8OrcHnLDq99l9Zr9+gBACi6dEkVqYgfd56SkgIAquht/BwSPMXFxWhOKy2llHwOyMLD14/qTep9SbPsFCKtJ+myFoaEQFu/PuykQ0ijTdle0ItQxGsj+XH7hsa3k6ZbFeWOyDGSElI7bNq0CSOlOXueWhpLMsWbAey4lMSCbrYzt59WY6Riqa3OnQN78UX5MCe6pyQLNJmPVJ5TpC6NadAARQBYVJSsoed9Eigliw7NpcTPEUU+CKTBJksRyT5p3rOysgAA6ek6UwqvoSfIcmPM14fWKaX6kAWAj8bGa87J8nJfsrzUlJ4HK3Lo4C2J0rqV1EYu0nbqDsja4RoZqag/DabR8BZWrr9wpufxKaQq9S3klyj5jiW0aAEAKLpfUnnet4Xug77FsE5UlC66mGSVzpQiu9lL904fkkvqW3j4eW6oD+UtO3z0NuqjioqKEL5hA1xcXIDu3XVlSXnsQ0NhaWmJ/Px8lWWH78NJ/qieJJd0HMkfPS+8ZZLvQ62trVHFzQ0AUJX6cnqeqV/gLTuNSKiknqBAapen2Ar+448/olmzZnL0R33mzp0LHx8fTJo0Cf/++y+8vLwQaUBG1IjQ0wKB4NlGWHYEAoFAIHjGiY6Oxr59+zB+/HiD+zUajfwRlJ6eDmdnZ4P51FA0NmOLQCAQPN08essOKceM+Y7wc6IYmVCDlG0JZmYqrR4fQYofV04+LzRenVL9WcjDpDyupPUjEw+tu3HbqUKktpSiSsnWBOn6nM4AloWAhukOkSMASeV2lZSFUYyptJOU8pYc/XVN586wAVCV02yDixYn19OIhp3WR+54E9jxJlb0Xo4JEybgaWPNmjUYZ8wfiaCbTBYZuicuUkr3Jl+53yld11aWAF60QIl1r6+UtpVSfh6OSGXx1yQfihpxcbKGmmSNLDO0nSwyZI3kI/QRfJQskg2yEJHPDsFHT6NySXb4Ger5qFbGrIh8efr+bgBgHR4OALgvadTzGzQAADQ+rzuO5mDJ59rMTtpuK22n3ZGSNr5RbKzueqXt2VK/YRdJBdAOqRxpdeXKlQBg9AXwseIoWQRIjkiO7ytXI6SX0Mbx8fKhvC8K73tlbm6OKvfuqSJV8u1Elg5jvjq8z46xSJG8tZnOk5OTg5cknx2i8PRpWFhYKCw6vKXKmJxRfXlLEq3T/FRUHyqH/hNsbGyQXKMG8gBUpXd7dynl+wPerwy1pdRTl7T5Q5dG8Gbxp4Np06ZhwYIFcp/A4+fnh169emHp0qXIzs7GkSNHHnMNBQKB4MkgLDsCgUAgEDzD7N27F05OTmjTpo3RPJs3b8bYsWMRHR2N/fv3Y9SoUUY/MpXQMDZh2REIBM8mj86yQ7NOk1adFIPGwi4Zm5TBUZEgycxMFdmKn6OExqUTZNkhLSAf1a2oqKjE1YX31eHrRVpAYyMAeKeDuwDiAIs83TVoeGuD3lB13qJDWlBeS09YWlqiFq3w4845vxSV9YOf2ISrt5OTk8FzPilWrVqFd3aPxzigRBh4+MlX+HU+sh5BVrkcAHHQTcTjihIZ8JLS9g25AyN1iWWxIl8LyQfjRm1JMxweroqOxWusyfeGt+iQ5pu0tbxGn6yY5NPDzz1F5VJ+giw4vB8brfP14KOC0X5j0b7oGbNLSAAAxHHR42SfkGa6cGr1JfkkC2VNSXlOYnmrTh3d+aR1erzypahvdhT9TYLEvZlknVwprT9JCw+T6qiJ4XZIlh26pnqShaaoqMholDJqD97iYSyaWVl+fzy8XPDR+PjoZ1ZWVnDt3x9AyWNH3MzPV/VpvG8QHx2O4KOv8ehbcPTRzy8/7tT3Ut/IRWVUT/YUx62/pktaHjdYlydJcHAwdu/ejf3790Or1SIjIwNvvfUWNm7cKOdZtWoVDh48CADo0KEDtFotkpKSTOvrufmLBAKB4FlCWHYEAoFAIHiGmTdvHqKjoxEZGYktW7age/fuig8dAKhXrx6OHj0KALh+/Tq0Wi1q1uQ/TQ1QDN2QX2OLQCAQPOU8fMvOGM6iw2vLaJ2fD4aPnMVNwEFRm8zNzVXjzflZwo2NJ6eU0I9YJRtCjFmgCD5ijyO37ialZBW4CyAdgAbQuOqdiKwN0vEZ9erBCkD+P/+oLDr8bOL6lizZwMRbK0glzk92Qee34vJxM9sPfP//gPeBDf9bj1HcGPzHyY8//oipYdPwDlByjcasVPwM6Ly/FR99ie4FqdQBXVsVQ6me1t8PANBpoVFYrKwPHeOhS16k7O2aAAASJM2+ZPhBjdu35baklCw1vO8EadrJMkKWFd5nho9qRfmpHN4yQPlpOz9/D2ne+frw1lHZksPNIcVbGkiDT8fZ3tXdjbtSBDE7yaJjJbVlY7LcSNeTyKW8C5odt05iXpusbE8QaTontLyuS8l/KYEqGx4OS0tLhRWO7hvB30+678YsMLxliI8KaMxCxG83Zk3Xl6P4gwcRGxuLruPGKcrSarUqnxreQmjM0sTPG2XMyq2f/6Ikg9RduNFOvm/n/RppnayE9yRhrHdImY9cdp7iqGzErFmz4O7ujgEDBuD777/HhAkTsGTJEmg0Gqxdu9aoxUwgEAieJx7fpKICgUAgEAgeKV27dkXXrl0BALNnz5a3N2/eHMHBweUvkEGtYBIIBIJniIf/sUNaM95Sw4+P5sbYq+BUthS9ycbGRtbu8XNO8JF9eC0kQfv52bsBlKhfqXPn563h/UB4SxXtf0FKEwGEAbCGTuPPRwqT7kMLaX6eKxYWqghevFaV/CSKi4tLNNg0NQdt4KPc8ZGG+HpQPs6KUb16dTxJqlatWrJiy6VGIvfJKUVbogh69ajRJMes9rrIYci/XVJeGIAsqYxIKTsFLXKQ8pGFiGSdZJlklixKhHQ6Jym/k2TaYQ11PkAxUVFym1JUNbKgkKWH96HgZ5An2eAjDfJzTPGaf96HiI+6xVuGjM14z0d7o/xkyeGjgFF+qodrok7w0qRhNU5SNcjHzVG6x5FSvVpKPkx0vjgH5YNKTWNz5YrueGk+oz///BMA4OPjg8dNK8bg7+8Py0mTAAA1pWukR65Iq1XNY2TMR4b3yTFmyeEtIcbmGDNm2eGtzLy8GCrvxJo1sn+kra0tUFwsWwj5CJNlWXYIvk/nr4cxhmucRYe6AXos7ehG09xP1Efy/pfUR9KBiVLnSo9GqJRGllrl5wfxsSMQCJ5xhGVHIBAIBAKBYcTHjkAgeMZ5+B87koVC5dvCa89I9UraNn48NVlKIhUJqtrYqCJRGZsVnrTcvHabtIx5eXnIlOa0cKN68eO4y4KfwZ0UzGRVcAewH7o/jB5QWyXIItNBl9SSZqC/e+6cSgvKzy9kZmaGlHv3YG5ujlBp9nQXqTw3agd+XiA+GhyfcvMfeY3xBgCsnLfisUay+vXXXzFpy/sYDajnwyB4h400bjtda71q0o+BUtpSeUCXn3Tp/fu6tsqBTrt7V5lNvjd0OB/xjs5LmmF+ziPaLt1bjfRMpEvz8lS7f1+2hJDGmywrxuZgIs02HcfPJUU+NMZ8NHh/N2OWBaoPXw/ep4i3svK+RbyPEaW0XTYs5ihvGT0mL0kWGv56akvzFYVLFh43KQocRbGjZ54slevWrQMAjBkzBo+TvLw8HPnhBzg6OsJ97FgAekbYrCyV7xXv68K3E2/p4S1ovMWEj4bGW0qMWXh4i46x+aBoP80nRddhbO6wsiw7fH35due3G0Ke2k2yDlpKqWwNd5NSEj7aTiYiycdKNaca9bECgUAgeKoRlh2BQCAQCASGYRBR1wQCwTPNQ/vYCZU0bfIUJ5L2S0P+C6ReIy03b9mhdY5USQtXOz1d1gryWm9eOyhHepK0i/rz6QA6v4jcevUAAC+S6pgq7ialVG8+eho/j41qbgZue03pN4Mywhfv2ySd10k6T4w0zwagjoBFWlXSogJAs+RkWcuZlZWFuwBSU1NRv3VrAEDVGly9SWvJRyyjOpK6WfqTc3Q0NrnNw4dpNHgPKPF7osskSw3VjTSwJEN8hDx5onM3KZXmyZAvmkw3TaTj7+vaoxhAAcCk8nOkVJ7Lhc7LRdRTwVucIpWnZZwrQFFRkSpyIFlmeH80XsPN++AYi7JlDF5DzluKyJeInjWSSUr5KG60zs+TQjJMlhZK6VmtEaeb20RDlgkppVhqdD5jkRibSBYeug7eIkH383H5oi1ZskRxPooKV1xcjMubNsn1trOzA9LS5Hrzc4Xx8xzxESmNWfzKYwHRh+pFckjl0jrt5/teus8kP9TeJA+8TxhvESR4yxRff0P7m2ZkoKCgALeke813zaq/Gul5dpT8NN2k1I63fvP+jlJBTPqPS5TusZMRf6hnHjGMTSAQPOMIy45AIBAIBALDiI8dgUDwjFPqxw6FrzQJT08AQPpffwEoUcbb3JN+JHNnzJVSacg39aWkd2TK3bD39lZpMXn/AX78Oj+niL5vjy1NXUNT72RK6VUplQJ1gfKRVq8Sl9L1UIXzubQQCJU0+V0/Qgk0IXUxlz9Dqs6rr+rq3qaNKvKSMa097y9RVFQkF2+bJF1OirQhWkopMhHvV0L10UrpiKFYNgJAR088SmJiYlBL+m0RKf2gicxJqOjeZemSAmldI2lqLWKl/Wek1JkadR5XUAadVZfES22VB3Q9WyKTdCusJUuMhXQvQZO2k4wUG0mpIEmYSfSpXKt27XRt6+NTpkXGWDQt4mHPm8Fr1PlIhsY07/zxfP34aGG8jBuLumUsKh1fHp+ft3xQ+tn/t/fmUVJV5/r/U/TA0C3QSDczdFQGRQmKOERFkpg45EbiGGNMnJUgCElWcrOS+7vLDDd3SGKM8asmFxKjJmqiiahXicEIcTnFAZBBZNBGbBBooYEe6K7urt8fZz+nqp7q3VXdXT1U837W6rX7VJ1hn332OXX2++z3fb/zHQDA8OHDMX36dNxxxx1tNUe7GTEi6M1jx44FEFc+1O+QZU1NTVL9qHhpO/qisGULKjJU9lTZ4XG1vno9dHsqQbqeKlA+fP0ssX+qKx8F3uHbt6OpqQlFSFYWY65eGwHU1QVr73cKYV1dHaZ/8YsAUtN8UeDl8crarLlhGIbRU5iyYxiGYRhG65iyYxhGjtPmYGfFihXt3uGLzkJHK9hEZ6grHCcruvnOFW6R86kLVq3CEBdRadiwIIoWrYic780IS3v3BjIFrYX0Kyl1uTrUirp//37kl5cDAMaczgq6UvMA+fIE+eZx03zoRILQ7FcHzH4EQB6w4jLERQVCsyD9QVwOh8p/uI/vvz+0shYXFwNIjWBF2D7qXwEAeccEDjCjnUG0kPXmebEdeH6c2K5+MR3oE+3hgQcewLlf/SoAoIzXotyV9JFh3V4PivVO2eHv8cdd1LTIye6Db7pGnsEdTHHlq0HxlpPe7nfXag+w4kigsib5cLzkY9jsrBfbsiIoaquSt2PTFa5fH147WsgT86ccHB44VpXKdoM/oiwaJ1MLuA9f1K10+VbUj4x9jRZ+9dnRCIjqfzZ48OCkkr4q/F7rw/2y1OhubFfWl4oJ68WSn/NZUlFRga5guLumel7qG8X6qE8Sl1XJ8SlqvuuuSki6/Dusp/qM6TNVt9N6JEaOBFIVPP0+nW+RKnp63JaWlpQgiQyiOCQaTfEVY7tT0WHJeo4cORIfrlyJwsJC7E04790u2t/FF1/caj37FBagwDCMHMeUHcMwDMMwWseUHcMwcpysDnbuuecepotJDVZGM7VTQHZL9vDC1atTrN0+/wONRMV57czaze1pBUy04k1mpJ2hUvJzVV504recR2jxoh8HlR0qNVwnz23rU3bqkj+mdT82eHBoTSeae0Lnv2skpObmZqCyEnV1daiYGEg4Q915lbp6R1gvyhF1ycsxdz7Z9QhJ5rVIJNRcACQkyHClhFOqdd+zqhN27UIkEsHmsmD2/KSn3RfshOc/H5Qffz55QxeFCTuQZMFU8S60GKt/kyPm2pIJ1kdu2YL+/ftjOOIWcVq0w20SFJNyRp9zuZGKnKq2z0WXqt2+PdzOl0cl8fvdLvfSdNbXlZWunv127PDmWVFfCo16ptHfqABQ6VF1UfenubFUEdLj8Tiaf0bbVZUGjSrGeiRGMgTianC2WLJkCQBg8uTJScdV5YOfa/3UJ0p9j1QBSrwuDaNHox7x22XKAfqmpaLPEsL2pGKm0fXaUlhGXHEFgNTUanwkDnnnnXA/VPR8Pkc+ny/fei0tLSmpzMa89x4aGxsRjUZToghqdEH+lrDU66L3269//WvcdNNNrdbJMAzD6B2YsmMYhmEYRuuYsmMYRo6TtcHOi5EIpiFu9B6iKzizHq3xmpS+pKgoVCRYpovcRGsy19fIRbTa7d+/H8MnTQqi5XzcHVCt8zrRW0NxkTrPsvrqcPtSBHJIPySrOjxxVVJcSZ+aoqIib04Vn38F20etxLFYDJFNm1BXV4c906cnVXO0q3fEmYMbo8nVZPXGoGu47777MNX9zzrF3EEjbFMqHXVJizhy69bQQpyXl4fSvXsRjUax2kXCmnh/sF7RSrcB+wD9lAoSygiCCH2jgSJXkaJaWU/9tlxfirhOH3V9ffDgwSkWYfVdaWpqwkdHHw0AKDvH7a88+XhDnW/S/qYmb9Sq1izs7OJhWiF3vmOeCcoP24jcphZsX54Xn5rIZfry0DeG2/PepM8E+6gqXxrVi+ot/dd4PEIFQuF6LHl8lsXnnQcA2OTWn9TJnCklJSUAUvMeaV4i4vNBUd+jxO9r3D3MR9cgBAH/qKBMqq72KnfE5+OjCpheF82Xk8iuhx9GaWkpCj/9aQDx34Iw1dqgQeH+9FmvSpPWL12/b2pqwiAXdW3Pxz4WnEOCrw7rzWX1nWKp+YR8/Yw+WX0aG+wYhpHjmLJjGIZhGEbrWIACwzBynKwNdoqkVBeQqCg6VAqO2rYttB768uMQWgN9UclojaTV7eDBg2hyVvMSWvNp5das99VS7pfvaZ5UaYMWL65PuYFm9QmIqzqjkRqiS6OdiT9KJBJJaY9089t92chZ5uXlYcjatWhsbMQuBFbO2tMDb6sij6ITzn9v9cidh5H0EgkznbtKsInytmxBfn4+ipFqGaalNi8vD+OqqtDQ0ID9CCL31Z9wAgDgOBd8rYh9wvnIYAiCazUQgQpCBUf9s9i5SxO2A0JFZqLzAYpEIilRn1TByM/Pj79H7JEymlSgf//+KT4bqhQkKjLh3cMdOON0zC3X19en+MBk2sc0r4puR5XVlyNK/en0PPi5qpmqLBFtl8R+AKT6AWrJ3jfJXctK9/mYDio8jCjJZ5Q+49RXRJUezZml1zsvLw9YuRIFBQWo/sQngs/eegtHHnkkihF/Rvr8+3yKju/ZQbT9NUpc4nXm/ctHIW+j0sLCFJVe66lqttZPfZ70/j906BCOfPttNDY2or6+3nu/+HzCFD0/rs/rbBiGYfReTNkxDMMwDKN1bBqbYRg5TqcHO8yrQyM3n4kalGzwxo0oKChAPgLr2UDErWhq9aV1Tq1vOo/cl2siMRv5NE6ppqLDilKCYoVpTa9wJRUXUu5KWvVprqRZXpUafl8OoAWBYlCAuN8H198QFLX0aXIf0wpa4eb+T9+3z2vl1MhWanXXyEpqlQWAmjfeQF1dHfqfdVbSMXh6tX/9K6qrqzET2eWee+4BEEStSnSdSYR9iE121KBBKSqgzsVXS3pBQQEKNm7E7t27sXrWLADAGa7tk3INtSC4K4Yi3ldYIY0Op33I7WeMW7/CRfhq2bo1xUchsc9P2r0bsVgMjc7HKHTtKkg+/IEDB8L8Hrt27QraxmV6p1Lw7LPPcmvc5sqYy2kVcYrWvXffHfgkPP986PdGZe1IF/mNPif8Xu9B4lMT2ffUAq5KD6O2+aKV+fL10BeI7an9gNupcqX5XEjoiudUvjEb0CF+8YtfAABmzgzuFJ4/lS6i0cB8PiW+6GyJz4L+L70UXi/6mhBtz0yimSWu51P69BnS2vL+FSswZswY7HARIMt3705RYvT46XyIdH39niXbj3lz1EdHf0tYH312ajQ/fs7loqIi/PKXvwQALFiwoNW65zw22DEMI8cxZccwDMMwjNaxwY5hGDlOpwc7nOuuriuR117DoEGDUIRU6xlLzYaeUjlnVVPrrVpn1erJnB21tbWtJPxxpEgortzsvq5KXr0onHDuSiaR0KhtWlYAOISgpbfJ5wB2uwajIMRqkWM//BD5+flobm72Ws953mrFVPVD/Re0/ZqamhB79VUcOnQILWefHazbyvGyCRWFAQMG+NLXpJCfn5/iw0E1j5ZynptGVxowYADwz39i165dqPj85wEA5ZsTDnwIgULTiPg11nBS7OS18jlxJ1JKtc75jVUjiJZ1ZFVVSv6UlpYWinyYzvq4vhZx+6ufMgVHAHj+9tuxciVDy/lhO7Jv3XLBnOCfv/41Zd0ZM2YEVXcKBJWC0aODRhjjcvZQ+dH8I8Tn08M+qLmweH3Uh4Xbs8x3finsge+7csSGoNXYj9QHxKfsaNl/jXO0muscucq1hTKDx9PrS9huVFk1cqSW2h6E/Z/Xi8qZzzdJyTT6mW979bnx5Wfq168fBidES0yn6PgUKF9UNvXd0fudz0T+xmheIt0Pf6u4Hyqb3B/3w+MVFBSkqHaGYRhG78KUHcMwDMMwWqcFFo3NMIycptODHQoeM2Ox0F+AuQd8EZg0R4NmB+eyKhJc9llNCZWNhoYGxJyfQoSKjES6Ul+bfRL5i5S77wt1eypHDFNGq39i1LUogBoAqxO225FU4MNnngmthbSejx49Gi0tLSntp5GmVNmhP4NGGqJ1Uq8Lv09q/5dfRkNDAwpnzw7WOfdclASVQDagbwMzzNPSDfhnTNCXpaGhITw3WlrVgqu+C9w/FYtYLIbdr76K6upqDDn33OA7XitCg6365rDTq5PR0OT1wzw9bj9lbrsX3f0xcdeuJDWSQlGYX0h8gSa6z6u/8Q2cCGDjPfekRI9K9N1R1bUt3njjDQDAJ5yCsnfvXgBxn6D33w+0FCo95eXlAIBS55fEeviiY7Fvad4cbvf2yJFJ9WGTH+vKMvre8T5z9+Hu4wInm/qKCgDxKGTa1zVPDI9Ly334vXte0HdnyZIlAIDrr78emcD9HDhwIKkeqnj5orRRJVDV26eU+aLp+fA9S9LltUmn8Pii3Pmi+un+0yk8vu/VB4ftQaVL+51GQ1Qlh+2v/ZPb8beFZX19fZco3r0Km8ZmGEaOY8qOYRiGYRitY4MdwzBynKwOdtSKqvPiiSoziT4jQGokIlpH1UrKUhUOLqt1v7ejShZRK6lP2aJiRpVDlRufLw/RiGGtWWXvvPNOAMCtt97ajjNLZdSoUQDiSguPmSmJltXEZVpmee6M9sVlHmfYsGEAUtugu6ES8+6772JgmnWVsWPHhj4wes2mT58OLF2atP7ll18eKjV/Fb+d8847D0CqRZt9jPWsrAziLH700UcAgHHjxgEAjjrqKAAIfTP03lcfHFUoOov6tPC4GvVM7yU9T6W1/E9tMX78eABx3ySqrDy+tgOfUarQcFl9cIhPTdDz0PbOFF9UNB8dVTfSKTvqk5MOVQ6pknOZvzGq7Oh14Pmw/yT5gSJ+Xevq6kI1sc9igx3DMHKcTr9pzMzStKau4pWXXkJzczOmupDKOiNJfcx1ppLMOkM5vcgZyrrclXRm1wgDewA0IXB8fz0+RYn72/n00zkxDaI7UudxBqD+ruq1yjacuVSyH8G1IpwhxgPrFEV2pqGynkabcCfAKZIMNa1wml6Ejc3SbVdQlXzYmlbOJRENB9+bmbJzJwBguxsE8/YKp69NdyVPyl2DMudLUO2CQKBKIou0k93u2pWd06ndGIZhGIbRS8iqWVtzFWhEIV/2bp/Pjs5z9yk6On+bVjxaV9VHqDcxaNCglNwNtBSqkqO5LDQnhvpNqFKmvlDp5tcXFBRA4+S1V4HxUVZWBiCuxGRquWW9qF7x2vLcaanl99XVwVsxz51z+ROjWB2aGBGQAAAgAElEQVTs+Gl0iFgsluJntXfv3nYPKEeNGhWer88/LpFp06aFviRU1mih1lxMLNVPjlHvqBC99957AOLtPGnSJADASOeD4/Mp4XXTe7mz0ALP/bK+2vfVgs9nTCGSydRqf++99wKI59ehwsXrW+UGYcyPxH5InyFeR809pss+1Tddnpr2RjvzkW49XxQ4ny9Qunr61k+3f37Pfsznli+PkB6Xz0z2H17HgwcPJi2XlJSEvzO/+tWvAAA333xzq+eWs5iyYxhGjnPY+OxUvPlmOJhIDDtaNWUKgLjBmEZ6+qYnxhkAgFpn+R0d+C2jhG+oVHaQvEFjVfBb0QCgoi6ebLXhueey9oLXleS/+Sai0Siip57a5ccavHFjytTDxKR+Y+CfbtQZjtiyBQcPHkTjiSciBiDSiECdoYRChUajVkx0JWUIyoGuTzQ6JejAnj1pX0aBhIBHPK4G1XDUr1wZviS3xkDntF/ovPsLXacuO+EElAHY8uKL3m17GjZ1OHlME7tCltkMnRN0QqrfeQcAUPY/QeCMc38aTO/Dub1bwTaMLiMGi8ZmGEZOk5XBDjNIH3/88QBSIwipMuNTFPRztWoSfWHULOtq5ad1jtY6je7WE0QikZTIQD7fJPVH0AhcbC9aoamo0crN9tHs7Ho91JqsuUmAzis7v/vd7wAAJ5xwQtIxiOZHUbVKlQBeY5Y8VyoWe/YEIwW2BS2ynMvPNuvKXBmJSo7PF4ERDDOhuLjYq85lwpFHHhlao6k00BdB7x1tf1rK2W5UdPbt2wcAWL16NQBgijMiMGqbRh0j7IvZgvXw7Z/no9HaVB1W0lnt6duj+2d7cZkKD+vJfsr7iqX2f92f777w3dPpfGKIz0emo4qOki5fTqbr+5SZTD9vLc8VEO8v6qtDRZT3Ca/30KFDw3VGjBjR5rnnLKbsGIaR4xw2yo4PTluhAbmECg3DBTslZ72z2m/7v/9DVVUV3kD8h3TcuHEY++lPA4hHxiWVCNx16o4/Hlt+/nMA2Zuy053Uv/ZaMFBwIX77IhUIrtXAGgBrEJf1qNhwmWNNdh5V9dyLAV13/BpMMg3PPRcMbOd9NviA8sae5MOno5xq42dc6fJklrlOvmfKFPQD0PLWWxnusfuYuns3ACDqpjkWqjOdJ5FrGJY8WxV5yZUT21zLMAzDMIxeTlYGOzrvXZUdWsnUaqo+KGpV9s2vV2umKju+XB+sh/ohtIeGhoaUHBi09qVDfZNYH1pr1e9Cs3WrqqFWVO6HVkeuly4ru+aiUGtnYju3x7emNZiXRXP76H41mhfrrH2J+yFU8Wgx57XhNWcbMJpYYlQs9dfIFs3NzV6VjufDemcyEI7FYikWb91vJgwYMCD0raECpv51eh1Y+qKG7XaDlXXr1iUdi9HaVDUkvC6dnabI/ECq3voURJIuOlxiHqjW0HuNCiKVGvrwUEGkUsB+SnWAPiHqc0IljfXmcjrfFb2HSaY+O+ny7Ch6H3c0Cpz61vjq6TtfXz4h9WPU3w4uq6LD60lfK0ZzHDBgQLgtr3Gfw5QdwzBynMNG2aHPSSGAegTG+SbEjfIlnEV0sisp9WwOivJ/BOUmz/7feeKJ4MXbhfAle2DTnXMFXquB9NkhvnBwVF4kahrDu9E/6+j2VoT7lT6YTtkZ46YG4kvug6+6ckbwYoaCYCAwdUPSbnslbOpQFeNNRFUtmryc7WiBsbeDMtK+yNOG0fewwY5hGDlOVgY7qgio9V2tbZqHR/PL+LJx+6zZOi9flZDOqhGJlJSUhFZ4qgOMTJXOn8WXY8Q3r57r0aqo66vvji9PDuvLktZnnZ+uVmCN4tbc3NxpPydaP7kfWlKJKgj8nm3AklDZYR1pKadFlm3B6G/0feB69Dnp378/uioAeDQaTRuJkPWgxbgtEveRSeADH83NzWH70GeIyojWT9VSwuuo+Wh27AhGixs2BCMrKhpjxoxJ2h+3V1W4oxM9qeSxn6kfnKrHqgBpfyTpcnbxnqJPDpepzDCgBNuBPmMatU37r/b3xIAdicu+Z6ZPTc80ils69Jmh/SXTKGy+730+RqqA+qKsqWKjiq9GAFVljvD+4P3J9m9sbAz33dM5u7oMC1BgGEaO00efznHqJk9GPgBOMOBUJQ4Twle0oVKKH0bRmgyPJ8s7/vhHNP3gB5ltbPQosRdeABYsQPPq1aiNAkWq5OjFZYIeWj2dbw1ztQxZuzac9pIJZ3/5y8E/VGREVfBNszti2jQAQAlVyfNdSUWn3g1gxIlowLFBuLamzb1P4ynQf4pkWZQdNtWEz30OALDvhRc6dXyqaCV6zQ3DMAzDyCmy6rNDJUAVHF+WcN98erX6qjVZfV9ohePxaUXtijDFiSF/Ncqc+o/wO81RorkfWGpuEPLhhx8mLU+YEMQ6ZkQthe2nvk88rvrwsN18PlekoKCgw1HL7rzzTgDAGWec0WadVdFhHame0eKtuYm0jTV6Fa+bRuGiOsf9dtTC3RotLS2hDwaP7/M7a898/8T7IRt9vKWlJeWeUT+0dNG22Mc4uON1YN/dunUrgLiioe2hPlydhdeZ9xbvFb3+mrPKp+yoiqrwvNnfVGlUxYD1YTtwe9aP7cHttX4sfTnHfFH/iG+9TPPkaH1UIfH5/WXqw+Pz2fF9r/tXpYntz/uc0fCoarN9eJ15fahY8jpxv7w/Dh06FO6bff6uu+4CAMyfPz+jc+312DQ2wzBynD6v7Ax4+23U1tbiIIIftrzTTwcQz6MTGo6Zy4TWb67QTstuZqEKjN5MEwLLfpHLkxNzP/TsCpzRUej6SoEr2YVY6uTJD1wY5nHbtiV9Hj3xRIwAMMaX3MkdmC48ODmQcNh3w+2oRvKL55yi86hbfiYodrvD16xd2+oAvTeQkmdHfWf48uVsDxF37hPdtdhxyikA4k14xPbtHarHq796JfinsrLtFQ2jBzl06BBmzZoVBtC59NJL8f3vfz9pndtvvx2LFy9Gfn4+SktL8Zvf/CY0nLWJDXYMw8hxsjLYoVVRo4z5rHLpslf7InT51qP1nFZQjdKWGIWss9lUmpubw/OjFZDWY/VbAAJfEfVF0nw/ep6h34L7nqoGLYclJSUAkJJYMl2+Ir7Ysr56vdSHR3156uvrO+z/xGP6IskRVe1oQeU11txBXJ+KEy2yXNZ8Maomsh4atS0b5Ofnh5b8RLWupqYmPL+qqqqsO9d3BF5XKky8Tqx3Oks7UR8e+iJRQVOlS/tTOgWlo1BxUT+/dL4reu8oS5YE2YWnTp0KIFWx8uUco8LAe0yVHh6X/Zj19flOKemiq/nON9Moba35Y5ace25Qd7fOgZUrU5TH9iqnmUaJ85UafU39OzXaHdufn6fzHTx06FCK2tbZXGQdoX///vj73/+O4uJiRKNRnHnmmTj//PNx2mmnheuceOKJeP311zFo0CDcc889+Pa3v41HHnkk/c5tsGMYRo7T55UdpW7FCjQ3N+Mggh/Euk99KvjCWfHLmF+jInm72v2Z7b955cqUH0gjt4jOmIF9992HHS66mc83V/PnUNUbvnEjmpub0Th1KvIRF1woUlS7F+NtAIYDqPrb3wAAKz4TJMYpfSJYj9vxOD4BJ1Q9KD0td6VTOWJO0XndfTxw7VrPGfUeIhwBasQ7vnRpaDrXOIUuqmK5u19L3fp7nIP5IJdENR283U/61AwAwI4Hn8xoO8PoCSKRSDhgi0ajSUFRyCc/+cnw/9NOOw0PPvhgt9bRMAyjp8jKYEcjHmneHVqH+fJPa6bOl/dl/1bU74HLtPpTCeH2PK76B3RkCk9dXV14nrS6st60atOyp8oKI/qwPTTfDRUoVSNUYdFBlFo/+T2P42svjeqmx+P2bNeWlpYO+1RoxD6tO89d1SZaULke25br83MqCbSQqx+UWnjZxtyO15JtUlhYiPoOnWmgXrSnb1VXV6OsrAzZ9zDzoz5SGiGQ7aj5idRXxKcM8B7hftiHeF19dHXCXeYBIjy/lDxCsp0vGptGfeMLp6rdWqqKSsWLsD+qCqs+Or6oZ/q573r5FJJ0ioqv/ySS+JnvuOny6aRTgnS7dPthu/E6sZ1Zan/X3GT6/BowYEB4TF4r9vXuprm5GTNmzMCWLVtwyy234FSXbqE1lixZgvPPP9/7fRIWjc0wjBznsFN2lNirr2LgwIHYheCFZfPkyQCAoVuC72lV39Pq1kZfZsg776CmpgYDEZ+OxZef/Px81CF5YBpB8gBaAoYh4v7h+/66Bx5ImvLSb+VK5OfnYz+Cl7YDrjzC+ZmFPjuy3xJ2TgZVqwiKmOvDVHT6r1mT1TDsXUnMSSsRKjhUeNSfiSUbm83vXBF4/xY51avWqXXvpVG3mrcEjbf+mGPaVe/DGXp/sF9umzULNQCKe2G0v75IXl4eVq9ejerqalx00UVYt24djj/++JT1HnzwQbz++utYuXJlZju2aWyGYeQ4WRnsqC+IKjaqLPjwWS191ktaU0tLS5OOr8qFWi25P41gxBfZtti/f39KtDPNiaERlXgcqgiqXmg7qbWZWe5VxVDlinC/9GGiQqMKlJZUdrgeLZSJUdt0znumqKrHUjOW67VmW7FNtU/4LLUaDYvHYx/huWof0OhNvIaMlqVtwmX6/HC/AwcORNuZWQKVYdSoUUnHJe2NXpUJifef5pfx3XOE9VCV1qcEcH+8HurfpopApr4o2YLXTX259J4lvnppdDc9T7aL9nuerypd7Fe6H703ffXy5UXyKSS+88r0OJnQ1rqaoybT/D/p6q39itdVfdI0TxdnBfB+1tkAqgC1Fm2zPeHmu4KhQ4di9uzZWLZsWcpgZ/ny5fiP//gPrFy5Mm3uqBAb7BiGkeMc9sqOMnzjRjQ2NqIFwYt2NeI/Yjt37uzRuhm5RcMLL6CgoAAbnJMw/UcydP8KOfjyy4HqeNJJAIL8PYkD+T0uX05pcpC3MLBgLvjoKDyVcjmn0C+JJ0elh3IC5S86NlERcm1f5N5Dj3HR2ratWtVmPWJsOwn/bqTCS6MB9GwGVNezZ88eFBQUYOjQoaivr8fy5cvxr//6r0nrrFq1CjfffDOWLVsWJlk2DMM4HMjKYEezerP0zSMn6bJjq9VUfYHUqq85LvQ4qvDQqkprHufNc/9cj8oNI0px8KNZ11Up0YhhrC/r6YtMpvVkbhK2H9tF5/H72lt9grQ+auWnFVN9dxobGzvss6NKCI+pvgtsG1qy1UKt11bz6XA9qmy00Oq5qgVZfYa4naqV6oujKhi3Y5/q378/hnnaJC8vL8W/jEqP7/xJOot9IgUFBSl9yqfo6Hp63qrIpTs+r4svgqCSzTxHmcBnB89PFRf1sVE0ep9GTUtU+oB4f1WlR585vmei4nuGqm+NXle9j3zKjS/vDuut901rtPWd+iH6fN3SRfb0zSLQZ64qizyuRsfT3zJu19r9r8/hjBWTLLJz505cffXVaG5uRktLCy6//HL8y7/8C/793/8dJ598Mi688EJ861vfQk1NDS677DIAwPjx4/HEE0+k33kLTNkxDCOnMWXHMLqYve6FYi/iyQxZtoeiVataDY3dvGEDYrEYdiL55TQP/pfE3g6z2kxwyk6Eoej0XZiKDmUElRU4tmpM/rzEKTx1EycCAJq3qYRktJeNzzyDQ4cOofyiiwDEowfuPe447AVwjKljXca0adOwqhWV8gc/+EH4//Lly1O+zwgLUGAYRo6TlcGOWtNozUz3ouXzC+ALHedHq3VSra1qHdTobrp/ohY5rTfVgaqqqqRltfLRL2Tv3iCJI62JjETF43A99QvgcdUvxec3oPP8VUmiusD11Gqtvknqp+JTfgoKCjqcB2XhwoUAgKeeeiqpLmoNpaVdr4X61PAaqPLCa8S2Zh/hfjXXkc+/SxUMHlfzdfj6ENUw1kdzGakPDFXD0aOD+VeqUqpqqD5Nvqhi2s6q4vnWS2f5T6cocH3eA4xEqDlI9HjdrewQjRrn88lSNGKhfq7KjpYabS3TfEbplA6f74rPf8anFPoUIY3Ol4nSF4vF0vr+aL19vmuZRm/z/SbpeegzW+83fWYn7sd3b991110AgPnz5yOnMZ8dwzByHFN2DMPoNWwYFkz6E1cbFNIhhMrOECm5wWhZjxZpRm2jr09d8uo73HEjldSUjI7y3p//jGHDhqF29mwAqfmoDMMwDKM7ycpgh5Ytn1VYlQJayTQCj1qdNW+PKj+ao4KlRh1TK6BGH9M51rT2UdFh2GH6GzAamkah49QkKjxqfddcGpqHh745tC7SUkirMffDemi2dq5PVYOltidVDn7O66PXUa9HeyIw+eAx1HdHFRqNluazZLNObFta4HkNVSXzqYKE565tqdZbVXSIHo99hPVPjGyXiOYPYtQozYGk+Pza9HyI+ujw/FVZ0IiKrK9PPfW1AyNTsVQ1V4/fW9Dz8kVqZLvQ94pKnvrXUaXmPav5oDQqoC8vjU8NJ3pdM1XKfPvxRdD05ehS36PWzqE1fP3PV0/feabzf9Tjab9LybckvxX6HGloaAhVPM391dU5o7oNU3YMw8hxTNkxDKPH2OJe+o9zy2cM8qzIWWTqo6OKDrfnyxm3c8pOrXPNoX7Dzbnb5CDuRjZgG3/gpmhO2LWr5ypjtB8b7BiGkeNkZbBDyxat3+pDopF21A/Bl6NCfXR80dRofdd58zrvmqh1mlAdYJZ1KjVUQtQ6zXqob5HmalBrrfpLcP4+24f1Y324P1qRqSzRaqz703bzWS+5Hdub9SCtWbU1p097ucg5L//lL39JqgPPnXXVPC4a4U/z86hVVefYq0VWI81ppnT60LDNfbmjNNeRRqfy5U5SnwT1q/LlgiJ6XsQXRas1X4PE81XLOtub56M+UD6VT/s0FSqNYpUNlbAr8LUX+4mi+Z303qUqzPW0nzFKnT5DSHt9mHxKhn6ezgdG+5Wq1Ko0dTRPkt4/Pp+ddOeR7vj6TOR1UN8jn88bt9frW1dXl/JM1N+1nMcCFBiGkeOYsmMYRo9B4aWQ0srJrmRUNfraMFga8+rQEURn90Wl5PfOR2ezWxyxI3DeKZCACc2eQY3Rfsa4cnSbaxmGYRhG15KVwQ6t67RwaSQrVRZ0XrbO+9aoYbQm+5QftcKmi5Sl/hOsP3106HNDqzQVHbWyq/VRI4Qxd4MqLJoXSH1vNO8PFSLf/HlCiyL3q6qHqhq6P59FMlGh80Wl6ii0mGs0JPUtUTVOI9Lx2voysauvDpUKXiO2tfot8dprnhnCzzVfENuJln0eTxUb9hUm+aOlX3MkaXv4fF/U0u1bn/Xkdr5oc+mibXE7tj/7MtuN56f+fD2t7KiKqgqfljfccEOb+1Flhp+zf9GXR31MuB6VtI4qYD7Fw6fkpNtO1WjWg+3kU/p8anIiiVHZ9JnsywvkOw9fDjU9Pz0PVbf1vlRfOJ4Pzz/xvtSZDL5cRjlLumlsZjI1DKOXY48pw+jjHJwwAUA8w/2o7dt7rjLCFGdgWO1CU0+nkjPdlZQHOAbQYGkce6uSQ0cRbjcoqTC6kI9dfDGAuDhH1W6Qu0Y9E1zc6DA22DEMI8fJymNq3rx5AIC//vWvwU6dpUutfL552LT+0prW2rzoxO+Zs4NWQVpVVclR67UqG1Q+1MeG1mkqO1RK0lnV1WqoJa28ikYWYn1oVVbrMdUP9V3iflh/jSDFdtVIYD6rJ+H6DQ0N3nNoL/Td+dOf/gQgNZ+JWrrVV0frqgqCXmPulxZpzX+jll36Rakfk++4qtRQveNypQtpTMsw98v1eM3Usu1TdHxKiS//TiLRaDRFoVILPb/X3EtaP40uxmVfXhOiubG6G7YTlTf2D31G8Pt0aD4d9l8u87r7FI1092CmZKro6Pq6rMqO+kfyfPSZov2qNRLXUd+z9voWEZ/Pjt4P6i/K+0/ro89kPkf43Ej09dE2S3xe9gnSDXYGtvGdYRhGL8BsMobRV5k8GU0Apga2AcQCEQUVPVWfNhi2LXDK2edUqJJy9wUdPphPRx2lqdz4ZldS6XE+PtztmtJAdxi6aVMHamu0BRUdqmiN7kWZyqL96BiGYRjdSVZ/dzSvi0baUmu15qDg99wPlR2NiMVlbkfrnFoDuR+NlKW+LNxvqXsBotVSIw7RGuuLyKVKFq26GvWM6gjPg8fjcfg516fVXNUCtg+Px/XY3lSmeHyetx6XllbuV69XorV/0aJFyCaXXXYZAOCPf/wjgPg1y1QhUKWD15Rtoz4T6jelEQJ9eTZ811zXS5cTigqPT9HQqFCqzPgUktZU1GTX+zjV1dUpkQHZN3wKkeYOUSXH5y/nyzzvi1LX3bCf6LOC98bOnTvb3J7ny/bRXFa+vET6TFFFwpf/SUkXdc0XzcznG+NTdDR/VWf8UWpra1N8bbQ+vqiCJJ2vDlE/UlV2tNTj83x5/tpfotFoiq8plfmFCxemaYkcwaKxGYaR45iRzTD6GPumBw4vs6lqOFN7pK719XsTDLpW8pr7Z6IrRaEJ5QNS4Ur6/HD2GZUf97JWGAhHONkdaPOMGQCAmpUrO1plwzHywguTltndaqWsnjIF9QD6AXivtDS8tONduHejl2F5dgzDyHGyOtihFZ1WTVo5Wao1k8oMl9W/gtZVtb7Rqsf1fBGeaM2jNU6t95qlXiNSqf+CzsVmPajgqIVP0VwqRCOBadQ5jY7G86YFUa3GtLqz3YlaUdVaq98TzWnTFVx++eUAgMceewxA/NzUN4aoosG+opZXonPztW3Z9j4FSTOp+/y3fNd+2LBhSefl67s+5cZn6dfPM8ntsX79ekzgdDEX/e2DDz4AEG8/9iHWm32JSg5hPiL1EWJf573Be92X/6in0TwsfJbNnTu3ze00OpdGpkwXFc93HRWfj1a6vDB6fvqs8MHzYT/V/sr7gGgUuY6QGKVNaa/vUeI+Af995lOGeP5UhNXnj9c5EomktEWficJGbLBjGEaOY8qOYfQx6OZCX4nCLUG5OwdeWD7GgAEuQEQ4tpogJRUfygcVrnSKTa37nK+hhfT5KQ+KiIvWNmZNUO7qXLUNxGc6UVTT7pYoNBYi+PGZgLhYt8EFnjnGhf43DMMwjGyQ1cEOrdb0fdEobLSA0UrMzzXCjfro0ArvUyRolWdJa6v6wnA/rIcqLaqs6Lxwon4eml+BqBVV/R5UrWB9ef6q+GjuB67H49LaqOfr84/Q/WhkJVVN9nbDS8gll1wCAFi6dCmAeJupXxbrqGogoaKgCo5aqNmm2ld9io3O7VefGu5H89NwPaqJ/FzvBcXXh1QlTVQ/08U3q6ysDI8/ZcqUpP3wGlPZYL14T7O9ta9qfhn2WW0Pnq8+C7RduxvWW/MxpcMXzc23f1W7M/VZ8kUVU0Ut0yhsvlxh3K/6qOizRlX27vK5SueTRLReWl/1udPteL78bTokyWYTZyXo74EqPTmPKTuGYeQ4puwYRh8jf+tW5OXlYSeCaWYHnF/Ku0uWYM+ePW1vDOCL3/xm0vKrbmphj8CQXuWupKLDPDp08nHqVYVTdHiWoaAT2GFQSNnBbf/2a845qI0kmIbjlFPCHDkxxH1wBrz8MgCg7tlnUVNTg90IpkfWffKTAOLXgJesFC5acT5QNhShX9UxO7q2+kYHsQAFhmHkOFkd7DBSF/0ufBFu1Pqp1l+dj87PqRz5oolxfVpN6XdA1NdGI2vxc/Xh4Xlo1DWin2ukLT0OS43EpFHqNBKSqhdEfXM0khL365tLrlbdxBwSQNy6efPNN7e6fVcwZ84cAMDTTz8NIDWPhy7z2lOBoLLjy5iuCo5GC9M+oEoK0b6jqphannmtmMeHfdTn76UWfe0r3E59X/bt2wcg8M8Z5z677rrroPzyl78EEG+v1izle/fuDS3Zes+xXpojS/uUqrWqrqriU5JSi66Byh/rx3uM7ZeOG264AQCwfPlyAKnXQ/0TWarSoFHdVDFURcPne6P9I50PjH5P5Y7nn+j7lvyUSd1XW/ttD5n4vKTztfFFTyQ+HyfN56XXo7VogrzG+vvVZzBlxzCMHMeUHcPo42y//3585StfSbve+TfeCAAY4/Ly0JniQvc5AKx59tlsVy+JbeOCodkYfsCoa5QFqMw4Xxu4IGoVThUY7AImDHUvsZtdAAZuVubW27J8c/CPTE8y/FBk00lavld7mmao7PBSRiYA+BDB6Gkiwn5W4g6Q6zHZSj7/eQDAarc8PU0wiF6PDXYMw8hxumSwoxGJaA2mFdc3T12txelyS2j+GrUScz3u1xcxSK373K9mU9cocUT9Q3w5LNTq6/P3IBrRivVQvwnN7u3zC/BZcVXJUYWnK6OwpeOCCy4AADzyyCMA4m3AqGCMFqYWXbYx21DzoPjUOe1bOrdflR3No6P74/fqu0NlR/P96DXyWeh9UbzYJza5ZJm7d+8GAPziF78AkJr7Y8GCBeH/lQmDGh/a97UePE9VOfWe8OUp6iw7dgSjGfWHU9TSz+tHRaO9OVK4P96r7J96Xdl+es/xe/YHzZFFfPmfOuszw/1QPVd/wbb2n/icTlTNO/qK39jY6H1W++4D9bXSevsUUJ9fpkbEJK3lndIZCIZhGEbvwpSdTjL6C18AELd6MrIQpzjXAcgD0Oxynxi9j9jMmeiHwGJ9OF+rMQkvrT/5yU8ABC/Vl3/jG91eF/rclFHBcT45lGjom7PrlVcAJEyLk/0k3ocAUGsW6k7DJmTb+oKHa2qkSKLE85FboRRxyceVDaNHowHAEVVV2alwN1PuykFtrZRDmMuOYRi5TpcMdq666ioAwEMPPQQgbi3UiFLp5nfTusdcIGoFp0VNrW3qj+HzHVJ0nj1Ra2GmuSoSSczHoFZtn8qgJc9D/VFYP86vr5KXBFUHfH4C6tvDz6+55pqMz7OroEWcPg9UdNgWGsGOJS3kqnBPVJsAACAASURBVPapQpFIJBJJ6WOqFBF+r8qRKh7qP8Xz0GhxmlOK+/f1OVVUmC9n165dSfVh37v77rsBAPPmzfOePxBXJjQ/Ee9l+hqpz5L6Svh8jjSvEWlbj0mF19FnoffBe4VqKAM3MBpge/Gpn9y/qrFab/W7Y7/WfuCLRqaf+xQQouupeq2KU1vtGovFUq5zd8H+plEZ+TzQZ6ZGqPQ9g3mf8/nB7Vrzy2Hb8Vr3NWwWm2EYuY4pO2nof9ZZ6I+4lZLWuqFSFuqEdpZRoLgGaFq1CseecQbefvHFrq2wkTEDP/EJAPEAX0VDgmuF1atwypmnYr37ha9nxK7DlOd+97vwJfKINOt2lkPO0f8tMYzoy3o4OEyzv+EbNwIAmtz6lXxJddPIjPQUf+pTAOIvvCzzXn65TYNPYvS1pA8KAPQDEHH/FySvWO5yKeWa707ZqacCiOe5iuS6r47DBjuGYeQ6XTrY+dKXvpS0TKWHVjfNrk7rmfru0MqseXJ8VmUfmiWd+CIgdQX5+fneiFs+PwZfVnSNFsfv1U+C32tuGq6nPk1s5yuvvLLD55ktHnzwQQDAkUceCcAfDa0ozD4ZoBnPSbq8Nq0xYMAAb7Q0XgPNtaG5izQHh/qvqbKTzgdDFSVVVHh8Ho/to75FPqj88J4dMWJE0v61vXlPaZQrnyLhy+/ii6KlqqsqYNqORHNvqQpKRefyyy9vu0HSwPxEjAbI8+JxeTz66qiPj153n1Klgz9tP2134lNofM9EjRbXGok+KppXqj2qt4+Wlhbvs0+VJM21pkqinp/v/lEFldurH2RixMtMczIZhmEYPYMpO8I+56/xcbdcopIO3/GGyHJbbATyo0DJSKDcWf/eP8zVgt5A6FPAazsRwEb3/xRg4uvBv5u6t1qG0aPEZs7EACQoMo4U/6ezzgIA5L/wAgBg0Oc+h0GIKxvlrixkdD8qO0UIlB3C8TdniDqpdV9ZGQDgyB7y3alwx5/gpoT6yDvuOABAOR8oQ/zr5iKm7BiGket0y2DnqaeeAhC3ipW5HxFah9UKqVZY9S2hNVStvOpnoTkTVPFQRUXnzXcleXl5obXRp+iolVrzFGkEIpaay0MjCmm0NfphcDldJKvu4K677gIAjB07FkBc2eE50yeH50K/LkY5Y19QnwlaagcOHOgNmasktodagPWaaJ9TS7PPAq99mfimcflyVg0ZMiRpf7feeiuAeD4d3nOZ+u5Qnb3vvvsAAMOHB2+u9Nnh/qhcfPjhhwDi9zDrwXuL964qWz7lJ50ypD4bvAe0fVgf9vUrrriizfNuL/RTZL4dzTvE+tAHSn1I2B68d1WBVCVDo94RfXZkqmAm9sf2et00NDSgvr6+yxzy0/kLJcJ2Y7vqb4MvKhuvj0a4BAIfSFXRM1G++goWoMAwjFyn25Wdcc4BmD+MB1327UwZfPbZAAJLUxRAwapV2ascgONcWUJrZGmaktDcWS3LjQjCFTnTmFnIeg+8VEkOWXkIft0LUvOJGEZfpmrkyDD1TSLMl6Pu9+Hg5pxzMA7xRyLz5aQ8KxP9GtuapemkoUlu/b3pKp5lIuPGYRCAiazvJ6YCABqDcXL43KCoX0Qlh8pVH8OUHcMwcp1uGezQf4KRbRLJy8tLiXCl8/9prWvN3+DQoUPh9r7oZTrfmvj8CrqD4uLiFGu/olZctVbT+qi+Tb7IQkQjkVEN8Pm59ATz588HAPztb38DkKoQ0KLKOn/EZJKe/DW0+Ksqlil6rXxRsLTP8bhsc5+So5Z4VY5IOv80n88G8+ncfvvtAOIKwv/+7/8mnR/ruWjRIgDAD3/4QwDxdmRfpLKm1+ULLhR7On79618n7ZeWeJ9PlSo3rC/VSH7e3vw42Yb9cPTo4I2d/VCvuyoQev7povGpWq0+TplGp9McYLmGnrfehz5Fx5fPKj8/v93KlmEYhtG76TGfnY5aimhs4/bVp5+OegAD33gjab36E05IWh66KTPPi/AnX0MPcbygYdi4gS/qaC3iprE9QIX7uCyj2hhdyZC1a1FcXIzYxz4GAIhEEVyrFpgp0zjsmEo1e4wrK4OiwLnM6COQj75Cn5LjUzpqATS7vz2I32uUSuQZu9VNYT1mb/doPFH9x51PoSvL+HkrkTcBxJNE9RFM2TEMI9fplsEOrcicp57IgQMHwvn/XI8lrcy+CFCJJEYGas3qHY1GU3x9SDqFpStIVFs0gpcqNuq3oZm62S60TlIBU/WA/itUbmg1ZruwnXtTvgj1w+I5+ZQb1p1tpZH8OhJ5r7m5OSXHEvEpKeqDwWupEQV1e58PEPEpS9ye509lTKGKx3uOJaFPy29+8xsAcR8d7vfAgQMAgBtuuKHV/WfKTTfd1KnteytsJ15fVWzYL3RZFQff9ff5MqkviU/R0X5GckHZiUQiKeflu39836tyqu1cUFAAfwauwxMb7BiGket0u7JT+/zziEajGPTZz3ZoexrNOOzhkIGvBPUzZgCIGyc5nTo6NZh3vc0tj9q+vdX9V7/7LmKxGPYffTQAoNTN0y7a4VZw1k6vwqOKUBSBUtACxOqAUVu3pjjHGj0L+0Q5r1UhgFIgckzwefGUKQCAfWvX9kDtDKObSGPjoIATUR8VVXI05xj3y4f3DgD1CO61DUhVgLhddfLuugv6KO12z/BS94CI+CJw8lnPDav7VtCCFliAAsMwcpsuHewsXrwYADBp0iQAcQUhFovFZ4cVFobz7hMjZQGpeXfamn/eWv6atki0mPpylXQFiZZHX+QpjRan26pPEq2yVHy4zFKj22nEJ/UPoWrSm9A+oOfoiyBHyy3PiW2XmIcj01eTaDSakr/DpxDxOL7oWunypxCfz47C9egzotxzzz0A4j5Nmu+H27Md9V7gcdNFbzvcufbaawEAK1asABC//uqbxHuc9yyfgXq9fQpQOj/FTH11MvXt6Q0k1lGfmTxvX7RDVcyowPHZqJE5DcMwjL5Dj/nsUJFp75SBI9asSUroFkHyFKIiF52t8sQTASRECHLz0Yvc/PN0s79btm5FU1MTKhF3xm5ubkZEsmRz/+G8dZaJMQEabSpAbyZSURH0qTM+Fpgw+yOwLpcH349xF27QSScBALZajiSjD/KaU2AmrAnKMA+VK1N8c8pdScWDzzxNyMPwZRVBsa8KaELgslNZBZSKT5Cq5JmkMssGe48JpNxwNoArw9kEVPl5Xio59Z7Zv1nFfrsMw8h1unSwQ2u8KhWFhYXhw3Po0KHeSFe0ivoiU+l+uZyXlxfOKGgLVXTUyql5cAoLCzs9n7u5udmbM4TWWi5TidGIS74s9Tpvn9vze6ob/F4jWmn0u94ALa9sG9aZdVRfg3T5WTQ/SXvzkQDxXDJAvE0ZaVB9jLRe2odVKdLPSTrfDfph7dnTune0+uZoRD5VcvTe44DfyAxeB/qM8V70+Yyw1IiTvA68fuz3mptL+3s6xUbXy1U0Gpvvvud5st/vdcEOEn38Mp8XcHhhgx3DMHKdHlN2aBTrqpAAwzZsQEFBASonBlkjJjmzYVEnczcMeOstNDc3Yw+CF5Q9J58MACh1Vr1BrkwUdpoRWDL3AKhy/h8jt2zpYA2MrqJ2R3Ct8hoQ+BXQgu0Sj5S4cdUpn/88AOCfTz7ZzTU0+gK7y8sBxHN68Vm4AUAEQKyHfMOOTRjQNjU1odIl6g3z7qiio/lz+EZMZYcWJ+fv2FgVX2xwX1UjNWVZKOU4+Xy085l5zU3BPMEF0cgWQ51aH6r0ruRp6GkVuA8KVclp7NmB43XXXYennnoKZWVlWLduXavrrFixAosWLUI0GsXw4cOxcuXKtPu1wY5hGLlOlw52vva1rwEA/vGPfwCIWzdjsVg4UyEWi4XWcVrpfUqH4ouilmitP+CpWyQSSVGEVCnSSD20uibmvenMDO9EJaq1+nN+v+88083P1/w8miWcig7Py2dd7kmoWDAqGNuMEet4Luq7o5ZzjdakapbP56ctBg4cmKIMqUW9NR+h1kqi1zpdDiiuv3v3bgDxaGmEeXSoMLDdtE+rPxjbk+106623elrBaI3LLrsMAPD8888DSM0P1RYHDhxIUZfVx0qfGfrMUjVY8/bodnrP92bflZaWFm9+K70P9fz0uVFTU9NncoFec801mD9/Pr761a+2+n11dTXmzZuHZcuWYfz48eEzwzAMo6/TY8oOjWJdPWFq8M6daGlpQWxMEJ8tkuUIqzReDpLlRBoRTykxYvPmnHAGPhypRHCtBh5C4F+g/leu7/SVlyOjZ6C/X9ExyR9MfTkoX+ruCnlgPy9k/p0JrhwtK+gzVZWePcmrlSK4pfIRqEaFx7ovKHVR2XEP00K3YWkXieEaTC4yKLkaMVFw9Dck5s6zp5/qs2bNQkVFhff7P/zhD7j44osxfvx4AEBZWWbZ3mKwaGyGYeQ23TLY0ShfibkMCgsLvdZFjcClvim0PtJqqtZ7tY4nUlhYmDJfXq3+VKLor6A5Wjpi/YxEIilKkmY9J5pbRvPs+BQnte4qPE+d/8/91NZm4vHUPXzwwQcAgBEjRiR9rtHDVIlQxUIt662dY2HKJ22TmDeKFmMej1HPMu0jPou/73PeE+yblZVBTHT22Z///OcAgGHDhgGI58+h8sP2YF9me33961/PqL5GZuzcuRNAsg9UuliH1dXVYb/m9WG/1v6gzwD6oLBkP6FPGeuhPmzsF1weMGBAj7+8+6irqwsVLn0WqzqvarYqwWyPw4FNmzYhGo1i9uzZOHjwIBYuXOhVgRKxaWyGYeQ6PabsDHjrrW5JZPf2yJEAgGFuuSDLT+1+L72EpqYm7J81C0DcAnbwmWfCF97YrbeiH4AjHnoouwc3skrj2rXA9dej4Z//RGUVMGZN8veVzlXg/ZdeynnHbqP7qT/tNNQjLpCEkgJLp5gc97nPAQDefe657qscgOqPfQxA3EeniIoOFRd+oTnGNBIlKXelO7+IK8vqgIKNAAqBwlMT9qt5bBjFzSlDRVlWdvKnT8cRiBs5QsVGos5FuALtIxJlLtLDvjqZ0tTUhDfeeAPPPfcc6uvrcfrpp+O0004LU0P4sMGOYRi5TrcMdmhVpnWR0BpJazTxvUiq/wIHS/RH0Jwh6V5IdToZrZq0ljPqFq32rD+tib7cKABQVVUVWlfVd0bnl2vkrXT1o5WX9VJFx1cvX3uor86+fftaXa8nWLhwIQDgL3/5CwBg9OjgjZBtyGtOaLllm+j3PEef8tPc3Jw2KtPAgQPD7VT9o2JE1aejlmO99rrMPvD+++8DiF8z3hNUUVmf6urgzey73/1uh+pjBMyePbtD2+3duzfsV1R28te7fza70sUHoOrd8M1vpqjZ6tfo89VRXzWN1KhR4aLRaBgshnplHgcbHPRvYsWlpHipNw6F5Xopm4HVdcGJzn4VwFuyv36yvXNDY1CD6IUXpig66fJXabskQm+9PB6P581BDXfJTdlQXL+dfYI5mLqbsWPHYvjw4SgqKkJRURFmzZqFNWvWpB3sGIZh5Do9pux0FzQ+8vfLBfaJW1ezRP3KlWFCx940DcxoP9EZM7Dz3nuxE6mJV03RMdrL/pUrkYe4gpDPl2d9aXaEL9+rVyetFnOr8qW/+Mwzs1rPYg5aONoplJLKR54sD5CSvyq8VRqlbEL8QZzoNqKDCfmcm3d2el3L668DiAs4eRxcccc8X67A82QFOBrtqlCiXcScOXMwf/58NDU1obGxEa+++mpG01ZN2TEMI9fplsEOrc/0H6C1ndZ1VSJUuWHpm5+tio/PByaR+vr6FCu/Khu0htMaSGu5otZD1lf3S+s/c2ZwPfUp4rJaZ7Uk6qOkfivazhpxi+3GyGeZzOPubi666CIA8ch+miuIig7PVTPPE58fmG7Pa09nXlUNVY3k91Tz0kW30uhnvmtKtJ7bt28HEFcf+T37Fo8/b948GNmjI1b5F11f42y1SXzqTnElLTJO4Ym5gQAzJkWlrHTlCf/3f2F/o3rO/DF8FrE/lLgw0lSn2f+5/d69e3H8mScEO+a0MpleFy5zmhmnuZW7khYkno9m5XQhqFENzP5x8O+KRKFRp4lxu+VB8VowRkHDHXeE56G+SOqHyHbgs622thYHXPj/MB4CB2kc1PB8uQLPm/XnQI0XooeUGuVLX/oSVqxYgaqqKowdOxbf//73w+fA3Llzceyxx+K8887DtGnT0K9fP9xwww04/vjj0+7XAhQYhpHr9Fplp9+sWWhGYGRrAdDPWePay+hdu9DS0oIWBD98o+CfNmYYhpEtKtyAgu/MJfoyzWXKzozq5RSFMjWnu/VHu8HAmiGBk8s4FwSh07BeHOyoS2VUPucg4OOuHHWcfOBGEePdCc7Y5T7fCCw5ADQ3AXMQJBgCgNWu5KCCgz/36I+89lpKMtz2UDRuHIoATOZ5DpEVaBfhoE19lIg7nbtv+n+9ypjwUAY+od/61rfwrW99q137NWXHMIxcp1sGOwsWLAAAPPzwwwDiIS81cg6tcYWFhTqzA/3790+JvqZ5eHz5YWiF5w8ll9V67stqrt/rPHGN+kZ/DY2aRiuqbx6+Ki2Krk+lSfPmaO4J1lcVH7YD67kzWy9NXci7774LADjmmCBuL/sAzyGxDyWiKpf6LqhSo3lJVHlRZYjH47KqaRr9im3NqFulpaWt1ot9kNGyGHWN2y9atAjG4U19fX3Ks43PSI1WSLgenwm5QCwWC+8H1p+KjT7Led58HnRF1LXeNNAxDMMw/PRaZSf/lVfCF8juiNpmGIaRTco5jfY4Z7wY477gezena3E6lG+uUEFyybwzQ7Jtbuf0NM2Tw3qqosNyFGNdznGlKDuhkwslrA8B/BbI2w8MPhEYHSReTVF2XGCEjmn6cY6Y4gLjzHUfSB6f8Px43uWuHC3rOfvJ0m88jjlzeK59H1N2DMPIdbp1sMOMzWPHjgUQj6KmVnJfBCG1ntPKp1HJNMs4v1dFh1Z333FpHVUru/rScL+0HlLZ0SkXiZGPEvejPjest65POPij9ZLH03w5LLm+Otvz+PRPufnmm9HbueaaawAECfKAeF/ScyTsE9qG2ha8hrzW/J7b+/ymNCoWUUszoSX6vffeAxC3rI9xSW+HDx+etF/6eTH4xbXXXtvqfo3Dl0OHDoX9iPe0PjN9SiaDqeTC1N78/PzwPuMzXf00eb767M4muaCAZxMb7BiGkev0WmXHMAyjT3CpK6kUuHxNoa+K5JPRN8tYXfLHFD4Gbd8eDoazgio2kk8mhAoPFZIUp5ZDUlLhKU8oH3P/nx1XdiSgAQM1jNq+HXv2sHE6wNmuvFo+F1+p0IenVNbjdZK8W4cLFqDAMIxcp1sHO7feeisA4IknngAQ9zlRBUezX6uiQis9rZlqfVf/CM1z47O687hUCRjJiFZDWkOphBDWS/PwqHVRz0f9OXyqAfFFj0vMEZNY+qLW8Tw08lguceWVVwKIKzzjxo0DkBr1TKMyqS8Or4nm6VALuPYNom3ri7pG+HKqffHyyy9Pd8qGkURTU1N4D9MfUJUdXz4a9mdu3xnH/64mPz8/JXIllR3f/Ujq6+txRJbrM3fu3PQrGYZhGL0GU3YMwzC6kh+4KY47nfGCSgF9QShaqM2Bik40eTW6+IxBdig66aRApPn/3AflUh8qHoz5QSGHFdoaBA3B0Y+4D06VFRnebGTCURsRSCq7UkM6b05eHICOsW5ocPyy690HDBY3mM45HOCVu3Ky1NNJOXveBAA8ds6juOSSSzpYm9zFprEZhpHr9Mhg58ILLwQQz5mikXJondP8OrTOq6JDNJqZ+sT4FBX1t1BlRgMlfPDBBwDi+XioKmhUNT0O8SWopPXVV2oWcFUdtJ34vc+/hNbgq666CrkKFZ777rsPADB6dDBXiKqcqoS8NqqsqKKjuZM0F5T6QKi/l/pb8VpQ2aGq2RVRoozDB1/ep3S+ZdrfezN5eXkp/pr67FPfHZ963xkOx4EOYIMdwzByH1N2DMMwuoNRzrgRdQMM9RnhjKyE5JsAUOgUlKHO1yd0lckSk053/5zjSio41VJqPalQVbiy1ik80z50H0x3JZe5o3cAVAENjcD79wCPuo9d8tB925J3OzXTExGO27s3MEh9++jkww+m4kQl5zRXftaVVHbuBAAsq/sPnHfeeR2sRe5jgx3DMHKdHh3sbNmyBQDCLM6MLqbzzQkVHc0NQWu9L4qZT9lR/wq10vN7rQetjBqVzZeLRdG8PKyPL9qb1svni0TYHqqEEe5/27Zt6CswSht57LHAAZp+VBp9jWgEPKLXJN3nRHM+MfqaRgRkBD1fbijDSEckEklRbPQZpL46+oxRdbk30q9fP+/9qct6/1G97gybNm06rAc7hmEYuY4pO4ZhGN3JePeiXu2MIVRSGAWMNgg65zhlp8gpPh8PbER4P1v1YcqYifK55PcJo7PRV4f15Aw6nkeBW3HMS0FJ3yQqQZsRqFc1AP4TwMrg491vB+W7L7+MMWPG4GhkaZon68loaoNcQw6ngjNENghWXL78YmzYsAGHOy2waGyGYeQ2PTrYue666wAAjz/+OACgvLwcQNzarsoFFQqNQqbWTLVaqn+GWgFVaSG+ee26rL5BGgXNtx89ripQiu5H24loniEqPWy/iooKALmRV6ejcH79XXfdBQAoLQ3eJIc6p2W+ROlcf0V9dnxR3NTSzO2Yx0QzvXP9XMpgb/QumpubvcqOz2dHo6+pr09vIDHKnM+/0qdQ+b7vCJs3bw4jiB7O2DQ2wzByHVN2DMMweoJpboBc4IwgFBiYj4c+JlWurAiKiHM5KT76aBQD+HBNxxLAlEyZghIAWCJf+N5sqdBUSMn1C2U9OhfRB2lDQrkDgVK0BNjktt/05JOhMSKrUIliM1FBG17h/qH0swsA8Oyz52Hr1q3Zr0eOYoMdwzBynV4x2PnCF74AAFi6dCmA1OhmGoVMo54RjT5G1Oqnn6sy4/Pr4Hq0in79618HADzwwANJ9VTrvx7Hp/ioYpMuB4yur/4f+nllZTAv5uqrNbte32X+/Pmtfs5rVlJSAiAevY2ki6CnfUktzFymrw6VHc2R1Bst60Zu0dTUFPZPjSCpPjukK6KVdZahQ4em5FrjfZTOT9H37NbfiEzYunUrvva1r7V7u76KDXYMw8h1esVgxzAM47DlWDdwrnMDEvrO8A2TCs9wVzqXmDKnVHzQwcOGUd2oeFBZoriiPjoVrqRCoz47qvwQ8fHZtwNoQpDlZnUUqHnhhfZWPSMqx7hMRFTKNFFR/d6gHMgG2OjKH3VJfQzDMIyeoVcNdubMCTxlaXWnDw+tlbT6qbVO53drrhOi0c/U50Wjnanic+DAAQDA/v37k/b7la98BUDc94gRwFQNYI4VRuLS3BE+RYioXwnPU+tJPxBGImLUtRtvvBFGAK8ZefTRIP6tL6qVzyfAl4+Hy7zmVHZIUVHwqmkWZKOz1NXVhc9EKpR8thAqO1yPz6DeAO8FIDUSpuYU47PeF+lSn+0dwe7JZGKwAAWGYeQ2vWqwQ/RFNJFoNIqNGzd6vzcMw8hJZjjjxnPuRZ4Ki5bi21Ny1lkoAbDj2WfbdbgKV079nfvnNVeWu5KB0KjwUBFx0eBCxYnQBqQB1Li9Wz+K4AWa06O66keIgk7oo6Mz2lx9nn/lR9i8eTMA4Kabbuqi2uQuNo3NMIxcp8cGO3v27MHChQvx9NNPIxKJ4IILLsDvf/97AMAf//hH3HHHHVi9ejVOOeUUrFixItyuoKAgVFZ887FV6aGVnb429KPgMq2A3J9G/qFSsm/fPgDAggULWj3u9u3bAQBDhgxJ2g+tkoyCRqtlcXExgLgSxGUqWb4IYYT14/6pHnz00UcA4tHu+gJt9QkAWL16Na6//nq8/fbbOPbYY7FkyRJMnz699Z21wqWXXgoAuO222wD48++oxVijPfF7RmGjssM+RAfsa6+9NuO6GUYmFBUVhYqNqtuqXhcVFYWzznqaI444IkXFTqfOs9ScbInnm6m3zvr1672+fYYNdgzDyH16bLBz8cUXY+bMmdi2bRsGDRqEdevWhd8NGzYMixYtwsaNG/H3v/+9p6po9CLa6hONjY2YM2cOFi1ahHnz5uFXv/oV5syZg82bN6dM5zGMXs+n3Yv/w6LwUCGRvDwTnS/Ma2ecgT0ASt95J6PDlO3ejebmZnwon28fNQpAXBlRgScqn7N6hZqXh+WQ5A3K9gAFNQCagQkA9kwMnJQoFJVt2tRqfatOOAH58AtPje7/InfoMVxhgpSu3Zav/5vNEjAMwzgMSDvY+clPfoJXXnklzEgPBMpGXl4e7rjjjg4d9Nlnn8X27duxYsWK0HJ+4oknht+fc845AIDFixe3uv2ZZ56ZtMxcKtyXztvuLqudT/FZsiSI7bpw4cJ27e8Xv/gFgNTz8h2nt7J161bMnDkTy5cvx0knnYQdO3Zg2rRpePTRRzF79uyM9tFWn1ixYgWampqwaNEiRCIR3HrrrfjpT3+Kv//97+3OfD58eOAFvmNHEC+X+XlU9SO0MFO5oZJTXR28ulFF/Pa3v92uehhGR2lubk7xIdNIlZpfispIOjW5OyguLk5Raqh2Z5NzzjknfK4YfkzZMQwj10k72Lnqqqtw2223obq6GkOHDkVTUxMeeeQRPPPMM5g3bx7+8Ic/tLrd+PHj8dZbb7X63SuvvILJkyfj6quvxjPPPIOjjjoKP/3pT3H22Wd37myMXsnRRx+N//7v/8aXv/xlvPHGG7j22mtxzTXXYPbs2R3uQ4msX78e06ZNSxqITJs2DevXr2/3YMcweg1XOIXnXtev6+R7p1AUOglmostns+G44wAA5e+916HDTqquDqdn1tTU4CDiwVk4aCosLETtCScAiCs7YXg3fjBIPqfSMxrAGqCgHigbspOzqgAACfhJREFUDhS5etMlyAd3SxecIu7fvYnHXBnh5xNbL//y0Z9x0UUXpTmaQSxAgWEYuU7awc6oUaMwa9Ys/OlPf8KNN96IZcuWYfjw4ZgxYwZmzJiBu+++u90H/eCDD/Dss89i8eLF+O1vf4vHHnsMc+bMwZYtW0LLenvo7fOt2+M7kkh7laDezI033ognn3wSp556KiKRCJ544gkAwN13392hPpRITU1N6CdFhgwZEqos7YHX6pJLLgEQV5Ko8DBylCo69JNK59dlGN1FdXU1BgwYAAAp+Ws0ciXXY6nRBjVSZTQaRXEX1Ts/Pz9UmHjc/v37Z83HyAY67cOUHcMwcp1+6VcJklA++OCDAIAHH3ywzWhpygsvvIDi4mIUFxdj6tSpAIKwp+Xl5bj++utRUFCAK664AuPGjcOLL77YgVPo/dxxxx0dnvLXl7jxxhuxbt06LFiwIKvTUoqLi0PLMzlw4EBKotBMsGtl9DrmxoK/agR/je6vwP0NCf5KEfyNRkIksi4k6v5YDQxyf64+YYW4zO+LAOS5jUqBooLgLx3Dtm0DVq0KmyGsgNtvZHjwFzYA/1w9llQuBs6Ltb5zwzAMo8+SUYCCL3zhC/ja176GdevW4amnnsL//M//AADmzp0bDoKUCRMmYP369TjrrLNScoxMmzYNTz75ZCerbuQSNTU1WLRoEa6//nrcdtttuOSSSzBs2LCM+lA6pk6dip/97GeIxWLhVLa33noLt9xyS6frfcMNN7T5/T333AMg7pvzjW98o9PHNIxssG3bNgwbNgxAqs8L7xNGb9PoZhodTfNOVVdXY0T2qwwgOW8Q66lRDzvC9ddf3+l9HI6YsmMYRq6TkbIzYMAAXHrppbjyyitxyimnYPz48QCAe++9FzU1Na3+tfWSetFFF2Hfvn343e9+h+bmZjz66KOorKzEGWecASD4YTt06BCamprQ0tKCQ4cOheGkjdxk4cKFmDFjBhYvXozPfe5zmDt3LoDM+1BbfWL27NnIy8vDnXfeiYaGhjBgxac+9anuP1HD6Cp+EAv+7nF/lDjqgr86JP91NbXuL1RapD6h8sI/fr4HgTIVDf6vjQZ/+xFP1dMWe1atwptPPIHKKFAZBWL7g7+QouDvwSsfAJ6OAf/q/owOwcGO788wDKO3k3Ho6auvvhqLFy/Gb37zm04fdNiwYXjiiScwb9483HLLLZgyZQqWLl0a+us88MADSXlIBg4ciKuvvhr33Xdfp49tdD9Lly7FsmXLsHbtWgDA7bffjunTp+P3v/89vvzlL2e0j7b6RGFhIR5//HHccMMN+M53voNjjz0Wjz/+eLeEnbZs60ZvZc6cOaE/HJ+tgwYF3vv0PaNyoooOlRTmIqurC4ZPjDJYV1fXZT47+/fvT4nGRsMGfeNYj7a46qqruqiGhxcWoMAwjFwnEtP5Ch7ef/99TJkyBR9++GGYBNMwDMPoWWrdgGWzW56e8EhPN9ihX5smNE432GHS3IsuuggvuuOfkXDcxx9/HABw5JFH4qxvzAo+pAxQCcyuBpqbgGUAKtzHDW+84U0SqoOdnTt3AogHTOA00nnz5vkbyugQR0QiaCvETv2MGXj99de7rT6GYRjtJSNlp6WlBbfffjuuuOIKG+gYhmHkCL6X//vvvx8AMHRoENCZgx+qoRxkMNQ0Bzsc/Hzxi19s87hcb9euXRnXtbKyMiWPFQddjKzIwU5filTZ2zGfHcMwcp20g53a2lqMGDECEyZMwLJly7qjToZhGEaGFDlFpWMB7jvPGWkmBzz6r38KlaNIJIJTzjsPTQAaEKg67zz2WBiQwOh9pBvsRNr4zjAMozeQdrBTVFSUEk3NMAzDyF2++tWvtvn9L3/5SwBIUVoyzWl2xRVXJC3/+te/BoBW/ej27dsXTkejkmR5qnoP6QY7Xe8ZaRiG0TkyisZmGIZhGNlg6W9/i6rJk3Fw8mS84pL2GoZhGEZXkXGAAsMwDMPIBrNnzwYArFixokfrYaRnQCSC8ja+L7YABYZh9HJM2TEMw+gm7rjjDhx11FEYPHgwRo8eja9//evhFK5EVq5ciUgkgn/7t3/rgVoaRhzLs2MYRq5jgx3DMIxu4vOf/zzefPNNHDhwAOvWrcOaNWtw5513Jq0TjUaxcOFCnHrqqT1US8OIY4MdwzByHRvsGIZhZMgjjzyC4uLi8K9///7hlKxMOProo8Nwz7FYDP369cOWLVuS1vnZz36Gz372s5gyZUo2q96rmD59OqZP76n4cYc3y5Ytw+TJk3HMMcfgv/7rv3q6OoZhGF2O+ewYhmF0gAMHDuDUU0/FokWLsG/fvjZfHJmMEwD+8Ic/YO7cuTh48CCGDx+O5cuX4+Mf/zgAYNu2bfjMZz6DN998E/Pnz8fYsWPxox/9qMvPxTg8aG5uxqRJk/C3v/0NY8eOxcyZM/HQQw/huOOO825TEIlgeBv7HGM+O4Zh9HIySipqGIZhxGlpacGVV16J2bNn4+abbwYAfOc738lo2yuvvBJXXnklNm/ejPvvvx8jRowIv7v11lvxwx/+MMxLYxjZ5J///CeOOeYYHHXUUQCCEOFLly5tc7ATA9DYTfUzDMPoCmywYxiG0U6+973v4eDBgyn+Nu1h4sSJmDp1KubNm4c///nPePLJJ3Hw4EF88YtfzGJNDSNOZWUlxo0bFy6PHTsWr776apvbnHPuuaiqqvJ+P3x4W7qPYRhGz2ODHcMwjHbw8MMP46GHHsJrr72GgoICAMCPf/xj/PjHP/Zu40vM3NTUhK1btwIAnnvuObz++usYOXIkAGD//v3Iy8vD2rVrsXTp0iyfhXE40tqsdU0cqyxbtqyrqmMYhtEtWIACwzCMDFm1ahUWLFiAxx9/HKWlpeHn3/3ud1FTU+P9I4sXL8bu3bsBABs2bMB//ud/4tOf/jQA4Ic//CE2bdqE1atXY/Xq1bjwwgtx44034re//W33nqTRZxk7diy2b98eLn/wwQcYPXp0D9bIMAyj67HBjmEYRoYsXboU+/btw5lnnhlGZDv//PMz3v7FF1/ECSecgKKiIlxwwQW44IILQkXoiCOOwMiRI8O/gQMHoqioCMOGDeuq0zEOM2bOnInNmzfjvffeQ2NjIx5++GFceOGFPV0twzCMLsWisRmGYRjGYcLTTz+NRYsWobm5Gddddx2+973v9XSVDMMwuhQb7BiGYRiGYRiG0SexaWyGYRiGYRiGYfRJbLBjGIZhGIZhGEafxAY7hmEYhmEYhmH0SWywYxiGYRiGYRhGn8QGO4ZhGIZhGIZh9ElssGMYhmEYhmEYRp/EBjuGYRiGYRiGYfRJbLBjGIZhGIZhGEafxAY7hmEYhmEYhmH0SWywYxiGYRiGYRhGn8QGO4ZhGIZhGIZh9En+f9ybwFi8ofo7AAAAAElFTkSuQmCC\n", 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\n", 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\n", 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\n", 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" ] @@ -118,12 +118,12 @@ ], "source": [ "for stat in stat_files:\n", - " plotting.plot_stat_map(stat, title=stat)" + " plotting.plot_stat_map(stat,threshold = 1.6, title=stat)" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -137,7 +137,7 @@ " '/media/Drobo/work/KPE_SPM_ses2/Sink_ses-2/2ndLevel/_contrast_id_con_0001/spmT_0001_thr.nii']" ] }, - "execution_count": 16, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -149,12 +149,12 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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37kRcXByGDBmC1157Df369cP333+v55kzZw4eeugh/Pe//0WfPn3w7rvv2m0cH3jgASQmJiIpKcmw3VKwOn36NDIzM/Hll1/i4YcfNtTLEWbPno3MzEwMGTIEy5cvx5QpUzBkyBCbeV1cXBAaGorhw4ejZ8+e2L9/v93y33nnHTz55JN4//338fDDD+O1115DWlqa/mz4+PggMjISrVu3xksvvYShQ4fCy8sLO3bswG233QbArCh49913MWfOHPTp0wfjxo3D2bNnnV4fAJgHsH///bdhm6enJwIDA0sUVtu1awcvLy+rfatVq4YlS5bg22+/xRNPPIHc3FysXbvWYBv8ySef4Pnnn8eMGTPw5JNPws/PDxMnTnS67m+88Qbmz5+PdevWoX///pg/fz5mzJihC4jh4eEAgEGDBhn2GzZsGOLj47F7924AZnvW8PBw7N+/HwMGDMC0adPwwgsvYObMmSUeX9aGyHjqqaewdu1anDt3DkOHDsXo0aNx5swZ1KtXD4Bz7d7ChQtx5MgRDBo0CLt378Y333yDjh07AjB3yBEREfjrr79w//334/7778f//vc/fd8HH3wQ48aNw1tvvYXHHnsMaWlp8PX1xenTp/Hyyy+jX79+WLhwIaZNm4a33npL36+kZ3fTpk347LPPAEA/5ssvv+zQdeGUtq+1pHv37ti5cyfy8/MxatQoDBs2DHv37tWFobp162L37t2oVq0aRo4cif/7v/9D9+7dsX37dqsBpjNtAicgIAAAcOrUKcP2kydPok6dOrriJSAgwCpPfn4+zp07p5fhaFmdO3fGsWPHdOE6JycH27dv1/e3pF+/fvp73rVrVyxYsADLly/Ho48+ijFjxuD333+3GhR/+umnMJlMGDJkCBYuXIgpU6ZY3etq1aohNDQUX3zxBUaMGIFmzZph2bJlWLlyJSIjIzF48GBcvnwZq1evtrluoLQEBASgoKAA0dHRVtfI8vxtXe9Lly4hKyvLcL0dKet6sfe+du7cGa+88gomTpyIF154Affee69BAUbYkv9kfP7550hNTcWQIUOwcuVKTJ8+3aqdLDWlNb85ePCg+O9//6v//v7770V+fr5o0aKFvm3WrFlCCKHb2gIQjz76qBBCiICAAAFAtGzZUhQWFlpNIy9ZskTs379fAGYzhcuXL4tvvvnGkGfbtm2GKSJ7U8YuLi7Czc1NnDx50srenJ+PvWn+K1eu6PWh44aHhxvy+Pj4iMzMTPHBBx8Ytm/atEmcOnXKcO2EEKJLly76tmbNmon8/Hzx4osvCgAiICDA6jq5uLiIY8eOiS1bthi2xcfHi0GDBunbLl++LCZOnCgAiNGjR4uDBw+K33//XS/7//7v/0R8fLyef+XKleLMmTOGaeHg4GAhhBD333+/AMzmMUIIMWfOHJtTQOPHjxedOnUSycnJ4uuvv7bK88orr4gjR47ov+kaCiFEbGysdPqKTGtq1qwp3NzcRJMmTURYWJjIz88Xd999tyGPLbp37+7QNFaTJk3EoUOH9P3OnTsnPv/8c4MtH2A2rfnss8+Em5ub8PT0FEFBQSI1NdUwZUcmOnXr1hV5eXmiQ4cOwsPDQyQnJ4uBAwc6PdWZkZEh+vfvL/1/z549ViYdPXr0EEII3fzn2LFj4pVXXnF4Wq9NmzbCZDKJKVOmGLZ7e3uL/Px8g/3f8OHDRUZGhhBCiNzcXPHrr7+K559/3uZ9JBMpuv9Lliwx5Dt06JBYuXKl1Xvp6uoqli5dKq5evSruvPNOh89jw4YN0nUBAMT06dNFUlKS8PHxMZxjamqqePnllwUAERISYlgfUNrP6NGjhRDmtR+W2/v37y+uXbsmNctwcXERERER4vTp08Ld3d1wbYQQokePHvq2u+++WwghRJ8+fQQAUbt2bWEymcSbb75pKO/kyZOG9t5eW1qjRg2RkZFh1bZNmzZNXL16Va/7unXrxObNmw15Tp06JUJCQvTfMTExYtGiRVbXxmQyidq1axvuu2Ue3oaU9HFxcRGxsbFizZo10jzOtHvTpk3T87i7u4uEhAQxc+ZMfVtJ0/kmk8mqHeEfNzc38c4774hz5845/OyW1vyG2mvA8b7W3uf3338v0aR05syZIiUlxWB+0bFjRyGEEMOHDzc8g/bahJI+I0eOFEIIq3V2vXr1EkIIcccddwgA4syZM+KLL76w2n/v3r3ihx9+cKqsU6dOifT0dHHixAnx+OOPi/79+4vDhw+LmJgYg030XXfdJQoKCkTdunUFADFx4kRx8OBB6bnQ9di6dathe2hoqIiNjdXNUKgd6Natm55n3LhxQghhkHvatGkjhBCib9++VscqrfnNu+++K1JSUqy2P/fcc0IIITw8PAQAkZeXJyZMmGCV79KlS+Kjjz5yqizLz40wv0lNTRXe3t76tgkTJgghhC6jyOQ/W5+WLVsKIYTVWtRjx44ZTLhmzJghrl69avWMtW7dusTyhSil+U3Dhg1xzz33WGmSYmJi8M8//+i/z549CwCIiIiw2kYj9l69eqGoqAhr1641aFR37tyJ9u3bw9XVFU2bNkXjxo3x888/G45HmqCSCAgIQHh4OOLi4lBUVISCggIEBAQYptNl51MStqb/+P533XUXvLy8rFZPr1q1Cq1bt9Y1RAAQHx+PP/74Q/998eJFREVF6SYFHTt2hKurq6EsoU39WU6vd+rUCd7e3gYzosjISHTt2hUA0K1bN+zZswd79uwxbIuMjDSUsXbtWoPZy5o1a5Cfn281lS+7Zg8++CC2b9+O0NBQvPrqq1b/y6bNt27dCl9fX7zzzjs2yyXS0tJQUFCAS5cuoWfPnhgzZgyOHDliyNO1a1d06NDB8ImKiiqxXCI2Nhb33XcfevXqhc8++wzJycl4/fXXcfToUcPUGwBMnDgRBQUFMJlM2LhxI/bs2WPTm0RSUhIiIiIwfPhw9O3bFy4uLti8ebND9bHk8OHDmDlzJkaNGoWmTZsa/vP09ESXLl3w448/Gt6nyMhI5OXl6aZnhw8fxqRJkzBu3DjccccdJR7P29sba9aswdGjR600EH369EFCQgIOHTqkbwsLC4Ofnx9Gjx6NsLAwtGrVCgsXLsSKFSvsntu2bdsMv//++280adLEsM3NzQ1hYWEIDAxEt27drLTVJXH48GE8++yzmDRpkpUZIAD07t0b27dvR3p6un7tMjIyEBUVhQ4dOuhl9OvXD1OnTtXfS0tcXV3tzg7de++9CAkJwZdffqlrrAmakpeZnc2cORNdunTB008/bTWTlZeXZyiPrg1dw3bt2sHT09PQlgohrNpWe3Tp0gXVq1fH6tWrDecaERGBhg0b6sdbtWoVevXqhTp16gAwzwq2bt0aq1atAgC0atUKfn5+Vs9rREQEPD09cdddd0nr4IzpTevWreHr62uYreI40+5ZPqekTeTPqYyoqCjEx8cbtlWtWhVTp05FdHQ0cnNzUVBQgI8//hgtWrTQnyF7z25ZcD19LVGtWjV07twZS5Yskebp1KkTtm3bZpgZP3DgAM6fP1/itQZstwn2EGwWkvpvy+08D+Xj2+2V5erqCi8vLzzxxBNYt24dNm7ciEGDBsHX1xdPPvmkvl9QUBD279+vz3wePnwY99xzD+bMmYOuXbtKTeLWrl1r+B0eHg5fX1/DNcnNzdVn3gHHZLGyQnYd+X+OXG9Hy7qRHDhwAKmpqfpvalP5dXNGfiyLZ1pGqYT6fv364Z9//sGZM2cM2y1PHDB3MHw7baOp7Lp168Ld3R3p6ekoKCjQP0uWLIGHhwcaNWqEhg0bAgASEhIM5fPfnOrVq2Pbtm1o2rQpXn/9dTz00EPo0KEDDh8+rB+/pPORUbVqVdSpU8eqYea/yWxDls/Hx6fEc0lISNDLaNSoETIyMpCdnW1VlpeXF6pUqQLA3FDs2bMHmZmZep49e/boDWXXrl2xd+9e7N27VxfqH3roIUMD0KhRI6s6FxUV4dq1a6hdu3aJ50w88sgjcHd3x9KlS63+q1atmtS8ICQkBLNnz8YHH3xgsFPldO3aFffddx/8/PzQoEEDLFu2zCrPoUOHEBUVZfhYXhd7FBUVISIiApMmTULHjh3xyCOPoHbt2lamCsuWLUOHDh3Qrl071KhRAwMGDJA+m2FhYRg6dChGjhyp22w6y7Bhw3Dw4EF88cUXuHjxIg4dOqTbJ/v4+MDd3R3z5883vE95eXmoUqWKPgh45ZVXsG7dOnzwwQc4c+YMzpw5g2HDhlkdq2rVqvj5559RtWpVDBgwAPn5+Yb/LU29LElOTsbixYv1gceiRYswYsQI/Oc//ynx3Gy1IZbvKmB+fh599FFERERYTc3a48MPP8S8efPw8ssv4+jRo7h06ZJh0Fm3bl0MHz7ccO0KCgrQs2dP/dotWrQI7777LoYOHYr9+/cjPj4e06dP14X7c+fOGfblbgCbN2+OTZs2YefOnTbNXiyn5Dnjxo3DpEmTMGrUKJvmRunp6YbOju4XXcPStqUcMjX4+++/DedKAwq6VuvXr0d+fj4GDx4MwPzsxsbG6koEKmfz5s2Gcsi2mQ9aiZLaEFvQoKIkF8zOtHuOPKcybLWZs2bNwhtvvIHQ0FD069cPHTp0wIwZMwAU3zt7z25ZUBbPh4+PD1xdXZ2+1oD52pTltU5JSQEAfa0PQb+p7JSUFKs8lM8yjyNlJScnIz4+3mBecv78ecTExOgmr4D1oHTnzp0YPXo0unXrht27dyMpKQnz5s1DtWrVDMeT3RtLM9GMjAxDO2BLFuNtQ1mQkpKCGjVqWCk6vL29kZWVpSshZNe7Vq1ahuvtSFk3Gplcy6+bTBZytMyyug/2VyLZwNnFSSWRnJyM/Px8PPjggzY1UwkJCfqCKb6gzNYCM0u6dOmCpk2b4uGHH8bp06f17dxGzdnz6dGjBzw8PAyadcB65EiNWv369Q321bSgznKbrXOpX78+Tpw4oZdVo0YNeHp6GgT7Bg0aICsrS3/QgoKCrATcvXv3ok6dOnj44YfRvHlz7N27F/n5+fD19cXDDz+Mhg0bGoT6q1evWtXH1dUVderUsbITl42WP/zwQ13r2bVrV8MMTq9evWAymayuH/HWW2+hQYMGCAkJQWJiok2b1kOHDjlti369bN++HUeOHLGy54uPj3d4BiA8PBwLFixAcHBwqX2AX7lyBaNHj4aLiws6deqEqVOnYv369WjWrBlSU1NRVFSEqVOn2hS2r1y5AsA80zFhwgRMmDAB7dq1w5tvvokffvgBR48excmTJwGY7/mKFSvQtm1bPPDAA1adiYuLC/r27YsXXnihxPoWFBTgiy++wJgxYxAQEICjR4+W6ryJjIwMDBs2DJs2bcLVq1ftzupYkpubiylTpmDKlCm4/fbb8dJLL+Grr77C6dOnsXXrViQnJ+Pnn3/WBSp+XMD8zH/55Zf48ssv0aRJEzz55JP46KOPcPnyZXz77bd47LHHDGsJ6JoDQL169bB161ZcuHABw4cPt2rz2rVrB19fX2zZssXq+IMHD0ZISAjefPNNw+IxZ6B1J/Xr19eFFPrtDNQOBAUF2ezMqL3NysrCpk2bMGzYMCxcuBBDhw411J3KGTt2rGG2hzh//rzN49trQzi0SLmk9THOtHvXg602Mzg4GCEhIfj000/1bbx9sPfslgWWz4clzjwfKSkpKCwsdPpaA+b+zNG21BFIsA4ICMDFixf17QEBAbh27ZquJT916pRVu+7h4YEWLVpgwYIFTpV18uRJw+JrwsXFRX/fvb290aVLF6tB2dKlS7F06VLUrVsXgwcPxhdffIH09HRDGye7N+UZM4g4deoU3N3dcfvttxuUpNyG3tb1btKkCapXr67nc7SsisLNmjmwh9Oaeg8PD/Tu3bvMhPqIiAi4ubmhVq1aVlrVqKgo5Ofn49KlS7h69SoGDhxo2Je0PzJoAUhubq6+rUuXLoZFss6eT61atTBr1ixER0fbXd1+/PhxZGVlITg42LB96NChOH36tGHBYYMGDdClSxf9d9OmTXHvvffq2rgDBw6gqKjIaoHQkCFDdK1Xo0aNcO+991qdy7Fjx5CSkoLJkyfj1KlTSEpK0oMpTZ48GRkZGb67OtkAACAASURBVDh8+LCe/88//8SgQYMMI+TBgwfDw8PDYKZTEvn5+RgyZAhOnz6NHTt2oHHjxvp/QUFB2LJlS4lebZ577jls2bIFy5YtQ2BgoEPHLEssTaOIqlWrokmTJk6NyDnp6emYNWsW1qxZ45B3hJIQQuDPP//EtGnT4OXlBT8/P5hMJuzbtw+tW7e2+T7ZaviPHTuGSZMmwc3NzdDQfvPNN+jbty8ee+wxm7NYnTt3Rs2aNQ3nUb16dZsaBzLxuZ5rZ0lERASCg4MxceJEm0G9HOHs2bN44403kJOTo2vQdu7cibZt2+LEiRNW187WNYiNjcWsWbNw9uxZvYzjx49btWEA4OXlpQ+0+vfvbzXrBpjfjT///NPKU0737t3xww8/YO7cufj8889Ldb4A9GA4lm2pi4uLVdtqjz/++AMmkwmNGze2+ZxZzoiFhYWhe/fu6N+/P1q2bGlwlHD69GnExsbC39/fZjkyYdqRNsQSOk5JAaHKot0jnNW8eXp6GvopV1dXK2cKlth6dkmx4+zidEtK29daYjKZ8Oeff9r0YEf8+eef6NOnj8EjV4cOHdC8eXOnr3VJnD9/HqdPnzb0wS4uLggODjaYPm7evBkdO3Y0COMDBgxA1apV9QG2o2Vt3LgRjRo1Mniva9GiBfz8/HQT0b59+yI+Pt7Q71pCHsv27t1r0O4D1gvPBw8ejCtXriA2Ntbh63Kj+P3335GWlma4Rp6ennjsscesrje//8OGDdMDTDlTVllQlpry8sZpTX23bt3g6uqqX/jr5cyZM1iwYAHCwsIwe/ZsHDx4ELfddhvatm2LVq1aYezYsSgqKsLs2bPx2WefISkpCXv37sUTTzxh5fKRs2/fPmRkZGDhwoWYPXs2mjRpgqlTpxoe/pLOx93dHZ07dwYA1KhRA/fddx/GjRuHatWqoW/fvnY7lJSUFHz55Zd47733UFBQgIMHD2Lw4MEICgqyarATExOxbNkyvP/++8jOzsb06dORkJCAxYsXAzCPWleuXIm5c+eiZs2aOHv2LMaOHYuAgADdTKVfv36Ijo62MkkQQuC3335D//79da0DYNbgv/LKK9i2bZvBZd6HH36IQ4cOYd26dZg/fz6aNGmCWbNmYcuWLU5Fqc3JycFjjz2GHTt2YMeOHejWrRuSkpLQr18/vP322yXuW1hYiODgYOzYsQPr1q1DYGCgtAGU0bFjRyvBKSEhQar9s2Tr1q04deoUNmzYgEuXLqFhw4Z45ZVX4OPjg2+//dapenBKE/WRqFmzJrZu3YqlS5fizJkzqFq1KiZOnIirV6/qGvY333wTO3fuRFFREX766SdkZGSgWbNmCAoKwuTJkxEdHY29e/di7dq1OH78OIQQGDt2LDIzM/VB5DvvvIMXX3wRH3/8MYqKivT3ADCbXGRkZNg09WrdujXWr1+PRYsW4ffff4fJZEL79u0xefJkHDp0qEw77I0bN+Lpp5/GDz/8gPT0dKlLVUvCw8MRFRWFQ4cOITs7W/fItWfPHgBmr0BPPfUUIiIiEBISgsuXL6NBgwbo3r07IiMjERYWhgULFiA5ORn79u1DWloaevTogTvuuMPgqUR27P/85z949tln0bJlS7Rs2VL/788//wRge9YwICAA69atw6lTp7Bq1SrDvUhMTDTMgtkjOTkZoaGhmDZtGgoKCnDixAmMHTvW0Lla8uCDD1p1djExMYiKisLUqVPx1Vdfwc/PD3v27IGrqytatWqFHj16GITATZs2wWQy4dtvv8U///xjiJ4thMDEiROxbNky1KxZE5s3b0ZeXh5atGiBxx9/XPe+wnGkDbFECIE333wTK1aswPLly7Fy5UrdrebKlSsRFRVVZu0eYG6vBw4ciIEDByI2NhZXrlwpUZO6fft2jB8/HmfPnkVycjLGjx9vJZzbe3ZJezlhwgREREQgPT3dYZNSorR9Leftt9/Gjh07sHnzZoSGhiIrKwtdunTBwYMHsWnTJsyZMwfjxo3D1q1bMWvWLFSvXh2ffPIJjh49ijVr1jh1LHtMnToVy5cvR0xMDH777TeMGjUKd9xxB0aOHKnn+emnnzB58mSEh4fj/fffR61atfDFF19gxYoVuu25o2WtXbsWUVFRCA8Px3vvvYfCwkJMnz4dZ86c0deS2DJbnDp1KmrXrq2b3txzzz3o3r271XPetm1bLFiwAGvWrEG3bt3w3HPPYcKECRVCU5ybm4tPPvkE77//PlJSUnDq1Cm8/vrrcHV1RUhIiJ5vwYIFePXVVxEeHo5Zs2ahRYsWmDp1KubMmaPPiDpalqenJ/r16wfAbOdes2ZNPPHEEwCAX375xWb7wXH2fXWUxYsXo3Pnzk6/P9eFsAPY6to5c+aItWvXWm23FUDJVhAgmVeFCRMmiOPHj4ucnByRkJAgdu/ebfCaA5g9UyQkJIj09HSxfPlyMWLECMMKbVtl9+nTRxw7dkyYTCZx5MgR8eijjxoCCsjOh1aQCyFEYWGhSElJEQcOHBAffvihleeCkjxFuLq6iqlTp4qLFy+K3NxcceLECTFy5Eib127QoEHi9OnTIicnR0RGRlpFqfP09BRff/21iIuLEzk5OeLAgQPikUce0f8PDw+3uYIfgHjzzTeFEEKMGDFC3zZ06FCrFfH06dmzp9i3b5/Izs4W8fHxYt68eYb7SF4geB3pkbIMPuXt7S0OHTokoqKixH/+8x9RUFCge7Wwdw19fHzE8ePHxdWrV0WLFi0cCixVkvebhQsX2l2hDpg9uKxbt05cvHhR5OTkiEuXLomff/5ZdOzY0ZDPVvAp/rGXxxlPA1WqVBGhoaHi1KlTIisrSyQmJooNGzaIu+66y5CvU6dOYvPmzSItLU1kZmaKEydOiM8//1zUrFlTABCzZ88WR48eFenp6SIlJUVERESIhx56SN9/165d0mtIHoT++usvKw8G3t7eYtq0aWLfvn0iKSlJZGVliZMnT4pPPvnE4FFG5v2G33/ertjygjJmzBhRUFAgRo0aZff6vfHGG+LAgQMiNTVVpKeni3379okBAwYY8jRq1EgsWrRIf8/Onz8vli1bpnvZGTVqlIiMjBTXrl0TWVlZ4siRI2LMmDF2j10S9KxbenFy5Hn+/vvvS7w2tt7HKlWqiHnz5onU1FTdO9V///tfvR6W98PeMZ988klx8OBBYTKZRHJysti3b5/Bixh9li1bJoQQ4uOPP7Z5bfr27Sv27NkjMjMzRVpamjh06JCYMWOGHpTH8txkbYgjn0GDBomDBw+K7OxskZSUJDZu3CiaNWum/1/ado8HqalTp44IDw8X165dE0II3WuULJhN/fr1RXh4uEhLSxNxcXFi1qxZ4vnnnze8I448u7NmzRKXL18WhYWFDnsB4c8HYL+vdeTTrVs38euvv4qsrCy9jbF8ttu3by927typ///DDz8YIts62iY48nn++edFdHS0yMnJEVFRUaJnz55WeXx9fcXatWtFRkaGSEpKEnPnzhWenp6lKqt+/fpixYoV+r0KDw8XTZs2FYDZE1NiYqIYOHCgYZ+goCCxY8cOkZCQILKzs8WpU6fEW2+9ZXU9Ro4cKVasWCHS09NFQkKCmDp1qqEcW+2A7Lm1de+pLs7eb8vPu+++Ky5duiRMJpPYs2ePaN++vVWeNm3aiJ07dwqTySSuXLkipk+fbtPjl72ySmqrHK2/M+8rv5YlyX/Lli0T0dHR+m/yfkPeyCzz/fHHH/rv6/F+47RQf/r0aSv3dJX5c6ucj4eHh0hPT3coil15ft555x0RGRlZ7vVQn+v7NG7cWAghDNEW1ef6PiNGjBCXLl0q93pU9I9qQ9SnMn+6dOkicnJynI54XtGiPKtPxfsIIYSLJrhLcTRym0KhUCgUCoWi7PHz80NMTAz69+9fZmsaFbcWQojSeb9RKCozLi4uVm6yLLFcX3Czqch1qwyUFDW4qKioQtidKsoeV1fXEhVQ/9b3pqT3QQjh8EJjSypSG3Ujzk8hpzK2rxXpeb0pOGt+oz7qU9k/luslbOFo1Nl/W90q+odsHWXwaLjqc+t8SloD8m/ux0qiNJE3geII6DJKa4ddUc5PfWx/SrJdF8K41qYifSrS83qjP0Io8xvFv5BGjRoZXGxyTp8+7VSQqrKkItetolO9enW0bt1a+n9ZeTRQVDxatWqFGjVqSP8vS9/nlQmKIG2LjIwMp73jAGYzEAoaZoujR49aBam7UdyI81PYxsPDo8TggUlJSbhw4cJNrJFjVKTn9UYjhIAS6hUKhUKhUCgUikqMEML54FMKhUKhUCgUCoWiYqGEeoVCoVAoFAqFopJjV6hv0KDBzaiHQqFQKBQKhUKhcBKS1e3a1CsUiusnPDwcAPQFOZTS60cpuWDj22WvaUmvL62H4Sm59xo1alRpTkVRAZg7dy4A6AvA6Dlwdzd7Ka5fvz4AoGbNmoa0atWqAKCHTk9PTzek9Pz5+PgAABo2bAgA+iJU2i8tLc2QxsXFAQAmTpwIAJg0aZJeB6ojlUHb6Rh5eXmGsgsKCgAAWVlZAKAvDKft5IKOL27z8PAwbL927RoAYODAgVCUng4dbsfBg5+X8P8MHDx48CbWSKFQyFB+6q+D1157DQDw5ZdflnNNFOXNL7/8AgDIzc01pCSwkEBCwhcJ2OT3lwRt+s2FfBJkKOXCvuWCdr4PwfN+8803No9NKQmI9D8JTcOGDbN/QaDeD4Xi1kAAyCnvSigUCgdQQv11cPjw4fKugkJRYVHvR9lDGnp/f38AxZp30k7LvJXRdspPkHacBmxVqlQBANSqVQsA4OXlZcgvm0nig9OqVauievXqhmPSIJGXweuUk5NjyMc1+XQuVB7Vmc7B09PTUN7q1asBAMHBwVCUhiIooV6hqBzcUKHe398f//vf/9C7d+8beRhFGeDv74/4+Hi4ubmhevXq6Nu3L+bOnat3zAozO3fuBFBsEkCCBmnmSSPPIxlybTgJJCSIcA09admpPIKXS/vb0tTTviTw0XYu+NFvykfnQnXmdV+0aJHh2JQOHz4cCoVCoVAoygelqVfobNiwAb1790ZcXBz69OmDmTNn4qOPPirvaikU/3pCQkIAAE2bNgVgrY2mgRdtp5QGj3wQSb9JC07cdtttAABvb29DfsrHB4j8+DRArFKlil4WaeKrVaum/2drXzoWaeppgEuDUxps8nL4LAMNPik/KSZoMDpmzBgonKEIQG55V0KhUDiAEupRPKVNU83UCZG2lBZsvfTSSw6XRR0PdTjUwTz//PNlVe0bRsOGDdGnTx9lPgEgIiICQPGCQHoW+IJXbvNOggq3S5cJVyQMcbMG2o/gdvFcaLNVBw6vA5VFghq3yeeafyqXnmmZBl+hUNwKKJt6haKyoIR6hRWxsbHYvHkzevbsWd5VUSgUAJo3bw4AVuZwXINOGnquHaeBFjfBov9poMe169yunZuZEVxT7+7uLh3IclMzXgb9T9DgkupEXnSornyWgsqlulJ+Yvny5QCAp556CgpHUDb1CkVl4ZYW6r/++msAxR0hTc9y7Sq5XKPFYdQ5UGdhMpkAAN9//z2A4s7i6tWrAICFCxfqnRxNj1NZVAZNKa9YsQJAcafIOyLSBI8ePfq6zr00PP7443BxcUFmZiZ69uyJadOm3fQ6VBQ2bNgAAMjIyABQfP+4zTzXYnNBReaaktvOyzT1Mu83XENvqannZcmEK3ofeH7uKpC7SyT4uXMzCXo/Fi9eDAB49tlnoVAoFAqF4sZwSwv1CudYt24devfujV9//RUjR45EUlKSblurUChuPqtWrQJQ7Nude4ohZPEKuHacFBQEbSflAtd+00CNNPV8cMkHt5b14YM+KkPmQpWblPGBLw1C6RpQXfk50KCU8pFSh/4nzb3S2DuKMr9RKCoLt6RQT411q1atABQ37tRpkMcS8mBCtvTU2FPjzzsL4sKFCwCKO7Lc3Fw0atQIQHGwFupwuNs27s6NOhyqG3VgpCmOj48HcHNt8bt3745nn30Wb7zxBtatW3fTjluebNu2DQCQmpoKwNqrDRdaeCAnfv+49pv7jOdmENzTDDd74EIVCTh8P8tjyrzccCGKfsv82hMkbMnMI7jGns6BBMkFCxYAsJ4pePrpp6FQKCoqyvxGoags3HChPj8/XzddAMyCAZ/GV1Q8XnvtNfj7++Pw4cNo3759eVdHofhXQaZ+tWvXBmA9WOS+32WmVNyMiwdFI+UDmQvSgI2bfcnK425QLU24+CCPBsq0Lx2LLxqn3zL/9nRM2p+bVRK0P7fhp+2NGzcGUByE7eWXX4bCFkqoVygqCzdcuu7Xr5/h9+TJk/Hhhx/ekGOtXLkSANCkSRMAxVpw3inQb74Aizo4vniMOiMqjzT7loFWyEyFyqC8XMNLZdO+VBZfyEbbqQ7z588HUNxxUUf5+uuvO3BlnKdevXp45plnMGPGDKxZs+aGHKM8iYyMBAAkJycDANLT0wEUCyfcvICQRX7lwg7/zYUtboPP7d65pp7uO8/Hy7Xcl5tKyJCtA+BedGRmE5SPb+f7Ubn8nP73v/8BKH53lDmEQqFQKBTOc0OF+piYmBtZvKIMsXWvaCChUChuDt999x2AYsUEDXS4mRYpAeh/rlHnPtv5wIoGVDwfhwcw46ZVfABoWT4NkCnl5mB0bG7uSHUlxQiZRdKidXImQHXhvvRJSUMplU/1oHMhxUmzZs1snruCUDb1CkVloVLZwZBNLjXG3N6Yd4SUUqNO+agzoP95ZEzqDOg3dQKkHeU2+h4eHlYdEp8Op2NyTT39pjpSPrJD5h556Nh0DWj9QFJSEgCz2YzCmkOHDgEo9jdP14vWVdA95vboMmGH/uf5+AJD7vqPmzfQcXl5BDcp4Bp6rpW3PCYXxPixZbMKvO7c371MUORecripCBcAKeXvpQoSpFBUJJT5jUJRWahUQr1CoVDcinz55ZcAgICAAADFtvRcOcA19ZRy0yi+GJnb5MuCo/EBHw0MZRFlZYNRW2VwUzGqG9e4c7/zpLGntVmkqbc1oLW8BqQw4celc+ZmlOvXrwcADBgwwOpc/t0IqIiyCkXloFII9aSN9vf3B1DcGZA2OyUlBYC1dw5Zx0XTsDzMOJ/Slmk0S+rAuJaTOg7qYLidMnclR3Xji4mprtTBkQaf6lKnTh0AxQvsysPPfUWENPRkO08aenp2uEDAnxWuXZZ5weH25FxLLoPb2PPt3Oaee9vhWnbL75Ty94DPPsjOkZtU2Fs0KXNvyDX3BI/KS9eAhLeFCxcCKNb0P/PMM1AoFAqFQmGbSiHUKxSK8uFZbSE2GQFt0Ba1KsoWPz8/AMWDde75RbYImf/mnmRkC7O5AoMPuGgAxwdcsoEcHxy7urpa1U12DG6nb2nWCBQrRmgxOzkuIGSzE9x1K/fBT/m444SlS5cCUIPIYpT5jUJRWaiQQn1ISAgA6L7fyVaeT5dSo0xTw7JOgzoLavR5kBJq1LnXG74gS+ZNpKioSBpVk8qklEN14X7OudaS6lSzZk0AxRp73vHRNVEdkxmaxSENPV1Pmc28TBPO771M+83XYfCUB9iRac1l2m4+u0T7W2r6uQ09D9ojC+7jqEkFlc/t+rlwRnCBlHvb4SYh/H2je6ZmoW49qrRujUwA9WAWHbO07d65ytyj4qCEeoWislAhhXqFQlEx8NLS1HKtxa3LkiVLABSbFtIgn5ssyWziCZkfesrPNe400KOU4KZVPOUafF6uZf1oEMf9z3MTN1tYDvy4Fxs6N6o7KUwoHx8c8lkNmccgKp/81ysI5f1GoagsVCihnlwokma+bt26AIq109Roy7xzyPxtc283XOPPF05RY899lstCsQPWWk0eGp27ZyOoDjSlTPnp2DRbwKeWuYaea0mpvH+rJ5Fdu3YBABITEwEUa3tlmviS7q1lfoL7ZufPEl+gyIUhrrHnayi4eQO//7IFjpbbuIkFF+Bk6wm4MGaJi4uL1PSCm2jw+vC6cmGL14O7X6R349/6TFcEGnfqBACgeUeTlkaGhTlVzl2d25m/9NY2mK2P4GUO1g2hPbN5OUqYLH+Upl6hqCxUKKFeoVBULMiWXmnqbwwNGjQAYK1t5l5vONxeXBZwjA9aKT+fEXBUIy+D19PV1VVad2cQQlgpMPigkOBuaXmwQZltP9fg07qGtWvXAgAGDRp03eehUCgUN4MKIdST/3nS0Pv4+AAo1m5TB8Rt6Ll9NNc8yuyiuccZ3thzrTm3OebecIQQVnbIXMtI+1CnTfAw61xDT//zAC3cZz79pmtC+amDWrZsGQDg6aefxq3Mr7/+CqBYQ0/Xk9uXE7bupeV2HtKenhX+TPD7wkPXc9/xHG6awJ8jPhNA2LLBp228TrIZLZmQw68VbZO9V1xTL0s5svUDXMPP3SqSxp7qqSLRlj2iVSsAwL21tA1ttFR7NHw0I/iho4cBAL7WVPf3jxhhKId296EvD2hpFy0lixdzYG64/H199VaUJfbMb65/8KZQKMqGCiHUKxSKisllLd2zcKFNIV9ROtasWQMAaNq0KYBiLTTX1HPzLNmAimupZR5laLDPF+jzgVduBVqoyp0EEKR84coduobcrIsrXvhAmdvu16tXD0Cxa9WxY8eWyflUPuyZ33jerIooFAo7lKtQP3fuXADF7tzIhp46OB4Zltvk8giwXAsqi/Yp03ryqWaujeXbicLCQuk+Mo85BC+bOijqVHkAFq4JpnOn/HRutJ06JurkSZi4dOkSgFsnAm1kZCQA4Nq1awCs/f3zwDbcHIFr7GXQ/vx+U/ncHR9/Nnkq02bLYi7w54ovkLQsm69B4djzWkPnQGXxc+TRkmWzEHw7n8WSeRSSLaTks1+kwad4FkpjX3a0Ig36EC2l3+Sm5ooxdd9rTv0batvJ6J4epXqsHPrtzfIpKhBKqFcoKgtKU69QKKT8tmiRzQWzitLx9ddfAwDatTMvFOUub7lmng9KufaZ243LbO25XbrMjItS7gu+vLA0bSRFBp0DDe744I8PqLnfeoLPYhB89oNcKysUCkVFp1x6awqJ3rx5cwDF0VDJMwxp5rmdMfdzzcOBp6WlAbDW/Mk09bJFZryxl3k2IVxdXa06Aqq7bOGarCMhjSv9T9eENPbUUVHKj0O/aT86dzonPutxq0ARY2ktAvcbzzX0XCttz3c6wa+3zF5cNqMiE5C51pn7mqf60P/ctp+2W9aF27rbW1wp09TzayErRzbbwWcCZAGLZJFn+fGpXvxe0runNPZlSActHaClpFGP0VIvtv2Qlt6tpaTJd3aldZb9LAprCgsL0aFDB/j6+mLjxo2G/xYsWIB58+bBzc0N1atXR2hoKO68804HShUAKo45lkKhkKNUcAqFQnGT8PY2S798wTz3Q0/YcwMqizBraToFFA8u+SBV5gbYnrebm4Wlpp4HHSTFBR8McrNNPgjlg0mu+OADcXI2QA4dXnrppTI6u7Lnq6++Qps2bfTou5aMHDlSr/v69evx+uuvY8uWLQ6UqlxaKhSVhXIR6snLjUxDL7Mnpt/U2JKGnuzQudca2WIxvjiM4PbQvFOg/HRcqtdtt92m27zLFmnJXMvJOll+jtTRUJ14oBXLulimdC25T3/ixx9/BAAMHToUlZnUVLMqkE/Vc824TGvMtdT8ujqqseezQPQckMkA3y6LJCz7zf3c24KbG3DNvcx9ob11Btw2n78vXPDkmnXuvYbK4wIoP64smi8Xxrhtv9LYlwEeLM1nKcFt4r3Y/zw/z1ePpXx/hV1iY2OxadMmTJ48GXPmzLH633KhcVZWlhMuR1XwKYWisqA09QqFotTcrQ0GW1E0Ik0oy7sAfAcgISCgXOpVUaFBJnfLy4OZcfMtrj2WRWeVmQjywaM9t6YVBVtB1XiwQFJg8IE1n+Xgg1M+WOTXhrt2JcVNReW1117D7NmzkZGRIc0zb948zJkzB3l5eYiIiLiJtVMoFDeDmyrUU0h08nZDjaRMI841g7zDokadd5A8Kivl527cCK6h5PXh5XItuaenp1Wny9cFyGzY+XS5zIsK79x50BhCFnGUewyhtH79+gCA7777DgDw3HPP2axnRYW0sXSv+UJA2XXiNurczptP9cvsymWaf9k6Dm42IXNVyLXPMg81XPNv+Z3PTBEym3uZByfuf14W/McWrq6uVu8dN3/gNvGyWRR+rvwaEzwCrdLYXwdkE39ES0kjz23kSfPOHwmuoafBH3m/uV1L27PtR6Bwgo0bN6J+/fq47777sHv3bmm+8ePHY/z48VixYgU+/PBDvU8uGWV+o1BUFpSmvhR0f+QRAEA9TRn2xEtmf28xSebf6UdUj6S4MfQaNQpAsezjoglJlzXXgb/+8MNNqUcPLYiZb11tA6238zcnVfIBl51AvbN/Y8iEYPz01eqbUq+KyldffQUAqF27NgAgMzMTQPGAiZsc8gXxPPAeN8PjygPZQI4PzGS+3CtSTALZQJYPmGXnSNeYK3v4gJnvz93P0j0iRw8VyR3wb7/9hvXr1+OXX35BTk4O0tPT8dRTT+kDWs7w4cMxbtw4xw8gccmsUCgqFjdFqCc3bi1atABg7b6NsBfdk2s3eVhvapzJvpprIGVTzFxLyzsB3ujbw8PDw8oWXub1xFLbb3lOfOEcn3qW2exzLS2/BtwFHtWTwtVXNkwmszQrm3onZLbs/H/q8PlCQW73zcuXmTXYcwfJ7y/XrjsrXFWvXt3umhF73m/ouecRlelZKo2phru7uy6Ack0/vwb8eITMGw+/9wRfh1AWGvvAwMBS7RcbGwtAbjYjC4wkE2Bl/xOyeyRb28P/1yNZH9D+OKeltL6XHmtqhrRiDseb00Cy7CDPmHQraf1mgpbuonJodKgVnB1nThua11sV3vOQ08+dLAaErJ+R7UfPIbUN9F6scwD15QAAIABJREFUW7fOqfoQJWnSS8vMmTMxc+ZMvfzPPvvMSqCPjo7GHXfcAQDYtGmT/t0uRQDy7OZSKBQVAKWpd4L7OnYEALiQuzat30F/c+KvKeizNDdhKVqAJ4Xieuk6cCAAwIdkH38t1WzYfRPNqbeWL2L9+jI9fk/NLMtP++1CX0hDT/JBY4ud9sEs7PUGBg4aBAD4SVuY/W9DJjzLtNB84CMTULkwb8+7jaw+nIro8lY2EJHlk5lx2RPu+TXjChauUKnIfPDBB+jQoQMGDBiAuXPnYseOHfDw8ICPj4+DpjcKhaIycVOEeh8fHwDFWmjCnvcN/j+PEso9xHBbXdKw2LND56HRaaER2dLLInLao6CgwMr+V9bJ0rWhdQY0Pc/z82l23uFwu2XSZFPKta1UHs12VBb7Y+qQZIvgZJp7/kwRssV1XGMv06zy2R1C5qKQsGdaUFrc3Nykwgyvu8zOn96b0j7/tnB3d5euN+HvIUH1lM3syTT7Mhv+lStXAgBGjBjhdP1Lq2UNCQkBUOzSktZ+8NkHvjiTm+FQymf26Ddv6/jzJfPyRNC1ojbQ1LQpAKAVOU4hhYa/lpJNvK85CXzXnO7+r7Y9WkvJNp8mvMj/PUWqrdtV+9JZSy+Yk7D5AICsEeaI0SIjQ/oOyjTrPEo3n4ni3pj4+hVqO6lNpngoFXX9UWBgoD6jNH36dH07mYA5jYD12giFQlEhUZp6B/DvbO5oXEhLSm7XrlEGY34vrQGspgXXirtyBQpFafgP19Az23V94aKWemkLGLsEBQEAftuwwVDefVp5tF6R+up9P/9s8/hdh5ilrvp8YSMdn2voqWATgCraAepZaPb/pdgbeHBzHG4GI9MuywZs9uzM7Wm7afBgcvgMyw8+UCfXxiSEc2GefsuEfD4IJPjA6l+DEuoVikrDDRXqyZa+qabt4fakXNNiz+6Z4AuXKCV/99To8uiu3C6aa3YoGil1BqThuV7S09OtwsHLomRa+hIGrCPByvzgc3tlOnfecRHcqw5di7p166Iis2rVKsNvui72fKDbC+rDZy5I80laOllwIIJ7jqFU9qzzZ5w/mzLBwlmEENIIrrz+sjqWJYWFhVbnLBNA+f9cg8rvNcHvOdfA0nsdHh4OABg8eHAZnd2th/s5szF9VsuWAGy4j6fBGg32qPnqrqWkAPlVS0lz/4eWpmnp3WuNKe2nKexprKgCzZYDSqhXKCoNSlPvAB72MtTSUtKiaju4aB1T6z5mX90JF4BCAG5JSWVbQcUti26iThpx7vqPIBeDWucr07Du++knuLi4oPMTTwAofrbv0zTyf61ZAwB4UBN065PQ9oCWck09/U9CGHEBxhfH7kt0a0ImDzTo5mZxsiimfEE8t7Xng3Q+OOWaf0LmHYfg+5OZUEVCZkJEgzxSypAJEfd2wxdQy64dv0Y8v0KhUFQ0bqhQT5pzstcme1KyG5d5gJB5MOGNLw/YQilpWSnl+3ONIDX6pKmnlKZxy5rc3Fwr+2A6J9Lk8yidMq8ZfH+Zz33uW5/gWky6ZosXLwYAPPvss86f4A1gvbbwk64Hj+pL98peTAHCXkRZus50PWTrNeh6y4IF2QuEQ4IC925UlgsVZYs0bVGW9vO2sJwR4O891YtfO/5McxtpLhjLTFm4hr+kID0KI+maCaFHY/NosgrJ+jTYa6M9rx6aHVjLhtoff5uT37Wf3MaerL5o0EfmZNrgNEbT1NfPylLCdHkhoLzfKBSVBKWpL4E7Nbtk6mf0uWfqgFwk2/lUpabFrE+LzPqZV5XFaN5y6irhQsG4+/HHAQBV2mgbOtIfWkr2CGe1VBOWEjQh6MDatSWaz+z76Sf9u+VAo9OwYQCA+vQs0wwBLWyk2SjS0PtrqafZ/zqyk81pKsytiwvM74VWXpeRI83H1xar3uo01oRgUmzQ4JAGJjTAoEEpNyPjrnFlC1t5AD7SsMueAa75l7m6pOOWt0BteXxeRz5Y44M+brbFzct4YDju4pXKvdHKngqLMr9RKCoNN1Sol9my86idvFGV+WLmGj1Zh8W1orwx55p+avypseYeT8oDmYbZHtzrC2ma7dnac6843FNRecOjA3MzBS58UH46f5m/eHs+rPkskGwxHQlfdN1k5hP8ODL/9teLq6urle0698Ak8wJ1M7CcEeDXWGZrL5udomstO0/ZLA09I7ROY5g2oFHIISuv+rRBNwO7X0svaqnWfmiuVmnQmXfSnF6NibFaL0TvqmX7X7FX+PxLUEK9QlFpUJp6G3Ts0wcA4EMdVj2W0vZTWprHUlrNRXGDSLtJ9sja/v6aVhX3mM2UMg8pjf2/nXs0W3Z/elZowSFp6ElDTtJVjDkR2sJDmRcbR9Fn2WuxlJ59epab0UtAFdOEOM8/zanXFcAV5hbGG7rLQ3/N7CJPi0i7f9my66pvRWXRokUAgFatWgEo1pzTQIMPprnGnQYcfKE2N8cjZIoMmYZd5ptdFrBMd6Fb4lk7Dg2CAXkgPe6r3x5cI8/NsLgtPXeUYC/oICkSGjVqBAAICwsDYI7OqlAoFBWBGyrUU+PIbVe5v3muaeOeWfh27k+b2wzbm1J2xsa4vJBF3ZR1vvaig3LNPF/0xferKFDURm4OwO2nKaXzIl/S/FnjAgLX6nLXg/Yi+HItI4+FIHM1KPOff724urpaHZvPBsh845c3vL58NoTP8NnS7Frm47NTssi1ZFaxZcsWAEDfvn3L7qRuMfShBI3p/GkDuXnUzK9OmiPo6jbzmvebtAQKJauoNChNvUJRaVCaehv4kPKRtKXMF7iVmzZyNUKLv2jKmZRRNIdMdtEtSd2paTf9/gIAeGkLi7OUjf0tC9nKH2Eh5skbjS8JS7QAkR4VeuboWSNb+oPmZBPzR19aTmr1avX848bj0bOtd+6ttZSCBcXbLtAN5veA3iVNKmwVY07raRr7LStWlL7SFRByDUtOASgluAtUWSAtGpRSfj4oJ0UH7cdd1DoahZUrDQirgIAllmIfFxcXuy6LZUEIZWaYsoBysiCGXNHBFRxUP3L0wAN90TUn2/3rCWZWKVALZRWKSsMNEep59ERq/GThtksbPZHb4nINpD0NPf2m8mgxW0VCth6AkC2UK230RNqfNM7fffcdgPKLnsijAtMzwa8DPQM0rc/Pm8/6cGRT8TJ7bLo+vKOn/7kXGTo+p6y83JC2GZD7o5d5lSIcFQBvFNw0RWZCwmfuuD96/k7I1uDwfDS7o5CjP8X0GtFjd3WXOaWAfJ9r6WZzcn7/P7qQrKhkKE29QlFpUJp6C9rd9x/zFwpdTvbLpKEnzTt1aKS2Ii0muWsje2fNjlj3jqP78iYtp1awr1lT70IzBIpbjkc0W3kv7dmpp2nsCS8e64C8ztAzQ8ITrcPQZonyjpRtPXVIQ0+zTn+ztCVp5kkQjjEnSdrLcAVm7R4JBHQe9C5pMxI+2rvRV/OKs/UW8YrD3fbywSgPFicz/6JBONfU84EPH7jI3IHKtNz2TBKv1zzMMggaX7QuMwezN8iUmSLKZjm4Rp4HmuP3igbiXPnETfLq19eXDSsUCkW5UqJQHxgYWKpCEzS7SZkbNpltL8E7IO4dh6fXa5es+xon5epOLSUzUbpKpOjT+pjDl81pIAU5JU9nVA4tpD2kpaFUzl5jwbSfZlJR1K+fdMEaR2YTL1tXYG9hHD8edYTLbvKCxiQtQJc9YUXW8XONub0oqTLvNzJf5/zZlJVH+eZq2920Z4Pr0t0ytS+aOY1uXuPJMlKQY02WpruXOG1acVl23hOZYGd5zb6h49AzfElL/9LSz2O0L6u1VBsFkEYvHTj8D4AiIPAbFL8T9MpTPu286e/k6dOlz6i9iNOyNQSyfDz19/dXix7tkHLJ/CB49TBHCSdNPGhwSYNAbfsZbYyntEeVGKWpVygqDaqttYRr4t1ZSvIgSWQkoOSwlMfvyWVpNW0xWa5WgDY4yM8yHkZx6yCsvpjRhwT2LF7IpjVdS1PMSXzr1sZyyojktu1QVFSEuqdPmDfQO0DPsNVDb7LeXKR9clF8fvRwU4W1V8BdS2ufNPs8vBYQcP0nUQ4sXLgQANC2bVsA1ov5uS90PsjkC79lKWmZadDKtc6ODn4Je4N+2o9HsnWUvLw8fV+qq2yg7Kz5F3fdSshM4HggP655lwUx4/mp3jQr8+233wIAXnzxRafqX+FRQr1CUWkoUajfvXu3U4WFhppV0XfcYbYd8PHxAVA8nUnwKWbZb+4BhsqhcmvXNge84R5HCHtecXi+mt00GwhyI0iLFsk0gsxoNOE78CNzupvWCpJ2lcxvyHynn5YO0NI22gLZi5ogpNmfJnxtTqtrXjgs68ztoelakQ18erpZ2iPbapnLPG4zTlBHZulqzrLc06dPA7h5HdaPP/5oqBetd+DCDMUW4B0vXTeqP+XjEXtlAWz4dedBgwiyqZeZOxC9goMBFFufkHULiSFV6I/2WkrPIC0wJRMvWpytaUL/0haYkstEwNqHP8E19QT/bWm+0PL+2431ekJLX6I4Bl21VFPVRv1jTn8HAr8GkAPsHmZxolRNkg3pnTlsTlI0P+bbpk61MjWh+tM9pPPktvHclp6QuXuk/G5ubsjLy8OaNWvMp/rEE1DY5rJ233x/0Tb4a6nWNgptBiZ+zx7Uq1cPikqMWiirUFQalKYeQLImMNYkm3ZqwLh2ggQTkshILk6UpCTcUzkxtL9WwAFtsybI1M3IKLOFk4qKxQ5tkMIFyvs0W/J6Zmsj+JDNOg0kyZae1mtowvyeHWbp3uhTpezJ0urlRWM9PbwyCfVkWx9jTizfgXyY35FUFAvztD+9SzTw1SAb+2FPm81gln23tNR1Lw9q1qwJoHjAwbXCfPDHTYXsmRwR3DkAaehpwMP91hOyAZ0sSqvMXt2oppEjhLAKHEd1lSlXZOZSMg893N0tDbS5P3qZ62TuQpkPhmXRdblmn5RNCoVCUV6UqVBP2lTSGlLjTSnBtca8A+F24pTKfIbz/e15u6mIfukJWd1558w191zTzL3c8GtK+/GOkK+DoHJulmegn376yfBbtjiNoO0kOPBBEQlX3BsQtze3ZyNPyOzQZfeNa4+pPg0bNizxOPZo0aKF0/vIYh8Q/JngM2zlQZUqVaSuC/msCp994rM2XLiztZYAKA74pJBz6Q9ztLML2rV7IPBB8x+aaeIVWzspKifK/EahqDQoTT0An1RNpV5PUyNy+ZVr7kkDzzX12vbLWr6qZxOlQY8IFQr9303esWMAgBRNw5quDTIa+fsDAKpoGvIETc7Mu3QJNxOTtujd6wHNw8cO7Y+7tXUhvr+bUzLDoIW+V2BeAF4Eo6aeNP78N/OKQ+mwV8wa+xhtxuDXxYtLdyI3CT4o5gMHrt2V+afn0Uy5xp5S0jKThp77qbdnp25vobxM4cKVBTIKCwv1AbXM4489jzyOzi5QW0uzJfQ/Df74oJVr6nlbzU36CJmrVK68umVQQr1CUWkoU6GeNPSONo7c3lumBdUrq+3Pj+NoB8a1sbIp5rIiMzNT99UvO4a9qWV+DbhwQB0Sn+6X7Sfr0EhTzzte6sB48JwbBQ/JLvNLz58p0q6SAME7ajo/somnjp5wNLANN5/h2mH+bNHxSOii9SYNGjQw1NNZ+PEtz4cHNuLPFL92PEovj9xckUzCPDw8pJ6NOPai93KhjLtCVDjOxnBz8LPEt94CAPw2ZYqypb9VUEK9QlFpUJp6C5LjzJFT0uvUAQD4k09w8h3emO1ADZ2mqU/RtKlxBw+ijlaGQlEaUuLiANhwPSoJLHWjSfrD/JB7aoKaF9n4axp3odn60ytRpS6KNfSJKF5IyWM+UEo71rO93V9bf4InnwQARN5kF6uOQoM4SvmgjZu50YCCD7Bk5nOywH3co4yzgcTsubp11j2opV96e+aWjro8pnO250OfNOZ8YM2PJxusykz9aLAn838vC/qmUCgUN4syFep5pFeCR+fkmkCZT3XegcmmSR3VuPNG11Ff8M5SUFBg1we/rA7c7pnD7aHpWpDNO3Xy5O2F2x3z/biWlv6njovyca84ZQ15HKHj0bMki8TKBQbuIYVro6n+PGop19bK1jLIBBOZjT9339eyZUsAQOPGjQ37yQQYbv5A5dF9pd98BsFyG917Loxw0w6qC82KUORPeqZolqYi2NgT7u7uVu4c6drz9kbm3UcmZNJ1Cw8PBwAM1gKHKRT/SoqgvN8oFJUEpam3Qc1rZo39Jc09ZINmzQAAVbppGUjO1IJGJWiBgI7v3GlwLahQ3GpkxcebXT/WNa8EEdeu6cIwuVONiYkBACS89BLqnztpdltJLjH52JCvSc1iv0mz768l2ru2r/SncEOhARANvmiARdv5IJFr2rn7XkplJoY8tafgcDYYncx0i/vbJyzrw03XZHWQ4WhdeTkyM03ZOgXZPeAKALqnlJLJX1pammH7LYcyv1EoKg1lItTPnWuOl3n33WafkFz7y21zecdgr6MiuFbUXmfBtd1cM0e/uaszOq6zduR+fn66hpmm2WW22tzdGp+NsBdBlpfLOybq0Gxpcm2VT/m4NpdrvL/+2uxM/9VXX5VcBedYvdockZSfP392ZN5puE07CUGy/fjUPJ/JkHlG4Z6Y+HEJLsg0adIEANCoUSNDvWSCCX82U1JSDCndHyqHnjPLRXr0nTTuVCYJIeS7n1LanqotGKdovlQ2LTwkG2kfHx/dlWZhYaFeFzpemzZtAOCGDnAtbev5O8HfMdrOn3F+T/kzoWzrFQoooV6hqEQoTb0DpGkeQOr5ax5ANO1hrjYlmXDs2K3r+UChsEHmxYu60F8SuXnA5SuAL/nf5+tSeCwH0tSb2G/ixlqBlRoyH6OF0DSIpIESH5TRgIcGoY4uVrbny91RW3jZfo5GlnVm8bTMZt5e3e2ZQ9pzkMBt42WzGLx+fHBHGniaiaLBcEZGhmF/Mq1butQcW+GZZ54psf6VBiXUKxSVhjIR6rmbNa6Jl/ka55p3R32E8/z23KrxDpEWTsVpixFJU0eaSLIl5hp8Gb6+vtJZBqozdeaJieYFh9c0Ex8KWMI1uTySqT33b4TM9Z1ME0zXgjosqqdMC8o9GF0vsoV/Mj/yXBPO7appcCUzR+DH4VpZfr78OHwBI/fnT9tJ4KX7KlsbwMnMNIfijI42r0SNjY0FAGzdutWQ75FHHjGcL2nJgeJnilL6jwRJer5J0CTNPB2bzoWEFno2KD9FciZf+zxytKVHphu1dNDNzU2/l1RfmetBHoXZnjtGvo5BoVAoFIrKgNLUO0HqZbNQowuIjz1WntVRKCo8bg8+iMIVK5Dg5wcAqE8xHex5O+SxIbgGv4JB3q5oQTYN6miAk5xs9uvPB880EOL5aTtfMC5zMyrTWl+v/bos3/XAA+DZC+QmOxd7fu25Mkdm+iZbdE8KD26eRveQ7jXde5l3nkqP0tQrFJWGMhXquVaUazllHQbXStvzFc7t0XnAF74/rxdNp5K2nDpc0tyTHTRpInnodVkwFEuojjRVe+HCBUNKHUdAQIDhWLyjI7idMHU0PKAKnw2R2RnT/qSdpQ5MtvDN3myIsyxfvhxAsfaYu/aTeaPh95Tbwst8kcsEAK6V5Rp9rsmn/0kIo+Nxb0G0HsNSg255PILqQcf/+2+znQpN4cvgCzEt7b/pmaPnu662qJVmoqhO5CufBMgEzcyM9qdngt5felbo2JSPZiMo5bb0tWrVwo2wTucRY2XRk/k95+sm+LvG2xmF4l+NgPJ+o1BUEpSmXqFQ3HCqpqYiNzcXCTAPbOt16gQA8NP+dyFbe4rmTNZKJExoGnpRQeVs7u6TBnu0yJgG3TQwokE1DZxoOw08aNBIwesope18cOioPbpsUbFs0G5Pg29v0O1MXWTHlA3UZXXl5cv+55p5GqzSAJmbJtKgkczN6N7SAJ7Kp98hISEAgP/7v/9v79yjrKjvbL8bvASFLEGwDS9BROaCEYlcJRI16IhoHMG5EEVF5GkAAVERXGRmomvmOjEZlYhDEkcBUUGMDxCWtoqPaBITMGOcEJ8hYkg3IPJGRZA+949T+zz26V/X6aZfBfuzFqs4j6r6VZ3qqu9v/76//Z1aZXsTg5V6YxJDnQT16iCi+ceqwGvOvebWh2zaeNNlri9vxswR5jCo5taqQs/28earw6tcqnJPxVMnxVZWVmaOkdvavHkzgBx7v0gF5bEwL5kP6VCeL9vOz5mTz9EFnkuOJmhecyjPWJfqABLn136w6ERAVehVeddRH82l16Fvfq7HpyMWqsqq/7y+z2uG+2UwFvJMJyHVmNul6h2n0A8ePBhAocuP/g3lHjuvY7aVijr/Xvj3EwqWVLHnOeHfCYMg/n0dH1nAKvy76dGjB3ZWe5TxVFZWFjgzhWoJ6LUVGsHL3Xbu9hYsWAAAGDNmzEG22hhjjKk/rNQbYxqco7dtw4YNG/BHAOvWrcO3ogJPpcydj8u5byL87Gc/AwD07Zs24mcHiB0fKvRqdcvvqbMKO0ja6dPOtObUa6cx5HoTZ6Ua5zgTSh+LU8mLIS4XvdgigyFLY03Z429AkYhLvs/v8TekEMP0Mv6m7DTyt2TnkYp+4rFSb0xiqJOgnp7lL774IoBClZTE+dCrjz0/5wOSDz4qjrzpUh3lELV6vWt7uB7VbeYa82ZMlZ0OJFQ6u3XrBiDtR5+73V27dmWUcyrzFRUVeW2mskq1v1OnTgCyDwY+SLQqryrPWgBFc765n9BoRWj4PPSbqL3bwQ4l33333QCALl26AAiP2ug1oEGCziXQoXT1Io+bZ0FCjie8tvj7sOAMXWnOOeecvHbx9+LIjSrpul/mv58RpaWsXr0aAHD++efnHaeux/bkVvwNjc7wGuM1yt+UufXMtddRDD1XPDYdndq4cWOV3ws5KFHRr83oz5dfflkwmkN0XkTICYpoFWe95pxbbw5rHNQbkxis1BtjGp3y//5vrF+/HmdEin0nfkDFPuqzlKT7xBh0+eUAgJcjf/jGhqlI2inU6qZMdWInTC1JtaiZWrCGOt9xDjH6eZyCH5cHr/ut6vtx7jXFOvSEcuHj9hd6XyfH6/wGLT7IpaY4sl0Ubtj5Y+dQJ8knFk+UNSYx1GlQz5sjJxDFucTozVYdT1Sd5vZ5U1ZVOu6hEHogcUicw6vq061+9nzA8qGwceNG/PWvfwWQVUFVeWf+MhV6PtyJ+pyHlF1VqKlIMyebwYN664d85+Mq2fKYeTwHSygXXHPR49IANCDQvG89T1rWPqTG8jfl9zmKw/PKEZmnn346rz2vvvoqAODiiy8GkL1mee1wezqhktcYXZH4vfPOOy/v+Dg6xcCC149OxKzq3KhtIrdFD3yee16jPFYdDVLlXhV7Xov0vdd5G1plmb81R23og18TmjdvXvC3Ebq29G9Al5rCohVnjTHGmKaMlXpjDiNOjibakl8vXdpILama9158EZ9++imOGjIEANA2qt6cUeyj13x/6JWXAgD2Re44LFC78oEH6r2tQLYjoZ1KdgzYcWGHhx0cqrjslOnk+1AF17jOrq4f8nAPqeQ6UTxkIasdqKrapal0IdEllH8fZ0+rxCn1mt6poygqOLATGrKvpUKvozOq2Ccep98YkxjqNKhnnjHzj/VmGvKnDz1AePOkskjFjA9ALbGuhKzRiLaP22H7meesk9jU8WTHjh0ZVVP9zvnwLi0tBVDoy65tjRtapurIJR84VOq55JCxnpu4/Gg9RzwebvdgUbcadbsJeYhrEMJ269A3t6/pCiFVNuSmQ4We1xpdh5YvX17t8alDDOdnsJ38Xfh5eXl53vZ5/nk96aiUBh7VpT+Q0PXP7XD0geo/rykeO697HU0KBYb6PR6LVvslPCb+jaxbty54LMXSrFmzgnOkozLFKvOaEmNqTt/+/QFkO11fRCObpm7YsGEDRo0ahU2bNqFZs2a49tprcf311+d9Z+fOnRg5ciT++te/4ssvv8SMGTOKc3RyUG9MYrBSb8xhQOe//3sAQKf8rCxcOHw4AICFXve9914DtirMq8uWIZVK4dLr/jH9ButZcT4wjyN6v0UULZam56djUBSsvPzQQ/XaTgoATN1jx0kVbZ28zI6STqQOpcGpUh+Xj87Pi00dqqlbjR6PihTNmzcv6LAXS5x/fWjSvBLq6PL7mr4ZskDlOWSqHAUOVer1t2dntiE44ogjcOedd+K0007D7t270a9fPwwaNAi9e/fOfOc///M/0bt3b6xYsQJbtmzB3/3d3+Gqq64KimIZHNQbkxjqNKjnZDE+4PSmHspp1wcCb5Ja9IMqp6qW+iAMVWMNOatoe7hdKpc8LqruzD3mfktLSzPb1hs+txFS6HXfJHSu9Ji5pArKBw/3TzRXXfOjqV5qO7Ty7MESGi0JjVyows52as0BPphUoVdFXj3V9cFLtZjnmXnnZWVlRR0f0zD0mud+qcjze5rDz+N7/fXX87b77W9/G0D2d9XfvaqgLC5doSp27NiRGaXguaRyrwq8bpff5zWvbdSRMcK2829Ez9nBos5IofkhqtyzHTfeeGOdtONwov+IEQCAbv8neuNf04tSVhu7Le18tD3Kkvp0w4aGa9whSIcOHTL1J7761a+iV69eKC8vzwvqS0pKsHv3bqRSKezZswfHHHNMjTtcxpimjf+ijTkM2LBqVTpIveACAJnUdBZqxR+eegodO3asct3G4BuRCw56yAdximGk4DeUCyVz4tnh186cdmT4uaaJhex8STFpVlV9T1OPatrRixt50Bz8YnP+iyGU7x8SPELr6fuayhiy/2UnkIIGBRsKHZqWpueosVi/fj3efPNN9I9SnsiUKVMwZMgQdOzYEbt378bSpUuLa6vdb4xJDA7qjTHG1Ant334bANDtnOiN4dHyCn7gQpkfAAAgAElEQVShe3o54C8AAJZnavv1tAPSx1Gp4X1W7mvFnj17MGzYMMyZMyfT4STPPfcc+vbti5deegnr1q3DoEGDcPbZZxd8rwCn3xiTGOo0qJ8yZQoA4KEoj5XqjTo7EFWTOKyvxaXUto+pEbT3C+WhUkEJFaMJFZXh51qc6qSTTgKQLT7FtIRu3bpl0jbYxg8//BBAfNoNCRVH0nPEY2UqUqiQDtM0mF6iDg76/dDkQP4WEydOrLb9NUXVtNBEXU230WqPoWJbOumRx8P1qbZx//z9eH43REEF1blvfetbALLXMrf78ssv5+33uihVgxMCH5s7N28/OgmV15hOAGbRKU0Z4XnQvODcvzGdjJyrAm9YtSqjMH788cfZc1FRkbnGND+c21M1mtvhfpiWxnOpx6qqsf498th2796Nbsyd55AClUKeWGaX7cx/ny44v3roofQ5TaUKzmFIUQ39bRiTBPbv349hw4bhqquuwv/lSFcOCxYswC233IKSkhL06NEDJ5xwAt59991MwbsgDuqNSQxW6o0xppaw48LOFTvxmnajHay41zVNY9E5JNphiiPOGSyu2vegyCr19mOiDVCZ/060bH9a9J+oPsenaaU+MwE6rZegdH16Wd6lC1IASsrLg2k4odSRUIXgUOVh3S6PSUUhdmZ1YqlWNtaCYT/5yU8AoMCNpi5JpVIYN24cevXqFZwDcvzxx+PFF1/E2Wefjc2bN+O9995D9+7d661NxpiGp16Celpb8mZKhwg++EKTQjVXkcqf+gVT3QxN8tGbs1r6FZvzyP307NkTAHDiiSfmvZ+rZHJyICcmUdXkxNVQ3ifRNunDWfNB+cDQiZKq+PJcqm2nTlDl5/pAq2sHh5CCznaqxaZaRLLdPG59IIdsCuMUel5LFRVp+xSej/bt2+d9ftxxx+Vt55JLLgEAXD1+PACgRVTxtFW6/hJWrVpV5Xn4+8iNhtcJr222i78Tj59FrFavXg0AOPPMM/O2x2syd5sMMNl2ngu2nX+nHNWhQr937160PuUUHA1g6xtvBP29dfSB6/NvQdfTvGuuT+vY999/H4P+8R/RFQB6RQejSj0VQ04GiBR79alv3rx5gV2p3gd08njI5tWYps6vf/1rPPTQQzjllFPQt29fAMDtt9+eKYo4ceJE/PM//zNGjx6NU045BalUCnfccUfm/lYtlbBSb0xCsFJvjDG1JDQRVZ2/QilRcVW3FZ24qiq0dkRqqtTvihxUjo46kaGUKR7ncf36pb9Hl5ut0XJAtDye0j35ZXrxdvSSvTAWF4smOneKgsj3owrcbTZvDhbiChWpiptcHDr3qrSrSBSaWKsTb7mMzVmvA84666zYyc8dO3bE888/X/ONe6KsMYmhXoJ65tbPmzcv733mgetNUS0seROkAqgPRN5c1T6QqL+w3ozjhrj5PhVHVXOpLLLdmzZtKhhF6BQ9jD75JC3ZqkIcIjTErLZ8moOuDxIq2To/Qf2wNUjguaJyXle2goTt11EUvh8KgjQ40eF/LRCktoi8tvg+FXfuj1aT/B35m+sokiro3E4L+qZHwQh930O8+OKLANIPYyA7msVrjtcR98fj6BcFUWwXf9/cERW+pwXIeK6o0HMUqXnz5hg3e3b6uGmAc1F60W1EOlp79YFfZrbLvzteg1p4jdvn6+3bt+cdO9fn3wbVxC1btmRs6MEMB/HVzyCKPVPsGSOmUqmCOTNxo1Rq8+qiU8bAOfXGJAgr9cYYU0vY2dMJ1KrUq+c/X8d1WklcymBIlQ6p2youfDVS6L8Wpbzv+9rXAAA7o8nU2g6uT4Ed9J9n74offJmuVowd0ZIKfYUcAL/P7URB5LFvRO1JpYLHoqMJ+n6oojkJ2YCqgQOFBhJKiVShJGQUYYwxdU29BvW8uWkhJM0Dp3JHZU0feLx5hvKuVd3l9tVVI1R1UYdt2W6qpnwQU1nkktv985//nGkzlVsqvdxGKL835F4Tqk5IFVQfYOrUocECVVnuT52DdD8MVqZOnYq6RIsu8TdUFxd9EKpHtebck5DHNL//tShY4Xmhisx8cF5LbI/OKeD5Zr569yg3nr/ijsiNZfrQocFzkAudlTiyw+2y/bzm1UVJ50DkFlRim9WdRkdhDhw4gEm33goAKKUF4fhoScV+SXpxfFT8as1jjwWdi0IFwt588828Y9JrgOsdffTRmRGO0vLoPzICkpHio+WnMjLyh6VL0/vdvz/TLg3GQvNP9BqbOXMmjDnssVJvTGKwUm+MMbWEHRRan2pqj1a/VrccrRCtgoZ27kPE5ZuTkJjQKlLoqZi3iIK4T5l6GFm8qurdQq1HyUfRUpV5XVLvaSHLaLu5sWScUh/6XNcPEafYa469ikD8npoTNHYxqoPGQb0xiaFeg3qqi1TsuFSVmcqe5rbyfXVM4U2T22HusKq/OnGJilyo+iFfa34828ERB60kuHXr1swNn0seO9vGJR/++lDVNum5yPXwzt13XG68eu5z+1TidQSBQcq1116L+mDGjBkAgPnz5+e1R9MVQuicA4XHzfOkue/c3+bNmwFk3W3atk2XwQnNQQi1b81jjwEAVkft4nnFsmXVHsfQSMnv1q1b3vvtBgzIe70hcs/h97h/Vd937NiRWYcjSXosPPbcbZQymOPAAic8MhiLgrM3n3wy/fdVWVlwbarSrfMmOAdF98+/idy/0989/TRKSkpwRuQqVEof+ghV5t988sn8kbwDBzLt4N9iyNUmVKfCrjfG5OCJssYkBiv1xhhTS5hex3QxdupyO1lAtpPPpZoAaEE99bsPKe+hPPKQYBFyiGEl1zbRkq3/atRB1FSugo4PLUaZrUYn1y2ypDK/X5bMkGLwuDN/s7nJeHHHGLIPLtb7XzvyOuqiaWcqjKiSX9OaA8YYU1vqNainEsYHnlY55U2SihoVPK6nSqMq8VT6QsqhPii5fmiyGPfPByofuFTXqWKr+8eePXsy7iWa/69KvX6uueQhZyCeE3UY0aqfup6OZjCY4DmiqstjzPU7r090/oSOMOgDWh+kmsetOfTcDuc2EK30y6V6ruu1oZVruR+2j45NbM+5554LoLDi7MUXXwwgq7z3GTgQANCWp11soztFlWXXvfVW3v40UGC7gexvzTZyyUCT128qlcpOUGQU90C0jIKy5bctS18be/ZkzoG6w2itAf2NuFRP/ursFlevWFHwm6tdZCqVQjMUOinxbyEuZz6UphFS8I05LIlLv7E0aEyTwX+OxhhTSzTdjh0fdjzY+VZhgOuFKtFqbn1I7dW0u2Jz6JXm7Nyz4xQYISjI8Wew90G0ZOfwGXktxcIKgkRWlmU6WJRzf1SUJpfbFhLKVQ+JNjVVzDXFTzuzFBK006hmCIlP53JQb0xiqNc/x7FjxwIAFi1aBCCr0IWUNfWRVmVercV0KJgjAOpfH9o+H6Tcrt70tQqpDquSZs2aZR7ORNvCfdFlRa3vNP9XHxjaRvVL1891u2qll9t2IBtcUOWtbzhqw/SFkFKvE/P0WuD55fY0h57nYXNOcJC7Hc3z5nnQ+Ry5SjiQ/X3Yfp0X0rVr2pvv/Ehp5zXEkYO+550HAGhLCz+6zXDCYTTw0ipKW/jfp54KAFj39tt57dbc/9zPOOpChZy//ceRTeH+/fuzwdTr0TLKpV/4/xakz/m2bZl9qFIfqgqsfx9aAVp/y2KrLWsQp85HGnCGAlpNq+B6GpwZYxAf1Nux05gmg/vYxhhzkLDDxDQ67SyrQBGXbx1Kswp1OLTjEmffW9P98njYEfqsSxcA2RT4FpxYzVp1b0j7ZIJz5caNsUUA43zl4+YXhEYt4hR77RSqQYMKNpqupcKM2uIaY0x90SBB/ahRowAADz/8cHqnkWKnip8+ODRXXtdTZZBL5hBr7q7m8HK7VFF5E9ZCMjqyoGr4UUcdldmX2prxxq+fh9xU9IGiecB8X4vaaLVcPZeaX6wPJAYfWlOgvrjxxhsBZK8Jjqao+qoPYFWFM24zEVTCebz8nP70VNap3DM9Qivt8hrQ+Rm8RjR9gukVHOmgOs7zvCGyBOQDPjNeolaAjHrElz30q/Aa3bZtW+Y9VmjlZz179gQAdIgKDH322We47Oqr01/uEa0U+cKvT2dhYO/evZlzzGPlsROeY63qq6kjWpQnFHQVm14RSjUJTVjU9Af92+N+Q7UPjDmssfuNMYnBSr0xxtQS7dBobj07dXHOKJpbH2ftqoSU+DiFPk6xJ5oG1/KjtNfplijNrE3Ut2b36dPoP5z/zT7ql+XlaN68OUqqaUtc/j8JHWuxn8dtVxV6ikUUPigYaHFDnit+TuEgsdin3pjE0KBBvaqbetPkUqud8gFHpVBvuuqkoo4xWjWV8OZcXl6et167du0AZFXXkFqem4+tqp/6iasDCdvKiqJxhU24Pc1LVoVZv0fUa5/tIdxvQz+AeD50oqCOjvC35m+kijnnKmiOPZV7rT1AH3sq7DxfXJ/XgLZLr1G2g7+Dfp/XELfP80vhqxX/Q/Oi9dEiUsx3RNVYM+q2eK2zIu769dGKyDoa8dpRt6mWLVuiBSckRiMD70c/+7Nz5qSPcdeuYM0DLrVCbKgYj9ZSCAWMxQaYOiGR+4/LhddrKVTgadasWdVux5jDCgf1xiQGK/XGGFNLNI2NHSh2Itmpiyt4p+lyoWJ0inZkQmr3tijtjPOx2Ydk8lqUfYXSqJNIVMDQ9L7Nv/99env9+uWt14o7YIXanPyxuDSrYpX62n4/RKizyN+UyjuXap+rwg63N3369DppnzHGxNEgQf3Pf/5zANm8ZuYrEyp56mOvHuy61AehuuIQHSLn90Ie8GwHVVfdXnUPEa1Ky31RPWXus+Zuaw62qp78nraVhBT6kEuMVt0MOQDVN1OmTAGQza3nedDJZjpKw2CJOfI8LlYvpdKu8yp4Pukrzwez1hGgks9Ks/p7cMl2Ubnn+aQarKNT/P0ywpcU4UlFCv22KFiqjH4XTX/gCAd993OLHb3++uvIhU5ABw4cwKkXX4zOABY/8kiBEn/gwAG0QnY04re//W3eds4++2wAhRWadc6LXkPqcqMBYlzhJJ0PwnPOdsbl5ms7Negi3J4xJgcr9cYkBiv1xhhTSyhAsGOkk+7ZqeRSi8zFdWhIsTabahrAJXPbW0T/2RdJ9FToj43EhlDl2bj9MOZrzubTqrVbtIyU+iM7dUrvf9Omgm0V68gTNy+gpsKEdho1d17dbjTlTn/j2rajyeKJssYkhgYJ6jW3Vt0wVGHnzZRqKR+EXFL11PX4mgo74U1aJ7Op0k/UI16riVblna4PP7ZFH/bcpubGs41U8rkPKtdsA19TVdSHfchOjbnjVCt1FCLjyiI+9g3FyJEjAQBPPPEEgEJHEp4PtpvKOs8rvdepmGsNAp1Xwe9xuzw/WoE2NHdBzzuvTa2dQPj7UVHPePZQYN+f/1JVbLaD7fwomqjIEaDf/OY3CFFRka7ks2nTJqy94w7MnDkTVwKYO3cugOxoBK8tjnLw9XPPPQegsEqxzh/htaMVXfk3oJ76OuoRCijVlSbkfqPtUgcpdZ7Sa6yhnJ+MSRRW6o1JDFbqjTGmlqhgoBazfK2F79iRiJsYHze5mGhHR205W0YTtHdKR6d9wN9e7UC1o6XtXltWlv7+hRfmbS9TITbKrW8bVZ7dmNMp1o5zKD1Kv6/ETbgOoZ1PzZnXtCwVlXSpVsmJx0G9MYmhQYL6kE90SLHjA42qJBU0VeL15srXfICqFZnmozOvmiqrDq9yv/web9LcX+4IRMilRsvDcx1VdumKwtEJzY2nMq1l6HVUQf3xuV1+rso/UTWzsRg2bFhR31uxYgWA7MgGzwPzxzkUzt9MvdO5ZE4+XWSYk8/3NTdeR2D0mtOgh2iu/ZrHHgMAHHvZZQCAVtHzn89ODWz4u1Lp1xGI6uCoxLRp0/Lenzp1at7rJUuWAADatEmb53eKUiVOOukkAMA777wDIHtt6d8dr2n9+wj52ZO4yaChQkrqSkVCtRo08FWnpVtuuaXK/RtjjDFJwEq9McbUEnb8dYK8pnexU8bvs3Onij07IOx8czuaIkhC6XfFesBrnjq3p2IB0dRDXW7t1QsAsD7qAHZjPlmk1HMieHUpi6rYF5tDX6wffbGVatkOdlpVuNEiZmqLq2JWUnFKvTHJoUGCej7QdChX85Q1f5pLqqhaKVbzv7m+DptyqWo225Hr3w0UFhWhUs8HLG/abF/Lli0Lisfw4agPcc355ra0TXyo6sNYFfZQhVWeM35O5VnL2KsjSFKqaV5yySUAsnnhek2pb7ymN+goEfPIed54Pvmg1hESrYGgaQ+a/80RE7aDv0PGrz6awFgaSfXlkt7Aa7NrVOynS5cuALLXF1V1AFi8eDGArFsNPfzj4DGzrRy16NEjXXa2c+fOAIB169YBCBdOCs2Z0QBW0YA09DouZYXota0TIvnarjfGhHH2jTHJwUq9McbUkkmTJgEAXn31VQDZDoO64qh9bihnXTuPqhKHbEE1fS6kqIcqzRJtv3aMdIJ/SB3/3aOPorS0FB8iOxGbwkIqlQL27SvoXPFYKXyErE9JnCJfbCqhGjkw1VELzimq0KtQcqh0Fh3UG5McGiSoZ/GNxx9/HEBhLqxOJtPcWg5FM5+Yjh+8eVLF5Hp8cGqOPB8ifGCqG44Oq6ryT0IP1tx1qKBqNU4+OLSgiebC6zC4VlDVNnI9niO+rwq95mBrVV76xjd17rvvPgCFiroWAdJrS5V3XgO8hhiA5Hq3535Pf0cSUoG3bEmXbF21ahUA4Kyzzsrbf1tWAzozWkaVXduedlr6+N59N6/dOtGS7eDfCACMGjUKQNYRSBXsEKNHjwaQVfo3btwIALj88ssBAK+99hoAYMaMGXnr3X333QCy54xt0fkjGsiGcuLjXscVZtK/GV4LOmLI9WfOnAljjDEm6VipN8aYg4QT4qkyh6qQskOh+dhqmxvysSdxVVSL/b5uX00CtCgdO5GqTquafsQRRxSIJNwmO1fsBHJdNQMI2evW1Le+WNhO/oY8Vu0Mhqr4hooYJh0r9cYkhwYN6vngY446b/q8SWqVVaLlu5n3/Le//Q1AYZ45H6hUSWfNmlVle+bNmwcg65jCm7qWfldFUFX19evXZx5IbLt6bFMJZtt44+exjB8/vso23nXXXQCyOd88dzraoBP22rdvDyD7gNKggftPqv0a2/+rX/0KAHDuuecCKFTQdQhcHZT4ueaH63bUbYa/J69NXgtc0hv+qaeeytsOA5XeF1yQfmNI9MGAaPl2ekEnwO3i+a45+xokAtnKzer6FMedd94JIHut3XTTTXmfh8rd33DDDVW+/y//8i8ACgNenfdAVLkPBU9xkzt53Pzb4rX9gx/8oMp2GmPCeKKsMcnBSr0xxhwkm6IKqdpx0fQ7dvrZudNqpBQHuAylToUKcMUp+DrJmKi6rVaqRCeIhzpezZo1K5h8r+lQ7JCqp39ognScc09Iodf14rajE6/VvEDnMXDJc8Nzxk5l0rFSb0xyaNCgfuzYsQCy6qX6yeuDL3RT501UfexVkYzLJZ48eTIA4PnnnwcAXED1tEgefPBBAIV+39Uxf/58ANlc95BCT3hu6F/PB6IOz/Mhy5xwnkN1ClKFV3PxmyoPP/wwgEJXGaKWggyKNHAgOp8jNLGQqGsOfxfmnTOoW7lyZbXHQQ/4itWrAQCdvntG+oPo9H+anm+JrR+kq/SkZCKlKvXavtxj5TmJG4Xh9d+vXz8AWe//hQsXAsjm2tcUOvKMGDEi733Oh9AK0Zorr2hAqqMkvIbVj98YY4w5HLBSb4wxBwk75+wgMb2LS7X3ZOdTOzZauCvkaqM57Koek5CfPFGVOlTAT/Pg2ZEi/Dw3FYr/pxChggIJOfvoMRxsLn1oArZao2p71M1GHYyITtCOE2ySgpV6Y5JDowT1HJbkA4Q3T/V/1/x03kSpwvIByJsoFUnedKmKLlu2DABw6aWXVtmemir0BwNHK4qlY8e0PYpWpOVDV33vdTifSz6Y9MFDVbapu96MHDkSALBgwQIAhWkHenyEx89riOcxVKRHJyqqeqxVisvLywEAzz77bFHHceyx6So8vHbfWv6HvHZmhvwDlodxeeZAodvT9773vSrbQiV+8ODBefvgXBWu/9xzzwFIzx2pbnvFcu2111b7+b333gug0NVKzwHbR1tJY0zd46DemORgpd4YY+oIdqjYaWOnW9PgVJFX9xku2ZHRHHwSsvcMKfxE1WlN46NIoP76WiRPjztXnWcH+n/JZG/uS+1h1XZWqSu3m5AIxHOh51oLzKnLjZoiHCquN6QSnihrTFJolKCeajX9sENlwXlz581V84h58+WDhA9QjgTwpqvuOEmAows8Np4LLR+vDx4d1leFmueEVUPp+Z8U1C9e36eCzlEa9a/XIfTQA5yoA5JOfGS1VVa4XbFiRZXtpjsP51KE5ouEPNxDjjCaMgBk0x00RYL85Cc/AZC9lnjOOnToACDrfqMjXlqvob7QUSM6QKnFYbGuPsYYY8zhgJV6Y4ypI9hJZpqVChREi8yFis2pJS47XNppV7U6lGMf51/P9ajUa/oXO7Oaj84OV+7IgBb5UlcZrSCrzkHa5poq9KEOMzunnFjN30KNGrRdKi5pyh+3QyvlQwWn3xiTHBo1qOdNVYeiCW/+OiSsHu2q2PFhwZs3lcskoQVMjjnmGABZdVWVZR4zlyGFno5BdG0JeY83Vfib8kF73nnnASjMdVf7OV4DXOoDW+30eG1p2oIGM1z/hBNOAABcdNFFAApz7BmM8fshC8HQslgLQiDrlBTKNec1s3XrVgDACy+8AADo2bMngOy1xWuJ19CwYcOq3F59c+ONNzbKfo0xDuqNSRJW6o0xpo6g/eeqVasAFE72JVR5VZhgZ1Rz19lpY/E5LdAXmkgdB9uhRcy41GJ36mTD1yrMtGjRItNRVstSTauk8QE7vHpMIXecOKVeU9zUuUcVdv2cr7lUM4KQ/35NzRDqirFjx2LlypUoLS3F2rVrg99bs2YNvvnNb2Lp0qUYPnx47HYd1BuTHBo1qKdPPB1N9OavDzh1dNEhap2AxZvu5s2b6/Eo6ofLLrsMAHD33XcDyD40damTy0LBARVs+qnz3CcNVi9lNWCeBx43j5O/OQMGXht8MDOAUE93dc/RNAa+1iF4/g7MmSff/OY3AQClpaV5+9OJjDWd7KfpELn58xyNiePmm2+u0T6NMU2X0aNHY8qUKRg1alTwOwcOHMCsWbMyjlfGmEMLK/XGGFPHML2N6XLaaVOVmEt2Etl5pNBR1YToXEITqUOdRnZK2QFkZ5j70zQ/LivFalWrqWp7gEKXG25Lvfz5vWJ96UPVc0OpaToaoaMdTFvjOQlNWlcHIn6vsU0HzjnnnIztbIi5c+di2LBhWLNmTdHbTcHuN8YkhSYR1I8ZMwYAsGTJEgCFarR6i2vec5wjiKqnSYLK9BNPPAGgsCiNKsZc8iHLnPyPP/4YQLxHeFLgSMNPf/pTAFkFXN19GDDwGmDQoiXgeR51yF9RpT2U9tC/f38A2fQF7l8n7el+dFJhqMS9pknkVgQOudTMnTsXQM0qIBtjDg3Ky8vx1FNP4aWXXqpxUO/0G2OSQZMI6o0x5lDi6quvBgCUlZUBKOwE0iNdnVe0oqta1PJ9TQtjJ5553Wrzq3ag7MSyHbmdQiCbtkc7U+5fvdp1meviw32otSpT4lQp5z61wJ4SEnFIXEXaUI6/VpClYq+/nc6H4DlkgbymyvTp03HHHXcUuAvF4aDemOTQpIJ6qsm8mXOp9m9EVerQRKfLL7+8PpvdIPDBwQeSWuDpA4kKPYeEJ0yY0HCNbUDo8MIqpFr5VR2UdKRDFXNV6lWJV4tCneioVZHbtm0LIJy+QLQdIfcbTWXg78+/HSBcHTiUrmCMOfR54403MGLECADp58IzzzyDI444Ilhp3RiTPJpUUG+MMYcSH374IYCs5Sk7d1pMTie+q1Ut08g0/YudSaabcakpiFpUjbCTqNavFBFU1dURBHZiVe0+4ogjCjrU6v/OY2AuO7elx6qT09lGnaTONmkOvp4DvlYPfq7PVDk9J4SCAduzYcMGJAFei0B6Uu0//MM/FBXQW6k3Jjk0qaD++uuvB5DN/eVNmXnJehNWhZ65xFSnQz7dSYTD+ffffz+AQp/63PLsQOPZqjUWfNCqgs2AgcGTwmtMqxUTVcpVued+mL7AYIjtoD+9OjKR0HZ1vzpCwNdU6FlFuTqmTZsW+x1jTDK54oor8Morr+CTTz5B586dcdttt2WejRMnTqz1dj1R1pjk0KSCemOMOZSgsPDkk08CyAoUOmFbc+pVuVe/e3b22ImnoMFOpaZ7EU3B4v5DqY4MCrldquxU3fm+5vofeeSRmfe4jjoBsSOs+fw8dnWrYVuY68628lh5bpmzr+dWfetDk+K1A82Ou3bkWbyNtQkaGxpNFMPChQuL/q6VemOSQ5MM6tWdgw4n6jmuE5WS6r1eE8aPH9/YTWiS3HTTTQCAO++8E0D2gcyS7Xzgq2KvOewhdxt1WmJAwQCDgQm/pwGNwkBDXYy4/9D32V6ORlVUVAA4OCXOGGOMMcmnSQb1xhhzKMHOV/v27QEUerSrcs/OG19rZ0+dZUI+96pCF2vhqhO6tcKtzg2oKoefirvmyHMSP1PjONrA74UUdR094HY0t56jCHrO9JjUDYdt11ELLeTH7RST8nYoYKXemOSQiKD+UMqNN/ULFfs5c+YAyAYAH330EQCgc+fOAAoL3qgrjgYAakHIoEiDHQ0wNGDQQIMBA9MnNN1CC/IwOGTFXAZGxhhTHzioNyY5JCKoN8aYJEOb0V/84hcAsp09zaFnZ1E7maqEhyq6qvKuOcJonC4AAA/MSURBVPWE67NTqZ1UrRCr+eX8XM0LSLNmzQqKCKrtK/elCrmmV+r7emyhAnza0WbHmfvVY9P2qosO12PK3aFSyC8OT5Q1Jjk4qDeHJNOnTweQ9a/ng/i9994DUJhjzyH7UK67Blea465BEv3pQ1aCREcK6GbD11yfOftMOWC7PIpljDHGGMBBvTHGNBjf/e53AQDPPPMMgEKrU+3ksVOnnciQOq3VVBXNU9dKtKr4szOr7eIIA1+zs5kLPwtVn+VSU9TYFir0auuqCnxIoedSJ7Wr7zyPTYseqkLP9davX19wrIcyTr8xJjk4qDeHNEx7YO0DdVZS7rnnHgDZAjTMvdeS9VTktVgPAwmuHyrJrukK3D63w4I2M2bMqLa9xhhTnzioNyY5OKg3xpgG5jvf+Q4A4PnnnwcAtGnTBkCh3zvVYk3v0tx3zT/XzqQq76pmc7tUzWnFGrd/9cvPHQHgd7gu20hVnwo6RyPYoeWx08KYhHLo9XM9Rp4jtp374fs8Rk5OZyqejhxwkjqFgsMFB/XGJAcH9eawIE6hJ1rwRiu4amDBwEWDIir1ofWJFhPiZD4r9MYYY4ypCQ7qjTGmkfjLX/4CADjppJMAZCdwawVZVbupcmsuvHq060TtkJpN2CkNpZ1pp5SdWlqr5jrNsOKqVoRlm3XSOduqCr166+tSc/TVg5/wnPAY1TmI7eL6ZNu2bQCAyy67DIcjlbD7jTFJwUG9MVUQKlSjxXjUHo9uOgyKtKgPUXs+pgRwMp8xxjQFnH5jTHJwUG+MMY3ExIkTAQALFiwAAJxwwgkAsup1SFVWRxa+rwq9dirVe5370TxyVbXVoYbtYSe0KtceXYff0Y4xX1Oh19GGUOoalXhNgVOlnutze9w+z5G65/CccqRh2LBhOJxxUG9McnBQb0wON9xwAwDgvvvuA5ANBHSioJaoZw59u3btABRa/mm6g77PIX7u3xhjmgIO6o1JDg7qjTGmkRkzZgwAYNGiRQCArl27Asiq21yqR7tWflVfe00jU2U+VIGWOf26VF/6UOXZNm3a4Nhjj83bJzvEzNPnpHA67XCpVXaJeuarZz9Rpx+izkCh0Q+283BX6I0xycNBvTFVoBP/GKwwAGAOPIOd7t27A8jm0mvqgCr0DEiYvrBly5b6OhRjjKk1KXiirDFJwUG9McY0EUaNGgUAePDBBwEA3bp1A1Dopc5OI5equGs1V6rSWjWV63O7qujrCAHR3Hsu+f5XvvKVzDapvLMtWsGVijy/x/XUeUfnASiq4IfazO1QkWe7du7cCQB4//33AQAXXHBBlfs53HD6jTHJwUG9MVVw00035b3+0Y9+BACYOXNm3vtMl2CqAdF0hlChnM2bNwPITpg0xpimhIN6Y5JDgwT1M2bMwPLly7Fp0yZ06tQJs2fPzihSAPCHP/wB48aNwzvvvINevXrhgQceQN++fRuiaSYBfPHFF5g0aRIef/xxHHXUUZg5cyZuvPHGxm6WMfXGNddcAwCYP38+gGx6V9u2bQEUerurKq0OMFpdVV1tmDamjjJa/ZXfp4penTMN28Bcec3Pp/0rO8A8llBVXB0NIDqPQO1ndZI7l3S52b59OwDgvffeA1B8oTpjjGlqNEhQ36pVK6xYsQI9e/bEmjVrcOGFF6JHjx4YMGAA9u3bh6FDh2L69OmYPHkyfv7zn2Po0KH44IMPCoZfzeHJrbfeig8++AAfffQRNm3ahHPPPRe9e/fGhRde2GBtUIWecMIhr1WdtKfBDgMP2uWx9LwxxjRFrNQbkxxig/of//jH+O1vf4snnngi897UqVPRvHlzzJkzp6id3HbbbZn/9+/fH2effTZef/11DBgwAK+88gq+/PJLTJ8+HSUlJZg2bRr+4z/+Ay+99FKDBm2mfli3bh1OP/10rFq1CqeddhoqKirQp08fPP744xg4cGBR21i0aBEWLFiAtm3bom3btpgwYQIWLlzo68Mc8owdOxYAcO+99wIAevbsCSBbeZYKulZd5ftUqdm51Nx89Ybn96jU06GGE8O5X/Wc5whArjuP2riGfOM1F57r8Vj4PZ0HQHQ7RF1teE54TJ988gkAYMiQIQCcQx/CE2WNSQ5Vl7vMYeTIkSgrK8OOHTsApG+0S5cuxdVXX43JkyejTZs2Vf7r06dPldv7/PPPsWbNGpx88skAgD/96U/o06dP5kYPAH369MGf/vSnujg+08iceOKJuOOOO3DVVVfhs88+w5gxYzB69GgMHDiwqOtn+/btqKiowKmnnprZ5qmnntpkro+WLVuiZcuWaNasWV5aQGVlJSorK5FKpfJSI/bu3Yu9e/diw4YN2LBhAyZNmoRJkyY1RtONMSYWKvWhf8aYpkOsUt+hQwecc845+MUvfoEJEyagrKwM7du3R79+/dCvXz/MmzevRjucOHEiTj31VAwePBhAWjVh4R5y9NFHZywFmzLO+y+OCRMmYMWKFejfvz9KSkrw9NNPAwDmzZsXe/1QVcu9RpJyfRzu+O+j7pgyZUre64ULFwIo9Hjn3wXVafVsV4tVdaDR/HN1rOFSrV2Ze09SqVRBDjy3yb9pbkNz6dlGvuaoQsjhh6/Vt57KPNvG/TLlbcSIETDGmEOJonLqr7nmGvz0pz/FhAkT8PDDD+Pqq6+u1c5uvvlmrF27Fi+//HLmhty6deuMVzfZtWtXZhJVU6bY9COTDuyHDBmC++67LzPZrhiYHrBr167Mw70pXR88Fg0sQnz88ccAgCuuuKJ+G9YE8N+HMcnHOfXGJIeigvpLL70UkyZNwtq1a7Fy5cqMvd/EiRPx8MMPV7lO165d81IkfvCDH+DZZ5/FL3/5y0xeJgCcfPLJuPPOO5FKpTKB/v/8z//guuuuq/VBmabFnj17MH36dIwbNw633norhg0bhmOOOaao66dt27bo0KED3nrrLQwaNAgA8NZbb2XSt4w5HBk9enTea7rkUGnX6qyhZciznQo8FX9+n4o/nWOYl87v8fO9e/cW5PNTQed3mdJJ9Z9t5mvuk9thh5ltVKWfr1Wp37ZtGwBg/fr1AIDJkyfDFI+DemOSQ2xOPZAe/hw+fDiuvPJKnHHGGTj++OMBAD/72c+wZ8+eKv/lBvT//u//jsWLF+OFF15Au3bt8rY9cOBANG/eHPfccw+++OKLzISw8847r66O0TQy119/Pfr164f7778fF198ccaTvdjrZ9SoUfi3f/s3bN++He+++y7+67/+qyCoaSyYU09KSkpQUlKSybHn688//xyff/45ysvLUV5e3ogtNsaY4uFE2dA/Y0zToWhLy2uuuQb3339/RhGqCbNnz0aLFi1w0kkn5b3H95ctW4bx48fjlltuQa9evbBs2TLbWR4iLF++HGVlZfjjH/8IALjrrrvQt29fPPLII7jqqquK2sZtt92GSZMmoWvXrjjyyCMxa9YsO98YkwNdcsjixYsBZIuiaSVaquGqvFNFp1KvTjVUv7ds2QIgq/CXlpbmbW/fvn2Z/H71kVcXG821Z+4819O2cLvMlacynztKAGRT3fTcGGPMoUrRQf3xxx+PI488EsOGDavxTrQwivKNb3wDv//972u8XdP0GTp0KIYOHZp53bp1a/z5z3+u0Ta+8pWvYP78+bXqUNY3DEzUro8wdYAFbhxgGGOShNNvjEkORQX1lZWVuOuuuzBixIi8fHhjjDFNjyuvvBIAcM899wAAOnXqBCBbkZYT0DVXniq35qtTwaepAZV9FXnuvvtuAMDw4cMzLlfs6HJyO1+zii3bwI4x28B9cJ+aK09ln4q8K8HWD3FBfUk1nxljGpbYoP7TTz/Fcccdh65du6KsrKwh2mRMYhgwYEBR3/v6179ezy0xxpi6Jy6od6KsMU2H2KC+VatWGUXEGGNMcpg2bVqV799///0AshViNe895DFPlfyyyy6L3TcVdvW+Z36/VpxV33mOFnA7XHKivTHGmHyKzqk3xhhjzOFFJap3ubFSb0zTwUG9McY0ID/+8Y/x4IMP4qOPPkL79u0xefJk3HzzzZnPf/Ob32D69Ol45513cMIJJ2DevHk466yz6rQN48ePL+p7zJG/4YYbaryPkSNH5r3m6ABz6TkaQDSvf+fOnQDCow2mYfBEWWOSQ1E+9cYYY+qGVCqFRYsWYfv27SgrK8O9996LRx99FEC6UNKQIUNw8803Y8eOHZg5cyYuueSSjHuSMQ0Ng/rQP2NM06EkFec3aYwxJsPSpUsxbty4zOv9+/fjzDPPxCuvvFKr7U2bNg2pVApz587FypUrMWvWrLziaz179sSsWbPy9tlUGThwIADU+lyY+qesrAzXX389Dhw4kKkPUx0tSkrwtWo+L+3XD2+88UbdNtIYUyus1BtjTA24/PLLM5WPKyoq0L17d1xxxRX44Q9/iDZt2gT/VUUqlcJrr72Gk08+OfNadZZUKoW1a9fW+3HVBX379kXfvn0buxkmwIEDB3Ddddfh2Wefxdtvv40lS5bg7bffrnYdK/XGJAfn1BtjTC2orKzElVdeiYEDB+J73/seAMSqnsqtt96KyspKjBkzBkDaIrWiogJLlizB8OHDsXjxYqxbty5TVbWpM2fOnMZugqmG1atXo0ePHujevTsAYMSIEVi+fDl69+4dXCeF6ifKGmOaDg7qjTGmFnz/+9/H7t27MwWeasq9996LRYsW4bXXXssUYGrXrh2WL1+OGTNm4LrrrsPgwYNx/vnno3PnznXZdHOYUl5eji5dumRed+7cGb/73e+qXef8wYPxySefBD9v3759nbXPGHNwOKg3xpga8uijj2LJkiVYs2ZNxuP99ttvx+233x5cJ7fex/z58/HDH/4Qr776akHA/u1vfxtr1qwBkK6ieuKJJ+Kmm26qh6MwhxtVTaFjfYAQLjppTHJwTr0xxtSAN998E1OnTsWyZctw7LHHZt6fPXt2Jte+qn/kkUcewezZs/HCCy9k0iB0+/v378euXbswY8YMdO7cGYMHD26QYzOHNp07d8aGDRsyr//2t7+hY8eOjdgiY0xd4qDeGGNqwPLly7F9+3acddZZaN26NVq3bo2LLrqo6PX/6Z/+CVu3bsXpp5+eWT+3SuqPfvQjtG/fHl26dMHGjRvx1FNP1cdhmMOQ008/HR988AE+/PBD7Nu3D48++iiGDBnS2M0yxtQRtrQ0xhhjDhOeeeYZTJ8+HQcOHMDYsWPx/e9/v7GbZIypIxzUG2OMMcYYk3CcfmOMMcYYY0zCcVBvjDHGGGNMwnFQb4wxxhhjTMJxUG+MMcYYY0zCcVBvjDHGGGNMwnFQb4wxxhhjTMJxUG+MMcYYY0zCcVBvjDHGGGNMwnFQb4wxxhhjTMJxUG+MMcYYY0zCcVBvjDHGGGNMwvn/1JYa/levGdwAAAAASUVORK5CYII=\n", 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\n", + "image/png": 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\n", + "image/png": 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" ] @@ -215,7 +215,7 @@ ], "source": [ "for stat in stat_files_ses2:\n", - " plotting.plot_stat_map(stat, title=stat)" + " plotting.plot_stat_map(stat,threshold = 1.6, title=stat)" ] }, { diff --git a/task_based_analysis/sub-KPE008.npy b/task_based_analysis/sub-KPE008.npy new file mode 100644 index 0000000..6b35450 Binary files /dev/null and b/task_based_analysis/sub-KPE008.npy differ diff --git a/task_based_analysis/task_timeseries.ipynb b/task_based_analysis/task_timeseries.ipynb new file mode 100644 index 0000000..6deab17 --- /dev/null +++ b/task_based_analysis/task_timeseries.ipynb @@ -0,0 +1,430 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\"\n", + "Created on Mon Jan 8 2020\n", + "\n", + "@author: Or Duek\n", + "Check Aging data timeseries\n", + "\"\"\"\n", + "\n", + "# KPE timeseries analysis\n", + "# Using the connUtils.py file\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/sklearn/externals/joblib/__init__.py:15: DeprecationWarning: sklearn.externals.joblib is deprecated in 0.21 and will be removed in 0.23. Please import this functionality directly from joblib, which can be installed with: pip install joblib. If this warning is raised when loading pickled models, you may need to re-serialize those models with scikit-learn 0.21+.\n", + " warnings.warn(msg, category=DeprecationWarning)\n" + ] + } + ], + "source": [ + "import os\n", + "import pandas as pd\n", + "from nilearn import plotting\n", + "import numpy as np\n", + "from connUtils import removeVars, timeSeriesSingle, createCorMat\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# here we load the atlas - this is the Yeo one, but we can use others\n", + "#atlas_filename = '/home/or/Downloads/1000subjects_reference_Yeo/Yeo_JNeurophysiol11_SplitLabels/MNI152/Yeo2011_17Networks_N1000.split_components.FSL_MNI152_1mm.nii.gz'\n", + "#atlas_labes = pd.read_csv('/home/or/Downloads/1000subjects_reference_Yeo/Yeo_JNeurophysiol11_SplitLabels/Yeo2011_17networks_N1000.split_components.glossary.csv')\n", + "#coords = coords = plotting.find_parcellation_cut_coords(labels_img=atlas_filename)\n", + "# take one subjects file " + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# use aal atlas\n", + "import nilearn\n", + "aal_atlas = nilearn.datasets.fetch_atlas_aal(version='SPM12', data_dir=None, url=None, resume=True, verbose=1)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "atlas_filename = aal_atlas.maps\n", + "atlas_labels = aal_atlas.labels" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "41" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "atlas_labels\n", + "atlas_labels.index('Amygdala_R')" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# put functional file, confound file and event file here - this is for one subject\n", + "func_file = '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz'\n", + "confound_file = '/media/Data/KPE_BIDS/derivatives/fmriprep/sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-Memory_desc-confounds_regressors.tsv'\n", + "events_file = '/media/Data/PTSD_KPE/condition_files/withNumbers/sub-{sub}_ses-{ses}.csv'" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "sub = '1322'\n", + "ses = '1'" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NiftiLabelsMasker.fit_transform] loading data from /home/or/nilearn_data/aal_SPM12/aal/atlas/AAL.nii\n", + "Resampling labels\n", + "________________________________________________________________________________\n", + "[Memory] Calling nilearn.input_data.base_masker.filter_and_extract...\n", + "filter_and_extract('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-1322/ses-1/func/sub-1322_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz', \n", + ", \n", + "{ 'background_label': 0,\n", + " 'detrend': False,\n", + " 'dtype': None,\n", + " 'high_pass': 0.01,\n", + " 'labels_img': '/home/or/nilearn_data/aal_SPM12/aal/atlas/AAL.nii',\n", + " 'low_pass': None,\n", + " 'mask_img': None,\n", + " 'smoothing_fwhm': 6,\n", + " 'standardize': True,\n", + " 't_r': 1,\n", + " 'target_affine': None,\n", + " 'target_shape': None}, confounds=array([[ 7.004881e+03, ..., -3.041630e-03],\n", + " ...,\n", + " [ 6.749717e+03, ..., -2.198550e-02]]), dtype=None, memory=Memory(cachedir='nilearn_cashe/joblib'), memory_level=1, verbose=5)\n", + "[NiftiLabelsMasker.transform_single_imgs] Loading data from /media/Data/KPE_BIDS/derivatives/fmriprep/sub-1322/ses-1/func/sub-1322_ses-1_task-Memory_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz\n", + "[NiftiLabelsMasker.transform_single_imgs] Smoothing images\n", + "[NiftiLabelsMasker.transform_single_imgs] Extracting region signals\n", + "[NiftiLabelsMasker.transform_single_imgs] Cleaning extracted signals\n", + "______________________________________________filter_and_extract - 88.9s, 1.5min\n" + ] + } + ], + "source": [ + "# create timeseries of all ROIs in atlas\n", + "timeSer= timeSeriesSingle(func_file.format(sub=sub, ses=ses), confound_file.format(sub=sub, ses=ses), atlas_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(1150, 116)" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "timeSer.shape\n", + "# 116 regions in aal atlas" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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016.013122.246traumatrauma1
1143.220115.761relaxrelax1
2263.397122.803sadsad1
3391.141115.757relaxrelax2
4511.190122.237traumatrauma2
5642.469122.798sadsad2
6769.435115.764relaxrelax3
7889.335122.242traumatrauma3
81015.616122.802sadsad3
\n", + "
" + ], + "text/plain": [ + " onset duration trial_type trial_type_N\n", + "0 16.013 122.246 trauma trauma1\n", + "1 143.220 115.761 relax relax1\n", + "2 263.397 122.803 sad sad1\n", + "3 391.141 115.757 relax relax2\n", + "4 511.190 122.237 trauma trauma2\n", + "5 642.469 122.798 sad sad2\n", + "6 769.435 115.764 relax relax3\n", + "7 889.335 122.242 trauma trauma3\n", + "8 1015.616 122.802 sad sad3" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "events = pd.read_csv(events_file.format(sub=sub, ses=ses), sep=r'\\s+')\n", + "events" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0., 0., 0., ..., 0., 0., 0.])" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# create vector of zeroes and ones according to onset + duration\n", + "x1 = np.zeros(timeSer.shape[0])\n", + "\n", + "for line in events.iterrows():\n", + " onset = round(line[1][0])\n", + " duration = round(line[1][1])\n", + " x1[onset:onset+duration] = 1\n", + "x1" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize = [20,5])\n", + "plt.plot(timeSer[350:700,40], color = \"blue\") # time series of region 43 (V1)\n", + "plt.plot(x1[350:700], color=\"red\")\n", + "plt.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize = [20,5])\n", + "plt.plot(timeSer[850:1100,40], color = \"blue\") # time series of region 43 (V1)\n", + "plt.plot(x1[850:1100], color=\"red\")\n", + "plt.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize = [20,5])\n", + "plt.plot(timeSer[:,41], color = \"blue\") # time series of region 43 (V1)\n", + "plt.plot(x1, color=\"red\")\n", + "plt.tight_layout()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/task_based_analysis/tfce_analysis.py b/task_based_analysis/tfce_analysis.py index 6175e21..cafb9ce 100755 --- a/task_based_analysis/tfce_analysis.py +++ b/task_based_analysis/tfce_analysis.py @@ -5,6 +5,7 @@ @author: Or Duek run tfce analysis for KPE study +Need to turn it into nipype pipeline for convenience. """ import os @@ -55,15 +56,35 @@ nilearn.plotting.plot_roi(group_mask) #%% # grab con files for all relevant -contrast = '02' # set number of contrast +contrast = '06' # set number of contrast ket_func_ses1 = ['/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_%s/con_00%s.nii' % (sub, contrast) for sub in ket_list] ket_func_ses2 = ['/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_%s/con_00%s.nii' % (sub, contrast) for sub in ket_list] mid_func_ses1 = ['/media/Data/KPE_results/work/kpeTask_ses1/1stLevel/_subject_id_%s/con_00%s.nii' % (sub, contrast) for sub in mid_list] mid_func_ses2 = ['/media/Data/KPE_results/work/kpeTask_ses2/1stLevel/_subject_id_%s/con_00%s.nii' % (sub, contrast) for sub in mid_list] - +allSub1 = ket_func_ses1 + mid_func_ses1 +allSub2 = ket_func_ses2 + mid_func_ses2 #%% First compare ketamine group # create diff image +group = 'all' +for ses1,ses2 in zip(allSub1,allSub2): + print (ses1) + print (ses2) + sub = ses1.split('id_') + sub = sub[1].split('/')[0] + print(sub) + diff_file = 'kpe' + sub + 'diff' + group + 'con' + contrast + cmd = ['fslmaths', str(ses2), '-sub', str(ses1), str(diff_file)] + subprocess.call(cmd) + + +diff_list_con = glob.glob('/media/Data/work/fslRandomise/kpe*diff%scon%s.nii.gz' %(group,contrast)) +len(diff_list_con) + +#%% Midazolam +############# +### DONT RUN THIS IF YOU RUN THE PREVIOUS ONE - ONE IS FOR KETAMINE OTHER FOR MIDAZOLAM ### +################# group = 'mid' for ses1,ses2 in zip(mid_func_ses1,mid_func_ses2): print (ses1) @@ -72,15 +93,13 @@ sub = sub[1].split('/')[0] print(sub) diff_file = 'kpe' + sub + 'diff' + group + 'con' + contrast - cmd = '!fslmaths' + ses1 + '-sub' + ses2 + diff_file - cmd = ['fslmaths', str(ses1), '-sub', str(ses2), str(diff_file)] + cmd = ['fslmaths', str(ses2), '-sub', str(ses1), str(diff_file)] subprocess.call(cmd) diff_list_con = glob.glob('/media/Data/work/fslRandomise/kpe*diff%scon%s.nii.gz' %(group,contrast)) len(diff_list_con) - #%% Creating concatenated contrast (across subjects) and group mask copes_concat = nilearn.image.concat_imgs(diff_list_con, auto_resample=True) copes_concat.to_filename(os.path.join(work_dir, "con%s_%s.nii.gz" %(contrast, group))) @@ -99,7 +118,31 @@ randomize.inputs.one_sample_group_mean = True randomize.inputs.tfce = True #randomize.inputs.vox_p_values = True -randomize.inputs.num_perm = 500 +randomize.inputs.num_perm = 1000 #randomize.inputs.var_smooth = 5 randomize.run() + +#%% negative +from nipype.interfaces.fsl import BinaryMaths #MultiImageMaths +maths = BinaryMaths() +maths.inputs.in_file = os.path.join(work_dir, "con%s_%s.nii.gz" %(contrast, group)) +maths.inputs.out_file = os.path.join(work_dir, "negative_con%s_%s.nii.gz" %(contrast, group)) +maths.inputs.operation = 'mul' +maths.inputs.operand_value = -1 +maths.cmdline +maths.run() + + +randomizeNeg = pe.Node(interface = fsl.Randomise(), base_dir = work_dir, + name = 'randomizeNeg') +randomizeNeg.inputs.in_file = os.path.join(work_dir, "negative_con%s_%s.nii.gz" %(contrast,group)) # choose which file to run permutation test on +randomizeNeg.inputs.mask = os.path.join(work_dir, 'group_mask.nii.gz') # group mask file (was created earlier) +randomizeNeg.inputs.one_sample_group_mean = True +randomizeNeg.inputs.tfce = True +#randomize.inputs.vox_p_values = True +randomizeNeg.inputs.num_perm = 1000 +#randomize.inputs.var_smooth = 5 + +randomizeNeg.run() + diff --git a/task_based_analysis/timeCourse_analysis.ipynb b/task_based_analysis/timeCourse_analysis.ipynb new file mode 100644 index 0000000..164e501 --- /dev/null +++ b/task_based_analysis/timeCourse_analysis.ipynb @@ -0,0 +1,466 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## This script analyzes the timecourse produced by different scripts" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/or/miniconda3/envs/neuroAnalysis/lib/python3.7/site-packages/sklearn/externals/joblib/__init__.py:15: DeprecationWarning: sklearn.externals.joblib is deprecated in 0.21 and will be removed in 0.23. Please import this functionality directly from joblib, which can be installed with: pip install joblib. If this warning is raised when loading pickled models, you may need to re-serialize those models with scikit-learn 0.21+.\n", + " warnings.warn(msg, category=DeprecationWarning)\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import nilearn\n", + "from nilearn import plotting\n", + "import glob\n", + "import os\n", + "from nilearn.input_data import NiftiMasker\n", + "import matplotlib.pyplot as plt\n", + "import scipy\n", + "work_dir = '/media/Data/work/KPE_ROI/timecourse'" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "# load ketamine timecourses\n", + "vmPFC = np.load('ket_func1_vmPFC.npy')\n", + "amygdala = np.load('ket_func1_amg.npy')\n", + "hippo = np.load('ket_func1_hippo.npy')\n", + "vACC = np.load('ket_func1_vACC.npy')\n", + "dACC = np.load('ket_func1_dACC.npy')" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "## load groups\n", + "import pandas as pd\n", + "medication_cond = pd.read_csv('/home/or/kpe_task_analysis/task_based_analysis/kpe_sub_condition.csv')\n", + "\n", + "ketamine_list = list(medication_cond['scr_id'][medication_cond['med_cond']==1])\n", + "ket_list = []\n", + "for subject in ketamine_list:\n", + " #print(subject)\n", + " sub = subject.split('KPE')[1]\n", + " ket_list.append(sub)\n", + "\n", + "\n", + "midazolam_list = list(medication_cond['scr_id'][medication_cond['med_cond']==0])\n", + "mid_list = []\n", + "for subject in midazolam_list:\n", + " #print(subject)\n", + " sub = subject.split('KPE')[1]\n", + " mid_list.append(sub)\n", + "mid_list.remove('1480')" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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A7gTwOs75PTkcW2PA8IIgkbQNXTqeH9PwRzM0/EZMw++u0pZecxgYfiu2ghH9gla0jq8xxOg74HPOPQBvB3AbgIcBfJxz/iBj7N2Msdf1+/oaAidmVvEfPnLvUDBbFa7PYcW6ZYY+fEVnL9sGamUrFx8+DVcZhs+hqSaly0Id1bKOxjAjl5m2nPPPAPhM4ne/0WHfl+VxzKsNdz0xj88+eBEnZlbxtL1jgz4dCTHEPJvhS0nHNKRPnXMOxsQDor4Blw4NSB+GpC2dQzGUdADo4iuNoYautN0maIfB8/JKe8BnEocXJFormErhleujaBZQKDCMlkwEPB7kN+LDb4W99ofBlkl9/8thjgKIisuaji8bw2loDAt0wN8maIUB8fLycJUxeAGHpXbLtKLWCi3HR9kWD4AsjbvpeCiHK4JuXTrE8B0/yJygtZVohs3hhKQj3t9S04UfcLzyfV/Cn335xCBPT0MjBR3wtwlIs768PDwMn3MuWisYaQ2fGD4F9IgBR5JHw/GlFNK9hq9M0xqwIyaynaqSjouHzi/j/FILD55fGuTpaWikoAP+AMA5x9/de7anxCMlK4dJ0iFnjdo8jTEmeuK7PppuIAP+aEmki1SnTtONpmF1q+GrUs6gE7ctaTstxB5od56cAwCcW2gO7Nw0NLKgA/4AcGJmFb/4iftx24MXu/4byfCHpIcMICyZAOTEJwINQaEqVCBb0mk4vvz9Rhj+oBO3ap1BySrAMkTxlQz4izrgdwvXD/D+fzs+8If4lQ4d8AeApVDWmK87Xf8NMfxLQyTpEMM3EwGfxhy2XEXDJ4avSDr1tieZcdcuHW/4GH7ZMsAYw1jZwkLdwV1PzMMoMMyuOgN/KG0XfOv0It5726P4+onZQZ/KFQ0d8AcA6uW+2Ojes03BZaaDpPOhrz2B93z2kf5PrgdQ0lSVdIAo4DeUpOxoKSNp6/qoFg3YZgHtrgO+wvAHHPApmJeUPMUdJ+ew0vbw0htEpbhm+d1hsSHIDyXCNTYHOuAPABTweynSIXfKzEobnKftfl9+bAb/+tClfE6wS3ih7VBN2gKKpBP2mQFUDT+etK3YBmyjANfrttI2yPx5EFAZPgCMli2cnm8AAH7gOfsB5BfwT8818NffON1xexBwBNvYBkrXRcPRdQybCR3wB4DVMOAvNHqRdERwcfwgc2XgeP6WT4GigK/aMoFsSadkCSavdsxsOj7KlgnbLMDxu2PrbXeIGH74wKH3SE6dw9NV3HRwHABwdqGRy7H+/ltn8Sv/8J2OMuBbP3w3fvOfHszlWIMAkZ9By3RXOnTAHwA2JulEbDbLqdP2glhR01aAJJ0kwy9ZBTnxqmxFl5hooCbeO+ccDcdDxTZgGaxrhq9q+IPWx+mBQ1ZUylO84PAUdtVKMAssN6cOve/jl1cztz92cQVPzNZzOdYgIAvWdMDfVOiAPwBQYF7sRdLxfNihVn4po/jK8QLU216m3LNZkEnbhIZfNA0505bkDgCiZ3yo4be9AAEX7Fgw/O1pyyxZBdkqghxHzz88BaPAsHuslJukQy6mxy+vZG5fbLoDfwD2gyVZoaw1/M2EDvgDAEk6Sz1IOi03wP7JMoDODN8L2/VuFciWaaVcOgVZeFWylYCvDEGhtgpV24BldB/whylp20o80CbCmoLnHZ4EAOyfKOfG8J01GH7b89Fw/Firiu0GIgKD/k63Gv/ynQu464n5LTueDvgDgJR0OjB8zw+wkNBq256PAxMVANlefAoI9fbW3TBeyPBTPnzLkL3h1YC4Y6QoXUaUnKvYJmyj0HO3TGDwDF9IVtH7e9PNB/GHb7oJO0dLAIB94xWc3YKAv9TY/vo32XW383vYCN77uUfxR198fMuOpwP+AEBBeanpZjor/vc3TuPl7/tSrPlWyw0wWbUxUjQz2ysQ8+2UuP3YXadztwi6HWyZRbMgbXZqQNxZK8rVido62TYLPVTa+hgpCq180Gyw6UaFZQCwf6KC1z1rr/z3vokyLq20chmKQiugrIC/mFg1bUeoTefywnzdSRGnYYPjBTg1t3W5Fx3wBwAKypwj1SMeAB69tILFhhsLaK2w86QImmsw/AxbW8v18c6//w7+951P5vUWAHS2ZZYsQ2qyZUXS2TlaxHzdgeMFMjiRLbMXhj9aMsEY0BpwgGslAn4S+yfK4By4uNR/dTR9PheWWqkhKxTUBv0A7Ack6TRyfA9v+6t78Muf/HZur7cZcLwA5xaaWzYpTQf8AUANyovNNAO5FAYI1ZPc9oSnfedosQPD7yzpkIf/TM69XYiVm0lbpmmAFidqQCSpY3a1LQN+OdTwe6m0LVkGSqYx8ADXcoPYAy2J/eMi55KHNVOVsk7MxBnh4iaw463GUs7vYb7u4N7TC5gZolYkWXB8YV7Iy767HnTAHwBWFdkly5p5IQz46sUvGf5oKTNpG2n4aYbfDj3uZ+bzvag82TwtqeFHl1VM0hktAhBJ55iGb3bP8OlzKNtbF/B/8eP34+c/9q3U75MupCT2TYQBPwcpzfEDaftMyjqk4Q9Dy+iNYjlnH/7Xjs+C8+GXuei6f3JOB/wrFvW2J4NfVvEV2S4poHHO0fYCFInhr7Ri9ks/4FJeyapUpIsqbxbhB9m2TBqCAqQ1fED09E+7dLr34RctA2XL2JJKW845/u3Ry7jjxFxqm2gO1/kW2jNWBmP5dM10PB9Hdo7ANgopa6Z6DQ161bMRuH5UQ5LX+X/1sRkA2yfgb5WOrwP+AFBv+5L9JdsrtD0fc6EmSxcrLedJw2+5QaxFgcqOVzMkHdo+u+rkWroeSTprMHw7LelcXmnHkrZFswDH6+7GbIcMv2QVtiS4nV9qYb7u4PJKOzWEveWtreHbZgG7Rku5OHUcL0DFNnDtjipOJBj+YqJ6ebtBzWPlcf6cc3zlcRHwh/kBGChETTP8KxirbQ/7Qn03Kemo+jwlJUmDL1kGdtVE0FS1SdWbnsnwlWV+XjZBQGmtkGL46Rm3ALBjxAZjaUnHMpgs4loPbS8IA76xJUnb75yNhpgkA23LWVvSAYSsc26x/5vZ8QPYRgHX7RzB48mArzD8YWe0WVBJTx6SzmOXVnFpuY2JijXUvXnU+3JbMXzG2GsYY48yxo4zxt6Zsf0djLGHGGPfZox9gTF2TR7H3Y7gnKPe9rC3Q8C/qFTRRgw/GrQxTTq48mCIM/zOkg6Qr45PDD/pw1eDvBoQTaOAqaqNmZWWdGNUqNK2Bw2/FEo6W8HeHjinBPxEsrSp9ArqhP0T5VzssI4XwDZFwD8z34gFRvUaGmZG2wmk3+8YsXM5/6+G7P6Wo7vQcoOhbSqnBvxtw/AZYwaA9wN4LYCjAN7EGDua2O1bAI5xzp8J4JMA3tPvcbcrHF9UxI6VLYwWzZRLR7XwUVAkrbpoGjFZhKA6OBpZLp11Aj7nfEN+5a6StomAOD1awuVlIekwJmSqXlw6Tsjwy7axJUU63zm3hOt3jsAyGE7MxJl10oefhX3jZVxYbPU90FwEfAPX7RxBwBHrm7OwTRi+6weZnwMx/F21Ui4B/8uPzeC6nSM4Mj0CYHgfgkRyRksmzsw3tiThngfDvxnAcc75Sc65A+BjAF6v7sA5/zfOOUWaOwHsz+G42xJkm6zaBsYqlnRYENQ+Oa0Mhk+JT3W/di8MP0PS+crjs7j5dz6P8z0yUWqt0G3SFkCYdG6j3vZRtU0wxnpi+ELSMVCyDNmtcrPAOcd3zi3h2QfGcWgqrp1zztFS2j93wt7xMryAY3a1v8E1jhdJOgBiss5iw5WdOoe5UvUH//Tr+IPPP5b6PeVGdtdKfT+wWq6Pu56Yx0uun0YlJBvD+hCka/6GXaPwAo7zi5tvIc0j4O8DcEb599nwd53wkwD+JWsDY+xtjLF7GGP3zMzM5HBqwweyTVaLJsYrVqq9QozhO1RuHjH80aKJsmUkGP46Gv46DP/MfAOuz/HQ+eWe3oucadulpANAuoyarifZv91DLx1qWFa2Np/hU8L2GfvHcGR6BMcVhk8P2fU0fJoD0G/rascXks61O6oosLg1c6npYs+YWPkNa3ADgFNzDTyRIV0Qw99ZK8HxslcB3eKbTy6g7QX47ut3oGyHFdlD+pnQfXl9+BDfCh0/j4DPMn6X+Y0xxn4UwDEA783azjn/AOf8GOf82PT0dA6nNnwgBj5SNDFetmMJNwC4sNzCXrp53TTDZ4zFWhQA8YCeWXgVbt8zVpIDOlRQMEpKFushao+cbq1AKNnxbTtrRcyuOlht+5KBUbfMbjp9Rgy/sOk3MiVsn7FvDEd2VnF6riGlp2ja1dq3ED38+pUV1GT13vEynpyLSzqUExrmJGXTyZ7ZQH10doeGhH4e5FTDcu2OasTw3eH8TIjkXL9rFABi3+lmIY+AfxbAAeXf+wGcT+7EGHsVgF8F8DrO+fAMZt1ipBh+UtJZauHgVCXWOkBl+IDoOqmW16uSTlZrBbqwjkyP4OxCMxVYNxzwO028CoNcgUG2dCbsHC3BDzjOLTQkO7aMAjhHV8yu7fkohgx/s7XZB84twSgwPHVPDUemR+AFXCbX6NjrMXza3u9qhJK2AHBgImrKJgbNBJLhD6uk4/kBHD/IDPhLTReWwTBRFbJUP98rrRbGypZcQQ7rqoeI2v6JMkpWAae2IHGbR8C/G8D1jLFrGWM2gDcCuFXdgTF2E4A/hwj2l3M45tCjE1tdXU/SWW5hz1gZZcuQFyrdxMQmk3IGXTi2Wci8oWj7kekqVtte6iFD3v2TM70xjM4Tr6LzpF7xBCo4OzXXiDF8AOvKOn7A4focJdNAaQuStpSwLVmG1M7poSjHG67j0qHt/fR555xLWyYgAgQV0dF3GTH84QxuFMSzzm+5JXIQ9HDsZ+VGAb9WtlDJ4fU2E2p9zaGp6vZg+JxzD8DbAdwG4GEAH+ecP8gYezdj7HXhbu8FMALgE4yx+xhjt3Z4uSsGP/ahu/A/PvNw6vckuaiSDtnGgoDj0nILu2qlGIOlC4PkgaJViCUsaftkxc6UdCjgU9A6k6i4XW2Lm2Tjkk5ypq04z6xgSEnn+bqDSqixko9/valXJG0Rw297m2e5o4TtM/aNAQAOh44P0s6b8iHcHcPvR2rxAg7Oowfj/okKLi230XJ96fIadg2fgm62pOOiVooYeT8P8qWmi9GiCaPA5PU1rJ+JStSumapsycQyM48X4Zx/BsBnEr/7DeXnV+VxnO2CxYaD20/MpuyKQHTBV2wD4xULAQdWHQ+1koX5hgPX59gzVhK9YhIMn7TxsmXIvvJAdOFMVO1MSYcCJdnUzsw38cz948o5ie0LDRfzdQeTVbur9yknXmUMQBH/zwj4oa2UPgMgCmSi54/V8XhtN2JEhJbnyxt7o2i5Pu4+NY8XHtkhawooYfvM/SLgjxRN7K6VUgx/vYCfh4avBgYAOBAOwjm/2JQMf1etJGTAnFY9QcBxer6BQzuqubwevf+s63Op6aKmMvw+3sNy+FoAFElnODV8ygcRw/+3R2bgBzxV15IndKXtJuDOk/PgHJkzZtWkLVnpyJpJDp1dtRIqtpFqrUDBo5TQrymgT1atNRk+sdQ0w49uiJM9sHwvCGAUWEq2ofPM0repcAxQAn74YFyv2rblRUE2j+U/4R++dQ4/9qG78L3vvx3fPruILz82g7f8xV0AgOdeMyn3u27niCy+orzKehp+JQfWKgO+ETF8QFRNU9J/vGLFZMB+8YVHLuMV7/sSLizlU5ndkAw/S9Lx4gG/T0mH7qvtYsu0DQPXTFXh+EHP1uheoQP+JuDOk6LRVhazoN8JDV8waWJp5K3fPRaXdLIYfpaGP1Gx17RlTo3YGCtbKWtmXWn10Ius4/k8xe5j55kh6ZQsQ3Z9JNuc1PDX8eKrDD8PNkiYD4vOLiy18Lo/vh1v+Yu74PoB/uebj+Ho3prc78i08OJzzqNeQF1KOv0EMcptRJIOtV2OGP5ExUYlxw6i5xYaCDgwt5rPABGV4SfzW0LSMeU4zH564m+rgE8DhEwmpcO//PqpTT1mLpKORhwy4GewmdW2GEZumwWMhzNQSYclS9nuWkLS8eLyQdKSKDX8qo2G4yMIOApKILsNgw0AACAASURBVHb8AIwJ6eXAZDlVfLXa9nDj7lHMrLZ7Sty6Pk/10YmfZ3Yw3FUrYbm1Km9IqeGvk7SNklwGTEMEjTw6Zq60PNhGAV/8pZfiL772BGolCz/y/IMyF0E4snMEq21PNH+TSdu1OZNM2vZxnklJZ1etBMtgOLPQQK0krqHxihW7ZvrFUmiV7Ld+gEDnxbkI/qoMtxwGabka6pPhk3QZJcyHU9JRV2437h7BW15wDT70tSfw4ut24OU37tyUY2qGnzPm6w4euSja12bplfW2h2pRXIg09Fpl+AUmeopUbFP6h5Padck20FLYsMrwgTRDonYEjDFh6ZtPSzq1soVrp6q9MfwgSCVsARHAjQLryH4pcVtRCq/U99EJqluJGrTloVmvtl2MlEzUShZ+4VU34K0vvjYV7AHgujCQPHZpRQb8rP1U0HfWD/NW3RyA6F20d7wsGH7TgR2ueISkk09wW8p5bKL6IFJlHc55rhq+yvDt8DocWoafeJC/6/98Km7cPYpf+sT9uLy8OVW3OuDnjLueEOz+WfvHMhm+CPiC3YyVSdIRDP/iUgs7R0swjdBnrjB8OwzYgGhdoFYkRhq+LY+hou1Flr4Dk8LDrbpb6CF0ZGc11SBsLbg+T027IqiySxKUuJUunS5tmSrDj5hzDgG/5ck5uWvhGfvHULENfOq+82h3actkjIXf5cYDcVLDByJr5mLdxXjZEsexzdzaTVDAV0mL6wf44FdPxiq7u4VKQtSHUtP1ZW+p3AJ+SKQYY6jkmNfIG+2EVFeyDPzxv78JdcfDOz5+/6Y40HTAzxl3nJhD2TLw/CNTmXrlajsKLsREiOFfXG5hV2ivU5fnbTeItRymIEM3nuMJyYZeLzPgh0x052gRjh/EervX2z6qRROHd4zg9Hyj6742fhBkOpGAMLHaIRiSF58YfrFLhp+0ZQL5JG1X235XAX+0ZOH7n7MPt95/Xk6xWk/DB9D3dK6khg+I4qsz84Lh08qubBVyky8kw1dIyz2nFvDb//wwvn48PQxmPagyjWoSkL75kiU1/Kzv9JunF/AnXzq+9jFcH20vkPcBgFxlrrxB13vRiK6h63aO4re/9xn4d8/cA7YJZh0d8HPGnSfncezQBMbKwnKZ1JjrTsTwbbOAqm3I4quLSy3sVuQOtbVCUQksFPybiounaBbk6yadECTpAJCJYrrRHE9UQI7YJo7srMIPOE7Pd8fyPZ9nSjoA8NIbpnHs0ETmNnLq0AOBGP66Gj7NBQibpwHZkk63nTcJJOl0g7e84BAcL8Df3i3aR61nywQQMvz8NHxAMPzZ1TYuLrclo63YZozNen6ARy4u47MPXMBH7nwys7FeJyxnMHyq7t5IIziV1avnSG0VVIaf9Z3+3b1n8fuff7yrc64pAV+9j4YNbsaDHAB+8Ln78cabD6bcb3lAJ21zxNxqG49eWsHrnr0X1VCuqDtejOmutn3pUgFEAFYZ/guPTAFATNJpu0GsZ4ssUAkDAUk21fD3ydwBNd4ColWAXLIrlb+Hd1BxUR3X7Rxd9/26AU9V2RJ+74ef3fHvdtZI0ulRw1cYPnmVk8z51Gwdr/69r+DvfvaFeEbooV8Pq20Pu5T6gLVw/a5RvOi6Kdx+fE5qxOuh31bOMjDEJB1hzXzkwjJeesO0PI76efzKP3wHH7/nrPz3SNHA993UXaPaLA2frqu5DbTSVqWmTIZfNmEZBZgFlrkamlt14Hii31KnQKi2VSBUbHP4k7bm1vFuzfBzxN2n5gEAzz88Jdl2Usevt+N68VjZwlLTwZcevYyVlocDk+JGLtuiktQPOFqeH0sOJtktzXmNGH4i4Hu+DBbJgC/rAkomDk+LIpuTs90lbj0/2FCRCFWFjoYOk65dOkryuhPDv/vUPBw/SNUarIXVVrTq6gZvecEhAOs3TiP02/enE8MHxHcfSTpx+eLETB1H99Tw0Z98HoCITXcDco6pzJxacMxvJOCrDL+tMvx4kO5USzBXF6uK9hqkIDvgD6+G73gBCiw9QGgzoQN+jiBb5eEd1Y5su9GOB5fxioUHzy/jZz/6TTxtbw0//F2iD51asNNKMPxSQr+mXunk/kkWfKmNtzoG/KKJ0ZKFXbUiTlzuTtJxfZ7qlNkNnntwAn/wxmfjReFqRlbarqvhK0nbDhr+g2GL527zEECYV+lS0gGAVz51F/aNl7uSc4B0IO4V7YyAT8QAgLT3Jn34Cw0H105XpbTWi6QTrQBVd434+41JOunXUY9D9tJOPZJmw3qA9hpJ6ayAXx7mgK+svLcKWtLJEcSgRksmKsTwEwF/NcHwJyo2vr40hwOTZfyvn/guyXqjHiw+2p4fGypCgYaSmNRBsiPD9yMNfy1JBxATmi51aQnz1kjaroVCgeH1z45GJtiS4a9TaavYMmnFk3SlUE//XpwkKy0Poz0wfKPA8N++92k4NdvdKqJkG5LJbgSOUoJPmB4pyjkClJdJBreFuoOJioWiKaSnbj31bc+XuSf1+qW/3xDDd32YBQYv4DESROYBtVgq6+FID5mW52OsQ/uN5GvR66njQIcJjuKe2yrogJ8jVlouKrYBU9XTE57juuNLJg4A10xVsGOkiL966/NifWbU4Q0phi+TtuKmpAuHbI4pl47bDcMPWy+Xra7HHXaqtO0VXVfaKgy/mOHDDwKOhy4sx/ZdD44XoO0FXbl0VLzixl1d71u2Cri0lEdrhei6KRQY9k2U8cRsXTL8shW36y41XUxWbDDGUO2B6apDxesZ7pqNSTo+pkZsXFpuZzJ8GhSTJX+1PR8rrXhNSuZ5N7I1/GHth6+657YKWtLJEcstV164Uae+6GIjTV6VdH7p1U/BV//Ly3FtokmV6klOMvxkV0Gp4Wc8ZID40rFkiSpfujnkyMXwnEZLFpZb3d0grh9sSNJJwu7WpUNJW7OAQoGhaBZiAf/MQkMGpbUCg4q6ksPYLGyGhg9EOv54opVA0/Wx3HQR8MiVNVI0u5Z01NVIo51m+Btpt9B0fdRKFiyDxR4iy02x4qXrKGt0pfqAaa2xcqPqYNUUMey2zOIWSzo64OeIlZYntUipp7fTDEllk4UCy/SrR31APLTcIDYYPNmB0fECFI0CTKOAollIyUjq0pExFiaK45IOnVOtZHYtP3gB35CkkwS9xvqVtuJ9UNuIpCtFHdHY7cjErO8kb/Ttww+DXPKzJqdOJOlEJIMGm1MxXrVodi3pdGL4dC3P1dtdTSdT0XDEhLNq0Yw9RJZbbjxAW0aqtYL6gFlPw1cfHgBQsYzMhm3DAHcAGr4O+DlipeWtyfCj1sjrB5eoD4gv5rhmDAZvuXENH8hmcmrSFkAs4K8kA37ZwkorXTBG5/If/+Zbsie8F3SutO0F3Q5AaXt+jBElk6EPnl8Ou3dCVsKuB/qsRjeV4Zt99YfJKrwCFIZfied9mo4vAz5tq/bA8OnaEL2ZVJdONGO510Ro0/VRsgxUbVO6fehYtWShVOK7U5PEazN8NybnAFEie7PmJqyHlZaLRy5mz4oehIavA36OEJJOguFnaKAjxfV1u7ikE8QKryi4U8BXpyFVimmttr1GwE8mbUdLJhw/yNTAv3Z8Fv90/3nccWIWgLBl5sLwC91r+OpKJymVPHRhGddNj6BoFrrW8KPvpHMf/n5RtgubIum88MgUbtw9Kh07qqSzUI+CNiCux14Z/p6xUsxCqf59rzp+UzL8eL+f5WTAz5C/OjH8+84s4mc+co+UApMPDyBa9az1oNhM/NUdT+L73v/1TALl+AEsc+ssmYAO+LliJezrDdB4v6QGGtfL14La2rXlppktEFXxthXJRzCoLJdO9MBIBnzbLEgvPElSausFwlcemwm3idf3/HyGNRQKDJbB1tXwxecQdyuplcwPnl/C0b01FE2j+4Df2hoN3wt4zxXAhKxeOgBw08EJfPYXXiJXZ+oM1/mQ4ZNHv2qbXUsblN/ZM1aOOWpW2548h16tmU3XR9k2UElcnwsNRzYRBEINPynp1BWGrzwMvnFyDrc9eAmnwklRoutm/HscdIvk+bojSVsSmuFvc6woSVvhjIgvX+nm6Sbgq83B2l4Q83ynNHyF4VeLZkrDbyceGGrAT9pE6fyzinS+HAZ8+ls3yCdpC4jiq14ZfsmKkrazq21cWm7jaXtrPTH8lR5WXRtFyeov6LTD73e9UntJBBxfNuSbqEZJ26zurVmg5GeK4TuelJE2wvDLlhky/Og151YdTI1EQ3GyVkOzKsNXvld62J8MA36WpKNKo4MAvdes4yel1q2ADvg5YrnpxbRgUeWX1vC7SRBKH37bS2XzqQRdavhuxOArthF7yADpAo8kw1fPh1YoKwmGf2q2jtNhW2VK6no+h5VTlaBtFrqqtC0m3EoUHChhe3RvDbZZ6NqHLxn+pko6/U296jYwqGx2vu7CMph0bvWatK3aBsbKFhquL+WIetvHwSkhH/XaXkEw/EK40hDn4QccCw0HU8pIzawitdnVtmwkpn6G9N2fUgI+rVAJg2b4dL5Z/Xza/ja1ZTLGXsMYe5Qxdpwx9s6M7UXG2N+G27/BGDuUx3GHCS3Xh+MHsQuuWjQTLofuGT4ldhfC5XWyqlMdc6gG9JGECwJILx3HwsSsH3CsJip/yTGRtGYSux8pmlLu8XKyZQIhw+8iaVtKavjh50v++6N7emP4NMB9syUdIM7y1JnE66HngO8Khj8RevABCvjd+/DHyhYqRQN+wOVnudr2cDDMF/RqzWw4Hiq2Gd4T4tpabDgIOOIB3zbRVB4ydCzqsBpn+OL9PLEGw1fdboMAHbcjw99ukg5jzADwfgCvBXAUwJsYY0cTu/0kgAXO+XUAfg/A/9PvcYcNVBhSSzL8tqqBii99pAuXDgU2Wpon/bqqfq1KNhU7zuQ8P0DAkWL4gGDqQtKJHiZSw09YM7/82Ayumarghl0jUu5xc7JlAkKfdry1nRSC4cftqZSMe/D8MvaNlzFesYWG36UPf7XlgTFh39ssJPu8339mETf/zuel22k9dBsYSoqkM1+P2iYDQNU24PhBVy0nKPlZlU4zH274t9MjRZSsAubr3T+wgoCj5QYoW2HSVto7xbUdk3RkFXl0nnP1thzBGWP4ThTwHS9A0/XTko5lxvbdalBNQaeurtvRh38zgOOc85OccwfAxwC8PrHP6wF8OPz5kwBeyTaj9+cAQax3VGX4dlw3lbbMLvRiGpzRmeEXpPUwzvCN2Koiy9KnVttSL3wCnf+KwvDbno87TszhpTdMo1a24gw/B1smnV8Ww19quPB86gqakbQNRzreeXIOzz44DkC4mLqWdNo+RmwzNhIybySHtTw53wDn6Hpgdbc9V1Qr8GLDxUQ1vtoEuhtZmBw5WG97sdXpVLXYE8Onh3LZNmKmAnqNuKQTb/1N++0Law5iDD983VNz9aiPTmW4JB1qGpfl0tquGv4+AGeUf58Nf5e5D+fcA7AEYCr5QoyxtzHG7mGM3TMzM5PDqW0dJMNXXAJJi2TSEbMeKrYh/dTJzoxkXwsCDtfnkYYfarW0JM5yeMQDflLDJ0knYvj3nFpA0/XxkuunUStF+r8XdO6H3ytsowA3wT79gOPl7/sS/uL2JwAgTF6nbZn3n13EzEobtzx1l3ytbpun9dILf6NQk6kAsBR+p91q6huRdOYbcYZP33E3iVuSRmTHV8ePFahNjdg9afh0D1DhVdsL4PmBdN/Ek7bxhyPnHHOrDvaGHVbVBzk9FC4tt3ExbFzYUdIZUE98eh9ZDxzHy8fW3AvyCPhZZ5xcm3ezDzjnH+CcH+OcH5uens7h1LYOK50YfkzS6W6UHqFkRQE/OTtVSDp+isGPFE14AZe/l/1nlEBJLGhJSjrxSkezwGJJ2688NgPLYHjBkSnUymY8aZuXhm+yFMO/uNzCfN3BA+eEPp+0ZVLS9vMPX4JRYHjZU6bD95q2Zd5zaj5zWd3rd7IRJINYsuhtPXQr6Yi5xZFLZ0Jhzp2G42RhKcnwHU8G/GrRxGTVjlkl1wMF5pJlKK/pRwx/JDrPpANtpe3B8QNMjxZhm4WYDVdlzfedXQSAlA+fmhgOqid+cy2XzjattD0L4IDy7/0AznfahzFmAhgDMJ/DsYcGaqdMQrIXtzrAvBtUbEMW0HRi+MkB59EyPGq7AMQZ/ng5HvBVSYcxhtGSGbNlPnxxBTfurqFaNDFWFr12OOfwgo31w8+CbaRdOjRs/cnw/20vQ8N3A3zuwUu4+dCkbDGQTNouNhy84c/vwCfuPYskVlq9tUbeCMoJW+ZiI170th66DQwkA9YdHwsNN+Zvp+uum2rbKOBHMx0iScfAVLWI+R4kHQrMFduQD9eG42Gu7oAxxFYiyQS3+lAoJtxXbTcaZ3j/GRHwUwy/T0tsv5BzqTtJOsbm5Y6ykEfAvxvA9YyxaxljNoA3Arg1sc+tAN4S/vyDAL7Ie23GMeQgRpxy6aiFV44vE2HdoGIbStI2fmEULcF22r64kCggJLXarF7q0SxdBw3HT7mGRHuFiOHPrLSlS6JWsuAHouunm6Mt0zLSzpozC0LjPj1Xl+8lWWkLAI9fXsUtR6PulcnAIFpFAGczhqJsBcNPstZklfN6SFZKr4WyZeDySht+wLMlnfCYrh/geb/zefz9N+MPQTX5GWf4vnwdknS6vYUp6JUtQzLuetvD3GobExU7RhqSqyEq8JqqFlOFdk3Xx427xWS2+zoE/PKgNfzwfVwxGn6oyb8dwG0AHgbwcc75g4yxdzPGXhfu9iEAU4yx4wDeASBl3dzuIA0/i+HTjbHUSJd+r4WSFSVgkwyfJJ0kw1dHKwLKoGTlwqJzoIEtyaKj0ZIZs2XOrrblHFr6W2qhnJctM8uHfyZk9gsNF8stN9VTSP1M1IBvm3ENn262S0vpPv+rra2TdIjlLW5A0unWzVG2DZkMVgN+snX2QsPBpeU2Hr4Q7/NCD6Pxiqrhx5O2k1UbbS9IDdrpBAq2ImkbrUDn63EPPpDF8EnnTzP8pitaLu+ulXBiRjiekgG/aBZQYIMvvEo+cDjn23cACuf8MwA+k/jdbyg/twC8IY9jDSuWWy4YQ4zBV0M9nSplZ1ZFJWi3IIYFpF065Q4afrJLZ5ZLp2SJfvLnwsCQLDqqlSyp0/sBx3zdwY6RiOEDUaVlnknbZKL17ELkYjk91+jI8NV+MgBSrRUo0F7KGISxFQxf9rhxNsbwe/FrV2wD58LPbbKaZvgk6ZBUmEy+RjNmrVhwpuE0I0VTBun5Vaerz44+/7JloBCa8+qOh7lVJ3aOQHo1RFW2O0YEw1fttk1HEIBDOyq4uJydtGWMCavyADT8QKlhSEo69HluR1umBqKpSaq9r5pYTl5ebsWGnKwHtatm2odfSGj4UUUlEAWTrOEZgLgxKDAk8wqjJVOuWBYaDvyAY0eYWCMXDyXtOg0x7xWZDH+hIVdMJ2fr8AOeStoCcXYPhJJOhl/70koHhr/JGn7JTEg6iVkE66EXJli2DPk+xzM0fLoW6YGdbJGgjgmMEp5+3JYZXguzXSZuI5eOGa1A2z5m621JJAiVxGqINPzJaoaG7/ko2Qau3TEi/zbLRDConvjNjGuQIInYdiu80hBQO2USVL2y3vZQd3wpjXSDrP45hHKoZ6pDQQAoxTKJgJ8IGGNlSy79kyytVoq89qShTocPKmJQdCPmxfCzeumcnW/gBYeFe/fxSysA4jLO7loJBQa89ul7Yn8nfPhpSSc56o5zjlWnt/GGGwENa0m5dDoMmnG8IMb+e9F6y7YBktYnM1w6q4qkA2QFfPHvsbIlV1D1mKQjkrYAuk7cqknb6MHjYb6eZvjJ3jdz9TbGKxYso5DW8B0fZcvAtTsq8pyzsFWDzBcbjpQhgUTATzB8uta3oy1TA+k+OgBilYpUSr+zh4CvSjpZlbZN109p9BS85Ui4xAOBMF6x5DI4mbQdLVny72dXaEkdMvyUpJMnw4+SgI4X4OJyCzfuHsVU1cajF1fC9xF9JjdfO4lv/MqrcDQhk5GkQ7kTChKrbS/mUhH5lc1tq0BQWeZ6ks7vf/4x/MCffl3+uzdJJ3ov44qGXzRF/6XkXNpkAZXK8I2CcP0IH74P2xCzhClId9tAjSyRJcuQ19pS08Viw41ZMoF0VfLcaqTzqwyfcy7681gGDk1V5Tlngd4DAPzpl07gZz5yT1fn3St+/VMP4i3/6y75b5XVJx84ERHbfi4dDQiXTtoDHDGkyyvElDcY8DN66ZCjAlB8+KUOkk4Gw6eZECmGXxbVkH7AMbMqHgo7Eklbar+7WS6dC0tNBBzYP1nBwakKHg/bEKgPLsZY5udJ+9ADRNVP1QHtW9ELn0B9f9qeL7+zTrryk3MNPDkXMcVeJR1ADFpX23wILTvqib/QSdJJzIWlPvqqpXjjkk4U8IkJTyUknWRn0dnVttynqPjwnbBlSMkq4PC0CPidDBFiCIp435994AJue/CS7L/TCy4utfCezz6SabH0A46vPDYT65Gksvrk33S6LzcbOuBvEGfmG/jUfefkv8V4ww4Mv60w/NrGJJ0shg9ETc4iDT/ut+40LUm9ObIkHUDo28TwKbDSKoaW83n58IsJDf/MvJCbDkxUcM1kBU+G1syktNXptYBoddPsEPBXtqAXPoHqJtTxgZ088cstF03Xl59Hr5IOAExUrFQ7ZTENLdTwwwd20/VjTFTOhZVzck00Qg2fgnXFNlG2jJ4lnZJlSF88dV5NunRk8Rgx/LojV5cly5DfKQX+kmXgwGQFBbaWpCPegx9wPBpKg5++P1kqtDbqbQ9v/cu78SdfOoHvnFtKbX/g3JKsXKeVpfq5pjX8OFHbKuiAv0H87d1n8PMfu08ypkwN31YZvgg0vSVtxd8zlg741HOE3DR04RRNA7ZZkJY/6cM30gyfkJZ0ovYKs6tt2GZB6tyWUUDFNqS7I7dKW4PFNPwzoWd+/0QZBycrcjXSjashCvji9dSbTdXx5XjDTdbwgchGSwy6ahuyNXMS9J3S9l4CfkUGfDu1TZ2VoDJ7tWqWWiPT90qrgqSbSVTbdivpiOZ+RoGhUBArjdPhAz0Z8Kl4rKky/Gqa4Uvnj22gaBo4ureGa3dUM49PctoTs3W0XFEs+OlvX+jq3AHB3n/+Y/fJjqz0Har42nExBS7g2e0Ukhp+p/tys6ED/gZBwYKW3pkMX/Exz6y0YRaYrHLtBnTzCtYTZ2vEdIkxqoFwtGjGgkVyOxAP+GlJJ6rEnVlpY3qkGDv+WNmSN3tutswEwz+70IBRYNgzVsLBqehGLlrdBPx4x0V1vF1M0tlChk+zVen72j9R6ajh06ptueVKv3axy8BAkk6ngL/aTgd89edki2HxkPBRd+IV2Tt66KdD064IFdvsKOnQe6AVzmLDlU4eleGrxVwA8Mn/8EL88v/xlMzjU9KWag7e8Nz9ePTSCh4L2f56+P/+9VF8/uFLeOuLrgUQ1VGo+Nrjs/Jnuq5acmVTSDF8bcvcZqAb5/R8HZzzcNpVPJirPubLK6J4qZeujBTUk1W2QLR0TzJ8QASw1S40fAAosHRRFzH8lZaHmdW21O8JtZIl2+Pm1S3TMgrwAi6HTZ+Zb2LveAmmUcA1U5HHvtRFkksORaeAr2jIF2MaPrHtrUvaUluFfRNl1J3s4drLiouHAkPPkk41TSxGlMrvhYYjbZtziYCvyn0V25CVttUkw+9yzGHD8WPtp6tFQ16fSYYPRIaEkzNCxiM5McbwvUgmov93Wm2qAd8yGP7jK69HgXUv6/zdvefwyht34udfeT2AqGU5oen4uPfJBewK5Vp6b8Twp6rFji4dLelsE9DS+NRcQ9y4HGmXToLh95KwBSLHRTIgA9FDIIvhjxRNxaUT9+kT6GavFs3U6kGdazu76mA64aSolU2p3+bWD5+CdMjyzyw0sH9cBPpr1KKqrhh+WsMvWwZ210oxSSerOnqzUAqdIvR97R0X0l4yccs5l5bY5ZbbMQfTCWtLOob0/i/UXVw3Lfzrqha/nGT4til76agV2dWi2bW3vekKv7z6moDI/2Tp7mVbyF9//pUTKFkFvPppos5iLYa/FsqWiabj4aELyzgyPYJ942U8//AUPv3tC+u2h+CcY67exvW7RjFaMlFgiOVhAOAbT8zB8QO85mm7AUQBn4L8RNVaw5apA/62AN04T841oj46qeELlEAVDL8XSyYg5nsCazP8pQyGP1pKSzqdGH6Wfl1TeuLPrKSLY2olS5bV52bLNOIB/+xCEwcmxdCL6dGi/CyzPosk6KHQlnpvgLJtYFetFJN0ehk52S+oMprkgH3hwyxZfNVyA8nql5texwHmax0HQKxTJkHtRT9fd3DdzhH5MyEp6RDDr7e92EqIZJdu0HT8mOOMjAWTVTtzxVuxDTx6cQWfuu88fvR518jrjxg+WTKB7pL4FdtAwxUM/+geYeH9d8/ci5OzdanLd8JS04Xri8LDQviAWkxo+Lcfn4VtFPCyG3cCiCQdOsfJalEnbbc76lLDr3dkipSgarQ9zKy0emb4NK0ni+GXwgslYvjRhT9StGTS1vF9GAWWctNEtruMgB9W0y42HMzX0ysT9cGW50xbAHC9AC1XuJoOhEMvGGNytF7WZ5FEUsNvuj5KZgG7asVYta3a8nezobp0GBMDwtVzIKhzCFZabs9+7XIYlCcqaeZM4wWbjrCGHpiswDJYStKJBfwi+fDjGr46T5jwV3ecwvf/ye2p4zYdHxUr3nIEyJZzABHET8zUYRYY3vaSw/L3ZE12/CCmj68HKka7tNzGU8OA/4owON9zamHNv40KD8U9MF6xUxr+Vx+fxXOvmcD0SFzSofqDqard2ZapGf72ADHcJ+caUnNNaviAkGWWWy7m6o6sVu0WxIqyWEyS4avSymjJlPp0uCh0BAAAIABJREFUp6KdtQI+Md7T8w0EHCmGrwaEPGfaAuJmpq6Wan8c+rkbhp/U8ElSEAy/LZfxK20PRbOwJSyLNPylhoPRoikfqqmA31QDvtdzRea6Lp22L6tsp6o2Jqu2zMc4XoDLKy35MAKimQ7JQTlZw8YfvrCC+84spvISjQ6STrLoSn1tAHjTzQexsxadC0l1LTeQWr6aDO6EqrIPBXySNNfrsTMjCw/FPSAYfvSAnF1t45GLK3jx9Tsk4YsCvjjHiYqdKrzK6mK7FdABf4MgDf/8UlM2eEq6dACxfD0djrTrmeErLp0kVJdO0sUzknDpZF1UxNKz5AzTKKBqGzJplpZ0TGXf/JqnAYDrcdkWef9EWW6nxG1vtkxxk7VDDX9nrQTHC+SSfLWVro7eLFBbgKWmi/GKrfSU6czwhYbf29J/LZfOSFHMtSVZa6JqY7JalJLOmQXxgD+k2BsrtphQFfA4OaAhM2pwb7kil5XsAtrKSNoCQurIQsU2YBsF/MxLD8d+T9d82/N70vDV6uOn7hHtlNVhMWshmsolPs/xihXT8KmA6+n7xlLtKxquB9soYKSUHszeyT232dABf4MQmqZYKpIO2Inhk3WzZw3f6szwS0rSNhkMyKWzVgtWtZIyC7WyhZNhy9m1JB0zr0pbmbT15eATleEfu2YCExWrq/bSWZIOJW2BqInaVnTKJFTCIeJzdQdjZUtaQdMMP/r3SstTku7d3arX7xrB4ekqnprRlVVWuSrdNKeqtiQsp8LgdY1ig1WvDzVpmzVsnIJw0sXScL2ULRPoLOn8zEuP4A/fdBP2jJVjv5cPcjeqMO8qaRsee1etKG2gjDFUrPV77MyGBZNEesYTGn603U51JG05wo6a9Vn1mozPCzrgbxD1ti+Xhw+ElXeZDN82ZN/5XgN+ZS2GHyZ0V1peSuYYKZpwfdGate1mSzpF00DJKnRsKzBaMnE+PO8dSZdOSQ34OSdtPY4TM3UUzYLURAHgNU/fjW/++i0bq7R1fJQsQ9rmqE3yVnTKJNBNf2m5hfGKFQWHVrcafnef8/6JCr74iy/DvvFyahutKsgDP1EhSScM+CExuTbB8OXfxyQdcT6qjk9zY5NJzaYT9+HTe09eV4RnHxjHa56+O/V7leGTJp5sOZIFuo/ofpXvIUzmroXZVQcFZSrXeMVOSToAMD1SRNEswDJYLGlbtozMweyu1vC3D/xAuASoaReVWmexz4pyk2xY0sli+Gu0XVC1xLYfdLQyvvrobjzv8GTmNjWop3z4yqD2/GyZ4nUcP8AXH7mMFxyZijk4GGMp+2jn14q7dJpuEAb8kOGHksbKFjJ80rAvLLVEr/kOQ8VJw5+s2gmXTv9NtuiYlCOZrCYC/mwdtZKZORpR/XsgPZkKiOSRZFKTuloSKutIOp0Q1/B7Z/hZAT+Zh/jgV09KAgeIgD5ZLUrTA4349EMpa2ZVjGmcrNpgjMWK2xrE8DMGqRPDtzTDH36Qfr9/oozRoomZlTYsg2UycTVh1GvAJ9km63XLawR8lT2u1WnxD990E37o2IHMbfTQUNsqEGqbkLSlgPbAuSWcnm+ketz3gqKUh8JB7mGlJ33+NPlqK6ZdEej7Wml5GC9bqeU/gaps942XsdLu3Ye/Fih4n11ogoW9Z6aqtiAGno9Tc3Uc2lGNPVhVhq9+VkQ4VPdJ001LOpxzNNyELXOdpG0nxDR8V7jPuiEc42VxnKfvHYv9vmJFrSboXH/nMw/jr+86LX83u+rEViKU7KUH82w4ppHugxEl4LeI4dvRXAGCdulsI5DuVy2auCbsxT1aSjeron0AcXN14zBRUQjb02bJGJZRkKwjGQxGFR99L+PxVFBQT7ZVAJKSTl7dMsXr/HPY4+SWp/YR8CkwuHFbZskyMFGxBqLhqw9ocS3E2xUTlsMk/NSIHXPp5BHw6b2emW9gPGx/PDkStTo+NVeXrYYJKmGpZgT8WIOwDElHtKmOr0ir60g6nRDT8J0AZcvoatX31D2j+IsfP5aSicqJPvktVySn1Z72s6vxOhQK+LSKmVttx96HaphoJDR89eGo++FvI8hhELaJaybD1qwdtGC6YXrV7wmvuHEnjl0zkbktKkbKZvgrbXfDg5KJ4SflHCBuy8yrUpDO8RtPzOHZB8ZjdrxekVlpKxN3Janh19tbqOHb0ec0HnayrCrBgbActtmmMZN5MkEKtOcWm7IwixKnF5daOLfQxCGljQUQlySzkrYxhu+kAz79TmX4T99Xww27RnAkrPTtFvQgb3k+Wp7flQcfEHLgK27clapFqSQkHZLX1NGas4mATqsFWsWIFUB0j6gMvxmubJI9/gGgHZopupUp80JfVxFjbJIx9q+MscfD/6ciE2Ps2YyxOxhjDzLGvs0Y++F+jjkMoOrIatGUdsEshw4Q3TC9yjmE9//Ic/D9z9mfuY0u+DTDVySdDQ5KJhafbKugbgPynXgFiG6DVEq/UZgFhgJTmqe5kYa8s1bCuYUm3ve5RzFXd6RzZ7NRVgqPxhRL7Gqi0na5KZrw0ZjJPCUdIgKuzzEZJiFJR//22aWUJRPozPCzNHz6eUGRdNRpV4Qbd9fwuf/80tiAlm5QUiqoW2Eivh8kJ2E1wu/i3EITQcDBOU8x/LEEw09uHylF/YrILEAP+0ZC0um2IV6e6PeI7wTwBc759QC+EP47iQaAN3POnwbgNQB+nzE23udxBwpiAlXbUAL+5jD8tdCpuZqqD7c9f0PskB5gWQ8qlRXnNdNWXaW8ug/9HhCMzjbFyMQg4Gi5gWSHu0aLeOjCMv7oi8fxhufux1tffG1fx+oWqktlLGSJajMzAjF8mjrWqy1zLahBlxg+Ta+690lRcXpNQtJRGX5M0jGJ4adtmapPnYJcv8EZiK7zVqjhd5OwXQtl24w9sOi+dvwAl1ZaaDg+Wm4QW+VSt1tqkTybaD0yUjRlHULE8LM1/K22ZAL9B/zXA/hw+POHAXxvcgfO+WOc88fDn88DuAxgus/j9ozjl1dkz5tuwDnHx+46nTndhhI9laIpb5BaJ4Zv98fw1wLdRFk+fEAEfKHh935jkBMnWXQFiKZX9IAzcmb41+6o9rzUzwKNOaSAScHhWQfGMVa28EdvugnvfcOzYknJzURSwwfiXSMJy00XtZKFWtmE4weybUc+SVul22UlLul887QI+Mme8rGCKbWXjh23Zar9bdSkbUsy/P4/5xjDd3Ng+JYRS9qqP5+Zb0rLZVzDF5/XUtMVw90dHztGszV8cifRw16NJe4GV979ot8j7uKcXwCA8P8719qZMXYzABvAiT6P2zN+4E/vwAe/+kTX+z9ycQXv/PvvZA5KoGX4SLELhl8khp+/dLCuhk8unQ1p+CIoZQV8IHrA5ZW0Jevoq4/uykXXpPmnUYGOeP0fed5B3Pcbt+B7nrW372P0AjXgq51KkwGf2hPT508tiPPQ8ClRDEQMn2bXnl1oYjRhyQQiC2XZMmIauHTphKxVLSpazGD4/bJxcf5R4MyH4cclHbWR3Zn5hgz4qpuIcnWLDTfzgRDT8BNJ26Y7eIa/7mOXMfZ5AOkqCOBXezkQY2wPgI8AeAvnPOiwz9sAvA0ADh482MvLrwnPFyXtl1e6698NRE/7xy+nhyQ0wi+0YpvYNVpCrWR2HF24uQw/W8OXBSDtjQd8urA7nXetbOHcYjO3pO3uWgnveu2N+L6b9uXyekWrIJkgEEkqW50kI5SUpK3sVFoycXGpFdtvORykQ58/BZU8ggMlipeaLibDfvmFAsNExcLsqoNrE5ZMQDxozAJL9VxKBjE1cMaStonPvx9Ihu8FaLpBx5GG3aIStmEmqAz/9HxDvme1ANA0ChgtmVhsOphZjapsCSOlaJxiVHgV+vBVSccPtrw1MtBFwOecv6rTNsbYJcbYHs75hTCgX+6wXw3APwP4Nc75nWsc6wMAPgAAx44dW7tRdQ9ohexjuQdJhxofHb+0mtq2qrh0CgWGf/y5F2W6WYBIXulllm23KHVg+IwxubTcaNL2qXtqOLqnhmfuH8vcXiuZYCy/mbaMMfzMS4/k8lqACFRtZch7HhpyP8hk+Hac4XPOhaQTunQAYC5se5AXGxwJA77aa2cybK+QtGQC0fDzkUQLjqRMQZ9z0SzEJB3qGJkvwxdJ29193lMV24Drc7hh8CWGX2CirxDds8lV7njFwlLDTbVdAKLV9WLDgRdwYau2qWAswfC3YdL2VgBvCX9+C4BPJXdgjNkA/gHAX3HOP9Hn8TYESpasJCxwa4G+nOMz6YBPT2pa7h6eHumo4b/wyBT+6/ccxc2Hsita+0EnDR8QkoxI2m7swtpVK+EzP//d2D9Rydw+VrZyS9huBkjDb+aYNOwHFPAsg8mfk5JO0/XhBRxjZUtKhLN1UcmZl3RGidvJajzgA0hZMgnVopli+JS0pUBPn/OesRKWmq5sqpbl0tkoqNCqLW2Z/b1mKcG8KWl7aKqKs/NNzIadMpMFYuNl0SKZehBlBXxi/+WwEZxRYLGkbXubJm1/F8AtjLHHAdwS/huMsWOMsQ+G+/wQgJcA+HHG2H3hf8/u87g9gYJ3L0lbulBPzzdSidu648E2C10tyYqmgZ940bW5VaSqWGsoiJh65W648Go91MpWbpbMzUDREho+efHzYJj9wDQKsI0Cxsq2lE1GQwsfdVGkxmkiaSsIxOxKG7aRn1+bArc6IIUaiiUtmQTB8NOzHmyzIO8Tukd2j5VEx0yl+AjIR9IBxLXecoNUu4aNoJKogCWG/5TdozizIDT88YqVus/HK6JFcpbGTyv6mZUo4MvB7NtBw18LnPM5AK/M+P09AH4q/PmjAD7az3H6BX3Qy83uA35Lug+AkzN12TcHiDplDhqdNHxAXHjLoa1vMy6s63eOyAElwwiRtA2kNDdohi/OoYAxpQ9RtWgi4GTfM6XkWCubkuHP1du5fn8UuCcVSYecOklLJuHAZCWmYxPKliGTtnSP7Q07XC42HYxVLOltzyvgl6woGZ+HDx+ItPuG44ExcW1/9sGLuLDUzDQtjIX5q9nVNmolMzF8KB7w1ZkWSQ1/q6q8VWz9EQeARh+SDiASt2rAbyQGOg8KnVw6gBhdeCZskrUZDP9tLzmMn/7uw+vvOCDYpiGscz002dpslG0jVmyk9k+v2KYkJLVS5NJpufkGBnKNqQyfglrSkkn4sx99LrIWGOWwxz8Q3WO7w+Epiw0X10yJqt6Ropk5SnMjIIafhy1TNjVTGH7VNnFwqgrOgfvPLuFwxmciNfzVdip3lwz4dN2V7ULaljmMSdsrAbRk6yVpqxaUnLgc1/HrTny+56CwloY/UjJlF8TNYPiie2XuL5sbimHhVeTSGXy+oWwZMWcJJULrbR8YhcLwLVRtAwUmKo/zDAzVogmjwGKtQH74uw7g4GQlpuur6BRYS1YhreGHbZmp2vbJuToOTlZyk6SKVgENx4Pr8xwknaTTyEPFNnAgHLwzs9LGzdemc29Sw19xUiuAtKQj/l2xzCui8GpboCV1xkD2JlkPdBEcmCzj8WTAb/syYTtIFNfR8GXAHwCTGDSSPvyNFJ/ljTe/4BDe8NyoTQbNIqBq20jDN8EYkyw/z8BwZHoET9k1GgvAu2olfO8G7LAlRZduSUlHMHyqtj0935C1KnmgaBrS9tnvQ7ySZPiOWLmrg3eypKzxigU/4Dg1V09tTyVtaYiRndbwh9KWeSVA/aBXWq5MUq2FluvDMhiesquG4xkMfxD6WxLldRg+TZ/rdgD2lYSiaWT68AeJZBsHkldIalQZPiCSulkTzfrB//2yI/jZnOyvZcXH3nTTkk4QiHGVr+qj82kSJasgC7v6LrySLQ9CDb8tGP6uWgmWweD6PLOjJ63SLq+0U9s7afhlq6AZ/lZB/aC71fEpKXT9rhE8MVuH60crg0bbz8Vm1i8oadtJwycM4sIaNIRLJ7JlDoOGnwQFh4jhi0BGCdvaJjB8xlhssEw/EBp+vPCKmtEtNBxcXG7B8QIczJXhF7AUykXdTLtaC2mGL6Rao8DkxLCspK2ah0luryYCPslhKZfONm2tsC0QZ/jdBfxWOCXpuukReAGXc2kBkWQbBg1/zaStUhdwNQZ82yjA8XyZixkGl04SMuA7xPA9lKyClJ/kEJohleSyJJ2RkkjQLjZcec9QC/E8UDSN3Bh+MuA3HF+uukjWyVIDxpX2E8mkrWUUULIKsqqfVpblhKSz0fqYfjGcV1LOULPj3SZuqaXu9btEI6/jSouFhuMNhUunU6UtEJ9OtBkunWGHZPiuLwtfhg1qzyMgapxG2AwNP0+UraiffNPxUWDi4TRetbDUdHF6noai58fwS1Yht/48yWrhetuT3UGp4DBL0hlXEu9ZK4CRoiVzGBXJ8NNJ20Hcl8N5JeWMuKTTXcAXvawLsnOjquPXneFI2q7n0iEMa8DYTESVtl7XgzK2GtWkpBO2RiZQx9JhzcGUFFsm1RIwxoSLpeHg9HwDZoFhz1h+jQPV5Hu/eZlkj5uG48v6moOTFPAzfPgKw88a0xgbFCMZfoYtc7sVXm0XqMODyQmxHlqeYPjVool942UZ8F1fOH2GQdKJNPz0ha9q+IMYtDBoEHtaaXlDkbDNQsU2wFjcpaPaJaWGP6QVzWoQUwuhxisWFkJJZ99EOdcqc/Xh3e+DnKqfIx++J6tvqYnf/tCiqUK11ma5eIhsMRZdh2Wl8Mrzg9zttt3iqogEtNwEsiWd+bqDd/39d+LzOR1fJoWO7ByR1syGMu1q0Hja3jG8+LoduHH3aGqbZvjiPS823aHU74GwyZ0dDcxIMXxlkPwwomQaMR8+2STHK3Yo6TQkU84LKrnJ43st2waajmhvoWr4u8dK+NmXHcmsHyiahtT/syUd8b2pM3cpacs5l1PMLC3pbA5ari9HuS1nJG2//Nhl/M1dp/Hg+aXob7xALvkO76jiybkGOOexaVeDxvRoER/9qedlJpZGrnaXTviel5ruUDp0CFVl6lVHDX9IV2iUiOScx3rbjJdFr5kn5/L14ANxVp/H90pjDh0/gBfwrge1jIXFcVmrR7r3VCcfFWC1vSDXOcW9YvA0dQvQdH2MFA20XTNTwz8zL4YW19UJ9o6Pcmgx2z9Rxmrbw1LTjQaYDwHDXwua4YubbbHhdJw3PAyoFg3ZtGu55UndHlBcOkP6/ZUsA5xDJsfLCUkHwLZg+A3Xj1buXRK5sbLV8XuhgK+eHw3gaTq+tHhrDX+TQMOEaTB0EmfDnjPqfFHRflV8IZSxPzPfhB92NqwOQdJ2LYwWFVvmkDLEzQRN0FpqepsyfCYvjJQsrIQdM5MMn+SdYQ34FODbbhjwbQr4USLzYI6WTGBzGL4YVRiNLe0Ge8fLHav2iWzFGX6YIHZ92TpaB/xNAl2MnGd3zDy7EDJ8tTe5E13ABybL4X4NeRNu1SzUjaJkiUlFXsD7LlDZjqCH3FLTQdmqrbP34FArmXjkwjLueXIBXsBjGn7kwx/O748YbNP10XJ92XVTtS3mLenk6dIBRI+bhuPJhGq3Zozf/YFngHcY0VRVNHyC/KwcX/ag0rbMTQJ56mvlTgxfBHy1fWnL9eXFRQz/7EJTPhSGobXCWmCMSaZxNTN81+dD69IBgLe//DpwAD/053cAwPby4SuDzBuOyvCj95C3pKMy/DwCZjlk+DSIplu79c7REnbVsu2mo5mSTuT5l5KOdulsDkhfHC1ZKZeOH3CcXxQBX50+1HIDeQHTBKIzC41o2tUQBxECPZSGNWBsJvLWejcLzzs8hc//55fiB58jmqqpU6eG3aVTVlgryaZAFPB3jNi557roey1Z+QyFoaRtpOH3f75ZSVs5bMX1o6StlnQ2B8Q+zALD8ctxhn9puQUv1NRoEIIfCOtUSQkaByYqOLvQxA27hAVy2JO2QHThXZWVtsp7HuaAD4hCnve+4Vn4tf/raKyohxj+sH5/9Lm2PF+uooFIw8+b3QPRyi0v51U5DPhSw8+ByElJJ6bhi/NuOD7oMaW7ZW4SWqFlrGQZKYZPcg4QjTjL6qG+f6KMJ2br8qGwHQL+/9/e2QbJVWZ1/Hf6dbp7ksxLSAiZCQETAwFZwBGCLJgFogHXzX5Qiy22iLrIB7BkV9ddqHxSv6yF7+XuagQlWMhSIi6prRU3G9eXslwgKxYgLyaCkkAgk8kLzGvP9Bw/3OfpuTPTk+lO90z3vX1+VVPd9/btvueZp/t/zz3Pec7T6rVYlpJZsd4WF3xPWOwBuvNpbtzUy9X9XU2y6NyUBb9YcjNtZ9IyYeEVtOrB92uj+jTvKn428nftf3e+GifMjuGn3aQg8/CXCD9o67N0VLV8O+gzdGBm0NYLftgz7O/J86+HTzI80Zg6HstBZzZFKtG46ohRIvxjikJfVSKVTPDEPduabcaChEsThNMyV+XSrMimKk4IrBcfw+9oUEg1n0kFHn6NaZnnwq9zEHYYwzH87DmWJl1q2kfwXQy/NK3luh8w4+H3defK8fmxCoLf151jbLLEsVOj5NLJlizGNZfOjnTLhgOWmtkhnfb8Hyw1PmRxZmwS1RkRTiUT/MMXbq5YZ6ZeyjH8BtUX8hU/ZwZtGxDDL6dlznxWOIafm3I1sKI2aCsiPSJyQEQOu8fucxy7UkTeFZE/qeectTI9reVSxz4DIlxP59jpUdasyNJbyJQ7vVJJXZ+p88b7H0UinAPQk09HxtZGk01HJ4YfVbzXesbVpw/fSV3UlVuSVcb8xbtRmVc+DOVXh8s34Lvii6dVytIZLc4M2kYxLfNB4KCqbgYOuu2F+G3gn+s8X81MuH+uD+nA7IqZx06P0dedc7d2s0M6uVkhnSAX/8jgcMtPuvLc/4lN7L17oNlmNIVG52sb8/GC5sVyOUJnSxHDBzj50QT5TLIh4c9ySCech+/CO+MRz9LZBWx3z/cB/wR8ee5BIvKjwFrgOWBZFWgsJN5+UsuHcwT/6v4uRotTvHdmctZ7wqEAvwJOcWq65Sddedas7GDNArnCcSf8Y2rU7b8xG//78AuWL8eF1d+5NSpM50V5cHiiYb/rnkKGq/pWcVXfqvK+TDJBQuCpF49y2l0gm3H3Xe9/ba2qHgdwj2vmHiAiCeD3gN9Y7MNE5F4ROSQihwYHB+s0LcB77bn0jIfvC6j5HPy+7lxQxOocHv6KjnQ5v7gzIh5+OxO+XTYPf2lohofvz9moMJ0X+ZPDxYbduWdSCfb/yse5cdPq8j4RYUNPnuGJKe74kXX89T3XV6y0udQseokRke8CF1Z4aU+V57gP+LaqHl1sooSq7gX2AgwMDCwwcbk2yhk3mWR5Iosvr+Bz8Pu685wenSyP1PsyyXO/VP3dec6Mno2Mh9/OpBJCQmBao5ul0+qkkwnSSeH0iFtycDk8/FRj8/DLIZ3hiSUX4AO/9hMINHR9gFpZVLlU9baFXhORD0RknaoeF5F1wIkKh90A3CQi9wGdQEZEhlX1XPH+hjFWDOJl+dCgrS+vcPRUkJLZ153jrcHhmbTMqcrroPZ153jl3bORieG3MyJC1tVrt0HbpaMjneRUhUHbpTwfNO7ikgsN2l68BBPFwjRjotVc6rVgP7DbPd8NPDv3AFW9S1U3qOpG4IvA48sl9hCK4WeS5ZmLXvB9SmZ/T55CNsXYZInStDJenB/Dh5nVb1phtStjcXwc39Iyl46OdLIck16OC2u23KeN9fBL09qQlMxWp95fwleAHSJyGNjhthGRARF5pF7jzoeJqRIvvH2K42cDMQ/n1Hekg1tQP2jrBf+iro6y1z42WWJ8qvLkKr+SfbumOkaN8u2/xfCXjFw6WR60XY76UulkgssuXFEucVIvYZtbYVGjpaYu5VLVIeDWCvsPAfdU2P8Y8Fg951yMj8an+Pk/+3d+a9cV3H3DxnI83i83tqIjXU7LPHZ6lLUrs2RTyVkLSi8Uw/cefhQKpxmNr7tizCeXTuJKUS3bhfW5z9/csM/KVZgcFWdid6/bnc8gAkPDgdcxHgrpQFCB0E+8CnLwndeemRH8ShOvIBi0BfPwo8JMZUUT/KUiXOIgihfW8ESrdhibi53gJxNCVy7N0MgEMDsPHyh7+BNTJd54/0M2ugJP3msfmQjqgmSSiXnlE/p78mxdt5Ir16/CaH0aHe815tMRoaqklQjflbSDhx/LFvZ2Zsu5waPF2YK/Mpfiw/EpDrz2AadHJ/mZj60DZkoJjxSnGJ8sVRzo60gn+fYDNy1HE4wGkGlwCp8xHy+YIq1bxvlcZFMJREC1PWL40euhKugpZDg5J6TjpzavyAYe/pMvvMP6rhw3bb4AmCmaNFoW/Ph3ftzJpoLZjelk6xe6iyr+Ypp3Y2RRQ0TKYR3L0okoqzszZQ9/rFgiITOV6VZ0pHjn1Cj/dmSIO3+svxy28bNnhyfcYg5tcLWPO9lUsjxYbywNuQbnxTcDP3BrHn5E6SmEBN+VRvY/+pW5NOOT0yQEfm6gv/weH78bnZgKJutY/ZXIk00lIi1EUSDb4FIHzcCP35mHH1F6CllOjxbLte/DqVe+ns4tl63lwlUzhcXKWTrFEmOT0w1bYMFoHlm3ypmxdJQ9/Aj/n73gt4OHH8tL2urODKpBFb/xYmnWyjO+vMJnruuf9R6/Wn2QllkiZ7MzI88v3riRnVdUKgNlNAr/24rynZS3vR3SrWPZwp5CsNLO0HBx1tJrADuvvJCxyRLbt8wu7JlOJsikEuUsHf8ZRnS5dkM3bGi2FfEmXh5+LOVwFrFsYW8hqHo3NDLBaHG24F/UleP+T2yq+L5CJhny8KP7BTaM5aLRxcyagV9sPG8Tr6KJX0vTe/jVxnEL2RSjbuKVxX4NY3E6zMOPFLEUfB+OOTVSrCnFspBJuZDOtAm+YVRBnEI65uFHlHI9nZEiY8XqwzPcJ12SAAAID0lEQVSFbJKRiRLjxcozbQ3DmI13pqKc1dYRmjwWd2KpasmE0J3PMDQ8MW/Q9lz4ZQ7HpyyGbxjV4B2jKIvlD63p5OLefFNXolouYhu08pOvxidLVXsf+UyS986MMVlSC+kYRhXEYdD2s9dv4LPXt0c6V2wFv7eQCQZti6WqvY9CNsXQMi7IbBhRJxeDmbbtVHojtvcwvZ0ZhkZcSKeGQdszo8HiKBbDN4zF8b8tc5CiQWxVrbeQ5fjZcaa1eu8jPNMuyh6LYSwXcSie1k7EVvB7Cpl5tfAXI1xLwwTfMBZnQ0+eL+3cwk9uXdtsU4wqqEvwRaRHRA6IyGH32L3AcRtE5Dsi8rqIvCYiG+s5bzX4yVdQvfcRrpZnt6iGsTgiwn3bN9HbmW22KUYV1OvhPwgcVNXNwEG3XYnHgYdV9XLgOuBEneddFF9eAaoX786sefiGYcSXegV/F7DPPd8HfHruASKyFUip6gEAVR1W1dE6z7so4eJn1Yp3eE3LcIVNwzCMOFCvqq1V1eMA7nFNhWN+GDgjIs+IyEsi8rCIVFRgEblXRA6JyKHBwcG6DDufkE541fqsLYBiGEbMWDQPX0S+C1QqKr6nhnPcBFwDvAM8BfwC8OjcA1V1L7AXYGBgQKv8/Ir0hjz86gdtwx6+Cb5hGPFiUcFX1dsWek1EPhCRdap6XETWUTk2fwx4SVXfcu/5JrCNCoLfSLpcPR3VmeJIi2FpmYZhxJl6Qzr7gd3u+W7g2QrHvAh0i8gFbvsW4LU6z7soyYTQkw+8/PPJw7csHcMw4ka9gv8VYIeIHAZ2uG1EZEBEHgFQ1RLwReCgiLwCCPDndZ63KvzAbfUzbcNZOjZoaxhGvKirlo6qDgG3Vth/CLgntH0AuKqec50PZcGvNksnHNKxQVvDMGJGrN3Y1W4ySNWC747LpBIkEu1TUMkwjPYgttUyYcbDz6aqu64lEkI+kyTdBnWxDcNoP2It+LdevobxyVJN3nohm8Kce8Mw4kisBX/7ljVs31JpLtjCFCz/3jCMmBJrwT8f8pkU01rXnC/DMIyWxAR/Dp3ZFMXSdLPNMAzDaDgm+HP45ZsvpTRtgm8YRvwwwZ/DDlvIwTCMmGL5h4ZhGG2CCb5hGEabYIJvGIbRJpjgG4ZhtAkm+IZhGG2CCb5hGEabYIJvGIbRJpjgG4ZhtAmiLVo3RkQGgf+r4yNWAycbZE6zsba0JtaW1iRObYHa23Oxql5Q6YWWFfx6EZFDqjrQbDsagbWlNbG2tCZxags0tj0W0jEMw2gTTPANwzDahDgL/t5mG9BArC2tibWlNYlTW6CB7YltDN8wDMOYTZw9fMMwDCOECb5hGEabEDvBF5GdIvKmiBwRkQebbU8tiEi/iHxPRF4Xkf8SkQfc/h4ROSAih91jd7NtrRYRSYrISyLyLbd9iYg879rylIhkmm1jtYhIl4g8LSJvuD66Iap9IyJfcN+xV0XkSRHpiErfiMhfiMgJEXk1tK9iP0jAHzs9eFlErm2e5fNZoC0Pu+/YyyLydyLSFXrtIdeWN0Xkp2o9X6wEX0SSwFeB24GtwGdEZGtzraqJKeDXVfVyYBtwv7P/QeCgqm4GDrrtqPAA8Hpo+3eAP3BtOQ18rilWnR9/BDynqpcBHyNoV+T6RkTWA78KDKjqlUASuJPo9M1jwM45+xbqh9uBze7vXuDry2RjtTzG/LYcAK5U1auA/wYeAnBacCdwhXvP15zmVU2sBB+4Djiiqm+pahH4BrCryTZVjaoeV9X/cM8/IhCU9QRt2OcO2wd8ujkW1oaI9AE/DTzitgW4BXjaHRKltqwEbgYeBVDVoqqeIaJ9Q7C8aU5EUkAeOE5E+kZV/wU4NWf3Qv2wC3hcA74PdInIuuWxdHEqtUVVv6OqU27z+0Cfe74L+IaqTqjq28ARAs2rmrgJ/nrgaGj7mNsXOURkI3AN8DywVlWPQ3BRANY0z7Ka+EPgS4BfFb4XOBP6Mkepfy4FBoG/dCGqR0SkQAT7RlXfBX4XeIdA6M8CPyC6fQML90PUNeGXgL93z+tuS9wEXyrsi1zeqYh0An8LfF5VP2y2PeeDiHwSOKGqPwjvrnBoVPonBVwLfF1VrwFGiED4phIuvr0LuAS4CCgQhD7mEpW+OReR/c6JyB6CMO8TfleFw2pqS9wE/xjQH9ruA95rki3nhYikCcT+CVV9xu3+wN+GuscTzbKvBm4EPiUi/0sQWruFwOPvcmEEiFb/HAOOqerzbvtpggtAFPvmNuBtVR1U1UngGeDHiW7fwML9EElNEJHdwCeBu3RmslTdbYmb4L8IbHbZBhmCAY79TbapalyM+1HgdVX9/dBL+4Hd7vlu4Nnltq1WVPUhVe1T1Y0E/fCPqnoX8D3gZ91hkWgLgKq+DxwVkS1u163Aa0SwbwhCOdtEJO++c74tkewbx0L9sB+422XrbAPO+tBPqyIiO4EvA59S1dHQS/uBO0UkKyKXEAxEv1DTh6tqrP6AOwhGtv8H2NNse2q0/eMEt2gvA//p/u4giH0fBA67x55m21pju7YD33LPL3Vf0iPA3wDZZttXQzuuBg65/vkm0B3VvgF+E3gDeBX4KyAblb4BniQYe5gk8Ho/t1A/EIRBvur04BWCzKSmt2GRthwhiNV7DfjT0PF7XFveBG6v9XxWWsEwDKNNiFtIxzAMw1gAE3zDMIw2wQTfMAyjTTDBNwzDaBNM8A3DMNoEE3zDMIw2wQTfMAyjTfh/LtOQWFErTCoAAAAASUVORK5CYII=\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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j323H7mEPLCbqat1bNl0B5Rq+LMmUjAeUn2dCXefC3hVs6oCfyuYQTRnbKFRiW1Bpzsp2yS3j5EoCNotyS9vnsrGBGlOTUCKDXF6g32OD3WLGrkEPTnRxh6oM+CYqzvCFEFrTlWTYp3yX58Ic8I3Y1AFfdtnqM/xabOt3IZsXmF7tjhNqaiWOLQGn4tfvsmKVyzKZGsimK1mssG+0uyt1pKQz4LEXZfjLsTRi6VxRwB/yOgAA85HuKazoJjZ1wJdNV40E/Am1dPPccnfIOpPLCWxRT/iAy6ZlbwxTCdl0NaCe97uHvZgOJRFPd5dliEQG/CGfHZFkVltjm5Q1+LqA77SZ4bVbsNCBgP/k+RV886kL677fRtjcAV/no1Mv29Vu3HNL3bFwO7USx9Y+JwAg4LRCCGODKYaR6LvLAWgVLkvR7pQDZQ3+sNeBXF4grj4+r6vB1zPos1cdh9guPv/zM/jzf3uuq4ewbO6Arzll1q/hD3sdsFlM2snWCYQQyObyiKayWIlnsKVPOeH73MpiM8s6TDUKko6S6Mg73OUuayiU6DN8oKDjFwoWnEXbD3sdmA+vf4a/FE0hns51VRVfKZu6LFOe4P0NZPgmE2Ei6MK5DlbqvPMLh/HI6SVs71fkpa1BNcN3Fbx+dsC4l4BhFqNpEBU6x4OeDRLwVX0+nMxgxO/AbCgJn8MCt704jA357Hjy/Mq6H6e8Qzo+E67Yy9NpNnWGvxhVfHS89saue9uCro5KOs9PhzEecMLnsGJLnxOXb1HGMwacSobPboFMNRajKQRdNs1wTzYeLnVrwE+XZvjK+T0TSmLU7yzbfshrx3w4ZdhPk8+LtlXYyb9fN3v5bPIMP4Wg29bwMJOJfhceOb3UkUEomVwei9EU3nZoAn98656i1/pc3enmyXQXS9FU0V1tQdLpzsoWmeEPyww/oUg6c+Ekhv2Osu2HvA6ksnmEk1n4ncU9NR/5/gk8fX4VX/tP17f0GLO5vPa96+aKp02d4cvmk0bZFnQhns5hoQOeOovRFIQAhn3lJ3rApZzcK5zhM1VQfHQK573HboHVTFjuUuO90gw/rM/wDb4HcrsFg4Xbk3MRnFqItvwYV+IZCAEQoau9fDZ1wF+MphvS7yXbVO38fAdknVm1g3DEX36h8jmsMBEQ4gy/J8jm8njtJx/Gg8fnWvq5imFg4bwnImVec5dn+AUNP4t0VrnTHamQ4QPAnMHC7Woig1AiU9U+pZRkJlfTm0cuhF+2JYCZULJrGyA3TcD/7M9O4/kLxQObS43T6mVbf+dKM+VJLE9qPSYTwe+0cobfI4STWTx/IYzHziy39HMXo6my7vKg297Vi7Z2i0m7gw0nMpiPJCEEMGoU8NUM36g0MxRX+lQaGVN652cfxX/912erbiMXbF9x0QCA7s3yN0XAX4ik8FffO46vHp7UnhNCYD6cwpDBLWEttvS5YCJ0pPxKtowbSTqAUqnDZZm9gcxsL6y2zp01lc0hksyWJTr9blvFRdtkJodUNmf42nqQTOfgtJnhsJphM5sQSWZ1d7pGGb4a8Ctk+EBjs59PzUdx/9PTmK9i1yAt02/YrQb8Ll243RQB/4lzSoakv+KHk1mksnnt5GgEm8WEUb+zIyZqc+EkLCaqeGeiGKh1Z6bGNIbUrqdbGPALpcjF532f21ZxsM9dX3oCf3bfcy07hkZJZHJwqgOJfE4LwsmMZo5mVKXjsVvgspnL7BXyeaF9N+qdDJfMKBfIbF4UJYylyO7lvSNeDHrtON6l3kQtCfhE9GoieoGIThHR3Qav/wkRHSOiZ4noQSLa1or91svhs0pNrl7Tk1frtWT4gCLrrDXDX4qm8P///MyaWtnnwikMee0wmYyrgwJOK1fp9AjtCPiFLtv6M/xj0+GOmqslMnkt4HsdVkSSWe1O1yjDJyKlNLMk4EfTWcgm2HoDvszcLSbClx8/X7GkcymagsVE8Dms2D/q69pKnaYDPhGZAfw9gNsA7AdwJxHtL9nsKQAHhRCXAfgGgI82u99GOHJWzfB1t2TyZFhLhg+oAb9BDV8Iga8fmcQtf/dTfOg7x/DDY40vxlUqRZMojpks6fQCUtKZj6SQzramdlwGsFI7kaDbhoi6GKonlVUmqs2EOjf0J5HOaiNHfQ4Lwgklw3fZzPA5jCvLh7yOMsdMfX9KvQFfevK88aotmA4l8eMT84bbSZt1k0mZunVyPtKyf7NW0ooM/xCAU0KI00KINICvALhDv4EQ4idCCBkdHwWwpQX7rYt4Oovnp8OwmgnzkZTmcyHlnbUG/C19LizH0g1l6X/z/Rfw/m88q+nvsVTjuuhcOKnVIxsR4IDfM8hzS4jW2f1qGb67dNHWuIdDauUr8UyRL/16ksgoGj4gM/wMZkNJjPgdFftgBn32MgM1/fei3u+IlGrecmgrRnwO/PNj5w23W4qlNJls/5gPmZzAS20o/2yWVgT8cQB6cWtKfa4S7wLw70YvENFdRHSEiI4sLCy04NCAp8+vIpcXuOGiAWTzAsvqCa1Vu6xR0hkLKO9rZNDC4bPLuHIigK/cdR0A1HWx+IP/+wS+8cSU9ng2nNQ8v40IuKyIprI84q0HSOomPbVq4bbUR0dSyU9HbwM+2yGP+US6VMPPYiaUMKzQkSh+OsXHq5/3XCnDf9Nnfln0fZMXjRGfA3cemsDPXlzQBqfrWYymtbum/aPKpK1uXLhtRcA3usQaFrkS0W8BOAjgY0avCyHuEUIcFEIcHBwcbMGhKfo9EXDbgVEAhUxpPpyC22aGp0FbBcmIT1ksmm0g4K/G0xjzOzXvj3iNjCmTy+Pfn5/Fd5+dVrfPIpLM1pB0VAM1zvI3PPrRfs3o+Pm8wN//5BT+7L7n8K9PXIDdYio77ysFfL2UM9PCtYRGSGTymqTjtesyfF/5gq1kyGdHLJ1DTFd+WZThJ8rXK9LZPI6cW8Gjp5e056QE1u+x4XVXjgGAoayjL/GW/vydukBWoxUBfwrAVt3jLQCmSzciolsAfADA7UKIdevwOHJuGXtHfNg1pMzrlKVa85HkmrN7YG0ZfiiRgd9lhdVsgs1sqhnw5yNKV+1RNVOQdyXVJB2/aq/AlTobH/350UzAP70YxcceeAHffXYa6Vweb7hqS5kUUslPR39+T3dobGAyk4PLVsjwV+MZzEVShs2HEq00UyfryJJMi4kMLcRl1q//Wy9EUvA7rbBbzNjW78b2fhd++mK5+rAUTWuSjt1ihtNq7srvYCu8dA4D2E1EOwBcAPBWAG/Tb0BEVwL4RwCvFkIYr3q0gWwujyfPreCNV28pG302r1a7rBWpw9eb9QghsBrPaAZnLru5pqQzq2ZX85EUFiKpqpUJEi3D51r8DY/UzO0WEy40MWFNNuJ96m1X4cY9xnfOWoZfYhdyYTUBj92CaCqrnY/rjV7S8TqsSKmLoSMGJZmSQrdtUnOulB3o431Owztgo4C/GE1hUBcnbrp4CF89PIlkJqfddcTTWcTTuSKZrM/VnQ2QTWf4QogsgPcCeADAcQBfE0IcJaIPEdHt6mYfA+AB8HUiepqI7m92v/VwYjaCWDqHg9uD2j/aXIsyfIfVjKDbhpk6b9vi6RyyeaF1C7qs5poZvj67Oj4T1jVdVb5QaQZqXdo1ydSP1PB3DnqayvBldUqpkZiegMsGImC5JEjNrCYwEXSh323rWIavX7TVV+UY+ehIhn0GGX48A6fVjCGvvXrADyW14g6lK7kQyH9lzyASmRyOnC3YL8uFcH33sr9Liyda4pYphPgegO+VPPdB3c+3tGI/jXJYLce8Znsf7BYlQM+p1TnzkeYyfEBp665Xw5cZt1/L8C11ZPiFzz42E4Ysva/UZQsUMrXFLp1exNRPPJ2DxUTYFnQ1VfEhzz2ZbBhhNhECTmuZn85MKIktfS4QrZ+G/8S5FSxEUnj1gREASsB36DJ8SbU7XW22rS4hW01kEHBZ4XdaDWdSS5knnc1jKZbGoFep9LlUtR8HgGt3BmGzmPDQC/NaV63R5LyAszsbIHu60/bkfBR9LqvWjaf4ZCcRTSm3YK0I+PVmXvIf3+9UTgqXrXaGPxtKwmk1Y8zvwLHpMObCKbhqLDQPee0wm6ijddNMa5AdpmMBJ6ZXEw0ZfukJJWpn+ABUA7XSKp0ExgIOjPqdDa1XNcNnf3YaH/7OMQBALi+QzuZ1VTqF36FalY7PaYHNYioqzVyNZ+B3WuF32gyrdPTPye+1vvoGAFw2C67dESzS8eXkPH2pa5/b2pWyak8H/AsrCW38H6BkxnPhVE0/mnoZ8TvqXomXt9Uyy3JazYjXqMOfCSu1xvvH/Dg2E1ZLMivXHgOAxWzCsNe+5jK+f/zpS/jy48a1xsz6klA9ZMYCDsTSOc0HvlFkINNnx0b0u+1Fc22jqSzCySxG/U6MBRzrFvBj6axqAy60SiWnTQlVXlXSsZlN2t2sEUbdtqFEWsvwjQK+PiOfXk0gkc4hmsqWGc39yp5BnJyPat8xo+5lv7M7JZ3eDvhqdiIZ9tkxF05qlTrNZ/jK4k89DSmlt9VuuwXxTG1JZ8TnwP4xH04vRHFuKVZVv5fIjHAtfPXIJL7zbFmRFdMBpHY9HlDuUNd6EQ8nMvA5LNqEq0oE3baixisp4YwFHBjxOxBKZNZkB9Io8XQOqawys1l+t7QMX71oVWu6kgz7iiVXpWjCVrFXJaS7oF5YTWglmYMlceKmi5WF75+pWf5irDzDl55Wa70raxc9G/CFEJheTWA8UJzh69vEh+oIntWQt5T1yCfyah9QJR1nnZLOqN+B/aM+5NXyzHruSsYCa7/9Xo1n1tQBzLQeWZ0ypgb8tV7EV+Np+Kvo95K+EklnWmdQNqbKouuR5cvvxUIkpS1cO3SNV0B1/V6ypc+JqdVCk5TU8PU2y3pCiQw8dgvcNjOmV5Pa3cFgSYa/a9CD8YATP1Hr8ZeiabhtZm1hGVCqdLJ5gViHupMr0bMBfzWeQTydw7huov2Qz4G8KHTANVOlAxROunoWbmWjh5bh26pLOvm8wJwq6Vwy5gOgtNiP1BvwVwuVBvWSU90E1yOLY2ojM3wt4K9xXSaUyNTU7wGlFn8lntHOG32GryU3TZSH1os8/xajaZ2kU7xoW02/l0wEXZheTSKby0MIgVBc6YORf4tSjV3+neQdcqUMn4hw6/5hPPTCAkLxjDoysngbmdh128JtzwZ8efsrb4cBYFj9h3vuQggOq6nh4eWlNJL1hOIZ2C0mLVNx2apX6SzGUsjmBUb9Dmzpc2rHWs9FaizgQDqX12416yWcyCAv1ubxw7QemeH3u22wWUxrlnTqDfhBtw25vCiqRydS7oxl4cNaLzqNIDP8xWhKk3Rk45VXHceo/15XYmufC7m8wEwoiUQmh3Quj4DTpv0tSnX8UCIDnwz4oYS24Fuq4QPAm67egnQuj28/O204OS/QpR3vPRvwp1YMAr4aLI9OhzHkra0B1mKkAUknpN5OSmpV6ci7BrlIu0/N8uvK8OWXs8FsTOq3nOF3Bwm1w9RkIoz5HQ3/e0pWExkt46yGDFqyzHA6lMSQ1w6r2YRhtau1ESuRtRJX7RAWIiktw5eJkslEuPedh/DOG3bU/BxpcXB+Oa4F94Auww+VBONwIgO/01KW4RuNQb1kzIeLh72478kpLEZTZWZ0Aa3jnQP+uiD1Tr2kIwN+NJWta/GzFg6rGX0ua10ZvlwwkrhsZmTVkjMjSgc87B9VAn69i7ZA43XTMuB3m+64WUmkC/XnzSzEh9XMtRaljpmKQZlyLtktZgx4bG0v9xVCIJ7RZfiZ4kVbAHjZrgHDrLuUif5CwC+soVkLwbjET2c1kUbAacN4wIHFaBpTKwn0qVYopRAR3nDVOJ48v4rTi7Eyu2mZ3HXbbIqeDfgXVhNwqgFZMuBRugkB45mwa2HU76xbw9ffVrts0kDNOJsutVE4tCMIq5m0k7gasjJJSgDpbB43fewn+OZTF6q+byVWaDxht83Oo5/0tNaAL4SoW9KRXdqyzHBmNVl0hzzqd675LqNeUtk8ZGHLQqQg6egXROtlxOeA1UyY1AV8f5UMX6/hA8BzU6GqF5bXXzkOEynfl4qSTihHKIMAACAASURBVJfV4vduwF9RSjL1so3FbNL+AUsXYtbKqN9RV8v5qrpgJJGaZCVZZyaUhNVcGGV424ER/OLuV9Z1ofI7rXCplQYA8MJsBGeX4hWHN0iWddlIrQqiXkUu8HUD8XTBNGzMrwz0qDRxqRKJTA6ZnKhv0dZTcMwUQuDCarEFcSOd5WtF726p1/D1GX69mE2K1q9IOmrRhNOm2TMYLtq6CgH/5HykapwY8jnwit1KiWappFO4qHCGvy5cWE1gvK88G5aSSLMlmZIRv6MuU6lQomCcBhQyFn2Gf2I2rA2Lng0pTVZylKHSSFLfXQkRFWWEz0ytAgCevxCq+j69/85m1PGzuTxe/+lf4n1ff7bThwJAtRRQz5NBrx15UW5fXIvVeG1bBUnBIjmFlXgGqWweo0UZvqPti7b6RGNBX6WzhoAPKDq+PsMPuKywmJWCDf2ibSqbQzKTh99p1e5q8sJ4wVbPG69WZjkNlFwY7BYzXDZz1xmo9WzAV2rwy1fypbVwNYvhRhgLOLESzxQNqzBiNV68aOu2FXvix9NZ/MYnf45PPHgSgKKf1rNAW+24pN763JQS6E8vxhBOVj4B9SfnZqzU+benLuC5CyH865NTRZ7onaDUUkAGnoVoY5VX9doqAEqQ8tgt+NHxefzg6CwA5c5CMhpwIpLMIppqXzJQWKQ1YVFfh78GSQdQA/5Koqzx0e+yGo489DmtaqGE8nwtJeC2AyP44Gv345V7h8pe68Zxoz0Z8BPpHJZiaWzpKw/4sqyxZRm+tEmucqubzOSQyOS0xSKgIOnIwLocSyOTE7jvyQtqDX6qruaSSoz5HZql7jNTq3Cr+zt6ofIUns2c4WdyeXzixydxyZgPY34HPvydY8g12MfQSmTgk+eJzCAbNcVrJOADwO/ftAun5qO4+77nAKAswwfQVptkKelMBF1YiKa0hGitGf5EUBlFOrUSh81s0j6n1F5B7yhqs5i0LvxaGb7VbMI7b9hh6G+l7IMlnbZzQdcwUoom6bRq0TZQuzQzbPClc6knSEK1V5An30woiUdOL9Uc4VaLsYATi9EUQvEMTs5HcceVytTJ5y6sVnyPvqJgs2X433hiCpPLCbzvVy/Gf71tL45Oh/GvT07VfmObKNWuZeBZjLQvwweA99x8ER7981fhQ3dcgjcf3IJ96rg+oL7kplHue3IK33tuRnssf++JoBvpbB4LkRSsZjKslKmHraqs+9yFMPwuq7amF3AVm5uV/p2kjt/MWl+gCz3xezLgayWZgXIN/8qJPowHnNgarN24UQ+ybK3aYlYoUa6jli7a6rONf/rFGSQz+aoDHmohT9gHT8whlxe4ac8gxgNOPFctw4+ndce1eTL8VDaHTz54EldOBHDTxYO4/fIxXDURwMceeKFjf4dCdYqSGMiyv0WdpPPiXATv+sLhMi8nuQ4E1OeFX4rHbsHvXL8dH33T5bBbCpm1vMtodB2hGp/68Snc+8uz2uOYFvALJZWONWb3+s85PhMuWkMry/AThbJNoPD9KS23bARF0uEMv+1cMKjBl/zKnkH84u5XamWRzVJP1qPph85ySUfaK8gv5uVbA/jR8fmiz14L8u7m+8/Pap97YNyH56YqZ/jLOhlsM9Xif+upaUyHkvjjW/aAiEBEeM/NF2EhksKzU9UXuttF6WKlx26B3WIqCvg/e3EBD56Yx/HZwkX8+EwYl3zwAbwwGwGgy1zrWLStRX+LZy3k8gKTK3FEkoWLqrzAblPLjydX4muWc4BCwE9n80UJV6mbZWmGP64F/LVn+H6XlTX89eDCSgJmE2lWCu3EaVMm6Jyci1TcZtUgyyqtw5cn3Dtfvl3bpjkNXzlhf/riAoa8dgz7HLhsSwBnl+JlLeX645QneryNC3Pdxn1PTWHnoBuvUAdaAIVAMd+ghNIqSm2BiQgDHntRsJVJxtnFmPbc05OryOYFnlMrskKJDEwEeFqQ4PgcVlhMVDYkZa3MhBLI5ERRIYEm6agBf2o5saYafInfZdUslf1OvX2xoq/LEtzSgL9jwA2ziZqSVftU2ahbynyBXg34q0qFi2WNul+jXLMjiMfOLFf8h5W3dUaSTqxE0nnl3iFNbmrmZJMXi1Q2j8u2+AEAB8aV/x81KM/M5wVW4mltfsBmyfBnQgk8dmYZd1w+XtSzIRf35+ucd9BqZCLgtBYC9YDXXpThSxnx7FLBEfKMGvzPLSn/lw1/phrWyPVgMhH63LYiz/xmOK8etz7Dl+fdNpmZ5/JNZfhA4eKt//4FXFZkcgW/fX2VDgC88aot+PZ7bygzRWuEgFPxJmpnVVOj9GzAr8dcqVVctyOImVASk8vGC7dGt9V2iwkmKmQ0oUQGZhPBY7fgzkMT6HNZm1owcljN2u3oZeqItkvVgP+sQcCPJLPIi4IMtlky/G8/Mw0hgDuuGCt63udQJJS5DgX8ZIlLJAAMemwlGb5yvukz/NMLMuArwTSUyDak39ei323TvHaa5dyycozRVFZLlhLqhW4s4NT8+5vR8AFdwC/R8IHC3fdqPAOvvTAzwGYxYb/qX7VW/F1ooNabAX8lYajft4trd/YDAB49Y1y7vRpXgrnenZOI4LJZEFNP8FW1MYuI8J9u3IWf/Zeb11yZIJE6/qVqhh9029SF2/KAL7tsh7x22MymTZPhf/OpaVy+NYDtA+6i54kIwz5H5ySdtNJRq89uFUnHKMMvBPwzi8rsWxlM67VVqJd+j00b6dcs8qKUywuteCGmzvF1qC6hwNpLMiVbjTL8EsfMev2GGqGvCw3Uei7gZ3N5zIaThiWZ7WL3kAdBtw2PnV42fF3eVpe6c7ps5qIMX34xTSaqOY6uHqSOf5ma2QPAZVv8WiOWHlmS2ee2wWU3b4oqnZNzERybCeN1Jdm9ZMhr71iGL//+LltxwF+OpZHPC+TyAnPqxejMYgxCCGRzeZxXA72UdEItDmRBt71lVTrnlwsXKinrJHR2EvIOtRkNHygEfL+rWMMHCsG41M22FRT8dLqnUqfnAv5iNI1cXhiWZLYLIsKh7UE8ViXDDxh86Vw2s5ZJtyPDePnuAdy4Z7BIh7xsSwDnl+NlWZpsuupz2eC2WbqmDn81nm6pkdt8JIn7npzCqfkIvvX0NEwE/Pplo4bbdjLDL530BCglgjl1rWUxmkIuL7Bz0I1IMouVeAYXVpVF0N1DHqzGMwjFMwjF00UNf83SUklHt/YQURdu4+msVtAgy0BbpuHrJR1XcYbf6jsh/f66qRa/5wL+iN+BF/7y1XjDVePrut9rdwYxtZLA1Eq87DVpylSKy2bRNMt2nHC/fd02fPGdh4qeO7QjCAB4tORuRGZtQZdN9ervfIafyuZw8/96CF/4xdmWfebnf34Gf/K1Z3DL3/0Mn/rJKbz8ooGKTXhDPrs2/3i9iZcM/gCKu21lr8l1qpx4dimm6fc3q23+55Zj6nnVmhJkQAn4kWS2qNZ/LQghcH4prpVfhtUMP5bOwWVX/YNalOFfNRHAbQdGtHMf0Gf4ynnfloCvXmi7yUCtJQGfiF5NRC8Q0SkiutvgdTsRfVV9/TEi2t6K/VbCbjE3vdDTKNfuUL54RrJOqXGaRD8EpR0nnBGXbfHDZTPjkdOLRc/LW9s+txUuu6UrNPyj02GsxDM4rerSrWBOHerxN2+8FHcemsAf3bKn4rZDXgeiqWyRg+N6UTr4A9B120ZTmn5/vQz4izGcVhdv5ZBtWYLbWg1fOQZppb1WVuMZRFJZHBhT5EaZ4RdJOt7WaPhehxWf+a2ri+ZBD/sccNnMOKqOO23H98/fixk+EZkB/D2A2wDsB3AnEe0v2exdAFaEEBcB+DiAv2l2v93G3hEv/E6roayjGKeV31brA2upuVq7sJpNuGZ7EI+8VHycy/E0LGqVkDJvd/2D3JGzy0WZ45PnVgBAGzXXChajaYwFnHjLNRP46zdciqu39VXcVtpw1JJ1ZkKJhm2La5HI5GCzmLSqEaC421bW4B/aEYSJlIB/ZjEKv9OKK7YqVVlHp0PIi8a6bGsRdJd3/Eq+fmQS7/rC4bo+Ry4qXzKuVMJIDT+ezsKllqK2KsM3wmo24dCOIB5RTfJW2xDwbRYT3DZzzy3aHgJwSghxWgiRBvAVAHeUbHMHgHvVn78B4FXU7HzBLsNkIhxS6/FLWY2nDU8ml9WMRDqLfF5pPlmPDB8Art/Vj5cWYkU15qvxNPrcNl310Ppm+JPLcbzpHx4parN/6rzSFbxQR933145M1hzwAigXj3rLXaXUU23hNpLM4Ob/9RDue7L2vhtBn+lKNMfMSAqz4STsqsnXeJ8TZ5fiOLMYw44BN1w2C4a8dm1xvp7xhvWi98wv5RenFvHgiXktW6+GXFQuZPgy4OskHfXfqV136y/b1Y9T81GcX4ojnc23fA0NUGSdXlu0HQcwqXs8pT5nuI0QIgsgBKC/9IOI6C4iOkJERxYWFlpwaOvLtTuCOLcUx3ykECByeYFw0rgW2mUzI5bKIZLKQrQ4E6uGlAEe0VkAL8fS2nQwdweqdOSt9Y+OFYa0PHleyfBrGYatxtP44Leexyd+fLLmfhajqbrb5evJ8KdWEkhm8jijK41sBXKAuR6/0wqrmbAYTWMmlMSoXxnws73fjbNLMZxZiGGnWl66rd+lBfxWBjJZKrlk0G07r6saqoVsupK17oVFW4MqnbYFfKWz+vtHFfO2dtxhB7rMXqEVAd8oUy9tOa1nGwgh7hFCHBRCHBwcHGzBoa0ve0eUk/el+cIJL50yjU4ml92MRCanbdOODMOIS8Z88NotRZ7vK7GMVjfs6kCVzvEZJeAfObeM1biyKDkTSsJrt2Ahmqranv5/HzuvBN3FWFFX42woqXnKAErJ7nI8jcE6DbHq6baVWnqjLpa10I83lBAR+t12VcNPaN3U2/vdODUfxXQoiR1awHcjov4tWtt4pQRho25beSf00kLtNZdzy3EM++zod9tgIl2Gn9JV6WgBvz21JftGffA5LPh31W+qHQlXtxmoteIvOQVgq+7xFgDTlbYhIgsAPwDjovUNzI5B5cumX2QsHbygRwms2aIBy+uBReqXOh1/JZ7W9Fl3B6p0TsyGYbOYkBeK/4/M7m/eO4R0Nq9VcZSSzubxxUfOwu+0Qgjg2HTBSOyD33oed33piPZ4OZ6GEPVb3tbTbSu19EYGk5yci+DQX/2o6pCVRDpnqF0PeG1YjKYwvZrUnFq3D7i1xX95DkprAqC1gczntKh+OuVBTFY0yWqhapxfimNb0A0iZd1Iy/AzhQx/IujCFVsDuExdk2g1ZhPhup39mnTYjoDfbQZqrQj4hwHsJqIdRGQD8FYA95dscz+At6s/vwnAj0U3OQq1iFGfAw6rCWd0J7zmo2Ogo7psZqSyea3Ldb0kHUDR8c8uxbX2/BVdvbbLbkE8nUN+HQeAnJiN4FV7h9DvtuHB4/N48twqHFaTZmhmtEgIAN99bhpz4RQ+8Ov7ABTGOObzAo+dWcbUSmFBVS7+1ivp1NNtK4eBVDo+I47NhDEfSeG9//JkRVttowwfUI59PpzCXDipy/ALwV3L8HWdw62UKogIQQM/nXg6q91R1JfhxzSDNK/DWqThywud02bGN9/zclw1UXlhvVletqugLLfj+xdwWrtqkHnTAV/V5N8L4AEAxwF8TQhxlIg+RES3q5t9HkA/EZ0C8CcAyko3ewGTSdFTT+s0TBksZPasR2Yyc+qXvhUWtvVyvXqiP/LSEoQQWIlnEHSrGr56XIkaYxtbRSyVxbmlOPaP+nDz3iE89MI8Dp9dxmXjAS2LNarUEULgcw+fwUVDHvzm1Vsw6LXj+Wkl4J+cjyKUyCCXF9q/gfShKZ0/Wo1a3bYzmqRT/227/F0iySze8y9PIp0tr/CJV8rwPXacWogimxeauZ7eFmJ7f3szfEApzSxtvpLZPVHtDD+ZyWEunNKO0euwIJzMIpvLI53Na+M/14OXXVRwSG2npLOeyVM1WiKOCSG+J4TYI4TYJYT4K/W5Dwoh7ld/TgohflMIcZEQ4pAQ4nQr9tuN7Br0FC1aHZsOgwjYPewp21ZqlXIw9Hpm+PtGfOh32/DVw5NaYJQavlv1/Imtk6xzQtXZ9436cMu+IYSTWTx3IYQrtwU0+cUog3745CKOTofxrht2gIhwYMynjXB8/GxBMZR3MVJnH2zAAXHY56jafCUD/lKs+jqDnoVICjazCX/75svxxLkV/O0PXijbJlklw5cXCHkx3NrngomU+Qny3042NFlMVFbt0yxKt23x30ReFPeN+HB6MVZ1PKS0f5AZvs9hRSSZQTxT3mzWbnYPebRy13Z8//o9NuRF8TS5TtJznbadZseAG+eX49qX8uh0GLsGPYYDV+SJPaPOnm1l+VwtTCbC+37tYjx2ZhmffuglANAF/OLhLO3mhDrAY++oFzfsHoTVrKzxXzXRV6g9L8nwk5kc/sf9RzERdOH16vjGA+N+nJyPIJHO4fCZZa2GXc72lReNRjL8Qa+9qqQjLyaZnKg4Z6AUWRr62svG8GuXDONbT5cueamSjmGGXzhHZIZvs5gw3ufU5BxAKQf0O60IuMo9nJol6LaVafjS1+f6Xf1IZ/NaJ7AR0t1zQpfhR5JZ7Xxr1XCieiBSdHwitMS/qpTBNc4ibhcc8FvMjgG3NskHUJpfLqlgsypP7JlwEjazCY42VSNU4q3XbMUNFw3gnp8pN1xSdpLHtW4Z/kwEXocF4wEnPHaLZhdw1UQf+lw2mE1Utij6mYdewpnFGP7ydQe0Ou1LxvzIC+UCcuTssqb/y+CzEEnBYTVpklU9DPsqd9sKITATShbVx9fDQjSlXXSu2R7EbDhZ9t64QR0+ULzgrB+Q8+E7DuD9r764aNtt/a62VH4pjpmlkk5x5++pKjr+U5OrsJpJq2rzOiyIpDKGhnHrwR/cdBE++Nr9RU1urcLo3JhcjuN/fvto1bugdsEBv8XslJU6CzEsqR2RsrmklEKGn4DPwE2z3RAR/voNl2oBUC7uubVpXOuT4R+fCWPfiE/7/X/vxl2468adGPTaYTIR+t22Io381HwUn3noJdx++Rhu3FMo35U20A8cncN0KImbLx6C12HBzGphYXXAY2/o71ytFj+SyiKezuFStVu03kqdhUhKk5XkUBq59iBJpnOGDUcygNjMJgR13ds3XTxUtrj5hivHcfvlxk6gzdDvtiGaKvbTmY+kYLeYcOWEUlFTTcd//MwyLh33a3cwPqeyaCvPt3Z01lZj/5gP//HlO9ry2UaS5ANHZ/FPvzhr6LvVbjjgt5idA4pWf2YxqjUTVc7wlRN7NpRsqcFVI2wNuvDfX7sfNotJm3YlOx3Xw0NGCIETsxHsHfVqz92wewB//pp92uNBr70omH74O8fgsJrw3167r+izxvwO9Lms+PLj5wEo2fN4wKmTdNIND5Wp1m0rK2zkYJl6b9sXo4VuX3luPF9iWV2tSgcAhv32mlOs3vHyHVW9gtaK9NPRyzpz4SSGfQ4E3TYEXNaKlTrJTA7PTq3iGp2RmSbpqAF/PRdt243e/0giz5tOTMLigN9i/C4r+t02nFmM6QJ+pQxfObEjqdZOJWqUtx6awLP/41e1ILSeGf7USgLRVFa7vTdCP/gjk8vjkZeW8JZrtpa5XBIRDoz7EUpk4HVYcPGIF2MBpybpNNJlK5EZvlHAlwu2l6oTxeppvsrm8liKFS48XocVOwbcRRl+OptHNi8MpQ2p4csF204gpT+9rDMXVkzpiAg7B9w4XSHgP3V+FZmcwLVFAd+KXF5os3LXO8NvJz6HBTaLqUjSmVXPpU5YkHPAbwM7Btx4aSGG56dD2NLnrFhuqf9Ct9KzfC3o5QNt3u46ZCCyw3afLsMvZdBr174wZxdjSOfy2DdqfIGQF9eD2/q0IdRyYXUh0njAlxcVI31eSkV7R7ywmKiuWvzlWHnz14FxP56/UGgYM3LKlMg1jWbmHTeLvOjoSzPnIynNjXLXoAcvVZB0Dp9dBhFw9bbiDB8oZL6yaKAXICIMeorvUGXVVydcWDngt4Gdg26cWYzh2HS4on4PFKQTYH1LMmshS/vWI8M/MRsBEbBnuHLAlxm+lH8A4OIR4+0PqHq6lAzGAk6sxDOIJDOKrUKDko7PWbnbdiaUBJGysNvvsdW1aDuvlYYWLvCXjvtwYTWhSSSJKlq2yUS4/fIxvFL1vO8EQc1eoTiIDal3QzsHPViIpBA2MFF7/Mwy9o74is53WR0jK31c1t6RdADlAmmU4Uc44PcGOwaUE/7MYqyifg8Ul591U8DXMvx1qNJ5cS6CrX0u7SJjxIDHppU9vjAbgdlEuGiovK8BUKpEDu0I4jUHlClWcpj90emwklnX6aMjkd2255biODkXwXNTIa2JZlat0LFZTGXzZishM72iDF9NCmSXcKJGPfrH33IF7rhifQf86JGSjrxAxVJZRFNZ7W5ol65wQU8ml8cT51aK5BygkOHLBsReknQA5d9aru8IIXSSDgf8nkBfD31gvHKGr1+UWy/jtHqwqz7s61GHPxdOakG5EvpKhxOzEewYcMNuMQ4K/R47vvZ712vdp1L6eHZK8UtpVNIBlPLHHxybw60f/xl+41M/x3efU9wVZ8JJjKmfrwT82ou2heavgiRziXqOyOHyWoa/zkN86sXnsGiunUDhrmVYl+EDKNPxj06HkcjkcM324oDvkwE/0nuSDqCcGzLDX41ntB4dDvg9gsxwgMoVOoBi3iRr79fLOK0eFE9887pk+HPhlBYoKjGo1TKn8cJcuKKcY8SYejF5ZlIJpo00XUk++Nr9+NAdl+CTd16JAY8d31fdFfWOlY1m+HKaE6Dc3W3rd+HotMzwlb+7s0urVaSfjlxklXKX1PC39bvgdVjwyR+fwuRyofTwcXU40DU7istHNUlH1bYdFS7mG5VBrx3LsZQ6eL4gDXKVTo8w0a+0ug967ZrFbiVkRUw3STqAclztzvCFEEp1R42/kczwzy3FMLmcwN4qen8pI34HiIBnLygZfiO2CpID4378zvXb8RuXj+HW/YrXTyqbw4zOsVK5ba9tr7AQScFjt5R1kx4Y8+syfCUD7NYMH1BskqWkUwj4yt/Wajbhn95xDZaiKbzxM7/EE+dWcGw6jAePz2PHgLusukov6bhs5prlphuNAY8deaFIYHqzvGgFB9h2wgG/DdgtZmzvd+OyKnKOROqV3RbwXfb2Z/jhRBapbB5DNbJuKcP8QrVzbiTDt5qVqVCTy0pFzVoyfD2/un8EsXQOPzw2h0gqq8vwbXXZK1SauHVg3I/J5QRW42mt47SrA75uIVJWnQzqAvnB7UF84/dfBhMR3viZX+I1n3gYj51Zxg06szKJzPAjqey6d9muB3pJUl4cidavk11Pd94z9gD/8NtXV12IlMgTfD2dMuvBbbO0vUpH3t4O18jw5aSnX55SBq9XKsmsxFjAiblw47YKRly/qx8umxlffOQcgMIagf5LXa3EVt9lq0c2bz07FdIWbbt58fKSMT8++/BpzIaSmI8k4bCaNC1esmfYi2++5+X44fE59LttGPU7DHtS3DYzTATkRXf/zmulePi8cnEc8zsR5Tr83mHPsLfmYiRQqNTpJg0fkOMX25uByMywVsBX7BUUS163zVzX31WP1PEHvY3ZKhjhsJpx08WDeFydXTziK2j4gLLOUA3FR6f8gnDlRAAeuwX3PTmF5AYI+Hce2opcXuCrhyfVdRiH4d92xO/Ab1+3Da+5dBRXTvTBZikPOXIICtBbXbYSmQwsRFKYiyTR77ahz21FtI7Zv62GA36HcXWppOO2r0OGX6L9VkN+afaMeBvWePWVNK3g1v3D2s9SwzdqoTeiUobvtlvwmwe34LvPzeCcOu+1myWdbf1uvGL3AL5y+DxmQomaslwtpKzTzRe5taI5vkZTmAspFhTuDowRBTjgdxyZ4XdTWSaAdanSkZJO6SKeEfJLs7cB/V4iM/xWBfybLx7SnBWH/cpnVvPtlyQzOUSS2YrNX2+/fjuyeYF/Ub2Aul3P/g/XbsNMKIkj51ZqLrzXQi7cdvvvvBY8dqV5byGSwqw6qcxjt3CVzmbEZTPDbjEZttF3kvWo0pkPp+B1WOrK6mSQvLiBCh2JXtJpBQGXDdfuCGLAY9f6AQJOq2LjXKXbdtGg6UrP9gE3XnnxEFbjGRAp/RDdzC37hjDss0MIYLiOi3Y1fGqGv55e+OsFEWnNV4rJnB0eh6Uji7bdfUZtArYGiwdXdAu1qnSEEE37eUuHxXqQ2fnFVUzWKjHmb22GDwB/cfsl+Ls3X6491mycq2T48mJQ7cLzjpdvB6DIOettl90oFrMJb71mAkB9slw1ejnDB5Rzb3o1gcVoWpF07BYuy9yM/H+v2oN//f2XdfowypBVOpXqyj/90Eu49e9+WvdYPyNktlMPOwc9cFhNVU3WKjHR74LLZq5ox7AW9gx7i7z4gdrdtgsGXbal3HDRAC4a8nS1fq/nzkMTGPU7tFkEa6UQ8HsvwweUi7w0ChzxdU7S6c2/7gbCZjEZVi50GpfdjFxeIJXNG8pNj7y0hNOLMUytJLBVNzC7lCfOLeMd/3QYP/7Tm8oy2/lICodK2uwr8forx/ErewbX5Crqd1rxy7tfqckG7WLAW73b1qjLthQ5lOal+coTo7qJEb8Dj/zZq5r+HK8m6WyMC12jDHjsCKsZ/bDfgblwCqlsHtlcHhbz+n3/uy/SMF1BNU98IYSWrTyjetRU4pGXlhBJZosGu8vPUBwW65N0zCZqSoMPuGxt7+Ac9NireuLLDL/fXf33uGZ7EG89NNHSY+t2el3S0Z+7w14HPOrvu96VOhzwGUOqeeIvRFOaF/ozk9UD/kk1U5W+K5LVeAbpXO0u243EgNeGxWi6osy1EEmhJ7xj8QAAE8xJREFUz2Xtyju6TuPt4UVboNilVanSUb5fkdT61uI3deYRUZCIfkhEJ9X/9xlscwURPUJER4noWSJ6SzP7ZNaHap74J2YUT3qbxYRnSkbzlfLinBLwS7XtertsNxL9bhvSuXxFbVY/2pApZrNk+DazCX0uq/b92mgZ/t0AHhRC7AbwoPq4lDiA3xFCXALg1QD+NxEFmtwv02aqeeJLOec1B0bw/IVQxWqdXF5os02XSgN+uNhStxeQg0H0s171VPLRYXo/4MsKsSGfvaizeL0XbpsN+HcAuFf9+V4AryvdQAjxohDipPrzNIB5AIOl2zHdhXZCGpSOnZiNYNTvwI17BhFP53CqwgLj+eW45v29VCLplFrq9gJBtyJLVAr4M6Fk0/XqvYpsPOxVSUcGfGnFsVED/rAQYgYA1P9XnbtGRIcA2AC8VOH1u4joCBEdWVhYaPLQmGaQVg9G7o/HZ8LYO+LFZerw7koLty/OKdIPUXmGX09N+kajWoafzOQwE0pqg1mYYqTdRJ+7uzrOW4U8z4dVm4+CpNNlAZ+IfkREzxv8d0cjOyKiUQBfAvAfhRB5o22EEPcIIQ4KIQ4ODvJNQCepFPDT2TxOzUexd9SHnQNueO2Wigu3MvPfN+IzzPD9TmvXdRg3Q9BVPPpPz3l1EMi2/solrJuZS8Z8+PLvXofrd/Z3+lDagttuwYDHjp3qBb9TGX7N+ychxC2VXiOiOSIaFULMqAF9vsJ2PgDfBfDfhBCPrvlomXXDVyHgn5qPIpsX2Dfqg8lEuHSLH89WWLh9cS6C8YATE0GXpuVLGmm62ijI7HQlXh7wz6plqdv7OcM3gohw/a7eDPaSb//nlyPgVJICT7dm+DW4H8Db1Z/fDuBbpRsQkQ3AvwH4ohDi603uj1knHFYzHFZTWcA/Mass2O5TTcwu2xLAidmwZumr58W5KHYPe9DvsWllnBJpqdtLeOwW2Mymst8VgOaAyQF/8zLqd2q+Ue4qa2TtpNmA/xEAtxLRSQC3qo9BRAeJ6HPqNm8GcCOAdxDR0+p/VzS5X2YdCDhtWC3JVo/PhGGzmDT/nyu2+pHJFRqxJLJCZ/eQB/0eO1biaWRzBSVvPpysyyVzI0FE6HNbsWIQ8M8uxRBwWbtu0A3TGWSHfXSdDdSaWhIXQiwBKOurFkIcAfBu9ed/BvDPzeyH6Qx+p9Ugw49gz7BHawfXFm4nV3HlRKENQ1bo7B72IpnJQQhgJZ7BoNeOfF5gPlJ7ePlGJKib9arn3FIc2zi7Z3R47JYNJ+kwPYzfZcVqvDjgKxU6BcfKUb8DIz4HjpxbKdrupFqhs3vIo1kJyEC4Ek8jmxc91WUrCbqthgH/7FIM23nBltHhtps3XOMV08OUZviL0RQWo+miISREhGt2BHH47HKRpYC0VNg97EXQrSxULanmYbNqDX6zQzO6EaMMP5XNYXo1wRk+U4TbZkFkg2n4TA8TKAn4syElUG/pK85UD23vw1w4hcnlhPbci3MRjKmTfbQRb2ogPK8uYE5UcdncqARd5Rn+1EoCeQHO8JkivA6WdJguIuAqz/CBwrhByTU7FIvjx88ua88pFTrKnUC/2lQjM/zTaoliNw5+aZagW7HBzegWqM8tKb8vZ/iMHrd9/adeccBnKuJ3WhFP5wr2CGq3bOnkqD1DXvidVhw+owT8yeU4js+EcfU2ZRE34LTCRAUN/6WFKIZ9dq00rZcIGtTin12UJZmc4TMFOjH1igM+UxG/2jkqs3wtwy9ZbDWZCAe39eGwmuF//YkpEAFvvHqL9nrQXZgGdWYxhp0DrZs+1U30qesVK7HCndG5pRi8dou2lsEwAODtwNQrDvhMRQr2CkqgXoymYLeY4DZwNLxmRxCnF2OYDyfx9SOTuHH3IMbV4eGAYh28FE1BCIHTCzHsHOxNeUNboNZZSZxdimPbgKvrZ9Qy64ubyzKZbiKgBnxZmrkUTWPAYzcMXIdUHf9vf/AiZkJJvOWarUWvy27b5VgaoUQGOwd7M8MPVsjwWb9nSlE0/BzyFezF2wEHfKYipQZqC9FU2YKt5MCYHw6rCV89Momg24Zb9g0Xvd7vsWMpmtIWbHf24IItUAj4csJXJpfH1EqC9XumDK/001nHhVsO+ExFAq7iDH9RzfCNsFlMuHKrskj7xqvGy8b49buVDP+0aqLWq5JOn+aYqfzNplcTyOYFZ/hMGZ2YesUBn6lIaYa/FE1VDPgAcJ1qbVsq5wBKKWckmcXxmQhsZlNZLX+vYDWb4HNYtAz/LJumMRVwq3Nt13Phtvfq4piW4XVYQQSsJjLI5wWWYmn0V5B0AOBdr9iB63YGcdGQt+w1ORzkyLllbOt3wWzq3QXMoNuGZfWuSFpM9GLPAdMccqzjei7ccobPVMRsInjtFoQTGYQSGeTyomqG77FbcG2FARbyQnFsOtyzco4k6LZpGf5Tk6sYDzh7arIX0xrctvUfgsIBn6lKwKVYJMsa/GoZfjXkYm9eADt6tAZfogR8JcN/8twKrtrWV+MdzGbE3YGpVxzwmapIe4UFNeAPVsnwqyEdM4HeXbCV9LlsWImlMRNKYCaUxFUTgU4fEtOFdGLqFQd8pip+pxWriUzBVmGN0kRQd2ewq8cDftBjw3IsjSdUy+irJjjDZ8rxODjDZ7oMaZGsSTprtAfwquP/APSsrYIk6LIhncvj4RcX4bCasH/MV/tNzKaj0iDzw2eX8ejppbbskwM+UxW/04pQXAn4JirUmTcKEaHfY0Ofy6r5zfQqsvnqwRPzuGw8AKuZv2ZMOXaLCWYTlUk6n3jwJP7m+yfask8+E5mqSA1/MZJG0G2HqYlyykGvHbt61FJBjwz4i9EUrtzG+j1jDBGpYw6LG6/i6RxcBn5VrYDr8Jmq+J1WZPMC55ZjFW0V6uXDdxyAxdy79fcSvSvm1azfM1Xw2MunXsXTuTXfSdeCAz5TlYBTOfFeWogVjTZcC5dv3RzZrj7gc0kmUw1lrm1xwE+ks23L8FnSYariU+0VFiKpNS/YbjZkwJ8Iuqo2qjGMy2ZBPFMu6UjbhVbDAZ+pijRQA8onXTHGeOwW2Cwmrr9nauK2mxEvy/BzcFrbI740FfCJKEhEPySik+r/K96/EpGPiC4Q0aea2SezvkgDNaAwm5apDhHh42++An/4qt2dPhSmy3HZFE98iRACsS6WdO4G8KAQYjeAB9XHlfgwgJ82uT9mnSnO8FnSqZdfv2y0Z4e8MK3DZTMjrvPDT2XzyAvA2aUB/w4A96o/3wvgdUYbEdHVAIYB/KDJ/THrjFy0BdbeZcswjDEumwVxXYafUH/u1gx/WAgxAwDq/4dKNyAiE4C/BfD+Wh9GRHcR0REiOrKwsNDkoTGtwGE1aR2yA24O+AzTSty2Yg1fLuBKJ81WU/NTiehHAEYMXvpAnfv4AwDfE0JM1hriLIS4B8A9AHDw4MH1G/TIVISI4HdZsRBJYcDLkg7DtBKXXanSyecFTCZCQpV32iXp1Az4QohbKr1GRHNENCqEmCGiUQDzBptdD+AVRPQHADwAbEQUFUJU0/uZLsLvVAJ+kMsyGaaluG1mCAEkszllATfV3ZLO/QDerv78dgDfKt1ACPEfhBATQojtAN4H4Isc7DcWAacVPocFdkt7TkKG2azIwC4DvdTzu3XR9iMAbiWikwBuVR+DiA4S0eeaPTimOwi6bRjyOTp9GAzTc7hUrV4u1iYy2aLnW01TnyqEWALwKoPnjwB4t8HzXwDwhWb2yaw/7/+1ixFZR89uhtksyI7amKrdywzfzeZpTKfYPdychw7DMMbITD5eEvC7VdJhGIZh1kiphl+ow+9CawWGYRhm7RQyfCXQS2mnW6t0GIZhmDUiNXwp6STSORAp07DaAQd8hmGYDiEzfGmgFk/n4LZZUKtJda1wwGcYhukQWoafKizatmvBFuCAzzAM0zEcFlmWKRdt22eNDHDAZxiG6RgmE8FlM2seOrF0Dk4rB3yGYZieRD8EJZHOcYbPMAzTq+jHHMbTWbjt7euH5YDPMAzTQZxWc1GVDks6DMMwPYrbbinU4WdY0mEYhulZlLm2aqdtKgdnm2wVAA74DMMwHcVtsyCe4rJMhmGYnsdlNyOWzkIIgThLOgzDML2LlHRS2TyEaJ9TJsABn2EYpqO4bRbEUllNx+cMn2EYpkdx2SxIZfOIJDMA2jf8BOCAzzAM01GkgdpiNA2AM3yGYZieRWb0i9EUAA74DMMwPYtbXaQtBHxetGUYhulJZEa/1O2SDhEFieiHRHRS/X9fhe0miOgHRHSciI4R0fZm9sswDNMrSLO0jSDp3A3gQSHEbgAPqo+N+CKAjwkh9gE4BGC+yf0yDMP0BDLAL0SUgN/N1gp3ALhX/fleAK8r3YCI9gOwCCF+CABCiKgQIt7kfhmGYXoCV6mG38VumcNCiBkAUP8/ZLDNHgCrRHQfET1FRB8jIsPfiIjuIqIjRHRkYWGhyUNjGIbpfly2krJMe/sCfs17ByL6EYARg5c+0MA+XgHgSgDnAXwVwDsAfL50QyHEPQDuAYCDBw+KOj+fYRhmw6LX8M0mgs3cvlqamgFfCHFLpdeIaI6IRoUQM0Q0CmNtfgrAU0KI0+p7vgngOhgEfIZhmM2GzPAjySy8dguIqG37avZScj+At6s/vx3Atwy2OQygj4gG1cevBHCsyf0yDMP0BHaLCSY1xrfTVgFoPuB/BMCtRHQSwK3qYxDRQSL6HAAIIXIA3gfgQSJ6DgAB+GyT+2UYhukJiEhrvmpnSSZQh6RTDSHEEoBXGTx/BMC7dY9/COCyZvbFMAzTq7jsZkRS2bZ22QLcacswDNNx1ivD54DPMAzTYWQpZrdr+AzDMEyTuKyc4TMMw2wKZIbPGj7DMEyPwxo+wzDMJkEGeg74DMMwPY4M9O10ygQ44DMMw3Qcl50lHYZhmE2BmyUdhmGYzYGsznG20Qsf4IDPMAzTcdxqWaa0Sm4XHPAZhmE6jFys5U5bhmGYHkfT8FnSYRiG6W2u3dmPu27cicu3Btq6n/YKRgzDMExNPPb/1979hUhVhnEc//7QtDRis3+UK6kgpUmlSNgfIixITdwuujCEhIRugiyC0rzqMor+gRmhpYVoZFaLUCQmdKWlFWapuWXllqVRWhSk0tPFeZcmnckZd/PMOef3gWHO+87ZmefhOTxz5j2zu4N5ZOb4//11fIZvZlYRbvhmZhXhhm9mVhFu+GZmFeGGb2ZWEW74ZmYV4YZvZlYRbvhmZhWhiMg7hrokHQS+6cdTnA/8NEDh5M25tCfn0p7KlAu0ns+lEXFBvQfatuH3l6StETEl7zgGgnNpT86lPZUpFxjYfLykY2ZWEW74ZmYVUeaG/0LeAQwg59KenEt7KlMuMID5lHYN38zM/q3MZ/hmZlbDDd/MrCJK1/AlTZe0W1KPpIV5x9MKSaMkbZK0U9Jnkhak+RGSNkjak+7PzTvWZkkaJOljSevTeIykLSmXVyUNyTvGZknqkLRW0q5Uo2uLWhtJD6RjbIek1ZLOLEptJL0o6YCkHTVzdeugzLOpH2yXNDm/yE/UIJfH0zG2XdIbkjpqHluUctkt6dZWX69UDV/SIGAJMAOYANwpaUK+UbXkGPBgRIwHpgL3pvgXAhsjYhywMY2LYgGws2b8GPBUyuUXYH4uUZ2aZ4B3IuJy4CqyvApXG0kjgfuAKRExERgEzKE4tVkBTD9urlEdZgDj0u0eYOlpirFZKzgxlw3AxIi4EvgCWASQesEc4Ir0M8+lnte0UjV84BqgJyK+iogjwBqgK+eYmhYR+yPio7T9G1lDGUmWw8q020rg9nwibI2kTuA2YFkaC5gGrE27FCmXc4AbgeUAEXEkIg5R0NqQ/XvTsyQNBoYB+ylIbSLifeDn46Yb1aELeDkym4EOSRefnkhPrl4uEfFuRBxLw81AZ9ruAtZExJ8RsRfoIet5TStbwx8J7KsZ96a5wpE0GpgEbAEuioj9kL0pABfmF1lLngYeAv5K4/OAQzUHc5HqMxY4CLyUlqiWSRpOAWsTEd8BTwDfkjX6w8A2ilsbaFyHoveEu4G303a/cylbw1educJ971TS2cDrwP0R8Wve8ZwKSbOAAxGxrXa6zq5Fqc9gYDKwNCImAb9TgOWbetL6dhcwBrgEGE629HG8otTmvxT2mJO0mGyZd1XfVJ3dWsqlbA2/FxhVM+4Evs8pllMi6QyyZr8qItal6R/7Poam+wN5xdeC64HZkr4mW1qbRnbG35GWEaBY9ekFeiNiSxqvJXsDKGJtbgH2RsTBiDgKrAOuo7i1gcZ1KGRPkDQPmAXMjX9+WarfuZSt4X8IjEvfNhhCdoGjO+eYmpbWuJcDOyPiyZqHuoF5aXse8Nbpjq1VEbEoIjojYjRZHd6LiLnAJuCOtFshcgGIiB+AfZIuS1M3A59TwNqQLeVMlTQsHXN9uRSyNkmjOnQDd6Vv60wFDvct/bQrSdOBh4HZEfFHzUPdwBxJQyWNIbsQ/UFLTx4RpboBM8mubH8JLM47nhZjv4HsI9p24JN0m0m29r0R2JPuR+Qda4t53QSsT9tj00HaA7wGDM07vhbyuBrYmurzJnBuUWsDPArsAnYArwBDi1IbYDXZtYejZGe98xvVgWwZZEnqB5+SfTMp9xxOkksP2Vp9Xw94vmb/xSmX3cCMVl/Pf1rBzKwiyrakY2ZmDbjhm5lVhBu+mVlFuOGbmVWEG76ZWUW44ZuZVYQbvplZRfwN0bdHAP/s0EQAAAAASUVORK5CYII=\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot each subject - look for irregularities\n", + "for i in range(len(ket_list)):\n", + " plt.plot(dACC[i])\n", + " plt.title(f'Subject # {ket_list[i]}')\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot each subject - look for irregularities\n", + "for i in range(len(mid_list)):\n", + " plt.plot(amygdala_mid[i])\n", + " plt.title(f'Subject # {mid_list[i]}')\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [], + "source": [ + "# all in all, ketamine group seems reasonable. Lets look at midazolam\n", + "vmPFC_mid = np.load('mid_func1_vmPFC.npy')\n", + "amygdala_mid = np.load('mid_func1_amg.npy')\n", + "hippo_mid = np.load('mid_func1_hippo.npy')\n", + "vACC_mid = np.load('mid_func1_vACC.npy')\n", + "dACC_mid = np.load('mid_func1_dACC.npy')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Generating global maximum graphs (session 1-2)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "ket_func1 = 'ket_func1_{region}.npy'\n", + "ket_func2 = 'ket_func2_{region}.npy'\n", + "mid_func1 = 'mid_func1_{region}.npy'\n", + "mid_func2 = 'mid_func2_{region}.npy'\n", + "# now lets built it around individual global maximum\n", + "def maxVec(funcArr):\n", + " vec = []\n", + " for mat in funcArr:\n", + " vec.append(np.argmax(mat))\n", + " maxi = []\n", + " for i, x in enumerate(vec):\n", + " maxi.append(funcArr[i][x])\n", + " return maxi" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " T test for ketamine group diff Ttest_relResult(statistic=1.5433996488468762, pvalue=0.15376419602078736)\n", + "T test for midazolam group Ttest_relResult(statistic=0.7009216115690157, pvalue=0.501070531766361)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reg='rACC'\n", + "ket1_max = maxVec(np.load(ket_func1.format(region=reg)))\n", + "ket2_max = maxVec(np.load(ket_func2.format(region=reg)))\n", + "mid1_max = maxVec(np.load(mid_func1.format(region=reg)))\n", + "mid2_max = maxVec(np.load(mid_func2.format(region=reg)))\n", + "\n", + "plt.figure(figsize = [10,5])\n", + "labels = ['','Ket_ses1', 'Ket_ses2', 'Mid_ses1', 'Mid_ses2']\n", + "x_pos = np.arange(len(labels))\n", + "plt.boxplot([ket1_max, ket2_max, mid1_max, mid2_max])\n", + "plt.xticks(x_pos, labels)\n", + "print(f' T test for ketamine group diff {scipy.stats.ttest_rel(ket1_max, ket2_max)}')\n", + "print (f'T test for midazolam group {scipy.stats.ttest_rel(mid1_max, mid2_max)}')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Calculate cross-correlation between vmPFC and amygdala" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/task_based_analysis/usingFSLRandomise.py b/task_based_analysis/usingFSLRandomise.py index 781a9d9..7dfe0e1 100644 --- a/task_based_analysis/usingFSLRandomise.py +++ b/task_based_analysis/usingFSLRandomise.py @@ -1,5 +1,6 @@ #!/usr/bin/env python3 # -*- coding: utf-8 -*- +# %% """ Created on Fri Mar 1 11:10:24 2019 @@ -16,7 +17,7 @@ import nilearn.plotting import glob - +# %% # grab all spm T images spmTimages = glob.glob('/media/Data/work/KPE_SPM/Sink/1stLevel/_subject_id_*/spmT_000*.nii') print(spmTimages) @@ -35,8 +36,8 @@ -#%% Now we grab al the contrasts per subject -subjectList = ['1223','1253','1263','1293','1307','1315','1322','1339','1343','1351','1356','1364','1369','1387','1390','1403','1464'] +# %% Now we grab al the contrasts per subject +subject_list = ['008','1253','1263','1293','1307','1315','1322','1339','1343','1351','1356','1364','1369','1387','1390','1403','1464','1468','1499'] copes = ['/media/Data/work/KPE_SPM/Sink/1stLevel/_subject_id_%s/con_0003.nii' % (sub) for sub in subjectList] copes = {} @@ -47,8 +48,8 @@ copes[i] = list(con_images) ess[i] = list(ess_images) print(copes) - -#%% Smoothing the specific contrast we want (v[3] meaning the 4th contrast) + +# %% Smoothing the specific contrast we want (v[3] meaning the 4th contrast) smooth_copes = [] for k,v in copes.items(): @@ -59,15 +60,15 @@ display_mode='lyrz', colorbar=True, plot_abs=False) - -#%% plotting the smoothed contrasts + +# %% plotting the smoothed contrasts nilearn.plotting.plot_glass_brain(nilearn.image.mean_img(smooth_copes), display_mode='lyrz', colorbar=True, plot_abs=False) -#%% Grabing brain mask for analysis -brainmasks = glob.glob('/media/Data/KPE_fmriPrep_preproc/kpeOutput/derivatives/fmriprep/sub-*/ses-1/func/sub-*_ses-1_task-Memory_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz') +# %% Grabing brain mask for analysis +brainmasks = glob.glob('/media/Data/KPE_BIDS/derivatives/fmriprep/sub-*/ses-1/func/sub-*_ses-1_task-Memory_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz') print(brainmasks) %matplotlib inline for mask in brainmasks: @@ -79,14 +80,14 @@ nilearn.plotting.plot_roi(group_mask) -#%% Creating concatenated contrast (across subjects) and group mask +# %% Creating concatenated contrast (across subjects) and group mask copes_concat = nilearn.image.concat_imgs(smooth_copes, auto_resample=True) copes_concat.to_filename("/media/Data/work/KPE_SPM/fslRandomize/TraumaVsSad_cope.nii.gz") group_mask = nilearn.image.resample_to_img(group_mask, copes_concat, interpolation='nearest') group_mask.to_filename(os.path.join("/media/Data/work/KPE_SPM/fslRandomize", "group_mask.nii.gz")) -#%% Running randomization +# %% Running randomization from nipype.interfaces import fsl import nipype.pipeline.engine as pe # pypeline engine randomize = pe.Node(interface = fsl.Randomise(), base_dir = '/media/Data/work/KPE_SPM/fslRandomize', @@ -100,13 +101,13 @@ #randomize.inputs.var_smooth = 5 randomize.run() -#%% Graph it +# %% Graph it fig = nilearn.plotting.plot_stat_map('/media/Data/work/KPE_SPM/fslRandomize/randomize/randomise_tstat1.nii.gz', alpha=0.7 , cut_coords=(0, 45, -7)) fig.add_contours('/media/Data/work/custom_modelling_spm/randomize/randomise_tfce_corrp_tstat1.nii.gz', levels=[0.99], colors='w') -#%% opposite image run +# %% opposite image run fig = nilearn.plotting.plot_stat_map('/media/Data/work/custom_modelling_spm/neg/randomize/randomise_tstat1.nii.gz', alpha=0.7 , cut_coords=(0, 45, -7)) fig.add_contours('/media/Data/work/custom_modelling_spm/neg/randomize/randomise_tfce_corrp_tstat1.nii.gz', levels=[0.95], colors='w') -#%% +# %% from nipype.caching import Memory datadir = "/media/Data/work/" mem = Memory(base_dir='/media/Data/work/custom_modelling_spm') @@ -119,12 +120,12 @@ num_perm=500) randomise_results.outputs -#%% Look at results +# %% Look at results fig = nilearn.plotting.plot_stat_map(randomise_results.outputs.tstat_files[0], alpha=0.7)# , cut_coords=(-20, -80, 18)) fig.add_contours(randomise_results.outputs.t_corrected_p_files[0], levels=[0.95], colors='w') -#%% F contrasts +# %% F contrasts smooth_es = [] for k,v in ess.items(): smooth_ess = nilearn.image.smooth_img(v[0], 8) @@ -134,26 +135,26 @@ display_mode='lyrz', colorbar=True, plot_abs=False) - -#%% plotting the smoothed contrasts + +# %% plotting the smoothed contrasts nilearn.plotting.plot_glass_brain(nilearn.image.mean_img(smooth_es), display_mode='lyrz', colorbar=True, plot_abs=False) -#%% +# %% ess_concat = nilearn.image.concat_imgs(smooth_es, auto_resample=True) ess_concat.to_filename("/media/Data/work/custom_modelling_spm/lossTotal.nii.gz") -#%% +# %% randomize.inputs.in_file = '/media/Data/work/custom_modelling_spm/lossTotal.nii.gz' randomize.inputs.f_only = True fig = nilearn.plotting.plot_stat_map('/media/Data/work/custom_modelling_spm/randomize/randomise_tstat1.nii.gz', alpha=0.7, cut_coords=(-20, -80, 18)) fig.add_contours('/media/Data/work/custom_modelling_spm/randomize/randomise_tfce_corrp_tstat1.nii.gz', levels=[0.95], colors='w') -#%% Fliping to see the negative +# %% Fliping to see the negative from nipype.interfaces.fsl import MultiImageMaths maths = MultiImageMaths() maths.inputs.in_file = "/media/Data/work/custom_modelling_spm/GainRisk_cope.nii.gz" -maths.inputs.op_string = "-add %s -mul -1 -div %s" +maths.inputs.op_string = "-add %s -mul -1" !fslmaths "/media/Data/work/custom_modelling_spm/negGainRisk_cope.nii.gz" -mul -1 "/media/Data/work/custom_modelling_spm/oppnegGainRisk_cope.nii.gz"