Iteration_analysis_A.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SDK version: 1.0.45\n",
      "Turning diagnostics collection on. \n",
      "Workspace configuration succeeded.\n"
     ]
    }
   ],
   "source": [
    "import azureml.core\n",
    "import logging\n",
    "\n",
    "print(\"SDK version:\", azureml.core.VERSION)\n",
    "\n",
    "from azureml.telemetry import set_diagnostics_collection\n",
    "set_diagnostics_collection(send_diagnostics=True)\n",
    "\n",
    "import os\n",
    "subscription_id = os.getenv(\"SUBSCRIPTION_ID\", default=\"52f3cf55-fed4-4f7e-9aca-f3da535a03c1\")\n",
    "resource_group = os.getenv(\"RESOURCE_GROUP\", default=\"automl_rg\")\n",
    "workspace_name = os.getenv(\"WORKSPACE_NAME\", default=\"automl_ws\")\n",
    "workspace_region = os.getenv(\"WORKSPACE_REGION\", default=\"eastus2\")\n",
    "\n",
    "\n",
    "from azureml.core import Workspace\n",
    "from azureml.core.authentication import InteractiveLoginAuthentication\n",
    "\n",
    "try:\n",
    "    interactive_auth = InteractiveLoginAuthentication(tenant_id=\"1591aa04-9c2a-4144-9a04-fb8b0d506de5\")\n",
    "    ws = Workspace(subscription_id = subscription_id, \n",
    "               resource_group = resource_group, \n",
    "               workspace_name = workspace_name,\n",
    "               auth=interactive_auth)    # write the details of the workspace to a configuration file to the notebook library\n",
    "    ws.write_config()\n",
    "    print(\"Workspace configuration succeeded.\")\n",
    "except:\n",
    "    print(\"Workspace not accessible.\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset_exp = {\"defect_camel_1_2\":\"AutoML_29aecac8-d329-4ead-85e9-55db459752a2\"\n",
    ",\"defect_eclipse_2_0\":\"AutoML_b89e58d1-6878-49b4-9c20-93c9b96cb05b\"\n",
    ",\"defect_eclipse_3_0\":\"AutoML_d551db36-cd0d-4c80-8931-7c3912d47cb2\"\n",
    ",\"defect_prop_2\":\"AutoML_5072b529-0b82-4718-9e82-343bd6bf8aac\"\n",
    ",\"defect_xalan_2_6\":\"AutoML_561e7b85-1240-4bcc-aff3-5c674497ae0a\"}\n",
    "\n",
    "exp_runid = {\"defect_camel_1_2\":\"Automl_defect_camel_1_2\"\n",
    ",\"defect_eclipse_2_0\":\"Automl_defect_eclipse_2_0\"\n",
    ",\"defect_eclipse_3_0\":\"Automl_defect_eclipse_3_0\"\n",
    ",\"defect_prop_2\":\"Automl_defect_prop_2\"\n",
    ",\"defect_xalan_2_6\":\"Automl_defect_xalan_2_6\"}\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calProcessTime(remote_run):\n",
    "    from dateutil import parser\n",
    "    delta = parser.parse(remote_run.get_details()['endTimeUtc'])- parser.parse(remote_run.get_details()['startTimeUtc'])\n",
    "    return delta.seconds/3600\n",
    "\n",
    "\n",
    "def calElapseTime(remote_run,initalCreateTime):\n",
    "    from dateutil import parser\n",
    "    delta = parser.parse(remote_run.get_details()['startTimeUtc'])- parser.parse(initalCreateTime)\n",
    "    return delta.seconds/3600"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [],
   "source": [
    "from azureml.widgets import RunDetails\n",
    "from azureml.train.automl.run import AutoMLRun\n",
    "from azureml.core.experiment import Experiment\n",
    "a_allrun_map={}\n",
    "for dataset,exp in exp_runid.items():\n",
    "    experiment=Experiment(ws, exp)\n",
    "    remote_run = AutoMLRun(experiment = experiment, run_id =dataset_exp[dataset])\n",
    "    a_allrun_map[dataset]=remote_run\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Performing interactive authentication. Please follow the instructions on the terminal.\n",
      "To sign in, use a web browser to open the page https://microsoft.com/devicelogin and enter the code EVHLUBHJR to authenticate.\n",
      "Interactive authentication successfully completed.\n",
      "AutoML: defect_camel_1_2\n",
      "\n",
      "AutoML: defect_eclipse_2_0\n",
      "\n",
      "AutoML: defect_eclipse_3_0\n",
      "\n",
      "AutoML: defect_prop_2\n",
      "\n",
      "AutoML: defect_xalan_2_6\n",
      "\n"
     ]
    }
   ],
   "source": [
    "a_performance_tb={}\n",
    "a_all_metrics={}\n",
    "for dataset,remote_run in a_allrun_map.items():\n",
    "    totalProcessTime = round(calProcessTime(remote_run),2)\n",
    "    expCreateTime = remote_run.get_details()['startTimeUtc']\n",
    "\n",
    "    children = list(remote_run.get_children())\n",
    "    a_metrics = {}\n",
    "    for run in children:\n",
    "        if run.status=='Running':\n",
    "            continue\n",
    "        prop    =  run.get_properties()\n",
    "        iterationNum = int(prop['iteration'])\n",
    "        if iterationNum > 100: iterationNum = 200 - iterationNum\n",
    "        #print(iterationNum)\n",
    "        algo = prop['run_algorithm']\n",
    "        auc_w = prop['score']\n",
    "        durationT = calProcessTime(run)\n",
    "        PriorElapseTime = calElapseTime(run,expCreateTime)\n",
    "        a_metrics[iterationNum] = {'Algorithm':algo,'AUC_weighted':str(round(float(auc_w),6))\n",
    "                                   ,'Iteration':iterationNum\n",
    "                                   ,'TrainTime':str(round(durationT,3))\n",
    "                                   ,'PriorElapseTime':str(round(PriorElapseTime,3))\n",
    "                                  }\n",
    "   \n",
    "    sorted_performance_index =sorted(a_metrics, key =  lambda kv:a_metrics[kv]['AUC_weighted'],reverse=True)\n",
    "    top3 = sorted_performance_index[0:3]\n",
    "    a_all_metrics[dataset]=a_metrics\n",
    "    import pandas as pd\n",
    "    tb = []\n",
    "    for index in top3:\n",
    "        row = a_metrics[index]\n",
    "        #row['Iteration']=index\n",
    "        tb.append(row)\n",
    "\n",
    "    df = pd.DataFrame(tb, index = ['Rank 1','Rank 2','Rank 3'])\n",
    "    #df.columns=['Iteration', 'Algorithm','AUC_weighted','TrainTime','PriorElapseTime']\n",
    "    a_performance_tb[dataset]=df\n",
    "    print('AutoML: '+dataset+'\\n')\n",
    "    #print(df)\n",
    "    #print('\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AutoML: defect_camel_1_2\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AUC_weighted</th>\n",
       "      <th>Algorithm</th>\n",
       "      <th>Iteration</th>\n",
       "      <th>PriorElapseTime</th>\n",
       "      <th>TrainTime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Rank 1</th>\n",
       "      <td>0.630715</td>\n",
       "      <td>ExtremeRandomTrees</td>\n",
       "      <td>29</td>\n",
       "      <td>0.242</td>\n",
       "      <td>0.016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rank 2</th>\n",
       "      <td>0.629801</td>\n",
       "      <td>ExtremeRandomTrees</td>\n",
       "      <td>20</td>\n",
       "      <td>0.121</td>\n",
       "      <td>0.045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rank 3</th>\n",
       "      <td>0.629184</td>\n",
       "      <td>ExtremeRandomTrees</td>\n",
       "      <td>30</td>\n",
       "      <td>0.261</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       AUC_weighted           Algorithm  Iteration PriorElapseTime TrainTime\n",
       "Rank 1     0.630715  ExtremeRandomTrees         29           0.242     0.016\n",
       "Rank 2     0.629801  ExtremeRandomTrees         20           0.121     0.045\n",
       "Rank 3     0.629184  ExtremeRandomTrees         30           0.261      0.01"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "AutoML: defect_eclipse_2_0\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AUC_weighted</th>\n",
       "      <th>Algorithm</th>\n",
       "      <th>Iteration</th>\n",
       "      <th>PriorElapseTime</th>\n",
       "      <th>TrainTime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Rank 1</th>\n",
       "      <td>0.83084</td>\n",
       "      <td>LightGBM</td>\n",
       "      <td>31</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rank 2</th>\n",
       "      <td>0.830132</td>\n",
       "      <td>LightGBM</td>\n",
       "      <td>85</td>\n",
       "      <td>1.779</td>\n",
       "      <td>0.005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rank 3</th>\n",
       "      <td>0.829923</td>\n",
       "      <td>ExtremeRandomTrees</td>\n",
       "      <td>32</td>\n",
       "      <td>0.475</td>\n",
       "      <td>0.015</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       AUC_weighted           Algorithm  Iteration PriorElapseTime TrainTime\n",
       "Rank 1      0.83084            LightGBM         31            0.45     0.019\n",
       "Rank 2     0.830132            LightGBM         85           1.779     0.005\n",
       "Rank 3     0.829923  ExtremeRandomTrees         32           0.475     0.015"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "AutoML: defect_eclipse_3_0\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AUC_weighted</th>\n",
       "      <th>Algorithm</th>\n",
       "      <th>Iteration</th>\n",
       "      <th>PriorElapseTime</th>\n",
       "      <th>TrainTime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Rank 1</th>\n",
       "      <td>0.808516</td>\n",
       "      <td>LightGBM</td>\n",
       "      <td>61</td>\n",
       "      <td>1.55</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rank 2</th>\n",
       "      <td>0.808213</td>\n",
       "      <td>LightGBM</td>\n",
       "      <td>68</td>\n",
       "      <td>1.703</td>\n",
       "      <td>0.006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rank 3</th>\n",
       "      <td>0.808095</td>\n",
       "      <td>GradientBoosting</td>\n",
       "      <td>28</td>\n",
       "      <td>0.526</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       AUC_weighted         Algorithm  Iteration PriorElapseTime TrainTime\n",
       "Rank 1     0.808516          LightGBM         61            1.55      0.02\n",
       "Rank 2     0.808213          LightGBM         68           1.703     0.006\n",
       "Rank 3     0.808095  GradientBoosting         28           0.526      0.12"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "AutoML: defect_prop_2\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AUC_weighted</th>\n",
       "      <th>Algorithm</th>\n",
       "      <th>Iteration</th>\n",
       "      <th>PriorElapseTime</th>\n",
       "      <th>TrainTime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Rank 1</th>\n",
       "      <td>0.828701</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "      <td>83</td>\n",
       "      <td>5.097</td>\n",
       "      <td>0.059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rank 2</th>\n",
       "      <td>0.827398</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "      <td>63</td>\n",
       "      <td>3.562</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rank 3</th>\n",
       "      <td>0.826727</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "      <td>21</td>\n",
       "      <td>0.699</td>\n",
       "      <td>0.046</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       AUC_weighted          Algorithm  Iteration PriorElapseTime TrainTime\n",
       "Rank 1     0.828701  XGBoostClassifier         83           5.097     0.059\n",
       "Rank 2     0.827398  XGBoostClassifier         63           3.562      0.05\n",
       "Rank 3     0.826727  XGBoostClassifier         21           0.699     0.046"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "AutoML: defect_xalan_2_6\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AUC_weighted</th>\n",
       "      <th>Algorithm</th>\n",
       "      <th>Iteration</th>\n",
       "      <th>PriorElapseTime</th>\n",
       "      <th>TrainTime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Rank 1</th>\n",
       "      <td>0.828889</td>\n",
       "      <td>RandomForest</td>\n",
       "      <td>80</td>\n",
       "      <td>0.794</td>\n",
       "      <td>0.025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rank 2</th>\n",
       "      <td>0.828358</td>\n",
       "      <td>RandomForest</td>\n",
       "      <td>64</td>\n",
       "      <td>0.564</td>\n",
       "      <td>0.007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rank 3</th>\n",
       "      <td>0.823589</td>\n",
       "      <td>ExtremeRandomTrees</td>\n",
       "      <td>21</td>\n",
       "      <td>0.128</td>\n",
       "      <td>0.018</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       AUC_weighted           Algorithm  Iteration PriorElapseTime TrainTime\n",
       "Rank 1     0.828889        RandomForest         80           0.794     0.025\n",
       "Rank 2     0.828358        RandomForest         64           0.564     0.007\n",
       "Rank 3     0.823589  ExtremeRandomTrees         21           0.128     0.018"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from IPython.display import display, HTML\n",
    "for dataset in a_performance_tb.keys():\n",
    "    df=a_performance_tb[dataset]\n",
    "    print('AutoML: '+dataset)\n",
    "    #print(df)\n",
    "    display(df)\n",
    "    print('\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [],
   "source": [
    "def extractElapseTime(iteration,all_metrics):\n",
    "    return float(all_metrics[iteration]['TrainTime'])+float(all_metrics[iteration]['PriorElapseTime'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Dataset</th>\n",
       "      <th>1st</th>\n",
       "      <th>10th</th>\n",
       "      <th>20th</th>\n",
       "      <th>50th</th>\n",
       "      <th>100th</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>camel_1_2</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.12</td>\n",
       "      <td>0.50</td>\n",
       "      <td>1.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>eclipse_2_0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.11</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.93</td>\n",
       "      <td>2.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>eclipse_3_0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.33</td>\n",
       "      <td>1.23</td>\n",
       "      <td>2.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>prop_2</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.45</td>\n",
       "      <td>2.70</td>\n",
       "      <td>6.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>xalan_2_6</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.12</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from IPython.display import display, HTML\n",
    "import pandas as pd\n",
    "tb = []\n",
    "for dataset in a_all_metrics.keys():\n",
    "    all_metrics = a_all_metrics[dataset]\n",
    "    printed_row = {}\n",
    "    printed_row['Dataset']=dataset.split('defect_')[1]\n",
    "    printed_row['1st'] = extractElapseTime(1,all_metrics)\n",
    "    printed_row['5th'] = extractElapseTime(4,all_metrics)\n",
    "    printed_row['10th'] = extractElapseTime(9,all_metrics)\n",
    "    printed_row['20th'] = extractElapseTime(19,all_metrics)    \n",
    "    printed_row['50th'] = extractElapseTime(49,all_metrics)    \n",
    "    printed_row['100th'] = extractElapseTime(99,all_metrics)        \n",
    "    #row['Iteration']=index\n",
    "    tb.append(printed_row)\n",
    "\n",
    "df = pd.DataFrame(tb)\n",
    "\n",
    "df=df[['Dataset','1st','10th','20th','50th','100th']]\n",
    "display(HTML(df.to_html(index=False)))\n",
    "print('\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 522,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Iteration</th>\n",
       "      <th>Elapse Time</th>\n",
       "      <th>AUC_weighted</th>\n",
       "      <th>Algorithm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>81</td>\n",
       "      <td>47.60</td>\n",
       "      <td>0.828889</td>\n",
       "      <td>RandomForest</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>65</td>\n",
       "      <td>33.80</td>\n",
       "      <td>0.828358</td>\n",
       "      <td>RandomForest</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>22</td>\n",
       "      <td>7.70</td>\n",
       "      <td>0.823589</td>\n",
       "      <td>ExtremeRandomTrees</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>96</td>\n",
       "      <td>55.10</td>\n",
       "      <td>0.822766</td>\n",
       "      <td>RandomForest</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>9</td>\n",
       "      <td>2.50</td>\n",
       "      <td>0.822709</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>91</td>\n",
       "      <td>52.70</td>\n",
       "      <td>0.822017</td>\n",
       "      <td>RandomForest</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>6</td>\n",
       "      <td>1.60</td>\n",
       "      <td>0.821542</td>\n",
       "      <td>RandomForest</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>98</td>\n",
       "      <td>55.90</td>\n",
       "      <td>0.820978</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>66</td>\n",
       "      <td>34.40</td>\n",
       "      <td>0.820644</td>\n",
       "      <td>RandomForest</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>46</td>\n",
       "      <td>20.90</td>\n",
       "      <td>0.820382</td>\n",
       "      <td>ExtremeRandomTrees</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100</td>\n",
       "      <td>59.20</td>\n",
       "      <td>0.819981</td>\n",
       "      <td>LightGBM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>31</td>\n",
       "      <td>12.00</td>\n",
       "      <td>0.819716</td>\n",
       "      <td>ExtremeRandomTrees</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>97</td>\n",
       "      <td>55.60</td>\n",
       "      <td>0.819512</td>\n",
       "      <td>LightGBM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>38</td>\n",
       "      <td>15.70</td>\n",
       "      <td>0.819021</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>83</td>\n",
       "      <td>49.70</td>\n",
       "      <td>0.818978</td>\n",
       "      <td>LightGBM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>43</td>\n",
       "      <td>18.80</td>\n",
       "      <td>0.818722</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>95</td>\n",
       "      <td>54.70</td>\n",
       "      <td>0.8186</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>2</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.818511</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>58</td>\n",
       "      <td>29.20</td>\n",
       "      <td>0.818438</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>99</td>\n",
       "      <td>56.30</td>\n",
       "      <td>0.818372</td>\n",
       "      <td>ExtremeRandomTrees</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>20</td>\n",
       "      <td>6.10</td>\n",
       "      <td>0.81814</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>67</td>\n",
       "      <td>36.60</td>\n",
       "      <td>0.818075</td>\n",
       "      <td>GradientBoosting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>89</td>\n",
       "      <td>52.00</td>\n",
       "      <td>0.818062</td>\n",
       "      <td>LightGBM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>87</td>\n",
       "      <td>51.20</td>\n",
       "      <td>0.818026</td>\n",
       "      <td>LightGBM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>40</td>\n",
       "      <td>16.70</td>\n",
       "      <td>0.817895</td>\n",
       "      <td>LightGBM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>39</td>\n",
       "      <td>16.10</td>\n",
       "      <td>0.817818</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>92</td>\n",
       "      <td>53.50</td>\n",
       "      <td>0.81772</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>60</td>\n",
       "      <td>30.20</td>\n",
       "      <td>0.817421</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>29</td>\n",
       "      <td>11.20</td>\n",
       "      <td>0.817207</td>\n",
       "      <td>LightGBM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>79</td>\n",
       "      <td>47.00</td>\n",
       "      <td>0.817075</td>\n",
       "      <td>LightGBM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>56</td>\n",
       "      <td>26.80</td>\n",
       "      <td>0.80734</td>\n",
       "      <td>ExtremeRandomTrees</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>5</td>\n",
       "      <td>1.30</td>\n",
       "      <td>0.806719</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>14</td>\n",
       "      <td>4.10</td>\n",
       "      <td>0.806406</td>\n",
       "      <td>ExtremeRandomTrees</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>23</td>\n",
       "      <td>8.80</td>\n",
       "      <td>0.806263</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>36</td>\n",
       "      <td>15.00</td>\n",
       "      <td>0.806201</td>\n",
       "      <td>ExtremeRandomTrees</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>72</td>\n",
       "      <td>41.30</td>\n",
       "      <td>0.806192</td>\n",
       "      <td>LightGBM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>11</td>\n",
       "      <td>3.20</td>\n",
       "      <td>0.805219</td>\n",
       "      <td>LightGBM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>28</td>\n",
       "      <td>10.90</td>\n",
       "      <td>0.80501</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>52</td>\n",
       "      <td>25.00</td>\n",
       "      <td>0.804497</td>\n",
       "      <td>LightGBM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>77</td>\n",
       "      <td>46.00</td>\n",
       "      <td>0.804021</td>\n",
       "      <td>LightGBM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>85</td>\n",
       "      <td>50.50</td>\n",
       "      <td>0.803964</td>\n",
       "      <td>LightGBM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>21</td>\n",
       "      <td>7.20</td>\n",
       "      <td>0.80304</td>\n",
       "      <td>XGBoostClassifier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>55</td>\n",
       "      <td>26.30</td>\n",
       "      <td>0.802056</td>\n",
       "      <td>LightGBM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>17</td>\n",
       "      <td>5.10</td>\n",
       "      <td>0.801215</td>\n",
       "      <td>LightGBM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>61</td>\n",
       "      <td>30.60</td>\n",
       "      <td>0.797691</td>\n",
       "      <td>ExtremeRandomTrees</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>15</td>\n",
       "      <td>4.40</td>\n",
       "      <td>0.79687</td>\n",
       "      <td>ExtremeRandomTrees</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>76</td>\n",
       "      <td>43.40</td>\n",
       "      <td>0.795574</td>\n",
       "      <td>RandomForest</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>27</td>\n",
       "      <td>10.50</td>\n",
       "      <td>0.774625</td>\n",
       "      <td>LogisticRegression</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>41</td>\n",
       "      <td>17.10</td>\n",
       "      <td>0.773679</td>\n",
       "      <td>ExtremeRandomTrees</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>19</td>\n",
       "      <td>5.70</td>\n",
       "      <td>0.769618</td>\n",
       "      <td>LogisticRegression</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>8</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0.768577</td>\n",
       "      <td>SGD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>3</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.7658</td>\n",
       "      <td>SGD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>7</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.760412</td>\n",
       "      <td>SGD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>88</td>\n",
       "      <td>51.60</td>\n",
       "      <td>0.756871</td>\n",
       "      <td>LogisticRegression</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>12</td>\n",
       "      <td>3.50</td>\n",
       "      <td>0.749617</td>\n",
       "      <td>BernoulliNaiveBayes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>47</td>\n",
       "      <td>22.70</td>\n",
       "      <td>0.731902</td>\n",
       "      <td>LogisticRegression</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>16</td>\n",
       "      <td>4.80</td>\n",
       "      <td>0.729913</td>\n",
       "      <td>SGD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>18</td>\n",
       "      <td>5.40</td>\n",
       "      <td>0.718442</td>\n",
       "      <td>BernoulliNaiveBayes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>26</td>\n",
       "      <td>10.20</td>\n",
       "      <td>0.53137</td>\n",
       "      <td>ExtremeRandomTrees</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>86</td>\n",
       "      <td>50.80</td>\n",
       "      <td>0.5</td>\n",
       "      <td>RandomForest</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Iteration  Elapse Time AUC_weighted            Algorithm\n",
       "19         81        47.60     0.828889         RandomForest\n",
       "35         65        33.80     0.828358         RandomForest\n",
       "78         22         7.70     0.823589   ExtremeRandomTrees\n",
       "4          96        55.10     0.822766         RandomForest\n",
       "91          9         2.50     0.822709    XGBoostClassifier\n",
       "9          91        52.70     0.822017         RandomForest\n",
       "94          6         1.60     0.821542         RandomForest\n",
       "2          98        55.90     0.820978    XGBoostClassifier\n",
       "34         66        34.40     0.820644         RandomForest\n",
       "54         46        20.90     0.820382   ExtremeRandomTrees\n",
       "0         100        59.20     0.819981             LightGBM\n",
       "69         31        12.00     0.819716   ExtremeRandomTrees\n",
       "3          97        55.60     0.819512             LightGBM\n",
       "62         38        15.70     0.819021    XGBoostClassifier\n",
       "17         83        49.70     0.818978             LightGBM\n",
       "57         43        18.80     0.818722    XGBoostClassifier\n",
       "5          95        54.70       0.8186    XGBoostClassifier\n",
       "98          2         0.40     0.818511    XGBoostClassifier\n",
       "42         58        29.20     0.818438    XGBoostClassifier\n",
       "1          99        56.30     0.818372   ExtremeRandomTrees\n",
       "80         20         6.10      0.81814    XGBoostClassifier\n",
       "33         67        36.60     0.818075     GradientBoosting\n",
       "11         89        52.00     0.818062             LightGBM\n",
       "13         87        51.20     0.818026             LightGBM\n",
       "60         40        16.70     0.817895             LightGBM\n",
       "61         39        16.10     0.817818    XGBoostClassifier\n",
       "8          92        53.50      0.81772    XGBoostClassifier\n",
       "40         60        30.20     0.817421    XGBoostClassifier\n",
       "71         29        11.20     0.817207             LightGBM\n",
       "21         79        47.00     0.817075             LightGBM\n",
       "..        ...          ...          ...                  ...\n",
       "44         56        26.80      0.80734   ExtremeRandomTrees\n",
       "95          5         1.30     0.806719    XGBoostClassifier\n",
       "86         14         4.10     0.806406   ExtremeRandomTrees\n",
       "77         23         8.80     0.806263    XGBoostClassifier\n",
       "64         36        15.00     0.806201   ExtremeRandomTrees\n",
       "28         72        41.30     0.806192             LightGBM\n",
       "89         11         3.20     0.805219             LightGBM\n",
       "72         28        10.90      0.80501    XGBoostClassifier\n",
       "48         52        25.00     0.804497             LightGBM\n",
       "23         77        46.00     0.804021             LightGBM\n",
       "15         85        50.50     0.803964             LightGBM\n",
       "79         21         7.20      0.80304    XGBoostClassifier\n",
       "45         55        26.30     0.802056             LightGBM\n",
       "83         17         5.10     0.801215             LightGBM\n",
       "39         61        30.60     0.797691   ExtremeRandomTrees\n",
       "85         15         4.40      0.79687   ExtremeRandomTrees\n",
       "24         76        43.40     0.795574         RandomForest\n",
       "73         27        10.50     0.774625   LogisticRegression\n",
       "59         41        17.10     0.773679   ExtremeRandomTrees\n",
       "81         19         5.70     0.769618   LogisticRegression\n",
       "92          8         2.20     0.768577                  SGD\n",
       "97          3         0.70       0.7658                  SGD\n",
       "93          7         1.90     0.760412                  SGD\n",
       "12         88        51.60     0.756871   LogisticRegression\n",
       "88         12         3.50     0.749617  BernoulliNaiveBayes\n",
       "53         47        22.70     0.731902   LogisticRegression\n",
       "84         16         4.80     0.729913                  SGD\n",
       "82         18         5.40     0.718442  BernoulliNaiveBayes\n",
       "74         26        10.20      0.53137   ExtremeRandomTrees\n",
       "14         86        50.80          0.5         RandomForest\n",
       "\n",
       "[100 rows x 4 columns]"
      ]
     },
     "execution_count": 522,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values('AUC_weighted',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 529,
   "metadata": {},
   "outputs": [],
   "source": [
    "    df_perf_max = df.sort_values('AUC_weighted',ascending=False).iloc[0] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 517,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_metrics = a_all_metrics[dataset]\n",
    "df=pd.DataFrame({\n",
    "    'Iteration':[x+1 for x in list(all_metrics.keys())],\n",
    "    'Elapse Time':[ round(float(x['PriorElapseTime'])*60,1) for x in all_metrics.values()],\n",
    "    'AUC_weighted':[ x['AUC_weighted'] for x in all_metrics.values()],\n",
    "    'Algorithm': [ x['Algorithm'] for x in all_metrics.values()]\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 544,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  0.,  50., 100., 150., 200., 250., 300., 350., 400.]),\n",
       " <a list of 9 Text yticklabel objects>)"
      ]
     },
     "execution_count": 544,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "fig1, ax1 = plt.subplots()\n",
    "ax1.set_title('AutoML',fontsize = 29)\n",
    "plt.rcParams[\"figure.figsize\"] = (10, 5)\n",
    "\n",
    "axes = plt.gca()\n",
    "axes.set_ylim([0,370])\n",
    "colorlist = ['blue','r','g','purple','c']\n",
    "color_idx=0\n",
    "for dataset in a_all_metrics.keys():\n",
    "    all_metrics = a_all_metrics[dataset]\n",
    "    df=pd.DataFrame({\n",
    "        'Iteration':[x+1 for x in list(all_metrics.keys())],\n",
    "        'Elapse Time':[ round(float(x['PriorElapseTime'])*60,1) for x in all_metrics.values()],\n",
    "        'AUC_weighted':[ str(x['AUC_weighted']) for x in all_metrics.values()],\n",
    "        'Algorithm': [ x['Algorithm'] for x in all_metrics.values()]\n",
    "    })\n",
    "    df_perf_max = df.sort_values('AUC_weighted',ascending=False).iloc[0] \n",
    "    plt.plot( 'Iteration', 'Elapse Time', data=df, \n",
    "             #marker='o', markerfacecolor='blue', markersize=12, color='skyblue', \n",
    "             color = colorlist[color_idx],\n",
    "             label = dataset.split('defect_')[1],\n",
    "             linewidth=2)\n",
    "    \n",
    "    plt.scatter ( 'Iteration', 'Elapse Time', data=df_perf_max, \n",
    "             marker='>',  s=300,\n",
    "                 #markerfacecolor='blue', color='skyblue', \n",
    "             color = colorlist[color_idx],\n",
    "             label = '')\n",
    "\n",
    "    best_performance = float(df_perf_max['AUC_weighted'])\n",
    "    df['AUC percentage'] = [ float(x)/float(best_performance) for x in df['AUC_weighted']]\n",
    "    df_perf_morethan_099 = df.loc[df['AUC percentage']>=0.99].sort_values('Iteration',ascending=True).iloc[0]\n",
    "\n",
    "    plt.scatter ( 'Iteration', 'Elapse Time', data=df_perf_morethan_099, \n",
    "             marker='o',  s=300,\n",
    "                 #markerfacecolor='blue', color='skyblue', \n",
    "             color = colorlist[color_idx],\n",
    "             label = '')\n",
    "    color_idx= color_idx+1\n",
    "    \n",
    "plt.legend(loc='center left', bbox_to_anchor=(1, 0.5),prop={'size': 20})\n",
    "xlabel ('Iteration',fontsize = 29)\n",
    "ylabel ('Elapse time (minutes)',fontsize = 20)\n",
    "\n",
    "#plt.axhline(y=threshold, color='r', linestyle='-.')\n",
    "for vx in range(0,101,10):\n",
    "    plt.axvline(x=vx,linestyle='-.')\n",
    "        \n",
    "plt.xticks(range(0,101,10),fontsize = 25)\n",
    "plt.yticks(fontsize = 20)\n",
    "#plt.axhline(y=threshold, color='r', linestyle='-.')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculateImprovement(iteration,all_metrics,bestPerformance):\n",
    "    # return the absolute performance improvement\n",
    "    return float(all_metrics[iteration]['AUC_weighted'])/bestPerformance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Dataset</th>\n",
       "      <th>1st</th>\n",
       "      <th>10th</th>\n",
       "      <th>20th</th>\n",
       "      <th>50th</th>\n",
       "      <th>100th</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>camel_1_2</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>eclipse_2_0</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>eclipse_3_0</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>prop_2</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>xalan_2_6</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from IPython.display import display, HTML\n",
    "import pandas as pd\n",
    "tb = []\n",
    "for dataset in a_all_metrics.keys():\n",
    "    all_metrics = a_all_metrics[dataset]\n",
    "    bestPerformance=float(a_performance_tb[dataset]['AUC_weighted'][0])\n",
    "\n",
    "    printed_row = {}\n",
    "    printed_row['Dataset']=dataset.split('defect_')[1]\n",
    "    printed_row['1st'] =  calculateImprovement(1,all_metrics,bestPerformance)\n",
    "    printed_row['5th'] =  calculateImprovement(4,all_metrics,bestPerformance)\n",
    "    printed_row['10th'] = calculateImprovement(9,all_metrics,bestPerformance)\n",
    "    printed_row['20th'] = calculateImprovement(19,all_metrics,bestPerformance)    \n",
    "    printed_row['50th'] = calculateImprovement(49,all_metrics,bestPerformance)    \n",
    "    printed_row['100th']= calculateImprovement(99,all_metrics,bestPerformance)        \n",
    "    #row['Iteration']=index\n",
    "    tb.append(printed_row)\n",
    "\n",
    "df = pd.DataFrame(tb)\n",
    "\n",
    "df=df[['Dataset','1st','10th','20th','50th','100th']]\n",
    "display(HTML(df.to_html(index=False)))\n",
    "print('\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Dataset</th>\n",
       "      <td>camel_1_2</td>\n",
       "      <td>eclipse_2_0</td>\n",
       "      <td>eclipse_3_0</td>\n",
       "      <td>prop_2</td>\n",
       "      <td>xalan_2_6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1st</th>\n",
       "      <td>0.94</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10th</th>\n",
       "      <td>0.91</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20th</th>\n",
       "      <td>0.94</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50th</th>\n",
       "      <td>0.95</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100th</th>\n",
       "      <td>0.96</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(HTML(df.T.to_html()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "camel_1_2\n",
      "0.9366639448879446\n",
      "0.91164947718066\n",
      "0.9373330268029141\n",
      "0.9515676652687822\n",
      "0.9610204291954368\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 180x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcAAAAB7CAYAAADjX1BxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+17YcXAAAacklEQVR4nO2deZwdRbXHvyeQsIhsBgmrAYIIGA0QwiY4T4yiwOMJeYCAOMagwtPHUyOiCCIuyEcQWRRBgRExgguboAKigwIBDOBKWFQCIRAIGCCBELbz/jh1mZ6e7rtMZuZm0r/v59Ofe7uquup0dVWd2svcHSGEEKJqjGi3AEIIIUQ7kAIUQghRSaQAhRBCVBIpQCGEEJVEClAIIUQlkQIUQghRSVY4BWhmi82sM3PvZjZlEMLpNLPFmfsTzexvAx1Oxv9BeY9+yDHCzM41syeTTB3tlqkd9Od7m1m3mZ09WDIVhHe1mXUNVXh15BjS916RyJczTT7TZWZXD5ZMBeGdbWbdTbpdrtJC0wrQzLY3s5fN7OYSe0/X7jnzlcxsXr4AN7M5Zja9/6I3zQbAL5px2OLHuRTYvN9SlctQlnibfo9B5r3Ah4B9CZluqefYzK5K6WZygV3hu5pZR0ovozNmo8zsM2Z2l5k9Z2b/NrNbzeyjZrbKsr9Wy5wKvH2gPR3CfJEPd38zu9bMFpRVbMxsFTM7y8yeMLNn07fdOGPf57sNgFw7p/BWauDuzJTOjiiwK6ysmNnYJO/EjJmZ2TQzm2lmi8zsGTO708yOMbM1B+atWmKwypnlShENJK3koVZagNOA7wBvNrOtS9zMBabmzN4DvNRCOAOKu89396UD6aeZjXT3Je7++ED6W4/BeI9+Mg541N1vSTK9UObQzDYA9gROJ9JPvzCzUcC1wHHAhcBuwA7ANwllvEt//e4v7r7Y3Z8c6nAHkdcQlZlP1XHzLeAA4P3A7sCawNWNlNMysh9wtbu/XOYgVYAOBb7OMqSzxA+Bs4BfEmn3LcDxwH8A+y+j3y0z1OVM5XD3hhewGvAUMB44Hzi1wI0DJwGLgTUy5pcDX0r2UzLmc4DpzYRfR65xQDfwPHAvsE8KvzMnVzbcE4AHgaXAfOCiZN6V3GavsUBH+v9e4HbghRROJ7A44++JwN+IDPgQsAS4AhidcdNFZGbyz2X+52XoKHmP8cBvUjj/Tn6vlQ8LOBqYBywklMfqDeJ0D+C2FKePEcprVEkczWng1+eAnwNvSHK+LmffJz6SeS3OR6f7Y4BXgIkFbkcAazaQYy9gEbByJt048N2Mm68Av8ncbwNck557HPgxMKbou6X7lVNcLUzX6cA5QHfGTTdRifwa8ETy91RgRMa+1/fPPLsrcCPwXPqe52TfG1g9xefi9N0+n75/V4t5anQ23WXM1yLS/qEZs03Sd3k3kVfyabermfduIM/dwPsauHk/cEeKg0XAm8vyWM68JvPEdH9gut+/JJy1G8jxpvT8mMw3WQr8OuNmGvCPzP1GwCWZdHMNsGXGvpNMOZPJV4+lb30R8EUyeZEGeZ+Ssq7JdL9S+nY1eb9FLp03iKNu4LvAGRk/vpFNC8Ao4BTgYSK9/xF4d8Z+JHAm8EiK37nA1xvloaKr2RbgFOBBd/8rUUM63MxGFrj7CzAbOAjAzF5PtAAvbDKcV0nN2K469iMI5TqCaAFMJRJ6aXeYmR0ATAeOArYkFNntyfpoYGaSdYN0zc08fgrwBSKR31YSxFjgMKLW+s4UxgVl8hRwKvATQrHVZOjTxWhmryFaRIuBScD7iAIyH9buwJuTLAcld0eXBW5mGwG/Au4CtgM+TBQuJycnRxOVnIeTbDvW8cuIb3Kxuz9IxNkHytw34FBCOc3KW7j7K+7+TIPnbwJWBWpdXR1EQdyRcdNBZJ5ay/X3RIVmEhF/awBXpnRXxHSisJoG7Eyky0NK3uUl4nt9HPg/Un4hWhgPE3Fc+/6Y2XjgOuAq4K3J3QR6f+9TgclEC21P4vvtUSJrf9iBKHiuqxm4+1wiv+9K5JUDktW2SfZsWqv33oWY2ZZEnrqunjsizi929+eICld/W4GHAve5+2VFlu7+VL2H3f0eolLdkYx2BZ4BdjOzlZNZBz3pbHXgd0Rl8+1EOfYo8Jtk1wczO5hQeMcB2xPxX9Rqr5f3C8u6JtP9p4EjgI8meVci4q0VDqWn3P4o8BEiPdS4kIiPQ9I7/AD4hZm9Ndn/b3qfg4ky9iCiAQQleaiUFrT29PTfiNbblJwbJxTlkcDNyWw6qVZN3xbMHOq0AIEbgJPr2L8LeBnYNGP2thROZ16u9P9TKaJG1nnPs3NmHcmPA3LmnfRtAZbJs2W2ZlavdlrkpuA9jgCeBl5bIOe4jD9zgZUybr5HppVTEMZXgfvpXRvrJGpZtdrjdBq0/DLyPElP63Eq8Necm7J3rb1LrQX4HHBGM2m1jjy3Ap9L/y8mCpElRAap1dTfluxPAm7IPb9OkmlSyXd7FDg2c28prXVnzLqBmTl/rwe+Xy9fELX883NmE5I8rycKqaX0bp2tQfTadLUYT2UtwEMIBWY5898C5xZ9t1beu0SWzwBXNXCzGdEyrbW63kFUblYpy2MZ87H0bgHeDVy5jOnskkx8fIVoHc0Bdklmc4HDMnni/mycEgrlSeDATP7LljMzyfRcJLPr6NsCrJv3KS7rmkn3jwDHZexHAPfRWgvwvtw7fwF4OP3fguhV2DT33BXAd9L/Mwn9YCVhzKHJ3sWGLUAzG0cU5DMgtSfhR0TroIgZwHZmtlX6wOc3CqMId9/T3T9Xx8nWwDx3fyhjdhsReWX8lGgJPGBm55vZf7cwgaJP66OAMnnKxkz7y9bAX9x9UcbslhTWNhmzu7332MkjRIFZz99b3T0bhzcRXRLjWpRxGvAT7xkj/BmwhZnt1KI/EMpkWemmp2b+dqKle1sy25Uo3Gu9ATsAe1jMKF6cZuHVegO26COc2VrAmMzztXxye94t0UuSpdE3qclzWE6e2mS0LdI1iigca+EvBv7awN+hpD/vvR9wZQM3HyYK7fnpvpuoMP1XqwIy8Omsg2jhdQMdqSzdON1DfNfNgEWZ7/o0oXT6pLPEm+ibrop6pFrN+zV5StN9Sucb0DudvVISfj1uTfmjxkxgozTJaHviO9ydk2NveuKki6gA3mdm3zazvev0zNRl5cZOmEbUSh6KXi1IAmJmm3h0g7yKuz9tZpcR/bxjiG7K5QJ3n5sU855E8/404ItmtpO7P9vg8Ub2zfAKfTNZUVfyspBNWC8W2PV36Ys3dhKY2dpEd9io3Ky8lYj0VMswz1Cc0dcm4qqm4O9j2SsR3cDH0wSuNYkxo25icsPjRAulpqxHEOMgRTPJHltGOfrzTUYA3yfGFfPMA964jDI1w3zi+40GFmTM1wf+0MTzLb13Gj7ZiToTT9Lkm05gQzPLTrQbQaSzS9P9M8QYZp610+/T6Xeg0tk5SdlNTPerEy3oBcA/3f3hjJx/Irry8vx7GeXobzqrl+6HYtncCELWHen7DksA3P1OMxtLjD3vSXSR/tnMJucq700FVkrqt/4gMeg6IXO9lajRfajk0fOJ2s8Md3++FYFaYDZRa9gkYzaJBu/k7s+7+zXu/kkikrclZhVCdKUsy4y2Mnlmp/sF9O2TnpC7b0aG2cB4M3ttxmzXXFj9YTawc6429bYk0z9b8OdQ4l3fSu908xHgoDSGCdFFuI2ZrZZ7fntizLk263UG8M7sdPUaFusSm5mefhMxPnwMcFOqHXcTCrCDnlo5wJ1EunjQ3f+RuxaRw92fJhTEq2OiaQy0dIy0DkXf/05g2wJZ/uHuS4hv8yIx9lgL/zXE+MlAcUcK49XlLGkJxNb0jFPXKhADMSt0X+A2rz8Dci/gdYSiyaazfYA9UyEJkc42SGNcWbZPMj+Q7mcAW5pZodJNFbu6eM844HGEsnucSFu7EXHXnXF+J9Gz8kTBdy1TgPfQN11NaiRXAaXpjJJ0n9L5o/ROZ9aP8HeyTGsq+feIx1j+XUQjYUyBDPNqDyR5fubuRxKtw3fQ00vVfDneoL92PyLRv67A7rNEwrF0nx/jG03vfviiMcBv0jvhTqBn3KfRGOAI4O9EF8MEYkD19iRvZ1G49ExSGE90PRybImuzZH8ekdHHJvlHUD6u0UnfMcDFxJhITZ6/khnjImosTnQNjyMK46foPZb0eaLbYaskw8iC91id6NK4PL3LHkQm/3nGny4ajDcWxOlGREv3u0TBtjeRmU/LuGk4BkhkpG8WmI9K7zs13a9N1Cx/SnS/jCMqVc8AR2aeW4UYnF9IDIBPSN9vf6Lw7agnT8afW1P6qI1nr0rUKl8ijf8l8w2JVuFlRCtkc6LH4DzSuGs+LlNaepIYnN+KSNtPA7/LuOmm77hLr+9EjOdcnb5FLS+8hejW+y4xuWUcUcifm3nunJRuJhOF2KUpHruajJt1U7x2pLQ2Ld2PyYXxcIqL7Yi89yfSWFOS+RUifa9Hmg3ezHsXyHMV8JkGMl8OXFZiNxs4Kf1fmZjY0U0oos2JHopHgFMyzxgxhreEWPqwIzGDeS+iZdRZT56MP5ekdHZ2xmxOMjssY7Y6kW9vJLrlNyPy8mn0zBvopHc5c3CSbyoxAaRWhjzQSt6nuKxrJt1/NoU3hUjnZ6R01t1k3HQTPTtnpOenJP+mZ9xcTMzUn5JkmEiUO/sn+08Rk/O2JvLCGUReq81T6JOHSuVpIOxVwHUldpsTGeVd6b6XgitwX6QAveD6eMa+buYlun5uJCYA3A/8J3WWQRDjAjNThD9LTK/dJ+ffTKKwcXovg2hGAf6NaOXMJRLplcB6BQnx0fTBalPDswlzvfQBF9F4GcQNKZyFlCyDqJcJSuK0tgxiKT3LILIVmboKkKhVO7Brif1FwC25OL+M6MpbTBSo0+g72WIVIvP9OfPOtxKzyEY1mfm+TmbSQyZDPpv3gyhcfpbCWUIUVGfRM6mnV1wShey3UtpaSCjALuBXubAaKcCd0zs+T+9lEBOBXxOFzbNE5eqkjP1rUtwuJgqx42lhGQSRnovy44m5b3AWoeifIzZm2CTnz/FE+n6F3ssgmlaAhGJ4DnhjHXnXJxTKISX2JxH5sLbEZMMU5pzk990pPY3MPWdEHr4txWWtVXIMmUlnDeLyY/TNr13JbOOC97gwfbOlRKPiAnoqP530XQbx+eS+tgzi68DsVvI+BWVdk+m+ttznqXSdRf+WQZxNT145jd4TdkYmef9FNFDmE7poh2R/BFHJXpS+z41kyhtK8lDRVWu9CSEGGDO7i+hu/US7ZRlOmNn7gK+6+zYNHQvM7HJijeu+7ZZluNHMJBghRAPM7A1EF/eNRA32CKLrss/WXKIhzxKtM5EjrQ88kugNeInoyt2PnjWYogXUAhTDHjPblOjSKmMb7708ZTBk2ITYNWM8MZ5yN3C8uzdaxD3oWOzP+6sye3dfYwjFGdZY/Y2p3+PuzcyIXZbwVyO6nrcjdui6nxjHnDGY4TbD8pAPW0UKUAx70mzlsXWczHH3tu1H225SoblRmb27/2MIxRnWpOUNZczzmJVbSYZjPpQCFEIIUUlWuPMAhRBCiGaQAhRiGbHcIcxCiOGBFKBYobE4dNfNrM+etGZ2SrIb9NOzzWy8md1oZkssDog+IbcbRtEz25vZ9Wb2lJk9aWbnmdkaGftO6zmIOn/t2KybXJijrecA6wE72FaI5REpQFEF5gIHZrZgqw3YH06c3TiopK3aric2FtiROI7mM9Q5fNbMNiSOxfoXsSvHXsQOL10ZZ5fSc+RL7bo4PTOrBTdZLiQ2IxBihUcKUFSBvxDTxQ/MmO1N7BTRnXVoZh8ys7vN7Hkzu8/MPpndG9XMxplZd7K/18z2aSL8Q4ndTT7o7n9z958R50t+qk4rcB9iN5Wj3P1ed/8jscPIAbWZiB6nhc+vXcSuGPsSRyd5s24y73Z0kvO0Jt5JiGGPFKCoCucT+yfWmEq0dl5VAunkiq8BJxD7DH6aWJB9VLJv6hDmpCC7M0a7AH/ITZG/ltiea2yJvKsAL3rvI21qz7+t5JkDiS3R6h3CXOjGzLYj3vVw6h8pJsQKgxSgqAozgIlmtqWZjSG6FLtybo4HjvHYZf4Bd/8Fsc/iUcn+ncR5i4e5+13ufjNxknV+R6WH6N21Ooa+xyg9lrEr4rfAaDM71sxGmdk6SRYoP+X6I8QekPNL7AvdpK7hS4BPeGbHfSFWdLQVmqgE7r4w7Zk4ldiEt9vdXz3j0szWAzYBzjWzczKPrkzPGY5NHcLs7ocPgLx/N7MPEptqf5XY9upMQnH2aaGZ2bZES3PvMj/ruDmT2LP058sqtxDDCSlAUSUuIA7PXEx0c2ap9YZ8jJ7z7QaK+cSu/1nWz9gVkra3mmFm6xP7YzoxceZfBc5rp5D8uo4cZW72BDZJChd6FP58MzvF3Y+r46cQwxYpQFElbiCOVxkNXJG1cPfHzOwRYAt3v6jk+VcPYXb3ucms4SHMxLEzp5jZqt5zQPRk4jy6OY2EdvfHAMxsKjFx5/qsvZmtCnwAONNLTsRu4OZdxFmNNXYkKgsdxOQhIVZIpABFZXB3N7O3EFsALi1w8kXgLDN7CvglcarD9sBG7n4ysSzhHuAiM/sksRnx6UT35KuY2UUpvFpX6Izkd5eZfYU4i+1Y4Eu1mZjpCKCTgT1r43Bm9nFCeS4iFOY3gGPd/amc3FOAtag/+aXUjbvfl5O/tv7vHnd/oo6fQgxrpABFpXD3RXXsvm9mzxJr9E4mZl3+nTi8E3d/JSmq7xFjfw8RM0XzO/FvmvP3aTObDHybWHtXOwT0mxlnaxEnZI/MmE0CvgSsQSjej7r7DwtEPwK4tsFO+824EaJSaDNsIYQQlUTLIIQQQlQSKUAhhBCVRApQCCFEJZECFEIIUUk0C1QMGaNHj/axY8e2WwwxDLjjjjuecPf12i2HWLGRAhRDxtixY5k1q+gEHiF6Y2YPtlsGseKjLlAhhBCVRApQCCFEJZECFEIIUUmkAIUQQlQSKUAhhBCVRApQCCFEJZECFEIIUUmkAIUQ/WbdddeFE9fCzEqvddddt91iClGIFsILIfrNwoULgTWpd6yamQ2dQEK0gFqAQgghKokUoBBCiEoiBSiEEKKSSAEKIYSoJFKAQgghKokUoBBCiEoiBSiEEKKSSAEKIdqC1geKdiMFKIQQopJIAQohhKgkUoBCCCEqiRSgEEKISiIFKIQQopJIAQohhKgkUoBCCCEqiRSgEEKISiIFKIQQopJIAYpBxcw+YmazzGzWggUL2i2OaBNm1ucSot1IAYpBxd3Pc/eJ7j5xvfXWa7c4ok24e59LiHYjBSiEEKKSSAEKIYSoJFKAQgghKokUoBBCiEoiBSiEEKKSSAEKIYSoJFKAQgghKokUoBBCiEoiBSiEaAtaDC/ajRSgEEKISiIFKIQQopJIAQohhKgkUoBCCCEqiRSgEEKISiIFKIQQopJIAQohhKgkUoBCCCEqycrtFkAIMfwxs1K7ddZZZwglEaJ5pACFEP2mtpuLn9heOYToD+oCFUIIUUmkAIUQQlQSKUAhhBCVRApQCCFEJZECFEIIUUmkAIUQQlQS06GUYqgws0XAve2Wox+MBp5otxD9ZLjKvpW7v7bdQogVG60DFEPJve4+sd1CtIqZzRqOcsPwld3MZrVbBrHioy5QIYQQlUQKUAghRCWRAhRDyXntFqCfDFe5YfjKPlzlFsMITYIRQghRSdQCFEIIUUmkAIUQQlQSKUDRL8zsKDN7wMyeN7M7zGz3Bu4PMbM/mdlzZjbfzC42szEZ+04z84Jr1eVA9v8xs9lmtsTM7jWzwwvcHGBmd5vZ0vT7vuVd7qGIczPbw8yuMrN5ye/OJp4Zb2Y3JrnnmdkJljtwcCjiW1QAd9elq6ULOAh4ETgC2Bo4C1gMbFrifjfgZeCTwGbAzsCdwA0ZN53As8CY7LUcyH5ksn8/sDlwMLAI2DfjZhfgJeC45Odx6X6n5VzuQY9z4L3A14ApwHNAZwP3awLzgZ8Ab07PLQI+PZTxrasaV9sF0DX8LuA24Hs5s/uBk0vcTwcezJl9CFicue/M3i9Hst8CnJ4zOw24KXN/KXB9zs1vgB8v53IPSZxnwlvchAI8EngGWC1j9gVgHj2T9gY9vnVV41IXqGgJMxsF7ABcl7O6Dti15LGbgQ3MbF8LRhMtkl/m3K1mZg+a2cNmdrWZbbccyL4K8HzObAkwycxGpvtdCvy8to6fLTGIcsMgx3k/2AX4g7svyZhdC2wIjM24GbT4FtVBClC0ymhgJeCxnPljRBdaH9x9JqHwfgS8ACwADPhgxtm9wFRgP6Lb7nngZjPbsp2yEwXrVDPbMSnvicA0YGTyj/RsK362ymDJPRRx3iplcVmzq+dmoOJbVAQpQDHomNk2xJjVl4mWzF5EYXVuzY27z3T3H7j7n9z9D8SY1z+BT7RB5CxfBq4huhRfBK4EfpDsXmmXUE3QUO7lOM6FGBKkAEWrPEFMaFk/Z74+MXmhiM8Bt7v7N9z9L+5+LXAU8AEz27joAXd/GZgFDGRrpGXZ3X2Ju08FVie64DYF5hATMxYkZ/Nb8bMfDJbc+WcGI85bpSwua3b13AxUfIuKIAUoWsLdXwDuACbnrCYTrY0iVicK8Cy1+8I0mKa9vwV4tH+S9qWfsteefdHdH05K4mDganevtQBn9sfPZhlEuXsxGHHeD2YCu+eWYkwGHiEUeM3NoMW3qBDtnoWja/hdRFfZC8SY0tbAGcQMvzck+4uAizLuO4luuCOJKfm7AX8E7si4+SLw7mQ/AbggPTOpzbK/EfgA0SqaBFwCPAmMzbjZlZiGfyzwJqLF+yIDvwxioOUe9DgH1kh+TyCWQZyQ/m+a7E+m93KYtYiW3CXEMoj9iVmh2WUQgx7fuqpxtV0AXcPzIrow5wBLidbJHhm7bqA75/4TwN9TIfgoMSFm44z96cCDyb/HiUkcu7Rb9qRs7kpyPw1cQRzWmvdzCnBPUlKzgf2Xd7mHIs6BDsALrq5k3wXMyT0zHvg9MSnn0aSobajjW9eKf2kzbCGEEJVEY4BCCCEqiRSgEEKISiIFKIQQopJIAQohhKgkUoBCCCEqiRSgEEKISiIFKIQQopJIAQohhKgkUoBCCCEqyf8DLiS/27tvzv8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 180x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 180x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 180x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 180x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from pylab import *\n",
    "for row in df.T.iterrows() :\n",
    "    print(row[1][0])\n",
    "    if row[0]=='Dataset':\n",
    "        continue\n",
    "    auc_weighted_list = row[1]\n",
    "    plt.rcParams[\"figure.figsize\"] = (2.5, 1)\n",
    "    fig1, ax1 = plt.subplots()\n",
    "    title = 'AML: distribution of AUC_weighted_'+str(row[0]) +' / AUC_weighted_best'\n",
    "\n",
    "    #print(title)\n",
    "    bp_dict = ax1.boxplot(auc_weighted_list,vert=False,showfliers=False,widths = 0.7)\n",
    "    plt.xticks(fontsize=14)\n",
    "    ax1.set_xlim([0.85,1])\n",
    "    ax1.set_yticklabels('')\n",
    "    ax1.set_title(title+'\\n'+'Med:' + str(round(median(auc_weighted_list),4)),fontsize = 14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>camel_1_2</th>\n",
       "      <th>eclipse_2_0</th>\n",
       "      <th>eclipse_3_0</th>\n",
       "      <th>prop_2</th>\n",
       "      <th>xalan_2_6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 0, 'POB': 0.9274601048016933}</td>\n",
       "      <td>{'Iteration': 0, 'POB': 0.9937966395455202}</td>\n",
       "      <td>{'Iteration': 0, 'POB': 0.9973296756032038}</td>\n",
       "      <td>{'Iteration': 0, 'POB': 0.9374780530010222}</td>\n",
       "      <td>{'Iteration': 0, 'POB': 0.9758363303168458}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 4, 'POB': 0.8750069365719858}</td>\n",
       "      <td>{'Iteration': 4, 'POB': 0.9694297337634201}</td>\n",
       "      <td>{'Iteration': 4, 'POB': 0.9709999554739795}</td>\n",
       "      <td>{'Iteration': 4, 'POB': 0.8944287505384934}</td>\n",
       "      <td>{'Iteration': 4, 'POB': 0.9732533547917754}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 9, 'POB': 0.91164947718066}</td>\n",
       "      <td>{'Iteration': 9, 'POB': 0.9860033219392422}</td>\n",
       "      <td>{'Iteration': 9, 'POB': 0.9927397849887942}</td>\n",
       "      <td>{'Iteration': 9, 'POB': 0.977388708351987}</td>\n",
       "      <td>{'Iteration': 9, 'POB': 0.9761620675385969}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 14, 'POB': 0.9488009639853183}</td>\n",
       "      <td>{'Iteration': 14, 'POB': 0.9782894420104954}</td>\n",
       "      <td>{'Iteration': 14, 'POB': 0.9774166497632699}</td>\n",
       "      <td>{'Iteration': 14, 'POB': 0.8680151224627459}</td>\n",
       "      <td>{'Iteration': 14, 'POB': 0.9613711848027903}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 19, 'POB': 0.9373330268029141}</td>\n",
       "      <td>{'Iteration': 19, 'POB': 0.9467779596552887}</td>\n",
       "      <td>{'Iteration': 19, 'POB': 0.9705831424486343}</td>\n",
       "      <td>{'Iteration': 19, 'POB': 0.9810715807028109}</td>\n",
       "      <td>{'Iteration': 19, 'POB': 0.9870320392718446}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 24, 'POB': 0.9286444749213193}</td>\n",
       "      <td>{'Iteration': 24, 'POB': 0.9947835925087862}</td>\n",
       "      <td>{'Iteration': 24, 'POB': 0.9901201707820253}</td>\n",
       "      <td>{'Iteration': 24, 'POB': 0.987352495049481}</td>\n",
       "      <td>{'Iteration': 24, 'POB': 0.9776894131783629}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 29, 'POB': 1.0}</td>\n",
       "      <td>{'Iteration': 29, 'POB': 0.9828354436473931}</td>\n",
       "      <td>{'Iteration': 29, 'POB': 0.9968163895334168}</td>\n",
       "      <td>{'Iteration': 29, 'POB': 0.9934487830954711}</td>\n",
       "      <td>{'Iteration': 29, 'POB': 0.9802760080058971}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 34, 'POB': 0.9391214732486146}</td>\n",
       "      <td>{'Iteration': 34, 'POB': 0.9682165037793076}</td>\n",
       "      <td>{'Iteration': 34, 'POB': 0.9879235537701171}</td>\n",
       "      <td>{'Iteration': 34, 'POB': 0.9764173085346827}</td>\n",
       "      <td>{'Iteration': 34, 'POB': 0.9844756052981762}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 39, 'POB': 0.9598011780281109}</td>\n",
       "      <td>{'Iteration': 39, 'POB': 0.9942660440036589}</td>\n",
       "      <td>{'Iteration': 39, 'POB': 0.9918913169312666}</td>\n",
       "      <td>{'Iteration': 39, 'POB': 0.9871594217938677}</td>\n",
       "      <td>{'Iteration': 39, 'POB': 0.9867364629039594}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 44, 'POB': 0.9597456854522248}</td>\n",
       "      <td>{'Iteration': 44, 'POB': 0.9825850946030522}</td>\n",
       "      <td>{'Iteration': 44, 'POB': 0.9897812782925756}</td>\n",
       "      <td>{'Iteration': 44, 'POB': 0.9719090480161119}</td>\n",
       "      <td>{'Iteration': 44, 'POB': 0.979331370062819}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 49, 'POB': 0.9515676652687822}</td>\n",
       "      <td>{'Iteration': 49, 'POB': 0.9870468441577198}</td>\n",
       "      <td>{'Iteration': 49, 'POB': 0.9915004774178866}</td>\n",
       "      <td>{'Iteration': 49, 'POB': 0.9818124993212268}</td>\n",
       "      <td>{'Iteration': 49, 'POB': 0.9833994660322432}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 54, 'POB': 0.9519973363563573}</td>\n",
       "      <td>{'Iteration': 54, 'POB': 0.9865930865148524}</td>\n",
       "      <td>{'Iteration': 54, 'POB': 0.9971231243413858}</td>\n",
       "      <td>{'Iteration': 54, 'POB': 0.9966212180267672}</td>\n",
       "      <td>{'Iteration': 54, 'POB': 0.9676277523287196}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 59, 'POB': 0.9437844351252149}</td>\n",
       "      <td>{'Iteration': 59, 'POB': 0.9851174714746521}</td>\n",
       "      <td>{'Iteration': 59, 'POB': 0.9614169663927492}</td>\n",
       "      <td>{'Iteration': 59, 'POB': 0.9096827444397919}</td>\n",
       "      <td>{'Iteration': 59, 'POB': 0.9861646131146631}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 64, 'POB': 0.9537857828020578}</td>\n",
       "      <td>{'Iteration': 64, 'POB': 0.9880337971209859}</td>\n",
       "      <td>{'Iteration': 64, 'POB': 0.974212013120334}</td>\n",
       "      <td>{'Iteration': 64, 'POB': 0.9391541702013151}</td>\n",
       "      <td>{'Iteration': 64, 'POB': 0.9993593834638896}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 69, 'POB': 0.9535891805332043}</td>\n",
       "      <td>{'Iteration': 69, 'POB': 0.9974688267295748}</td>\n",
       "      <td>{'Iteration': 69, 'POB': 0.9600750016078841}</td>\n",
       "      <td>{'Iteration': 69, 'POB': 0.9619404344872275}</td>\n",
       "      <td>{'Iteration': 69, 'POB': 0.9857411547263867}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 74, 'POB': 0.9428236208113014}</td>\n",
       "      <td>{'Iteration': 74, 'POB': 0.9959185884165422}</td>\n",
       "      <td>{'Iteration': 74, 'POB': 0.979441346862647}</td>\n",
       "      <td>{'Iteration': 74, 'POB': 0.9846627432572183}</td>\n",
       "      <td>{'Iteration': 74, 'POB': 0.9846975891826287}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 79, 'POB': 0.9728641303916983}</td>\n",
       "      <td>{'Iteration': 79, 'POB': 0.9924967502768282}</td>\n",
       "      <td>{'Iteration': 79, 'POB': 0.9955721346268966}</td>\n",
       "      <td>{'Iteration': 79, 'POB': 0.9812381063857772}</td>\n",
       "      <td>{'Iteration': 79, 'POB': 0.9805124691002053}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 84, 'POB': 0.8860277621429646}</td>\n",
       "      <td>{'Iteration': 84, 'POB': 0.9984353184728708}</td>\n",
       "      <td>{'Iteration': 84, 'POB': 0.9887782059971603}</td>\n",
       "      <td>{'Iteration': 84, 'POB': 0.9943091657907979}</td>\n",
       "      <td>{'Iteration': 84, 'POB': 0.9699296286957603}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 89, 'POB': 0.9288204656619868}</td>\n",
       "      <td>{'Iteration': 89, 'POB': 0.9754369072264215}</td>\n",
       "      <td>{'Iteration': 89, 'POB': 0.9739077519801711}</td>\n",
       "      <td>{'Iteration': 89, 'POB': 0.9848413360186604}</td>\n",
       "      <td>{'Iteration': 89, 'POB': 0.9757036225598361}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 94, 'POB': 0.9461341493384491}</td>\n",
       "      <td>{'Iteration': 94, 'POB': 0.9871022098117567}</td>\n",
       "      <td>{'Iteration': 94, 'POB': 0.9785001162623869}</td>\n",
       "      <td>{'Iteration': 94, 'POB': 0.9938964717069244}</td>\n",
       "      <td>{'Iteration': 94, 'POB': 0.987586998982976}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>{'Iteration': 99, 'POB': 0.9610204291954368}</td>\n",
       "      <td>{'Iteration': 99, 'POB': 0.9807736748351066}</td>\n",
       "      <td>{'Iteration': 99, 'POB': 0.937917122233821}</td>\n",
       "      <td>{'Iteration': 99, 'POB': 0.9811584636678368}</td>\n",
       "      <td>{'Iteration': 99, 'POB': 0.9892530845505249}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from IPython.display import display, HTML\n",
    "import pandas as pd\n",
    "groupedIterationMap ={}\n",
    "for dataset in a_all_metrics.keys():\n",
    "    all_metrics = a_all_metrics[dataset]\n",
    "    bestPerformance=float(a_performance_tb[dataset]['AUC_weighted'][0])\n",
    "    tb = []\n",
    "    for ita in range(0,105,5):\n",
    "        index = ita\n",
    "        if index != 0:\n",
    "            index = index -1\n",
    "        printed_row = {}\n",
    "        #printed_row['Dataset']=dataset.split('defect_')[1]\n",
    "        printed_row['Iteration'] = index\n",
    "        printed_row['POB'] = calculateImprovement(index,all_metrics,bestPerformance)\n",
    "        tb.append(printed_row)\n",
    "    groupedIterationMap[dataset.split('defect_')[1]] = tb\n",
    "\n",
    "display(HTML(df.to_html(index=False)))\n",
    "print('\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f83ac8c27b8>"
      ]
     },
     "execution_count": 286,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "df=pd.DataFrame({'Iteration': [x['Iteration']+1 for x in groupedIterationMap['eclipse_2_0']]\n",
    "                 ,'eclipse_2_0': [x['POB'] for x in groupedIterationMap['eclipse_2_0']]\n",
    "                 , 'eclipse_3_0':  [x['POB'] for x in groupedIterationMap['eclipse_3_0']]\n",
    "                 , 'camel_1_2':  [x['POB'] for x in groupedIterationMap['camel_1_2']]\n",
    "                 , 'prop_2':  [x['POB'] for x in groupedIterationMap['prop_2']]\n",
    "                 , 'xalan_2_6':  [x['POB'] for x in groupedIterationMap['xalan_2_6']]\n",
    "                }\n",
    "               )\n",
    "\n",
    "plt.rcParams[\"figure.figsize\"] = (15, 10)\n",
    "axes = plt.gca()\n",
    "axes.set_ylim([0.85,1])\n",
    "plt.plot( 'Iteration', 'camel_1_2', data=df, marker='o', markerfacecolor='blue', markersize=12, color='skyblue', linewidth=4)\n",
    "plt.plot( 'Iteration', 'eclipse_2_0', data=df, marker='', color='olive', linewidth=2)\n",
    "plt.plot( 'Iteration', 'prop_2', data=df, marker='', color='olive', linewidth=2, linestyle='dashed')\n",
    "plt.plot( 'Iteration', 'eclipse_3_0', data=df, marker='')\n",
    "plt.plot( 'Iteration', 'xalan_2_6', data=df, marker='')\n",
    "plt.legend()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Iteration</th>\n",
       "      <th>eclipse_2_0</th>\n",
       "      <th>eclipse_3_0</th>\n",
       "      <th>camel_1_2</th>\n",
       "      <th>prop_2</th>\n",
       "      <th>xalan_2_6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.89</td>\n",
       "      <td>0.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.87</td>\n",
       "      <td>0.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>30</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>35</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>40</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>45</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.95</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>60</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>65</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.94</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>70</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>80</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>85</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.89</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>90</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>95</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>100</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from IPython.display import display, HTML\n",
    "import pandas as pd\n",
    "groupedIterationMap ={}\n",
    "for dataset in a_all_metrics.keys():\n",
    "    all_metrics = a_all_metrics[dataset]\n",
    "    bestPerformance=float(a_performance_tb[dataset]['AUC_weighted'][0])\n",
    "    tb = []\n",
    "    for ita in range(0,100):\n",
    "        index = ita\n",
    "        if index != 0:\n",
    "            index = index -1\n",
    "        printed_row = {}\n",
    "        #printed_row['Dataset']=dataset.split('defect_')[1]\n",
    "        printed_row['Iteration'] = index\n",
    "        printed_row['POB'] = calculateImprovement(index,all_metrics,bestPerformance)\n",
    "        tb.append(printed_row)\n",
    "    groupedIterationMap[dataset.split('defect_')[1]] = tb\n",
    "\n",
    "display(HTML(df.to_html(index=False)))\n",
    "print('\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f83a264dd68>"
      ]
     },
     "execution_count": 305,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "df=pd.DataFrame({'Iteration': [x['Iteration']+1 for x in groupedIterationMap['eclipse_2_0']]\n",
    "                 ,'eclipse_2_0': [x['POB'] for x in groupedIterationMap['eclipse_2_0']]\n",
    "                 , 'eclipse_3_0':  [x['POB'] for x in groupedIterationMap['eclipse_3_0']]\n",
    "                 , 'camel_1_2':  [x['POB'] for x in groupedIterationMap['camel_1_2']]\n",
    "                 , 'prop_2':  [x['POB'] for x in groupedIterationMap['prop_2']]\n",
    "                 , 'xalan_2_6':  [x['POB'] for x in groupedIterationMap['xalan_2_6']]\n",
    "                }\n",
    "               )\n",
    "\n",
    "plt.rcParams[\"figure.figsize\"] = (15, 9)\n",
    "axes = plt.gca()\n",
    "axes.set_ylim([0.8,1])\n",
    "plt.axhline(y=0.98, color='r', linestyle='-')\n",
    "\n",
    "threshold = 0.99\n",
    "plt.plot( 'Iteration', 'camel_1_2', data=df ,label = 'camel 1.2')\n",
    "plt.plot( 'Iteration', 'eclipse_2_0', data=df,label = 'eclipse 2.0')\n",
    "plt.plot( 'Iteration', 'prop_2', data=df,label = 'prop 2.0')\n",
    "plt.plot( 'Iteration', 'eclipse_3_0', data=df,label = 'eclipse 3.0')\n",
    "plt.plot( 'Iteration', 'xalan_2_6', data=df,label = 'xalan 2.6')\n",
    "plt.legend()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 364,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'AW_ite / AW_best\\n(AW: AUC_weighted)')"
      ]
     },
     "execution_count": 364,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAucAAAFrCAYAAABynSf2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+17YcXAAAgAElEQVR4nOydd5wU5f34389eA+6OE46OcIKNYucgYEXFFmJU7BGVGIOKmoJ636iJIcaouZ+mmEgiGqOIxp7EFDU2bIAeh42qtLMgvR31yn5+f8zs3d7e7O7M7szO7N7zfr3udTv9+Uz9PJ/nU5SIoNFoNBqNRqPRaPwn5HcDNBqNRqPRaDQajYFWzjUajUaj0Wg0moCglXONRqPRaDQajSYgaOVco9FoNBqNRqMJCFo512g0Go1Go9FoAoJWzjUajUaj0Wg0moCglXONRqPRaDQajSYgaOVco9F0CJRSIaXU50opMf9e87tNmUApNTtKZlFK/cPBtrUx2z4SZ71HotYZ61bbNRqNpiOilXONRtNROBUYEDV9olJqv0wdXCm1X5QCOy1Tx7VgvFKqV7KVlFKHAUdloD0ajUajiUIr5xqNpqNwhfl/h/lfAd/1qS1+sRvIBy61sW7kfO32rjkajUajiUUr5xqNJudRSpUDZ5mTjwLvmr8vV0p1pPfg383/CTslSqlC4BJz8nlPW6TRaDSaNnSkj5JGo+m4TAQKzd+PmH8AFcDJPrTHLx42/w9XSo1MsN63gR7m77962ySNRqPRRKOVc41G0xGIWIoXich84GlglznvCutNDKKDHZMdJF7gpLntqqhZP48JtBSl1Oo4+yxWSk1VSr2plFqvlGow/89WSv1YKdUlWbuieB2oM38nkjtyvt4CVjjYv0aj0WjSRCvnGo0mp1FKjQAONycfBRCR7bS6a5ytlOrmR9uSoZSqBD4F7gWOB3oCBeb/E4DfAJ8qpWwFboqI0DpqcJFSqpPFMfsBp5mTD8cu12g0Go23aOVco9HkOhELcTMwK2p+xF2jE/Adj9twKK0KL8CfzHnRf6dGb6CUOhB4A+hnznoWw91kBIb/fKRz0R94Qym1v822PAoIsA9wjsXyy4E8jMDZZ23uU6PRaDQuoZVzjUaTs5iW4Yji/T8R+Tpq8RvYc/FIGxFZiGEBj7BeRBbG/H0as9lDQIn5e6qInC8i/xKRBSLygoicC9xsLu8KPGizLauA2eakldyTzP9Pi8hOO/vUaDQajXto5Vyj0eQyEzAsxNDqzgG0uHjMNCePMvN6BwKl1JEYbiwAs0Xkt1bricjdtGaeOVEpdbjVehZE3FVOUkoNjDruscBBMetoNBqNJoNo5Vyj0eQyEcvwFuCfFssfwXDxAPheJhpkk2gXlweSrPunONsl4jlgO8Y3YFLU/Mj5+lRE3o3dSKPRaDTeo5VzjUaTk5jVP08yJ58Skb2x64jISuBtc/ISM793EIi24s9Nsu6cqN+2LOcisht40pycpAyKgfPNeTp9okaj0fiEVs41Gk2u8l2MKqAQ49ISQ0QRLQfO9rJBDiiP+r02ybrRfvTlcddqT0TuQRiZXy7A8HFvptXdR6PRaDQZJt/vBmg0Go3bmFU/L4+aNU8pFW/1aK7AyIGe84jIPKXUEmAohtyDzEUvi8ga/1qm0Wg0HRttOddoNLnIyRjVP51yilJq35h5zZEfptJviekW4habon73SbJu9PJNcdeyJmI9vwA4NmaeRqPRaHxAW841Gk0uEgnuFOD7QLKUgBXA3bQGSN4Rtaw+6nc34ivAQ5McI2mF0Sg+pjUF5BhaUz5acXTU748cHAMM95U7gSJzehPwgsN9aDQajcZFtHKu0WhyCrPaZ8R3fJ6I/MXGNiHgBxgFfyYppX5lploEWBm16kjgpTi7uSzJYXZH/S6Ku5bBSxidBYCraA3etOLqqN8vJ9lvG0RknVLqBWC8OWumiDQ42YdGo9Fo3EW7tWg0mlzjElqV36fsbCAiYeAZc3J/jADJCG9E/b7ByrVFKXU6MCXJYTYDkYwxByVaUUQ+At40J8cqpX5ktZ5S6kbgOHPyNRH5OEkbrI51roh0Mv+mOt1eo9FoNO6iLecajSbXiLi0RCvcdngK+KH5+wrMKpoi8olSajYwFhgHvKiU+gPwFdAbOMdcfy6tftvtEJEmpdRccz9nmgr3W8Auc5VGEVkRtcn3gQUYGVR+q5QaAzwGrAH6Y1jqzzPX3Y5hYQ8Cp5tpLJOxWETe97gtGo1Gk3Wo1pFbjUajyW7MypoLzMm3ROSEROvHbKuA1cBADIW5r4hsN5cNwrBkD4izeS1wBrDenH5URCZZHONkDNeTPIt91InIfjHrjwT+geFuE4+vgG+LyAKrhWbH4gQAEbGVsiZm+/2AVeZkPLkeoW12HDv8XkQsRwQ0Go2mI6PdWjQaTS5xRdRvRykRTR/zyDZdgIuilq0CjgLuAT4F9gDbgBrgx8DRIrLBxjFew7CuP4nREdiTZP0aDBeYGzCs7BuBJvP/W+b8g+Ip5hqNRqPJPrTlXKPRaDQajUajCQjacq7RaDQajUaj0QSEnFbOlVIPK6XWK6UWxlmulFL3KaWWK6U+VkodFbXscqXUZ+afU19KjUaj0Wg0Go3GMTmtnAOPAKcnWH4GcKD5Nxn4E4BSqjvwc+AbwCjg52buZI1Go9FoNBqNxjNyWjkXkbcwcgvH4yyMohsiIvOAfZRSfYHTgFdEZLOIbAFeIbGSr9FoNBqNRqPRpE1OK+c26A98ETX9pTkv3nyNRqPRaDQajcYzdBGiNFFKTcZwiaG4uHjEkCFDMnbsRWu2AzC8X1frFb7+GKS5/XyVB30P87Blzlm5YScAg3sW+9yS9Am0LGs+iLtoUVFhy+/h5cOB9rKsr9/Luu2t2f96d+1Er9JkleiDQaCvSwrkkjxtZElwj9LvyIT72fTVDpqb2mcgy8tXlPcvSa1xDtvTRpYsegfHUr95D2t2GQVtu4dDdCopoLR7p6TbNawyUuKHdxq1tULFXQAoHDTIo5baI5eeFzepra3dKCI9/W6Hpi0dXTn/irZFRfY1532FUcUvev5sqx2IyAxgBkBlZaXMnz/fi3Zacs70dwH4+5RjrFeYVhZ/42mZa6cdfv3SUgD+7/TMdW68ItCyWNwTAlR334e9Za2dvPOHnk/VyCqqX14GtMpSW7eFSx6aR2NTmIL8EI9fOZoRFS6HY9zZHxp2tJ9fWAK3fJXybgN9XVIgl+RpI0sa7603n1jK4ne/JtzcqqCH8hTDju3HCRcfnFrjHLbHLVn8Zue2vXzvF28iYeHE5iIuvWMMxWX2O+J1l14GQMVjM71qoiNy6XlxE6VUnd9t0LSnoyvnLwDXKaWexAj+3CYiXyulXgbujAoCPRW42a9GxiOuUp6F5NILM5tkiSjms8q6MnHoREMhr6lm1pJZAFSdVoVRONNgREU3Hr9yNPNWbmL04HL3FXOwVswTzbdJNl0XO+SSPG7JUjl+EEvmroUo5VyFFJXf3M+V/dshV65LcVkR11QOZOHbaxh6fF9HirlTauu2ePtOIXeui6ZjkNPKuVLqbxgW8B5KqS8xMrAUAIjIn4H/At8ElmOU6/6uuWyzUuqXGNX/AG4XkUSBpRoNACLSRpmNnQ4aCigNCxO3badqpKGIV42sAqC0sNSy7SMqurX7gGbi46rpIBSWxB85SUJxWRFDx/RpsZ6H8hRDj/ZWscxlKscP4vPFm1Pq3Ni1mEdG4xqawhR6NRqn0WQZOa2ci8jFSZYLcG2cZQ8DD3vRLrf4xq9eBeC9W8f53JL0ufqxWgD+fOkIn1uSOtM/nE59Qz2rlp0MKP408Siqa6opLSxlyhFT/G5eXKZs3YZAiyIeUdCVUrauS7Z8XHPhHosml+RpI4tD16VY94lo63mmreaQW9flhhcWwsFFXOph52beyk00NIUJCzQ2hZm3cpMn749cui6a3CenlfNcZ3j/OIGgWchRFfv43YS0EBHqG+qZtWQWh+SVM3bAiS3uIROHTgyOBT2OVVLFWCUjbbVzXTL1cU2XbL/HYskledyUJWI9X/j2Gnes5g4t+fq6xMdqhG304HIK80MtcSyjB5e7eswIuXRdNLmPMozHGjfIdEBoUjwKrPOTILtPiEgbf22gxY87EIq5R7geJJowiG5b6vv1gxx8Bl0ljfMTsZjvqjG8D7uMHAkYFvSd2/by/P+rZcJNI/x1adHXv4VEI2xBfq/nOkqpWhGp9LsdmrZoy3kuc8tXmcmukSGC7j4RcQeJVs6zWTG36z/vepBoGj7HgcOj4NZ2ZKsS6NH5KS4r4tI7jm4zzxcFMMjnPsMkGmGzimPJCbL1udT4jlbOs5hDp70MwCfTTou7Tkaya7jAhQ/MBeCpq8bEXSfo7hMRy/muuskAdKmYQXVNNVUjq/j8ssuB4KQVS0bEf37BB8cD8OTk0Qn95139uHr00bJzj2UTbeTJVCfAIy7c+1MAniq6w/Y2kWfJTsq+THbsc+k+ayNLmopmptxX4uHLdcny51LjH1o5z0Yiw/57Hmw7DZbD/rlilfD75Z6IaJeW3l1+xoDSARw1dFeLFf1CjMwo2UC0/3xp/SAGlA4Ipv+8RmMT2x17hwqo29b4QLt3JFI0Y13RLM5XthiKMoaNc6bpuGjlXJM1BPnlrpSi9L0HmSiNLNhUB5vqqPr6To5+qzd5PMzuNSEgeIU5rIhOpzijbh3rdq1jsamYZ7ObjiYOWT70budZiu3YXz3neHhzp/2DWJwft63xQXfbc0QcRT5XDEWeoK3pmii0cq7JKoL8cp+yaQMCXGROK2BAYxMK2EWA8yxbKGcKqCosYQY/aZmnFfMcpQMMvcd27PP+6kAxj4PbbnZeue0F2hqv0Wgs0cq5RuMisarrfidvAqBuxVlAQC3mFkqYANUl+bC1dV7Ef14r6A7IouDWutcMN7EK857NCBk8P2537NN1s4tVmr1w28spa7xG04HQyrlGo2mDANXd92FWWVd6N/Ru5z+vFXQHJHALcdWimUWdgDZEzo8ZrMdV2ZMqMx03u3hKs9tue0EPoo+QDe5+KRHvudRokqCVc0120AH8YoOCAkrDwsRt21lQOgCgxQe9tLA0axXzvUuXmr/8z6LhukUzjWcgYjHftaGozbQTC3rOKldJSNUaH09pDpp1vw1a0XSO1XOZqI6DRmOilXNNdtAB/GKDxJSt2wz/+b7GdCRINJOKeS77ymaLRVNj4vIIRKYyT7lqjbdSNBMZTWwQW0gqVzt5beTK1lEuTUbRynk2EkmXaOY5z7qqiblKAF66biq0sWp4phVztyzLkQ9jc1Flm2k/FYAgpQWtOGMvNOxobzG3cd/6qlylM5qW6Fn1eiTuzv6MaNjB0jwgz5z31/jHTveZ9jSIPgtGLQOHPmcaG2jlPIsZuV/uWNpOHtrL7yakj/nSPfmtFcb08Tdl9PApK7QJFBW/rosXluVRaxcbPwLw2Lhh0XTt2kSUhRWGYs20zHdaUpIlndE0DxWkpLI4yBfeXFDMJXv+4m1AZ4JOzsnHvuXusWJwUkgqHnY7L368yzrKyIDGfbRynsU8PGmU301wjcnH7+93E1zDL1lSVmgTKCqTXWyfE9y0LEc+hJcF7MOYrkXT7fsslfPihnIF+vmPR17jTu/dnxJ0FoJ+XZwYJIIui0YTjVbONZoAkY6SEyRXiXQJcsEpL8llP3tNauTKM52IVDt1QY/dcKvzqul4aOU8iznU9Dn/ZNppPrckfS40U6k9dVWcTBoB8Oe2S1JZPMILhdYvWcB9X9mqY68B4CnX9uguTt2S/Lw2sVgpHU4UkiDJki5uy2LrmfYom1VKsmQws5YTg0Qu3WOa3Ecr51nMGYf08bsJrnHeiH0Tr5BFQTRJZbHALd9EtxXaVGQJIiLSRhYRQd21b3DSczoMEoTcuTagZUmErWfao2xWKcmSwcxaTgwSft5j2mKucYpWzrOY6vMO97sJrnF+5QC/m+AaXsjil7tDLlyX6R9Op76hviUVpIhQXVNNaZc8pjRYbOBHes4UFJqgXptUOpopyRLQ0bSksmRRvvCg3mPR2DVIZIMsGk0ErZxnMSs2GC/4/XsGz7XDKZt3GlpS9+JCn1uSPqnIksg30c8S3NlwXRJ1XESE+oZ6Zi2Zxe69eVx/5PU8tPh3zFoyi4khhdA+ZWS2kA3Xxi4pyRLQ0bQ3lq5nft1mThrS2/o59SBfeFok6OS4fY/56XudS8+LJvfRynkWc/b97wK54XN+zaxaIDf8Ad2Wxc+gp6Bfl3gdl2iFPVLddMZLRTz2xgy6VMxi4tCJVP33zqxVzCG41yaVILigyuKU2rotXPFoDSLwl3dW2e9I+9nRSHDsa3LITzsb7jEdEK6JoJVzjSZAWCkyuZSFxW2sOi5AO4W9amQVM176Y8t2VSOrUP+9069ma3KUeSs3IWL8DmL2EL+IFLjatSG38n27KYefI6Sa4KGV8yymsSlMYzjME+99zne+MdDv5mgseOQn77Jz695284v3KWLS3cfY2kdHTStoB6uOS6zCPnfFRl5dNwPo0rJddU01VWSvS0s2kO2KVyqMHlyOUiBCZjvSQfK/j9eWUF77eZoWgp4WUpNZtHKepTzx3ufsaQoDcMvfPwHQCnoAGXRYOYvf/Zpws7TMC+UpBh3ew9F+PC3BbZKN1qx4HZdWhV2xMvwEryx5lt5dfsaA0gEcNXQXs5bMgp69qNqwvr2CHiSFJoCpQjXxGVHRjWF9u7J9dyO/u+jIzClXQfK/t2hLxTTjv613TAZTMaaKF5U/9QipJhqtnGcpLy78ut20Vs6DR+X4QSyZuxailHMVUlR+cz//GpVjxHZcYhX297aspnfXiSzYY2RriPiglxaWoo6Y4kub2xEQpUOTPiVF+ZQU5WurZ6pkMBVjkNAjpJpotHKepZxxSF/e/mxjm2lN8CguK2LomD4t1vNQnmLo0X0pLivyu2kteGEF8ptohX1ExRREhIs+mAeAUqolraJGY4Xbz0AuPFNukCvye1X5MxMjpJrsQCvnWcp3vjGQ2/+1iMZwmF+edWh2WM0TDVeWPxus9rhoyYy2nmuruYs4uH6xinj0tM6QoLGDvk+CSVA6Pm7EFwVFFo3/aOU8iynID1FAKJCKufWL6jGKQ5uY1OvKtrP9Gq7M0PBpxHq+8O01gbOag3dWIM9x4frpDAnZj5tKc7xRpI13/D6l+yQXR6U0rURfR7fiizQa0Mq5xiMsX1Q0MqjoPR9b5R+V4wfx+eLN2moeMOJlSNBKVHaQqc5VR8ikkW0jA0Hr+KQTXxQ0WTT+o5XzLOaMQ/r43YS4WL6oCFNZ8ozl+ueN2DdTTfMcK1mKy4q49I6jfWiNfaw+BLl+XbI5Q0Jgr00K7mKpyuK20hxvFGl03Rbb90m0LNkyKhWvk+PLPeZR5iKvZcmG+CJN9qCV8yym+rzD/W5CXCxfVIWvUZy31XL98ysHZLiF3qFlCQDTytpOF5ZwvoViGJshocdPf0gd2WHBCuy1ScHdKFVZMtW5cpJJI7DXJQHxOjm+yGIz3sdpxycTsqQaX5QtnThN5giMcq6U6gSMBgYCPYDdwHrgQxFZ4WfbgsqKDcbHbv+ewcyF3O5FFcdqDrB5ZwMA3YsLM9U8z9CyBJCGHXFlic6QUJfxhqVOzlwbUpfFq/RzVsqR3UwaVrL4omw5GMGI18kJ2j2WiutNJP5plzJGcbuIEQzuJFDTLkGPL9JkD74q50qpAuB84HvA0UDkDaAAiVrvK+BZ4AERWZbpdgaVs+9/F4BPpp3mc0usafeiWtUEDRYrFpZwzaxaAJ66akzmGujR8KkvsnhEpmRJyd813vWLgx1ZElmwMu6Tm0S50veZQdDSz3l6XZy4DDkYwYjXyQnSPRbP9SZZxycS//RCZyNBwUU7ijwN1EwnvkhbzDURfFHOlVIh4GrgNqAn0Ax8BNQAa4HNQGegHBgCfAP4EfBDpdS/gZtE5FMfmh4oLh+zn2f7diMtFMS8qMriD1d+f/G6VJqZHh4Vfvn+cYM92a8fZEKWlIP6rK5frDtLFOnI4ktWlyTKVcbvMw9Tj+pnxiYeZpiy6uQE6bqkGl8QGcGt3NOq7niZ0jYb4os0wccvy/lCDKX7DeBR4DkR2ZloA6XUYcAk4BLgE6XUd0XkCa8bGmRuPO1gz/btVloouy+qccN6O25jUNGytGLH2pypTBhOZIm1YAUxW0fG7zMPFUP9zASTIMmSanxBZARXdKCmJovwSzn/ApgkIu/b3UBEPgamKqVuBX4IBGcc0ydmL1sPwNiDe7m+70yXnQ+6/7wTtCwGdq3NmQrqS0eWIGZ1Cex9loK7WGBlSQEtizekE19QOX4Q78xbQ1jC9Azl65S2msDji3IuIik7SYvIbuBuF5uTtVz/tw8Ab3zOM50W6pbnPwGC4duYLloWA7vWZleD+hIohunI4lXgYToE9j5LwcUlsLKkgJbFO1KNLyguK+LtnsLObY3cMWKAr1Zzt1xGNblNYLK1aIKHLjuvSQcn1mbXgvoSKYYPzLW9Gyt3HLttzIl0aPH8y+NhkbrSq5gOjU08CnjPVkrLO7FnZ5Pv3zFdSVRjh5xXzpVSpwO/B/KAh0Tk7pjlFcDDGIGpm4GJIvKluezXwHhz1V+KyFMZa3gA0GmhAoCHQXheE0Rrsx18Cf60wk/lKl0/chf80N0ipyyVTu6JgL8fMk0oL0TvQV19/45l2mVUk534la1leoqbiohc6+A4ecD9wCnAl0CNUuoFEVkctdo9wEwReVQpdRJwF3CpUmo8cBRwBFAEzFZKvSgi21Nse1aiy877jIdBeJkgaGnu7GDLHcei0/SXLx5mT0E3KJ5kzLj6dSANJVArV64QVEtlSiMsSe6JjKf79Pm42YiuJKqxg1+W86vjzBeMHOfx5gtgWzkHRgHLRWQlgFLqSeAsIFo5HwZMNX+/Afwjav5bItIENCmlPgZOB56Oe7Rly2Ds2MQt+ta34MYbjd9jx8KkScbfxo1w3nnJJYpef8cOKCpqPfZVVyXf/oYb4MwzW9e/8044+miYMwduuaXd6sXApQDvmDNi13/gATj4YPjXv+Dee5MfP3b9Z5+FHj1g7VpYtxbG3px4+8j6jzxi/M2ebcy/5x7497+THz96/blz4bnnjOmbbzamE1Fe3nb9TZtgxgxjevJk+NTM7jnsQuN/rCwHHdR2/fJyuOsuY/rcc439xbI6KonRvnkwrpPx++ldUHJP23spGance9GyxK4fey8lw+G9145U773P50K4Gc6/E/IVXHwyzG2AS3rAr9a23ksml+1pYuTX2wmLEFKKoW90hU75be+9GetgUrGxwZy98GkTZ++cyp6CMiAUdXCheJ8imNfF/XtvxHeN6eh7Lx5O773VMcmzou+9T8bBmDHGvTStDB6Jk2hr9tjW38nuvXjPTIQ07r1jm8Ls2ud0Vu47mn22fsHYt37L+0dfSeU3Pbr3rGSxeu8BxStW2Ht2bbz36vc00fz1dkaI0KwU9X27UtrJ/MSneu8NuxDyC4AxrevHvPfqP14c/7iQ2nsvmjFj2q4fuffA+Xvvow/hkWWpf3Ndeu9Vjh/B5udfZdSch1AKen/UFR4IWW/v1Tc35r2nCRZx7gbPGRrzNwx4AdgB/Bo4AzjS/F9tzv8nMNzhcfpjZIaJ8KU5L5qPgAnm73OAUqVUuTn/dKVUF6VUD+BEoF39X6XUZKXUfKXU/MbGRofN02g0nhNutp7faK1UlnbKZ2jfrgzo3oWhsYpGAvbpsq6dZUEpRWn3Tg4aq3GbvPwQA4Z0I5RnXh0F+x1a7pulcs+SpXxxzRR21dTQsGole5YsZc+SpWnvd/ueRsJijA6ERdi+JzPfI7+Om2k+/GIrX23dzfL16Y9aFpcVUTa4FICCknzy8v1SxTRBRYlI8rW8boRS1wO3A5UissJi+YEYBYpuFZH7Hez3POB0EbnSnL4U+IaIXBe1Tj/gj8Ag4C3gXOAQEdlqpm08H9gArAdqROR38Y5XWVkp8+fPt9u8tDl02stAcCuEOuFCM1gvKFkB0sFVWRIU1WHatvT3n4R0ZQlEcKR5Di/c+1MAniq6I2rZtuRtdBAc+ea2ySzadSqi8gjlKYYd248TLvamHoGnz4zd+86l+9Pr53/ntr089tO5NDeGySsIcekdYyguK/LEHSOZLJH7bVdNDQBdRo4E0n9GIrESkQBsy1gJhzEsdq6LreMGgHTuMbfjUGrrtvD9B+Zx7tYCnuvWyIOT/TtnSqlaEan05eCauAQlIPRq4GkrxRxARD5TSj0NTMHwIbfLV7S1du9rzove9xpMy7lSqgQ4V0S2mst+BfzKXPYE0OGrkmo6BpEgujUlRiDd/en6T2czDvz7K0ueYUnTeJobw9kd5GU38DBLMoJYBbf7FfgbUcLd7rjaCsD2IIYlWwO/neB2EbJ5KzexVcI82HUveWECUdRMEyyCopwPxnBbScQmDOu2E2qAA5VSgzCU8ouA70SvYLqsbBaRMHAzRuaWSDDpPiKyyaxOehjwP4fH12jSwyflZ1DTf1jMCW3mhWhkUNOrQHLlPNY6GAgLegx1r5XDistcbWNx3pbcyHBkNxg1i4JWY4Pbg1j1NV38CsBOetwszjoFqRchi5cpqKCkgMLOwSpqpgkWtpVzpVQvYIeI7EqwTmegVETWO2zHJoyMKokic07BSHVoGxFpUkpdB7yMkUrxYRFZpJS6HZgvIi8AY4G7lFKC4dYSCTgtAN5WSgFsx0ix2OTk+F5z+Zj9/G6Ca3z/uMF+N8E1XJXFpw9XZecnWLLjOCr3tL4iFGEqOz8O3OlLm9Ll+/n/9f4ghSW2Mxyl2xnQz4wzisuKuPSOo1umvar6aleWIHVU4+HadQlA1ql0ZEl1dCBepqCDR/Ti8aMPyenRBk162PY5V0o1A9NE5JcJ1rkVuF1E8hw1QqnfA9cBjwO3RPKMm8v6Y1QE/Q7wBxH5kZN9Z5JM+5xrNJ4xrYw3t01m8e5xhCkgRCPDOr/CCWUPOvIlDoTFPInVLmkbPfL7D8S56eBkawrAlO8dv2JYfI6dyQgW71evD/sAACAASURBVJmdzd14bMOfaaawZV50zEMQ0D7nwcSJW4vCOs2hG/wMOB6YCFyolFoFrAN6Y7iyFAAfArd5dPysZPYyY4Bi7MG9fG5J+qzYYLzU9u8ZLF/VVMgVWSpLnuGdvScSJo+e4TCVJc/41pa0CsmYow9BuS5uufwERR438EsWL9xAOtJ1yaYCT55fFwsDQHHeFoZ2fo3FDd/UOc01jnDb57wXENftJR4isl0pdTSGz/ck4CDzD4z0h38F7haR3S61Mye4/m8fALmRreWW5z8BciNbS9BkSdU6WJy3hbdLtrAz3I07ml+nOG+r42O3UTjT8Dt1o5BMvOuSVCkOaNBj0O6zdHBbFj8t4l5el7Q7dg7v5R/87QO2727kdxcdaXkefS3w5PB9Yve6uD2iVVnyDEu2jodmye4gcU1GSaicK6UuiJl1iMU8MPy5B2JYvhem0hBT8b4NuM0M0iwDtonIxlT21xH4yRlD/G6Ca1SdnkK6uYAGGaUki0ekm5HipwUP8eb2q6ncxwWreRp+p26UvLZzXawtgY85sgQmUwzdytYRpPssXdyUxa8sLBECfV0cvBdr67bw2bp6GpuFSx6aZ3kefS1F7/B94uZ1sX5P/J3i0CYm9bqyzdycCRLXZJRklvMnMapyYv4/1/yzQgF7gTviLLeNqZBrpTwJl3yjouV3Ng0vWjGiorvzjQIQZGRFSrIkIVVFLuWMFKaF7diCBRxbPrntfB9wo+S1neuSriUwk4qhF/eZU9x677gpi99ZWLy8Ll6lYbRi3spNNIUFIf55tP1cBmD0Kdl1cTIqYfmeoJFBRe9Z7jtZkHi2f7817pNMOb/G/K+A6cC/gf9YrNeMkXHlHRHZkGpjlFLdgLMwqoaWiMi15vzuGDnKl4lI+zu4g/L4e3WAoaT7OrzoArV1RiKeICgc6WJXlkwMvaeckeKWr6it28LFM+bS2CwUFfhfXCTaSpfMOmf1YbVzXdK1BDpRDNMvOuP9M5NMCXTrveOmLF5lYbFLrrzLRg8uJz+kaGqWhOfR1nOZ7kimg0Jg8XDzuli+J4gflxObKSiWbP9+a9wnoXIuIg9EfiulLgf+ISIPe9EQpdREjA5AMUZnQGhNazgAWABcieF/rgHuftEo+XzJNyr8HV50geqXlgHZ4z+byNLx4iCjFLOdqnrJLKzp+pimUyBk3spNNJj3UxDyQFsVknGCnXssXQt9JhXDIDwzbr133JTFzj3viaXSVCCrYyvReuBml4kMPyMqunFg79J2PuexRoV0n8tY4rqWxbiMPLL+IXaG2z9fxaFNTLLYb7J7zMmoRETmRe9+jTQLKk8xtPPb1nE5NkYHsv37rXEf2wGhIuLZF0ApdSLwCLAM+AVwMoYiHjn2R0qppcDZaOXcEjeG/TX2SWjp2J48HX8mh95TzUgxenA5SoEIgSmUkWx4+C+T/8WeUDEUTzJmRFU2xew02TmGXQt9LF5US/QjuNFupzCo751k97wnlsoMutll6p4oKcqnpCi/jWJuZVSwm9vfDnZdRgYVvd+S6rX9euen3Y5kFB7enca3viIfRUNzmMLv/giGp1YDIqjPkcY/nBQhKgV6Al+ISGPU/IsxlOadGHnIP0ihHT8BNgDHiMhWpdRQi3U+BL6Rwr47DOkoFRpnJLR0PJlcObdrYU1kzfHa73RERTeG9e2aMFuDI1zwO40eHra0sIWKjd6Eas36qqTZdqcpcoxULYEi0kYxFBGUSj0Drd/BjXbIxvdONlsq/bwn4hkVkrltOMGuy0hlyTMs2X1Sm3mKMJXd/wvck/AYCUdObL5PF6zfzsLCZg5ryGNRYTMF67czZnjqaY2z8TnSeIc9U5LB3cDH0NpNVUpdDczC6KZOAt5SSh1kuXViRgH/EpFEudq+APqksO8OQ0SpQNExet3xlLoMBBlFznUoz1C8nFo6IhbWqaceHEiFK0JJUT799unsTvtu+cooOBL7l+KQ/6DDylvOfwQVAhUzL1RY4PhDVzl+EF3LOznabvqH06muqSZS2E1EqK6pZvqH0x0dOxorZcgrauu2cP8by6mt20LFYzOpeGwmXUaOpMvIkS3TVmTjeyfd59cLYgsCxisQmMl7IpaIUSFPeTeaZnltOr/WzmXEyCH+etv1ThhM8c8WJz2G1bvD6cjJ6MHl1JY0sz0k1JY2p30usvE50niHkzznxwKvi0h0HvP/A9YCl2Mozg8BNwKT22+ekE7A9iTrlAFhh/vtcLg5vBh4fEyXCOlbOpy4m7SxmJ9wIISb2bXBeHnXmWWpK87Y6/s5ySRWFrZQXogDRvTi07lfISovZaXLqSVQRKhvqGfWklkAVI2sorqmmllLZjFx6MSULehp+bA7SDWarjXWznsnkbXSrsuRmwTJUjn9w+nUN9RTNbIKpVRLx660sJQpR0xps66fAa9euG1Z0e7axAm0TDWHuBsjJyMquvHgVca5eNClc9Ghvt+ahDhRzvsDb0QmlFJDgArgFhF51Zx3FjA2hXbUAUcmWWck8FkK++5QuDm86BXZWjI7FrcDoWwTbraeb8O3NZdSdsXz06z85n4sr11Pc2M4Y0qXUoqqkVUAzFoyq0VJnzh0YovClQppKUMOfKDjuSvYdZmy895JN07DbXx7fmNw2rHLlIIcDy+qqsbS7tqsaoIGi/U6NzJ0aJJrGOmkmoG6TDudYmBo0bUsDp+Slo+32+ciG77fmszgRDkvpm31z2MwMqr8L2reZ8AZKbTjBeAGpdS3ReSF2IVKqUuAozCKFGmyGC/8Jf1U9v2wdFScbAxj171W3mbaDplK2ZWpToCV9dMvpSuioEeULCAtxTxCJpShTFhj043T8IJUn99ERWgoW912dhI3u1Q6dnbuiXjPoBVB7Jy3uTZl8UcEK7ftTXwN43RSKzs/wZK9pya1uueSQUOTPThRzr8Cov3JTwXqMQI1I+yDUYjIKb8GLgKeU0o9AfQAUEpdCRwHXAysAH6fwr41AcLtLCV+B8xlm6UjU4FwrncC4rhoFBeWMHTMa+0UcT86TRFXhGiqa6ptKegZVwCmlbWZHFFYwuNXLvS0k+s0I0UmOt2pPr9x7+9jD4Pt+xozrtpme39edOys2mgcjNbSggQ3n7bda5PqNbRbuVPnINf4gRNHvzeBbymlrjRzkp8N/E9Eov3ABwNfOm2EiGzCcIepBS7FsL4r4AFzegEwTkTqne5bEyzcDijyMzjKbypO3uTIag6ZC4SrHD8IFYoN1kyjE5DARcMqeDPywc6U1TyimEdcET6+7GMmDp3IrCWz2gSJxsONALW0aNjBiIpuXHviAZ52bqPvi0T3Q6TTfe//lnHJQ/OordviWZtSwe37O17HLtl9kwirNobyFXl5bT/7fvvb+4mdwG/X32UajQ2cWM7vAs7FUJgVsBsjJzkASqkSDCt3SnndRGQlMFopNQoYA5QD24B5IvJuKvvMdX5yxhC/m+CYeP6SVacfnNL+/K4GaEWqsmQKJ4FwqcqSyby9di1nXl4XpRSlhaVtXBEirgqlhaVJLaCpjGgE/T6zorisiPJDurH+g030OLRby/0QK0sm6wCkQqL72+l1ie3YRfucQ+oWdKs2DjumH4jYfi6z8R6LR1XBU+3m2Xl36BzkGj9wUoRouVLqEAz3E4C/i8iKqFWGYCjmaSVdFpH3gffT2UdH4ZJvVPjdhJSw8pdMtaSy38FR1m1yLosjt4Y084U78clOp9R1kLJhgPfl1KccMaVN8F5EQbejWKWiACSVJ9594iO1dVu4q24N54YK+EvdGgbVDTTfB21lyVSnO51aAbH398oPNrDwzVbf6Hnm/2SuSfE6dl2ePJzQ3EKmP/xGm/WduDrFewYXzfkaAFEkfC69fma8wuq6jgglySeRILtR5bUrA/Uu0+Q+TizniMiXxMnuLyLzgfmpNEIptRj4o4jETQislLoK+KGIDEvlGLnI4+/VARlW0h2kZ3NCbZ0REJbKxyATAXNOSEUWR36NLqRLtOuTnc51ie0EPHPXfF8Dq9KRxS6xirgTi6fTzkxSeazukxhf80wzb+UmtkqYB7vuJS9Mi0U8WpZIR/V6Wjsm8+76gE8CFoAXe39HLNJf0ARA/+Y8265JVh27Qyv3Y0mavs5WHfHaui18lN/IIU15LMxvYunWXYyI6/fv/TPjOWYntTZ8IBClpMcaMxK4zgUls4+m4+BIOY+glCoE9gdKRKTGhXYMwQwCTUAPIHfG2Fzg7heXAqZy7pHS3A6PSlRXv7QMgKeuGpPWfoJAKrJkumKhXVeQZLIks/i36QREDadHyKRfddDvMacKQNDlsSKeRTxalkQdVbeCRCOW1V01NW2mnVrQYzu5S+au5e0iQzm/aEeeo2c4tiPX96XfsqTzuaCiPtNNjSkV1Ipu47yVm5hT1MiAhhBziho5LIHLUPR1yYasJdbX9WQqHptJ9QNzgdSfF52DXJNJHCnnSqnewG+ACUAhRsx3vrnsGOAPwA9E5B2X2wlQgmWm047LHy6OSg3vkdKcKe6ccKhvx3Y7K0QqsmTar9GuzMlkSWbxj+4EpNUBSdOVB/y9x+ziRAFISR4XzmM6xHNDi5Yl3n1SeFg3XzMzWRHbyR06pg+nzfkKCcd/hu0quZ1kNwOalvN53v5IqAAlzQxoWk5x2alx22PVyYht4+jB5fyhMMRfy/YmdRmKvi7ZnrUk3ec/2zJzabIb28q5UqoXhi/4vsDLQHeMwkARaoD9gAuBpMq5ub9oii3mAeQBA4FzgNV229sRGHuw1enKTvbvmRnlIBYvUjGmKkumfLSdyJxMFicKd1odEBdGf/y6x5zgRAFISZ4MVJBNpnxauaFFyxK5Txa9+UWbKq8L1m93LUg0orym43NuReR5aA6HUQXWz4FdJbfisZn02LaXmVVvIkCosIATq7+XdhudxOlEX5dMj+6lQqLrmg3Pv0YTwYnl/OcYivk3ReRlpdTPiVLORaRBKfUWcLzN/a2lTbZVbjT/4qGA/3PQ3pznnpeNIccbT8t+b59XF68DYNyw3hk9rhdZIVKVJVN+jU5kTiaLU4XbzyBRv+4xr/BLnmSjLqlYWKNlqbv0MvqoziwuOgfJy4OmRvq8+BtKfnl3xjIzpTqaVlxWxJ7hpdQt2szZR/dveQ6i9+e0QzugaTl1+QcnfK6cuukkjdMx3SRfbT4KgHF5C1yrqukXufb8a3IbJ8r5t4AXROTlBOt8Dhxrc39PYyjnCrgAWAwstFivGdgEvGZVPbQj8+jc1UBuKOcPvr0SyPyL04usEOnI4sStIVUFwonMdmRxonD7GVjl1z2WKsks0H7IY2fUJRULa6wsnWQ3fdbOY02/YxnQtJxOspuDPcjMZKW8pjua9m54DxuKw9xhymu1Pycd2hN/8z2e/3+1mbVQm65PDzZ9EzCUc7BXVTMIvulW1zXp8+Kzy5dGE40T5bwPsCzJOnsxfMOTIiKRlIwopS4AnhGR2x20R+MHPr3AvHrhBy0Vo123hnQUCLdldqpwd/jAKpvB28ks0HuXLjXnphasmwp2Rl3SjZ+IKFZ7LruKrbKDE3/zPYrLpgCZyczUTsbffcy83c3t1ot3HkN5IXoP6toir9U5m+SwQ5vsneCVm067ttioqpm1vukZcPnSaOziRDnfAvRPss6BGO4qTukMZv4pTWpkSmn26QXm5Qs/aKkY7ZCuO47bMjtRuDt8YJXN4O10fXy9eGbsjrq44b7USXZz0u7nKS47O+X2pkKsjL2G7MPGjzenfB6tzlk2p+ZL9qy75ZvudUdDowkyTpTzOcC3lVI9RWRD7EKl1GDgdOBJp40QkfbmHY0zcrzXnw3BSJkkaJVRO7zC7QHxLNAbr/s+G4HmokogvhLjxTNjd9TFDeXTL6UsVsYh+3ThsYVzUz6P8c6ZFyNImThnyZ51XVFTo0kfJ8r5PcC3gTeUUtdjpFJEKZUPHAfch+E//ttUGqKU6gpcBowCumFkaYlFRGR8KvvXZDf6hd8WL9xx3E4pqUkfKwv0xv/a29arZ8buqIurymem6jiYxMqY7nm0Ome53KFNZ+TErRz0Gk02Y1s5F5E5SqnrMJTwV6MWRazeYeD7IvKR00YopQ4AZgN9MRT8uM1wum9N7hC0cvB+46ZrihcpJZ0Q5A9wIt/tQ68Z5mmHxsoCXWyeo7wf/xWAiofinzM/nxlXlU+f6zh0uHdPmm6SXrntBPk9odG4iaMiRCLyZ6XUO8C1wGigHNgGzAPuE5FPUmzHvUA/4HfADOALtA+6JoZs9tMMOin7sGfYoukH8Xy3SwaXZKRDk44FWj8z7tDhzmPk2TWranLVNse7SPW+zVRwq0YTZBwp5wAishC4xuV2nAC8LCJTXd6vJsfo8Jk+PCJlH/Y0LZrZMIQdz3d73b6daFiVQofGoVVy43Xf53iguKztOSkaMsR2+/Uzkz76PDrDzZGTbHhPaDRu4lg594g84GO/G6EJPrnsp+knQUspGSTi+W6XDO9F4dyVzjs0GR5R0M+MfZKln9TnMXNoxVvTkVEizty4lVKVwHeBI4EyDLeWD4BHRKQmpUYYlUU3isiEVLYPCpWVlTJ//vyMHW/2svUAjD24V8aO6RUrNhiWxFwosdyhZJlWFn/jafaHwjNhCUvnuuw0y6iHVT55BSEuvWMMxWVFngbRxloLu4w0CjJHzpGVPNlqUczUfZaMN59YaunCNOzYfpxwsb1ib29/91oAjvvr/a61yy+C9i5L5/4OmixBQSlVKyKVfrdD0xZHlnOl1P8DptI+aHM0cLVS6l4RqUqhHXcA/1ZKHS0ic1LYvkOSC0p5hFx6YWaDLHY/ctkgi13SkSVeGXU/c+R3qGuToToObqSfHNhUn/Lx/excWR27Q91jGk2AsK2cK6WuBm4APgfuwsiushajcuiJwM3ADUqp5SIyI8m+LrCY/Q/gdaXUo0AtsNVqWxF52m6bc517XjYKtt54mj2Ljpu4bTF8dfE6IHtKq0ew+qAFRpZEwZqcbGsXmZIl+vx5VQ02VVki13jfj5ax7sip9Hnxaer+u9tzBSpZYFy0PNnuk5v02mTIFSid9JORc/76FzsBOCnLroEVgXmXmaRzLoMmi0aTCCeW82uBdUCliGyMmr8NWKaUeg74BLgeI+NKIp6kfVrEiDX+++af1XIBtHJu8ujc1UDmlXMv0u49+PZKIDdenIGRxUIxr3vN8IvetcGeEpdUFg8sml5Vg033uhQ1bOfo96bRyXQv8ZvA3GcuECRZ0k2b+PwBJwBw0l77Lo5+dq4SHTtI1yVdckkWTe7jRDk/AHgwRjFvQUQ2KKWeBb5nY19uZ3vpkPzj2vZWxGQWbTeskumWjrfiTxNHpLV9pkn0Qcs2WRKRVBYPLJpeVYNN9br4ndot3vGi5fG7jelyy5y/GD+uGgOAiKBUq/dk7LSXpJo2MXLO77j8yjbTQefVzuezJ1QMYye1mV/8k3f508+C0RF1g1x6L2tyHyfK+WZgT5J1dpnrJUREHnBwXE0cYn3o7Fi03bBKelE6vntxYdr7CApBlqXi5E0A1K04y5h+bKbRYbv69XbrputGkipeVbYM8nVJhVySZ59wQ8vv6R9Op76hnqqRVSilEBGqa6opLSxlyhFTMtKedNImRstiFz87VweMPTDuNyGX7jG7suhKyZog4EQ5/xdwplLqFhFpVyBIKZUPnAn8063GuYFS6nTg9xjpGh8SkbtjllcADwM9MToWE0XkS3NZNTAeCAGvAD8Up+ltPKTqWaMYa/V5hwP2LNpuWCW9SLv3zPwvADi/ckDa+8oEiT6mbWTJgiI9iTpsfl0XLyoypitL0CyhVvK42cZMWK8jz88/1xn33rcvvYxD6z9nyjlGJ7JqZBXVNdXMWjKLiUMnZsyCnk76yfd/+CsAKtxskIck+iZk23s5EXZk8btSskYTIeRg3Z9gWM5fVEodFb1AKTUCeNFcfot7zUsPpVQecD9wBjAMuFgpNSxmtXuAmSJyGHA7RrArSqmjgWOAw4BDgJEYxZICw4sL1/LiwrUt0xGLdp4irkU7YpUM5RkfuFStkiMqunHtiQe49uJ6tvZLnq390pV9+U0bWXwuOx6PisdmtihyleMHoUJtFZ7Ix9mv6xK5T1G4VpExl+4x8Fae6R9Op7qmmogtImK9nv7hdE+O98rAkbwycCQKGFA6kIlDJzJrySwOm3lYi2IesaQHnXSuS/RzmSkSfRNy6ZmxI4uVgUuj8YO4lnOl1GKL2Z0wlNUapdQuYD3QC+hiLq8D3gWGO2lEnGPFEga2A0uA50XkPza2GQUsF5GV5nGeBM4Coo83DCM9JMAbGFljwAg+7QQUYgSjFmAExAYWuxZtL6ySHZWgWVPbYDNY0ys3knTRFRn9QUSob6hn1pJZgLfW68jzk/fjvxrTDxnTVSItx4+0IRsU82zFi29CNrqHeOGyqdGkQiK3lu60z5gChkIeoQuww/wD6Gz+OaU7hhU/4vgsGIp4V1qzuGzECEodDUxSSv0duEBEwgn22x/4Imr6S+AbMet8BEzAcH05ByhVSpWLyFyl1BvA12Yb/igiS1KQLaPYybucasCTJstw4DYTxA6brmzpD0opqkYa5SpmLZnVoiRnynodsdJH88cbXia0q73PsF9xERkhgy5xbn8TstU9RFdK1gSFuMq5iPTJYDv2x3CLKQBuBd4Vkb1KqSLgWIwiRY0Y/t/7Ab/BUKSvA+5L89g3An9USk0C3gK+ApqVUgcAQ4F9zfVeUUodJyJvR2+slJoMTAYYOHBgmk3JHNoqqYmmI3bY0slc5FUu9qAQUdAzZb0uGjIEaFXMo11ZqmuqWbzyfYbvORoVbvXEdCO9ZqDJsEucm98ELzJ6ZQo/C4tpNBGc+JynhFJqWJyiQ9H8CqOY0Qki8rqI7AUQkb0i8hpGkaO+wC9E5BMMxXwtcGmS/X4FREd/7GvOa0FE1ojIBBE5EqNjgIhsNY8xT0R2iMgOjM7DmNgDiMgMEakUkcqePXsmaU5wiFglO4ISprFH5fhBdC3v1GE6bIMOK2/xs41gV+FLZ9tswMp6He2D7hVKKUoLS9tY6atGVjHoxBJi+wVBGeHJFdz8JtiJf/KVO/vDtLL2f3f297tlGg2QAeUcOB/4W5J1zgVeEBHLHFQisgcjC8x55vQOjOwpQ5LstwY4UCk1SClVCFwEvBC9glKqh1Iqch5uxsjcAkYl1BOUUvlKqQKMYNDAu7VoAka8Yjwulx13g2zosNXWbeH+N5ZTW7cl7X0lCoT1ctugE2u9/viyj1sCNDOhoE85YkobK71SiptO+DGHHLNv2oHsmswQcQ+ZeurBwXRpCWigvkYTwUkqRS/pgZHqMBEhjHSHEb4mSftFpEkpdR3wsrn/h0VkkVLqdmC+iLwAjAXuUkoJhlvLtebmzwInYVQ9FeAlEfmXI6k0moCkS3QDv1053PZjTScQNqhBtG4Qz3oNUFpYmpHAzNhjKKUCGRehiU9Ou4dkQYpcTXYTFOV8NXCOUupWEdkVu1ApVYJhXa+Lmt0HSGo+E5H/Av+NmXdb1O9nMRTx2O2agatstl+jyXncKGCVDl74saaj8OWysjjliCltsrJEFHQ/M6Z0xLgITeZ4ZP1D7AyXQ0xBNkvjg7a8azwmE24tdngIGAjMUUqdq5Tqo5QKmf/Pw0jPuC/wYNQ2J2BkWtFo2uGm+4PGwG9XDi/8WNPJp+5FLvYgYWW99psOFReRRS5xucCgovcJ0dhmXi7FkWiyC5WBAJ+fA7eJSFy3FdPn+yFgEtbpGxUwE/iuiIhSqg/wfxiuJi+73+rUqKyslPnz52fseCs2GL30/Xtm/8t6804j3MCNctF+p/FyUxa/iZXlzSeWtnHlGHZsP064+OCMtSed3MnxrsvObXt5/v/VMuGmEY4V7HS2TZdcvs+yGS1LMGkjy7Sydst3NnfjsQ1/opnW5zivIMSld4xp/2xbbN+6bJsr7c0USqlaEamMnldbW9srPz//IYwCjEEx4uYSYWBhU1PTlSNGjFhvtUIg3FrMXOVXKKX+BlwOHAGUYeQ6/wCjguf/otZfC/zYj7YGiVxQyiO4+fL3O42Xm7L47ecdK4vfrhzp+LGu2rjTUrFPJ5+6n7nYc0FhiqBlCSY5K4tFgbbivC0MLXmbxbtPybk4Eqfk5+c/1KdPn6E9e/bcEgqFvLXgdkDC4bDasGHDsLVr1z4EfNtqnUAo5xFE5BWMLCwaG1Q9a3j1VJ93uM8tcUbdpZcBbatrPjPfqBV1fuUAy21sc2d/rm3YwbXR79M3gbmZC9RxTRb89/OOlSVb/X5r67Zw4Yy5NDcLRQXZUxQlEW7eZ37T0WXxuxMej5y9LnG+BZXb9rLkp3NzMo7EIYdoxdw7QqGQ9OzZc9vatWsPibdOoJRzjTNeXLgWyD7l3Ipna78EXPgIBCBQxzVZaGupjpDJj4aVLNlYwGreyk00mecw24qixCOV+yyoSqCbz4zfpCKL353weHS062Lb+GBheW+ZnxuEtGLuLeb5jesy5ItyrpTqZf7cYPqQ90q4QRQiYumf0xH5ZNppfjfBERGL+a6amjbTFY/N5Kmr2tV3ylrclMXvlH1WsvjpypEqoweX06kgRGNTOJhFUVIglfssqEpgR3/+/e6Ex6MjXhdbxgedLjGnOPfcc/f71re+te273/1umwwSDz/8cLc777yz38qVKzvNnj17yfHHH98um+Dy5csLLrnkkkEbN24sUEpx+eWXb/jZz36Wtp6aCUd/Zf5FsxZYAxwYNf21jb81GWivRhMoorOkBOGDnY0EvihKhvA7447GmkgnXBdZ8p9sKMamyQxHHHHE7ueee255ZWVl3KH3goIC7r333i9XrFixqKamZslf/vKXXrW1tZ3SPXZCy7mZxvB1EdmcxjF+CdwVM+9pjKwsAx+WOQAAIABJREFU22OmNQ644pH3AXh40iifW2KPiI+5lc/5jLdWADD5+P0z3zCXcVsWP/28c+m61NZtpiBP5Yxinsq18XskJh65dJ+lKovfwdZW6Oui8Ys//vGP5ffdd19vpRRDhw7d/Y9//GPVE088UXb33Xf3bWxsDHXr1q3pqaeeWjlgwICmqVOn9lu9enVhXV1d0ddff1141113fTF37tyS119/vWvv3r0bX3311eVFRUXy9ttvd5k6deqAXbt2hbp169b0+OOPr66oqGiM14ajjjpqT7J2VlRUNEb20a1bt/D++++/+/PPPy8cMWJE0m0Tkcyt5WkgrJT6CHjN/HtLRHbbPYBZzKc5Zt5FiaY19qhZnTs5vF9bYowC5cKL0wtZ/PLz9kIWq85ZJsilewxSlyeISmAqsgTVfz7V6xLEYGvPn5kMVtrMtec/aLyzfGPxu8s3lh5zQI/6Yw/osTOdfc2fP7/TPffc03fu3LlL+/bt27Ru3bo8gFNOOWXHRRddtDQUCvGb3/ymx+23397nwQcf/BKgrq6uaM6cOZ8uWLCg00knnTTk0UcfXfHnP//5y1NOOWX/p59+uuyCCy7Y9oMf/GDgf/7zn+X9+vVrevDBB7vdeOON/Z955pnVLogPwLJlywoXL17c5YQTTkg7yC2Zcv4MRnn7I82/G4BGpdR7GIr6q8B7pgKu0SSk5WNaPMmYYVZiK96nCAa55GGVo4E62ejnrQkmQVQCU8G2/3wWlVrPxmDrtAhAAH800VVxraY11ryzfGPxFY/UHNTUHA795Z1V4Ycnjfw0HQX95Zdf7nrmmWdu6du3bxNA7969mwFWrVpVePbZZ++7YcOGgoaGhtCAAQNaeufjxo3bVlRUJKNGjdrd3NyszjvvvO0Aw4cP371q1arCjz/+uOizzz7rfNJJJx0EEA6H6dmzZ1yruVO2bdsWmjBhwv533333F927dw+nu7+EyrmIXAiglDoUOAkYBxwX9fdzYKdS6i1My7qIfJxOg5RS+wFDgRIReSadfeUq0695HRFoKGsC4H5TyVUKpvzpJD+blpCEH9Pt6XhORRGwj62mlUQBwZrMkooSGDRLte0gyoApgInQnXD/mP7hdOob6qkaWYVSChGhuqaa0sJSphwxxe/mBZp3l28sbWoOh8ICTc3h0LvLN5amaz234rrrrhv4wx/+cO0ll1yy7d///nfp7bff3i+yrKioSADy8vLIz8+XUMgw+IVCIZqampSIqAMOOGD3hx9+uNTtdu3du1eNHz9+//PPP3/z5ZdfvtWNfdrK1iIinwCfAL83q3lW0qqsjwG+CZwBoJTaICJ9nDZEKTUMeBAYHTX7GXPZCcDfgUtE5EWn+841uvXpwuav2wUN061vsQ+tsU/Cj+mTLinnmuzi87nW1fYCaNXMJVJRAoOW6SWo/vMa/0jUgUw0Oisi1DfUM2vJLACqRlZRXVPNrCWzmDh0oragJ+GYA3rU/+WdVeGm5nAoPy8UPuaAHvXp7O+0007bft555x1w6623ru3Tp0/zunXr8nr37t1cX1+fN3DgwEaARx55xFHKrcMOO2zP5s2b81999dXicePG7dy7d6/65JNPiiorK9PyDQ+Hw1x00UUVBx100J5p06atS2df0ThOpWhW83zf/LtbKVUIjAemAYcCPZ3uUyk1GHgH6AQ8AAwGTola5W1gD3A+0OGV83FXDOfpX9VYzB/mQ2vsoz+mHRvLgOB4ZbD9smpmwAUiaBZouwQx3V8Q/ec1/pHq6KxSiqqRVQDMWjKrRUmfOHRiiyVdE59jD+ix8+FJIz91y+e8srJyzw033PD1cccdNyQUCskhhxyy67nnnlt96623rrn44ov3Lysrazr22GPrP//8c9vKQ6dOneTJJ59c8YMf/GBgfX19XnNzs7rmmmvWJVLOZ86cuc9NN900cMuWLfnnnHPOgUOHDt31zjvvfLZ69eqCyy+/vOLNN99c/sorr5T84x//KD/wwAN3DxkyZBjAL37xi68uvPDCbemcg5TynCulOmO4tZyMYUE/AsgDwsCCFHY5DegMjBaRj5RSPydKOReRsFJqDvCNVNqba/QcUEr3vl1gV2tcbvd+xfTct9THVtmjI3xM9y6NjJrlTo7gDkMGXCCCZoG2SxA717niP69xh3RGZyMKekQxB7Ri7oBjD+ix001Xluuvv37T9ddfvyl63sSJE7dOnDixndvIb37zmzZptnft2vWB1bKjjz569/z585fFbv/cc8+ttmrDZZddtvWyyy5rd7z99tuv8c0331wOcNppp+0QkVobIjnCVhSeUipfKXWcUmqa6V++BcOCfSOGgv8H4CygXERSyes3Dvi7iHyUYJ3PgX4Jlncoxl0xPGY62FbzCJGPKQr9Me2gVDw2s0P7mWdzrvEg5tyvHD+IruWdAtEWjUPiBeqnGMBfXFZE+SHdaDIzMzch9Di0m63vTMTHPJrqmmpEdJZnTeZJluf8/zAs48cAXTBykS/CcD15A3hTRNzI51eOoXwnQ2tyJj0HlKIUiGSP1TxCrmYkiLhrNBdVtpnuyIqopj1BtEDbJYiW6qT+8zmawSkn8CCuZP2ATohpNxVg3b7J68FEFPOIj3m0zzloC7om8yRza7kLw1XlOYyc52+KyEYP2rEew888EcOALz04dtaSX5hH497mrLGaR9AZCTQdnWx278q6zrUOLO5QjB7eixn/q+OQPXks6dTM5OG9km6jlKK0sLSNj3nEB720sFQr5pqMoxIN2Sil9gCFGAr6Iox0iW9gFCJKy9k95jiPAecBh4jICtPn/DYRyTOXHwnUAA+IyLVuHddtKisrZf78+X43Q+Mz2mLugKDloI4XoAowzbVXHgBvPrGUhW+v4ZDj+3PCxQfb3i5bA0o1mkwxd9F6Fjy8lKOuGMIYG8p5hI6Y51wpVSsildHzPvroo9WHH364F4ZYTRQfffRRj8MPP3w/q2XJLOf7YLi0nGT+XQ/8CGhWSn0IvE6rst4+t5997sZQzt9WSt0K9AJQSu0PHA/cAewC7knjGBqNJmgEzaqZQReIVC3Q2RpQmhGC1tnT+MKY4b0Yc699pTxCrCKe64q5JrgkK0K0B7O4EIBSqhSjYuhJwIkYAaE3YVQNnY+prIvI604aISKLlFIXArOAh8zZCvjU/L0DuEBEVjnZb65zxSPvA/DwJAcxuAH9eM14awWQG6WVX/7+zwGY7HM73CCXrouVLO0sZTd/mbEPcqruXRGXmPfzGwAYtbfAddeYTFvnXbvPAlBwKNefmUCT4Ps249i3gNRl0SOimkziKJWiiNQD/zL/UEr1wFDSTwJOBW4Bbna6X3PfL5iW8iswChGVA9uAecCDIrLe6T5znUVfbXe+UQA+XlYsqHOlqFYg0LIEk1hZsrUiYCQo8/na1Yh4E1Caaet8Lt9n2UzWyZLg+5Z1smhsc99995XPnz+/eObMmZ9XV1f37NKlS/i6667blHxLZ9TX14fOPPPMwXV1dUV5eXmceuqpW6dPn25p1bz55pv7PP744z1CoRD33nvv5+eee64jhS2lPOdRDAAGmn89MazdKSMiG4Bfp9mmDsN7t47zuwmu8edLR/jdBNfQsgSTaFmyvSJg5fhBTJi7lubGMKrA/YDSTBccytX7LNvRsrRazHfV1LSZ1hb0YFJVVbXBy/3fcMMN684888z6PXv2qGOOOeagp59+uusFF1zQRvGura3t9Pzzz3dftmzZorq6uoJTTjnloLPOOmthfr59lduRcq6UGkKr//lYoFtkEUYFzxYXGIf77SMia51up3GHR9Y/xM5wOVzd1htJB5hpcpVsrwjodUrDbE73qNFoMsiv+h5J4672NXMKuoS59esPLLawxfTp07v/6U9/6t3Y2KiOOuqonTNnzqzLz8/n2Wef7Xrbbbf1b25uVt27d2+aO3fup9HbTZ06tV9JSUnz7bffvm7UqFEHDx8+fNfcuXNLm5ub1YwZM1adeOKJu/7zn/+U3HDDDQPB+BbMmTNnabdu3cI/+9nPev/973/v3tDQoMaPH7/1t7/9bZviRqWlpeEzzzyzHoyKo4cddtiuL774ojC27c8+++w+EyZM2Ny5c2cZMmRIQ0VFxd7Zs2cXjxs3znaRpmR5zitoVcZPBPpGFgFNGC4nr2Mo5HNEpMHugWNYo5RajBFc+howW0T0GFQSzpn+LgB/n5KeAj2o6H0W7x5HmIKWeZkOMPv1S0ZVzf87fUjGjukVWpZgEitLtlcEfLu4mWX7CJM8smZnMt1jLt9n2UC8LCXZKEs8UpUlYiHXFvM4WCnmiebbYMGCBZ2effbZ7vPnz19aVFQkEydOHPjnP/+5fMKECduuu+66/WbPnr10yJAhDevWrctLtq/du3eHli5duvjFF18smTx58qDPPvts0b333tvnvvvuqzv11FN3btu2LdSlS5fw888/33X58uWdPv744yUiwrhx4w548cUXS8444wxLX6mNGzfmvfLKK/vcdNNN62KXffXVV4WjR49u2a5fv34NphLvjnIOrMLI46/M/5/Qah1/S0TcclT+F0ZWlmuBKUA4KhvMa8DbIrI7wfYdkuXr3Tn9lSXPsGT3SW3mZTr38oI657WsgppSLhVZgkouyxKvImC2KOifrN0O+3XxzJqdyYJDrt1nASg4lG3PTKLYiwV1R/rdPNfI1HXRSnz6vPTSS6ULFy7scvjhhw8F2LNnT6hXr15Ns2fPLh41alT9kCFDGgB69+7dnGxf3/nOdzYDnHHGGTt27NgR2rhxY97o0aN33HjjjQMuuOCCzRdffPGW/fffP/zSSy91feutt7oOGzZsGMCuXbtCS5cu7WSlnDc2NjJhwoTBkydPXjds2LBUjdIJSaacrwBepTULiyd5L0XkLKVUCKgETjb/jgZGYGSEaVRKvQe8JiK3e9GGDoPFx6s4bwtDS95m8e5TsmoIO1tTygW1U+EHfp0LXRHQHrlUcMgPpSnoz3qy2Iusw8POmVa2M4eIqPPPP3/T/fff3+aBfuKJJxIUorDGKj3mnXfeufbss8/e9s9//rPsuOOOG/Kf//znMxHhRz/60dc33XRTUj33O9/5zn6DBw/ec9ttt1kmKunfv39DtLvLmjVrCgcMGOBIiU+WSvFAJzsDUEp1F5HNTrcTkTDwvvl3l1KqCENBPxm4EjgOOBbQynk6xPl4VW7by5Kfzk1tCDte+iorXEzZmOmgNbvs2NvE9t2N1NZtYURFt3bLs7VT4QV+nQtdEdAeQavmm21WyaA/68liLy76YJ6fzXNOom/LA3M9PbQOHHWP008/ffuECRMOuOWWW9b179+/ad26dXnbtm3LGzt27M6pU6dWLF26tDDi1pLMev63v/2t25lnnln/8ssvl5SWljaXl5c3L1q0qGjUqFG7R40atbu2trbLwoULO51xxhnbp02b1m/y5Mmby8rKwqtWrSooLCyU/v37N0Xv7wc/+EG/7du35z355JOr4x3z3HPP3XrJJZcMvu2229bV1dUVrF69utPYsWNtu7RA+tlaWlBKnYCR2vlsoDjNfVVgKOXjMPzdI9UEvkhnv5r4pDWE7SQNo4spG4MYtFZbt4XFX29HBC55aB6PXzm6nYIe1E6FH/h5LqYcMaWNr21EUfFCMa+t28K8lZsYPbjcssOm8Q4/laZseNazPfZCk3uMGDFiz09/+tOvTj755IPC4TAFBQVy3333fX7yySfvvO+++1afc845B4TDYcrLyxvnzJnzWaJ9derUSYYOHTqsqalJzZgxYxVAdXV1rzlz5nRVSsnBBx+8+7zzztvWuXNnWbRoUaeRI0cOAejSpUv48ccfXxWtnK9YsaLgD3/4Q99BgwbtGT58+DCAyZMnr586derGxx9/vKympqb4d7/73ZrKyso9Z5999uaDDvr/7N15fFT11fjxz0lCWINCWETEAMquYCUi8mjFpQpa1ypWRYstUKu0tS5UH6uiz8+Nqn1qlRaqVBC1VuqOQt1QHwElUUB2EQiKbLIJBMwy5/fHnYFJyDL7XXLer1deZGbu3Pke7szkzHfOPd/ufbKzs3nkkUdK4unUAkkm5yKSD1yDM7PdDac2fVcC+2mDk4RHSlq6hPe1Beck0XdxSlq+TGa8pm6++wqbzJ60Fot5q7ei4b/D5RUh5q3eelAyFvlQseT9r1DJ9sSHCre4/QEr2RUBY0n0iku2c+UT8yirCJGbk1XjBzZTN7/OSrr9/I5FXedeBF0qPzQ32BNHGzUL1dqtJQmjRo3aPmrUqINOFBg2bNh3w4YNWxp93W9+85utwFaARx55pEqHlREjRmydPHlylYndKVOm1DjRe8cdd2y+4447al1T56ijjipX1eKabrvyyit3XnnllTsjlx988MGNDz74YMJdCBNKzkXkDGAUcAGQi5NIz8NZ3fOfCexyIwcS+w+Ax3CS8c8TGZ9JjNe+wo5FJk9ai8XArvmIgCo0ysliYNf8g7YpuepqDpOmLG18EZqdDRXlHPbmI3D5RBdG7D6vfcBKtXmrt1JWESKktX9gM+njdtLk5ed3fedeOH0agsk+NKdIEu0STe1iTs5FpB0HZsm7cmBmuy0wRVWvSWIckU9dS4FioAhYlsT+jE88df109lS25psWzklTj4d7rTfP3saIxy+JaR9emvHvX9CK3h1a8t3ecv73pz+o9c2+ie7lsI3z+Obwk+lUsYomDbgZkdc+YMUinpncgV3zyc3JorwiVOsHNlM3txPsZHj5+V3fuRdBlq4PzX56bgbdJ598ssLtMSSq3uRcRM7CqSU/D2gElAOvAk8BbwDfh69LxjkcKGm5M/xTKiIfEm7dqKoLknwM40Fdcj9m6d6qK51mUU6X3HlAbMm512b8WzTOoUXjnFrf6CNv3vuu/iU7dDenPfILmh/i3eXiM8FLH7BSrX9BK54ZOdBqzl3mZtLk5ed3XedevP9xek+idJN9aDZeVt8iRKuBApxZ8oU4Cfkz0S0VU3HSiKrOBGaG99eaA/XnpwNDABWRbTjtHIcl/YAB0axRvf33Y1Nbt5VYO6vU1r6qtm2jRHqsN4mqThNCFLZ4AXgotn16TKtmBy0YVqMmupfT975I80MuTMs4UtHGLdZYkpWJD1ipjCXemdz+Ba1SnpRn6thkQqyx+GFWsqZYvDaBUF1t514E+TlmH5qNl4mq1n6jSAgIAQ8C41T1oBny8DZPqOrolA9OpBVwNXAbTscWVdUUZaSpV1hYqEVFRW4PI37j6mgdOm5n7bel6LHf3zl6/wqlWZTTu+lbnHrI39P/2AH3/rPLa2zj1vvkwzn18h4ujiw4/Fhm4UXWzcYYd4hIsaoWRl+3cOHCtf369UvLujbmgIULF7bp169f55puq6+s5X3gVOBWYLSI/BN4qrazVZMlIk1weplHSlx+gFOPLsBunJNFTcBEr1B6YNbc45L9tiED/NDGze+8kpR7fbGbutiJecYYU9XB7W+iqOppQHfgEZwZ9OuBT0RkkYj8LnySaNJE5HYReRfYDswCfg8cC/wfcBdOwt5aVX+ciscLiosmfMRFEz5yexhJa569nc9brOGDJmX0avoOzbN3uD2k+tVWxlO2mwdnLufBmcszO54aRE5Ey8p2vqJOpI2bV2JJhSDFAlXj6dI3f/9xjvDSYjd1mbd6K/vKq56Y52dBep5ZLCbIXnrppZZ9+vTp1b179959+vTp9eqrr9Z4FvSmTZuyBw0a1K2goOCYQYMGdduyZUvaKzjqTM4BVHWVqt4CHAH8FKfveB+cguCvAAXaikgyPdP/B2cF0EU4JTRnAa1U9TRV/X+qOkdVK+rcQy1EZIiIrBCRVSJyaw23F4jIO+EPHLNF5Ijw9aeJyIKon30ikp7i4AR9t7ec7/Ymey6uy8I16E0bfUVl1t4Ds+YpWG7ZLTtKy9hRGtdKvWlTeG4XJCt8olcCs+ZeiiVZQYoFqsYTfZwj/PItycCu+WSL8/VoEE7MC9LzzGIxsQhpqM7L6VJRkVBauF+7du3KZ8yYsWrlypVLn3rqqTUjR47sUtN2d911V4fBgwfvKikpWTx48OBdd95552FJPXAM6qw5r/VOIl1wOrj8DDgMJ0H/FpgKPKmqcX08FZHzgdmq+l3cg6l7v9nASuBHwNfAfOByVV0atc0LwOuqOkVETgeuUdWrqu2nNbAKOEJVS2t7PKs5b0B89H/2/rPLWfzhNxzzw45Wax5g0ecY+O3cAqs5T47Xy5q8Pj43eOV8lWRrzsfPH3/4rrJd2XcPuvurLMkipCHumnNXp7zcvMqxJ4z9pv49HGzFihW5Q4YM6XbssceWLl68uFn37t33vvDCC2vz8vJCHTt2PPb888/f9v7777e84YYbNh5zzDH7fvWrXxXs3bs3q6Cg4Ptnn312bdu2bSsHDBjQo0+fPqVz587Nq6yslEmTJq057bTTas3fQqEQrVq1Om7jxo0LmzZtWiUx7ty58zHvv//+ioKCgvKSkpJGp556ao+1a9cuTiS2aHXVnNc7c14TVV2jqrcBRwKXAm8B+cBNQNwDVtVXE0nMReR6EVlaxyYDgFWqulpVy3AWSLqg2ja9cVYgBedbgeq3g9PT7826EnNfq22W2sez1+aAwnO70DK/iS9mUU3siku28/h7qygucRbRS/ZbEjf1L2jF9acdbYl5grxe1uT18ZnEhDTErrJd2S+verndXXPu6hRJzF9e9XK7XWW7spOZQV+7dm2TMWPGbF69evWSvLy80B//+Me2kdvy8/Mrli5dumz06NHbR4wY0eW+++77euXKlUv79Omz9/e///3hke327t2btXz58qWPPvpoyejRo2ucFY+YMmVKqz59+pRWT8wBtm7dmlNQUFAO0KlTp/KtW7cmUykSk6QeIFxq8m/g3yJSgLNq6IgUjCtWbYC6poY64pTeRHwNnFhtm4XAxcCfgYuAPBHJV9Xowsef4tTde8oZD88G4J2bBie3Iw+cwHjbi4sAuP/ivi6PJHleiyWZNm5eiyUZQYqluGQ7w/42h0qFJo0OnETp1cVu6hOkY+NGLOk6+TtVsXjh5HSvPMfiWcDM67Iki7sH3f0VwMurXm738qqX2wFcePSFmyMz6Yk67LDDys4666w9AFddddXWRx99tB2wCeDqq6/eDrB169bsXbt2ZZ977rm7AUaNGrX10ksv7RrZxxVXXLENYOjQobt3796d9e2332a3adOmsvpjFRUVNbnzzjs7zpw584t6Y87KSkkL8XofJ1U7UtUSVf0Dzmy6n9wMnCoin+F0plkP7D94ItIB5+TUWTXdWURGi0iRiBRt2bIlE+Pdb/Ou79m86+CvChNVfSYuk1Zv2cPqLXsy/rgJq+PbhppicfP/Nhm+Oy51CFIs81Zv3Z/nRJ9E6ddvSYJ0bNyIJRUnf9ckVbGka3zxCNJzzEuiE/SIZBNzqL33PkBeXl5MU/J17SPiyy+/bHTJJZcc/eSTT67p06dPjQlVfn5+RUlJSSOAkpKSRq1bt06u2D0GKZ+aV83QmQCxWQ90irp8RPi6/VT1G5yZc0SkBfATVY1uFzIMeKmmHu/h+08CJoFTc566oWeWp9qZ+aBNYZ3jmFh1VT1P/d+aQBjYNR8RUK16EqXXF7sx6RM9O+3Fsiavjy9T4l3AzOsipSzR1901565OySboGzZsyH377bebn3nmmXueeeaZ1oMGDTooKcjPz69s2bJl5cyZM1sMGTJk95NPPpl/0kkn7d/uueeea3XeeeftmjVrVou8vLzK/Pz8KrPm3377bfY555zT7e677/46Mktfk7PPPnvHxIkT8++7776NEydOzB8yZEjaW8qlbObco+YD3USki4jk4pSnvBq9gYi0Edn/DLoNmFxtH5cDz6V9pC6bt3orZRUeaWdWR5tCL3vq1o94/Np3+eaLHXzzxQ4ev/ZdHr/2Xeb97yLv/N+aQOhf0IreHVrSqVVT+7BngAOz0wieLGvy+vhM/KJrzC88+sLNC69eWHzh0Rdujq5BT1Tnzp33/eUvf2nXtWvXPjt27Mi5+eabayxN+Mc//rHm97///RHdu3fvvWjRoqYPPPDA/pNQmzRpor169eo9ZsyYgokTJ66tft/x48e3W7duXeP777//8J49e/bu2bNn7/Xr1+cAXHbZZQUffPBBM4C77757w3vvvdeyoKDgmNmzZ7e8++67NyQcWIzSXtTuJlWtEJExOCUp2cBkVV0iIvcARar6KjAYuF9EFGeRo+sj9xeRzjgz7+9neOhpV707wsCu+eTmZFFeEQpEOzM3dOmbz9KPqr5ms7KFtr0OJferUvu/NSnVonEOLRrnWGJu9is8twvrlm7z7Ky018eXSX6fMQenpCUvN68yusY8UuKSl5tXmczMeU5ODq+88sqa6tevX7/+8+jLgwYN2rtw4cIaOwSOGDFi6+TJk7+q6TaA8ePHbxg/fnyNifbzzz9fEvn9sMMOq5w7d+7K2EefvEAn5wCq+gbwRrXr7oz6fTowvZb7rsU5qTRQaiuzeGbkQGtnloT9X9tGkSxh6GU96bLjSPu/NcakldfLmrw+Ptf4oZSzFmNPGPtNSENEEvFIgp5szXlDF/jk3BysphKW/gWt9v+YxOz/2vZT58N+9ElP/Q9pbP+3xhVBqW01JrB8WsoZUT0RTzYx79GjR9kXX3yxJJl9fPLJJyuSGoTL6vwfFJFjMzUQkzmREpZsCcaKfF5SeG4XZ6lD/NdrOlP82rnGGGOMyYT6Zs4XisiXwIvAy6o6t57tjQ94voQlt0XtX/F5XPNDGtO8ZS57dpbFd9KTj7/WjId1rsmcIPVTNt6lqlVa1FW/bIyJX33J+e3AhTi9wG8WkY3Ay8BLwHuqelAz9wz7P2C8y2NwTbu8xM9291oJS9e2zQ9c8Hkyeky3fNYu3BLfrLlHv9asclwaIkH5AAAgAElEQVRSoLaSqkxIdSxuS1U8XlhaPUjHpiHFMmHBBHaV7WLsCWMREVSV8fPHk5ebx3XHXZehUcYmSMfFBJ+o1t+aW0Q64qyeeTFwCk45zE7gdZxZ9VmqujfuBxf5BXAI8Jfa+oiHWyCOAbar6j/ifYxMKiws1KKiIreH0aAEZtZm3CF13LYzc+NIs8jMeaRzjc2cp199M+bvP7ucpR9tIBS1emNWttD75MM59fK6FmA2DVkkEZ+2bBrDew1n7AljD7rsy/diN7j4/i8ixapaGH3dwoUL1/br1+/btD6wYeHChW369evXuabbYjohVFXXA48Bj4lIa+B8nGT9EuBKYJ+IzMKZUX+t2iI+NRKRATiL9zxQW2IefuwyEWkF/FFEFqlqcSxjNsHnp1mbKmorYWkAPF9S1QB5YWn1oAjMZEEMRISxJ4wFYNqyaUxbNg3AEvNE+LiU0wseffTR/KKiouZTp05dN378+LbNmjULjRkzJi0LipxyyindNm/e3KiyslIGDBiwa+rUqetycqqm0qFQiJ///Oed3n333UOaNGkSmjx58tqTTz65NJ7Hibtbi6puA54CnhKRZsA5OIn6OTglMOUi8gHwoqr+tY5djQD2AA/G8LDjgd8AIwFLzsPOeHg2AO/cNNjVcaTCyClFbN61j7vO6xNTwqaq7Crbtf8PQvVZGzf/KN724iIA7r+4b80b+CgxrzeWBLhVUpWOWNwUazz11ZhHugxFZs/dWFo9CMcmMlmw/auhiMB9Fx3rj8mCOtR3XCIJeuR9GPBsYu7p55jPSzm9ZOzYsTUuVpQqr7zyypetW7cOhUIhhg4detTkyZNbjR49ukp3gxdeeOGQ1atXN1m7du3i9957r/l111135KJFi2rsxV6bpFopqmopTo/w6SKSA5yJk6ifD5wO1JWc/xB4V1W/i+FxdonIu+H7mLCWTRu5PYSUKC7ZznsrNlEZgiufmBdTqUMqZm3SVWt7aLPchO/rNRaLd6UyHreXVvf7sYmeLDi6sj0DO5zomcmCZNR3XCLfVkYbP3+8JxN0vz/HvG7NpcN6AHR54V8paWE4YcKE1n/961/bl5eXy/HHH79n6tSpJTk5OUyfPr3lnXfe2bGyslJat25dUX1xoBtvvPHwFi1aVN5zzz2bBgwY0KNPnz6lc+fOzausrJRJkyatOe2000pnzJjR4qabbjoSnFxizpw5y1u1ahW644472r/00kuty8rK5Nxzz93xpz/96Zvq42rdunUIoLy8XMrLy6Wm5/krr7xy6JVXXrk1KyuLM844Y893332XU1JS0qigoKDWKpHqUtbnXFUrgJnATBG5FjipnrsUUG1xoHp8AfwoweEF0kvXZeZkrXSbt3orkVMf4jlJMNlZm8iKntVrbbv0axNfANX8fkjPpO5fhctfa6Y0FpcFKRZIbTyR2fPFH37jytLqfj82VScLHmbVZmCz/0s86jouddWcg/dm0P3+HGtIPv300ybTp09vXVRUtLxx48Y6fPjwI//2t7/lX3zxxTvHjBnTefbs2ct79uxZtmnTpuz69rV3796s5cuXL33zzTdbjB49ussXX3yx5OGHHz7s0UcfLTnrrLP27Ny5M6tZs2ahF198seWqVauaLFq0aJmqcuaZZx795ptvthg6dOhBX3WffPLJ3RYtWtT81FNP3XnNNdcc1BN4w4YNjTp37lwWudyhQ4cy15LzaOqcZTqnns0aAfF0e6kE6j0Qxn8ifdfjXd4+2VkbT9baBujkT+MvtrR6cvxU4pEKIkJebl6VDyCRDyh5uXmBjdtUFZkx3/f55y2iLyczgz5z5sy8xYsXN+vXr18vgH379mW1a9euYvbs2c0HDBiwq2fPnmUA7du3rzeHvOKKK7YBDB06dPfu3buzvv322+yBAwfuvvnmmzsNGzZs2+WXX779qKOOCs2cObPlBx980LJ37969AUpLS7OWL1/epKbk/P/+7/++KC0tlYsuuqjra6+91vKiiy6qtwIkXm6uELoF6BrH9l0BO3s4yon3vg3Ax7ef6fJIktO/oBX9jjiUbXvKeOAnfWOuOU921iZdtbbXPu2cFvG3q/ontR8vsFi8K9XxuLm0ehCOTeQ9ae/XwwFoesQ0z5Z4xKq+43LdcddVKdmJJOhejDcIz7GGQlXl0ksv3fr4449XKcZ/9tln62hrU7Pqz0UR4b777tt44YUX7nzllVcOOeWUU3rOmDHjC1Xlhhtu2HDLLbfElGc2a9ZMzzvvvB0vvfTSodWT8w4dOpSvXbt2fx3Vhg0bcuOZNYd6VghNsyLgRyKSV9+G4W1+BMxP+6h8pLS8ktJyt1vNp07r5rkxnyhY26zN8F7D45q1KTy3C5IV/sOSolnz7aVlbC8tq32D2kpVPHhmfr2x+EiQYoFgxeP3WKInC9o17kL/Nj9keK/hTFvmJOixtCz2oliOS03Jjxf5/TnmVV1e+NeKLi/8a0WTY4/d3eTYY3dHLiezzyFDhnz3+uuvt1q/fn0OwKZNm7JXrlyZO3jw4D2ffPJJ3vLly3Mj19e3r+eee64VwKxZs1rk5eVV5ufnVy5ZsqTxgAED9t57770b+/btu2fx4sVNhg4d+t3TTz/dZufOnVkAa9asaRR5/IidO3dmlZSUNAIoLy/nzTffPKRnz54HtRE///zzdzzzzDP5oVCId955p3leXl5lvMm5mzPnzwMXAI8C19Sz7f/i9EN/Pt2DMmEpWrGyuGR72trmpWLWxpVaWzsz35hAiZ4s+HRfJwAr8TD7pfPvYBD1799/3x/+8If1Z5xxRvdQKESjRo300UcfXXfGGWfsefTRR9dedNFFR4dCIfLz88vnzJnzRV37atKkifbq1at3RUWFTJo0aQ3A+PHj282ZM6eliGiPHj32XnLJJTubNm2qS5YsaXLCCSf0BGjWrFnomWeeWdOxY8eKyL6+++67rHPPPffosrIyUVUZNGjQd7fccsuW8D7bgtMtZtiwYTtnzJhxSEFBwTFNmzYNPfHEE2vj/T9wMzn/F/A74OrwIkf3AHNUNQQgIlnAIOAOnC4wn4TvYzIhBStWZmKp9lTM2litrTEmWZHJgp9+Ng/wdomHyZxM/B30glR1aYkYNWrU9lGjRh10suWwYcO+GzZs2NLo637zm99sBbYCPPLII1U6rIwYMWLr5MmTv4q+bsqUKVUuR9xxxx2b77jjjs21jalTp04VixcvXlbTbdEtHLOysnj66afX1bafWLiWnKtqSEQuAt7CSb7PwFnMaFN4k/ZAE0CApcDF6tfvBhsoN5dqj4ebtba+kqJvU4wJKr+UeJjM8cvfQeMtCSfn4TrwFqq6IdF9qOo3InIi8HucBYbaA52jNtkE/B0Yr6r+WbnFAIl3YTEelYJvU4wxpiGxv4Pu+eSTT1I6m59JcSXn4RVB7wKuBDoAGtmHiAwA/gDcqaoLYt1nOOm+A7hDRI4O7xdgg6quimd8xltsqfaGrSEtZW6qsmNvjMP+DppExJych2fKPwT6AouB74AeUZsswVkVdDkQc3IeLZyMW0IeIG4t1e5HQUpoIkuZR2puI90s/LyUuYmNHXtjqrK/gyZe8bRS/ANOYj5SVftS7eRMVd0DvI9TO278zkft/oJgwoIJVVquRRKaCQsmuDyy+EUvZR6JKdJmblfZLt+2lTP1s2NvjDHJi6es5SfAf1R1cvhyTe+ya4HCWHYmIkvr2SQE7AAWAlNU9ZMYx9lgHN0ujYlyhk/wOz5AswrxxhKd0ABVFlQa3mu4qzPoiRyXqkuZT9sfl9tLmQfpOQbejCfRY+/FWBJlsXhTkGIxwSexzmSIyD7gz6r6+/Dlu3Dqy7OjtnkQ+K2qNolhf6E4xqnAOFX9nzjuk3GFhYVaVFTk9jCMD0XPMEa4ncweJM5uLapK36l9919edPUi78TSgLjRY9mOvTH+ICLFqlplUnXhwoVr+/Xr56sV2Zs1a/aD0tLSz5Ldz7hx49o//fTTbbKzszU/P79iypQpa7t3737Q6lX79u2Ta6655si5c+fmiYjedddd60eMGLEjnsdauHBhm379+nWu6bZ4Zs53A23r2aYLEOsB7VXP7VlAG5xe578DxonIHFV9J8b9G+MbkRnH6OTcU4k5xPVtSuTDRjS/L2XuR270WLZjb4zxq/79+5fedNNNy/Ly8kIPPvhg29/97ndHzJgxY3X17W677bYObdu2LV+7du3iyspKNm/enNLW5PHsbD7wYxFpUVNbQxE5DBgKvBnLzlQ11hY3H4rI88DnwHWAJedhJ977NgAf336myyNJ3rVPFwPwt6v6uzyS5CUSi1cTmmRiiZTlRJfpgHsfOoL0HIPY4sl0j+VEj32Qjo3F4k1BisVLJt/yYd+9u8obVb++aV6j8p//8ZRFiezz/fffbzZq1KjOCxYsWFZRUSHHH398r+eee+7L7t27lw0ZMuTonTt3ZldUVMidd975zfDhw6vMVu/cuTOrpm1WrFiRO3To0G4DBgzYXVRU1KJ9+/Zls2bNWtWiRYsq5SPnnXfersjvJ5988u7nn3++xt6Xzz33XJuVK1cuBsjOzqZDhw4VNW2XqHiS80eBGcDrIjIq+gYR6QY8ATQNb5dSqrpWRF4BTkv1vv2sT8eWbg8hZY4vONTtIaRMvLF4NZmFxI5L9FLmkbF7YSnzID3HILZ4Mt1jOdFjH6RjY7F4U5Bi8ZJOvVrvWFW8uU2oUve/uLOyRTv1bh1XiUe0U089tXTIkCE7brjhho579+7NuvTSS7eecMIJ+8rLy5kxY8aq1q1bhzZs2JBz4okn9rziiit2ZGUd6G3SrFmzUE3bAKxbt67JtGnTVg8aNKjknHPO6Tp16tRW11133bbaxjFx4sS2Z5555s7q13/77bfZADfeeOPhc+bMySsoKPh+0qRJ6zp16pSyBD3mmnMAEbkHp2uLAt8DjYEtOOUuAtyuqvenanDVHvt/gLGq2jgd+08Fqzk3iQpi+7kgtYb0M7dqzu3YG+N9ydac79q6r9G0u+YeG6o4kJxn54heec9Ji/JaN0k4Wd23b5/069evV+PGjUOffvrp8pycHL7//nsZNWpUp3nz5rXIyspi7dq1TVauXLnoyCOPrIjUnNe2zd69e7POOuus7iUlJYsBbr/99sPKy8tl/PjxNS6kOWHChNYTJ05sN2/evBVNmzatkihv2LAh5/DDD+83efLk1ddcc832cePGtV+wYEGzl19+eU08Maaq5hxVvVNEPgR+AwzESc4bA/8BHlHVt+LZX5xaAPvSuH8TZB5fev66466rksBEZhz9nNDYUube4EaPZTv2xjQMeflNyo8+vt23kdnzrGzRo/q3+zaZxBxg06ZNOaWlpVkVFRVSWlqa1bJly9DEiRNbb926Nefzzz9f1rhxY+3YseOxe/furdISvK5tcnNz9yfZ2dnZWv2+ES+//HLeQw891OHDDz88KDEHaN++fUWTJk1CV1999XaA4cOHb5s2bVqbZOKtLu4C9nACns4kvDZnAitdeFzPOnbcLAA+H3e2yyNJ3mUT5wLw/C9PSs8DxLr0fAqS+ERj8WJCk/Bx8eCHobQ/xzIsSPFYLN4U9FhKrroagIKnp6bscdz4psptAy84asOqTze3ARCBgRcc9U2y+7zmmmsKbr/99m/WrFmTO2bMmCOmTp26bufOndlt2rQpb9y4sb722mt533zzTW71+8WyTV0++uijpr/+9a8L3njjjS86duxY4weMrKwszjjjjJ0zZszIO//883e98cYbLbt167Y30VhrEs8KoVcAi1R1cR3b9AH6qeqzqRhceJ8tgAeA3sCdqdqvMTWKNYk3dUvT/2M6/pga9zx160fs2fE937T4HoDHr30XgOaHNmbEA//l5tBMhgSpBMqN7kheEJk9Xzl/U9tUzJo/9thj+Y0aNdJrr712W0VFBccff3zPV199NW/kyJHbhg4denT37t179+3bt7RLly4HVVPEsk1dbrnllk6lpaXZl1566VEAhx9+eNm77767CqBnz569ly9fvhTgkUce+fqKK67ocvPNN2fn5+dXTJ06dW0yMVcXz8z5NGAcUGtyDlwI3APUm5yLyBv1bJIF5AN9gCY4s+Z/jmWgxhhjvK9L33yWflS15DMrW+jSL6XfEKeNfVhMjlvn2kSOW+n8+VUuJ3scM90dyUsGXnDUhvUrd7RMxaz5mDFjto4ZM2YrQE5ODosWLVoeuW3BggXLa7pPpMd5hw4dKmrb5osvvlgS+f2ee+7ZVNM2c+bMqbVCI5KYA3Tv3r2sqKgo1q6DcUtpX0achDrWM0yHxLhdBfA88JuaWjgaY4IvXX9MjbsKz+3Csrkbq1wnWULhOZ3dGZDJGC+vjJyoTHdH8pK8/CblIx74r7omb00cUp2cdwdibZ8ztJ7bQ8BOYImq7klqVMYYYzyn+SGN6XXSYfCp0+QgK1voNagDzQ/xbFMuwD4spkJ0m81py6btT9LTtTLynqXLqAwpxSU96R8+Tqk+bv0LWvHMyIENrubcpF6dybmITKp21fkickQNm2YDR+L0Ia+vXAUAVZ0V0wiNiUOkhrW65tlPMqLtLw6+Q26LDIzKJKsgTX9MTQbVcpJwYXZHkIdBbda8ocnUysjFJdspLXPKoK98Yl5aa8Hd6I5kgqe+mfORUb8rcHz4pzZFwI3JDqomInIaMFpVL0/H/k0wRGpYQ5UHqquysoUuJx8Llx+0lsDBclvU3mXExM7+H011tZwM3LxyPc1b5rJnZ5kvZs3BPiymSiZWRi656mq+37GX5u1PAeCe9x7j+wWT4bUX7LjVLhQKhSQrKyv2hXBMXEKhkOBUiNSovuS8W/hfwTkh81HgLzVsVwlsU9XvEhlkbUSkLTAC50PC0eGrLTk3tdpfwxqVnMc1G+eBnueBkKb/R/tjGkx5+U3Yt6fCZs0bkEyujNyy6YHV5UWkymVTo8Vbtmzp3bZt252WoKdeKBSSLVu2HEIdDVbqTM5V9cvI7yJyL/BO9HXpIiJnAqOB84FGOB8O5gF/T/djG3+L1LBGZs+9UMMapFZhxqRDVnYW7bu09MWseTT7sJg4ESEvN69KjXmkBj0vNy9l75GRY6S/nUxlSOk67WmOsbKTOlVUVIzcuHHjExs3bjwGp9GHSa0QsLiiomJkbRvEfEKoqt6RkiHVQkTaAz/HmSXvjJOQA8wFRqnq0lru2mCd0Dk4bzBn9GqXsn1Fz567UcMaHYtbrcJSJZXHxW1BigWCFY/Fkrx0TAKkO5ZMrox8SpnTstPqwevXv3//zTiTo8YlolrzNxYicnj4142qGoq6XC9VjbnPpYgMAUYBP8aZJa8AZgFPAS8AT6jq6Fj3V8v+/4xz0uoTqvpAtdsLgMlAW2AbMFxVvw7fdiTwBNAJp+b+HFVdW9tjFRYWalFRUaJDNSn0/rPLWfzhNxzzw46cenkPV8ZQ19e26epIYIxnjTukjttiOB/E1MrvkwDGPSJSrKqFbo/DVFXXzPnXOFPvvXHqzb8mth7mWs9+ARCRPwC/wOnyIji1N1OAaaq6KbxNDA9X52NkA48DP8IZ/3wRebXaLPxDwFRVnSIipwP3A1eFb5sK3Kuqb4VXKq21eN94S+G5XVi3dJurNayZbhUWJMnMAmaqjKihlislfBJkkE4SrqXzDLktMn7eShD7hRvT0NWVRD+Lk2jvrHY5Ve7BSXb/DvxdVYtTuO+IAcAqVV0NICL/BC4AopPz3hzoMPMe8HJ4295Ajqq+BeDFBZCOHed0o/x83NkujyR5l02cC8DzvzwpJftrfkhjrvp/g1Kyr3hFx5KpVmHpkurjEotkZgHruu/7H/8ASE0sXpipdOPYJKWOpNV3sdTSeYay3WmNpbZWse0P/S+GX5zaSQBV5aeT5gFOLH5P8n33HDMNWq3JuaoOr+tyimQBFwN7RaRCVRemeP8dga+iLn8NnFhtm4XhMfwZuAjIE5F8wgsqiciLQBfgbeBWVa1M8RgTNvSYw9weQspc0r+m9vnuSaZFWnQsmWgVlk6ZPi7JzALWd99UxZKKmcpUzLpn+tikc+Edr73+k5HOWGptFduvLT9L4SRA5MPnJf2vAAhEmUyQnmMm+FK9QuhBROQ84Lwa6sa74XRk+RnwW+A3IrIQp9Z8mqpuS/fYwm4GHhOREcAHwHqc1pA5wCnAD4B1wPM4bR2fjL6ziIzGiYMjjzwyQ0N2jL+kX0YfL50uLezk9hBSJhJLJluFpUumj0sypUCZKiNK9nFSNeue6LGJ54NBccn2/asdtkno0WITxNd/OtTaKnZoQcomAaI/fA7vFZwymSA9x0zwpT05x1m06BeEE9iIcEvG34vI7cCF4dvPAP4EjBeRmFYarcd6nJM5I44IXxc9jm9wZs4J15X/RFV3iMjXwIKokpiXgYFUS85VdRIwCZwTQlMw5ph9ucX5avWotj6s2axm254yAFo3z3V1HKmYHYyOJROtwtLJjeOSTClQXfdNZSyJjjGV9cGJxBPPB4Piku1c+cQ8yipC5OZk8cz/+zP9C1qlZeEdr7z+UyGdsdTUKrbnSYfx2Mo/p2wSIPp9aurnLzL18xfJyin1/bkyQXqOmeBzvX+lqlao6nRVPQs4CngA2IqTsANcLCJ/FJGeCex+PtBNRLqISC7wU+DV6A1EpI2IRP4fbsPp3BK576HhhZAATqdqrbrrLnz8Iy58/CO3h5ESv5pWzK+mpeO0g8yLjuW6466r8gct8ofPL18Nu3FcaisFqq2zVKz3TWUsiY4xcvyH9xrOtGXT6Du1b8Lde+KNJ/qDQWSskSRuV9mug8Y+b/VWyipChBTKK0LMW7015seKV1Bf/+lQeG4XJCv8fpIlnHBulxonAYb3Gp7wJEBkH/vWD2ffeqei1e3EvPrzM5b3g2hBeo6Z4MvEzHnMwm0KbxeRO3F6bI4CzgJuAm4UkTmqekoc+6sQkTE4rRmzgcmqukRE7gGKVPVVYDBwv4goTlnL9eH7VorIzcA74rwjFWOLIAVeOpblrv4Hza8zT5mQTClQffeFH7o+Rkjum4H6RJehVO/nHG85zsCu+eTmZFFeEaJRThYDu+YDtvAO4Grnmcjs+eIPv9m/wFqq+4Uf+PDZbP91bp4r44UTsI3JJE8l5xHhky5fAl4SkU44SfrPgbjbb6jqG8Ab1a67M+r36cD0Wu77FtA33sdsqOpKDIyJRTKrBtZ3Xy+MEdJ3kvBBZSgjB9aaoMfywaB/QSueGTnQXtM1qatdYrgrSDrV1Co2VZMA0R8+2ze7g055nTi+V6lr58q43irSQ20zTcPhyeQ8mqp+BdwpIuOAc1wejqlFLImBn9jsoHuSmQWs677vf5y6pCnRMabqJOGavuKvqQyl+msw3g8G/Qta+fp1HFTpbBUb/eHz033OKVtuniuTqRO9a1VH20xj0sXzyXmEqoaA190eh6lZLImBMbFKZhYwU2VEiTxOsrPucOAr/kiZTiTh3iU55Ob0PqgMJSII3YNMZkQ+fP70M6fPebJlMslKZymYMV7km+TceFtt9anGmKqS+WYg+iv+vF1d6JTXqUrCPe0XJ/Lxmm211pxHPhhc9pclrONnjJ06BfBP9yCTOV46V8bv60UYEy9Lzk1KWH2qMbFLNPGJnmmfVLKJTaWbWFqt20th59a13j/ywWAdP6uyP0twjFd54RsfBaSOy8akmiXnJmWsPtWY9Isk1JNmPrb/ulgTlHSu8mlMOqSiFCwZEw49hF1ZwthtOxCcxHx860PJCynWJ8akSyaS83XAnAw8jjHpYWfrGw/xWps7Y9It1a0iY6Wq7GrUmGktmgAwdtsOxrc+lGmHtGT47n2+XS3VeF+dybmI/A14C5itqgmtQKGq/wD+kch9Td2GHnOY20NImUv6H5HwfdM++xfn2frJxOI1Fou3RH/F/8NeYzinyzmsDsXe5i4dffxTIQjHJsJiSY9ka+ATiUVEGHvdSgi/5qYd0hLIYKcY02BJXatsiUgI51scBRYB74R/PlDV0oyM0EcKCwu1qKjI7WE0OGlPNMYdUsdtO9PzmMbUIhULsngtOTfGy1SVvlMPLHmy6OpFgUnMRaRYVQvdHoepqr7kfBTOsvWnAe3CVytQDnwCvI2TrM8LLxzUoGU6Of9yizNze1Tb9K9Kl27b9pQB0Lp5bsz3qV4/2+yEE4A0JBxxJueJxOJVFos3qSrbS8sBJx6/f70epGNjsXhTorFEf1sVEaSZc0vOvSmrrhtV9e+qermqHgYcC9wAvAaUAicD43CWvN8uIjNE5EYR6ZfIQERkgog8LiJta7itXeT2RPYdVBc+/hEXPv6R28NIiV9NK+ZX04rdHkZKWCzeFKRYRKRKPH5PEoJ0bCwWb0okluqdYhZdvchpWbpsGuPnjz9oMTBjUiXmE0JVdQmwBHhURLKA44EzcWbWBwFDgSE4M+uJnGh6bfi+fwa2VLutVdTt1yew70D62Umd3R5Cyow6pWvc9/Fq/WwisUQUl2z3VDvKZGLxmiDFAsGKx2LxpoYeSyY7xVT/9svv34aZ5NRZ1hLTDkQOxUnMb8WZXVdVzU5gP78M//qcqn5X7bZDgJ/i7HxiUgNOI6s5d0fak/MMdWspLtnOlU/Mo6wiRG5OFs+MHOiJBN0YYxqydCfOqTiPJFFW1uJNcc9wi0gznHWjTwfOAPrh9OMP4dShv5fIQOpKulV1J+DZpNwts1dsBmBwj3b1bOl9ydTPp33GPM4EPNFY5q3eSllFiJBCeUWIeau3up6cB+m8hiDFAsGKx2JJn2QmL7wWSzKSiSWdq6VGr/oLVFlkaXiv4TaD3kDVm5yLSCOcspVIMn5C+H4KLAD+hJOQf6iqu9I3VFPdr5/7DIDPx53t8kiS998vfg7A8788yeWRJC/RWAZ2zSc3J4vyihCNcrIY2DU/HcOLi7VrlPAAAB/KSURBVB0X7wpSPBaLN1ks6RddKjNt2bT9SXqQTjo18auvz/lbOIl5k/BVi4DHcZLxD8Iz2gkRkVtxur0Uq51VYQz9C1rxzMiBnqo5Nw6rBzV+Y6vB+kckQY/uCGOJecNWZ7cWnJnyxsALwDGq+gNVvVFVX0smMQ+7D/gY2CoiL4rI9SLSM8l9GuNr/Qtacf1pR1ti7iETFkyo0pkhUg86YcEEl0dmjAmCA6v+HmDdYBq2+spa3gNOAoYBl4rIUuDd8M/7qrojice+H6dUpj9wIXABgIhsCO//beAdVbX10Y0xrrB6UONXXu1mZaqq3q4x+j0GbAa9oaozOVfVM0SkMU5pyxk4yfSvgF8DIRFZiJPAv4tT5lLLOuc17vt2ABFpAZwatf9jgeHAleHbv+DAyqTvqer2eAI0xphEWT2oMSadMtmu0fhHvSeEqur3OAn4e1AlmT49/PM74EagQkSKgXcjiXcswgn9jPAPIpKPsyJppId6d6AbTp/zENAo1n0bY0yyrB7U+JnNmHvfdcddV+VbuMh7jr3HNFz11ZwfRFV3q+oMVb1JVX8AtMWZ5V4GnIjT7zxhqrpVVaer6rVAD+AiYDFOu8a4x2uMMcmwelB/qX5c7DilVslVV+8vlTGpk852jcZ/ElnJEwAROZ4DpSgnA81SMaDwSaGRto2n4qwOKsAmYHYqHsMYY2Jh9aD+ksnFXKyDjzEmXWJOzkWkFweS8VOBQyM3AXs5UBf+TjwDEJECDiTjpwGHhff5LQfKad5T1WXx7NcYY5Jl9aD+kcmTd+v6EAA/SMljeI21ZjQmc+rrc/4LnMT5NKB95GqgHJiLk4i/C8xV1bJ4HlhE/h7ed+fwPrcD73MgGV8cz/4aop+d1NntIaTMqFO6uj2ElHEzllj+YMYz42fHxbv1oHZsqsrUybv1fQgYeUoXhGB8aLPnmDHukLrq8UQkFP5VgYU4ifg7OJ1Z9iT1wM6+Q8B04I/Ap35fjKiwsFCLiorcHkZgFJdstwV54lRfcp7Jr/2NcYOq0ndq3/2XF129KOUfpKLLnSIaSgcfmzEPFhEpVtVCt8dhqqrvBMu/AZcCbVX1eFW9WVXfTDYxD1sTfvxhOAn/KyLyOxE5LgX7bhBmr9jM7BWb3R5GSny5ZTdfbjnQibO4ZDtXPjGPh/+zgiufmEdxiX86aFaPJRMiJ2mVzp9P6fz5NZ60FT3jFzmhMZJg7CrbVeOJc27EUptkT/TzUiypEKR4UhVLpk7ejZ6lj4gk5nZcvClIsZjgq6/PeVxTaSKSBZynqq/Ut62qHiUiR+LUmkfqzX8MqIhEl7i8q6pL4xlHQ/Hr5z4D4PNxZ7s8kuT994ufA/D8L08CYN7qrZRVhAgplFeEmLd6q29mz6vH4hWJfO3vlVhSMePvlVhSJUjxpCKWTJ68W9uHgLEnjA38cfHrjHmQjosJvoS7tUQLn9Q5ErgG6ABkx3I/VV0H/CP8E+nUEn3S6UU4yfpmnE4t76rq31Mx5iC4dWhPt4eQMmOH9KhyeWDXfHJzsiivCNEoJ4uBXfNdGln8qseSCbGuBhhvz243YqkuVSf6uRVLurp6JBOP10rGUnFsMnXybn0fAm45exRBqWzxwuu/LvG8trweizHR6qw5r/OOItnABcBonAWDsnBq099W1aSncsV5hR2Hk6hfjbNyaEhVU/KBIh2s5jy1MpFABK0dWvXkvHo8oVCIPxb90Xe1sn6t8fVijX+kZKysIkRuThbPjBzI8UceGpjXQSZe0148rg2NHYPUsJpzb4o70RWRrsAoYATQLnz1t8BE4ElVLUl2UOFVQk+P+jk6clOy+w6SZz52/quvPLHA5ZEkr7hkGwD9C1rvv65/Qau0zuql6829plgyJXrGvHp8oVCIy16/jOXbl8f8tb+bsURLxSqdmY4l3a39Eo2nesnYXz59nF6bGrma5KTy2GRiMZe6Ovh45TWTCl6NJZHXlldjMaYmMSXnIpKDU2IyGqc2PAsoA14EfgK8oqp3JjoIEcnDKWOJJOPH4CTikVfXKhLooR50D7y5HAhGcj5+5gogc/WA6UycMh1LTWqK749Ff2T59uX0bNWTWwpvielrfy/EAnXX+MZ6nDIdSypa+9U1C5xoPFVLxoTWeZVMW/Y8kN7e4HXxyvMsHrV9CPBjLLXxaiyJvLa8GosxNamvz3k3nFnynwFtcJLlYuAp4FlV3R7VbjEuIhKpLT8d6I9Tpx55Ra3Hadv4LvCOqn6dyGMYU5tM9UR2S13x3VJ4C1lZWVW283K8fl6lM5kZ/3R9s9O/oBXPjBy4v2Ts+COHMn5+k0C+DkxwpeLbNGO8qr5WiiuAm4BK4BHgWFU9QVUfV9Vke9u9BdwKnAh8B7wEXA/0VNVOqvozVZ1iiblJl7raoQVBbfFFEvPo7bysthP9hvca7vlVOhNt7ZdI28t49C9oxfWnHU3/glaBfx2YqpJtSeoVmWqbaYwb6kvOwTnJ803g36q6JIWPPQsYizNr3lZVL1HVv6rqyhQ+hjG1Cvqbe5Diu+6466okjJGE0ssnflWf8V909SKG9xpeJeGuTfQHkGnLptF3at8q3xykMnEO0vPE1G3CgglVjm3k2E9YMMHlkcUnmdeWMX5QX3J+B7AOp0XiRyKyVETGikiHZB9YVYeq6sOq+lmsK4OKSN/6tzKmfkF/cw9ifJk40S+Vkp3xz8SMdhCfJ6Zm6f42JpP8/G2aMbGobxGie4F7ReRsnNrz84AHwtf9B5iS7gGKSDPgcpyTUfuTot7spmHLVE9ktwQ9Pr+oq6tHfVJxEmx9/PQ8CVrb00wL2nk2yby2jPG6mBJdVZ0FzBKRdsDPcRYcGgoMwSl7OU5E+qtqcaoGJiLH4yTklwMtcE4WtZIXkzJBf3MPenx+kciMfywnwaaKH54n1tM6NYJ2EqXfvk0zJlax1Jzvp6qbVfUBVT0a+BEwHSgHCoFPROQzEbk+0cGISAsR+aWIFAHzcWbrc4BngMGqGpwlMY0nBP3NPejxBVWmv7b38vMkSOUYbrPzC4zxh4RLRFT1HeAdEWmDsyDRSKAf8CjweDz7EpETcGbJLwOac6BlY3/gGVUdneg4RWQI8GecVo1PqOoD1W4vACYDbYFtwPBIhxgRqQQ+D2+6TlXPT3QcxhgTDz/MaGdC0Mox3OLnlqTGNDRJ12+r6rfAQ8BDIjIYJ0mvl4i0BIbjzI73xUnIN+KsNPqUqi5JtId61GNk43xQ+BHwNTBfRF5V1aVRmz0ETFXVKSJyOnA/cFX4tr2qelwyY0inW4cG54uEsUN6uD2ElLFYvMmPsdQ1o+3HeGpTXyx+Ksfw6nFJ5PwCr8aSiCDFYoJP3Po6S0R2A01xymJew1nYaKaqVkZtE8KZ7U5o5lxETgLGqerZ4cu3Aajq/VHbLAGGqOpX4rw77VTVlpExqmqLWB+vsLBQi4qKEhmqMcaYWkTP+kbYzHli7MRaE01EilW10O1xmKrc7HzSDAgBfwH+V1XXp+ExOgJfRV3+GmfRo2gLgYtxSl8uAvJEJF9VtwJNwvXvFcADqvpynY+2YgUMHlz3iH78Y7j5Zuf3wYNhxAjn59tv4ZJL6o8oavtNZ/2YZVeMYvDNv3Ae+5e/rP/+N90E5513YPv77oNBg2DOHPjv/67//tW3nzgRevSA116Dhx+u//7Vt58+Hdq0Ye1Dj5E//Z/kNannKRnenqeecn5mz3auf+gheP31+h8/evu5c+Hf/3Yu33abc7ku+flVt9+6FSZNci6PHg0rnfOVd+2rADg4lu7dq26fnw/3hz8n/uQnzv7qctJJVbc/6aSqz6X6JPDcqxJL9e2rP5fq4/Jzb/GdD/L9Ud3ov+ijKs+9/c+l+njsuVd8u1Oh1//eW/c/92rl8edera8ZnI4Db/ywLdOOWs6oDhfx6/s+4N/nFXD3smm0LtnCyMeLqDe1zOBzr8ZYannfc+O5J9Wee1LHc2/XvgoqWrWi1Zuv7d++tve9WnnkuVdcso3ul51P3rUjE/6b68f3vaSfe8YVcZ0QmmJPAqXAjcBaEXlTRIaJSG6Gx3EzcKqIfAacCqzHWREVoCD8ifIK4H9F5KjqdxaR0SJSJCJF5eXlGRs0wLptpUwvDsYCqm98vpF120rdHkZKrNtWarF40BMfrmH8zBVuDyNlxs9cEZh46nqeCdAkpwnDew3n1z/4NQL8pNtPGN5rOM0bNa8/Mc+wIL1m1m0rZeWm3W4PIyXGz1wRmONigs+1shZwurMAV+LUnR+PM0myE3gOp4f6PNJc1lLDeJar6hE13PYU8LqqTq/t8TJd1jJ7xWYABvdol7HHTJcvtzh/AI5qG3MVkWdZLN4UpFggWPHEEotfyjEa2nHxiyDFkkpW1uJNribn0UTkOOBanL7meTiJOsBs4ApV3ZTAPnNweqOfgTMjPj+8ryVR27QBtqlqSETuBSpV9U4RaQWUqur34W3mAhdUO5m0Cqs5N8YYY4xfWHLuTW6WtVShqgtU9VqgA85MehHON5qnAV+JyEsicm6c+6wAxgCzgGXAv8JdYO4RkUhbxMHAChFZCbQH7g1f3wsoEpGFwHs4Nee1JuZueGjWCh6aFYyvtd9euom3l8b9+cuTLBZvClIsEKx4LBZvsliMcYebJ4TWSFVLcerRnxSRY4Ff4tR8XwCcj9OvPJ79vQG8Ue26O6N+n46zmFL1+80Bjo13/Jk0Ze5aAG4+2/8tov7+4WoAzuzd3uWRJM9i8aYgxQLBisdi8SaLxRh3eGbmvCaq+rmqjgEOB36OU1pijDHGGGNMIHk6OY9Q1X2q+pSqnuz2WIwxxhhjjEkXV5JzEWnqhX0YY4wxxhjjJW7NnK8Rkd+KSON47ygi/UTkFZz+5MYYY4wxxgSGW8n5LOARYIOI/FVETqtrJlxEuorIr0RkLvAp0A+ng4oxxhhjjDGB4Uq3FlX9mYg8htO2cHT4p1JElgEbgO1AEyAf6AG0wWmruBm4HfiTqn7vxtiNMcYYY4xJF9daKarqfOAsEekG/AJnoaDjOLh94RbgReDfwL9VtTyjAzXGGGOMMSZDXO9zrqpfALcCiEgzoCPOjPleYLOqbnBxeMYYY4wxxmSMqKrbYwiMwsJCLSoqytjjzV6xGYDBPdpl7DHT5cstuwE4qm0Ll0eSPIvFm4IUCwQrHovFmyyW4BORYlUtdHscpipLzlMo08m5McYYY0yiLDn3Jl8sQmRq9tCsFTw0a4Xbw0iJt5du4u2lm9weRkpYLN4UpFggWPFYLN5ksRjjDtdrzk3ipsxdC8DNZ/dwdRyp8PcPVwNwZu/2Lo8keRaLNwUpFghWPBaLN1ksxrjDylpSKNNlLUGqodu2pwyA1s1zXR5J8iwWbwpSLBCseCwWb7JYgs/KWrzJZs59LAhJeUSQ3jAtFm8KUiwQrHgsFm+yWIxxh9Wc+9jY6QsZO32h28NIiReKvuKFoq/cHkZKWCzeFKRYIFjxWCzeZLEY4w5Lzn3szcUbeXPxRreHkRLTi79mevHXbg8jJSwWbwpSLBCseCwWb7JYjHGHJefGGGOMMcZ4hCXnxhhjjDHGeIQl58YYY4wxxniEJefGGGOMMcZ4hCXnxhhjjDHGeIQl58YYY4wxxniEJefGGGOMMcZ4hCXnxhhjjDHGeISoqttjCIzCwkItKirK2ON9uWU3AEe1bZGxx0yXbXvKgGAssWyxeFOQYoFgxWOxeJPFEnwiUqyqhW6Pw1SV4/YATOKCkJRHBOkN02LxpiDFAsGKx2LxJovFGHdYWYuPjZ2+kLHTF7o9jJR4oegrXij6yu1hpITF4k1BigWCFY/F4k0WizHusOTcx95cvJE3F290exgpMb34a6YXf+32MFLCYvGmIMUCwYrHYvEmi8UYd1jNeQpluubcGGOMMSZRVnPuTTZzbowxxhhjjEdYcu5jP3/qE37+1CduDyMlJn3wJZM++NLtYaSExeJNQYoFghWPxeJNFosx7rDk3Mfmr93O/LXb3R5GSryzbDPvLNvs9jBSwmLxpiDFAsGKx2LxJovFGHdYcm6MMcYYY4xHWHJujDHGGGOMR1hybowxxhhjjEdYcm6MMcYYY4xHBD45F5EhIrJCRFaJyK013F4gIu+IyCIRmS0iR1S7vaWIfC0ij2Vu1MYYY4wxpiEKdHIuItnA48BQoDdwuYj0rrbZQ8BUVe0L3APcX+32/wE+SPdYjTHGGGOMCXRyDgwAVqnqalUtA/4JXFBtm97Au+Hf34u+XUT6A+2B/2RgrMYYY4wxpoELenLeEfgq6vLX4euiLQQuDv9+EZAnIvkikgU8DNyc9lEaY4wxxhgDiKq6PYa0EZFLgCGqOjJ8+SrgRFUdE7XN4cBjQBec8pWfAMcAw4FmqjpeREYAhdH3i7r/aGB0+GIPYEX6IqpRG+DbDD9mulgs3mSxeFeQ4rFYvMliCbYCVW3r9iBMVTluDyDN1gOdoi4fEb5uP1X9hvDMuYi0AH6iqjtE5CTgFBG5DmgB5IrIblW9tdr9JwGT0hhDnUSkSFUL3Xr8VLJYvMli8a4gxWOxeJPFYkzmBT05nw90E5EuOEn5T4ErojcQkTbANlUNAbcBkwFU9cqobUbgzJwf1O3FGGOMMcaYVAl0zbmqVgBjgFnAMuBfqrpERO4RkfPDmw0GVojISpyTP+91ZbDGGGOMMabBC/rMOar6BvBGtevujPp9OjC9nn08BTyVhuGlgmslNWlgsXiTxeJdQYrHYvEmi8WYDAv0CaHGGGOMMcb4SaDLWowxxhhjjPETS859SkSGiMgKEVklIr47UVVEJovIZhFZHHVdaxF5S0S+CP/bys0xxkpEOonIeyKyVESWiMhvw9f7Lh4RaSIin4jIwnAsd4ev7yIiH4efb8+LSK7bY42ViGSLyGci8nr4si9jEZG1IvK5iCwQkaLwdb57jgGIyKEiMl1ElovIMhE5yY+xiEiP8PGI/HwnIjf4MRYAEfld+HW/WESeC78f+PX18ttwHEtE5Ibwdb48LqbhseTch0QkG3gcGIqzwunlItLb3VHF7SlgSLXrbgXeUdVuwDvhy35QAdykqr2BgcD14ePhx3i+B05X1X7AccAQERkIPAj8SVWPBrYDv3BxjPH6Lc4J4RF+juU0VT0uqh2cH59jAH8GZqpqT6AfzvHxXSyquiJ8PI4D+gOlwEv4MBYR6Qj8Bqcz2TFANk6HM9+9XkTkGGAUzirh/YAfi8jR+PC4mIbJknN/GgCsUtXVqloG/BO4wOUxxUVVPwC2Vbv6AmBK+PcpwIUZHVSCVHWDqn4a/n0XTqLRER/Go47d4YuNwj8KnM6BE6d9EQuAiBwBnAs8Eb4s+DSWWvjuOSYihwA/BJ4EUNUyVd2BD2Op5gzgS1Utwb+x5ABNRSQHaAZswJ+vl17Ax6paGu7a9j7OeiZ+PS6mgbHk3J86Al9FXf46fJ3ftVfVDeHfN+K0tvQVEekM/AD4GJ/GEy4DWQBsBt4CvgR2hP/Igb+eb/8LjAVC4cv5+DcWBf4jIsXirEwM/nyOdQG2AP8Ilxs9ISLN8Wcs0X4KPBf+3XexqOp64CFgHU5SvhMoxp+vl8U4iwjmi0gz4BycBQl9d1xMw2TJufEkddoI+aqVkDgrzP4buEFVv4u+zU/xqGpl+Gv6I3C+penp8pASIiI/BjararHbY0mRk1X1eJxytutF5IfRN/roOZYDHA/8VVV/AOyhWnmBj2IBIFyHfT7wQvXb/BJLuP76ApwPT4cDzTm49NAXVHUZTjnOf4CZwAKgsto2vjgupmGy5Nyf1uPMAkQcEb7O7zaJSAeA8L+bXR5PzESkEU5i/oyqvhi+2rfxAIRLDd4DTgIODX/VDf55vv0XcL6IrMUp/Todp9bZj7FEZjZR1c04dc0D8Odz7Gvga1X9OHx5Ok6y7sdYIoYCn6rqpvBlP8ZyJrBGVbeoajnwIs5ryK+vlydVtb+q/hCnVn4l/jwupgGy5Nyf5gPdwmfR5+J8nfqqy2NKhVeBn4V//xnwiotjiVm4jvlJYJmqPhJ1k+/iEZG2InJo+PemwI9waujfAy4Jb+aLWFT1NlU9QlU747xG3lXVK/FhLCLSXETyIr8DZ+F8de+755iqbgS+EpEe4avOAJbiw1iiXM6BkhbwZyzrgIEi0iz8nhY5Lr57vQCISLvwv0fi1Js/iz+Pi2mAbBEinxKRc3DqabOByap6r8tDiouIPAcMBtoAm4C7gJeBfwFHAiXAMFWtftKo54jIycCHwOccqG3+b5y6c1/FIyJ9cU6Uysb58P4vVb1HRLrizD63Bj4Dhqvq9+6NND4iMhi4WVV/7MdYwmN+KXwxB3hWVe8VkXx89hwDEJHjcE7SzQVWA9cQfr7hv1ia4yS2XVV1Z/g6vx6Xu4HLcDpQfQaMxKkx99XrBUBEPsQ5x6QcuFFV3/HrcTENjyXnxhhjjDHGeISVtRhjjDHGGOMRlpwbY4wxxhjjEZacG2OMMcYY4xGWnBtjjDHGGOMRlpwbY4wxxhjjEZacG2NMAyMig0VEwz8j3B6PMcaYAyw5N8b4loh0jkoyZ7s9HmOMMSZZlpwbYwJLRGaHE/e1bo8l3RpSrMYYE2Q5bg/AGGNMZqnqbEDcHocxxpiD2cy5McYYY4wxHmHJuTHGGGOMMR5hybkxJnBE5CkRUeDU8FUFUSeORv8MruX+R4jIvSLyiYh8KyJlIrJJRN4SketEpHEdjz0uav+dRSRHRH4pIu+JyEYRqax+8qqIdBeR34vIDBFZIyKlIvK9iHwjIm+KyOjaHjORWOPp1iIiA0XkSRH5QkT2hH++CF93Yj33rf5/ISJyVfj/YouI7BOR1SLyNxEpqGtfxhjTUFjNuTHGRBGR3wIPAtWT4XbAmeGfG0TkfFVdXs/uWgH/BGpNYkXkOOCzWm7uEP4ZAvxaRM5T1bX1BpECIpINPAZcW8PNR4d/fi4ijwO/VdXKenbZBHgdOKfa9V2AXwKXiciZqlqc3MiNMcbfLDk3xgTR7cBDwD+AQuAb4OwatlsTfUFE7gDuibptArAM2ICTnJ+Lk0h2A94Wkf6quqmOcfwD6AdMB54B1gH5QPQscQ7wPfAf4B1gyf9v795C56juAI5/f/qgiPGCEpSgYMRLJCW1SknToI0BxQcfjKKoCLUh3mkNlQr1RUSpxQdvKIg3iGC8UKiKUIzBmKCCUJoWUYyxTwZjxWsagzb468M5627/yc7MZv/Kdv1+YNi5/ObMmXlYfnv2nDPAJ8CcGnc55QfBQuDPEfHTzPx63Hvt4AHgyrq+HbgTeI0ykHQJ8DvKM7mu7ruupbyHgKXA08BayrM4ElgJXAQcBqyNiFMyc/eIdZWkqWFyLmnqZOY2YFtE7Ky7/pOZbzadExFLgFvq5r3Ab/eSJP4lIp4EXgLmAbcBqxqKXQT8OjPva4jZChybmf8acnxNRPwKeKSWdzHweO/gvtxrm4hYRj8xfxdYOqN+r0fEE8CrlJbvayPiqczc2FDsUmBVZj48Y/+LEfEV5UfICcC5wPPj1F+S/p/Z51ySipsp34n/AFYPa73NzFcprcoAl0fEgQ1lbmxJzMnMzxoS817Mo/S7vlzQFDtLbhhYX7W3+mXmB5R/EXpWt5T53F4S8547BtZ/0amGkjSlTM4l/eBFxMHA2XXzqcz8puWUl+vnAZSuJMM83nBsWF32j4h5EXFyRCzsLZTuKgCnjlrmqNcHzqqb72TmK8NiM3MdpeUfYHk9d5ihzyIz3wL+XTfnj1BdSZo6dmuRJPgJ/e/D2yPi9hHOPbrh2OYuBdSZWK4CLgV+zJ6DUQcd2b1q+2Q+cHBdf71D/GuUwaFzKF1ctg6Je7ulnE/rdQ/pcE1Jmlom55JUBjbuq4Majn3adnJEzAPWAQtm4Xqz4YiB9e0d4j+Yce6w5HznkP09vX8rmlrfJWnqmZxL0v9+F94KPDPCue83HGubXhBgDf3E/AXKwM+/Ax8Cu3pdbCJiDWXQpCRpipmcSxJ8NLC+e9zZTrqKiBPp9+9+MjMvaQg//HuoEsDHA+tHdYgfjPl4aJQkqRMHhEqaZtkx7m/0u1Wc8R3VZW9+NLC+dlhQRARwWktZXe+1zT/pD878WYf4JfVzB6PPpS5JmsHkXNI021U/mwZYkpmfABvq5vKI+E5nRBkw+O9lU1/yFTQPPIWO99qmvunzpbp5UkScOSw2IpZT5iYHWNfhLaGSpBYm55KmWW/6wbkRcWhL7C2U1ucA/lS7nAwVEcdExMox67dlYP2XtYV85nUW0J9Xvcko99rmnoH1hyJijwGzEXEU8ODArrvHvKYkCZNzSdNtU/3cD3g0Is6MiAV1DvGTI+Lb1urM3AT8vm4eB2yOiAcjYkVEnF6XcyPipohYT+nCccWY9dtMf7rFc4D1EXFhvdZZEfFH4A3KNIV/na17bZOZG+gn3idQnsUNEbG4LqspXYGOrzH31+cnSRqTA0IlTbOngZsos6GsqMugZfS7s5CZd0TEh5SW4zmUV9hfyXCfj1O5zMyIuIzyUqO5tT7LZoTtAC4Bzqe53/lI99rB9ZR/Eq6mdKm5a0jc/cBvRihXktTAlnNJUyszdwE/B/5AaaH+gpaBk5n5GHAscCPwImUe76/qsp3SQn0nZZaV82ahjm8BiyjJ75Z6nR2Ul/bcBSzKzGc7lDPyvbaUtzszr6EMCn0MeA/4si7v1X2LM/N6+5pL0uyJzNka4C9JkiRpHLacS5IkSRPC5FySJEmaECbnkiRJ0oQwOZckSZImhMm5JEmSNCFMziVJkqQJYXIuSZIkTQiTc0mSJGlCmJxLkiRJE8LkXJIkSZoQJueSJEnShDA5lyRJkibEfwF5+mBYdGIPQAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "df_eclipse_2_0=pd.DataFrame(groupedIterationMap['eclipse_2_0'])\n",
    "df_eclipse_3_0= pd.DataFrame(groupedIterationMap['eclipse_3_0'])\n",
    "df_camel_1_2= pd.DataFrame(groupedIterationMap['camel_1_2'])\n",
    "df_prop_2= pd.DataFrame( groupedIterationMap['prop_2'])\n",
    "df_xalan_2_6= pd.DataFrame(groupedIterationMap['xalan_2_6'])\n",
    "\n",
    "fig1, ax1 = plt.subplots()\n",
    "ax1.set_title('AutoML',fontsize = 29)\n",
    "plt.rcParams[\"figure.figsize\"] = (10, 5)\n",
    "axes = plt.gca()\n",
    "axes.set_ylim([0.94,1])\n",
    "threshold = 0.99\n",
    "plt.axhline(y=threshold, color='r', linestyle='-.')\n",
    "for vx in df_eclipse_2_0['Iteration']:\n",
    "    if vx % 10 ==0:\n",
    "        plt.axvline(x=vx,linestyle='-.')\n",
    "#text(0.00, threshold, str(threshold), fontsize=25) # draw above, centered\n",
    "plt.xticks(range(0,100,10))\n",
    "\n",
    "threshold = 0.95\n",
    "plt.axhline(y=threshold, color='r', linestyle='-.')\n",
    "markers=['o', '.', ',', 'x', '+', 'v', '^', '<', '>', 's', 'd']\n",
    "plt.scatter( 'Iteration', 'POB', data=df_eclipse_2_0.loc[df_eclipse_2_0['POB']>=threshold],label = 'camel 1.2',marker=markers[1])\n",
    "plt.scatter( 'Iteration', 'POB', data=df_eclipse_3_0.loc[df_eclipse_3_0['POB']>=threshold],label = 'eclipse 2.0',marker=markers[2])\n",
    "plt.scatter( 'Iteration', 'POB', data=df_camel_1_2.loc[df_camel_1_2['POB']>=threshold],label = 'prop 2.0',marker=markers[3])\n",
    "plt.scatter( 'Iteration', 'POB', data=df_prop_2.loc[df_prop_2['POB']>=threshold],label = 'eclipse 3.0',marker=markers[4])\n",
    "plt.scatter( 'Iteration', 'POB', data=df_xalan_2_6.loc[df_xalan_2_6['POB']>=threshold],label = 'xalan 2.6',marker=markers[5])\n",
    "plt.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
    "xlabel ('Iteration',fontsize = 29)\n",
    "ylabel ('AW_ite / AW_best\\n(AW: AUC_weighted)',fontsize = 20)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 477,
   "metadata": {},
   "outputs": [],
   "source": [
    "def pltSetting(plt,df,label,thresholdhigh,thresholdlow):\n",
    "    \n",
    "    axes = plt.gca()\n",
    "    axes.set_ylim([0.94,1])\n",
    "    plt.yticks([0.95,0.99,1],fontsize = 12)\n",
    "    markers=['o', '.', ',', 'x', '+', 'v', '^', '<', '>', 's', 'd']\n",
    "    plt.scatter( 'Iteration', 'POB', data=df.loc[df['POB']>=thresholdhigh],color = 'r',label = label,marker='+',s=30)\n",
    "    tmp = df.loc[df['POB']>=thresholdlow]\n",
    "    plt.scatter( 'Iteration', 'POB', data=tmp.loc[tmp['POB']<thresholdhigh],color = 'b',label='',marker='+',s=30)\n",
    "\n",
    "    plt.legend(loc='center left', bbox_to_anchor=(1, 0.5),prop={'size': 15})\n",
    "    leg = plt.gca().get_legend()\n",
    "    leg.legendHandles[0].set_visible(False)\n",
    "    plt.axhline(y=thresholdlow, color='g', linestyle='-.')\n",
    "    plt.xticks([])\n",
    "    plt.axhline(y=thresholdhigh, color='g', linestyle='-.')\n",
    "    for vx in range(0,100,10):\n",
    "        if vx ==0: \n",
    "            vx = vx\n",
    "        plt.axvline(x=vx,linestyle='-.',color = 'g')\n",
    "    return None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 478,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Iteration')"
      ]
     },
     "execution_count": 478,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x504 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_eclipse_2_0=pd.DataFrame(groupedIterationMap['eclipse_2_0'])\n",
    "df_eclipse_3_0= pd.DataFrame(groupedIterationMap['eclipse_3_0'])\n",
    "df_camel_1_2= pd.DataFrame(groupedIterationMap['camel_1_2'])\n",
    "df_prop_2= pd.DataFrame( groupedIterationMap['prop_2'])\n",
    "df_xalan_2_6= pd.DataFrame(groupedIterationMap['xalan_2_6'])\n",
    "\n",
    "fig1, ax1 = plt.subplots()\n",
    "fig1.suptitle('AutoML',fontsize = 29)\n",
    "plt.rcParams[\"figure.figsize\"] = (10, 7)\n",
    "\n",
    "thresholdhigh = 0.99\n",
    "thresholdlow = 0.95\n",
    "\n",
    "plt.subplot(5,1,1)\n",
    "pltSetting(plt,df_eclipse_2_0,'eclipse 2.0',thresholdhigh,thresholdlow)\n",
    "\n",
    "plt.subplot(5,1,2)\n",
    "pltSetting(plt,df_eclipse_3_0,'eclipse 3.0',thresholdhigh,thresholdlow)\n",
    "\n",
    "plt.subplot(5,1,3)\n",
    "pltSetting(plt,df_camel_1_2,'camel 1.2',thresholdhigh,thresholdlow)\n",
    "\n",
    "ylabel ('AW_ite / AW_best\\n(AW: AUC_weighted)',fontsize = 20)\n",
    "\n",
    "plt.subplot(5,1,4)\n",
    "pltSetting(plt,df_prop_2,'prop 2.0',thresholdhigh,thresholdlow)\n",
    "\n",
    "plt.subplot(5,1,5)\n",
    "pltSetting(plt,df_xalan_2_6,'xalan 2.6',thresholdhigh,thresholdlow)\n",
    "\n",
    "plt.xticks(range(0,100,10),fontsize = 20)\n",
    "\n",
    "xlabel ('Iteration',fontsize = 29)\n"
   ]
  }
 ],
 "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": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}