assemblies_thesis_v2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "\n",
    "path = '/home/seq/pelenet'\n",
    "sys.path.append(path)\n",
    "os.chdir(path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "# Allow reload of objects\n",
    "%load_ext autoreload\n",
    "%autoreload\n",
    "\n",
    "from pelenet.utils import Utils\n",
    "from pelenet.experiments.assemblies import AssemblyExperiment\n",
    "from pelenet.experiments.assembliesoutput import AssemblyOutputExperiment\n",
    "\n",
    "# Official modules\n",
    "import numpy as np\n",
    "from scipy import sparse\n",
    "import nxsdk.api.n2a as nx\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "from time import time\n",
    "from copy import deepcopy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Overwrite default parameters (pelenet/parameters/ and pelenet/experiments/random.py)\n",
    "parameters = {\n",
    "    # Experiment\n",
    "    'seed': 9,  # Random seed\n",
    "    'trials': 50, #20,  # Number of trials\n",
    "    'stepsPerTrial': 40, #40, #50,  # Number of simulation steps for every trial\n",
    "    'isReset': True,  # Activate reset after every trial\n",
    "    # Network\n",
    "    'reservoirExSize': 400,  # Number of excitatory neurons\n",
    "    'reservoirConnPerNeuron': 35, #40, #35 # Number of connections per neuron\n",
    "    # Noise\n",
    "    'isNoise': True,\n",
    "    'onlyExcitatory': True,  # Noisy input is only excitatory\n",
    "    'noiseMaxWeight': 120, #120,\n",
    "    # Neurons\n",
    "    'refractoryDelay': 2, # Refactory period\n",
    "    'voltageTau': 100, #100 # Voltage time constant\n",
    "    'currentTau': 6, #5 # Current time constant\n",
    "    'thresholdMant': 1000, #1200,  # Spiking threshold for membrane potential\n",
    "    # Plasticity\n",
    "    'isLearningRule': True,\n",
    "    'learningEpoch': 4,\n",
    "    'learningRule': '2^-4*x1*y1*x0*y0 - 2^-3*y0*w*w',\n",
    "    # Input\n",
    "    'inputIsAlternating': True,\n",
    "    'inputAlternatingNum': 1,\n",
    "    'inputOffset': 20, #10,\n",
    "    'inputGenSpikeProb': 0.8,  # Probability of spikes for the spike generators\n",
    "    'inputNumTargetNeurons': 40,  # Number of neurons targeted by the spike generators\n",
    "    'inputSteps': 30, #20, #30,  # Number of steps the input is active\n",
    "    # Probes\n",
    "    'isExSpikeProbe': True,  # Probe excitatory spikes\n",
    "    'isInSpikeProbe': True,  # Probe inhibitory spikes\n",
    "    'isWeightProbe': True  # Probe weight matrix at the end of the simulation\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initilizes the experiment and utils\n",
    "exp = AssemblyExperiment(name='assemblies', parameters=parameters)\n",
    "utils = Utils.instance()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9264137460213924"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Build network\n",
    "exp.build()\n",
    "\n",
    "# Get spectral radius\n",
    "utils.getSpectralRadius(exp.net.initialWeights)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#exp.net.plot.initialExWeightDistribution()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#exp.net.noiseWeights.toarray()[:20,:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "pars = exp.net.p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1;30m\u001b[1;30mWARNING\u001b[0m\u001b[0m:\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m:  \u001b[33melementType would be deprecated in 0.9 in favor of messageSize, which provides more flexibility\u001b[0m\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m:  Connecting to 127.0.0.1:36753\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m:      Host server up..............Done 0.51s\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m:      Encoding axons/synapses.....Done 0.28s\n",
      "\u001b[1;30m\u001b[1;30mWARNING\u001b[0m\u001b[0m:\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m:  \u001b[33m~/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages ~/pelenet\n",
      "Compiling in directory : /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705\n",
      "Include dir is : /home/seq/pelenet/pelenet/snips/ -I/home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/graph/nxinputgen/../../snips/\n",
      "Compiling -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/initnetwork_0_0.c\n",
      "gcc -Wall -I/home/seq/pelenet/pelenet/snips/ -I/home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/graph/nxinputgen/../../snips/ -Inxsdk/include -fno-stack-protector -msoft-float -m32 -march=i586 -fno-builtin-printf -fno-builtin-sprintf -fno-builtin-fprintf -fno-builtin-memcpy -fstrict-volatile-bitfields -Os -DNDEBUG -std=c99 -o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/initnetwork_0_0.c.o -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/initnetwork_0_0.c\n",
      "Compiling without -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/0_spiking_packed.c\n",
      "gcc -Wall -I/home/seq/pelenet/pelenet/snips/ -I/home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/graph/nxinputgen/../../snips/ -Inxsdk/include -fno-stack-protector -msoft-float -m32 -march=i586 -fno-builtin-printf -fno-builtin-sprintf -fno-builtin-fprintf -fno-builtin-memcpy -fstrict-volatile-bitfields -Os -DNDEBUG -std=c99 -o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/0_spiking_packed.c.o -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/0_spiking_packed.c\n",
      "Compiling without -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/1_reset_init.c\n",
      "gcc -Wall -I/home/seq/pelenet/pelenet/snips/ -I/home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/graph/nxinputgen/../../snips/ -Inxsdk/include -fno-stack-protector -msoft-float -m32 -march=i586 -fno-builtin-printf -fno-builtin-sprintf -fno-builtin-fprintf -fno-builtin-memcpy -fstrict-volatile-bitfields -Os -DNDEBUG -std=c99 -o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/1_reset_init.c.o -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/1_reset_init.c\n",
      "Compiling without -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/2_reset.c\n",
      "gcc -Wall -I/home/seq/pelenet/pelenet/snips/ -I/home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/graph/nxinputgen/../../snips/ -Inxsdk/include -fno-stack-protector -msoft-float -m32 -march=i586 -fno-builtin-printf -fno-builtin-sprintf -fno-builtin-fprintf -fno-builtin-memcpy -fstrict-volatile-bitfields -Os -DNDEBUG -std=c99 -o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/2_reset.c.o -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/2_reset.c\n",
      "/home/seq/pelenet/pelenet/snips//reset.c: In function ‘reset’:\n",
      "/home/seq/pelenet/pelenet/snips//reset.c:51:9: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]\n",
      "         nx_fast_init64(nc->cx_state, neuronsPerCore, *(uint64_t*)&cxs);\n",
      "         ^~~~~~~~~~~~~~\n",
      "/home/seq/pelenet/pelenet/snips//reset.c:79:13: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]\n",
      "             nx_fast_init32(nc->cx_meta_state, neuronsPerCore/4, *(uint32_t*)&ms);\n",
      "             ^~~~~~~~~~~~~~\n",
      "Compiling without -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/main_0_0.c\n",
      "gcc -Wall -I/home/seq/pelenet/pelenet/snips/ -I/home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/graph/nxinputgen/../../snips/ -Inxsdk/include -fno-stack-protector -msoft-float -m32 -march=i586 -fno-builtin-printf -fno-builtin-sprintf -fno-builtin-fprintf -fno-builtin-memcpy -fstrict-volatile-bitfields -Os -DNDEBUG -std=c99 -o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/main_0_0.c.o -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/main_0_0.c\n",
      "OBJFILES :  /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/initnetwork_0_0.c.o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/0_spiking_packed.c.o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/1_reset_init.c.o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/2_reset.c.o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/main_0_0.c.o\n",
      "gcc -Wall -fno-stack-protector -msoft-float -m32 -march=i586 -fno-builtin-printf -fno-builtin-sprintf -fno-builtin-fprintf -fno-builtin-memcpy -fstrict-volatile-bitfields -Os -DNDEBUG -std=c99 /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/initnetwork_0_0.c.o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/0_spiking_packed.c.o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/1_reset_init.c.o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/2_reset.c.o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/main_0_0.c.o -o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/launcher.link nxsdk/lib/embedded/libboot.a nxsdk/lib/embedded/libembedded_nx.a nxsdk/lib/embedded/liblmt.a nxsdk/lib/embedded/libnx.a -Wl,--script=nxsdk/utils/linker.scr -Wl,--build-id=none -Wl,-N -nostdlib\n",
      "\u001b[0m\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m:      Compiling Embedded snips....Done 0.32s\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m:      Booting up..................Done 0.93s\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m:      Encoding probes.............Done 0.02s\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m:      Transferring probes.........Done 0.07s\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m:      Configuring registers.......Done 0.45s\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m:      Transferring spikes.........Done 1.26s\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  Using Kapoho Bay serial number 308\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  Args chip=0 cpu=0 /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854341.8772705/launcher_chip0_lmt0.bin --chips=1 --remote-relay=0 --epoch=4 \n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  Lakemont_driver...\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Transfered values 20, 60, 10 \n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1 to 10\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 10\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 61 to 70\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 70\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 121 to 130\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 130\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 181 to 190\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 190\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 241 to 250\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 250\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 301 to 310\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 310\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 361 to 370\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 370\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 421 to 430\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 430\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 481 to 490\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 490\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 541 to 550\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 550\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 601 to 610\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 610\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 661 to 670\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 670\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 721 to 730\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 730\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 781 to 790\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 790\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 841 to 850\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 850\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 901 to 910\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 910\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 961 to 970\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 970\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1021 to 1030\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1030\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1081 to 1090\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1090\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1141 to 1150\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1150\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1201 to 1210\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1210\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1261 to 1270\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1270\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1321 to 1330\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1330\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1381 to 1390\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1390\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1441 to 1450\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1450\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1501 to 1510\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1510\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1561 to 1570\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1570\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1621 to 1630\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1630\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1681 to 1690\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1690\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1741 to 1750\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1750\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1801 to 1810\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1810\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1861 to 1870\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1870\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1921 to 1930\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1930\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1981 to 1990\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1990\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2041 to 2050\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2050\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2101 to 2110\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2110\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2161 to 2170\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2170\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2221 to 2230\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2230\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2281 to 2290\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2290\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2341 to 2350\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2350\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2401 to 2410\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2410\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2461 to 2470\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2470\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2521 to 2530\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2530\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2581 to 2590\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2590\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2641 to 2650\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2650\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2701 to 2710\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2710\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2761 to 2770\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2770\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2821 to 2830\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2830\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2881 to 2890\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2890\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2941 to 2950\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2950\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m:      Executing...................Done 73.21s\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m:      Processing timeseries.......Done 2.62s\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m:  Executor: 3000 timesteps........Done 77.65s\n",
      "\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m:\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m:  chip=0 cpu=0 halted, status=0x0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/numpy/core/_asarray.py:83: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray\n",
      "  return array(a, dtype, copy=False, order=order)\n"
     ]
    }
   ],
   "source": [
    "# Run network\n",
    "exp.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import rcParams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/seq/pelenet/log/2021-11-02_12-58-53_assemblies/plots/'"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exp.net.plot.plotDir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/seq/pelenet/log/2021-11-02_13-00-27_assemblies-2/plots/'"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exp2.net.plot.plotDir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "# Plot spike trains of the excitatory (red) and inhibitory (blue) neurons\n",
    "rcParams['font.size'] = 18\n",
    "exp.net.plot.reservoirSpikeTrain(figsize=(10,5), fr=0, to=500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "exp.net.plot.reservoirRates(figsize=(10,2), ylim=(0,0.4), fr=0, to=500, legend_loc='upper right')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "exp.net.plot.initialExWeightDistribution(figsize=(6,4), xlim=(0,100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#exp.net.plot.trainedExWeightDistribution(figsize=(6,4), xlim=(0,100))\n",
    "\n",
    "wgt = exp.net.trainedWeightsExex[-1].toarray().flatten()\n",
    "nz = np.array(np.nonzero(wgt)[0])\n",
    "\n",
    "plt.hist(wgt[nz], bins=np.arange(np.max(wgt[nz])))\n",
    "plt.xlim((0,100))\n",
    "pl = plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Weight matrix before learning\n",
    "exp.net.plot.initialExWeightMatrix()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Weight matrix after learning\n",
    "exp.net.plot.trainedExWeightMatrix()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.13375 0.828125 0.5775 0.40125\n"
     ]
    }
   ],
   "source": [
    "size = exp.p.inputNumTargetNeurons\n",
    "\n",
    "input_regions = exp.net.trainedWeightsExex[-1].toarray()[:2*size,:2*size]\n",
    "\n",
    "inp_lt = input_regions[:size,:size]\n",
    "inp_rt = input_regions[size:,:size]\n",
    "inp_lb = input_regions[:size,size:]\n",
    "inp_rb = input_regions[size:,size:]\n",
    "\n",
    "print(np.mean(inp_lt), np.mean(inp_rt), np.mean(inp_lb), np.mean(inp_rb))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Sorted weight matrix after learning\n",
    "expSupportMask = utils.getSupportWeightsMask(exp.net.trainedWeightsExex[-1])\n",
    "exp.net.plot.weightsSortedBySupport(expSupportMask, exp.net.trainedWeightsExex[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cluster_mean = []\n",
    "all_mean = []\n",
    "\n",
    "cluster_mean.append(np.mean(exp.net.initialWeights.exex[:40,:40]))\n",
    "all_mean.append(np.mean(exp.net.initialWeights.exex))\n",
    "\n",
    "for i in range(exp.p.trials):\n",
    "    cluster_mean.append(np.mean(exp.net.trainedWeightsExex[i][:40,:40]))\n",
    "    all_mean.append(np.mean(exp.net.trainedWeightsExex[i]))\n",
    "\n",
    "cluster_mean = np.array(cluster_mean)\n",
    "all_mean = np.array(all_mean)\n",
    "\n",
    "x = cluster_mean/all_mean\n",
    "plt.figure(figsize=(10,3))\n",
    "plt.axhline(y=1, color='black', linewidth=0.5)\n",
    "plt.plot(x, label='A')\n",
    "plt.ylim((0.5, np.max(x)+0.5))\n",
    "plt.legend()\n",
    "pl = plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# New parameters\n",
    "newParameters = {\n",
    "    **parameters,\n",
    "    'trials': 2*exp.p.trials,\n",
    "    'inputAlternatingNum': 2\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initilizes a second experiment\n",
    "exp2 = AssemblyExperiment(name='assemblies-2', parameters=newParameters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get weights from previous experiment\n",
    "weights = deepcopy(exp.net.initialWeights)\n",
    "weights.exex = exp.net.trainedWeightsExex[-1]\n",
    "\n",
    "# Build experiment\n",
    "exp2.build()\n",
    "exp2.net.initialMasks = exp.net.initialMasks\n",
    "exp2.net.initialWeights = weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mWARNING\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m\u001b[0m:  \u001b[33melementType would be deprecated in 0.9 in favor of messageSize, which provides more flexibility\u001b[0m\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m\u001b[0m:  Connecting to 127.0.0.1:41925\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m\u001b[0m:      Host server up..............Done 1.09s\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mWARNING\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m\u001b[0m:  \u001b[33m~/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages ~/pelenet\n",
      "Compiling in directory : /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203\n",
      "Include dir is : /home/seq/pelenet/pelenet/snips/ -I/home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/graph/nxinputgen/../../snips/\n",
      "Compiling -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/initnetwork_0_0.c\n",
      "gcc -Wall -I/home/seq/pelenet/pelenet/snips/ -I/home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/graph/nxinputgen/../../snips/ -Inxsdk/include -fno-stack-protector -msoft-float -m32 -march=i586 -fno-builtin-printf -fno-builtin-sprintf -fno-builtin-fprintf -fno-builtin-memcpy -fstrict-volatile-bitfields -Os -DNDEBUG -std=c99 -o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/initnetwork_0_0.c.o -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/initnetwork_0_0.c\n",
      "Compiling without -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/0_spiking_packed.c\n",
      "gcc -Wall -I/home/seq/pelenet/pelenet/snips/ -I/home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/graph/nxinputgen/../../snips/ -Inxsdk/include -fno-stack-protector -msoft-float -m32 -march=i586 -fno-builtin-printf -fno-builtin-sprintf -fno-builtin-fprintf -fno-builtin-memcpy -fstrict-volatile-bitfields -Os -DNDEBUG -std=c99 -o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/0_spiking_packed.c.o -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/0_spiking_packed.c\n",
      "Compiling without -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/1_reset_init.c\n",
      "gcc -Wall -I/home/seq/pelenet/pelenet/snips/ -I/home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/graph/nxinputgen/../../snips/ -Inxsdk/include -fno-stack-protector -msoft-float -m32 -march=i586 -fno-builtin-printf -fno-builtin-sprintf -fno-builtin-fprintf -fno-builtin-memcpy -fstrict-volatile-bitfields -Os -DNDEBUG -std=c99 -o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/1_reset_init.c.o -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/1_reset_init.c\n",
      "Compiling without -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/2_reset.c\n",
      "gcc -Wall -I/home/seq/pelenet/pelenet/snips/ -I/home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/graph/nxinputgen/../../snips/ -Inxsdk/include -fno-stack-protector -msoft-float -m32 -march=i586 -fno-builtin-printf -fno-builtin-sprintf -fno-builtin-fprintf -fno-builtin-memcpy -fstrict-volatile-bitfields -Os -DNDEBUG -std=c99 -o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/2_reset.c.o -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/2_reset.c\n",
      "/home/seq/pelenet/pelenet/snips//reset.c: In function ‘reset’:\n",
      "/home/seq/pelenet/pelenet/snips//reset.c:51:9: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]\n",
      "         nx_fast_init64(nc->cx_state, neuronsPerCore, *(uint64_t*)&cxs);\n",
      "         ^~~~~~~~~~~~~~\n",
      "/home/seq/pelenet/pelenet/snips//reset.c:79:13: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]\n",
      "             nx_fast_init32(nc->cx_meta_state, neuronsPerCore/4, *(uint32_t*)&ms);\n",
      "             ^~~~~~~~~~~~~~\n",
      "Compiling without -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/main_0_0.c\n",
      "gcc -Wall -I/home/seq/pelenet/pelenet/snips/ -I/home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/graph/nxinputgen/../../snips/ -Inxsdk/include -fno-stack-protector -msoft-float -m32 -march=i586 -fno-builtin-printf -fno-builtin-sprintf -fno-builtin-fprintf -fno-builtin-memcpy -fstrict-volatile-bitfields -Os -DNDEBUG -std=c99 -o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/main_0_0.c.o -c /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/main_0_0.c\n",
      "OBJFILES :  /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/initnetwork_0_0.c.o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/0_spiking_packed.c.o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/1_reset_init.c.o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/2_reset.c.o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/main_0_0.c.o\n",
      "gcc -Wall -fno-stack-protector -msoft-float -m32 -march=i586 -fno-builtin-printf -fno-builtin-sprintf -fno-builtin-fprintf -fno-builtin-memcpy -fstrict-volatile-bitfields -Os -DNDEBUG -std=c99 /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/initnetwork_0_0.c.o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/0_spiking_packed.c.o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/1_reset_init.c.o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/2_reset.c.o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/main_0_0.c.o -o /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/launcher.link nxsdk/lib/embedded/libboot.a nxsdk/lib/embedded/libembedded_nx.a nxsdk/lib/embedded/liblmt.a nxsdk/lib/embedded/libnx.a -Wl,--script=nxsdk/utils/linker.scr -Wl,--build-id=none -Wl,-N -nostdlib\n",
      "\u001b[0m\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m\u001b[0m:      Compiling Embedded snips....Done 0.20s\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m\u001b[0m:      Encoding axons/synapses.....Done 0.37s\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m\u001b[0m:      Booting up..................Done 0.86s\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m\u001b[0m:      Encoding probes.............Done 8.11ms\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m\u001b[0m:      Transferring probes.........Done 0.06s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m\u001b[0m:      Configuring registers.......Done 0.45s\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m\u001b[0m:      Transferring spikes.........Done 2.25s\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  Using Kapoho Bay serial number 308\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  Args chip=0 cpu=0 /home/seq/.local/share/virtualenvs/seq-r0_WvjRo/lib/python3.6/site-packages/nxsdk/driver/compilers/../../../temp/1635854436.9286203/launcher_chip0_lmt0.bin --chips=1 --remote-relay=0 --epoch=4 \n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  Lakemont_driver...\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Transfered values 20, 60, 10 \n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1 to 10\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 10\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 61 to 70\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 70\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 121 to 130\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 130\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 181 to 190\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 190\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 241 to 250\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 250\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 301 to 310\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 310\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 361 to 370\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 370\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 421 to 430\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 430\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 481 to 490\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 490\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 541 to 550\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 550\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 601 to 610\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 610\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 661 to 670\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 670\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 721 to 730\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 730\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 781 to 790\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 790\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 841 to 850\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 850\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 901 to 910\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 910\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 961 to 970\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 970\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1021 to 1030\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1030\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1081 to 1090\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1090\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1141 to 1150\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1150\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1201 to 1210\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1210\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1261 to 1270\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1270\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1321 to 1330\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1330\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1381 to 1390\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1390\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1441 to 1450\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1450\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1501 to 1510\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1510\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1561 to 1570\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1570\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1621 to 1630\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1630\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1681 to 1690\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1690\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1741 to 1750\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1750\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1801 to 1810\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1810\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1861 to 1870\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1870\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1921 to 1930\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1930\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 1981 to 1990\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 1990\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2041 to 2050\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2050\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2101 to 2110\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2110\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2161 to 2170\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2170\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2221 to 2230\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2230\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2281 to 2290\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2290\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2341 to 2350\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2350\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2401 to 2410\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2410\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2461 to 2470\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2470\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2521 to 2530\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2530\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2581 to 2590\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2590\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2641 to 2650\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2650\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2701 to 2710\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2710\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2761 to 2770\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2770\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2821 to 2830\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2830\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2881 to 2890\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2890\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 2941 to 2950\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 2950\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 3001 to 3010\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 3010\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 3061 to 3070\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 3070\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 3121 to 3130\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 3130\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 3181 to 3190\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 3190\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 3241 to 3250\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 3250\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 3301 to 3310\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 3310\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 3361 to 3370\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 3370\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 3421 to 3430\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 3430\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 3481 to 3490\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 3490\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 3541 to 3550\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 3550\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 3601 to 3610\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 3610\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 3661 to 3670\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 3670\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 3721 to 3730\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 3730\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 3781 to 3790\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 3790\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 3841 to 3850\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 3850\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 3901 to 3910\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 3910\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 3961 to 3970\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 3970\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 4021 to 4030\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 4030\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 4081 to 4090\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 4090\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 4141 to 4150\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 4150\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 4201 to 4210\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 4210\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 4261 to 4270\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 4270\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 4321 to 4330\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 4330\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 4381 to 4390\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 4390\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 4441 to 4450\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 4450\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 4501 to 4510\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 4510\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 4561 to 4570\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 4570\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 4621 to 4630\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 4630\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 4681 to 4690\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 4690\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 4741 to 4750\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 4750\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 4801 to 4810\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 4810\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 4861 to 4870\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 4870\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 4921 to 4930\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 4930\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 4981 to 4990\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 4990\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 5041 to 5050\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 5050\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 5101 to 5110\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 5110\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 5161 to 5170\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 5170\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 5221 to 5230\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 5230\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 5281 to 5290\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 5290\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 5341 to 5350\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 5350\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 5401 to 5410\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 5410\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 5461 to 5470\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 5470\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 5521 to 5530\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 5530\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 5581 to 5590\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 5590\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 5641 to 5650\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 5650\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 5701 to 5710\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 5710\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 5761 to 5770\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 5770\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 5821 to 5830\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 5830\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 5881 to 5890\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 5890\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset current/voltage from time step 5941 to 5950\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 Reset functional state at 5950\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m\u001b[0m:      Executing...................Done 145.82s\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m\u001b[0m:      Processing timeseries.......Done 4.67s\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mDRV\u001b[0m\u001b[0m\u001b[0m:  Executor: 6000 timesteps........Done 153.29s\n",
      "\u001b[1;30m\u001b[1;30m\u001b[1;30mINFO\u001b[0m\u001b[0m\u001b[0m:\u001b[34m\u001b[34m\u001b[34mHST\u001b[0m\u001b[0m\u001b[0m:  chip=0 cpu=0 halted, status=0x0\n"
     ]
    }
   ],
   "source": [
    "# Run network\n",
    "exp2.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Df3//EeeSM7Dan9uz+Xy3CSfS9DNNfFZn0hfyfCT4z1RsaKeLuJZp/7fDZGkeL2O4+gNn/eokzQeyfIKrPzRyqZfJyUnbUZBCdiPx5LIl8fM+0U7n2NhY6rWic1kbc8evcaCsrjLLGNRBmn5VSOaT5I95nt4qSzu4jim/iIfTrZ1JqtgjraLHeQmgdlzL6McpnbLoKi/i59nZSWczIpfD5W7fqk3GPk32yIqnSrdv2meO43d0xFH2GabtUbXrqSh+TRoPWrdfuNxtqFr2qfoGp27forKzyjPKhrNFlfKiKFydvyUIY/78rvzJoOLMyfOuZ1QZ8tb5a5N2Lc8uPqCzsDZpExvr/LXPN9EvhNDnGy5X/opQ1dlHv0jqp5oWzmnPQof+dfy2hsqfhuO0005Tt7wjhMwqxNatW0u39Pk+4YNDGrZu3Wr0+SZ8wwd0pMe0dqbQ0UvAqUU4iyz9OKalKrI9AXnXOLf8UfTMZnHaaaeJe+65x3Y0jCEzTonTWKYkQ0ND6OvrS72WNai/bDjfseEHefrVQVGag29kY1u7uvC1DG2Kfrpw6feEiNYLIc7U9kCdNUkuB/du3zyKukJ9eMMr2/XkQ9p1YdMWLncdBh/Jt4HL2tUJVz/RpR/X9HMGmlv+Gjnb11c4vonWSbDNYWRmujaR4CP5Nrjr2qtqjIm7NN1P2M5wDRyikZW/rq4u21FQRiaTFXVltdew4s4vP/Luys/wpeCqkoakL9Rlj97eXiPP1RF/X3zCRDpWr1qJy77xXe3PNYlOW3AvM1avWqml7GyTXCOREzrjzDH9AJrZ7cthwodKs7pMdy7nZvpk3B955JFS9/lAlTS5Yg9Z/YqoY1kkLtRlC13amST4xWHKlp1Z93OGu18gTPiozsDAgBgcHLQdjVrwsSt47dq1WL58ubbn+WijKpi2h279AvXxiec9B9f8YoPtaARKEvIeX3RP+Ghkt6+r6OyeaMOxUlN3M7rLNrLRPeGqPdh2rxhAty1kn3fWdddr/V4dBL84jC2/cBHOca8Fnc2IKgeAaQDOAvBVAG9IuX4ugDsAPAFgM4DLy4RJO0499dRq7a8WUJ3FK7v+kO2m7DL888rnSoVTWdCXKzLd/ap2MG2jhx56yMhzqy5k7ItvqMzqV/UNU9qZQtYWeeF88guZsrNMmcENlfxhs6yMAx8WeQZwKYCDALYAEADemLh+OoC9AD4A4NkAXg1gDMBlKmGyDg5j/mQpU2Bxz8RlF5rlnu6q6NwBpAouLxTcVB+RTbfL2tUFZx8JZad5TNnKl8rfMQBmtf5Pq/zdDOAniXPvAzCsEibr4LzOn+pEEB+pukWRz3AY1FznWnHBNw6jwxa+rPPXVL9I06+ptkjDZVvorvxZGfMnhNgjhNiddo2IjgLw+wB+mLh0K4CTiGhAJozuOLuCzHispu1QoJpOn8eCVNW8fb8vNmpKHpAh2OIwwRaHCbY4TJNsMc12BFKYC6AbwNbE+eHW3wEAv5UIM2U6LxFdCeBKAJg9ezZGRkYwOjqKxx57DADQ39+PsbEx7Ny5EwDQ19eHiYkJbNu2DcDhtcmGh6OvmD9/Pjo7OzE0NAQA6OnpQXd3N7Zs2QIAmDNnDmbPno3Nmzej/Z1z587F4OAgJicnMWvWLPT09GBoaAgTExPo7u7GvHnzMDw8jPHxccycORO9vb3Yvn07xsbG0NnZib6+PuzcuRO7d+/Gur/6c7zmu6sPpQMAFi5ciNHRUWz6399gxtq1uWm669qrDq3Z5UqaOjo6MDAwkJqmuE7j4+NYu3btlDTdfMWlOOu666V0WnLj1w/dH0/TXddehZf841etpEmn7w1+8J246Fu3VNLpN/smsH79eiNp2rp166G0mPa9b176Uiz78Kec1Knu/HTXtVfhtd9dXSlN+/fvx7Zt25xJUxWdbvrDi3HWddc7p5NJ39u6dSvWrl3rZbmnS6ebXnE+TvvQJ51Mk06sL/VCRALAm4QQN7Y+9wJ4BMBLhBCrY+FmABgHcAWAnxeFEUJ8Pes7ly5dKu6++279iWEIx2VOHn30UZxwwgm2oxEoSdCPL0E73gT9+NKEpV4mW3+Tceto/Z0mGSaTvXv3lo6cCxR1yWVdT1uhnlvFD8Cht6IkZbsqfeniBOTTUtaHdJClnwnKpIP7Tg5pyKRHJszXL32Zjug4QVWNOfpIWt7TVWb4QlPSaWXCR/xAYsIHgKe2zr0yEa6ndf7VMmHyvpPzhI84VWb0ujywtQiVQeec06kbV2zh2qQBV+xiE1kbuKZdnagsoeMqZfTjnuY6MWkr+DDhIw8hxOMAfgWgP3Gp/flhmTB53zF9+vSq0XSCrFY7ma5cji1+bebMmSMdNs9GjXnDa6GiuUnbqOhXB5zzgi5kbeCadnXiw97oZfTjnuY64WQr5yp/LX4CYBURUezcKgC/AfDfCmFS6ejoyLvMgrwf57gD+ljBmT179pTPZdKYVpD7YKsqaahrZ5ikfibxQVMdVBkSEb+3Tu1M0lS/0FF2xu/1zY6+pScPK5U/IuokouOJ6PjWqWNbn5/e+vxxAAsBfJqI+ojoTwC8FcBHhBAHFMKkwnnMn+oyLpzeRGRpz3xq2pI2pqnLjiZmriUJvqGH5EtSHdqZpOl+kdTvvFtuL13h8aElNA7HyY9VsNXy9zwAO1sHEFXkdgL4DgAIIe4BcF4r3L0A3gngaiHEp9sPkAnjI7q77ji/6ejOqD5k/DJp8PEN3gctdaLDHj74SPCLI6lqEx/8Amieb9ha5HmtEIJSjuWxMD8XQvyuEGKmEKJfCPHZlOcUhklj2jQXlzfUS95bTF3de6Yw0fXkSwFWhrq7wH3pOmwiQTvemNCP429IwN0xf0bhOOFDdTq+zxnyvr94k1J4GdtxtZep5W1M2mPu3LlGnqtqC18r/FVacovGEpvSzhRlbeGjb6xetVK57Ex7hg/oGhvNGp1Th7kcAwMDmdOpXaJoaQHVaeWclyqIx/tnP/tZYZiyz+aAbHyrpMukTbL0K0MdtuBCHbbQqZ1Jgl8cRqbsTIbzFc5+Ac1LvViviNk4fFnnrwgXHVgHVdca89UuZan7pcDlteKCbxwmzRYua2cSX/xCh36+2EIXddlDd+Wvkd2+XJd6Udm5o0o415k1axaA8ivTp3Vp+mAXm7t2qNDWzyRlu4C5dv/nUXbiV9qSUXVoZ5KyXcC++EVcv6p+4cvvCVBt+AxX37C+t68NfN7bV2aiB1dnbTMyMqI89ohzJtWJC3Yoo59pXLCLCxTZwUXt6sAX/9Chny+20EVd9mjC3r7G2bdvn+0oaMOHvXpVGRoakgrHfVazTlyq+MvqZ5rgHxEqdnBFO9P4Wq6q6lfUItxUfCg7Gln549zamVcoJa+lha2yqKcrTExMhNlaMbjZYmJiwtizVbqyfNzhJY6sLVSGQZjUziQyQyLyftB98Q2ZsjNuC1/tAMh1W2eFiXd9s0XnAEIux8KFCxWHWvLC9wG569atkw7ruy3KYNsmKvqZxLYdXKTIJq5oZxKf/aKqfj7bRgab6UeY8FEdjuv8BQ4zb9486bBFTfKs39xKYvutVUU/k8h21zTJR4r2BXdFO5P47BdN0M8kXLt402hk5Y9r14UsRQV4HI4F2PDwcOl7fR3LUwZbs56r6GeaMMbpMGnp/ualL7UQEzco6hrmQNW8xzHNpuH4Gwo0tPJ38OBB21GojC6H45iZx8fHp3zmmvlMUHWXizr8IamfKcrYgmN+kEHXLhfLPvwpHdGxSpVlgLj7h46y09fytmnLQzWy8nfUUfyTnWzda1Imnjlz5pTPKl27eWG52iOOaje3jYIrqZ8pVLvvuBbiMpTpyky7py7tTOKzzkWolp1tuLd4yqCaLvaTJ3UOIORyLFmyRH20Zc1U2dYt67ov27vt2rWrMEzZZ3OgrP5lw+kmS78yyKTB1W3udKPLL/LC69TOJKb9Qsf9dVFUdqqkg0uas+DsF9A84aORizwvWrRI3H///bajYRXOXVzr16/HGWecYTsagZIE/fgStONN0I8vYZFnDUxOTtqOQm1kNUtzrfgBwNjYmNbnsW66r4iNtOvWL2CGNN8I2vFGh35NLi99opGVPyKyHQVt5GVEma3eONLZ2Vn63qbO5pR5CajLJ6roZxLOeaIKsi+Iq1etdFa7OvBhL1sV/VQaDrjbpSocfaOR3b4+7+0bh3PXbh5V9qf01Sa6MWknLvvDBl85Ei7amYarbwT9zGPKN6x2+xLR0UT0diL6IhF9I3noipRp9u/fbzsKSsi+URTN5OT4dhKnHf+dO3cq39eGY4GdRlUti+41aSdV/YowZQuOvmI6f+vWziQmbcHNN9q24KSfKUznES6+odrt+2UA1wNYDKAn5WCBa2P+VH+IXerC001evNvrbO3evVsqfPw+mfCu2UzGFrLh0+63ZYu4frKYtoXqPTYpsoVKeNXn/+TNf6z0LNOo2KKsvhz8ougFqG0L1bIz+R1lrtWNrC2S95T5Hs4odfsS0W4AVwkhvmQuSuZZsGCBeOCBB2xHQxsy65Rx7aZI4z//8z/xghe8QPk+n2zAmbL6mST4hhwuamcS3/yiafqZpG7fsD3b9wkAP9P15baYMWOG7SjUjq63YBcYGBgodZ+OhbG54lJay+pnEt8X/85DJX0uamcSnyp+gLp+vvt+Fbj7hmrl7wYArzURkTrhNuYvSdrYvqKuzazxgBwz98jISGEYjulygTrsJqOfSVTS6FvLT1Vsa2caVd/ghu/6mYSj3nmoVv6OA/A2InqQiL7DdcLHgQMHbEehEkUVt7TrWS1/HH/YRkdHC8PI2MiHMZKyyG5FVMdLgYx+JlFpBeeYP1RR2abKtnam8d03fNfPJD71ngHqlb+lADYC2A7gaWA64cMHZFok8n7IORZceVSdsemTPXTMXvXFHqoTgnzGt4pMVYJvHManGe9Vka3UcbeNUuVPCLEi7zAVSd34MOavyePXFi5ceMS5qjO4fLKf6wt7p+lnCtOzXzmhY1xjndqZpomLFWfpV1SR8d0ucZriF6V3+CCi44jomTojUxeuLfXSpqyDtbswZbqBOTpxMs6yXRcq3Vmc3uKq+EnVZ+hAZ9dTmXSo2oGLb1TRVNYmnLoN6/ANLrTTUlY/nyqHVf2i7DOcQwihdAB4HqKu38nW8TCAl6k+x+bR398vXOTHF6zQHrYonMp31k1W3NasWaMUvsx3uEZdaavDHln6yeKTLapSNo4/vmBFqXs/fvayUt9XB3Vr7LJ/qJadRfeV/T4XqDtNpmwBYJ3QWA9SrfidDWAPgM8CuBDAZQC+CmACwLk6I2bycLXyF0fGgbLCcK7wZRGPc14BVvZHjZNNdFX8VZ6lk6qVvzg6bcEd3bZIC6dTO5MEvziMStmp+jxucE6j7crfWgDvTTn/UQD/oTNiJo8lS5aUs75jVK3kuejgMuzYsUP5Hq5p1Y0LdiijXx24YBubyKTfVe3qoOyLpUtU0Y972uvApI10V/5Ud/h4EsAyIcSWxPkBABuEEEeX6nuumVNPPVXce++9tqNRG76tVTY4OFh5sVnOS92Yoi4/0aGfKXzLK7po28Vl7Uzii1/o1C+UofX6he0dPsYAPCPl/NzWNRZwX+S5Tdag07QFnWXDcqDM5uRFC2OnhfER2eU+TNoibC7vLkWTxpqqXbsM5V5GlNUva7mwJlf8AN6TKVVb/m4AsAjA+UKIsda5ZwD4AYCNQog3GYmlZgYGBsTg4KDtaBhH5q2E4xvt2rVrsXz5cm3P42gDU9RhC936BeojaMeboB9fbLf8vQvAsQCGiOhHRHQbgAcBPAXAu3VFyjRdXV22o2Ccoh9xzk32fX19le7P2uqu6dRVCa6qX11we5M3zepVK9loZxquvmFKP6720A0nO6gu8vw4ohm/1wHYD2AvgI8BOFsIsVt/9Myg0trpMlW68DhXeCYmJjKvyTS/c067LDrWsjJFnn4mUe2a8dVPqqwTaUs7k7icV3RTVHaWhas9ivC6zFCZHQLgzwF065xxYuPgsNRLGThPY1dBZbkJ7mnVjQv2cGm5EBfs4TLJGa4uaVcHvvmH7mWWfLNPGeqyATTP9lXt9n0DgBforoAO0yymAAAgAElEQVQG1Mlrzcub3OH7+Lbkm5rKpA5OTfZlkB0D6jt5/tG+3gQ7xMmb6BG30V3XXlVXlKwgOySkSf4h6xu+I7v/MRvfUKkpArgGwJ0ApumsgdZ9nHbaaaVq3raQWa8vL0zZa67RTucjjzwiHV5nOJco89ZtYgeZMsjqJ4tpW3DC9K4EurUzia+7d5ShnZ4y+vlqi7rvrQosL/L8cgBbAGwG8D5ELYFXto4/1Rkxk4dLlT/Tu1FwWui57A8Q18ych42theqyhcoPUJWuparpcc03bNgi+Z2uVP6qdjnq0NYV/1CJR5p+PuUTn9KSxHbl72DOMakzYiYPn8b8VancuezoeZgY88fVFiq4YguXxo01QXcZZO3gknZ14Jt/lNHPNxvoom676K78qc72PSrn6KjYAx3Ioex4g+Ss36LxTlyQHVchu3BxsEV6OG6ojrcpGifLmSqzFH2zh2/pqYqOGay+jI31IQ2l0FmT5HKceuqp8tVtByg75s/HVj8hhPjnlc+VCieTRs52EEJPa17ds/YeeughI891ZUyjbVT0VA1nSjtTqPq2734hU3bK2ozzbF+OY4Rhudu3M+9QeM40AB8GsBXRWoHrAFyQCHMxgA0A9rT+vijlOYVh0g6XxvxVJcspsyqDLjhxVbZu3aoU3oc0V8Wlyp+qfqZpun+ovCS5pp1pfPMNFf2qTjRsAnWmX3flT3Wpl70AxnMOWT6NaLHo8wE8F8DdAL5PRJcAABGdD+AmAF8AsAzAF1vXz2k/QCZMFvv27VOIqnlkm52LFmsuWuKEw9R8GVsMDQ1JhZPdxcTVZv8qfhG/5tryPkNDQ8r36LBFVhiZnXBcQrctVHyjjHYm0WWLrC5Ml/JNHrJdsEVlp8ywoHi56qJ9ZG0hE64oTNZSUSxQqSkC+CMAr00cbwbwPwA+KfmMEwCMAHhK4vxPATzc+n89gM8nrn8RwNrY58IwWYdPEz7iqHT9cn5j0zHovMlvrbZngHOZNBD840i4aBdIp6p+Tc0TLgDLEz6+LIT4SuL4BwC/B+AZko/5FYB3CSGeSJz/AYBnEdFcAKcD+GHi+q0AziGio4nouKIweRGYPn26ZFR5kNe64+KbWVV6enqkwhW9sclOgPCN82653eqED1n9TCKjt8+TQfLI8w8XtKsDXzWvql9T8wTgX5opqlBqeBDRd4UQF1e4/68AfAjAOQB+AeB0IcSG2PXTEbX2LQVwTFEYIcSmrO9aunSpuPvuu8tG1WmyKoGudf1V4dFHH8UJJ5yg5Vk+2YULOvUL1EvQjjdBP74Q0XohxJm6njdN8cs7My6dAKB0pIioA8DlAL4PoKt1OjmG8MnW32NxON55YZLf0V6MGk972tMwMjKC0dFRPPbYYwCA/v5+jI2NYefOnQCAvr4+TExMYNu2bQCA3t5eAMDw8DAAYP78+ejs7Dw0Bqanpwfd3d3YsmULAGDOnDmYPXs2Nm/eDACYPXs25s6di8HBQUxOTmLWrFno6enB0NAQJiYm0N3djXnz5mF4eBjj4+OYOXMment7sX37doyNjaGzsxO//OA1WPjxz2L37t3o6OjAwMDAoXQAwM6PvgdLr/881q5deyhNP/o/l+CU930MM/78fdi2bRsmJiZw8xWX4qzrrnciTX19fdi5c2dmmhYuXHiETrfddhtOPPFEAMC2v74Wz7vxa1I63XXtVbjwS9+akqYTP/ZZjIyM4CsXn4ezrrveWpp0+d5d116F87/wL4U6bX7nW3HS+z9xRJr+46o34oXX32g0TRs3bsRFF11k3Pe2XPsOnPyhT0nptO6v/hyv+e7q1DTd+vpX46zrrmdRRuTpdNe1V+G1310tpVNWGbFjxw6ce+65zqSpbH76j9dfjpPe81EpnQY/+E5c9K1bnE+TjO/ddNNNWLZs2RE6bf7ANXj5TbdKpamOMsJWfnr4fVej/7q/056fdKVJJ0otf0R0EEDWDWuEEC8qFQmijyOa/PECAIsB/AzAYiHE/bEwiwHcC2AFgMmiMEKItVnfNzAwIAYHB8tElRW+tmqtXbsWy5cvtx2NQEmCfnwJ2vEm6McX3S1/qrN9X5dxXAZgVZkIENFHAPw+gN8TQvwawG9bl7oTQdutefslw2TCYcyfjllsaTN+OY5bSMZ5zpw5UuGqfIerqMTT1TRl6aeKD7bQRV220KWdSYJfHEa27EwL6xvBLxLonD2icgAgAP8AYDViM38BPAVRy94VifCvRdTq2CMTJu+7lyxZojTLhgtNWZdp165dpe/1If1lcGVrNyGq6WeaJvqHSpq/8eLnG4yJu/jiF6p5z5d0m6JJ6/yBiJ5BRG8ioo8T0dNb595CRPMUnnEUovX5ZiNa3PnQzN/W//8F4KLEbasA3COE2CkTJu/79+7dKxtV5ygzS9P1dZlUiY9/qLKdl49vd7LbAGZRx2w+E+NXsijrH2Xvd52qa9n1vPsjOqNjjap+UeYZLpCX9zivc6iTqlvfsfELlZoiokkdvwLwNUSTLU5unf8kgM9JPuMoAF8C8D1EE0WOTxwdiLqBDwC4BsApAN4F4CCAl8eeUxgm62jSOn8y17ihslaVT+muiivbXLm0VlzwjwhZO7iknWl89A1V/Xy0QVVs2QSWt3e7HcBbW/+PxSp/zwcwJPmMXkRds1lHbyvchYgmb4wD2ATglSnPKgyTdixatEijJO7i6962mzZtMvJcjraogq30mtIvUJ0inwja8aaMfr7+jnBDd+VPdbbvHgCLhBC/JKIxROvpPUxEfYi6W3MXV3aFZcuWiY0bN9qORmVkZ/P6Nuv3scce0zrw3Df7qGAj7br1C5ghzTeCdrzRoV+Ty0ub2J7tux3RPrpJXgSAzdopnMf8xZEdb8B6XEIKupfpKdrxwjdk9u80SROWWeJKkW8E7XhTVj/bZUZAP6qVv+sA3EhE7WVdnkpEVwD4GIAPa42ZQVRaO00gs5l0mfsA+YqMKxm4jC0mJye1bm4PuGEPk37hEpOTk4VhTNuCk83q8guZFh0Z7UxShy24+IbpspMTZWyhOunPN7spb+9GRG8G8NcAnopojN4ogL8UQnxFf/TMsGjRInH//fcXB/SAogKdYxP+xo0bsWxZWgO0PPEZ0E3FlvY69DMFx/xggiw7uKydaXwoM3SVnZxtYII6fEN3t2+5WSLRFmxnADgdwHSdgxDrOHxa56/sDF/OA3RV1qpyaX07V7CdVpfW+bNtCxfJs4lL2tWFTz6iUz9f1o2tSl02gO11/loVxn1CiPVCiP8RQuTupuEi+/btsx0FLWS9gcm8hdSxnpsp2vsgysCtG9wUqmN2TPqFin6m8V13GZJa59nEJe3qwicfUdWvaF1Zn2xTFq42UKr8EdHRRPR2IvoiEX0jeZiKpG6E5TF/usiq2BRVeLgP3p2YmJAKJ9sUz7ECbIo6ui9k9TNJ0DxCpQtv9aqVTmhnEt/9QkW/0L17GB/9QnWpl5sAvBzAOgBPJq8LIVboi5o5fB/zJ5NpOWfs9evX44wzztD2PM62MIFpe+jWL1AfQTveBP34YnuplxcDeL0Q4neFECuSh65ImWb69Om2o2CMJlRk5s2T3knwCMIWRhFltgnURRX96sTHt31ZstLORbtAOjr0a3K+8AnVyt8TAH5mIiJ14lvXRXzKetH+vm04V3iGh4dtR4E9Ntc2dFk/7kMidJHlHy5rVzccK0E69Gvauqi+olr5uwHAa01EpE4OHjxoOwqVSKvI5U3gyGsN5JiJx8fHp3yWHd8ITJ3owjHtRZSxhez9ukjqZwoVW/hOGVsk/WP1qpW1aWeSsn6RLDM4vhyolJ151zmmvYgqfsESlanBAP4WwG8APAjgOwC+ET90TkM2eSxYsEBlhjUb0qacZ01D5zxF/84775QKF/akPIxLtpDVzxRh+R/5ZTqS4WxrZwqVZUs4+4WMfmV9w0dU02jSHtC81Itq5W9N3qEzYiYPjuv86SiYfMms33jx80vd50Pak5gqmEzaytRacVXj7Jt/mNCb6zp/OrT1ofzctWuXM+WAbUzo6W3lz5dj4cKF6pavCVXncalFRzdZ8V63bl3uPWXT67KdqqTJtXTl6SeDT7aoSt22qKqdSXzM92UpU3bm3ccZX/wiVP40HP39/eqWZ4avu3sIIcSaNWu0PYu7LcpiM9069auDpvlIXnq5aReYShX9mpYPXEN35a/UDh/cISLbUdBC3ibmaYO128SvcRys2tnZKRWOY9pM4cpkD0BeP5ME3ziM7EoAq1etdEI70/jsGyr6qfhFU/AprY2s/HV1ddmOQiXK7MLQnp7vw5IvfX19qefLFFYc0y+Dis5tv6jLFln6mcQHv9dFGVu0/cOGdqZpkm8U6deEslEW39eEVdrhwxd82+FDZo0/n5x248aNWLZsmdI9vtlAB7ZsUka/ugh+ko/L2pmmjq0PTdNk/UxSh2/Y3uHDCyYnJ21HQStF6/xxLqzS2L17t/I9efZpEi682ZfRry7yhks0kWRvgcvamSZeznJFp36+rpVaBo6+kVn5I6I3ElF/nZGpC1/G/AHpXRZZCz3L3M+Bjo4O5Xt8eGuvQl766y7Ey+hnEptb3dmmaPHa5I+aa9qZhmP5mIeMfkXlQbws8T1/ZOGFX2TNBAEwCqAvce41ALp0zjixcSxdurTMZBsn8XmplyxGRkYyr5VZwsI3+7Qpk646bJGnnymqpMs3/6iy9IUN7Uzim7ZFFOnny7IoVXExPahrqRcA2wCcnjg3CWCOzgjYOBYtWlTO+o7Q9EU6N23aJB3Wx/SXwSU7qOhnCpfsYRNVO7ignWl89g0Z/XxcD1MXNu2iu/KXN+bvSwC+QERvIKLXENFrABCAK4joypTjT021TurmwIEDtqNQCpmJHUl83IT7x294TWEYGVv5YBeZvTld29t5dHTUyHNl06IyqYOjj8j4tuwM7+SzTGlnCtl8Hg/nq2+sXrWysOxM6+rPCscZlbJCdZw0G9tk1QoBdAD4AIAhAAcAHETU8ncw45jUWSs1eXBc5LlK965vb3Fr1qzRvg8nZxtx6+Y2uVAwN1uYxEQXHtdFnoNfRKiUnWn4ZJeyLZy2bADLe/sehAfdvhz39s0jz4l93OmjzP6iXNNqAtu2cHF/WNs2cZE0m7ioXR344h+69PPFHjqoyxa6K3+qS72sAPDrqq2NtuG41EvRjMSs7t28bl+uM7VGR0eVmu2B4rSyaarPQLZrCyhe8Nk0prsOVX0D4JsXZFDxjThpNvneq1ZpiZMtyvgG4I9/xPNeWb8A/FsSSSX+3vhGmRojgAsBfA7APyGaAdyhs0Zq+uDY7ZtG1Zm+XN/eZLqeQjdPhIuzn213HfqqdRlUbWFbO1M0ZZKDin5NsEcRLvkFLHf7dgL4AYBxABsA3A9gAsDPAMzQGTGTB/fKX9IZsxzUx4qfEOV+gDinVxeuLAvkWgUi+Ia8DT5+9jLDMXEPn/xDNe81Ycx0FepMt+3K30dblb55sXMDADYD+ITOiJk8fBjzV6Vixz2j7tixI/Oaiy1dNlBdDqhOG+TpZwofNS5D1WWibGhnmib5RlHZKUsTbOZaGm1X/rYBWJly/jwA23VGzOSxePHictZ3DNlJHr7NAn7ggQcKwzRpAkweZScDmURGPxMUVXJ91D+LsrawpZ1pZF6AXOoCLIts2el7A4IsLtnCduVvHMApKeefDWBcZ8RMHly6fav+cLvSzaeDeDzTui6a9NbKXVed3b66C2aX7VZEHX7hWpd9FiZtwc1HisrOZBifqSOPmLKl7crfXQDekXL+GgD/rTNiJg8ulb8kYW27iLJrVXFNbxHcbOHSOn+67nUREz9iXCp/SVz9Qa+bquv8xeHeEqor/k1p+XsZgD0ArgVwFoBzAFzXahG8QGfETB6nnXZaeQUcpildWlu3bi19r092KIML6a+iXx1w/1Eri0yaXdeuLrj6Ryg7zWLSRrorfxQ9Ux4i+kMA1wN4BqLt3h4HcLUQ4otKD7LIaaedJu655x7b0TCG6vZV3NYpGhoaQl9fn7bncbQBZ3TrF6iPoB1vgn58IaL1QogzdT1PdZFnCCG+AeCZAM5E1Pp3PKeKHwBMTEzYjoIxsioyPi30vG3bNumw3BcfNYVNu6joZ5rgH0eSZxOXtDONj75RRT8f7VEGX+ygXPkDACHEASHEBiHEOiHEPt2RCuhHpULoEzIr0XOsAFclK81N8Ik4vu/8UobgGxHBN6Zie2cgV/Dl96JU5Y87XV1dtqNgjLzt3Hyht7dXOqzsVjy+2ywNWxVhFf1MIqO5LwV9WVavWjllW0BXtKuDIv/g6Bsm9GvasBlffisaWflznSr7DALyrXwcMmywxWGq2iJJO83xH3gu6LCFL63huv2CMzptEfcPjnYz6Rfc9sU25Reqz3YKnbNHuBxcl3opQmWLN84zt0xsUcTZHiq4YAvXlgtpivYyFNnCNe1M4qNflNXPR1tUwYY9oHm2b2j5Y0xWl2baW5lMWB+R7ZJoQne5LBze5HXRtC6rPIItDhNsEfAdbZU/Ipqp61mm6ezstB0FLWR1W6V1V8iE5cL8+fOlw6p03XC0BUdU9DMN9649nci8ELqknUm86dpLUFa/8HI8lTT/4GYfpcofEf1txvm5AP5DS4xqgIhsR0GZPMdKDsqOk5dpuVZ2fvHGKwrDVBn/x4mi+CcLJRdmMJp6+VK1RRLOYyDjyMQ/L0zepChuL86ytijCh5eE1atWFpadMvlD9T4XkYmvSprOu+V2fhVklT5iAJsBfA/AzNi5BQAeAfAFhedMA/AeAA8DeBLABgCXJMJc3Dq/p/X3RSnPKQyTdvgy5q/sjh7cx29U2Z+Se9plcWUz8jRsjBtT3fvZZz+pkk98G/PXlP192+Tp5/u2oKq4lk5Y3t6tG8APAKwDMBfACwHsAvAmxed8E8AvAKwA8CwAbwFwAMAftK6fD2B/6/yzAbytVcE7J/aMwjBZhy+Vvzxcc1ydmPoB8tlmstRhA98qEE2g7RdBO96Y0C+Um/Wgu/Kn1O0rhBgDsArAagD/A+CrAC4WQtyg8hwA61utdGuEEI8IIT4H4G4Al7SufxDAl4QQnxNCPCiE+HsA/wrgI7FnyIRJZfr06YrRdZu0ro2iJmhWzdMJenp6St0XxvxFlO3a0UVZ/UzDOU/oJG/IhKva1QH34QBAdf24LpNlGo6+UWbCx0wAiwE8CmASwFLVBwgh/kYI8WT7MxEdDeAkAI8S0XEATgfww8RttwI4h4iOlgmT9/0dHR2qUXaS+Di/JmXA7u7uzGtlxzL5StaLgcx9psjTzySyY/6ahOqPuS3tTCLr6z6UszL6lSlDfUW2UsfSN1SaCQHMQzS27ruIKoHtz19DbByg4jOf1XreVgBzAJwNQAB4TiLc6a3zS2TC5H2nq92+VZvPZcZ5cWmiz4unbNcFl7QWoSMdLtmiSteTb7aogg1buNrtq0tTH3xDR9lZ9Bwu+OQX0NztS9Ez5SCinQC+DeAdrciAiI4BcBOAk4QQp6pUPIloP6LJH08CWC6E+G8iWg5gDYCFQogHYmEXIJpw8oLWPblhhBA/T3zXlQCuBICnPe1pZ2zevBmjo6N47LHHAAD9/f0YGxvDzp07AQB9fX2YmJg4tBF2e1uc4eFhANGU+c7OTgwNDQGImtO7u7uxZcsWAMCcOXMwe/ZsbN68GQAwe/ZszJ07F4ODg5icnMSsWbPQ09ODoaEhTExMoLu7G/PmzcPw8DDGx8cxc+ZM9Pb2Yvv27RgbG0NnZyf6+vqwc+dO7N69Gx0dHdjxkXdj8d/cgNHRUQDAwoULM9N017VX4fJ/vcX5NA0MDGBkZCQ3TbfddhtOPPHEKTrdfMWlOOu665XTNPjBd+Kib91iPU06fa9qmja+92pc/m8/MpamjRs34qKLLqrF97556Uux7MOfclKnuvPTXddehdd+d3WlNO3YsQPnnnuuM2kqq9N/vP5ynPSejzqpk0nfu+mmm7Bs2bIpabrr2qvwkn/8Kts06dTp4fddjf7r/s7JNK1YsWK9EOJM6EKlpgjg6ozzRwH4jGrNE8DxAE4G8A4AYwAuQlS5EwAWJcIubp1fLhMm73sXL15cpQLuNKpvKC680ahy3333lbqPY1rroO4W4bL6mSb4RzE3Lj/LdhSsw9lPXM17vmDSN2B5wseniKiTiF5CRG8iovYAglUA3l+i4rlLCPGwEOLvEM0A/jKA37YuJwcnHNv6u18yTCY+jPkrGpMhu7YVu3EKiN7o0pCd0OHzGL82LqcxSz9TqIzpctluuqiSxou+dYvGmNinjC04+0le3uOaJhOUtQUr31CpKQI4BdHafP8JYC+Ak1vnPw/gr6vUQgG8GVGr3bmIJpJckbj+2tb1HgBPKQqT912ujvlTRXXtMl+QGbfiU3rL4qoNXBg35qpt6qJsa68L2pnEd78o0s/39JfFBbvA8t6+nwLwNSHECzC1de2bAF4u8wAiOoGIzk+5tBTAQQCDAP4LURdwnFUA7hFC7BRCPFEURiYu3FHZgsiHFepVYPUGZghft6iqCtdtDXUSn50Y/CLQJpQZzUG18rcCUddskl8COFHyGfsBXE9ENxDR7xDRyUT0VgB/DODTQogRRGv4XUhE1xDRKUT0LkS7eXww9hyZMKlMmzZNMqr1oZrJqmxf5nqhXxQvmW5D1R94rraQuV+2i78uG5Tt9rWlkYu+UadfxL+v7i57GVzUxxa6ys4yvuEaOuPlZWOCSjMhgGEAK1v/j+Fwt+/lAB5QeM5sAJ8BsA3ABIAtAN4ORLOPW2EuBHAvgHEAmwC8MuU5hWHSjqVLl+pohTWGzu7crOsuNGPLkBbPkZGRUvdVCecCZeJapnvPtE1k9CuiShx9Gy5Rly2E0KOdSUwvl8WJsmVn3v1c8cEvYLnb93MAbiCiJYjG1gkiegGi7uDrFSqco0KItwsh5gshOoUQ/UKIz7QS2A7zfSHEqUKImUKIJUKIf015TmGYNPbu3SsbVaeRad3Kus6522twcDD1fPzNTDZ9nO2QR5UFwE3bJEs/U5RZ5LpMWA5UsQVQv3YmaeJuFTJlZxvfbZFFY2yhWlsE8AlErXUHEc263Qvg/TprpKYPXyZ8tMlq3eHe6peF7UWCuSNjA5N2cn3SAKfF0HVTlG7XtasDzr5RVj/Oaa4bU7aC5ZY/CCGuQbQ23ysA/BGixZ0Lx9m5BPelXtLe3su2ZnAcxzBr1qwjzqks55EFR1ukUXYP4zItp2VI088kqrqy3KpJAtltqvLur1s7k1RZzoMrWfpV3ffcl7ITqJ4WLv6htMOHLyxdulTcfffdtqMhTdnZib7Namxnyuf80zcxd+5cpft8sgPAe53GkZERJf2K0GELX3zEdDp0a2cS07bg5DPtuHLSzxScdItDRPXs8AHgfaqHziZJk8fAwED5tlfL6JzIwLUp/4477hBClJ8A4StcBjW39TNJ2AP4MDrT8annn67tWTbwaa/XMsTzHtc0mECnLbh0++ZV/h5MOYYQjfUbAbCzdfwG0YLLj+qMmMnDtzF/cfIcz5exTDo3J/fBHmWwmW6Xxo01Vf888mziknZ14Jt/6NDPN5uUpW476K78ZY75E0I8O3kA+CiADwgh5goheoQQPQCeDuAriJZqYQH3MX9ximbvJcdxcR/vBwDd3cld/crj+pqHOlEZ02fSHjr1C+hB1jeapB3X7sE8yuhXdYa4j/jgG6oTPt4K4OvxE60a6ccAvFdXpEwzffp021HQRlFlLm9xSq4LV86bN0/bsziPnVMhr7CKL+raxqQ9dOpXFtcWvraJim+4oJ1pfPYNFf3y7MAx7Trw6vdCpZkQwB4AL0s5/0IA4zqbJE0eCxYsUGltdRafx/Xlceeddx5xrsxCxj7aRgj3x7ul6WeKOhdAdh0d6alTO5O4nkdMkaUfx7SYwlVbwPJSL/8N4JNEdGgrt9b/1wNgM3324MGDtqOgBZmWO66te3mMj48fcU717dTX5TwAuaVcyj5DB2n6maLK0j6++YeOlqw6tTOJDltw9I8s/ZqwBJYsnLe0U0G18vcnAKYBGCKiTUT0AKKJIE8D8DrdkTPFUUcpL2/oLO3KXZYzFo1N4OjEM2fOlAoXuium4sp4T1n9TKPSDd4EZPzDFe1M42OXL1BOv7xx5E2FY8U/iVItSAgxBGAhosWd/x3ADwG8HkC/EOJ+7bEzRGdnp+0oKCHTQpHVwlc0oYGjEz/8vquVwte1eLENyhTEtgcr9/b2Gnlu2R+lqoumu4bJyqsp7Uyhwxa+bPe1etVK5bIzDR96k3TGn60tdPYhczkWLlyo2t3uDDqXLnF1bEMR69atE0I0d8xjGpxs0dbPFDrXwuSObluY1s4kTSgbi1ApO9v4aos2XGyButb5y7wBmA3gXAAvTh46I2by4LrOX9mKX9Haf9yIr1VVNm0+TvjQ8WJQh03qWCuuil/4hq4Xxh9fsIL9On9c8ogpZMtOmeuq4VyGgy2sVv4AvAHAXkQLPSePSZ0RM3lw3uFDBt8XNi6zQwT3NJvChl3q2OFDheAb2SRfklzTzjS++YYu/Xyziyo20q+78qc68+FaAD8AsBjAsxLHyeU7n+ulq6vLdhSkxqIUTeTIOl80QNe18SqytmjT19eXeS3rvCuTHYpQtUXVazYGcyf1y0ImLjpskWYD13ykLlskSY5//OUHrymMh2nqtIXrk8ZUbSFbdhZdc+03BLDrFy6WGUVQVKGUDEz0BIAzhRAPmIuSeRYtWiTuv5/N/JTK2B7gr5uNGzdi2bJl2p7nm310YNImuvUL1EfQjjdBP74Q0XohxJm6nqfa8vd/AbBf4n1yctJ2FLQg+6bjW8Vm9+7dSuGbtp6bCjZmgavqZxpub+w2aNvINe3qwCf/aKJ+JuHsG6qVvy8AuJGI/oqIVt5GYogAACAASURBVBHRi+OHiQiagIhsR6ESKtsP+bheVdbezD4tZ6MDVxeqtbG3NrcuLNOodlO1beTTvuhtmvRyWKQfx98DkxTlE9a+oTJAEOkTPdhN+Fi6dGnJIZdukjdz1ceZjSMjI8r3cE2rKWzao4x+Jgm+cZgiW7imnUl89Isq+vlojzLYsgMsT/hITvJgOeFj//79tqOglbxFnn1kZGRE+R7fdjkpiwsbk5fRzySs3941ItNT4Jp2JvHRL8rq5+PwobL4YgfVHT5+mXeYiqRuDhw4YDsK2iiatZg3W42rE4+OjiqFb1K3ThYymtdVCVbVzzRNqvxnIfvj/uM3vKaG2LiHLz5SJu+Fil8xHGf7+rPJrceojDnwfSsz1Qzma8FVZsyWr5Xgsn7Rhmu60zD9A3TWddcbfb4udG3114azj1TxCd/KT91+0YbllpB5fcIAJgHMiX1+BMDDWYfO/miTx5IlS8p0uddG1TEFPq1SnxbPXbt2aXkON3SnwZZNyuiXxBdb6MBU3HXlvToJfnEYk/pxs4uJ+NZtA2ge85e7zh8RfQnA24UQY63PHwOQeYMQ4t06KqSmOfXUU8W9995rOxqVkH0j8+3NDQDuv/9+LFq0KPValS5tH23VxqW05elXFy7ZwwVk7eGCdqbx2TfK6OezPVSwbQfd6/xZb4WzcXDc21fn5tPc3tqSrFmzRkvrKHc7tCmbDlvpN7k/rI40+eIbVdKQdS/XvX116snZN3SVnT6gM5/XUWZAc8vfNG21yIBRZAbqt8O0/9p+UzFJ2XS1beKTXXxKS1Wq2MI336iaR3xCR3q4T5RroyOP+ICudHC1idL2br6wdOlScffdd9uOhnG4OmURjz76KE444YTS9/tqFx3UYZuq+pnGlx95E7iunSl8KTOaqp8p6vQL29u7eYEv27s1lbGxsUr3+1CImyLeamyKqvqZxqfWP924rp0pfPGHpupnCs5+0cjKH+dFnstsycRt/aEidu7ceej/Kkt8+IaOtNXR6hXXzxSmlnTgiM40ff+PX6XtWTZoul9UKTvz4G6fqsvhcKSR3b4DAwNicHDQdjSM4ks3RRpr167F8uXLS9/vs204UFW/ugh+ciRctKsDjv4R9ONL6PbVQFdXl+0oaEFm8WeubyV59PX1ZV6TWfA3b9cTn3A1TXn6maKMLXzNQ1XSY0M705S1B7eKH1BcdgYimtAS2MjKH8fWzjSHkqnExMNw3IImjYmJidyV+MtU7jjvjVxlVwIbaZ6YmDD27LK2UNlFhws6dqtIlhkmtTNJWX25lglZFJWdKnD/PcmLf5Wyk0t5Ebp9PaSoO4Jjd0UcHV0XTZ7RaVt/bl1Ptu1VN3np5aZdYCpV9GtaPnCN0O0bqEzIwFNbCDm/vZYhbT/optkgkE1ThkUE1Ai/G37RyMqf72P+kl29ZZ7hMr29vaXu495Mr4Os4QN12qCsfrZogn/IjpPlpl1gKib04/gbEmho5Y8reeP5ssIVvcVz/WFTKXBkung5F2Am4s7VHmHpn8OoLgsVbFH9Hg7otgXn35AmL/3TyO3d9u3bZzsKpZAdhFpUKeSaWdsMDw9rTwNnm5iIu0l7DA8PG2tB4qyjbkzYwqR2JikzmcFHXypTdvpqizJp8mkLyNDy5xl549iaOs6tiWnOQmVIQBMI9jhMVi9BE+0SbHGYvMaEptnDJ1s0svLX2dlpOwpaSXO8osKL85vL/PnzM6/JTt/nmFlVcXW9wzz9TCGTrvhLQhN8Q9YmcT95+MPvNhmt2vFd5yRFeU91qIDPL9Y+pilOI5d6WbJkidi0aZPtaFSiSlM892b8bdu2SRVinNOoCxcr+zL6BepBNZ8E7XgjW3YCbpUZgbDUixa4jvmLo9KKJTtRhAtDQ0OFYXx+I1Wh7KLXJpHRrw6a7huA3KSxOK5oZwMfWoRly07Z8eXc7aEDrjZoZOWPO2mVubS12+LXi57hAzK7oPiY7jyyCmhfZz5nUXaHHF8p+uHO8o+7rr3KVJSs0BS9VSg7JMA3ZH2jPVOenS8JIaweAJ4K4P0ALk2cvxjABgB7Wn9flHJvYZi0Y/HixcJFfnzBilrur/o9dZAXxwceeMDYs11EZ3xdSHsV/eqMvwu2ykN3/GSeVzXvmcJ1rerEVNnJ0cYc45wFgHVCZ91L58NKRQD4DIARAN+KnTsfwH4AbwHwbABva1XwzlEJk3UsWbJEgxT2UXFsnzLBjh07Us/7lMaq1PUiUYYs/UwSfCOiqh1saGeSpvlFKDvlcNEeuit/Vid8ENESAF8D8BsAu4QQr2qdXw9gvRDiyljYLwI4WQixXDZMFr7v7ZvEt8kPYX9Rs5j2l6AfX4J2vAn68cWbCR9ERAA+1zri548DcDqAHyZuuRXAOUR0tEwYM7F2B9UJHuzGIyhSZRs732wjk56i8V6+2KSqLXyj6naPPo35C75xmGCLwzTFFtZa/ojoNQA+AGABgJ+g1fJHRGcD+AWA04UQG2LhTwewHsBSAMcUhRFCTFnLhYiuBHAlAMyePfuM++67D6Ojo3jssccAAP39/RgbG8POnTsBAH19fZiYmMC2bdsAHN4TcXh4GEC0XlJnZ+eh2VM9PT3o7u7Gli1bAABz5szB7NmzsXnzZrS+E3PnzsXg4CAmJycxa9Ys9PT0YGhoCBMTE+ju7sa8efMwPDyM8fFxzJw5E729vdi+fTvGxsbQ2dmJvr4+7Ny5E7t370ZHRwcGBgYwMjKC0dFRAMDChQsxOjqKW1//apx13fVHpGnbX1+L/QcFTn7vR9mlKa7Thg0bcMwxx5TS6aEPvQsv/fp3nEuTLd/7+V+8Bb/391+oNU3Dw8OHWh9c872bLzsfCz/wCed0suV7v/xItK7fSe+Jyoy9e/di8eLFrNNURqe7r7oSPe/+CPs0/eQnP0Fvb29lnTa+92pc/m8/ciJNtn3ve69ahYH3f9x4mlasWKG15c/mJI9dAC5rfV6L1pg/AMsBCAALEvcsaJ0/RyZM3vf7MuYvjRU3/Tj3Wt51LuzatUspvGyafbBNES7YQlU/UzRBb1lkbeGKdqbx1TdMlZ1NwaY9oHnMn61u3w8BGBJC3JRybbL1Nxm3jtbfaZJhMtm7d69kNN1l5bdXp56//RXnpV5b+e3VuP0V5+H2V5wn9RyXab/ZtSlKQ5ZNfESHLdq+YoqkfqaQsYVMOB/QlUfOu+EruqJkDZl0+lpmmCo7fbBV4/xCZ01S5gCwGNEs3efGzq3F4Za/pYha7343cd/ZrfPPlwmTF4f+/v7q1XAm+PjmtmbNGuV7fLQDV8roZ5LgG/K4pp0pfPWJpuhnAts+AQ9a/i5G1EK3moh2E9FuRF25l7T+vwDAQQD9ifvanx8GMCQRJpNp03IbBlmTfCvJe1Ph+gYze/Zs5Xu8emOrQJ4N6rJPGf1MEnwjQqZF2DXtTBFv+fbJN8roJ+MXTSCtN4Rz2m1U/j4L4GQAy2LHOgD/3vr/swD+C8BFiftWAbhHCLFTCPFEUZi8CEyfPr1qGpwlrSsry2lNdu2ZZO7cubajwJa8ik5d/hD0c5OiSvDtrzgvaMecMvrJ+EUT4fwbClio/AkhdgshhuMHgL0A9rQ+7wbwQQAXEtE1RHQKEb0LUYvhB2OPkgmTig9j/rJoZ9KisX2cnVZljUaZSnCgXlxYY1MmPwTfOBIXtDNJmuY+jJNuU1a/preOF/nFym+vZmcfJ/f2FUL8XwAvB/AaAPcA+EMAlwshblYJk/N8E9F2Gp+6MSYnJ4sDQe7NrEmFWtaLQd3I6mcK2Tf24BtHYls7F7Cdf6qgql/Ry3MgIm0ypes4UfkTQiwXrd09Yue+L4Q4VQgxUwixRAjxryn3FYZJo6OjoziQZ2RlYo4/brNmzZIKJ5MZuTfd66QuX5DVzxRBb3XavmFbO9P47hs69ePY2lUWH/3C6vZutli6dKm4++67bUejFnys3IyMjISxRwaoy1eCfnxItggG7XijSz8ff1dcx5vt3Wyyb98+21EwikxTPec3tvZq6KpwTrMuZAdum7RVWf1MEfwif93QuF+4pp1JfPQLVf1sTw5zEV/8opGVP86tnVkLOCcrfMlwvjgsAExMTADQt2yJD7aRXY6haGHjOsYFtvUzherSFD4uh9RG1S+K7nnLT36uJ2IWKCovsiYB+eQbsmWnql9wtEWbxvqFzkUDuRwLFy5MW0PRO4oWpbS9aGVZ1q1bV+l+ruk2gQ1bVNXPJME3IrLs4LJ2pvFhe0wd+nG3gW7qsgc8WOTZOj6v89emaEwG5zEb8+bNK3WfK7NdXcCmLcrqZ5LgGxFFdnBRO9PEbcLdP6roF/LIVLjbo5GVP9PdTi7g88Kcw8PDpe4rqgw3CZvLmJTVzySc84NOirq0XNTOND75RhX9mrT0kQzc/aKRlb+DBw/ajoIWisYq+DjZAwDGx8ePOCebprwBzNzt0qbMOC/Ze3WQpp8pmjb2s4iqvlGndqZpom9k6VfFL2Tu50Rj/EJnHzKXY8GCBeod7oyQHYPAdezGnXfeKR1WJo1c7VAVW+lW0c8UvueRqmSl2wXtTOOz5rr089lGaaik15RtoHnMn/WKmI1jyZIl6pZnQJbT5Tkjx0y8a9cupfDhh/4wLlSGVfUzTRN0l0HGDs///DdqiIkb+OgXZfKeC2WGa9hIr+7KXyMXeV60aJG4//77bUfDOEVdv1zHLKxfvx5nnHGG7WiwxuaEoKCfuxTpHrTjTVn9OP9e+EJY5FkDPu9PKbuNW9HAbpcZGxvLvJa35RD7dZk0IDNDzXRBn6efScr4RtE1X5Cdufj6H/y0jujUShntufpEmbzX1Ipf2TKBi280suVvwYIF4oEHHrAdjUBJfvGLX+B5z3ue7WgEShL040vQjjdBP76Elj8NdHV12Y6CcarOfnWZvr6+0vdyTK9JbNijin4mCb5xJMnWUle1q4O8lmMu6NTPB3vogqMtGtnyF8b8yV13lY0bN2LZsmXansfVDlWxlW7d+pmmaf6Rl15u2gWmUlW/puUFlwgtfxrwecyfClwz8e7du0vdFzYpn4qttQ3L6mcSXxdEL0OeX7ionWm4tejkUVU/zmPFTcDZDo2s/BGR7SgYocykDo7O29HRIR02awJM2nXfSUur7MbtOlHRzyTBNw6TVXYkw7iinUlkbcGRsmVnEhvlhm2Kys+8cE6ic90YLsfSpUtVltdxGtm1/cqsAegqIyMjmdfyNl/3yQaylLGHafL0M0meLdrXm0JZv7ClnUmKdPfJL4r0C/njMK75BTSv89fIlr/9+/fbjoI2st7Akuez3lA4dmmNjIyUui+rO8unrd2SxDejd6VFo6x+AX3E/QIobgVtc/7XbjYar4BZivJeUntZvwgwRGdNksvR39+vXu1mhGtvLLpZs2aNVLiws8eRuJBWWf1MEnxjKrLpdEE70/jsG2X045hO3fi4vVsjW/58Jq01z6cFnlUoskMynO/2KKJJ6Vf1jaYTfKM4nI8U7RLVFL/Is4FsWOfQWZPkcvi6t28cn1v/dO/ty9kWOqnLDi7t7Rt8Q462HVzSziS+7mdrQj+OdiiLzbQitPxVx+elXlzYvss0o6OjSuGLZqZxtoUqLixpoqqfSbLGPcpud+YLRS04bTu4pJ1JivwiK4zrqOon07LH0Q5lKUorp5bQRlb+fJrwkURmCj73bs7HHnus1H3cK706cEH7svqZIm1YRNP8RHbpDte0q4P4iwB3v1DVr4lLusjCvSGhkZW/JiBT0fF5lmsanDKmaZqmfR7BLwJ5BP+IcOHF0SW4+0UjK38zZsywHQUn4NoS1t/fX+n+UHjZ1b6qfqYIflHsF65qZxpffKOsfty7u03C1TcaWfnzdcyfzI4FPmTisbExpfCurG/nCrYr/ar6mcSH/KALGb9wSTvT+OgbTdLPFDK/JxygaBJJsxgYGBCDg4O2o1Ertn/wdbJ27VosX77cdjQCJQn68SVox5ugH1+IaL0Q4kxdz2tky18TKHo7aVJLVxpNWqMqjSanXZam2qip6ValiXZqYpp9pZEtf0uWLBGbNm2yHY1ASbZt24b58+fbjkagJEE/vgTteBP040to+dOA7xXerLczX1q7JiYmKt3vgw3KIpN20/apqp9Jgm/k47J2JvHFL8ro50KZ4TJc097Iyp/PBVjW2L72eR/G/W3btq30vT6NfVQhb9HiuicCVdHPJE30DdVJYq5qF5BDRb+iMiNO0/KNDzSy8uczWeu3hcU6m/nj3iZvzKcvLwVVaKpvFO1ZGnwjol2uNqnszPON4BOH4eobjaz8dXV12Y6CUYoW8OW+WGdvb6/yPaHAmorNRZ7L6GeKpm3jJkNeXnFJO9P4uPNLVf1COZq9swc3uzSy8heIaMIuD7I/7r7bIU6o8ESEH7KpBL84TPCNw/i43mFZfPKLRlb+9u3bZzsKlcmrrKQ5aFp4ro48PDx8xDmVylvWm5svFUBV35C5Tydp+pmiTJo4duHIUMYvkraoUztTFNkB8HdpLNWys6i88MUuQAP9QgjRuKO/v1/4yoqbfpx7Le86F9asWSMVTjatPthEFhfSKqufKYps4Es+UUUmzba1M42K7hx9RFU/jmnUiWpZYNJeANYJjfWgRrb8dXZ22o6CNvJmXbF+K8khb52q+Nuo7DZu3MdAppGVlqIWzjpsYGOdMZlZrfHrHFvEZSirb/s+H9eIk+nWLJpEx4Us/cqUF761/MUpmvCUZy8uhEWePYdr124eYaFSPdjyjaCfuxT5RNCON1X08/G3hBNhkWcN+DDmTxYfM+vQ0JDtKHiBLd8I+rlLkU8E7XhTRT8ff0uaTCMrf02hqEne1yb7OMEG2TQ57UDwjSyamu42wS/SaWq6AbnJINxoZOVv+vTptqNghKzxfz7N9AWAnp4eqXAyM9W42qAMMqvy11GQyepnCtkxoU3xDdndGlZ+e7V17Uzje5mgop/KLh5cK0A64LrIs5Uxf0R0I4D/k3LpHUKIf26FuRLAVQBOBLABwNuEEBsSzykMk8bSpUvF3XffXS0RzPCpUHv00Udxwgkn2I5GoCRBP74E7XgT9OOLL2P+ZgC4D8CyxPFtACCitwD4NIAPtc6vAfBTIupvP0AmTBZ79+7VmRan4Pb2UYYtW7ZIhw1dOFORSa9pm6joZ4qibpym+QUgp/vLPv/1GmJiD9/9okze455mHfjY7WtlnT0AXwawNuPaUQAeA3Bt4vztAL4sGybv8HmdPyHS1xrKWn+I4zpOutca42iDMrjiF5zWimuCb6j4xbL3f9x0dNjA0TdU8p5Pvxk+gAas83c6gOMA/DBx/lYAf6AQJhNfx/wBfnXvZjFnzhypcLJv8b7bq03aGNCstJu0iax+Jgm+cRgVv/iXy86vJU62UGkZ5+gbKnkva8w4x3RXRbZ1j1UroM6apOyBqOXvPgDfAzAGYDOA81vXLgcgADwtcc8lrfPHyoTJ+/4lS5boqIg7jcwuBlzZtWtXpfs5p10ntuxQVT+TBN+IyLKDy9qZxoedX3Tox90GuqnLHtDc8jetvmrmESwC8B0AfwHgCgDfI6KzAXS1ro8nwj/Z+nusZJjfxi+0Jodc2fq4j4jurRR7BlDF6w7zDAD/W+UBjNOuFUt2qKyfSYJvRGTYwWnt6oC5f2jRj7kNtFOTPQZ0PsxW5e8WRLXYz7Y+v5+IXgXgwwD+pXUu2SXd0fo7DcCkRJgpCCE+D+DzAEBE64TGWTOBegn68Sbox5egHW+CfnwhonU6n2dlzJ8Q4juxil+bTQDOxOEWu+7E9WNbf/dLhgkEAoFAIBAIJHBpwscMAJ0AHmx9Ti7Z0o+om3eXZJhAIBAIBAKBQILaK39ENIOILkucOwZRq98aRJM/tgO4KHHrBQBuE0JMSobJ4/Mlox9wg6Afb4J+fAna8Sboxxet2tW+wwcRPRvAXQA+h2h83wxEY/3OAXC2EGIzEb0OwI0A/hTAfwF4E4C3ADhXCHFn6zmFYQKBQCAQCAQCU6l9wocQ4kEieh6AvwbwCwDTEbX4nS2E2NwK80UiOgrA+wD0IBoP+JJ4pU4mTCAQCAQCgUBgKlb29g0EAoFAIBAI2MGlCR+BQCAQCAQCAcM0rvJHRBcT0QYi2tP6+yLbcQoARDSNiM4ioq8S0RtSrp9LRHcQ0RNEtJmILi8TJqCflnYfJqKtRLSXiNYR0QWJMIX5LuTN+mlp9x4iepiInmzZ/ZJEmKAdA4joqUT0fiK6NHE+6OcoRHRj6/cqefxJLMyVrd+zPUT0cyJ6TspzCsMcgc7tQlw/AJyPaA3AtwB4NoC3AdgD4BzbcWvyAeBSAAcBbEG0Pd8bE9dPB7AXwAdaur0a0baAl6mECYcx/T4D4DYASwAsA/DPLT0vaV0vzHchb1rT7puIxl6vAPCslv0PAPiDoB2vo5UPRwB8S0WboJ9Vzb4M4P8BOCVxHNu6/hYATyDa0vbZiCbH/hpAf+wZhWHSjkaN+SOi9QDWCyGujJ37IoCThRDLrUWs4bSW+pkuhNhNRALAm4QQN8au3wygWwjx4ti59wF4nRCiVzZMQD9EdAKADQD6hBBPxM7/FMCzhBAny+S7kDftQER/AeAfhBBPxs6tR7QD0xuCdjwgoiUAvgbgNwB2CSFe1Tof9HMYIvoygN40O7cmtO4C8LdCiOti528HsFUI8UcyYbK+uzHdvkR0HKLWoR8mLt0K4BwiOrr+WAUAQAixRwixO+1ay7l/H+m6nUREAzJhdMc5cIhfAXhXvOLX4gcAnkVEc1GQ70LetIcQ4m8SFb+jAZwE4FEZXYJ29iEiQrR02ucS54N+vDkdwHFI1+YPFMKk0pjKH6KmVADYmjg/jGhP4FMQcJG5iLbxS9MNiDa7lgkTMIAQYr8Q4kspl45B1PV7cutzXr4LedMBiOhZiNZefRLADZDTJWhnnysAPBNRF2KcoB8PjiOi7xHRWGvc3vmt889u/U3T5ngiOlYyTCpNqvx1tf6OJ86333ozjRSwioxuQVuHIKIORONPvo+gHwuIaD+AhwG8GMDLhRCPIWjnPET0VACfQNT6PpG4HPTjwSIA9wB4DoCbAHyPiH4HhvVrUuWvveVbMs0drb+1L3gdkEJGt6CtW1wHgAC8HkE/LswH0AfgWgC3E9FFCNpx4EMAhoQQN6VcC/q5zy0A3iaEeK8Q4iEhxPsBDCGatGFUvyYJ+9vW3+7E+XbNeH+NcQnII6Nb0NYRiOgjiMZf/p4Q4tdEJKPNExJhAgYRQuxq/ft3RLQYURfiC1vngnYO0tLpzQBekBEk5D3HEUJ8J+X0JkSz729ofe7G4ZY8IPu3LytMKk1q+RtCNAapP3G+/fnheqMTkEEI8TiiSQWZusmEMRfDABANOieifwBwJqL9tduVCZl8F/KmW2wE8NTWEbRzl4sRtfCsJqLdRLQbwDkALmn9fwGCfhyZAaATwIOtz2najCOa5SsTJpXGVP5asxH/C8BFiUurANwjhNhZf6wCkvwEwKrWrLY2qxAta/DfCmECBmjNtv4CgNkALojP/JXJdyFv2oGITogNLo+zFFGFYBBBO5f5LKIJVctixzoA/976/7MI+jkLEc0gossS545B9AK9BsBmANtxpDYXALhNCDEpGSYd24sc1nkg6o46AOAaRLOY3oWokHu57bg1+UD0lnN86xAtfY4H8PTW9dMQdU9cj2hc0p8A2Afgz2PPKAwTDiPaHQXgSwC+B+CEmI7to0Mm34W8aUW74xC1HNwA4HcQVSTeCmACwCdldQnauXMAWIupizwH/Rw9EM3U/Q2AjwBYiGjCx60AdgNY2ArzulZ+fC2i1rzrW5+fG3tOYZjU77dtAAsGvxDAvYiaRDcBeKXtODX9ALC8VelLHmtjYc5BtBL6OKKdQN6a8pzCMOHQrl1vhnbto7cVrjDfhbxpRb/ZiHaG2Nb6wdgC4O1AtAFA0I7Xkaz8Bf3cPlqVvu+0KoFPIFofdWEizOsRdc8/CeBOROOpk88pDJM8GrXDRyAQCAQCgUDTacyYv0AgEAgEAoFAqPwFAoFAIBAINIpQ+QsEAoFAIBBoEKHyFwgEAoFAINAgQuUvEAgEAoFAoEGEyl8gEAgEAoFAgwiVv0Ag4B1EJIjoy7bjEQgEAi4yzXYEAoFAwAA9iBasDQQCgUCC0PIXCARYQkS9rRa+3uQ1IcQuIcTj9cdKDiIaJqI/sh2PQCDQTELlLxAIBAKBQKBBhMpfIBBgR2s83yOtj4+0WgDXxq7vIqIPxD5/gIg2EtFFRHQfEe0lov9HRP1EdCER3UtEe4joTiJ6TuK7fpeI7iCicSK6n4j+UCJ+pxPRWiL6NRHtJqJfENFLieiPiEgAOAnAl1rxFrH7phPRx1rx301EXyei4+PpJqKfEtGbieh/iOgJItpEREtjYV7cSttviWi0Ff4sZSMHAgFvCZW/QCDAkXcAaFdozkI0xu+SgntOAfA6AJcBuADAfACrAfwJgFcCuALAaQA+0b6BiE4H8FMANwM4FcA7AXySiF5S8F1fBjAI4PTWMz8N4ACAf23FdTuAP2v93xO77+sAVgK4GMBzEW3U/r3Es18IYCaAlwP4QwDPAPBvRNRBRNMBfBPAj1rxPQPAVwEcLIhvIBBoEGHCRyAQYIcQ4nEi+lXr46+EELskbjsGwFuFEFsB3EdEXwfwlwCWx869BMDLYvdcB+ALQohPtz4PEdFcRJXIH+d814kA/lEIMdz6vC12bZyIJgE8Ho83ET0XwIUAetvnieiNAIaJaLEQ4r5W0HVCiE+1/n+EiPYAuA3AeQDuAPD0VpitrTDtOAQCgQCA0PIXCASaw+OxChEQtaolz+3A1HLxHABvbHWvPkFETwD4DIDegu96L4DPtLqT/5mI/kAifucA6ATwUOy7fgvghLzvE0L8FMAYgFOFELsB/A2ACYoNGgAAAihJREFUHxDROiL6h1alMhAIBA4RWv4CgUBT2Ct5Lo4AcDWAf0+c35d7kxB/T0Q/AXA+okrdj4joHUKIzxZ814OY2vLYZmfWTUREADoA7G99918S0bcAvBhRF/IdRHSJEOL7eXEOBALNIbT8BQIBrrQnSph8iV0L4EwhxEOJY1vRjUKIQSHEp4QQFwN4P4A3xC/jyHivBfCs1r3J79sTC9eZuO9lAI4GsCH23euFEB8VQvw+gC8BeL1UagOBQCMIlb9AIMCVXyOqRL2SiJYQ0Z8Z+I53A7iUiP6GiBYT0XOI6M+I6J+ybiCio4joO0R0ARHNJ6LFAFYA2BILNgrgAiJaQERvJaLZQoj1AL6BqJXwAiLqI6LziOjbidm6y4jo6tb11wD4CoA1Qog1RHQ8EX2TiF5ERM8kojMQTYiJf3cgEGg4ofIXCARYIoQYA/AFAH+FaDbu/FYXqM7vuBfACxDN2L0L0ezgFcD/b+eOcTEKojAMv6JRWIgtqK3BCqzADiQ2oCDRqCzBEvR/RWkddKO4I1EhGol5nnLumZvc7suZObe7L7btz9qL6rmto/dWnX+qualO2iaJj6uDuX5W3VfX1VPb/b3dfM+HXXVYPVa3bcMep/PZa/VSXbUFvoe59/LnXw38d3tjjO+rAPhz8/+GR2MMQxzAr+n8AQAsRPgDAFiIY18AgIXo/AEALET4AwBYiPAHALAQ4Q8AYCHCHwDAQoQ/AICFvAN05qbom2c56QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "exp2.net.plot.reservoirSpikeTrain(figsize=(10,5), fr=0, to=500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "exp2.net.plot.reservoirRates(figsize=(10,2), ylim=(0,0.4), fr=0, to=500, legend_loc='upper right')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "wgt = exp2.net.trainedWeightsExex[-1].toarray().flatten()\n",
    "nz = np.array(np.nonzero(wgt)[0])\n",
    "\n",
    "plt.hist(wgt[nz], bins=np.arange(np.max(wgt[nz])))\n",
    "plt.xlim((0,100))\n",
    "pl = plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Weight matrix after learning\n",
    "exp2.net.plot.trainedExWeightMatrix()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.935 0.43125 0.406875 0.80375\n"
     ]
    }
   ],
   "source": [
    "size = exp2.p.inputNumTargetNeurons\n",
    "\n",
    "input_regions = exp2.net.trainedWeightsExex[-1].toarray()[:2*size,:2*size]\n",
    "\n",
    "inp_lt = input_regions[:size,:size]\n",
    "inp_rt = input_regions[size:,:size]\n",
    "inp_lb = input_regions[:size,size:]\n",
    "inp_rb = input_regions[size:,size:]\n",
    "\n",
    "print(np.mean(inp_lt), np.mean(inp_rt), np.mean(inp_lb), np.mean(inp_rb))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cluster1_mean = []\n",
    "cluster2_mean = []\n",
    "all_mean = []\n",
    "\n",
    "cluster1_mean.append(np.mean(exp2.net.initialWeights.exex[:size,:size]))\n",
    "cluster2_mean.append(np.mean(exp2.net.initialWeights.exex[size:2*size,size:2*size]))\n",
    "all_mean.append(np.mean(exp2.net.initialWeights.exex))\n",
    "\n",
    "for i in range(exp.p.trials):\n",
    "    cluster1_mean.append(np.mean(exp2.net.trainedWeightsExex[i][:size,:size]))\n",
    "    cluster2_mean.append(np.mean(exp2.net.trainedWeightsExex[i][size:2*size,size:2*size]))\n",
    "    all_mean.append(np.mean(exp2.net.trainedWeightsExex[i]))\n",
    "\n",
    "cluster1_mean = np.array(cluster1_mean)\n",
    "cluster2_mean = np.array(cluster2_mean)\n",
    "all_mean = np.array(all_mean)\n",
    "\n",
    "c1 = cluster1_mean/all_mean\n",
    "c2 = cluster2_mean/all_mean\n",
    "plt.figure(figsize=(10,3))\n",
    "plt.axhline(y=1, color='black', linewidth=0.5)\n",
    "plt.plot(c1, label='A')\n",
    "plt.plot(c2, label='B')\n",
    "plt.ylim((0.5, np.max([c1, c2])+0.5))\n",
    "plt.legend()\n",
    "pl = plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Store data\n",
    "weights = {\n",
    "    'initial': exp.net.initialWeights.exex,\n",
    "    'train1': exp.net.trainedWeightsExex,\n",
    "    'train2': exp2.net.trainedWeightsExex\n",
    "}\n",
    "\n",
    "np.savez_compressed('data/assemblies/weights_seed-'+str(exp.p.seed)+'.npz', **weights)"
   ]
  }
 ],
 "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": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}