SomaticFeaturesTest_CA1_pyr_cAC_12AUG16.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "#pip install sciunit quantities efel scipy json2html neurom"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "#% matplotlib notebook\n",
    "% matplotlib inline\n",
    "from json2html import *\n",
    "from quantities import mV, nA\n",
    "import IPython\n",
    "import json\n",
    "import collections\n",
    "\n",
    "#import sciunit\n",
    "from hippounit import models\n",
    "from hippounit import tests\n",
    "#from hippounit import capabilities\n",
    "#import matplotlib.pyplot as plt\n",
    "\n",
    "from neuron import h\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\"><tr><th>AP1_amp.Step1.0</th><td><table border=\"1\"><tr><th>Std</th><td>5.46582296368</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>84.8916666031</td></tr><tr><th>Stimulus</th><td>Step1.0</td></tr><tr><th>Type</th><td>AP1_amp</td></tr></table></td></tr><tr><th>APlast_amp.Step1.0</th><td><table border=\"1\"><tr><th>Std</th><td>12.94176933</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>61.2768380869</td></tr><tr><th>Stimulus</th><td>Step1.0</td></tr><tr><th>Type</th><td>APlast_amp</td></tr></table></td></tr><tr><th>AHP_depth.Step1.0</th><td><table border=\"1\"><tr><th>Std</th><td>4.91970618493</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>12.1357640551</td></tr><tr><th>Stimulus</th><td>Step1.0</td></tr><tr><th>Type</th><td>AHP_depth</td></tr></table></td></tr><tr><th>voltage_deflection.Step-2.0</th><td><table border=\"1\"><tr><th>Std</th><td>14.4013027106</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>-45.0851328288</td></tr><tr><th>Stimulus</th><td>Step-2.0</td></tr><tr><th>Type</th><td>voltage_deflection</td></tr></table></td></tr><tr><th>voltage_deflection.Step-1.0</th><td><table border=\"1\"><tr><th>Std</th><td>5.97743835886</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>-22.9514081558</td></tr><tr><th>Stimulus</th><td>Step-1.0</td></tr><tr><th>Type</th><td>voltage_deflection</td></tr></table></td></tr><tr><th>voltage_deflection_begin.Step-2.0</th><td><table border=\"1\"><tr><th>Std</th><td>15.7193976351</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>-50.2771542801</td></tr><tr><th>Stimulus</th><td>Step-2.0</td></tr><tr><th>Type</th><td>voltage_deflection_begin</td></tr></table></td></tr><tr><th>voltage_deflection_begin.Step-1.0</th><td><table border=\"1\"><tr><th>Std</th><td>7.60658440662</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>-26.9601994129</td></tr><tr><th>Stimulus</th><td>Step-1.0</td></tr><tr><th>Type</th><td>voltage_deflection_begin</td></tr></table></td></tr><tr><th>time_to_last_spike.Step0.2</th><td><table border=\"1\"><tr><th>Std</th><td>123.499701459</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>83.4799264706</td></tr><tr><th>Stimulus</th><td>Step0.2</td></tr><tr><th>Type</th><td>time_to_last_spike</td></tr></table></td></tr><tr><th>time_to_last_spike.Step0.4</th><td><table border=\"1\"><tr><th>Std</th><td>141.569702022</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>187.077745098</td></tr><tr><th>Stimulus</th><td>Step0.4</td></tr><tr><th>Type</th><td>time_to_last_spike</td></tr></table></td></tr><tr><th>time_to_last_spike.Step0.6</th><td><table border=\"1\"><tr><th>Std</th><td>121.350947588</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>267.77495098</td></tr><tr><th>Stimulus</th><td>Step0.6</td></tr><tr><th>Type</th><td>time_to_last_spike</td></tr></table></td></tr><tr><th>time_to_last_spike.Step0.8</th><td><table border=\"1\"><tr><th>Std</th><td>112.16782043</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>279.147794118</td></tr><tr><th>Stimulus</th><td>Step0.8</td></tr><tr><th>Type</th><td>time_to_last_spike</td></tr></table></td></tr><tr><th>time_to_last_spike.Step1.0</th><td><table border=\"1\"><tr><th>Std</th><td>113.050566913</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>296.700294118</td></tr><tr><th>Stimulus</th><td>Step1.0</td></tr><tr><th>Type</th><td>time_to_last_spike</td></tr></table></td></tr><tr><th>inv_time_to_first_spike.Step0.2</th><td><table border=\"1\"><tr><th>Std</th><td>33.1818009502</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>22.920294291</td></tr><tr><th>Stimulus</th><td>Step0.2</td></tr><tr><th>Type</th><td>inv_time_to_first_spike</td></tr></table></td></tr><tr><th>inv_time_to_first_spike.Step0.4</th><td><table border=\"1\"><tr><th>Std</th><td>66.7987755836</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>58.2856477082</td></tr><tr><th>Stimulus</th><td>Step0.4</td></tr><tr><th>Type</th><td>inv_time_to_first_spike</td></tr></table></td></tr><tr><th>inv_time_to_first_spike.Step0.6</th><td><table border=\"1\"><tr><th>Std</th><td>91.7364918604</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>95.7682432487</td></tr><tr><th>Stimulus</th><td>Step0.6</td></tr><tr><th>Type</th><td>inv_time_to_first_spike</td></tr></table></td></tr><tr><th>inv_time_to_first_spike.Step0.8</th><td><table border=\"1\"><tr><th>Std</th><td>120.094726255</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>145.369663428</td></tr><tr><th>Stimulus</th><td>Step0.8</td></tr><tr><th>Type</th><td>inv_time_to_first_spike</td></tr></table></td></tr><tr><th>inv_time_to_first_spike.Step1.0</th><td><table border=\"1\"><tr><th>Std</th><td>143.713839424</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>192.505146651</td></tr><tr><th>Stimulus</th><td>Step1.0</td></tr><tr><th>Type</th><td>inv_time_to_first_spike</td></tr></table></td></tr><tr><th>inv_first_ISI.Step0.2</th><td><table border=\"1\"><tr><th>Std</th><td>22.9945399665</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>12.7755084053</td></tr><tr><th>Stimulus</th><td>Step0.2</td></tr><tr><th>Type</th><td>inv_first_ISI</td></tr></table></td></tr><tr><th>inv_first_ISI.Step0.4</th><td><table border=\"1\"><tr><th>Std</th><td>39.8476297367</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>38.4188926731</td></tr><tr><th>Stimulus</th><td>Step0.4</td></tr><tr><th>Type</th><td>inv_first_ISI</td></tr></table></td></tr><tr><th>inv_first_ISI.Step0.6</th><td><table border=\"1\"><tr><th>Std</th><td>48.0836477317</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>64.3547193671</td></tr><tr><th>Stimulus</th><td>Step0.6</td></tr><tr><th>Type</th><td>inv_first_ISI</td></tr></table></td></tr><tr><th>inv_first_ISI.Step0.8</th><td><table border=\"1\"><tr><th>Std</th><td>49.5349726635</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>88.1586638814</td></tr><tr><th>Stimulus</th><td>Step0.8</td></tr><tr><th>Type</th><td>inv_first_ISI</td></tr></table></td></tr><tr><th>inv_first_ISI.Step1.0</th><td><table border=\"1\"><tr><th>Std</th><td>48.2415016491</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>109.788308128</td></tr><tr><th>Stimulus</th><td>Step1.0</td></tr><tr><th>Type</th><td>inv_first_ISI</td></tr></table></td></tr><tr><th>inv_second_ISI.Step0.2</th><td><table border=\"1\"><tr><th>Std</th><td>8.65938397872</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>4.19259087372</td></tr><tr><th>Stimulus</th><td>Step0.2</td></tr><tr><th>Type</th><td>inv_second_ISI</td></tr></table></td></tr><tr><th>inv_second_ISI.Step0.4</th><td><table border=\"1\"><tr><th>Std</th><td>21.466084734</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>18.3120301336</td></tr><tr><th>Stimulus</th><td>Step0.4</td></tr><tr><th>Type</th><td>inv_second_ISI</td></tr></table></td></tr><tr><th>inv_second_ISI.Step0.6</th><td><table border=\"1\"><tr><th>Std</th><td>30.1651087158</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>39.262063079</td></tr><tr><th>Stimulus</th><td>Step0.6</td></tr><tr><th>Type</th><td>inv_second_ISI</td></tr></table></td></tr><tr><th>inv_second_ISI.Step0.8</th><td><table border=\"1\"><tr><th>Std</th><td>32.5073380676</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>58.9584670424</td></tr><tr><th>Stimulus</th><td>Step0.8</td></tr><tr><th>Type</th><td>inv_second_ISI</td></tr></table></td></tr><tr><th>inv_second_ISI.Step1.0</th><td><table border=\"1\"><tr><th>Std</th><td>35.0635841451</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>75.5752149078</td></tr><tr><th>Stimulus</th><td>Step1.0</td></tr><tr><th>Type</th><td>inv_second_ISI</td></tr></table></td></tr><tr><th>inv_third_ISI.Step0.2</th><td><table border=\"1\"><tr><th>Std</th><td>5.59320148694</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>2.26780561612</td></tr><tr><th>Stimulus</th><td>Step0.2</td></tr><tr><th>Type</th><td>inv_third_ISI</td></tr></table></td></tr><tr><th>inv_third_ISI.Step0.4</th><td><table border=\"1\"><tr><th>Std</th><td>14.0361888911</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>11.4742926717</td></tr><tr><th>Stimulus</th><td>Step0.4</td></tr><tr><th>Type</th><td>inv_third_ISI</td></tr></table></td></tr><tr><th>inv_third_ISI.Step0.6</th><td><table border=\"1\"><tr><th>Std</th><td>19.4915882727</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>23.9402894951</td></tr><tr><th>Stimulus</th><td>Step0.6</td></tr><tr><th>Type</th><td>inv_third_ISI</td></tr></table></td></tr><tr><th>inv_third_ISI.Step0.8</th><td><table border=\"1\"><tr><th>Std</th><td>21.9318520268</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>37.3347648764</td></tr><tr><th>Stimulus</th><td>Step0.8</td></tr><tr><th>Type</th><td>inv_third_ISI</td></tr></table></td></tr><tr><th>inv_third_ISI.Step1.0</th><td><table border=\"1\"><tr><th>Std</th><td>23.0096343861</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>49.7646305833</td></tr><tr><th>Stimulus</th><td>Step1.0</td></tr><tr><th>Type</th><td>inv_third_ISI</td></tr></table></td></tr><tr><th>inv_fourth_ISI.Step0.2</th><td><table border=\"1\"><tr><th>Std</th><td>4.43826691184</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>1.15366726766</td></tr><tr><th>Stimulus</th><td>Step0.2</td></tr><tr><th>Type</th><td>inv_fourth_ISI</td></tr></table></td></tr><tr><th>inv_fourth_ISI.Step0.4</th><td><table border=\"1\"><tr><th>Std</th><td>11.8788378935</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>8.01203074215</td></tr><tr><th>Stimulus</th><td>Step0.4</td></tr><tr><th>Type</th><td>inv_fourth_ISI</td></tr></table></td></tr><tr><th>inv_fourth_ISI.Step0.6</th><td><table border=\"1\"><tr><th>Std</th><td>16.9548351502</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>16.8945859886</td></tr><tr><th>Stimulus</th><td>Step0.6</td></tr><tr><th>Type</th><td>inv_fourth_ISI</td></tr></table></td></tr><tr><th>inv_fourth_ISI.Step0.8</th><td><table border=\"1\"><tr><th>Std</th><td>17.7187139157</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>28.5911378123</td></tr><tr><th>Stimulus</th><td>Step0.8</td></tr><tr><th>Type</th><td>inv_fourth_ISI</td></tr></table></td></tr><tr><th>inv_fourth_ISI.Step1.0</th><td><table border=\"1\"><tr><th>Std</th><td>19.0269276537</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>37.1616506865</td></tr><tr><th>Stimulus</th><td>Step1.0</td></tr><tr><th>Type</th><td>inv_fourth_ISI</td></tr></table></td></tr><tr><th>inv_fifth_ISI.Step0.2</th><td><table border=\"1\"><tr><th>Std</th><td>3.42660372442</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>0.629383867188</td></tr><tr><th>Stimulus</th><td>Step0.2</td></tr><tr><th>Type</th><td>inv_fifth_ISI</td></tr></table></td></tr><tr><th>inv_fifth_ISI.Step0.4</th><td><table border=\"1\"><tr><th>Std</th><td>10.0140355603</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>5.81877916662</td></tr><tr><th>Stimulus</th><td>Step0.4</td></tr><tr><th>Type</th><td>inv_fifth_ISI</td></tr></table></td></tr><tr><th>inv_fifth_ISI.Step0.6</th><td><table border=\"1\"><tr><th>Std</th><td>15.5430683467</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>13.3757219884</td></tr><tr><th>Stimulus</th><td>Step0.6</td></tr><tr><th>Type</th><td>inv_fifth_ISI</td></tr></table></td></tr><tr><th>inv_fifth_ISI.Step0.8</th><td><table border=\"1\"><tr><th>Std</th><td>18.6803014237</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>22.7441425648</td></tr><tr><th>Stimulus</th><td>Step0.8</td></tr><tr><th>Type</th><td>inv_fifth_ISI</td></tr></table></td></tr><tr><th>inv_fifth_ISI.Step1.0</th><td><table border=\"1\"><tr><th>Std</th><td>19.2396576537</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>31.2306022842</td></tr><tr><th>Stimulus</th><td>Step1.0</td></tr><tr><th>Type</th><td>inv_fifth_ISI</td></tr></table></td></tr><tr><th>inv_last_ISI.Step0.2</th><td><table border=\"1\"><tr><th>Std</th><td>17.231857258</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>5.71590657977</td></tr><tr><th>Stimulus</th><td>Step0.2</td></tr><tr><th>Type</th><td>inv_last_ISI</td></tr></table></td></tr><tr><th>inv_last_ISI.Step0.4</th><td><table border=\"1\"><tr><th>Std</th><td>8.49506521896</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>8.60364863426</td></tr><tr><th>Stimulus</th><td>Step0.4</td></tr><tr><th>Type</th><td>inv_last_ISI</td></tr></table></td></tr><tr><th>inv_last_ISI.Step0.6</th><td><table border=\"1\"><tr><th>Std</th><td>8.02817180026</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>12.4195455632</td></tr><tr><th>Stimulus</th><td>Step0.6</td></tr><tr><th>Type</th><td>inv_last_ISI</td></tr></table></td></tr><tr><th>inv_last_ISI.Step0.8</th><td><table border=\"1\"><tr><th>Std</th><td>7.63479359668</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>16.4950967344</td></tr><tr><th>Stimulus</th><td>Step0.8</td></tr><tr><th>Type</th><td>inv_last_ISI</td></tr></table></td></tr><tr><th>inv_last_ISI.Step1.0</th><td><table border=\"1\"><tr><th>Std</th><td>9.42799391629</td></tr><tr><th>Weight</th><td>1</td></tr><tr><th>Mean</th><td>20.5677718854</td></tr><tr><th>Stimulus</th><td>Step1.0</td></tr><tr><th>Type</th><td>inv_last_ISI</td></tr></table></td></tr></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load target data\n",
    "with open('./stimfeat/PC_newfeat_No14112401_15012303-m990803_stimfeat.json') as f:\n",
    "    config = json.load(f, object_pairs_hook=collections.OrderedDict)\n",
    "    \n",
    "observation = config['features']\n",
    "IPython.display.HTML(json2html.convert(json = observation))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\"><tr><th>Step-2.0</th><td><table border=\"1\"><tr><th>Delay</th><td>1000</td></tr><tr><th>RecLocationX</th><td>0.5</td></tr><tr><th>TTX</th><td>0.0</td></tr><tr><th>StimLocationX</th><td>0.5</td></tr><tr><th>Threshold</th><td>-20.0</td></tr><tr><th>Amplitude</th><td>-2.0</td></tr><tr><th>Duration</th><td>400.0</td></tr><tr><th>HypAmp</th><td>0.0</td></tr><tr><th>Type</th><td>SquarePulse</td></tr><tr><th>StimSectionName</th><td>soma[0]</td></tr><tr><th>RecSectionName</th><td>soma[0]</td></tr></table></td></tr><tr><th>Step-1.0</th><td><table border=\"1\"><tr><th>Delay</th><td>1000</td></tr><tr><th>RecLocationX</th><td>0.5</td></tr><tr><th>TTX</th><td>0.0</td></tr><tr><th>StimLocationX</th><td>0.5</td></tr><tr><th>Threshold</th><td>-20.0</td></tr><tr><th>Amplitude</th><td>-1.0</td></tr><tr><th>Duration</th><td>400.0</td></tr><tr><th>HypAmp</th><td>0.0</td></tr><tr><th>Type</th><td>SquarePulse</td></tr><tr><th>StimSectionName</th><td>soma[0]</td></tr><tr><th>RecSectionName</th><td>soma[0]</td></tr></table></td></tr><tr><th>Step0.2</th><td><table border=\"1\"><tr><th>Delay</th><td>1000</td></tr><tr><th>RecLocationX</th><td>0.5</td></tr><tr><th>TTX</th><td>0.0</td></tr><tr><th>StimLocationX</th><td>0.5</td></tr><tr><th>Threshold</th><td>-20.0</td></tr><tr><th>Amplitude</th><td>0.2</td></tr><tr><th>Duration</th><td>400.0</td></tr><tr><th>HypAmp</th><td>0.0</td></tr><tr><th>Type</th><td>SquarePulse</td></tr><tr><th>StimSectionName</th><td>soma[0]</td></tr><tr><th>RecSectionName</th><td>soma[0]</td></tr></table></td></tr><tr><th>Step0.4</th><td><table border=\"1\"><tr><th>Delay</th><td>1000</td></tr><tr><th>RecLocationX</th><td>0.5</td></tr><tr><th>TTX</th><td>0.0</td></tr><tr><th>StimLocationX</th><td>0.5</td></tr><tr><th>Threshold</th><td>-20.0</td></tr><tr><th>Amplitude</th><td>0.4</td></tr><tr><th>Duration</th><td>400.0</td></tr><tr><th>HypAmp</th><td>0.0</td></tr><tr><th>Type</th><td>SquarePulse</td></tr><tr><th>StimSectionName</th><td>soma[0]</td></tr><tr><th>RecSectionName</th><td>soma[0]</td></tr></table></td></tr><tr><th>Step0.6</th><td><table border=\"1\"><tr><th>Delay</th><td>1000</td></tr><tr><th>RecLocationX</th><td>0.5</td></tr><tr><th>TTX</th><td>0.0</td></tr><tr><th>StimLocationX</th><td>0.5</td></tr><tr><th>Threshold</th><td>-20.0</td></tr><tr><th>Amplitude</th><td>0.6</td></tr><tr><th>Duration</th><td>400.0</td></tr><tr><th>HypAmp</th><td>0.0</td></tr><tr><th>Type</th><td>SquarePulse</td></tr><tr><th>StimSectionName</th><td>soma[0]</td></tr><tr><th>RecSectionName</th><td>soma[0]</td></tr></table></td></tr><tr><th>Step0.8</th><td><table border=\"1\"><tr><th>Delay</th><td>1000</td></tr><tr><th>RecLocationX</th><td>0.5</td></tr><tr><th>TTX</th><td>0.0</td></tr><tr><th>StimLocationX</th><td>0.5</td></tr><tr><th>Threshold</th><td>-20.0</td></tr><tr><th>Amplitude</th><td>0.8</td></tr><tr><th>Duration</th><td>400.0</td></tr><tr><th>HypAmp</th><td>0.0</td></tr><tr><th>Type</th><td>SquarePulse</td></tr><tr><th>StimSectionName</th><td>soma[0]</td></tr><tr><th>RecSectionName</th><td>soma[0]</td></tr></table></td></tr><tr><th>Step1.0</th><td><table border=\"1\"><tr><th>Delay</th><td>1000</td></tr><tr><th>RecLocationX</th><td>0.5</td></tr><tr><th>TTX</th><td>0.0</td></tr><tr><th>StimLocationX</th><td>0.5</td></tr><tr><th>Threshold</th><td>-20.0</td></tr><tr><th>Amplitude</th><td>1.0</td></tr><tr><th>Duration</th><td>400.0</td></tr><tr><th>HypAmp</th><td>0.0</td></tr><tr><th>Type</th><td>SquarePulse</td></tr><tr><th>StimSectionName</th><td>soma[0]</td></tr><tr><th>RecSectionName</th><td>soma[0]</td></tr></table></td></tr></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#stimuli\n",
    "IPython.display.HTML(json2html.convert(json = config['stimuli']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/dist-packages/neurom/io/neurolucida.py:263: UserWarning: This is an experimental reader. There are no guarantees regarding ability to parse Neurolucida .asc files or correctness of output.\n",
      "  warnings.warn(msg)\n",
      "No handlers could be found for logger \"neurom.io.neurolucida\"\n"
     ]
    },
    {
     "data": {
      "image/png": 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KS3kL0i/Z9uQ2WitaT/n+iz8sxmw2kzA1+LvHNWNDUDpWNT2Zdf0srGFWtv12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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7857e34490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Load and visualize cell model\n",
    "\n",
    "model = models.Model()\n",
    "\n",
    "# outputs will be saved in folders named like this:\n",
    "model.name=\"CA1_pyr_cAC_12AUG16_test\"\n",
    "\n",
    "# path to mod files\n",
    "model.modelpath = \"/home/osboxes/bsp_data_repository-master/optimizations/CA1_pyr_cAC_12AUG16/mechanisms/\"\n",
    "\n",
    "# if this doesn't exist mod files are automatically compiled\n",
    "model.libpath = \"x86_64/.libs/libnrnmech.so.0\"\n",
    "\n",
    "# path to hoc file\n",
    "# the model must not display any GUI!!\n",
    "model.hocpath = \"/home/osboxes/bsp_data_repository-master/optimizations/CA1_pyr_cAC_12AUG16/checkpoints/cell.hoc\"\n",
    "\n",
    "# If the hoc file doesn't contain a template, this must be None\n",
    "model.template_name = \"CCell()\"\n",
    "\n",
    "# should be None, if there is no Section List in the model for the soma\n",
    "model.SomaSecList_name = \"somatic\"\n",
    "\n",
    "# if the soma is not in a section list, add its name here:\n",
    "#model.soma = 'soma'\n",
    "\n",
    "model.v_init = -80\n",
    "\n",
    "'''\n",
    "model.load_mod_files() #This automatically compiles mod files, if they are not yet compiled\n",
    "model.initialise() # Loads the model, creates stand alone cell from template. \n",
    "'''\n",
    "# uses the soma section list to set the location of somatic stimuli (and measurement)\n",
    "# If the given section list contains more elements, the last one is used\n",
    "\n",
    "\n",
    "# use this to visualize hoc morphology\n",
    "'''\n",
    "from PyNeuronToolbox.morphology import shapeplot\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "plt.figure(figsize=(7,7))\n",
    "shapeax = plt.subplot(111, projection='3d')\n",
    "shapeax.view_init(75,66)\n",
    "shapeplot(h,shapeax)\n",
    "plt.show()\n",
    "'''\n",
    "\n",
    "from neurom import load_neuron\n",
    "from neurom import viewer\n",
    "morph_path = \"/home/osboxes/bsp_data_repository-master/optimizations/CA1_pyr_cAC_12AUG16/morphology/dend-050921AM2_axon-051208AM2.asc\"\n",
    "viewer.draw(load_neuron(morph_path));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "#all the outputs will be saved here\n",
    "base_directory = '/home/osboxes/BBP_project/150904_neuronunit/neuronunit_MAGAMNAK/'\n",
    "#base_directory = '/mnt/extra31/Modellezo_csapat/CA1_pyramidal/'\n",
    "\n",
    "# Set the test\n",
    "#The vectors of the somatic and dendritic voltage values are saved in files during the simulation. \n",
    "#If force_run=False, and the files already exist, the test uses the saved files for further calculations \n",
    "#If force_run=True, or the files don't exist, the test runs the whole simulation.\n",
    "show_plot=True\n",
    "test = tests.SomaticFeaturesTest(observation, force_run=False, base_directory=base_directory, show_plot=show_plot)\n",
    "\n",
    "# Set the number of processes running parallel\n",
    "import multiprocessing\n",
    "test.npool = multiprocessing.cpu_count() - 1\n",
    "\n",
    "# set the target data to be used in the test\n",
    "test.config=config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- running amplitude: -1.0 on model: CA1_pyr_cAC_12AUG16_test at: CCell[0].soma[0](0.5)\n",
      "- running amplitude: -2.0 on model: CA1_pyr_cAC_12AUG16_test at: CCell[0].soma[0](0.5)\n",
      "- running amplitude: 0.2 on model: CA1_pyr_cAC_12AUG16_test at: CCell[0].soma[0](0.5)\n",
      "- running amplitude: 0.4 on model: CA1_pyr_cAC_12AUG16_test at: CCell[0].soma[0](0.5)\n",
      "- running amplitude: 0.6 on model: CA1_pyr_cAC_12AUG16_test at: CCell[0].soma[0](0.5)\n",
      "- running amplitude: 0.8 on model: CA1_pyr_cAC_12AUG16_test at: CCell[0].soma[0](0.5)\n",
      "- running amplitude: 1.0 on model: CA1_pyr_cAC_12AUG16_test at: CCell[0].soma[0](0.5)\n",
      "The figures are saved in the directory:  /home/osboxes/BBP_project/150904_neuronunit/neuronunit_MAGAMNAK/figs/soma/CA1_pyr_cAC_12AUG16_test/\n",
      "Results are saved in the directory:  /home/osboxes/BBP_project/150904_neuronunit/neuronunit_MAGAMNAK/results/CA1_pyr_cAC_12AUG16_test/\n"
     ]
    },
    {
     "data": {
      "image/png": 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55ppraG5u5pxzzuGcc85JwFNQjkb83btKOrBXIAeLQY82MOjU7o2wCTT4PRvO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\nrWyXdIFd1U0p3UUEMYqBiHweuBuYAsw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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7857a23bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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QkaGyu2WrTN3b0xlnU2cP6zt62LSjhx09SXZ0p8L7JF19afrSGfpS4S2doTf8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hkX3KNGD6lk7NCqti8Bhw0qZ+igcgZXlhV1ypX+TsGWiEgn9ho9mNMOGMetzyxm7bZGRg+pZNmG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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7865d51ed0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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7L1u2bKGgoIA//OEP7NmzJ7QpYkNDA8ePH2fgwIFhP7vNZsNmswFo48OvusIM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\nt99+S0lJCadOneLVV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4D82OLFi2lvb6e7u5tZs2bx2GOPsXHjRj766CP8/PwoLS2luroa\ngIceeogvvviCd955B61WC/w7RPT397Nr1y7MZjPvvfce+/fv57777mPChAl0dHTw2WefXdfmb7/9\nlm3bttHf309ISAh6vZ6pU6fyH//xH3h7e/PXv/4VgJycHJ588kn+/Oc/k5mZiU6nuyP35lrx8ZCX\nZ+sYUShsy7y8QTw3e9s7CiGEEDemuHr16tWRbsStfPvtt5SUlHDq1CleffVVvL29R7pJP5ler2fz\n5s135NiZmZnDMiwkhBBCOItR8SuhyZMn85vf/GbAbSdPnrQP0ajVavuwkbO7U2FFCCGEGItGRWC5\nmbCwMMLCwka6GUIIIYS4g5ziZ81CCCGEEDcjgUUIIYQQTk8CixBCCCGcngQWIYQQQjg9CSxCCCGE\ncHoSWIQQQgjh9CSwiHuCwQAvehloVATQr3DhkleArVAIIcSoMOrfwyLErRgMUPr/GNh6JZn76AJg\nQvNZ+hKTbf8DyLQBQgjh9KSHRYx5GRnw+ysZ9rDyg/G9XbaNQgghnN6YDCzZ2dmsX7+egwcPUlxc\nDNjm12ltbSU+Pp63336b559//ob76/X6W57jhzo/HPdaqampbNiwgffff5/GxsZBvYq/t7eXzMzM\n687/5Zdf8vrrr/PSSy/R2dk54L55eXloNBo0Go3D7NECTCZQY7rxRiGEEE5vzAWWvr4+uru7mThx\nIm1tbezZs4fNmzdTXl4OgLe3N2vXruXq1av09vba9/vXv/5FSkoKOTk5APz/7d1tbFN1/8fxd6v0\nQTc2rtBw5xxDZSFlSskIEwgyFpao2WTIExBIiJL5aGMJCPxDhBLZgijRZKJsGl0gG6iMUNBMNm9q\nCARIYQihNFSzO0AnbDqKu2Fj/B8s9HLcXSgdPWs/r4Q0Pae/H9/zTZp9ds5v55w7d4433niDwsJC\nDh8+zOuvv85nn33GmjVr+PXXX/F6vXz11VcAbN++nSVLlnDp0qXgfOfPnyc5OZm5c+fi9/s5duwY\nHo+H0tJStmzZwpo1a+ju7mbGjBlUVFSwZcsWLBbLHR9auHPnTpxOJzk5OcGnON8qNzcXj8eDx+Mh\nNTU1VO2MCImJ0Eji3XeKiIjhRVxgcblctLS00NraysWLF8nOzqagoIBnn30WgEuXLvHuu+/icDiw\nWCzBcQcPHuTll1/mtddeA2Dfvn2MHDmSMWPG8PPPP3P9+nUWL15Meno6p0+fxm63k5WVBcDixYuZ\nN28eZ8+eDc63Y8cOHn/8cV599VXGjRvH1KlTmTJlCgcOHGD48OFYrVaam5t56qmneOWVV7hw4cI9\nj8tkMoW6VVGjsBA2DCnkL6z9tvdYrH07RUTE8CIusLjdbjZt2sS6desoKSnhxo0b/fbfPMOSm5vb\nb/vMmTOprq7m888/ByArK4srV67Q2dnJM888w6OPPkpJSQn79+9n6tSpmEwmKisrATCbzZjNZnp7\ne9m2bRu9vb288847fP/99zz22GOMGjWKU6dOceTIEV544QUCgQDDhw9nxIgR+P1+PvzwQ2w2GwAf\nfPABtbW1HDp0CJ/Px3fffceCBQtwOp24XC7mzJnzELoYWRYtgjmfLeL/hpdSz1h6MXF1+Fge/bRU\nC25FRAYJ041bf6LLHRUUFNzXOhQjzOt0Ou94aUlERGSwiuo/a963bx+tra0AZGRkkHiP9QwDEVYG\ncl4REZFIEtWB5aWXXgp3CSIiInIfIm4Ni4iIiEQeBRYRERExPAUWERERMTwFFhERETE8BRYREREx\nPAUWERERMTwFFhERETE8BRaRh6W8HJKSwGzuey0vf5jDRUQGtai+cZzIQ1NeDrm50N7e976hoe89\n3NfzjB5wuIjIoBdRgaW4uJhAIMD06dPZsWMH8fHxZGVlsW/fvnveAt/tdvPnn3+Sk5MTslqKioow\nm81YrVby8/Pv+5lBmzdvxuv1UlZWFtzW2NhIcXExAMuXLychISFkdcoASE+/fduRI9DV1X9bezu8\n9hp8/PHtn3e7+71du/a/YeXvw9euVWARkegQMYGlp6eHzs5O4uLiaGtrIzs7m2nTpgV/0AN8/PHH\nNDc3Y7fbATh79ixPPvkkgUCA06dPM2HCBCZMmBD8/K5du2hqaiI+Pp7k5GQqKiqIiYnBZrPR1dXF\npEmTCAQC+P1+4uPjmTVrFmlpaQA0NDQwe/Zs0tPT8fv9eL1e3G43ra2t+Hw+rly5wurVq1mwYAFL\nly7F5/OxYcMGVq1aRUFBQb9jq6ysJC8vD4Ddu3ffth+gtLSU0tJSAEaPHh3a5sqDuzWs/K/tt2hs\n/GfbRUQiTcSsYXG5XLS0tNDa2srFixfZv38/W7duZdmyZQBcv36dzs5OvX/vQgAACEBJREFUEhIS\n+PHHH0lJSWHIkCFcunSJ8ePHk5GR0S+sAFy9ehWbzcbRo0cByMzMJC8vD4vFgtPp5NChQwDMmTOH\n/Px8XC5XcOy2bdtISUlh5cqVxMXFYbfbSU9Px+VyMWbMGGw2G3V1dYwaNYqFCxfS1dXFtWvX7np8\nJpPpnsefm5uLx+PB4/GQmpr6r3ooIeJ23/5v7Ng7f3bs2Dt//hZ3ey7nPZ7XKSISUSLmDIvb7Q6e\nTXE4HKxfv5558+YF93d0dNDU1MTTTz9NT08Pv//+O7GxsZw5c4YXX3yR3bt3M378eCZOnBgc4/P5\nmDx5Mt3d3QAMGTIEs9kcfO3t7QWgqqqKmpoasrOzqaysZMaMGVRWVtLR0UFMTAyxsbEEAgGqq6uZ\nO3cu9fX1WK1WEhMTaW5upqSkhN7eXiwWC9u3b6e2tpaqqirS0tKorq5m/vz5wWPLz89/WC2VUCos\n7L8IBcBq7ds+8MNFRAY9040bN26Eu4jBrKysDIfDgcPh+Ffj73dtyz/hdDpxOp0hnVNCoLy8b9FJ\nY2PfqZHCwn+0AOUBh4uIDGoKLH/j9Xo5duwYAImJiWRkZIS5on9HgUVERCJNxFwSCgW73R5ckCsi\nIiLGETGLbkVERCRyKbCIiIiI4SmwiIiIiOEpsIiIiIjhKbCIiIiI4SmwiIiIiOEpsIiIiIjhKbCI\nDBbl5ZCUBGZz32t5+WCYWkQkJHTjOJHBoLy8/8OEGhr63sMD359/AKcWEQmZqLk1f3FxMYFAgOnT\np7Njxw7i4+PJysqip6eHoqIi9u7dy7Bhw0L2/xUVFWE2m7FareTn59/3M4M2b96M1+ulrKwsuK2x\nsTH48MPly5eTkJBwzzl0a/4Ik54OR45AV9ft+8aOhfr6B5o+KakvpAzA1CIiIRMVZ1h6enro7Owk\nLi6OtrY2srOzmTZtGsXFxWzcuJHDhw/fcdyuXbtoamoiPj6e5ORkKioqiImJwWaz0dXVxaRJkwgE\nAvj9fuLj45k1axZpaWkANDQ0MHv2bNLT0/H7/Xi9XtxuN62trfh8Pq5cucLq1atZsGABS5cuxefz\nsWHDBlatWkVBQUG/OiorK8nLywNg9+7dt+0HKC0tpbS0FIDRo0eHsn1iBHcKK9D3JMQHdLcpQjC1\niEjIRMUaFpfLRUtLC62trVy8eJH9+/ezdetWli1bds9xV69exWazcfToUQAyMzPJy8vDYrHgdDo5\ndOgQAHPmzCE/Px+XyxUcu23bNlJSUli5ciVxcXHY7XbS09NxuVyMGTMGm81GXV0do0aNYuHChXR1\ndXHt2rW71mIyme5Za25uLh6PB4/HQ2pq6v22RgYDt7vvdMedJCY+8PR3myIEU4uIhExUnGFxu93B\nSyoOh4P169czb948ADweD0eOHOGjjz5i1apVPPLII8FxPp+PyZMn093dDcCQIUMwm83B197eXgCq\nqqqoqakhOzubyspKZsyYQWVlJR0dHcTExBAbG0sgEKC6upq5c+dSX1+P1WolMTGR5uZmSkpK6O3t\nxWKxsH37dmpra6mqqiItLY3q6mrmz58frD8/P/9htk6MorCw/0ITAKu1b7txpxYRCZmoWcMyUMrK\nynA4HDgcjn81/n7XtvwTWsMSocrLYe3avms1iYl9iSJEq2IHcGoRkZBQYPkbr9fLsWPHAEhMTCQj\nIyPMFf07CiwiIhJpouKS0P2y2+3Y7fZwlyEiIiK3iIpFtyIiIjK4KbCIiIiI4SmwiIiIiOEpsIiI\niIjhKbCIiIiI4SmwiIiIiOEpsIiIiIjhKbCIiIiI4SmwiIiIiOEpsIiIiIjh6VlCEWjZsmUkJCSE\nu4ywOX78OKmpqeEuI+zUB/XgJvVBPbjJiH1ISkpi6dKl//NzCiwScaZMmYLH4wl3GWGnPqgHN6kP\n6sFNg7kPuiQkIiIihqfAIiIiIob3iNPpdIa7CJFQM9o12nBRH9SDm9QH9eCmwdoHrWERERERw9Ml\nIRERETE8BRYRERExvEfDXYBIqJw4cYI9e/bQ3t7OW2+9RUxMTLhLemjOnTtHUVEROTk5WCwWamtr\naWtr4+233+a9997DbDZjMplYvnx5uEsdMAcPHuTw4cP4/X4yMjKoq6uLuh4AnDlzhgMHDlBXV8eU\nKVO4fPkyf/31F+vWrcPpdDJ06FBGjBjBkiVLwl3qgPr6668pKSlh/vz5UduDvXv38sMPPzBu3DjG\njx/PyZMnB/V3QmdYJGLs3LkTp9NJTk4ONTU14S7noUpOTg7eeKmmpoa1a9eSkpLCTz/9RFNTEwUF\nBdTX14e1xoE2c+ZMVq9eTVJSEl9++WVU9gBg4sSJjBw5kvPnz3Py5ElWrFgBwB9//IHZbGbFihWc\nOHEizFUOrNraWjo7O3niiSeitgcAMTExDB06lO7ubr799ttB/53QGRaJKCaTKdwlGFY09KaiooJx\n48bR0tJyx/3R0AOARYsWMWzYMD755BPgv8d962ukqqqqwmq1Ultbi9nc93t5tPUAIDMzk8zMTPbs\n2UNFRcUdPzOY+qC/EpKIcfz4cfbu3Ut7ezsbNmwgNjY23CU9NL/99hsbN26ko6OD5557jgsXLtDW\n1samTZt4//33MZlMmM1m8vPzw13qgPniiy/49NNPef755/nPf/4TlT0A+Oabbzh16hS//PIL06dP\n5/Lly7S3t/Pmm2/idDqJi4tjxIgRLF68ONylDriCggImT54ctT1wu90cPXqUuro6Zs6cSUNDw6D+\nTiiwiIiIiOFpDYuIiIgYngKLiIiIGJ4Ci4iIiBieAouIiIgYngKLiIiIGJ4Ci4iIiBje/wNXPZNq\nPb3y5AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7865723090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ffUZzczPt7e0sWbKEQCDA9u3bsdlsEfsGAgFOnDhBW1sbiYmJ2Gw2XnzxRZxO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\n/QHfpN1b/PovVQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7865157410>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Run the test\n",
    "# Call SciUnit's judge function. \n",
    "#This calls the generate_prediction function of the test to generate prediction (data of model behaviour)\n",
    "#Also calls the compute_score function of the test to calculate the error\n",
    "score = test.judge(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\"><tr><th>inv_first_ISI.Step0.4</th><td><table border=\"1\"><tr><th>feature mean</th><td>0.0</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_first_ISI.Step0.6</th><td><table border=\"1\"><tr><th>feature mean</th><td>53.4759358289</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_first_ISI.Step0.2</th><td><table border=\"1\"><tr><th>feature mean</th><td>0.0</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_first_ISI.Step0.8</th><td><table border=\"1\"><tr><th>feature mean</th><td>94.3396226415</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>AP1_amp.Step1.0</th><td><table border=\"1\"><tr><th>feature mean</th><td>120.383475482</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_time_to_first_spike.Step0.8</th><td><table border=\"1\"><tr><th>feature mean</th><td>344.827586188</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_fourth_ISI.Step1.0</th><td><table border=\"1\"><tr><th>feature mean</th><td>28.4900284901</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_time_to_first_spike.Step0.4</th><td><table border=\"1\"><tr><th>feature mean</th><td>0.0</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_time_to_first_spike.Step1.0</th><td><table border=\"1\"><tr><th>feature mean</th><td>526.31578943</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_time_to_first_spike.Step0.6</th><td><table border=\"1\"><tr><th>feature mean</th><td>181.818181813</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_time_to_first_spike.Step0.2</th><td><table border=\"1\"><tr><th>feature mean</th><td>0.0</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_fifth_ISI.Step0.6</th><td><table border=\"1\"><tr><th>feature mean</th><td>13.5501355014</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_third_ISI.Step0.8</th><td><table border=\"1\"><tr><th>feature mean</th><td>22.1729490022</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>APlast_amp.Step1.0</th><td><table border=\"1\"><tr><th>feature mean</th><td>84.7799006971</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_third_ISI.Step0.4</th><td><table border=\"1\"><tr><th>feature mean</th><td>0.0</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_third_ISI.Step1.0</th><td><table border=\"1\"><tr><th>feature mean</th><td>38.9105058366</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_third_ISI.Step0.6</th><td><table border=\"1\"><tr><th>feature mean</th><td>13.4770889488</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>AHP_depth.Step1.0</th><td><table border=\"1\"><tr><th>feature mean</th><td>10.3221030623</td></tr><tr><th>feature sd</th><td>1.73094661609</td></tr></table></td></tr><tr><th>inv_third_ISI.Step0.2</th><td><table border=\"1\"><tr><th>feature mean</th><td>0.0</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>time_to_last_spike.Step0.6</th><td><table border=\"1\"><tr><th>feature mean</th><td>393.6</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>time_to_last_spike.Step0.4</th><td><table border=\"1\"><tr><th>feature mean</th><td>0.0</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>voltage_deflection_begin.Step-2.0</th><td><table border=\"1\"><tr><th>feature mean</th><td>-67.6118692608</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>time_to_last_spike.Step0.2</th><td><table border=\"1\"><tr><th>feature mean</th><td>0.0</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>time_to_last_spike.Step0.8</th><td><table border=\"1\"><tr><th>feature mean</th><td>355.3</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_second_ISI.Step0.8</th><td><table border=\"1\"><tr><th>feature mean</th><td>48.5436893204</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_fifth_ISI.Step0.4</th><td><table border=\"1\"><tr><th>feature mean</th><td>0.0</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_fifth_ISI.Step1.0</th><td><table border=\"1\"><tr><th>feature mean</th><td>27.9329608939</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_first_ISI.Step1.0</th><td><table border=\"1\"><tr><th>feature mean</th><td>121.951219512</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_second_ISI.Step0.2</th><td><table border=\"1\"><tr><th>feature mean</th><td>0.0</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_second_ISI.Step0.4</th><td><table border=\"1\"><tr><th>feature mean</th><td>0.0</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_second_ISI.Step1.0</th><td><table border=\"1\"><tr><th>feature mean</th><td>91.743119266</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_second_ISI.Step0.6</th><td><table border=\"1\"><tr><th>feature mean</th><td>13.5685210312</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_fourth_ISI.Step0.4</th><td><table border=\"1\"><tr><th>feature mean</th><td>0.0</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_fourth_ISI.Step0.6</th><td><table border=\"1\"><tr><th>feature mean</th><td>13.5317997294</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>voltage_deflection.Step-1.0</th><td><table border=\"1\"><tr><th>feature mean</th><td>-29.2569184574</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_fourth_ISI.Step0.2</th><td><table border=\"1\"><tr><th>feature mean</th><td>0.0</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_last_ISI.Step1.0</th><td><table border=\"1\"><tr><th>feature mean</th><td>27.700831025</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_fourth_ISI.Step0.8</th><td><table border=\"1\"><tr><th>feature mean</th><td>21.7864923747</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_fifth_ISI.Step0.8</th><td><table border=\"1\"><tr><th>feature mean</th><td>21.7391304348</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_last_ISI.Step0.6</th><td><table border=\"1\"><tr><th>feature mean</th><td>13.5501355014</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_last_ISI.Step0.4</th><td><table border=\"1\"><tr><th>feature mean</th><td>0.0</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>voltage_deflection.Step-2.0</th><td><table border=\"1\"><tr><th>feature mean</th><td>-67.1682089814</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_fifth_ISI.Step0.2</th><td><table border=\"1\"><tr><th>feature mean</th><td>0.0</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>time_to_last_spike.Step1.0</th><td><table border=\"1\"><tr><th>feature mean</th><td>370.6</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>voltage_deflection_begin.Step-1.0</th><td><table border=\"1\"><tr><th>feature mean</th><td>-30.9686257461</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_last_ISI.Step0.2</th><td><table border=\"1\"><tr><th>feature mean</th><td>0.0</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr><tr><th>inv_last_ISI.Step0.8</th><td><table border=\"1\"><tr><th>feature mean</th><td>21.6919739697</td></tr><tr><th>feature sd</th><td>0.0</td></tr></table></td></tr></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Visualize model feature values in a table\n",
    "for key, value in score.prediction.iteritems():\n",
    "    for _key_, value in score.prediction[key].iteritems():\n",
    "        score.prediction[key][_key_] = str(value)\n",
    "               \n",
    "IPython.display.HTML(json2html.convert(json = score.prediction))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== Model CA1_pyr_cAC_12AUG16_test (Model) achieved score Z_sum = 37.66 on test 'Somatic features test (SomaticFeaturesTest)'. ===\n"
     ]
    }
   ],
   "source": [
    "#Summarize and print the score achieved by the model on the test using SciUnit's summarize function\n",
    "score.summarize()\n"
   ]
  }
 ],
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