Added IPython notebook example using pyNeuroML

.gitignore

@@ -23,3 +23,4 @@ simulations
 izhikevich15jun19
 MATLAB/results/*.dat
 NeuroML2/results/*.dat
+*.npy

NeuroML2/LEMS_2007One.xml

@@ -9,11 +9,11 @@
 <Include file="Simulation.xml"/>
 
 
-<izhikevich2007Cell id="RS" v0 = "-60mV" C="100 pF" k = "0.7 nS_per_mV"
-                        vr = "-60 mV" vt = "-40 mV" vpeak = "35 mV" 
-                        a = "0.03 per_ms" b = "-2 nS" c = "-50 mV" d = "100 pA"/>
+<izhikevich2007Cell id="RS" v0="-60 mV" C="100 pF" k="0.7 nS_per_mV" 
+                        vr="-60 mV" vt="-40 mV" vpeak="35 mV" 
+                        a="0.03 per_ms" b="-2 nS" c="-50 mV" d="100 pA"/>
 
-<pulseGenerator id="RS_Iext" delay="0ms" duration="520ms" amplitude="100 pA"/>
+<pulseGenerator id="RS_Iext" delay="500ms" duration="1000ms" amplitude="100.0 pA"/>
 
 
 <network id="net1">
@@ -26,22 +26,22 @@
 <!-- End of NeuroML2 content -->
 
 
-<Simulation id="sim1" length="520ms" step="0.0025ms" target="net1">
+<Simulation id="sim1" length="1600ms" step="0.0025ms" target="net1">
 
 
-    <Display id="d1" title="RS v" timeScale="1ms" xmin="-50" xmax="570" ymin="-80" ymax="50">
-        <Line id ="RS v" quantity="RS_pop[0]/v" scale="1mV"  color="#0000ff" timeScale="1ms"/>
+    <Display id="d1" title="RS v" timeScale="1ms" xmin="-50" xmax="1650" ymin="-80" ymax="50">
+        <Line id="RS v" quantity="RS_pop[0]/v" scale="1mV" color="#0000ff" timeScale="1ms"/>
     </Display>
-    <Display id="d2" title="RS u" timeScale="1ms" xmin="-50" xmax="570" ymin="-80" ymax="80">
-        <Line id ="RS u" quantity="RS_pop[0]/u" scale="1pA"  color="#ff0000" timeScale="1ms"/>
+    <Display id="d2" title="RS u" timeScale="1ms" xmin="-50" xmax="1650" ymin="-80" ymax="80">
+        <Line id="RS u" quantity="RS_pop[0]/u" scale="1pA" color="#ff0000" timeScale="1ms"/>
     </Display>
 
 
-    <OutputFile id="of0" fileName="results/RS_One.dat">
-        <OutputColumn id="v" quantity="RS_pop[0]/v" />
-        <OutputColumn id="u" quantity="RS_pop[0]/u" />
+    <OutputFile id="of0" fileName="RS_One.dat">
+        <OutputColumn id="v" quantity="RS_pop[0]/v"/>
+        <OutputColumn id="u" quantity="RS_pop[0]/u"/>
     </OutputFile>
 
 </Simulation>
 
-</Lems>
+</Lems>

NeuroML2/WhichModel.nml

@@ -1,6 +1,6 @@
 <?xml version="1.0" encoding="UTF-8"?>
 
-<neuroml xmlns="http://www.neuroml.org/schema/neuroml2"
+<neuroml xmlns:prefix="http://www.neuroml.org/schema/neuroml2"
     xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
     xsi:schemaLocation="http://www.neuroml.org/schema/neuroml2  http://neuroml.svn.sourceforge.net/viewvc/neuroml/NeuroML2/Schemas/NeuroML2/NeuroML_v2alpha.xsd"
     id="WhichModel">

Optimize.ipynb

@@ -0,0 +1,300 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "%load_ext autoreload\n",
+    "%autoreload 2\n",
+    "%matplotlib notebook\n",
+    "import os,sys\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import quantities as pq\n",
+    "import sciunit\n",
+    "import neuronunit\n",
+    "from neuronunit import aibs\n",
+    "from neuronunit.models.reduced import ReducedModel"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "# This example is from https://github.com/OpenSourceBrain/IzhikevichModel.\n",
+    "IZHIKEVICH_PATH = '/home/mnt/osb/IzhikevichModel' # Replace this the path to your \n",
+    "                                                                       # working copy of \n",
+    "                                                                       # github.com/OpenSourceBrain/IzhikevichModel.  \n",
+    "LEMS_MODEL_PATH = os.path.join(IZHIKEVICH_PATH,'NeuroML2/LEMS_2007One.xml')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:allensdk.api.api:Downloading URL: http://api.brain-map.org/api/v2/data/query.json?q=model::Specimen,rma::criteria,[id$eq'354190013'],rma::include,structure,donor(transgenic_lines),specimen_tags,cell_soma_locations,ephys_features,data_sets,neuron_reconstructions,cell_reporter,rma::options[num_rows$eq'all']\n",
+      "INFO:allensdk.api.api:Downloading URL: http://api.brain-map.org/api/v2/data/query.json?q=model::EphysSweep,rma::criteria,[specimen_id$eq354190013],rma::options[num_rows$eq'all']\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Getting data values from neuroelectro.org\n",
+      "http://www.neuroelectro.org/api/1/nes/?e__name=Input+Resistance&nlex=nifext_50\n",
+      "Getting data values from neuroelectro.org\n",
+      "http://www.neuroelectro.org/api/1/nes/?e__name=Membrane+Time+Constant&nlex=nifext_50\n",
+      "Getting data values from neuroelectro.org\n",
+      "http://www.neuroelectro.org/api/1/nes/?e__name=Cell+Capacitance&nlex=nifext_50\n",
+      "Getting data values from neuroelectro.org\n",
+      "http://www.neuroelectro.org/api/1/nes/?e__name=Resting+membrane+potential&nlex=nifext_50\n",
+      "Getting data values from neuroelectro.org\n",
+      "http://www.neuroelectro.org/api/1/nes/?e__name=Spike+Half-Width&nlex=nifext_50\n",
+      "Getting data values from neuroelectro.org\n",
+      "http://www.neuroelectro.org/api/1/nes/?e__name=Spike+Amplitude&nlex=nifext_50\n",
+      "Getting data values from neuroelectro.org\n",
+      "http://www.neuroelectro.org/api/1/nes/?e__name=Spike+Threshold&nlex=nifext_50\n"
+     ]
+    }
+   ],
+   "source": [
+    "import quantities as pq\n",
+    "from neuronunit import tests as nu_tests, neuroelectro\n",
+    "neuron = {'nlex_id': 'nifext_50'} # Layer V pyramidal cell\n",
+    "tests = []\n",
+    "\n",
+    "dataset_id = 354190013  # Internal ID that AIBS uses for a particular Scnn1a-Tg2-Cre \n",
+    "                        # Primary visual area, layer 5 neuron.\n",
+    "observation = aibs.get_observation(dataset_id,'rheobase')\n",
+    "tests += [nu_tests.RheobaseTest(observation=observation)]\n",
+    "    \n",
+    "test_class_params = [(nu_tests.InputResistanceTest,None),\n",
+    "                     (nu_tests.TimeConstantTest,None),\n",
+    "                     (nu_tests.CapacitanceTest,None),\n",
+    "                     (nu_tests.RestingPotentialTest,None),\n",
+    "                     (nu_tests.InjectedCurrentAPWidthTest,None),\n",
+    "                     (nu_tests.InjectedCurrentAPAmplitudeTest,None),\n",
+    "                     (nu_tests.InjectedCurrentAPThresholdTest,None)]\n",
+    "\n",
+    "for cls,params in test_class_params:\n",
+    "    observation = cls.neuroelectro_summary_observation(neuron)\n",
+    "    tests += [cls(observation,params=params)]\n",
+    "    \n",
+    "def update_amplitude(test,tests,score):\n",
+    "    rheobase = score.prediction['value']\n",
+    "    for i in [5,6,7]:\n",
+    "        print(tests[i])\n",
+    "        # Set current injection to just suprathreshold\n",
+    "        tests[i].params['injected_square_current']['amplitude'] = rheobase*1.01 \n",
+    "    \n",
+    "hooks = {tests[0]:{'f':update_amplitude}}\n",
+    "suite = sciunit.TestSuite(\"vm_suite\",tests,hooks=hooks)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "model = ReducedModel(LEMS_MODEL_PATH,name='vanilla')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "SUO = '/home/mnt/scidash/sciunitopt'\n",
+    "if SUO not in sys.path:\n",
+    "    sys.path.append(SUO)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "from types import MethodType\n",
+    "def optimize(self,model,rov):\n",
+    "    best_params = None\n",
+    "    best_score = None\n",
+    "    from deap_config_simple_sum import deap_capsule\n",
+    "    dc=deap_capsule()\n",
+    "    pop_size=12\n",
+    "    ngen=5                                  \n",
+    "    pop = dc.sciunit_optimize(self,LEMS_MODEL_PATH,pop_size,ngen,rov,\n",
+    "                                                         NDIM=2,OBJ_SIZE=2)\n",
+    "    return pop#(best_params, best_score, model)\n",
+    "\n",
+    "my_test = tests[0]\n",
+    "my_test.verbose = False\n",
+    "my_test.optimize = MethodType(optimize, my_test) # Bind to the score."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Start of evolution\n",
+      "V_rest = -91.9; SortKey = 0.505\n",
+      "V_rest = -54.2; SortKey = 0.230\n",
+      "V_rest = -70.3; SortKey = 0.998\n",
+      "V_rest = -60.9; SortKey = 0.600\n",
+      "V_rest = -94.4; SortKey = 0.453\n",
+      "V_rest = -49.9; SortKey = 0.000\n",
+      "V_rest = -54.3; SortKey = 0.230\n",
+      "V_rest = -73.3; SortKey = 0.911\n",
+      "V_rest = -86.3; SortKey = 0.600\n",
+      "V_rest = -45.9; SortKey = 0.000\n",
+      "V_rest = -98.5; SortKey = 0.386\n",
+      "V_rest = -43.7; SortKey = 0.000\n",
+      "Evaluated individuals 12\n",
+      "-- Generation 0 --\n",
+      "V_rest = -60.9; SortKey = 0.600\n",
+      "V_rest = -60.9; SortKey = 0.600\n",
+      "V_rest = -70.6; SortKey = 0.998\n",
+      "V_rest = -73.3; SortKey = 0.911\n",
+      "V_rest = -91.9; SortKey = 0.505\n",
+      "V_rest = -86.8; SortKey = 0.600\n",
+      "V_rest = -69.7; SortKey = 0.966\n",
+      "V_rest = -94.4; SortKey = 0.453\n",
+      "V_rest = -49.9; SortKey = 0.000\n",
+      "V_rest = -86.3; SortKey = 0.600\n",
+      "V_rest = -60.9; SortKey = 0.600\n",
+      "  Evaluated 11 individuals\n",
+      "-- Generation 1 --\n",
+      "V_rest = -73.3; SortKey = 0.911\n",
+      "V_rest = -60.9; SortKey = 0.600\n",
+      "V_rest = -70.6; SortKey = 0.998\n",
+      "V_rest = -69.7; SortKey = 0.966\n",
+      "V_rest = -91.6; SortKey = 0.505\n",
+      "V_rest = -70.9; SortKey = 0.998\n",
+      "V_rest = -69.7; SortKey = 0.966\n",
+      "V_rest = -60.9; SortKey = 0.600\n",
+      "V_rest = -69.4; SortKey = 0.966\n",
+      "V_rest = -94.7; SortKey = 0.453\n",
+      "V_rest = -73.2; SortKey = 0.911\n",
+      "V_rest = -70.7; SortKey = 0.998\n",
+      "  Evaluated 12 individuals\n",
+      "-- Generation 2 --\n",
+      "V_rest = -69.4; SortKey = 0.966\n",
+      "V_rest = -69.7; SortKey = 0.966\n",
+      "V_rest = -70.9; SortKey = 0.998\n",
+      "V_rest = -70.7; SortKey = 0.998\n",
+      "V_rest = -74.3; SortKey = 0.883\n",
+      "V_rest = -73.3; SortKey = 0.911\n",
+      "V_rest = -60.9; SortKey = 0.600\n",
+      "V_rest = -70.7; SortKey = 0.998\n",
+      "V_rest = -69.4; SortKey = 0.966\n",
+      "V_rest = -70.6; SortKey = 0.998\n",
+      "V_rest = -63.8; SortKey = 0.741\n",
+      "  Evaluated 11 individuals\n",
+      "-- Generation 3 --\n",
+      "V_rest = -61.7; SortKey = 0.651\n",
+      "V_rest = -69.5; SortKey = 0.966\n",
+      "V_rest = -69.4; SortKey = 0.966\n",
+      "V_rest = -70.9; SortKey = 0.998\n",
+      "V_rest = -70.6; SortKey = 0.998\n",
+      "V_rest = -69.8; SortKey = 0.966\n",
+      "V_rest = -69.7; SortKey = 0.966\n",
+      "V_rest = -70.6; SortKey = 0.998\n",
+      "  Evaluated 8 individuals\n",
+      "-- Generation 4 --\n",
+      "V_rest = -70.9; SortKey = 0.998\n",
+      "V_rest = -70.6; SortKey = 0.998\n",
+      "V_rest = -70.6; SortKey = 0.998\n",
+      "V_rest = -70.9; SortKey = 0.998\n",
+      "V_rest = -70.6; SortKey = 0.998\n",
+      "V_rest = -69.8; SortKey = 0.966\n",
+      "V_rest = -70.6; SortKey = 0.998\n",
+      "V_rest = -70.6; SortKey = 0.998\n",
+      "V_rest = -70.9; SortKey = 0.998\n",
+      "V_rest = -70.7; SortKey = 0.998\n",
+      "V_rest = -70.9; SortKey = 0.998\n",
+      "V_rest = -70.6; SortKey = 0.998\n",
+      "  Evaluated 12 individuals\n",
+      "gen\tevals\tstd         \tmin          \tavg          \tmax          \n",
+      "4  \t12   \t[ 0.0090403]\t[-0.99830022]\t[-0.99557446]\t[-0.96559118]\n"
+     ]
+    }
+   ],
+   "source": [
+    "rov = np.linspace(-100,-40,1000)\n",
+    "pop = my_test.optimize(model,rov)\n",
+    "#print('pareto front top value in pf hall of fame')\n",
+    "#print('best params',best_params,'best_score',best_score, 'model',model)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "-70.63 mV\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"%.2f mV\" % np.mean([p[0] for p in pop]))"
+   ]
+  }
+ ],
+ "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": "3.5.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}