simpleExample.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Note: This file is provided in two formats: \n",
    "Python (simpleExample.py) and a Jupyter \n",
    "notebook (simpleExample.ipynb).  The \n",
    "Jupyter notebook opens in a web browser and \n",
    "includes plots in an interactive format.  To \n",
    "open the .ipynb file, run:*\n",
    "    \n",
    "    jupyter notebook simpleExample.ipynb\n",
    "\n",
    "*To run the .py file in iPython at the command line, run:*\n",
    "\n",
    "    ipython\n",
    "    %run simpleExample.py\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "simpleExample.ipynb\n",
    "-------------------\n",
    "\n",
    "- Bryan Daniels\n",
    "\n",
    "- Last updated 2022/6/13\n",
    "\n",
    "- Uses a simple exponential decay example to demonstrate usage of SirIsaac"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Failed to import libsbml.\n",
      "SBML import and export not available.\n",
      "Failed to import pygraphviz.  Network figures unavailable.\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "from SirIsaac import fittingProblem"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load example data\n",
    "-----------------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the example data file, we have five columns, each with 100 data points, listing:\n",
    "\n",
    "* Initial condition *x_init*\n",
    "* Input condition *tau*\n",
    "* Measurement time *t*\n",
    "* Measurement value *x*\n",
    "* Measurement uncertainty (standard deviation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = np.loadtxt('simpleExample_data.csv',delimiter=',')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now put this in a format compatible with SirIsaac.  First we make a list of input values (in this case initial conditions):\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "indepParamsList = [ [ expt[0],expt[1] ] for expt in data ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[1.1272274339047885, 0.9521917233976885],\n",
       " [1.403399302209734, 0.9340177624532441],\n",
       " [1.140086651015479, 0.3559146053469723]]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "indepParamsList[:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we have a corresponding list of data taken at each of those input values, in the format below.  In this case, we only have one variable *x*.  (Note: In general, multiple timepoints could be also be measured at each input value; in all of our examples, we measure all variables at a single timepoint per input value.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# [ {'var1': { time0: ( value, uncertainty ) },\n",
    "#    'var2': { time0: ( value, uncertainty ) },\n",
    "#     ... },\n",
    "#   {'var1': { time1: ( value, uncertainty ) },\n",
    "#    'var2': { time1: ( value, uncertainty ) },\n",
    "#     ... },\n",
    "#   ... ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "sirIsaacData = []\n",
    "for expt in data:\n",
    "    sirIsaacData.append( { 'x': { expt[2]: ( expt[3], expt[4] ) } } )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'x': {0.5454701510335127: (0.531344985497982, 0.1)}},\n",
       " {'x': {0.17186531503221092: (1.2249327126800098, 0.1)}},\n",
       " {'x': {0.8529318094853018: (0.21097445827304884, 0.1)}}]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sirIsaacData[:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, SirIsaac will need to know what to call the input and output values.  In this case, the input corresponds to the initial value of *x*.  The way to indicate this to SirIsaac is by using the name 'x_init', where 'x' is the name of the corresponding variable.\n",
    "\n",
    "Here we have two inputs and one output:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "outputNames = ['x']\n",
    "indepParamNames = ['x_init','tau']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create SirIsaac FittingProblem\n",
    "------------------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll attempt to fit a model in the \"continuous time sigmoidal network\" (CTSN) class.  To do this, we'll create an instance of a CTSNFittingProblem.  Here we set up its arguments and create it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# complexityList lists which models in the model class may be tested.\n",
    "# (Note that by default SirIsaac will still stop once 3 models have \n",
    "#  smaller estimated log-likelihood.)\n",
    "complexityStepsize = 2 # increase complexity with steps of size 2\n",
    "complexityMax = 25 # don't try models with complexity > 25\n",
    "complexityList = range(0,complexityMax,complexityStepsize) \n",
    "\n",
    "# ensGen controls the generation of the initial ensemble of \n",
    "# parameter starting points.\n",
    "# (We use a small number for totalSteps here so that the example\n",
    "# runs faster; a more typical value for totalSteps is 1e3)\n",
    "totalSteps = 20 #1e3 \n",
    "keepSteps = 10\n",
    "seeds = (1,1) # use a fixed random seed\n",
    "ensTemperature = 100.\n",
    "ensGen = fittingProblem.EnsembleGenerator( totalSteps, keepSteps,\n",
    "    temperature=ensTemperature, seeds=seeds )\n",
    "\n",
    "# Parameters that control when local fitting stops.\n",
    "avegtol = 1e-2\n",
    "maxiter = 100\n",
    "\n",
    "# priorSigma controls the width of priors on all parameters\n",
    "priorSigma = 3.\n",
    "\n",
    "# If you have mpi4py installed, you can run on multiple processors\n",
    "numprocs = 4 #10\n",
    "\n",
    "# We'll only use a subset of our data to make the example run faster\n",
    "N = 20\n",
    "\n",
    "p = fittingProblem.CTSNFittingProblem( complexityList, \n",
    "    sirIsaacData[:N], indepParamsList=indepParamsList[:N], \n",
    "    outputNames=outputNames, indepParamNames=indepParamNames, \n",
    "    ensGen=ensGen, avegtol=avegtol, maxiter=maxiter,\n",
    "    priorSigma=priorSigma, numprocs=numprocs, verbose=True )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run parameter fitting\n",
    "---------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The bulk of computation time is used to fit the parameters of each model to the data.  Uncomment the following lines to run the parameter fitting, which takes an hour or two using 4 processors.  Or skip ahead to load a version that has already been fit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SloppyCellFittingModel.fitToData: generating ensemble for these parameters: ['wself_1', 'log_tau_1', 'w_1_0']\n",
      "generateEnsemble_parallel: Generating parameter ensemble with 20 total members, using 4 processors.\n",
      "SloppyCellFittingModel.fitToData: Cost = 993.7924458070916 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 1219.8530555432526 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 1630.9624477734403 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 1320.170604550665 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 1152.0337324729305 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 1098.5692232649888 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 927.3823057903097 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 880.1404710577058 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 762.1446132538285 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 106.2744124536134 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Best-fit cost =  106.2744124536134\n",
      "fittingProblem.fitAll: L = -73.12272406756854\n",
      "running build_ext\n",
      "running build_src\n",
      "build_src\n",
      "building extension \"CTSN_0_SFI_C02TJ318GTFL_2335264_0753415561_7442\" sources\n",
      "f2py options: []\n",
      "f2py: CTSN_0_SFI_C02TJ318GTFL_2335264_0753415561_7442.pyf\n",
      "Reading fortran codes...\n",
      "\tReading file 'CTSN_0_SFI_C02TJ318GTFL_2335264_0753415561_7442.pyf' (format:free)\n",
      "Post-processing...\n",
      "\tBlock: CTSN_0_SFI_C02TJ318GTFL_2335264_0753415561_7442\n",
      "\t\t\tBlock: res_function\n",
      "\t\t\tBlock: ddaskr_jac\n",
      "\t\t\tBlock: root_func\n",
      "\t\t\tBlock: alg_deriv_func\n",
      "\t\t\tBlock: alg_res_func\n",
      "\t\t\tBlock: dres_dc_function\n",
      "\t\t\tBlock: dres_dcdot_function\n",
      "\t\t\tBlock: dres_dwself_1\n",
      "\t\t\tBlock: dres_dtheta_1\n",
      "\t\t\tBlock: dres_dlog_tau_1\n",
      "\t\t\tBlock: dres_dw_1_0\n",
      "\t\t\tBlock: dres_dw_1_2\n",
      "\t\t\tBlock: dres_dX_2_init\n",
      "\t\t\tBlock: sens_rhs\n",
      "\t\t\tBlock: res_function_logdv\n",
      "\t\t\tBlock: root_func_logdv\n",
      "\t\t\tBlock: sens_rhs_logdv\n",
      "\t\t\tBlock: integrate_stochastic_tidbit\n",
      "Post-processing (stage 2)...\n",
      "Building modules...\n",
      "\tBuilding module \"CTSN_0_SFI_C02TJ318GTFL_2335264_0753415561_7442\"...\n",
      "\t\tConstructing wrapper function \"res_function\"...\n",
      "\t\t  residual = res_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"ddaskr_jac\"...\n",
      "\t\t  pd = ddaskr_jac(t,y,yprime,cj,rpar)\n",
      "\t\tConstructing wrapper function \"root_func\"...\n",
      "\t\t  root_devs = root_func(t,y,yp,constants)\n",
      "\t\tConstructing wrapper function \"alg_deriv_func\"...\n",
      "\t\t  alg_derivs_res = alg_deriv_func(alg_yp,dynamicVars,yp,time,constants)\n",
      "\t\tConstructing wrapper function \"alg_res_func\"...\n",
      "\t\t  residual = alg_res_func(alg_vals,dynamicVars,time,constants)\n",
      "\t\tConstructing wrapper function \"dres_dc_function\"...\n",
      "\t\t  pd = dres_dc_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dcdot_function\"...\n",
      "\t\t  pd = dres_dcdot_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_1\"...\n",
      "\t\t  pd = dres_dwself_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dtheta_1\"...\n",
      "\t\t  pd = dres_dtheta_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_1\"...\n",
      "\t\t  pd = dres_dlog_tau_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_0\"...\n",
      "\t\t  pd = dres_dw_1_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_2\"...\n",
      "\t\t  pd = dres_dw_1_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_2_init\"...\n",
      "\t\t  pd = dres_dX_2_init(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs\"...\n",
      "\t\t  sens_res = sens_rhs(time,sens_y,sens_yp,constants)\n",
      "\t\tConstructing wrapper function \"res_function_logdv\"...\n",
      "\t\t  residual = res_function_logdv(time,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"root_func_logdv\"...\n",
      "\t\t  root_devs = root_func_logdv(t,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs_logdv\"...\n",
      "\t\t  sens_res = sens_rhs_logdv(time,sens_y_log,sens_yp_log,constants)\n",
      "\t\tConstructing wrapper function \"integrate_stochastic_tidbit\"...\n",
      "\t\t  time_ptr,dv,stop_time_ptr,trajectory = integrate_stochastic_tidbit(seed_ptr,reseed,time_ptr,dv,cv,rmsd_ptr,stop_time_ptr)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\tWrote C/API module \"CTSN_0_SFI_C02TJ318GTFL_2335264_0753415561_7442\" to file \"./CTSN_0_SFI_C02TJ318GTFL_2335264_0753415561_7442module.c\"\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/./fortranobject.c' to sources.\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/.' to include_dirs.\n",
      "copying /Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/f2py/src/fortranobject.c -> build/src.macosx-10.9-x86_64-3.8/.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:ReactionNetworks.Components:Failed to import dynamically compiled C module CTSN_0_SFI_C02TJ318GTFL_2335264_0753415561_7442 for network CTSN.\n",
      "WARNING:ReactionNetworks.Components:No module named 'CTSN_0_SFI_C02TJ318GTFL_2335264_0753415561_7442'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "***STDOUT***\n",
      "b''\n",
      "***STDERR***\n",
      "b''\n",
      "SloppyCellFittingModel.fitToData: generating ensemble for these parameters: ['wself_1', 'theta_1', 'log_tau_1', 'w_1_0', 'w_1_2', 'X_2_init']\n",
      "generateEnsemble_parallel: Generating parameter ensemble with 20 total members, using 4 processors.\n",
      "SloppyCellFittingModel.fitToData: Cost = 108.24149355744366 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 102.85063808977046 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 103.26607492478705 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 103.73877942462019 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 107.08633179449767 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 109.14761701348945 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 104.09550296067758 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 103.8706085074381 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 104.07666972505284 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 105.44769407155617 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Best-fit cost =  102.85063808977046\n",
      "fittingProblem.fitAll: L = -71.85157277889262\n",
      "running build_ext\n",
      "running build_src\n",
      "build_src\n",
      "building extension \"CTSN_0_SFI_C02TJ318GTFL_434789_4104415561_7442\" sources\n",
      "f2py options: []\n",
      "f2py: CTSN_0_SFI_C02TJ318GTFL_434789_4104415561_7442.pyf\n",
      "Reading fortran codes...\n",
      "\tReading file 'CTSN_0_SFI_C02TJ318GTFL_434789_4104415561_7442.pyf' (format:free)\n",
      "Post-processing...\n",
      "\tBlock: CTSN_0_SFI_C02TJ318GTFL_434789_4104415561_7442\n",
      "\t\t\tBlock: res_function\n",
      "\t\t\tBlock: ddaskr_jac\n",
      "\t\t\tBlock: root_func\n",
      "\t\t\tBlock: alg_deriv_func\n",
      "\t\t\tBlock: alg_res_func\n",
      "\t\t\tBlock: dres_dc_function\n",
      "\t\t\tBlock: dres_dcdot_function\n",
      "\t\t\tBlock: dres_dwself_1\n",
      "\t\t\tBlock: dres_dtheta_1\n",
      "\t\t\tBlock: dres_dlog_tau_1\n",
      "\t\t\tBlock: dres_dw_1_0\n",
      "\t\t\tBlock: dres_dw_1_2\n",
      "\t\t\tBlock: dres_dw_2_1\n",
      "\t\t\tBlock: dres_dw_2_0\n",
      "\t\t\tBlock: dres_dX_2_init\n",
      "\t\t\tBlock: sens_rhs\n",
      "\t\t\tBlock: res_function_logdv\n",
      "\t\t\tBlock: root_func_logdv\n",
      "\t\t\tBlock: sens_rhs_logdv\n",
      "\t\t\tBlock: integrate_stochastic_tidbit\n",
      "Post-processing (stage 2)...\n",
      "Building modules...\n",
      "\tBuilding module \"CTSN_0_SFI_C02TJ318GTFL_434789_4104415561_7442\"...\n",
      "\t\tConstructing wrapper function \"res_function\"...\n",
      "\t\t  residual = res_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"ddaskr_jac\"...\n",
      "\t\t  pd = ddaskr_jac(t,y,yprime,cj,rpar)\n",
      "\t\tConstructing wrapper function \"root_func\"...\n",
      "\t\t  root_devs = root_func(t,y,yp,constants)\n",
      "\t\tConstructing wrapper function \"alg_deriv_func\"...\n",
      "\t\t  alg_derivs_res = alg_deriv_func(alg_yp,dynamicVars,yp,time,constants)\n",
      "\t\tConstructing wrapper function \"alg_res_func\"...\n",
      "\t\t  residual = alg_res_func(alg_vals,dynamicVars,time,constants)\n",
      "\t\tConstructing wrapper function \"dres_dc_function\"...\n",
      "\t\t  pd = dres_dc_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dcdot_function\"...\n",
      "\t\t  pd = dres_dcdot_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_1\"...\n",
      "\t\t  pd = dres_dwself_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dtheta_1\"...\n",
      "\t\t  pd = dres_dtheta_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_1\"...\n",
      "\t\t  pd = dres_dlog_tau_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_0\"...\n",
      "\t\t  pd = dres_dw_1_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_2\"...\n",
      "\t\t  pd = dres_dw_1_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_1\"...\n",
      "\t\t  pd = dres_dw_2_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_0\"...\n",
      "\t\t  pd = dres_dw_2_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_2_init\"...\n",
      "\t\t  pd = dres_dX_2_init(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs\"...\n",
      "\t\t  sens_res = sens_rhs(time,sens_y,sens_yp,constants)\n",
      "\t\tConstructing wrapper function \"res_function_logdv\"...\n",
      "\t\t  residual = res_function_logdv(time,log_dv,log_yp,constants)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\t\tConstructing wrapper function \"root_func_logdv\"...\n",
      "\t\t  root_devs = root_func_logdv(t,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs_logdv\"...\n",
      "\t\t  sens_res = sens_rhs_logdv(time,sens_y_log,sens_yp_log,constants)\n",
      "\t\tConstructing wrapper function \"integrate_stochastic_tidbit\"...\n",
      "\t\t  time_ptr,dv,stop_time_ptr,trajectory = integrate_stochastic_tidbit(seed_ptr,reseed,time_ptr,dv,cv,rmsd_ptr,stop_time_ptr)\n",
      "\tWrote C/API module \"CTSN_0_SFI_C02TJ318GTFL_434789_4104415561_7442\" to file \"./CTSN_0_SFI_C02TJ318GTFL_434789_4104415561_7442module.c\"\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/./fortranobject.c' to sources.\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/.' to include_dirs.\n",
      "copying /Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/f2py/src/fortranobject.c -> build/src.macosx-10.9-x86_64-3.8/.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:ReactionNetworks.Components:Failed to import dynamically compiled C module CTSN_0_SFI_C02TJ318GTFL_434789_4104415561_7442 for network CTSN.\n",
      "WARNING:ReactionNetworks.Components:No module named 'CTSN_0_SFI_C02TJ318GTFL_434789_4104415561_7442'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "***STDOUT***\n",
      "b''\n",
      "***STDERR***\n",
      "b''\n",
      "SloppyCellFittingModel.fitToData: generating ensemble for these parameters: ['wself_1', 'theta_1', 'log_tau_1', 'w_1_0', 'w_1_2', 'w_2_1', 'w_2_0', 'X_2_init']\n",
      "generateEnsemble_parallel: Generating parameter ensemble with 20 total members, using 4 processors.\n",
      "SloppyCellFittingModel.fitToData: Cost = 104.55529221236701 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 103.74423054265564 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 103.45697407349847 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 103.38019643233056 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 103.5002781202935 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 104.7762894041013 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 104.58730405622158 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 104.06627287526437 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 103.85074820568322 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 102.85063808977046 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Best-fit cost =  102.85063808977046\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/bryandaniels/Desktop/SloppyCell/SloppyCell/ReactionNetworks/Dynamics.py:711: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  ypIC[N_dyn_vars:] /= net.get_var_ic(opt_var)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fittingProblem.fitAll: L = -71.91118730091047\n",
      "running build_ext\n",
      "running build_src\n",
      "build_src\n",
      "building extension \"CTSN_0_SFI_C02TJ318GTFL_802379_7324415561_7442\" sources\n",
      "f2py options: []\n",
      "f2py: CTSN_0_SFI_C02TJ318GTFL_802379_7324415561_7442.pyf\n",
      "Reading fortran codes...\n",
      "\tReading file 'CTSN_0_SFI_C02TJ318GTFL_802379_7324415561_7442.pyf' (format:free)\n",
      "Post-processing...\n",
      "\tBlock: CTSN_0_SFI_C02TJ318GTFL_802379_7324415561_7442\n",
      "\t\t\tBlock: res_function\n",
      "\t\t\tBlock: ddaskr_jac\n",
      "\t\t\tBlock: root_func\n",
      "\t\t\tBlock: alg_deriv_func\n",
      "\t\t\tBlock: alg_res_func\n",
      "\t\t\tBlock: dres_dc_function\n",
      "\t\t\tBlock: dres_dcdot_function\n",
      "\t\t\tBlock: dres_dwself_1\n",
      "\t\t\tBlock: dres_dtheta_1\n",
      "\t\t\tBlock: dres_dlog_tau_1\n",
      "\t\t\tBlock: dres_dw_1_0\n",
      "\t\t\tBlock: dres_dw_1_2\n",
      "\t\t\tBlock: dres_dwself_2\n",
      "\t\t\tBlock: dres_dlog_tau_2\n",
      "\t\t\tBlock: dres_dw_2_1\n",
      "\t\t\tBlock: dres_dw_2_0\n",
      "\t\t\tBlock: dres_dX_2_init\n",
      "\t\t\tBlock: sens_rhs\n",
      "\t\t\tBlock: res_function_logdv\n",
      "\t\t\tBlock: root_func_logdv\n",
      "\t\t\tBlock: sens_rhs_logdv\n",
      "\t\t\tBlock: integrate_stochastic_tidbit\n",
      "Post-processing (stage 2)...\n",
      "Building modules...\n",
      "\tBuilding module \"CTSN_0_SFI_C02TJ318GTFL_802379_7324415561_7442\"...\n",
      "\t\tConstructing wrapper function \"res_function\"...\n",
      "\t\t  residual = res_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"ddaskr_jac\"...\n",
      "\t\t  pd = ddaskr_jac(t,y,yprime,cj,rpar)\n",
      "\t\tConstructing wrapper function \"root_func\"...\n",
      "\t\t  root_devs = root_func(t,y,yp,constants)\n",
      "\t\tConstructing wrapper function \"alg_deriv_func\"...\n",
      "\t\t  alg_derivs_res = alg_deriv_func(alg_yp,dynamicVars,yp,time,constants)\n",
      "\t\tConstructing wrapper function \"alg_res_func\"...\n",
      "\t\t  residual = alg_res_func(alg_vals,dynamicVars,time,constants)\n",
      "\t\tConstructing wrapper function \"dres_dc_function\"...\n",
      "\t\t  pd = dres_dc_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dcdot_function\"...\n",
      "\t\t  pd = dres_dcdot_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_1\"...\n",
      "\t\t  pd = dres_dwself_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dtheta_1\"...\n",
      "\t\t  pd = dres_dtheta_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_1\"...\n",
      "\t\t  pd = dres_dlog_tau_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_0\"...\n",
      "\t\t  pd = dres_dw_1_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_2\"...\n",
      "\t\t  pd = dres_dw_1_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_2\"...\n",
      "\t\t  pd = dres_dwself_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_2\"...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\t\t  pd = dres_dlog_tau_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_1\"...\n",
      "\t\t  pd = dres_dw_2_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_0\"...\n",
      "\t\t  pd = dres_dw_2_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_2_init\"...\n",
      "\t\t  pd = dres_dX_2_init(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs\"...\n",
      "\t\t  sens_res = sens_rhs(time,sens_y,sens_yp,constants)\n",
      "\t\tConstructing wrapper function \"res_function_logdv\"...\n",
      "\t\t  residual = res_function_logdv(time,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"root_func_logdv\"...\n",
      "\t\t  root_devs = root_func_logdv(t,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs_logdv\"...\n",
      "\t\t  sens_res = sens_rhs_logdv(time,sens_y_log,sens_yp_log,constants)\n",
      "\t\tConstructing wrapper function \"integrate_stochastic_tidbit\"...\n",
      "\t\t  time_ptr,dv,stop_time_ptr,trajectory = integrate_stochastic_tidbit(seed_ptr,reseed,time_ptr,dv,cv,rmsd_ptr,stop_time_ptr)\n",
      "\tWrote C/API module \"CTSN_0_SFI_C02TJ318GTFL_802379_7324415561_7442\" to file \"./CTSN_0_SFI_C02TJ318GTFL_802379_7324415561_7442module.c\"\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/./fortranobject.c' to sources.\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/.' to include_dirs.\n",
      "copying /Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/f2py/src/fortranobject.c -> build/src.macosx-10.9-x86_64-3.8/.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:ReactionNetworks.Components:Failed to import dynamically compiled C module CTSN_0_SFI_C02TJ318GTFL_802379_7324415561_7442 for network CTSN.\n",
      "WARNING:ReactionNetworks.Components:No module named 'CTSN_0_SFI_C02TJ318GTFL_802379_7324415561_7442'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "***STDOUT***\n",
      "b''\n",
      "***STDERR***\n",
      "b''\n",
      "SloppyCellFittingModel.fitToData: generating ensemble for these parameters: ['wself_1', 'theta_1', 'log_tau_1', 'w_1_0', 'w_1_2', 'wself_2', 'log_tau_2', 'w_2_1', 'w_2_0', 'X_2_init']\n",
      "generateEnsemble_parallel: Generating parameter ensemble with 20 total members, using 4 processors.\n",
      "SloppyCellFittingModel.fitToData: Cost = 104.31417857036543 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 106.64593448375115 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 105.72363552965213 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 103.22881002850504 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 102.88658163521569 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 105.23069512625649 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 105.25692059958092 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 102.45527025785351 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 104.91369594254866 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 102.85063808977046 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Best-fit cost =  102.45527025785351\n",
      "fittingProblem.fitAll: L = -70.64509888028904\n",
      "running build_ext\n",
      "running build_src\n",
      "build_src\n",
      "building extension \"CTSN_0_SFI_C02TJ318GTFL_8353079_5054415561_7442\" sources\n",
      "f2py options: []\n",
      "f2py: CTSN_0_SFI_C02TJ318GTFL_8353079_5054415561_7442.pyf\n",
      "Reading fortran codes...\n",
      "\tReading file 'CTSN_0_SFI_C02TJ318GTFL_8353079_5054415561_7442.pyf' (format:free)\n",
      "Post-processing...\n",
      "\tBlock: CTSN_0_SFI_C02TJ318GTFL_8353079_5054415561_7442\n",
      "\t\t\tBlock: res_function\n",
      "\t\t\tBlock: ddaskr_jac\n",
      "\t\t\tBlock: root_func\n",
      "\t\t\tBlock: alg_deriv_func\n",
      "\t\t\tBlock: alg_res_func\n",
      "\t\t\tBlock: dres_dc_function\n",
      "\t\t\tBlock: dres_dcdot_function\n",
      "\t\t\tBlock: dres_dwself_1\n",
      "\t\t\tBlock: dres_dtheta_1\n",
      "\t\t\tBlock: dres_dlog_tau_1\n",
      "\t\t\tBlock: dres_dw_1_0\n",
      "\t\t\tBlock: dres_dw_1_2\n",
      "\t\t\tBlock: dres_dw_1_3\n",
      "\t\t\tBlock: dres_dwself_2\n",
      "\t\t\tBlock: dres_dtheta_2\n",
      "\t\t\tBlock: dres_dlog_tau_2\n",
      "\t\t\tBlock: dres_dw_2_1\n",
      "\t\t\tBlock: dres_dw_2_0\n",
      "\t\t\tBlock: dres_dX_2_init\n",
      "\t\t\tBlock: dres_dX_3_init\n",
      "\t\t\tBlock: sens_rhs\n",
      "\t\t\tBlock: res_function_logdv\n",
      "\t\t\tBlock: root_func_logdv\n",
      "\t\t\tBlock: sens_rhs_logdv\n",
      "\t\t\tBlock: integrate_stochastic_tidbit\n",
      "Post-processing (stage 2)...\n",
      "Building modules...\n",
      "\tBuilding module \"CTSN_0_SFI_C02TJ318GTFL_8353079_5054415561_7442\"...\n",
      "\t\tConstructing wrapper function \"res_function\"...\n",
      "\t\t  residual = res_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"ddaskr_jac\"...\n",
      "\t\t  pd = ddaskr_jac(t,y,yprime,cj,rpar)\n",
      "\t\tConstructing wrapper function \"root_func\"...\n",
      "\t\t  root_devs = root_func(t,y,yp,constants)\n",
      "\t\tConstructing wrapper function \"alg_deriv_func\"...\n",
      "\t\t  alg_derivs_res = alg_deriv_func(alg_yp,dynamicVars,yp,time,constants)\n",
      "\t\tConstructing wrapper function \"alg_res_func\"...\n",
      "\t\t  residual = alg_res_func(alg_vals,dynamicVars,time,constants)\n",
      "\t\tConstructing wrapper function \"dres_dc_function\"...\n",
      "\t\t  pd = dres_dc_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dcdot_function\"...\n",
      "\t\t  pd = dres_dcdot_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_1\"...\n",
      "\t\t  pd = dres_dwself_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dtheta_1\"...\n",
      "\t\t  pd = dres_dtheta_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_1\"...\n",
      "\t\t  pd = dres_dlog_tau_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_0\"...\n",
      "\t\t  pd = dres_dw_1_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_2\"...\n",
      "\t\t  pd = dres_dw_1_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_3\"...\n",
      "\t\t  pd = dres_dw_1_3(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_2\"...\n",
      "\t\t  pd = dres_dwself_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dtheta_2\"...\n",
      "\t\t  pd = dres_dtheta_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_2\"...\n",
      "\t\t  pd = dres_dlog_tau_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_1\"...\n",
      "\t\t  pd = dres_dw_2_1(time,dynamicVars,yprime,constants)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\t\tConstructing wrapper function \"dres_dw_2_0\"...\n",
      "\t\t  pd = dres_dw_2_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_2_init\"...\n",
      "\t\t  pd = dres_dX_2_init(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_3_init\"...\n",
      "\t\t  pd = dres_dX_3_init(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs\"...\n",
      "\t\t  sens_res = sens_rhs(time,sens_y,sens_yp,constants)\n",
      "\t\tConstructing wrapper function \"res_function_logdv\"...\n",
      "\t\t  residual = res_function_logdv(time,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"root_func_logdv\"...\n",
      "\t\t  root_devs = root_func_logdv(t,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs_logdv\"...\n",
      "\t\t  sens_res = sens_rhs_logdv(time,sens_y_log,sens_yp_log,constants)\n",
      "\t\tConstructing wrapper function \"integrate_stochastic_tidbit\"...\n",
      "\t\t  time_ptr,dv,stop_time_ptr,trajectory = integrate_stochastic_tidbit(seed_ptr,reseed,time_ptr,dv,cv,rmsd_ptr,stop_time_ptr)\n",
      "\tWrote C/API module \"CTSN_0_SFI_C02TJ318GTFL_8353079_5054415561_7442\" to file \"./CTSN_0_SFI_C02TJ318GTFL_8353079_5054415561_7442module.c\"\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/./fortranobject.c' to sources.\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/.' to include_dirs.\n",
      "copying /Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/f2py/src/fortranobject.c -> build/src.macosx-10.9-x86_64-3.8/.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:ReactionNetworks.Components:Failed to import dynamically compiled C module CTSN_0_SFI_C02TJ318GTFL_8353079_5054415561_7442 for network CTSN.\n",
      "WARNING:ReactionNetworks.Components:No module named 'CTSN_0_SFI_C02TJ318GTFL_8353079_5054415561_7442'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "***STDOUT***\n",
      "b''\n",
      "***STDERR***\n",
      "b''\n",
      "SloppyCellFittingModel.fitToData: generating ensemble for these parameters: ['wself_1', 'theta_1', 'log_tau_1', 'w_1_0', 'w_1_2', 'w_1_3', 'wself_2', 'theta_2', 'log_tau_2', 'w_2_1', 'w_2_0', 'X_2_init', 'X_3_init']\n",
      "generateEnsemble_parallel: Generating parameter ensemble with 20 total members, using 4 processors.\n",
      "SloppyCellFittingModel.fitToData: Cost = 99.273861418542 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 99.28376953003541 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 99.4628625821131 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 100.05769545088538 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 100.80623739660349 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 100.2507708711533 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 100.12476193337554 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 101.07368031190904 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 101.17018734219175 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 102.40914917619384 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Best-fit cost =  99.273861418542\n",
      "fittingProblem.fitAll: L = -74.1526752962969\n",
      "running build_ext\n",
      "running build_src\n",
      "build_src\n",
      "building extension \"CTSN_0_SFI_C02TJ318GTFL_301571_4916415561_7442\" sources\n",
      "f2py options: []\n",
      "f2py: CTSN_0_SFI_C02TJ318GTFL_301571_4916415561_7442.pyf\n",
      "Reading fortran codes...\n",
      "\tReading file 'CTSN_0_SFI_C02TJ318GTFL_301571_4916415561_7442.pyf' (format:free)\n",
      "Post-processing...\n",
      "\tBlock: CTSN_0_SFI_C02TJ318GTFL_301571_4916415561_7442\n",
      "\t\t\tBlock: res_function\n",
      "\t\t\tBlock: ddaskr_jac\n",
      "\t\t\tBlock: root_func\n",
      "\t\t\tBlock: alg_deriv_func\n",
      "\t\t\tBlock: alg_res_func\n",
      "\t\t\tBlock: dres_dc_function\n",
      "\t\t\tBlock: dres_dcdot_function\n",
      "\t\t\tBlock: dres_dwself_1\n",
      "\t\t\tBlock: dres_dtheta_1\n",
      "\t\t\tBlock: dres_dlog_tau_1\n",
      "\t\t\tBlock: dres_dw_1_0\n",
      "\t\t\tBlock: dres_dw_1_2\n",
      "\t\t\tBlock: dres_dw_1_3\n",
      "\t\t\tBlock: dres_dwself_2\n",
      "\t\t\tBlock: dres_dtheta_2\n",
      "\t\t\tBlock: dres_dlog_tau_2\n",
      "\t\t\tBlock: dres_dw_2_1\n",
      "\t\t\tBlock: dres_dw_2_0\n",
      "\t\t\tBlock: dres_dX_2_init\n",
      "\t\t\tBlock: dres_dw_3_1\n",
      "\t\t\tBlock: dres_dw_3_0\n",
      "\t\t\tBlock: dres_dX_3_init\n",
      "\t\t\tBlock: sens_rhs\n",
      "\t\t\tBlock: res_function_logdv\n",
      "\t\t\tBlock: root_func_logdv\n",
      "\t\t\tBlock: sens_rhs_logdv\n",
      "\t\t\tBlock: integrate_stochastic_tidbit\n",
      "Post-processing (stage 2)...\n",
      "Building modules...\n",
      "\tBuilding module \"CTSN_0_SFI_C02TJ318GTFL_301571_4916415561_7442\"...\n",
      "\t\tConstructing wrapper function \"res_function\"...\n",
      "\t\t  residual = res_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"ddaskr_jac\"...\n",
      "\t\t  pd = ddaskr_jac(t,y,yprime,cj,rpar)\n",
      "\t\tConstructing wrapper function \"root_func\"...\n",
      "\t\t  root_devs = root_func(t,y,yp,constants)\n",
      "\t\tConstructing wrapper function \"alg_deriv_func\"...\n",
      "\t\t  alg_derivs_res = alg_deriv_func(alg_yp,dynamicVars,yp,time,constants)\n",
      "\t\tConstructing wrapper function \"alg_res_func\"...\n",
      "\t\t  residual = alg_res_func(alg_vals,dynamicVars,time,constants)\n",
      "\t\tConstructing wrapper function \"dres_dc_function\"...\n",
      "\t\t  pd = dres_dc_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dcdot_function\"...\n",
      "\t\t  pd = dres_dcdot_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_1\"...\n",
      "\t\t  pd = dres_dwself_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dtheta_1\"...\n",
      "\t\t  pd = dres_dtheta_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_1\"...\n",
      "\t\t  pd = dres_dlog_tau_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_0\"...\n",
      "\t\t  pd = dres_dw_1_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_2\"...\n",
      "\t\t  pd = dres_dw_1_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_3\"...\n",
      "\t\t  pd = dres_dw_1_3(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_2\"...\n",
      "\t\t  pd = dres_dwself_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dtheta_2\"...\n",
      "\t\t  pd = dres_dtheta_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_2\"...\n",
      "\t\t  pd = dres_dlog_tau_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_1\"...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\t\t  pd = dres_dw_2_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_0\"...\n",
      "\t\t  pd = dres_dw_2_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_2_init\"...\n",
      "\t\t  pd = dres_dX_2_init(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_3_1\"...\n",
      "\t\t  pd = dres_dw_3_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_3_0\"...\n",
      "\t\t  pd = dres_dw_3_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_3_init\"...\n",
      "\t\t  pd = dres_dX_3_init(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs\"...\n",
      "\t\t  sens_res = sens_rhs(time,sens_y,sens_yp,constants)\n",
      "\t\tConstructing wrapper function \"res_function_logdv\"...\n",
      "\t\t  residual = res_function_logdv(time,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"root_func_logdv\"...\n",
      "\t\t  root_devs = root_func_logdv(t,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs_logdv\"...\n",
      "\t\t  sens_res = sens_rhs_logdv(time,sens_y_log,sens_yp_log,constants)\n",
      "\t\tConstructing wrapper function \"integrate_stochastic_tidbit\"...\n",
      "\t\t  time_ptr,dv,stop_time_ptr,trajectory = integrate_stochastic_tidbit(seed_ptr,reseed,time_ptr,dv,cv,rmsd_ptr,stop_time_ptr)\n",
      "\tWrote C/API module \"CTSN_0_SFI_C02TJ318GTFL_301571_4916415561_7442\" to file \"./CTSN_0_SFI_C02TJ318GTFL_301571_4916415561_7442module.c\"\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/./fortranobject.c' to sources.\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/.' to include_dirs.\n",
      "copying /Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/f2py/src/fortranobject.c -> build/src.macosx-10.9-x86_64-3.8/.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:ReactionNetworks.Components:Failed to import dynamically compiled C module CTSN_0_SFI_C02TJ318GTFL_301571_4916415561_7442 for network CTSN.\n",
      "WARNING:ReactionNetworks.Components:No module named 'CTSN_0_SFI_C02TJ318GTFL_301571_4916415561_7442'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "***STDOUT***\n",
      "b''\n",
      "***STDERR***\n",
      "b''\n",
      "SloppyCellFittingModel.fitToData: generating ensemble for these parameters: ['wself_1', 'theta_1', 'log_tau_1', 'w_1_0', 'w_1_2', 'w_1_3', 'wself_2', 'theta_2', 'log_tau_2', 'w_2_1', 'w_2_0', 'X_2_init', 'w_3_1', 'w_3_0', 'X_3_init']\n",
      "generateEnsemble_parallel: Generating parameter ensemble with 20 total members, using 4 processors.\n",
      "SloppyCellFittingModel.fitToData: Cost = 99.19763004212449 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 99.18790408822247 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 100.46533653118921 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 99.08497396687075 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 99.62626888685377 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 97.48384855713758 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 96.35056627677257 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 98.26194803791873 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 98.38256486766932 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 97.22608947308764 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Best-fit cost =  96.35056627677257\n",
      "fittingProblem.fitAll: L = -73.57941722124676\n",
      "running build_ext\n",
      "running build_src\n",
      "build_src\n",
      "building extension \"CTSN_0_SFI_C02TJ318GTFL_281808_4097415561_7442\" sources\n",
      "f2py options: []\n",
      "f2py: CTSN_0_SFI_C02TJ318GTFL_281808_4097415561_7442.pyf\n",
      "Reading fortran codes...\n",
      "\tReading file 'CTSN_0_SFI_C02TJ318GTFL_281808_4097415561_7442.pyf' (format:free)\n",
      "Post-processing...\n",
      "\tBlock: CTSN_0_SFI_C02TJ318GTFL_281808_4097415561_7442\n",
      "\t\t\tBlock: res_function\n",
      "\t\t\tBlock: ddaskr_jac\n",
      "\t\t\tBlock: root_func\n",
      "\t\t\tBlock: alg_deriv_func\n",
      "\t\t\tBlock: alg_res_func\n",
      "\t\t\tBlock: dres_dc_function\n",
      "\t\t\tBlock: dres_dcdot_function\n",
      "\t\t\tBlock: dres_dwself_1\n",
      "\t\t\tBlock: dres_dtheta_1\n",
      "\t\t\tBlock: dres_dlog_tau_1\n",
      "\t\t\tBlock: dres_dw_1_0\n",
      "\t\t\tBlock: dres_dw_1_2\n",
      "\t\t\tBlock: dres_dw_1_3\n",
      "\t\t\tBlock: dres_dwself_2\n",
      "\t\t\tBlock: dres_dtheta_2\n",
      "\t\t\tBlock: dres_dlog_tau_2\n",
      "\t\t\tBlock: dres_dw_2_1\n",
      "\t\t\tBlock: dres_dw_2_0\n",
      "\t\t\tBlock: dres_dw_2_3\n",
      "\t\t\tBlock: dres_dX_2_init\n",
      "\t\t\tBlock: dres_dw_3_1\n",
      "\t\t\tBlock: dres_dw_3_0\n",
      "\t\t\tBlock: dres_dw_3_2\n",
      "\t\t\tBlock: dres_dX_3_init\n",
      "\t\t\tBlock: sens_rhs\n",
      "\t\t\tBlock: res_function_logdv\n",
      "\t\t\tBlock: root_func_logdv\n",
      "\t\t\tBlock: sens_rhs_logdv\n",
      "\t\t\tBlock: integrate_stochastic_tidbit\n",
      "Post-processing (stage 2)...\n",
      "Building modules...\n",
      "\tBuilding module \"CTSN_0_SFI_C02TJ318GTFL_281808_4097415561_7442\"...\n",
      "\t\tConstructing wrapper function \"res_function\"...\n",
      "\t\t  residual = res_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"ddaskr_jac\"...\n",
      "\t\t  pd = ddaskr_jac(t,y,yprime,cj,rpar)\n",
      "\t\tConstructing wrapper function \"root_func\"...\n",
      "\t\t  root_devs = root_func(t,y,yp,constants)\n",
      "\t\tConstructing wrapper function \"alg_deriv_func\"...\n",
      "\t\t  alg_derivs_res = alg_deriv_func(alg_yp,dynamicVars,yp,time,constants)\n",
      "\t\tConstructing wrapper function \"alg_res_func\"...\n",
      "\t\t  residual = alg_res_func(alg_vals,dynamicVars,time,constants)\n",
      "\t\tConstructing wrapper function \"dres_dc_function\"...\n",
      "\t\t  pd = dres_dc_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dcdot_function\"...\n",
      "\t\t  pd = dres_dcdot_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_1\"...\n",
      "\t\t  pd = dres_dwself_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dtheta_1\"...\n",
      "\t\t  pd = dres_dtheta_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_1\"...\n",
      "\t\t  pd = dres_dlog_tau_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_0\"...\n",
      "\t\t  pd = dres_dw_1_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_2\"...\n",
      "\t\t  pd = dres_dw_1_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_3\"...\n",
      "\t\t  pd = dres_dw_1_3(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_2\"...\n",
      "\t\t  pd = dres_dwself_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dtheta_2\"...\n",
      "\t\t  pd = dres_dtheta_2(time,dynamicVars,yprime,constants)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\t\tConstructing wrapper function \"dres_dlog_tau_2\"...\n",
      "\t\t  pd = dres_dlog_tau_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_1\"...\n",
      "\t\t  pd = dres_dw_2_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_0\"...\n",
      "\t\t  pd = dres_dw_2_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_3\"...\n",
      "\t\t  pd = dres_dw_2_3(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_2_init\"...\n",
      "\t\t  pd = dres_dX_2_init(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_3_1\"...\n",
      "\t\t  pd = dres_dw_3_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_3_0\"...\n",
      "\t\t  pd = dres_dw_3_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_3_2\"...\n",
      "\t\t  pd = dres_dw_3_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_3_init\"...\n",
      "\t\t  pd = dres_dX_3_init(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs\"...\n",
      "\t\t  sens_res = sens_rhs(time,sens_y,sens_yp,constants)\n",
      "\t\tConstructing wrapper function \"res_function_logdv\"...\n",
      "\t\t  residual = res_function_logdv(time,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"root_func_logdv\"...\n",
      "\t\t  root_devs = root_func_logdv(t,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs_logdv\"...\n",
      "\t\t  sens_res = sens_rhs_logdv(time,sens_y_log,sens_yp_log,constants)\n",
      "\t\tConstructing wrapper function \"integrate_stochastic_tidbit\"...\n",
      "\t\t  time_ptr,dv,stop_time_ptr,trajectory = integrate_stochastic_tidbit(seed_ptr,reseed,time_ptr,dv,cv,rmsd_ptr,stop_time_ptr)\n",
      "\tWrote C/API module \"CTSN_0_SFI_C02TJ318GTFL_281808_4097415561_7442\" to file \"./CTSN_0_SFI_C02TJ318GTFL_281808_4097415561_7442module.c\"\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/./fortranobject.c' to sources.\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/.' to include_dirs.\n",
      "copying /Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/f2py/src/fortranobject.c -> build/src.macosx-10.9-x86_64-3.8/.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:ReactionNetworks.Components:Failed to import dynamically compiled C module CTSN_0_SFI_C02TJ318GTFL_281808_4097415561_7442 for network CTSN.\n",
      "WARNING:ReactionNetworks.Components:No module named 'CTSN_0_SFI_C02TJ318GTFL_281808_4097415561_7442'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "***STDOUT***\n",
      "b''\n",
      "***STDERR***\n",
      "b''\n",
      "SloppyCellFittingModel.fitToData: generating ensemble for these parameters: ['wself_1', 'theta_1', 'log_tau_1', 'w_1_0', 'w_1_2', 'w_1_3', 'wself_2', 'theta_2', 'log_tau_2', 'w_2_1', 'w_2_0', 'w_2_3', 'X_2_init', 'w_3_1', 'w_3_0', 'w_3_2', 'X_3_init']\n",
      "generateEnsemble_parallel: Generating parameter ensemble with 20 total members, using 4 processors.\n",
      "SloppyCellFittingModel.fitToData: Cost = 107.36886122584806 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 99.63021672092857 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 99.61934819814904 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 100.32910128380607 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 100.26505247362063 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 101.03123353758875 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 97.66499612139881 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 96.47771105170251 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 99.0305324973917 ( 0 )\n",
      "SloppyCellFittingModel.fitToData: Cost = 96.35056574486659 ( 1 )\n",
      "SloppyCellFittingModel.fitToData: Best-fit cost =  96.35056574486659\n",
      "fittingProblem.fitAll: L = -73.69419317634126\n"
     ]
    }
   ],
   "source": [
    "## Uncomment to run parameter fitting.\n",
    "#p.fitAll()\n",
    "#\n",
    "#fittingProblem.save(p,'simpleExample_savedFittingProblem.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "running build_ext\n",
      "running build_src\n",
      "build_src\n",
      "building extension \"CTSN_0_SFI_C02TJ318GTFL_759068_7266515561_16872\" sources\n",
      "f2py options: []\n",
      "f2py: CTSN_0_SFI_C02TJ318GTFL_759068_7266515561_16872.pyf\n",
      "Reading fortran codes...\n",
      "\tReading file 'CTSN_0_SFI_C02TJ318GTFL_759068_7266515561_16872.pyf' (format:free)\n",
      "Post-processing...\n",
      "\tBlock: CTSN_0_SFI_C02TJ318GTFL_759068_7266515561_16872\n",
      "\t\t\tBlock: res_function\n",
      "\t\t\tBlock: ddaskr_jac\n",
      "\t\t\tBlock: root_func\n",
      "\t\t\tBlock: alg_deriv_func\n",
      "\t\t\tBlock: alg_res_func\n",
      "\t\t\tBlock: dres_dc_function\n",
      "\t\t\tBlock: dres_dcdot_function\n",
      "\t\t\tBlock: dres_dwself_1\n",
      "\t\t\tBlock: dres_dlog_tau_1\n",
      "\t\t\tBlock: dres_dw_1_0\n",
      "\t\t\tBlock: sens_rhs\n",
      "\t\t\tBlock: res_function_logdv\n",
      "\t\t\tBlock: root_func_logdv\n",
      "\t\t\tBlock: sens_rhs_logdv\n",
      "\t\t\tBlock: integrate_stochastic_tidbit\n",
      "Post-processing (stage 2)...\n",
      "Building modules...\n",
      "\tBuilding module \"CTSN_0_SFI_C02TJ318GTFL_759068_7266515561_16872\"...\n",
      "\t\tConstructing wrapper function \"res_function\"...\n",
      "\t\t  residual = res_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"ddaskr_jac\"...\n",
      "\t\t  pd = ddaskr_jac(t,y,yprime,cj,rpar)\n",
      "\t\tConstructing wrapper function \"root_func\"...\n",
      "\t\t  root_devs = root_func(t,y,yp,constants)\n",
      "\t\tConstructing wrapper function \"alg_deriv_func\"...\n",
      "\t\t  alg_derivs_res = alg_deriv_func(alg_yp,dynamicVars,yp,time,constants)\n",
      "\t\tConstructing wrapper function \"alg_res_func\"...\n",
      "\t\t  residual = alg_res_func(alg_vals,dynamicVars,time,constants)\n",
      "\t\tConstructing wrapper function \"dres_dc_function\"...\n",
      "\t\t  pd = dres_dc_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dcdot_function\"...\n",
      "\t\t  pd = dres_dcdot_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_1\"...\n",
      "\t\t  pd = dres_dwself_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_1\"...\n",
      "\t\t  pd = dres_dlog_tau_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_0\"...\n",
      "\t\t  pd = dres_dw_1_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs\"...\n",
      "\t\t  sens_res = sens_rhs(time,sens_y,sens_yp,constants)\n",
      "\t\tConstructing wrapper function \"res_function_logdv\"...\n",
      "\t\t  residual = res_function_logdv(time,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"root_func_logdv\"...\n",
      "\t\t  root_devs = root_func_logdv(t,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs_logdv\"...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\t\t  sens_res = sens_rhs_logdv(time,sens_y_log,sens_yp_log,constants)\n",
      "\t\tConstructing wrapper function \"integrate_stochastic_tidbit\"...\n",
      "\t\t  time_ptr,dv,stop_time_ptr,trajectory = integrate_stochastic_tidbit(seed_ptr,reseed,time_ptr,dv,cv,rmsd_ptr,stop_time_ptr)\n",
      "\tWrote C/API module \"CTSN_0_SFI_C02TJ318GTFL_759068_7266515561_16872\" to file \"./CTSN_0_SFI_C02TJ318GTFL_759068_7266515561_16872module.c\"\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/./fortranobject.c' to sources.\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/.' to include_dirs.\n",
      "creating build\n",
      "creating build/src.macosx-10.9-x86_64-3.8\n",
      "copying /Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/f2py/src/fortranobject.c -> build/src.macosx-10.9-x86_64-3.8/.\n",
      "copying /Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/f2py/src/fortranobject.h -> build/src.macosx-10.9-x86_64-3.8/.\n",
      "build_src: building npy-pkg config files\n",
      "customize UnixCCompiler\n",
      "customize UnixCCompiler using build_ext\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/setuptools/command/install.py:34: SetuptoolsDeprecationWarning: setup.py install is deprecated. Use build and pip and other standards-based tools.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-march=native)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "creating /var/folders/j1/f664b9hj1lz3vpy42qc9sw7h0000gp/T/tmpnyzel5b5/Users\n",
      "creating /var/folders/j1/f664b9hj1lz3vpy42qc9sw7h0000gp/T/tmpnyzel5b5/Users/bryandaniels\n",
      "creating /var/folders/j1/f664b9hj1lz3vpy42qc9sw7h0000gp/T/tmpnyzel5b5/Users/bryandaniels/anaconda3\n",
      "creating /var/folders/j1/f664b9hj1lz3vpy42qc9sw7h0000gp/T/tmpnyzel5b5/Users/bryandaniels/anaconda3/lib\n",
      "creating /var/folders/j1/f664b9hj1lz3vpy42qc9sw7h0000gp/T/tmpnyzel5b5/Users/bryandaniels/anaconda3/lib/python3.8\n",
      "creating /var/folders/j1/f664b9hj1lz3vpy42qc9sw7h0000gp/T/tmpnyzel5b5/Users/bryandaniels/anaconda3/lib/python3.8/site-packages\n",
      "creating /var/folders/j1/f664b9hj1lz3vpy42qc9sw7h0000gp/T/tmpnyzel5b5/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy\n",
      "creating /var/folders/j1/f664b9hj1lz3vpy42qc9sw7h0000gp/T/tmpnyzel5b5/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/distutils\n",
      "creating /var/folders/j1/f664b9hj1lz3vpy42qc9sw7h0000gp/T/tmpnyzel5b5/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/distutils/checks\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-march=native'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-O3)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-O3'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-Werror)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-Werror'\n",
      "CCompilerOpt.__init__[1701] : check requested baseline\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-msse)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-msse2)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse2'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'SSE' with flags (-msse -msse2)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -Werror'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'SSE2' with flags (-msse -msse2)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -Werror'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-msse3)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse3'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'SSE3' with flags (-msse -msse2 -msse3)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -Werror'\n",
      "CCompilerOpt.__init__[1710] : check requested dispatch-able features\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-mssse3)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-mssse3'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-msse4.1)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse4.1'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-mpopcnt)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-mpopcnt'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-msse4.2)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse4.2'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-mavx)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-mavx'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-mf16c)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-mf16c'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-mavx2)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-mavx2'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'AVX2' with flags (-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mavx2)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mavx2 -Werror'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-mfma)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-mfma'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-mavx512f)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-mavx512f'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'AVX512F' with flags (-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -Werror'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'FMA3' with flags (-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -Werror'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'POPCNT' with flags (-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -Werror'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'SSE42' with flags (-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -Werror'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'SSSE3' with flags (-msse -msse2 -msse3 -mssse3)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -Werror'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'SSE41' with flags (-msse -msse2 -msse3 -mssse3 -msse4.1)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -Werror'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'AVX' with flags (-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -Werror'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-mavx512cd)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-mavx512cd'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-mavx512er -mavx512pf)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-mavx512er -mavx512pf'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'AVX512_KNL' with flags (-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd -mavx512er -mavx512pf)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd -mavx512er -mavx512pf -Werror'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'AVX512CD' with flags (-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd -Werror'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'F16C' with flags (-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -Werror'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-mavx5124fmaps -mavx5124vnniw -mavx512vpopcntdq)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-mavx5124fmaps -mavx5124vnniw -mavx512vpopcntdq'\n",
      "CCompilerOpt.dist_test[581] : CCompilerOpt._dist_test_spawn[716] : Command (gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include/python3.8 -c /Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/distutils/checks/test_flags.c -o /var/folders/j1/f664b9hj1lz3vpy42qc9sw7h0000gp/T/tmpnyzel5b5/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/distutils/checks/test_flags.o -MMD -MF /var/folders/j1/f664b9hj1lz3vpy42qc9sw7h0000gp/T/tmpnyzel5b5/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/distutils/checks/test_flags.o.d -mavx5124fmaps -mavx5124vnniw -mavx512vpopcntdq) failed with exit status 1 output -> \n",
      "clang: error: unknown argument: '-mavx5124fmaps'\n",
      "clang: error: unknown argument: '-mavx5124vnniw'\n",
      "\n",
      "CCompilerOpt.cc_test_flags[1017] : testing failed\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'AVX512_KNM' with flags (-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd -mavx512er -mavx512pf)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd -mavx512er -mavx512pf -Werror'\n",
      "CCompilerOpt.dist_test[581] : CCompilerOpt._dist_test_spawn[716] : Command (gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include/python3.8 -c /Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/distutils/checks/cpu_avx512_knm.c -o /var/folders/j1/f664b9hj1lz3vpy42qc9sw7h0000gp/T/tmpnyzel5b5/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/distutils/checks/cpu_avx512_knm.o -MMD -MF /var/folders/j1/f664b9hj1lz3vpy42qc9sw7h0000gp/T/tmpnyzel5b5/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/distutils/checks/cpu_avx512_knm.o.d -msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd -mavx512er -mavx512pf -Werror) failed with exit status 1 output -> \n",
      "/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/distutils/checks/cpu_avx512_knm.c:22:9: error: implicit declaration of function '_mm512_4fmadd_ps' is invalid in C99 [-Werror,-Wimplicit-function-declaration]\n",
      "    b = _mm512_4fmadd_ps(b, b, b, b, b, NULL);\n",
      "        ^\n",
      "/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/distutils/checks/cpu_avx512_knm.c:22:9: note: did you mean '_mm512_fmadd_ps'?\n",
      "/Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/lib/clang/13.0.0/include/avx512fintrin.h:2716:1: note: '_mm512_fmadd_ps' declared here\n",
      "_mm512_fmadd_ps(__m512 __A, __m512 __B, __m512 __C)\n",
      "^\n",
      "/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/distutils/checks/cpu_avx512_knm.c:22:7: error: assigning to '__m512' (vector of 16 'float' values) from incompatible type 'int'\n",
      "    b = _mm512_4fmadd_ps(b, b, b, b, b, NULL);\n",
      "      ^ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
      "/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/distutils/checks/cpu_avx512_knm.c:24:9: error: implicit declaration of function '_mm512_4dpwssd_epi32' is invalid in C99 [-Werror,-Wimplicit-function-declaration]\n",
      "    a = _mm512_4dpwssd_epi32(a, a, a, a, a, NULL);\n",
      "        ^\n",
      "/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/distutils/checks/cpu_avx512_knm.c:24:9: note: did you mean '_mm512_dpwssd_epi32'?\n",
      "/Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/lib/clang/13.0.0/include/avx512vnniintrin.h:68:1: note: '_mm512_dpwssd_epi32' declared here\n",
      "_mm512_dpwssd_epi32(__m512i __S, __m512i __A, __m512i __B)\n",
      "^\n",
      "/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/distutils/checks/cpu_avx512_knm.c:24:7: error: assigning to '__m512i' (vector of 8 'long long' values) from incompatible type 'int'\n",
      "    a = _mm512_4dpwssd_epi32(a, a, a, a, a, NULL);\n",
      "      ^ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
      "4 errors generated.\n",
      "\n",
      "CCompilerOpt.feature_test[1482] : testing failed\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-mavx512vl -mavx512bw -mavx512dq)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-mavx512vl -mavx512bw -mavx512dq'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'AVX512_SKX' with flags (-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -Werror'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-mavx512ifma -mavx512vbmi)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-mavx512ifma -mavx512vbmi'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'AVX512_CNL' with flags (-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi -Werror'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-mavx512vnni)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-mavx512vnni'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'AVX512_CLX' with flags (-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512vnni)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512vnni -Werror'\n",
      "CCompilerOpt.cc_test_flags[1013] : testing flags (-mavx512vbmi2 -mavx512bitalg -mavx512vpopcntdq)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-mavx512vbmi2 -mavx512bitalg -mavx512vpopcntdq'\n",
      "CCompilerOpt.feature_test[1466] : testing feature 'AVX512_ICL' with flags (-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512vnni -mavx512ifma -mavx512vbmi -mavx512vbmi2 -mavx512bitalg -mavx512vpopcntdq)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512vnni -mavx512ifma -mavx512vbmi -mavx512vbmi2 -mavx512bitalg -mavx512vpopcntdq -Werror'\n",
      "CCompilerOpt.__init__[1722] : skip features (SSE3 SSE SSE2) since its part of baseline\n",
      "CCompilerOpt.__init__[1726] : initialize targets groups\n",
      "CCompilerOpt.__init__[1728] : parse target group simd_test\n",
      "CCompilerOpt._parse_target_tokens[1939] : skip targets (VSX3 XOP NEON VSX FMA4 VSX2 ASIMD) not part of baseline or dispatch-able features\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CCompilerOpt._parse_policy_not_keepbase[2051] : skip baseline features (SSE2)\n",
      "CCompilerOpt.generate_dispatch_header[2272] : generate CPU dispatch header: (build/src.macosx-10.9-x86_64-3.8/numpy/distutils/include/npy_cpu_dispatch_config.h)\n",
      "CCompilerOpt.generate_dispatch_header[2281] : dispatch header dir build/src.macosx-10.9-x86_64-3.8/numpy/distutils/include does not exist, creating it\n",
      "CCompilerOpt.feature_extra_checks[1546] : Testing extra checks for feature 'AVX512F' (AVX512F_REDUCE)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -Werror'\n",
      "CCompilerOpt.feature_extra_checks[1546] : Testing extra checks for feature 'AVX512_SKX' (AVX512BW_MASK AVX512DQ_MASK)\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -Werror'\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -Werror'\n",
      "building 'CTSN_0_SFI_C02TJ318GTFL_759068_7266515561_16872' extension\n",
      "compiling C sources\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "creating build/temp.macosx-10.9-x86_64-3.8/Users\n",
      "creating build/temp.macosx-10.9-x86_64-3.8/Users/bryandaniels\n",
      "creating build/temp.macosx-10.9-x86_64-3.8/Users/bryandaniels/Desktop\n",
      "creating build/temp.macosx-10.9-x86_64-3.8/Users/bryandaniels/Desktop/SloppyCell\n",
      "creating build/temp.macosx-10.9-x86_64-3.8/Users/bryandaniels/Desktop/SloppyCell/SloppyCell\n",
      "creating build/temp.macosx-10.9-x86_64-3.8/Users/bryandaniels/Desktop/SloppyCell/SloppyCell/ReactionNetworks\n",
      "creating build/temp.macosx-10.9-x86_64-3.8/build\n",
      "creating build/temp.macosx-10.9-x86_64-3.8/build/src.macosx-10.9-x86_64-3.8\n",
      "compile options: '-I/Users/bryandaniels/Desktop/SloppyCell/SloppyCell/ReactionNetworks -Ibuild/src.macosx-10.9-x86_64-3.8/. -I/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/core/include -Ibuild/src.macosx-10.9-x86_64-3.8/numpy/distutils/include -I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3'\n",
      "gcc: CTSN_0_SFI_C02TJ318GTFL_759068_7266515561_16872.cgcc: CTSN_0_SFI_C02TJ318GTFL_759068_7266515561_16872module.cgcc: build/src.macosx-10.9-x86_64-3.8/./fortranobject.c\n",
      "\n",
      "\n",
      "gcc: /Users/bryandaniels/Desktop/SloppyCell/SloppyCell/ReactionNetworks/mtrand.c\n",
      "gcc -bundle -undefined dynamic_lookup -L/Users/bryandaniels/anaconda3/lib -arch x86_64 -L/Users/bryandaniels/anaconda3/lib -arch x86_64 build/temp.macosx-10.9-x86_64-3.8/CTSN_0_SFI_C02TJ318GTFL_759068_7266515561_16872.o build/temp.macosx-10.9-x86_64-3.8/CTSN_0_SFI_C02TJ318GTFL_759068_7266515561_16872module.o build/temp.macosx-10.9-x86_64-3.8/Users/bryandaniels/Desktop/SloppyCell/SloppyCell/ReactionNetworks/mtrand.o build/temp.macosx-10.9-x86_64-3.8/build/src.macosx-10.9-x86_64-3.8/fortranobject.o -o CTSN_0_SFI_C02TJ318GTFL_759068_7266515561_16872.cpython-38-darwin.so\n",
      "running build_ext\n",
      "running build_src\n",
      "build_src\n",
      "building extension \"CTSN_0_SFI_C02TJ318GTFL_365309_7366515561_16872\" sources\n",
      "f2py options: []\n",
      "f2py: CTSN_0_SFI_C02TJ318GTFL_365309_7366515561_16872.pyf\n",
      "Reading fortran codes...\n",
      "\tReading file 'CTSN_0_SFI_C02TJ318GTFL_365309_7366515561_16872.pyf' (format:free)\n",
      "Post-processing...\n",
      "\tBlock: CTSN_0_SFI_C02TJ318GTFL_365309_7366515561_16872\n",
      "\t\t\tBlock: res_function\n",
      "\t\t\tBlock: ddaskr_jac\n",
      "\t\t\tBlock: root_func\n",
      "\t\t\tBlock: alg_deriv_func\n",
      "\t\t\tBlock: alg_res_func\n",
      "\t\t\tBlock: dres_dc_function\n",
      "\t\t\tBlock: dres_dcdot_function\n",
      "\t\t\tBlock: dres_dwself_1\n",
      "\t\t\tBlock: dres_dtheta_1\n",
      "\t\t\tBlock: dres_dlog_tau_1\n",
      "\t\t\tBlock: dres_dw_1_0\n",
      "\t\t\tBlock: dres_dw_1_2\n",
      "\t\t\tBlock: dres_dX_2_init\n",
      "\t\t\tBlock: sens_rhs\n",
      "\t\t\tBlock: res_function_logdv\n",
      "\t\t\tBlock: root_func_logdv\n",
      "\t\t\tBlock: sens_rhs_logdv\n",
      "\t\t\tBlock: integrate_stochastic_tidbit\n",
      "Post-processing (stage 2)...\n",
      "Building modules...\n",
      "\tBuilding module \"CTSN_0_SFI_C02TJ318GTFL_365309_7366515561_16872\"...\n",
      "\t\tConstructing wrapper function \"res_function\"...\n",
      "\t\t  residual = res_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"ddaskr_jac\"...\n",
      "\t\t  pd = ddaskr_jac(t,y,yprime,cj,rpar)\n",
      "\t\tConstructing wrapper function \"root_func\"...\n",
      "\t\t  root_devs = root_func(t,y,yp,constants)\n",
      "\t\tConstructing wrapper function \"alg_deriv_func\"...\n",
      "\t\t  alg_derivs_res = alg_deriv_func(alg_yp,dynamicVars,yp,time,constants)\n",
      "\t\tConstructing wrapper function \"alg_res_func\"...\n",
      "\t\t  residual = alg_res_func(alg_vals,dynamicVars,time,constants)\n",
      "\t\tConstructing wrapper function \"dres_dc_function\"...\n",
      "\t\t  pd = dres_dc_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dcdot_function\"...\n",
      "\t\t  pd = dres_dcdot_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_1\"...\n",
      "\t\t  pd = dres_dwself_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dtheta_1\"...\n",
      "\t\t  pd = dres_dtheta_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_1\"...\n",
      "\t\t  pd = dres_dlog_tau_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_0\"...\n",
      "\t\t  pd = dres_dw_1_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_2\"...\n",
      "\t\t  pd = dres_dw_1_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_2_init\"...\n",
      "\t\t  pd = dres_dX_2_init(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs\"...\n",
      "\t\t  sens_res = sens_rhs(time,sens_y,sens_yp,constants)\n",
      "\t\tConstructing wrapper function \"res_function_logdv\"...\n",
      "\t\t  residual = res_function_logdv(time,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"root_func_logdv\"...\n",
      "\t\t  root_devs = root_func_logdv(t,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs_logdv\"...\n",
      "\t\t  sens_res = sens_rhs_logdv(time,sens_y_log,sens_yp_log,constants)\n",
      "\t\tConstructing wrapper function \"integrate_stochastic_tidbit\"...\n",
      "\t\t  time_ptr,dv,stop_time_ptr,trajectory = integrate_stochastic_tidbit(seed_ptr,reseed,time_ptr,dv,cv,rmsd_ptr,stop_time_ptr)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\tWrote C/API module \"CTSN_0_SFI_C02TJ318GTFL_365309_7366515561_16872\" to file \"./CTSN_0_SFI_C02TJ318GTFL_365309_7366515561_16872module.c\"\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/./fortranobject.c' to sources.\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/.' to include_dirs.\n",
      "build_src: building npy-pkg config files\n",
      "customize UnixCCompiler\n",
      "customize UnixCCompiler using build_ext\n",
      "CCompilerOpt.__init__[786] : hit the memory cache\n",
      "CCompilerOpt.generate_dispatch_header[2272] : generate CPU dispatch header: (build/src.macosx-10.9-x86_64-3.8/numpy/distutils/include/npy_cpu_dispatch_config.h)\n",
      "building 'CTSN_0_SFI_C02TJ318GTFL_365309_7366515561_16872' extension\n",
      "compiling C sources\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/Desktop/SloppyCell/SloppyCell/ReactionNetworks -Ibuild/src.macosx-10.9-x86_64-3.8/. -I/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/core/include -Ibuild/src.macosx-10.9-x86_64-3.8/numpy/distutils/include -I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3'\n",
      "gcc: CTSN_0_SFI_C02TJ318GTFL_365309_7366515561_16872.cgcc: CTSN_0_SFI_C02TJ318GTFL_365309_7366515561_16872module.c\n",
      "\n",
      "gcc -bundle -undefined dynamic_lookup -L/Users/bryandaniels/anaconda3/lib -arch x86_64 -L/Users/bryandaniels/anaconda3/lib -arch x86_64 build/temp.macosx-10.9-x86_64-3.8/CTSN_0_SFI_C02TJ318GTFL_365309_7366515561_16872.o build/temp.macosx-10.9-x86_64-3.8/CTSN_0_SFI_C02TJ318GTFL_365309_7366515561_16872module.o build/temp.macosx-10.9-x86_64-3.8/Users/bryandaniels/Desktop/SloppyCell/SloppyCell/ReactionNetworks/mtrand.o build/temp.macosx-10.9-x86_64-3.8/build/src.macosx-10.9-x86_64-3.8/fortranobject.o -o CTSN_0_SFI_C02TJ318GTFL_365309_7366515561_16872.cpython-38-darwin.so\n",
      "running build_ext\n",
      "running build_src\n",
      "build_src\n",
      "building extension \"CTSN_0_SFI_C02TJ318GTFL_719392_9366515561_16872\" sources\n",
      "f2py options: []\n",
      "f2py: CTSN_0_SFI_C02TJ318GTFL_719392_9366515561_16872.pyf\n",
      "Reading fortran codes...\n",
      "\tReading file 'CTSN_0_SFI_C02TJ318GTFL_719392_9366515561_16872.pyf' (format:free)\n",
      "Post-processing...\n",
      "\tBlock: CTSN_0_SFI_C02TJ318GTFL_719392_9366515561_16872\n",
      "\t\t\tBlock: res_function\n",
      "\t\t\tBlock: ddaskr_jac\n",
      "\t\t\tBlock: root_func\n",
      "\t\t\tBlock: alg_deriv_func\n",
      "\t\t\tBlock: alg_res_func\n",
      "\t\t\tBlock: dres_dc_function\n",
      "\t\t\tBlock: dres_dcdot_function\n",
      "\t\t\tBlock: dres_dwself_1\n",
      "\t\t\tBlock: dres_dtheta_1\n",
      "\t\t\tBlock: dres_dlog_tau_1\n",
      "\t\t\tBlock: dres_dw_1_0\n",
      "\t\t\tBlock: dres_dw_1_2\n",
      "\t\t\tBlock: dres_dw_2_1\n",
      "\t\t\tBlock: dres_dw_2_0\n",
      "\t\t\tBlock: dres_dX_2_init\n",
      "\t\t\tBlock: sens_rhs\n",
      "\t\t\tBlock: res_function_logdv\n",
      "\t\t\tBlock: root_func_logdv\n",
      "\t\t\tBlock: sens_rhs_logdv\n",
      "\t\t\tBlock: integrate_stochastic_tidbit\n",
      "Post-processing (stage 2)...\n",
      "Building modules...\n",
      "\tBuilding module \"CTSN_0_SFI_C02TJ318GTFL_719392_9366515561_16872\"...\n",
      "\t\tConstructing wrapper function \"res_function\"...\n",
      "\t\t  residual = res_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"ddaskr_jac\"...\n",
      "\t\t  pd = ddaskr_jac(t,y,yprime,cj,rpar)\n",
      "\t\tConstructing wrapper function \"root_func\"...\n",
      "\t\t  root_devs = root_func(t,y,yp,constants)\n",
      "\t\tConstructing wrapper function \"alg_deriv_func\"...\n",
      "\t\t  alg_derivs_res = alg_deriv_func(alg_yp,dynamicVars,yp,time,constants)\n",
      "\t\tConstructing wrapper function \"alg_res_func\"...\n",
      "\t\t  residual = alg_res_func(alg_vals,dynamicVars,time,constants)\n",
      "\t\tConstructing wrapper function \"dres_dc_function\"...\n",
      "\t\t  pd = dres_dc_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dcdot_function\"...\n",
      "\t\t  pd = dres_dcdot_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_1\"...\n",
      "\t\t  pd = dres_dwself_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dtheta_1\"...\n",
      "\t\t  pd = dres_dtheta_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_1\"...\n",
      "\t\t  pd = dres_dlog_tau_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_0\"...\n",
      "\t\t  pd = dres_dw_1_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_2\"...\n",
      "\t\t  pd = dres_dw_1_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_1\"...\n",
      "\t\t  pd = dres_dw_2_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_0\"...\n",
      "\t\t  pd = dres_dw_2_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_2_init\"...\n",
      "\t\t  pd = dres_dX_2_init(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs\"...\n",
      "\t\t  sens_res = sens_rhs(time,sens_y,sens_yp,constants)\n",
      "\t\tConstructing wrapper function \"res_function_logdv\"...\n",
      "\t\t  residual = res_function_logdv(time,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"root_func_logdv\"...\n",
      "\t\t  root_devs = root_func_logdv(t,log_dv,log_yp,constants)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\t\tConstructing wrapper function \"sens_rhs_logdv\"...\n",
      "\t\t  sens_res = sens_rhs_logdv(time,sens_y_log,sens_yp_log,constants)\n",
      "\t\tConstructing wrapper function \"integrate_stochastic_tidbit\"...\n",
      "\t\t  time_ptr,dv,stop_time_ptr,trajectory = integrate_stochastic_tidbit(seed_ptr,reseed,time_ptr,dv,cv,rmsd_ptr,stop_time_ptr)\n",
      "\tWrote C/API module \"CTSN_0_SFI_C02TJ318GTFL_719392_9366515561_16872\" to file \"./CTSN_0_SFI_C02TJ318GTFL_719392_9366515561_16872module.c\"\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/./fortranobject.c' to sources.\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/.' to include_dirs.\n",
      "build_src: building npy-pkg config files\n",
      "customize UnixCCompiler\n",
      "customize UnixCCompiler using build_ext\n",
      "CCompilerOpt.__init__[786] : hit the memory cache\n",
      "CCompilerOpt.generate_dispatch_header[2272] : generate CPU dispatch header: (build/src.macosx-10.9-x86_64-3.8/numpy/distutils/include/npy_cpu_dispatch_config.h)\n",
      "building 'CTSN_0_SFI_C02TJ318GTFL_719392_9366515561_16872' extension\n",
      "compiling C sources\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/Desktop/SloppyCell/SloppyCell/ReactionNetworks -Ibuild/src.macosx-10.9-x86_64-3.8/. -I/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/core/include -Ibuild/src.macosx-10.9-x86_64-3.8/numpy/distutils/include -I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3'\n",
      "gcc: CTSN_0_SFI_C02TJ318GTFL_719392_9366515561_16872.cgcc: CTSN_0_SFI_C02TJ318GTFL_719392_9366515561_16872module.c\n",
      "\n",
      "gcc -bundle -undefined dynamic_lookup -L/Users/bryandaniels/anaconda3/lib -arch x86_64 -L/Users/bryandaniels/anaconda3/lib -arch x86_64 build/temp.macosx-10.9-x86_64-3.8/CTSN_0_SFI_C02TJ318GTFL_719392_9366515561_16872.o build/temp.macosx-10.9-x86_64-3.8/CTSN_0_SFI_C02TJ318GTFL_719392_9366515561_16872module.o build/temp.macosx-10.9-x86_64-3.8/Users/bryandaniels/Desktop/SloppyCell/SloppyCell/ReactionNetworks/mtrand.o build/temp.macosx-10.9-x86_64-3.8/build/src.macosx-10.9-x86_64-3.8/fortranobject.o -o CTSN_0_SFI_C02TJ318GTFL_719392_9366515561_16872.cpython-38-darwin.so\n",
      "running build_ext\n",
      "running build_src\n",
      "build_src\n",
      "building extension \"CTSN_0_SFI_C02TJ318GTFL_821676_0466515561_16872\" sources\n",
      "f2py options: []\n",
      "f2py: CTSN_0_SFI_C02TJ318GTFL_821676_0466515561_16872.pyf\n",
      "Reading fortran codes...\n",
      "\tReading file 'CTSN_0_SFI_C02TJ318GTFL_821676_0466515561_16872.pyf' (format:free)\n",
      "Post-processing...\n",
      "\tBlock: CTSN_0_SFI_C02TJ318GTFL_821676_0466515561_16872\n",
      "\t\t\tBlock: res_function\n",
      "\t\t\tBlock: ddaskr_jac\n",
      "\t\t\tBlock: root_func\n",
      "\t\t\tBlock: alg_deriv_func\n",
      "\t\t\tBlock: alg_res_func\n",
      "\t\t\tBlock: dres_dc_function\n",
      "\t\t\tBlock: dres_dcdot_function\n",
      "\t\t\tBlock: dres_dwself_1\n",
      "\t\t\tBlock: dres_dtheta_1\n",
      "\t\t\tBlock: dres_dlog_tau_1\n",
      "\t\t\tBlock: dres_dw_1_0\n",
      "\t\t\tBlock: dres_dw_1_2\n",
      "\t\t\tBlock: dres_dwself_2\n",
      "\t\t\tBlock: dres_dlog_tau_2\n",
      "\t\t\tBlock: dres_dw_2_1\n",
      "\t\t\tBlock: dres_dw_2_0\n",
      "\t\t\tBlock: dres_dX_2_init\n",
      "\t\t\tBlock: sens_rhs\n",
      "\t\t\tBlock: res_function_logdv\n",
      "\t\t\tBlock: root_func_logdv\n",
      "\t\t\tBlock: sens_rhs_logdv\n",
      "\t\t\tBlock: integrate_stochastic_tidbit\n",
      "Post-processing (stage 2)...\n",
      "Building modules...\n",
      "\tBuilding module \"CTSN_0_SFI_C02TJ318GTFL_821676_0466515561_16872\"...\n",
      "\t\tConstructing wrapper function \"res_function\"...\n",
      "\t\t  residual = res_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"ddaskr_jac\"...\n",
      "\t\t  pd = ddaskr_jac(t,y,yprime,cj,rpar)\n",
      "\t\tConstructing wrapper function \"root_func\"...\n",
      "\t\t  root_devs = root_func(t,y,yp,constants)\n",
      "\t\tConstructing wrapper function \"alg_deriv_func\"...\n",
      "\t\t  alg_derivs_res = alg_deriv_func(alg_yp,dynamicVars,yp,time,constants)\n",
      "\t\tConstructing wrapper function \"alg_res_func\"...\n",
      "\t\t  residual = alg_res_func(alg_vals,dynamicVars,time,constants)\n",
      "\t\tConstructing wrapper function \"dres_dc_function\"...\n",
      "\t\t  pd = dres_dc_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dcdot_function\"...\n",
      "\t\t  pd = dres_dcdot_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_1\"...\n",
      "\t\t  pd = dres_dwself_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dtheta_1\"...\n",
      "\t\t  pd = dres_dtheta_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_1\"...\n",
      "\t\t  pd = dres_dlog_tau_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_0\"...\n",
      "\t\t  pd = dres_dw_1_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_2\"...\n",
      "\t\t  pd = dres_dw_1_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_2\"...\n",
      "\t\t  pd = dres_dwself_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_2\"...\n",
      "\t\t  pd = dres_dlog_tau_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_1\"...\n",
      "\t\t  pd = dres_dw_2_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_0\"...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\t\t  pd = dres_dw_2_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_2_init\"...\n",
      "\t\t  pd = dres_dX_2_init(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs\"...\n",
      "\t\t  sens_res = sens_rhs(time,sens_y,sens_yp,constants)\n",
      "\t\tConstructing wrapper function \"res_function_logdv\"...\n",
      "\t\t  residual = res_function_logdv(time,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"root_func_logdv\"...\n",
      "\t\t  root_devs = root_func_logdv(t,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs_logdv\"...\n",
      "\t\t  sens_res = sens_rhs_logdv(time,sens_y_log,sens_yp_log,constants)\n",
      "\t\tConstructing wrapper function \"integrate_stochastic_tidbit\"...\n",
      "\t\t  time_ptr,dv,stop_time_ptr,trajectory = integrate_stochastic_tidbit(seed_ptr,reseed,time_ptr,dv,cv,rmsd_ptr,stop_time_ptr)\n",
      "\tWrote C/API module \"CTSN_0_SFI_C02TJ318GTFL_821676_0466515561_16872\" to file \"./CTSN_0_SFI_C02TJ318GTFL_821676_0466515561_16872module.c\"\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/./fortranobject.c' to sources.\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/.' to include_dirs.\n",
      "build_src: building npy-pkg config files\n",
      "customize UnixCCompiler\n",
      "customize UnixCCompiler using build_ext\n",
      "CCompilerOpt.__init__[786] : hit the memory cache\n",
      "CCompilerOpt.generate_dispatch_header[2272] : generate CPU dispatch header: (build/src.macosx-10.9-x86_64-3.8/numpy/distutils/include/npy_cpu_dispatch_config.h)\n",
      "building 'CTSN_0_SFI_C02TJ318GTFL_821676_0466515561_16872' extension\n",
      "compiling C sources\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/Desktop/SloppyCell/SloppyCell/ReactionNetworks -Ibuild/src.macosx-10.9-x86_64-3.8/. -I/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/core/include -Ibuild/src.macosx-10.9-x86_64-3.8/numpy/distutils/include -I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3'\n",
      "gcc: CTSN_0_SFI_C02TJ318GTFL_821676_0466515561_16872.cgcc: CTSN_0_SFI_C02TJ318GTFL_821676_0466515561_16872module.c\n",
      "\n",
      "gcc -bundle -undefined dynamic_lookup -L/Users/bryandaniels/anaconda3/lib -arch x86_64 -L/Users/bryandaniels/anaconda3/lib -arch x86_64 build/temp.macosx-10.9-x86_64-3.8/CTSN_0_SFI_C02TJ318GTFL_821676_0466515561_16872.o build/temp.macosx-10.9-x86_64-3.8/CTSN_0_SFI_C02TJ318GTFL_821676_0466515561_16872module.o build/temp.macosx-10.9-x86_64-3.8/Users/bryandaniels/Desktop/SloppyCell/SloppyCell/ReactionNetworks/mtrand.o build/temp.macosx-10.9-x86_64-3.8/build/src.macosx-10.9-x86_64-3.8/fortranobject.o -o CTSN_0_SFI_C02TJ318GTFL_821676_0466515561_16872.cpython-38-darwin.so\n",
      "running build_ext\n",
      "running build_src\n",
      "build_src\n",
      "building extension \"CTSN_0_SFI_C02TJ318GTFL_276341_2466515561_16872\" sources\n",
      "f2py options: []\n",
      "f2py: CTSN_0_SFI_C02TJ318GTFL_276341_2466515561_16872.pyf\n",
      "Reading fortran codes...\n",
      "\tReading file 'CTSN_0_SFI_C02TJ318GTFL_276341_2466515561_16872.pyf' (format:free)\n",
      "Post-processing...\n",
      "\tBlock: CTSN_0_SFI_C02TJ318GTFL_276341_2466515561_16872\n",
      "\t\t\tBlock: res_function\n",
      "\t\t\tBlock: ddaskr_jac\n",
      "\t\t\tBlock: root_func\n",
      "\t\t\tBlock: alg_deriv_func\n",
      "\t\t\tBlock: alg_res_func\n",
      "\t\t\tBlock: dres_dc_function\n",
      "\t\t\tBlock: dres_dcdot_function\n",
      "\t\t\tBlock: dres_dwself_1\n",
      "\t\t\tBlock: dres_dtheta_1\n",
      "\t\t\tBlock: dres_dlog_tau_1\n",
      "\t\t\tBlock: dres_dw_1_0\n",
      "\t\t\tBlock: dres_dw_1_2\n",
      "\t\t\tBlock: dres_dw_1_3\n",
      "\t\t\tBlock: dres_dwself_2\n",
      "\t\t\tBlock: dres_dtheta_2\n",
      "\t\t\tBlock: dres_dlog_tau_2\n",
      "\t\t\tBlock: dres_dw_2_1\n",
      "\t\t\tBlock: dres_dw_2_0\n",
      "\t\t\tBlock: dres_dX_2_init\n",
      "\t\t\tBlock: dres_dX_3_init\n",
      "\t\t\tBlock: sens_rhs\n",
      "\t\t\tBlock: res_function_logdv\n",
      "\t\t\tBlock: root_func_logdv\n",
      "\t\t\tBlock: sens_rhs_logdv\n",
      "\t\t\tBlock: integrate_stochastic_tidbit\n",
      "Post-processing (stage 2)...\n",
      "Building modules...\n",
      "\tBuilding module \"CTSN_0_SFI_C02TJ318GTFL_276341_2466515561_16872\"...\n",
      "\t\tConstructing wrapper function \"res_function\"...\n",
      "\t\t  residual = res_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"ddaskr_jac\"...\n",
      "\t\t  pd = ddaskr_jac(t,y,yprime,cj,rpar)\n",
      "\t\tConstructing wrapper function \"root_func\"...\n",
      "\t\t  root_devs = root_func(t,y,yp,constants)\n",
      "\t\tConstructing wrapper function \"alg_deriv_func\"...\n",
      "\t\t  alg_derivs_res = alg_deriv_func(alg_yp,dynamicVars,yp,time,constants)\n",
      "\t\tConstructing wrapper function \"alg_res_func\"...\n",
      "\t\t  residual = alg_res_func(alg_vals,dynamicVars,time,constants)\n",
      "\t\tConstructing wrapper function \"dres_dc_function\"...\n",
      "\t\t  pd = dres_dc_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dcdot_function\"...\n",
      "\t\t  pd = dres_dcdot_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_1\"...\n",
      "\t\t  pd = dres_dwself_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dtheta_1\"...\n",
      "\t\t  pd = dres_dtheta_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_1\"...\n",
      "\t\t  pd = dres_dlog_tau_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_0\"...\n",
      "\t\t  pd = dres_dw_1_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_2\"...\n",
      "\t\t  pd = dres_dw_1_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_3\"...\n",
      "\t\t  pd = dres_dw_1_3(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_2\"...\n",
      "\t\t  pd = dres_dwself_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dtheta_2\"...\n",
      "\t\t  pd = dres_dtheta_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_2\"...\n",
      "\t\t  pd = dres_dlog_tau_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_1\"...\n",
      "\t\t  pd = dres_dw_2_1(time,dynamicVars,yprime,constants)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\t\tConstructing wrapper function \"dres_dw_2_0\"...\n",
      "\t\t  pd = dres_dw_2_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_2_init\"...\n",
      "\t\t  pd = dres_dX_2_init(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_3_init\"...\n",
      "\t\t  pd = dres_dX_3_init(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs\"...\n",
      "\t\t  sens_res = sens_rhs(time,sens_y,sens_yp,constants)\n",
      "\t\tConstructing wrapper function \"res_function_logdv\"...\n",
      "\t\t  residual = res_function_logdv(time,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"root_func_logdv\"...\n",
      "\t\t  root_devs = root_func_logdv(t,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs_logdv\"...\n",
      "\t\t  sens_res = sens_rhs_logdv(time,sens_y_log,sens_yp_log,constants)\n",
      "\t\tConstructing wrapper function \"integrate_stochastic_tidbit\"...\n",
      "\t\t  time_ptr,dv,stop_time_ptr,trajectory = integrate_stochastic_tidbit(seed_ptr,reseed,time_ptr,dv,cv,rmsd_ptr,stop_time_ptr)\n",
      "\tWrote C/API module \"CTSN_0_SFI_C02TJ318GTFL_276341_2466515561_16872\" to file \"./CTSN_0_SFI_C02TJ318GTFL_276341_2466515561_16872module.c\"\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/./fortranobject.c' to sources.\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/.' to include_dirs.\n",
      "build_src: building npy-pkg config files\n",
      "customize UnixCCompiler\n",
      "customize UnixCCompiler using build_ext\n",
      "CCompilerOpt.__init__[786] : hit the memory cache\n",
      "CCompilerOpt.generate_dispatch_header[2272] : generate CPU dispatch header: (build/src.macosx-10.9-x86_64-3.8/numpy/distutils/include/npy_cpu_dispatch_config.h)\n",
      "building 'CTSN_0_SFI_C02TJ318GTFL_276341_2466515561_16872' extension\n",
      "compiling C sources\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/Desktop/SloppyCell/SloppyCell/ReactionNetworks -Ibuild/src.macosx-10.9-x86_64-3.8/. -I/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/core/include -Ibuild/src.macosx-10.9-x86_64-3.8/numpy/distutils/include -I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3'\n",
      "gcc: CTSN_0_SFI_C02TJ318GTFL_276341_2466515561_16872.cgcc: CTSN_0_SFI_C02TJ318GTFL_276341_2466515561_16872module.c\n",
      "\n",
      "gcc -bundle -undefined dynamic_lookup -L/Users/bryandaniels/anaconda3/lib -arch x86_64 -L/Users/bryandaniels/anaconda3/lib -arch x86_64 build/temp.macosx-10.9-x86_64-3.8/CTSN_0_SFI_C02TJ318GTFL_276341_2466515561_16872.o build/temp.macosx-10.9-x86_64-3.8/CTSN_0_SFI_C02TJ318GTFL_276341_2466515561_16872module.o build/temp.macosx-10.9-x86_64-3.8/Users/bryandaniels/Desktop/SloppyCell/SloppyCell/ReactionNetworks/mtrand.o build/temp.macosx-10.9-x86_64-3.8/build/src.macosx-10.9-x86_64-3.8/fortranobject.o -o CTSN_0_SFI_C02TJ318GTFL_276341_2466515561_16872.cpython-38-darwin.so\n",
      "running build_ext\n",
      "running build_src\n",
      "build_src\n",
      "building extension \"CTSN_0_SFI_C02TJ318GTFL_1896657_3466515561_16872\" sources\n",
      "f2py options: []\n",
      "f2py: CTSN_0_SFI_C02TJ318GTFL_1896657_3466515561_16872.pyf\n",
      "Reading fortran codes...\n",
      "\tReading file 'CTSN_0_SFI_C02TJ318GTFL_1896657_3466515561_16872.pyf' (format:free)\n",
      "Post-processing...\n",
      "\tBlock: CTSN_0_SFI_C02TJ318GTFL_1896657_3466515561_16872\n",
      "\t\t\tBlock: res_function\n",
      "\t\t\tBlock: ddaskr_jac\n",
      "\t\t\tBlock: root_func\n",
      "\t\t\tBlock: alg_deriv_func\n",
      "\t\t\tBlock: alg_res_func\n",
      "\t\t\tBlock: dres_dc_function\n",
      "\t\t\tBlock: dres_dcdot_function\n",
      "\t\t\tBlock: dres_dwself_1\n",
      "\t\t\tBlock: dres_dtheta_1\n",
      "\t\t\tBlock: dres_dlog_tau_1\n",
      "\t\t\tBlock: dres_dw_1_0\n",
      "\t\t\tBlock: dres_dw_1_2\n",
      "\t\t\tBlock: dres_dw_1_3\n",
      "\t\t\tBlock: dres_dwself_2\n",
      "\t\t\tBlock: dres_dtheta_2\n",
      "\t\t\tBlock: dres_dlog_tau_2\n",
      "\t\t\tBlock: dres_dw_2_1\n",
      "\t\t\tBlock: dres_dw_2_0\n",
      "\t\t\tBlock: dres_dX_2_init\n",
      "\t\t\tBlock: dres_dw_3_1\n",
      "\t\t\tBlock: dres_dw_3_0\n",
      "\t\t\tBlock: dres_dX_3_init\n",
      "\t\t\tBlock: sens_rhs\n",
      "\t\t\tBlock: res_function_logdv\n",
      "\t\t\tBlock: root_func_logdv\n",
      "\t\t\tBlock: sens_rhs_logdv\n",
      "\t\t\tBlock: integrate_stochastic_tidbit\n",
      "Post-processing (stage 2)...\n",
      "Building modules...\n",
      "\tBuilding module \"CTSN_0_SFI_C02TJ318GTFL_1896657_3466515561_16872\"...\n",
      "\t\tConstructing wrapper function \"res_function\"...\n",
      "\t\t  residual = res_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"ddaskr_jac\"...\n",
      "\t\t  pd = ddaskr_jac(t,y,yprime,cj,rpar)\n",
      "\t\tConstructing wrapper function \"root_func\"...\n",
      "\t\t  root_devs = root_func(t,y,yp,constants)\n",
      "\t\tConstructing wrapper function \"alg_deriv_func\"...\n",
      "\t\t  alg_derivs_res = alg_deriv_func(alg_yp,dynamicVars,yp,time,constants)\n",
      "\t\tConstructing wrapper function \"alg_res_func\"...\n",
      "\t\t  residual = alg_res_func(alg_vals,dynamicVars,time,constants)\n",
      "\t\tConstructing wrapper function \"dres_dc_function\"...\n",
      "\t\t  pd = dres_dc_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dcdot_function\"...\n",
      "\t\t  pd = dres_dcdot_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_1\"...\n",
      "\t\t  pd = dres_dwself_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dtheta_1\"...\n",
      "\t\t  pd = dres_dtheta_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_1\"...\n",
      "\t\t  pd = dres_dlog_tau_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_0\"...\n",
      "\t\t  pd = dres_dw_1_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_2\"...\n",
      "\t\t  pd = dres_dw_1_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_3\"...\n",
      "\t\t  pd = dres_dw_1_3(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_2\"...\n",
      "\t\t  pd = dres_dwself_2(time,dynamicVars,yprime,constants)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\t\tConstructing wrapper function \"dres_dtheta_2\"...\n",
      "\t\t  pd = dres_dtheta_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_2\"...\n",
      "\t\t  pd = dres_dlog_tau_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_1\"...\n",
      "\t\t  pd = dres_dw_2_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_0\"...\n",
      "\t\t  pd = dres_dw_2_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_2_init\"...\n",
      "\t\t  pd = dres_dX_2_init(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_3_1\"...\n",
      "\t\t  pd = dres_dw_3_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_3_0\"...\n",
      "\t\t  pd = dres_dw_3_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_3_init\"...\n",
      "\t\t  pd = dres_dX_3_init(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs\"...\n",
      "\t\t  sens_res = sens_rhs(time,sens_y,sens_yp,constants)\n",
      "\t\tConstructing wrapper function \"res_function_logdv\"...\n",
      "\t\t  residual = res_function_logdv(time,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"root_func_logdv\"...\n",
      "\t\t  root_devs = root_func_logdv(t,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs_logdv\"...\n",
      "\t\t  sens_res = sens_rhs_logdv(time,sens_y_log,sens_yp_log,constants)\n",
      "\t\tConstructing wrapper function \"integrate_stochastic_tidbit\"...\n",
      "\t\t  time_ptr,dv,stop_time_ptr,trajectory = integrate_stochastic_tidbit(seed_ptr,reseed,time_ptr,dv,cv,rmsd_ptr,stop_time_ptr)\n",
      "\tWrote C/API module \"CTSN_0_SFI_C02TJ318GTFL_1896657_3466515561_16872\" to file \"./CTSN_0_SFI_C02TJ318GTFL_1896657_3466515561_16872module.c\"\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/./fortranobject.c' to sources.\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/.' to include_dirs.\n",
      "build_src: building npy-pkg config files\n",
      "customize UnixCCompiler\n",
      "customize UnixCCompiler using build_ext\n",
      "CCompilerOpt.__init__[786] : hit the memory cache\n",
      "CCompilerOpt.generate_dispatch_header[2272] : generate CPU dispatch header: (build/src.macosx-10.9-x86_64-3.8/numpy/distutils/include/npy_cpu_dispatch_config.h)\n",
      "building 'CTSN_0_SFI_C02TJ318GTFL_1896657_3466515561_16872' extension\n",
      "compiling C sources\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/Desktop/SloppyCell/SloppyCell/ReactionNetworks -Ibuild/src.macosx-10.9-x86_64-3.8/. -I/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/core/include -Ibuild/src.macosx-10.9-x86_64-3.8/numpy/distutils/include -I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3'\n",
      "gcc: CTSN_0_SFI_C02TJ318GTFL_1896657_3466515561_16872.cgcc: CTSN_0_SFI_C02TJ318GTFL_1896657_3466515561_16872module.c\n",
      "\n",
      "gcc -bundle -undefined dynamic_lookup -L/Users/bryandaniels/anaconda3/lib -arch x86_64 -L/Users/bryandaniels/anaconda3/lib -arch x86_64 build/temp.macosx-10.9-x86_64-3.8/CTSN_0_SFI_C02TJ318GTFL_1896657_3466515561_16872.o build/temp.macosx-10.9-x86_64-3.8/CTSN_0_SFI_C02TJ318GTFL_1896657_3466515561_16872module.o build/temp.macosx-10.9-x86_64-3.8/Users/bryandaniels/Desktop/SloppyCell/SloppyCell/ReactionNetworks/mtrand.o build/temp.macosx-10.9-x86_64-3.8/build/src.macosx-10.9-x86_64-3.8/fortranobject.o -o CTSN_0_SFI_C02TJ318GTFL_1896657_3466515561_16872.cpython-38-darwin.so\n",
      "running build_ext\n",
      "running build_src\n",
      "build_src\n",
      "building extension \"CTSN_0_SFI_C02TJ318GTFL_319793_5466515561_16872\" sources\n",
      "f2py options: []\n",
      "f2py: CTSN_0_SFI_C02TJ318GTFL_319793_5466515561_16872.pyf\n",
      "Reading fortran codes...\n",
      "\tReading file 'CTSN_0_SFI_C02TJ318GTFL_319793_5466515561_16872.pyf' (format:free)\n",
      "Post-processing...\n",
      "\tBlock: CTSN_0_SFI_C02TJ318GTFL_319793_5466515561_16872\n",
      "\t\t\tBlock: res_function\n",
      "\t\t\tBlock: ddaskr_jac\n",
      "\t\t\tBlock: root_func\n",
      "\t\t\tBlock: alg_deriv_func\n",
      "\t\t\tBlock: alg_res_func\n",
      "\t\t\tBlock: dres_dc_function\n",
      "\t\t\tBlock: dres_dcdot_function\n",
      "\t\t\tBlock: dres_dwself_1\n",
      "\t\t\tBlock: dres_dtheta_1\n",
      "\t\t\tBlock: dres_dlog_tau_1\n",
      "\t\t\tBlock: dres_dw_1_0\n",
      "\t\t\tBlock: dres_dw_1_2\n",
      "\t\t\tBlock: dres_dw_1_3\n",
      "\t\t\tBlock: dres_dwself_2\n",
      "\t\t\tBlock: dres_dtheta_2\n",
      "\t\t\tBlock: dres_dlog_tau_2\n",
      "\t\t\tBlock: dres_dw_2_1\n",
      "\t\t\tBlock: dres_dw_2_0\n",
      "\t\t\tBlock: dres_dw_2_3\n",
      "\t\t\tBlock: dres_dX_2_init\n",
      "\t\t\tBlock: dres_dw_3_1\n",
      "\t\t\tBlock: dres_dw_3_0\n",
      "\t\t\tBlock: dres_dw_3_2\n",
      "\t\t\tBlock: dres_dX_3_init\n",
      "\t\t\tBlock: sens_rhs\n",
      "\t\t\tBlock: res_function_logdv\n",
      "\t\t\tBlock: root_func_logdv\n",
      "\t\t\tBlock: sens_rhs_logdv\n",
      "\t\t\tBlock: integrate_stochastic_tidbit\n",
      "Post-processing (stage 2)...\n",
      "Building modules...\n",
      "\tBuilding module \"CTSN_0_SFI_C02TJ318GTFL_319793_5466515561_16872\"...\n",
      "\t\tConstructing wrapper function \"res_function\"...\n",
      "\t\t  residual = res_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"ddaskr_jac\"...\n",
      "\t\t  pd = ddaskr_jac(t,y,yprime,cj,rpar)\n",
      "\t\tConstructing wrapper function \"root_func\"...\n",
      "\t\t  root_devs = root_func(t,y,yp,constants)\n",
      "\t\tConstructing wrapper function \"alg_deriv_func\"...\n",
      "\t\t  alg_derivs_res = alg_deriv_func(alg_yp,dynamicVars,yp,time,constants)\n",
      "\t\tConstructing wrapper function \"alg_res_func\"...\n",
      "\t\t  residual = alg_res_func(alg_vals,dynamicVars,time,constants)\n",
      "\t\tConstructing wrapper function \"dres_dc_function\"...\n",
      "\t\t  pd = dres_dc_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dcdot_function\"...\n",
      "\t\t  pd = dres_dcdot_function(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_1\"...\n",
      "\t\t  pd = dres_dwself_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dtheta_1\"...\n",
      "\t\t  pd = dres_dtheta_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_1\"...\n",
      "\t\t  pd = dres_dlog_tau_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_0\"...\n",
      "\t\t  pd = dres_dw_1_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_2\"...\n",
      "\t\t  pd = dres_dw_1_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_1_3\"...\n",
      "\t\t  pd = dres_dw_1_3(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dwself_2\"...\n",
      "\t\t  pd = dres_dwself_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dtheta_2\"...\n",
      "\t\t  pd = dres_dtheta_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dlog_tau_2\"...\n",
      "\t\t  pd = dres_dlog_tau_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_1\"...\n",
      "\t\t  pd = dres_dw_2_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_0\"...\n",
      "\t\t  pd = dres_dw_2_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_2_3\"...\n",
      "\t\t  pd = dres_dw_2_3(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_2_init\"...\n",
      "\t\t  pd = dres_dX_2_init(time,dynamicVars,yprime,constants)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n",
      "<string>:1: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma?\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\t\tConstructing wrapper function \"dres_dw_3_1\"...\n",
      "\t\t  pd = dres_dw_3_1(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_3_0\"...\n",
      "\t\t  pd = dres_dw_3_0(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dw_3_2\"...\n",
      "\t\t  pd = dres_dw_3_2(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"dres_dX_3_init\"...\n",
      "\t\t  pd = dres_dX_3_init(time,dynamicVars,yprime,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs\"...\n",
      "\t\t  sens_res = sens_rhs(time,sens_y,sens_yp,constants)\n",
      "\t\tConstructing wrapper function \"res_function_logdv\"...\n",
      "\t\t  residual = res_function_logdv(time,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"root_func_logdv\"...\n",
      "\t\t  root_devs = root_func_logdv(t,log_dv,log_yp,constants)\n",
      "\t\tConstructing wrapper function \"sens_rhs_logdv\"...\n",
      "\t\t  sens_res = sens_rhs_logdv(time,sens_y_log,sens_yp_log,constants)\n",
      "\t\tConstructing wrapper function \"integrate_stochastic_tidbit\"...\n",
      "\t\t  time_ptr,dv,stop_time_ptr,trajectory = integrate_stochastic_tidbit(seed_ptr,reseed,time_ptr,dv,cv,rmsd_ptr,stop_time_ptr)\n",
      "\tWrote C/API module \"CTSN_0_SFI_C02TJ318GTFL_319793_5466515561_16872\" to file \"./CTSN_0_SFI_C02TJ318GTFL_319793_5466515561_16872module.c\"\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/./fortranobject.c' to sources.\n",
      "  adding 'build/src.macosx-10.9-x86_64-3.8/.' to include_dirs.\n",
      "build_src: building npy-pkg config files\n",
      "customize UnixCCompiler\n",
      "customize UnixCCompiler using build_ext\n",
      "CCompilerOpt.__init__[786] : hit the memory cache\n",
      "CCompilerOpt.generate_dispatch_header[2272] : generate CPU dispatch header: (build/src.macosx-10.9-x86_64-3.8/numpy/distutils/include/npy_cpu_dispatch_config.h)\n",
      "building 'CTSN_0_SFI_C02TJ318GTFL_319793_5466515561_16872' extension\n",
      "compiling C sources\n",
      "C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/bryandaniels/anaconda3/include -arch x86_64 -I/Users/bryandaniels/anaconda3/include -arch x86_64\n",
      "\n",
      "compile options: '-I/Users/bryandaniels/Desktop/SloppyCell/SloppyCell/ReactionNetworks -Ibuild/src.macosx-10.9-x86_64-3.8/. -I/Users/bryandaniels/anaconda3/lib/python3.8/site-packages/numpy/core/include -Ibuild/src.macosx-10.9-x86_64-3.8/numpy/distutils/include -I/Users/bryandaniels/anaconda3/include/python3.8 -c'\n",
      "extra options: '-msse -msse2 -msse3'\n",
      "gcc: CTSN_0_SFI_C02TJ318GTFL_319793_5466515561_16872module.cgcc: CTSN_0_SFI_C02TJ318GTFL_319793_5466515561_16872.c\n",
      "\n",
      "gcc -bundle -undefined dynamic_lookup -L/Users/bryandaniels/anaconda3/lib -arch x86_64 -L/Users/bryandaniels/anaconda3/lib -arch x86_64 build/temp.macosx-10.9-x86_64-3.8/CTSN_0_SFI_C02TJ318GTFL_319793_5466515561_16872.o build/temp.macosx-10.9-x86_64-3.8/CTSN_0_SFI_C02TJ318GTFL_319793_5466515561_16872module.o build/temp.macosx-10.9-x86_64-3.8/Users/bryandaniels/Desktop/SloppyCell/SloppyCell/ReactionNetworks/mtrand.o build/temp.macosx-10.9-x86_64-3.8/build/src.macosx-10.9-x86_64-3.8/fortranobject.o -o CTSN_0_SFI_C02TJ318GTFL_319793_5466515561_16872.cpython-38-darwin.so\n"
     ]
    }
   ],
   "source": [
    "# Load saved version of fittingProblem that has already been fit.\n",
    "p = fittingProblem.load('simpleExample_savedFittingProblem.pkl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Analyze the selected model\n",
    "--------------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we plot predicted timecourses from the selected model for the first 10 in-sample initial conditions, using plotBestModelResults:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x144 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,2))\n",
    "p.plotBestModelResults(plotInitialConditions=True,indices=range(10));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And now for out-of-sample data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x144 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,2))\n",
    "m = p.getBestModel()\n",
    "m.plotResults(sirIsaacData[20:30],indepParamsList[20:30],\n",
    "              plotInitialConditions=True,plotFittingData=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can look at the selected model's parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[\n",
      "('wself_1', -0.01905525855311797),\n",
      "('theta_1', -0.10042336489771024),\n",
      "('log_tau_1', -1.3429818941609932),\n",
      "('w_1_0', 3.5028638262853438),\n",
      "('w_1_2', -1.1983546770965334),\n",
      "('wself_2', -1.377691298915458),\n",
      "('log_tau_2', 0.3949860716779374),\n",
      "('w_2_1', -1.0013279544798095),\n",
      "('w_2_0', -0.5236628896994605),\n",
      "('X_2_init', -0.2889053308674365),\n",
      "]\n"
     ]
    }
   ],
   "source": [
    "m = p.getBestModel()\n",
    "print(m.getParameters())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following will use SloppyCell to output a latex file with the ODEs describing the selected model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "m = p.getBestModel()\n",
    "fittingProblem.IO.eqns_TeX_file(m.net,filename='simpleExample_selectedModel.tex')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "More details\n",
    "------------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can examine the dynamics of the hidden nodes as well using plotResults."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x288 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,4))\n",
    "m = p.getBestModel()\n",
    "m.plotResults(p.fittingData[:10],\n",
    "              p.indepParamsList[:10],\n",
    "              plotInitialConditions=True,\n",
    "              plotHiddenNodes=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have access to raw trajectories using evaluateVec.  Here we use this to plot a projection of trajectories in phase space for the first in-sample initial conditions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(4,4))\n",
    "times = np.linspace(0,1,1000)\n",
    "xdata = m.evaluateVec(times,'x',p.indepParamsList[0])\n",
    "X2data = m.evaluateVec(times,'X_2',p.indepParamsList[0])\n",
    "fittingProblem.Plotting.plot(xdata,X2data)\n",
    "plt.xlabel('x')\n",
    "plt.ylabel('X_2');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also look at other models that SirIsaac fit in searching for the best one.  In this case, 'Model 4' was selected because it has the largest estimated log-likelihood:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model 1: #species = 2, #params = 3, L = -73.12272406756854\n",
      "Model 2: #species = 3, #params = 6, L = -71.85157277889262\n",
      "Model 3: #species = 3, #params = 8, L = -71.91118730091047\n",
      "Model 4: #species = 3, #params = 10, L = -70.64509888028904\n",
      "Model 5: #species = 4, #params = 13, L = -74.1526752962969\n",
      "Model 6: #species = 4, #params = 15, L = -73.57941722124676\n",
      "Model 7: #species = 4, #params = 17, L = -73.69419317634126\n",
      "\n",
      "Selected model: Model 4\n"
     ]
    }
   ],
   "source": [
    "for name in p.fittingModelNames:\n",
    "    if name in p.logLikelihoodDict.keys():\n",
    "        print('{}: #species = {}, #params = {}, L = {}'.format(name,\n",
    "              len(p.fittingModelDict[name].speciesNames),\n",
    "              p.numParametersDict[name],\n",
    "              p.logLikelihoodDict[name]))\n",
    "print()\n",
    "print('Selected model:',p.maxLogLikelihoodName())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also look at predictions of a model with more parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x144 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,2))\n",
    "m2 = p.fittingModelDict['Model 7']\n",
    "m2.plotResults(sirIsaacData[:10],indepParamsList[:10],\n",
    "              plotInitialConditions=True,plotFittingData=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Also potentially useful is the Hessian at the best-fit parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.11134041e-01, 1.11283180e-01, 1.12277342e-01, 1.16442583e-01,\n",
       "       1.92911514e-01, 2.27930617e-01, 7.85855047e-01, 3.46607042e+02,\n",
       "       4.13662200e+03, 3.94715198e+05])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hess = p.HessianDict[p.maxLogLikelihoodName()]\n",
    "u,singVals,vt = np.linalg.svd( hess )\n",
    "np.sort(singVals)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Other details about what happened during parameter fitting are stored within each fittingModel:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acceptance ratio for initial parameter ensemble = 1.0\n",
      "Sum of squared residuals at best-fit (without priors) = 100.48242932539453\n",
      "Convergence flags for local fits: [1, 0, 0, 1, 1, 0, 0, 0, 0, 1]\n",
      "Number of cost evaluations for local fits: [188, 327, 304, 61, 76, 304, 304, 307, 304, 14]\n",
      "Number of gradient evaluations for local fits: [58, 101, 101, 16, 21, 101, 101, 101, 101, 1]\n"
     ]
    }
   ],
   "source": [
    "m = p.getBestModel()\n",
    "print(\"Acceptance ratio for initial parameter ensemble = {}\".format(m.acceptanceRatio))\n",
    "c = sum(np.array(m.currentResiduals(p.fittingData,p.indepParamsList,includePriors=False))**2)\n",
    "print(\"Sum of squared residuals at best-fit (without priors) = {}\".format(c))\n",
    "print(\"Convergence flags for local fits: {}\".format(m.convFlagList))\n",
    "print(\"Number of cost evaluations for local fits: {}\".format(m.numCostCallsList))\n",
    "print(\"Number of gradient evaluations for local fits: {}\".format(m.numGradCallsList))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, since in this case we know the function used to create the data, we can compare:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x144 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,2))\n",
    "indicesToPlot = range(10)\n",
    "axArray = p.plotBestModelResults(plotInitialConditions=True,indices=indicesToPlot)\n",
    "\n",
    "# compare to model that generated the data (see simpleExample_makeData.py)\n",
    "f = lambda x0,tau,t: x0 * np.exp(-times/tau)\n",
    "\n",
    "for i,indepParams in enumerate(np.array(indepParamsList)[indicesToPlot]):\n",
    "    times = np.linspace(0,1,100)\n",
    "    x0,tau = indepParams\n",
    "    fittingProblem.Plotting.sca(axArray[0][i])\n",
    "    fittingProblem.Plotting.plot(times,f(x0,tau,times),'k:')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.8.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}