{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 340,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using /home/studen/temp/humanHG_withHairPC4\n",
      "Using solution from /home/studen/temp/humanHG_withHairPC3\n",
      "t0=240.0\n",
      "At t=245.77\n",
      "At t=249.01\n",
      "At t=252.22\n",
      "At t=255.62\n",
      "At t=258.70\n",
      "At t=261.96\n",
      "At t=265.16\n",
      "At t=268.43\n",
      "At t=271.65\n",
      "At t=274.87\n",
      "At t=278.28\n",
      "At t=281.36\n",
      "At t=284.77\n",
      "At t=287.86\n",
      "At t=291.14\n",
      "At t=294.37\n",
      "At t=297.60\n",
      "Done simultaneous LSODA SE\n",
      "Time: 87.733 s\n"
     ]
    }
   ],
   "source": [
    "import scipy.integrate\n",
    "import numpy\n",
    "import matplotlib.pyplot\n",
    "import os\n",
    "import json\n",
    "import scipy.interpolate\n",
    "#for partial specialization\n",
    "import cModel\n",
    "import importlib\n",
    "importlib.reload(cModel)\n",
    "import time\n",
    "import ivp\n",
    "importlib.reload(ivp)\n",
    "import runSolver\n",
    "importlib.reload(runSolver)\n",
    "\n",
    "  \n",
    "#run solver\n",
    "fh=os.path.expanduser('~')\n",
    "i=4\n",
    "#jobDir=os.path.join(fh,'temp','humanHG')\n",
    "jobDir=os.path.join(fh,'temp','humanHG_withHairPC')\n",
    "#modelFile=os.path.join(fh,'software','src','PBPK','models','humanHGplusI.json')\n",
    "#parameterFile=os.path.join(fh,'software','src','PBPK','models','humanHGplusI_parameters.json')\n",
    "modelFile=os.path.join(fh,'software','src','PBPK','models','humanHG_withHairPC.json')\n",
    "parameterFile=os.path.join(fh,'software','src','PBPK','models','humanHG_withHairPC_parameters.json')\n",
    "#modelFile=os.path.join(fh,'software','src','PBPK','models','humanHG.json')\n",
    "#parameterFile=os.path.join(fh,'software','src','PBPK','models','humanHG_parameters1.json')\n",
    "if i>0: \n",
    "    targetDir=jobDir+'{}'.format(i)\n",
    "else:\n",
    "    targetDir=jobDir\n",
    "if i==1:\n",
    "    srcDir=jobDir\n",
    "if i>1:\n",
    "    srcDir=jobDir+'{}'.format(i-1)\n",
    "\n",
    "code=''\n",
    "if i>0:\n",
    "    code='{}'.format(i+1)\n",
    "setupFile=os.path.join(fh,'software','src','PBPK','setup','setupFast{}.json'.format(code))\n",
    "\n",
    "if i>0:\n",
    "    runSolver.main([setupFile,modelFile,parameterFile],targetDir,srcDir)\n",
    "else:\n",
    "    runSolver.main([setupFile,modelFile,parameterFile],targetDir)\n",
    "setup=runSolver.parseSetup(setupFile)\n",
    "scale=runSolver.getScale(setup)\n",
    "tmax=setup['tmax']*scale\n",
    "#t0,y0,S1,lut,lutSE=runSolver.getStartPoint(setup)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "201\n"
     ]
    }
   ],
   "source": [
    "humanHG=os.path.join(fh,'temp','humanHG')\n",
    "humanHGplusI=os.path.join(fh,'temp','humanHGplusI')\n",
    "t,sol,se,sOut,qt,lut,lutSE=runSolver.loadSolutionFromDir(humanHG)\n",
    "print(len(t))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 378,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "kHScaled\n",
      "{'redBloodCells': 0, 'plasma': 1, 'venous': 2, 'kidney': 3, 'urine': 4, 'richlyPerfused': 5, 'fat': 6, 'slowlyPerfused': 7, 'hair': 8, 'brainBlood': 9, 'brain': 10, 'liver': 11, 'gut': 12, 'intestine': 13, 'feces': 14, 'inorganicMercury': 15}\n",
      "2.880781921710105e-08\n",
      "    0.33    0.019       17 [bodyWeight]\n",
      "    0.11       15   0.0073 [kRBCScaled]\n",
      "    0.73  2.2e+02   0.0034 [plasmaVolumeFraction]\n",
      "  0.0076      1.3    0.006 [redBloodCellsVolumeFraction]\n",
      "  0.0089   0.0025      3.5 [rbcPC]\n",
      "    0.38  3.2e+02   0.0012 [kidneyVolumeFraction]\n",
      " 6.8e-07       24  2.9e-08 [kHScaled]\n",
      "  0.0066     0.12    0.056 [slowlyPerfusedVolumeFraction]\n",
      " 0.00085       17  4.9e-05 [kBRScaled]\n",
      "    0.57  2.7e+02   0.0021 [brainBloodVolumeFraction]\n",
      " 0.00029    0.049    0.006 [brainVolumeFraction]\n",
      " 0.00028  0.00032     0.88 [brainPC]\n",
      "   0.051      7.8   0.0065 [liverVolumeFraction]\n",
      " 1.2e-06      2.5  4.9e-07 [kBScaled]\n",
      " 6.6e-05   0.0016    0.042 [intestineVolumeFraction]\n",
      " 0.00012       24  4.9e-06 [kIScaled]\n",
      "  0.0005       21  2.4e-05 [kRScaled]\n",
      "    0.19       73   0.0026 [gutVolumeFraction]\n",
      " 1.2e-05       24  4.9e-07 [kDScaled]\n",
      " 2.7e-05       24  1.2e-06 [kFScaled]\n",
      "    0.37     0.32      1.2 [kidneyPC]\n",
      "     1.1       15    0.073 [cardiacOutputScaled]\n",
      "     1.5       29    0.052 [kidneyFlowFraction]\n",
      "    0.27      4.8    0.055 [richlyPerfusedFlowFraction]\n",
      "   0.064      2.1     0.03 [richlyPerfusedVolumeFraction]\n",
      "   0.062     0.21     0.29 [richlyPerfusedPC]\n",
      "   0.043     0.98    0.044 [fatPC]\n",
      "     0.5       32    0.016 [fatFlowFraction]\n",
      "   0.035     0.54    0.066 [fatVolumeFraction]\n",
      "   0.012    0.021     0.59 [slowlyPerfusedPC]\n",
      "    0.18      2.4    0.075 [slowlyPerfusedFlowFraction]\n",
      "    0.55      1.9     0.29 [brainBloodPC]\n",
      "    0.57       17    0.034 [brainBloodFlowFraction]\n",
      "   0.066     0.97    0.068 [liverOutFlowFraction]\n",
      "   0.059    0.041      1.5 [liverPC]\n",
      "    0.78      1.2     0.63 [gutPC]\n",
      "    0.41      6.8     0.06 [gutFlowFraction]\n",
      "   0.066      4.5    0.015 [liverInFlowFraction]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "model=cModel.model()\n",
    "#sys.parse(os.path.join(fh,'software','src','Integra','models','cDiazepam.json'))\n",
    "setupFile=os.path.join(fh,'software','src','PBPK','setup','setupFastLoad.json')\n",
    "modelFile=os.path.join(fh,'software','src','PBPK','models','humanHG.json')\n",
    "parameterFile=os.path.join(fh,'software','src','PBPK','models','humanHG_parameters1.json')\n",
    "model.parse(modelFile,parameterFile)\n",
    "setup=runSolver.parseSetup(setupFile)\n",
    "scale=runSolver.getScale(setup)\n",
    "tmax=setup['tmax']*scale\n",
    "jpar=6\n",
    "SS=model.fSS(1)[jpar]\n",
    "lutSEi={model.lutSE[x]:x for x in model.lutSE}\n",
    "print(lutSEi[jpar])\n",
    "matplotlib.pyplot.imshow(SS)\n",
    "matplotlib.pyplot.colorbar()\n",
    "print(model.lut)\n",
    "w=model.getWeights(model.lutSE)\n",
    "sqw=numpy.sqrt(w)\n",
    "print(sqw[jpar])\n",
    "for p in model.lutSE:\n",
    "    jp=model.lutSE[p]\n",
    "    jSS=model.fSS(1)[jp]\n",
    "    jm=numpy.max(jSS)\n",
    "    jw=sqw[jp]\n",
    "    print('{:8.2g} {:8.2g} {:8.2g} [{}]'.format(jm*jw,jm,jw,p))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model=cModel.model()\n",
    "fh=os.path.expanduser('~')\n",
    "#sys.parse(os.path.join(fh,'software','src','Integra','models','cDiazepam.json'))\n",
    "setupFile=os.path.join(fh,'software','src','PBPK','setup','setupFast.json')\n",
    "modelFile=os.path.join(fh,'software','src','PBPK','models','humanHGplusI.json')\n",
    "parameterFile=os.path.join(fh,'software','src','PBPK','models','humanHGplusI_parameters.json')\n",
    "model.parse(modelFile,parameterFile)\n",
    "setup=runSolver.parseSetup(setupFile)\n",
    "tscale=runSolver.getScale(setup)\n",
    "\n",
    "model.inspect()    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "***********done************\n",
      "(16, 16)\n",
      "22\n",
      "Time: 0.714 s\n",
      "[ 0.          0.          0.          0.          0.          0.\n",
      "  0.          0.12434798 -0.00099998  0.          0.          0.\n",
      "  0.          0.          0.          0.        ]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "model=cModel.model()\n",
    "fh=os.path.expanduser('~')\n",
    "#sys.parse(os.path.join(fh,'software','src','Integra','models','cDiazepam.json'))\n",
    "setupFile=os.path.join(fh,'software','src','PBPK','setup','setupFast.json')\n",
    "modelFile=os.path.join(fh,'software','src','PBPK','models','humanHGplusI.json')\n",
    "parameterFile=os.path.join(fh,'software','src','PBPK','models','humanHGplusI_parameters.json')\n",
    "sys.parse(modelFile,parameterFile)\n",
    "setup=runSolver.parseSetup(setupFile)\n",
    "tscale=runSolver.getScale(setup)\n",
    "\n",
    "sys.inspect()    \n",
    "\n",
    "print(\"***********done************\")\n",
    "print(model.M(1).shape)\n",
    "#print(sys.fSS(2))\n",
    "print(model.m)\n",
    "\n",
    "nt=setup['nt']\n",
    "qtmax=24*60*365*10\n",
    "qt=numpy.linspace(0,qtmax,nt)\n",
    "#ft=[fw['derivatives']['fetusGrowthDuration'](x) for x in qt]\n",
    "try:\n",
    "    fw=model.get('fetusWeight')\n",
    "    ft=[fw['value'](x) for x in qt]\n",
    "    matplotlib.pyplot.plot(qt/tscale,ft)\n",
    "except (KeyError,TypeError):\n",
    "    pass\n",
    "\n",
    "try:\n",
    "    hw=model.get('hairVolume')\n",
    "    ht=[10*hw['value'](x) for x in qt]\n",
    "    matplotlib.pyplot.plot(qt/tscale,ht)\n",
    "except (KeyError,TypeError):\n",
    "    pass\n",
    "start_time=time.time()\n",
    "for i in range(100000):\n",
    "    model.M(1e7)\n",
    "end_time=time.time()\n",
    "print('Time: {:.3f} s'.format(end_time-start_time))\n",
    "print(sys.M(1000)[8,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 341,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1440 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# #copy output of Thompson et al1\n",
    "# merge solutions \n",
    "humanHG=os.path.join(fh,'temp','humanHG')\n",
    "humanHGplusI=os.path.join(fh,'temp','humanHGplusI')\n",
    "humanHG_withHairPC=os.path.join(fh,'temp','humanHG_withHairPC1')\n",
    "t,sol,se,sOut,qt,lut,lutSE=runSolver.loadSolutionFromDir(humanHG)\n",
    "t1,sol1,se1,sOut1,qt1,lut1,lutSE1=runSolver.loadSolutionFromDir(targetDir)\n",
    "fig, axs = matplotlib.pyplot.subplots(4, 3,figsize=(15,20))\n",
    "name=['plasma','kidney','liver',\n",
    "      'plasmaI','kidneyI','liverI',\n",
    "      'brain','hair','redBloodCells',\n",
    "     'brainI','hairI','slowlyPerfused'\n",
    "      ]\n",
    "\n",
    "tscale=scale\n",
    "max=[-1]*len(name)\n",
    "for i in range(len(name)):\n",
    "    row=i//3\n",
    "    col=i%3\n",
    "    ax=axs[row,col]\n",
    "    try:\n",
    "        fy=sol[:,lut[name[i]]]\n",
    "        fe=se[:,lut[name[i]]]\n",
    "        ax.plot(t/tscale,fy)\n",
    "        ax.fill_between(t/tscale, fy-fe, fy + fe, color='red',alpha=0.1)\n",
    "        ax.plot(t/tscale,fy-fe,color='red',linewidth=1,alpha=0.2)\n",
    "        ax.plot(t/tscale,fy+fe,color='red',linewidth=1,alpha=0.2)\n",
    "    except KeyError:\n",
    "        pass\n",
    "    try:\n",
    "        fy1=sol1[:,lut1[name[i]]]\n",
    "        fe1=se1[:,lut1[name[i]]]\n",
    "        ax.plot(t1/tscale,fy1,color='black')\n",
    "        ax.fill_between(t1/tscale, fy1-fe1, fy1 + fe1, color='black',alpha=0.1)\n",
    "        ax.plot(t1/tscale,fy1-fe1,color='green',linewidth=1,alpha=0.2)\n",
    "        ax.plot(t1/tscale,fy1+fe1,color='green',linewidth=1,alpha=0.2)\n",
    "    except (NameError,KeyError):\n",
    "        pass\n",
    "    if max[i]>0:\n",
    "        axs[row,col].set_ylim([0,max[i]])\n",
    "    axs[row,col].set_xlim([0,1.1*tmax/tscale])\n",
    "    axs[row,col].set_title(name[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 380,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sum (hair, der, sigma_p)\n",
      "\t4.5e-05 [7.5e+04 6e-10] kRScaled \n",
      "\t3.3e-05 [1.1e-07 3e+02] bodyWeight \n",
      "\t3.2e-05 [3.9e+10 8.3e-16] kHScaled \n",
      "\t7.8e-06 [2.3e-05 0.34] slowlyPerfusedPC \n",
      "\t4.9e-06 [0.0016 0.0031] slowlyPerfusedVolumeFraction \n",
      "\t1.2e-06 [0.00025 0.0046] liverOutFlowFraction \n",
      "\t1.1e-06 [5.2e-07 2.2] liverPC \n",
      "\t7.8e-07 [0.019 4.2e-05] liverVolumeFraction \n",
      "\t7.3e-07 [5.9e-08 12] rbcPC \n",
      "\t6.3e-07 [0.018 3.6e-05] redBloodCellsVolumeFraction \n"
     ]
    }
   ],
   "source": [
    "model=cModel.model()\n",
    "#sys.parse(os.path.join(fh,'software','src','Integra','models','cDiazepam.json'))\n",
    "setupFile=os.path.join(fh,'software','src','PBPK','setup','setupFast.json')\n",
    "modelFile=os.path.join(fh,'software','src','PBPK','models','humanHG_withHairPC.json')\n",
    "parameterFile=os.path.join(fh,'software','src','PBPK','models','humanHG_withHairPC_parameters.json')\n",
    "model.parse(modelFile,parameterFile)\n",
    "t,sol,se,sOut,qt,lut,lutSE=runSolver.loadSolutionFromDir(targetDir)\n",
    "compartment='hair'\n",
    "d=model.getDerivatives(sOut,lut[compartment])\n",
    "w=model.getWeights(lutSE)\n",
    "print('Sum ({}, der, sigma_p)'.format(compartment))\n",
    "s={x:d[lutSE[x]]*w[lutSE[x]] for x in lutSE}\n",
    "s=dict(sorted(s.items(), key=lambda item:item[1],reverse=True))\n",
    "for p in list(s)[:10]:\n",
    "    j=lutSE[p]\n",
    "    print('\\t{:.2g} [{:.2g} {:.2g}] {} '.format(d[j]*w[j],d[j],w[j],p))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 382,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BZgUc1du5f6yTmVlVDKYeTQeaZtZO+3s0nTprVigHmhVQ766xd8gPSzOrlkaPplNnzaZG0jxJayVtSn/nTnDcinTMJkkrcuWnSrpf0mZJV0vSZPVKWi7pPkn3Stoo6VWHOkcVuEfTrBz8r38F1LtqDI2MMeqlTsysQtyjaTZtlwHrI2IxsD5tH0TSPGAVcDpwGrAqF5BeA1wCLE6fZYeodz1wSkQsAd4GXDeFc5SeezTNysGBZgX0pQfmwLAfmGZWHY1ZZ92jaTZly4E16fsa4Lwmx5wDrI2IXRHxGLAWWCbpOODoiNgQEQHckPt903oj4sl0LMAcICY7R6tucrbtn3XWPZpmhfK//hVQ9wPTzCqoMbbcPZpmU7YgIral79uBBU2OWQg8nNveksoWpu/jyyetV9IbJX0P+GeyXs3JzvEUklamtNuNO3bsOMTttUd3ZwddNbHHw47MCtVZ9AXYodVTI23AD0wzqxD3aJo91dKlS9m+fXuzXcfkNyIiJLV8zMz4eiPiZuBmSb8MXAEsnWZ91wLXAvT395dmjE9fdyd79/kFvVmRZvSvfwGD1l8s6WuS9kn6H+PO8eNU172SNk73GsvMqbNmVkXu0TR7qnXr1vHAAw885QM8DjySUmBJfx9tUsVW4Pjc9qJUtjV9H1/OVOqNiLuA50s6dpJzVMac7pp7NM0KNtPXzO0etL4L+D3ggxNcz2siYklE9E/nGsuungJNzzxrZlXiHk2zabsVaLyQXwHc0uSYO4CzJc1N7amzgTtSauxuSWekF/cX5n7ftF5JL8y95H850APsnOgcrb3V2TWnp9NDjswKNtN//ds9aP3RiLgHGG7xNZaaU2fNrIo866zZtF0JvE7SJrIU1isBJPVLug4gInaRpbjekz6XpzKAS8lmjt0M/BC4fbJ6gV8FHpB0L/Ax4NcjM9k5KqGvp9OzzpoVbKZjNNs+aH0SAXwxjTv42zRm4HDrKpX9qbMONM2sQryOptn0RMRO4Kwm5RuBi3Pbq4HVExx38jTqvQq4aoJraXqOqpjTXWOPx2iaFeqQgaakdcCzm+z6s/xGuwatT+JVEbFV0rOAtZK+l8YbTLkuSSuBlQAnnHDCjK67lRqB5l6P0TSzChkcHqO71kFHh4q+FDN7munr7uSxvQNFX4bZ09ohA82ImHD2MUmPSDouIrYdYtD6mbntRcCdTGHQ+iHqHX+dW9PfRyXdTDYe9K7p1FXWmdMaaWeD7tE0swoZHB6lp8u9mWbWfnN6ah6jaVawmbYA2jpofSKS5kj6ucb3dI4HDqeuMvLCw2ZWRftGxujp9PhMM2u/vm6P0TQr2kzHaF4J3CTpIuAh4M2QDVoH3h4RF0fELkmNAeXw1EHr1wN1sgHrtx+i3mcDG4GjgTFJ7wJOAo4lWwOqcU//GBH/MlldVdKYDMips2ZWJfuGR+l1j6aZFWBOt3s0zYo2o0CzgEHr2zk43bZhN3DKdK6xSnq7OpCcOmtm1ZL1aDrQNLP26+vpZO/QKGNj4XHiZgVxC6ACJFHvqnkdTTOrlMHhUS9tYmaFmNOYsd/ZYGaFcaBZEfWumlNnzaxSBkdG3aNpZoXo68mS9vY4fdasMG4BVES9u+bUWTOrlMHhMfdomlkhGj2aez0hkFlhHGhWRF+3U2fNrFoGh0f3T2ZmZtZOjRn73aNpVhwHmhXh1FkzqxqP0TSzoszpST2afklvVhgHmhXh1Fkzq5rB4TF6vLyJmRVgTmOM5j73aJoVxS2Aiujr7mTvsB+WZlYd7tE0s6LMSamz7tE0K44DzYrw8iZmVjWDw6P0djrQNLP260uTAT3pHk2zwjjQrAinzppZ1QyOjFHv9j8zZtZ+jdTZvQ40zQrjFkBF9HV7MiAzq47h0TFGx8I9mmZWiEaP5h6/pDcrjAPNinDqrJlVyWB6MeYxmmZWhJ7ODmodYq+XNzErjAPNiqh31xgayXoIzMzKbmB/oOl/Zsys/STR111jzz6/pDcrilsAFdFIARlw+qyZVcC+4TEAetyjaWYFmdPd6R5NswI50KyIeldj4WE/MM2s/Bqps3UHmmZWkL6emsdomhXIgWZF1NN6UINDYwVfiZnZoQ2mHk2P0TSzoszp7vSss2YFcqBZEY3U2b3DfmCatZqk1ZIelfRArmyJpA2S7pW0UdJpqVySrpa0WdJ9kl6e+80KSZvSZ0Wu/FRJ96ffXC1JqXyepLXp+LWS5rbzvmfT4IjHaJpZsfq63aNpViS3ACqikX424Aem2Wy4Hlg2ruwDwJ9HxBLgvWkb4FxgcfqsBK6BLGgEVgGnA6cBq3KB4zXAJbnfNc51GbA+IhYD69P2EaHxrHKPppkVZU6Px2iaFcmBZkXUux1oms2WiLgL2DW+GDg6fX8G8JP0fTlwQ2Q2AMdIOg44B1gbEbsi4jFgLbAs7Ts6IjZERAA3AOfl6lqTvq/JlVeex2iaWdH6umvs9ayzZoXpLPoCbGoOTAbkB6ZZm7wLuEPSB8leyv0/qXwh8HDuuC2pbLLyLU3KARZExLb0fTuwoNmFSFpJ1nvKCSeccJi3016DI40xmn6faWbFOKqnkz3u0TQrjFsAFeHlTcza7neAP4iI44E/AD45mydLvZ1NF8qNiGsjoj8i+ufPnz+bl9EyjR7Nnk73aJpZMfq6O92jaVagGQWaU53IolUTZEh6saSvSdon6X/k6nlRmrCj8dkt6V1p3/skbc3te/1M7rkoTp01a7sVwOfS938iG3cJsBU4PnfcolQ2WfmiJuUAj6TUWtLfR1t4/YXaN+wxmmZWrDk9NfYMjZC9xzOzdptpj+YhJ7Jo8QQZu4DfAz6YP0dEfD8ilqRJO04F9gI35w75cGN/RNw2w3suhNfRNGu7nwCvTt9fC2xK328FLkyzz54BPJHSX+8AzpY0Nz3jzgbuSPt2SzojvUy7ELglV1fj5duKXHnlDQx71lkzK1ZfdydjcWC5JTNrr5m2AKYykUXLJsiIiEcj4h5geJJrOgv4YUQ8NIP7Kp2+tI7mgB+WZi0n6VPA14AXSdoi6SKyl2AfkvQt4C9JYySB24AHgc3AJ4BLASJiF3AFcE/6XJ7KSMdcl37zQ+D2VH4l8DpJm4ClafuI4HU0zaxoc3qy54/HaZoVY6aTAU1lIotZmyBjAucDnxpX9k5JFwIbgXengPcpyjzhRk9n9k5gwA9Ls5aLiAsm2HVqk2MDeMcE9awGVjcp3wic3KR8J9nLsSPO4PAonR2iq+YeTTMrRuMl/d59o3BUwRdj9jR0yBaApHWSHmjyWZ4/brKJLGZiOvVK6gbeQDaequEa4AXAEmAb8KFJzlXaCTc6OkS9q+bJgMysEgaHx9ybaWaFmtPtHk2zIh2yRzMilk60T9Ijko6LiG2TTGSxFTgzt70IuJMpTJBxiHqbORf4ZkQ8krv+/d8lfQL4whTrKp2+7pqXNzGzShgcGfX4TDMrVF9P6tF0oGlWiJm2AqYykUU7J8i4gHFps40ZHZM3Ag9Msa7S6e2qedZZM6uEwaFRL21iZoVqLA3nl/RmxZjpGM0rgZvSxBkPAW8GkNQPvD0iLo6IXZIaE2TAUyfIuB6ok02Ocfsh6n022TjLo4GxtITJSRGxW9Ic4HXAb4+7xg9IWkKWfvvjJvsro6/bqbNmVg2DI6P7l2UyMyvCgRn73XYyK8KMAs2JJrJIE19cnNtuyQQZEbGdg9Nt8/v2AM9sUv6WSW+iQpw6a2ZVkY3RdOqsmRWnz2uQmxXKrYAK6fVkQGZWEYPDo/Q6ddbMCrR/1lkHmmaFcKBZIX3dHqNpZtUwODzqWWfNrFAHUmc9GZBZERxoVki9u+aHpZlVwoBTZ82sYHWnzpoVyq2ACql3dTI4PFb0ZZiZHdI+92iaWcG6Ozvo7BB7PezIrBAONCuk3t3hMZpmVglOnTWzMqh72JFZYRxoVkjd62iaWUUMjjh11my6JM2TtFbSpvR37gTHrUjHbJK0Ild+qqT7JW2WdHVap3zCeiUtl3SfpHslbZT0qlxdo6n8Xkm3zva9z5Y+DzsyK4xbARVS7+5kYHiUiCj6UszMJuVZZ80Oy2XA+ohYDKxP2weRNA9YBZwOnAasygWk1wCXAIvTZ9kh6l0PnBIRS4C3AdflTjUQEUvS5w0tvMe26uvu9KyzZgVxoFkhjdnTPE7TzMosIhhw6qzZ4VgOrEnf1wDnNTnmHGBtROyKiMeAtcAySccBR0fEhsjeSN+Q+33TeiPiyTjw9noOcMS9yXY2mFlxHGhWSD2loXmcppmV2dDoGBEHZnw0sylbEBHb0vftwIImxywEHs5tb0llC9P38eWT1ivpjZK+B/wzWa9mQ29Kp90gqVnA2/j9ynTcxh07dhz6DtssS511u8msCJ1FX4BNXWPhYQeaZlZmjayLnk6/yzQbb+nSpWzfvr3ZrmPyGxERklrewzi+3oi4GbhZ0i8DVwBL067nRsRWSc8HviTp/oj4YZP6rgWuBejv7y9dj2i9u8buQY/RNCuCA80K6fV6UGZWAfvSyzCnzpo91bp165qWS3ocGJV0XERsS6mwjzY5dCtwZm57EXBnKl80rnxr+v7IoeqNiLskPV/SsRHx04jYmsoflHQn8IvAUwLNsuvrrvHI7sGiL8PsacmvmyvkwBhNB5pmVl6NHk0HmmbTdivQmEV2BXBLk2PuAM6WNDdNAnQ2cEdKjd0t6Yw02+yFud83rVfSC3Mz074c6AF2prp7UvmxwCuB77T2VtvDkwGZFcc9mhXSCDSdOmtmZTawv0fT7zLNpulK4CZJFwEPAW8GkNQPvD0iLo6IXZKuAO5Jv7k8Inal75cC1wN14Pb0mbBe4FeBCyUNAwPAr6fU2l8A/lbSGFmnxJURUclA0+tomhXHgWaFNCbW8Js5MyuzRtZF3T2aZtMSETuBs5qUbwQuzm2vBlZPcNzJ06j3KuCqJuV3Ay+d5uWXUl+XJwMyK4pfN1fI/h5NPzDNrMQGPUbTzEqir7vGwPAoY2Olm6fI7IjnQLNCGj2aHqNpZmU2ONIYo+l/YsysWPU0Y//giNtOZu3mVkCFeIymmVVBI+uip9M9mmZWrD4POzIrjAPNCvEYTTOrgn0jTp01s3Koe2k4s8I40KwQL29iZlWwfzKgbgeaZlasRo+ms8HM2m/GgaakeZLWStqU/s6d4LgV6ZhNklbkyk+VdL+kzZKuzq3n1LReSb8h6b70m7slnZKra5mk76e6LsuVP0/S11P5pyV1z/S+i9BVE7UO+a2cmZXa/nU0O/0u08yK5dRZs+K0ohVwGbA+IhYD69P2QSTNA1YBpwOnAatyAek1wCXA4vRZdoh6fwS8OiJeClwBXJvOUQM+BpwLnARcIOmk9JurgA9HxAuBx4CLWnDfbSfJ03SbWel51lkzK4t6VzYZ0N6hkYKvxOzppxWB5nJgTfq+BjivyTHnAGsjYldEPAasBZZJOg44OiI2REQAN+R+37TeiLg71QGwAViUvp8GbI6IByNiCLgRWJ56SF8LfOYQ11gJvWmabjOzshpwoGlmJdHnMZpmhWlFoLkgIral79uBBU2OWQg8nNveksoWpu/jy6da70XA7Yc4xzOBxyNiZFz5U0haKWmjpI07duxodkjh6l01BvxWzsxKbHB4bH+qv5lZkZw6a1aczqkcJGkd8Owmu/4svxERIanlK+I2q1fSa8gCzVe18DzXklJx+/v7S7myb597NM2s5AaHR92baWal4FlnzYozpUAzIpZOtE/SI5KOi4htKRX20SaHbQXOzG0vAu5M5YvGlW9N3yesV9LLgOuAcyNiZ+4cxzepaydwjKTO1KuZP0fl9HbVGEgTbZiZldG+EQeaZlYOfd0eo2lWlFakzt4KNGaRXQHc0uSYO4CzJc1NkwCdDdyRUmN3SzojjaW8MPf7pvVKOgH4HPCWiPhB7hz3AIvTDLPdwPnArWns55eBNx3iGivBqbNmVnaDw2P0dnnGWTMr3v7UWWeDmbVdK1oCVwKvk7QJWJq2kdQv6TqAiNhFNkPsPelzeSoDuJSsd3Iz8EMOjLlsWi/wXrJxlx+XdK+kjekcI8A7yYLa7wI3RcS302/eA/yhpM3pt59swX0XwqmzZlZ2AyW5gkIAACAASURBVEOj9Ha6R9PMitfT2YHk1FmzIkwpdXYyKXX1rCblG4GLc9urgdUTHHfyNOq9OF/vuH23Abc1KX+QbFbayuvtrvlhaWalNujUWTMrCS8NZ1Yc5zZVTJY664elmZXX4PAodQeaZlYS9e5OB5pmBXCgWTFOnTWzshscHqPHYzTNrCT6uj2/hVkR3BKomLrTP8xaTtJqSY9KemBc+e9K+p6kb0v6QK78TyRtlvR9Sefkypelss2SLsuVP0/S11P5p9OEZUjqSdub0/4TZ/9uZ5+XNzGzMunrdtvJrAgONCumt6vGvpExxsZKucynWVVdDyzLF6S1epcDp0TES4APpvKTyGa1fkn6zccl1STVgI8B5wInARekYwGuAj4cES8EHiNbA5j097FU/uF0XOU50DSzMqk7G8ysEA40K6YxTffgiB+YZq0SEXcBu8YV/w5wZUTsS8c01vJdDtwYEfsi4kdkM2aflj6bI+LBiBgCbgSWp6WbXgt8Jv1+DXBerq416ftngLPS8ZU2ODxGb6f/eTGzcnCPplkx3BKomHpjPSg/MM1m288Dv5RSWv9V0itS+ULg4dxxW1LZROXPBB5PSzDlyw+qK+1/Ih1/EEkrJW2UtHHHjh0tubnZNDA8uv+lmJlZ0epdngzIrAgONCumkY7mmWfNZl0nMA84A/gj4Kaiehsj4tqI6I+I/vnz5xdxCdMyMDxKrwNNMysJTwZkVgwHmhXT6CXwWAOzWbcF+Fxk/h0YA44FtgLH545blMomKt8JHCOpc1w5+d+k/c9Ix1fW6FgwNDJGX9eMl2k2M2sJp86aFcOBZsU01qYbdKBpNts+D7wGQNLPA93AT4FbgfPTjLHPAxYD/w7cAyxOM8x2k00YdGtEBPBl4E2p3hXALen7rWmbtP9L6fjKarwEq3f7nxczK4d6t9cgNyuCXzlXTN2ps2YtJ+lTwJnAsZK2AKuA1cDqtOTJELAiBYHflnQT8B1gBHhHRIymet4J3AHUgNUR8e10ivcAN0r6C+A/gE+m8k8CfydpM9lkROfP+s3Ossazqe5ZZ82sJPq6a+wdHiUiOALmWzOrDAeaFdPr1FmzlouICybY9ZsTHP9+4P1Nym8DbmtS/iDZrLTjyweBX5vWxZZcI9vCy5uYWVn0dXdmaf2jY/R0+tlk1i7ObaqY3k6nzppZeR1InXVjzszKwdlgZsVwoFkxdfdomlmJNRpyXt7EzMqiz0vDmRXCgWbFHHgrN1bwlZiZPVWjIefUWTMrC69BblYMB5oVsz/QdI+mmZVQI63fkwGZWVn0dWdTkjh11qy9HGhWTG9aMsBjNM2sjDxG08zK5kDq7EjBV2L29OJAs2K6ax10yG/lzKycvLyJmZXN/tRZv6Q3aysHmhUjiXpXzeMMzKyU3KNpZmXT6NH0S3qz9nKgWUH17hqDI35Ymln5uEfTzMqmr8tjNM2KMKNAU9I8SWslbUp/505w3Ip0zCZJK3Llp0q6X9JmSVdL0mT1SvoNSfel39wt6ZRUfrykL0v6jqRvS/r93DneJ2mrpHvT5/Uzuecy6O2qeYymmZVSo0fTs86aWVk4ddasGDPt0bwMWB8Ri4H1afsgkuYBq4DTgdOAVbmA9BrgEmBx+iw7RL0/Al4dES8FrgCuTeUjwLsj4iTgDOAdkk7KXcaHI2JJ+tw2w3suXN2BppmV1MDwKF010VVzwoyZlcOB1FlPBmTWTjNtCSwH1qTva4DzmhxzDrA2InZFxGPAWmCZpOOAoyNiQ0QEcEPu903rjYi7Ux0AG4BFqXxbRHwzff8Z8F1g4QzvrbTq3TWnf5hZKQ0Mjbo308xKpddrkJsVYqaB5oKI2Ja+bwcWNDlmIfBwbntLKluYvo8vn2q9FwG3jy+UdCLwi8DXc8XvTCm3qydK702/XSlpo6SNO3bsmOiwwvV21byOppmV0uDw6P7eAzOzMqh1iO7ODredzNrskIGmpHWSHmjyWZ4/LvVKRqsvsFm9kl5DFmi+Z1z5UcBngXdFxO5UfA3wAmAJsA340CTnujYi+iOif/78+a27iRbLAk2/lTOz8tk7NOqJgMysdDzsyKz9DhloRsTSiDi5yecW4JGUAkv6+2iTKrYCx+e2F6Wyren7+HImq1fSy4DrgOURsTNX3kUWZP5DRHwud/2PRMRoRIwBnyAbJ1pp9a4OBp06a2YlNDDs1Fmzw9XuSRZzv3uFpBFJbzrUOaqq3uVhR2btNtPU2VuBxsNnBXBLk2PuAM6WNDc92M4G7kipsbslnZEehBfmft+0XkknAJ8D3hIRP2icIP3+k8B3I+Kv8ydvBKzJG4EHDvdmy6Lu1FkzK6nB4VGvoWl2+No9ySKSasBVwBeneI5Kqne77WTWbjMNNK8EXidpE7A0bSOpX9J1ABGxi2yG2HvS5/JUBnApWe/kZuCHHBhz2bRe4L3AM4GPp6VKNqbyVwJvAV7bZBmTD6S3e/cBrwH+YIb3XDg/LM2srAacOms2E22dZDH5XbKMsHxWWtNzzPjuCuT5Lczar3MmP06pq2c1Kd8IXJzbXg2snuC4k6dR78X5enPlXwU0wTW+ZdKbqCCvo2lmZTUwPMoz6l1FX4ZZVbV1kkVJC8myvV4DvGIK53gKSSuBlQAnnHDCJLdWrHpXh9tOZm02o0DTiuEB7WZWVgNDTp01m8zSpUvZvn17s13H5DciIiTNyiSLuXo/ArwnIsbScM7Dqe9a0rrm/f39Lb/eVvHScGbt50CzgupdNYZHg+HRMS+KbmalMjDs1Fmzyaxbt65puaTHgVFJx0XEtkNMsnhmbnsRcCdTmGSxSb39wI0pyDwWeL2kkUnOUVn1rhqP7x0u+jLMnlYcpVRQo7fAvZpmVjYDngzIbCbaOsliRDwvIk6MiBOBzwCXRsTnJzpHi++1rTzsyKz9HGhWUGPpAA9qN7Oy8WRAZjPS7kkWmzrEOSopG3bkNcjN2smpsxXUCDQHh/zANLPyGBsL9o2MeR1Ns8PU7kkWxx3z1nHbTc9RVZ6x36z93KNZQXX3aJpZCQ2OZM+kPqfOmlnJ1Ls8GZBZuznQrKB6d/Y/mwNNMyuTvakR5zGaZlY2jXU0syVGzawdHGhW0P7UWQeaZlYijd4Cp86aWdk0XoDtG/GwI7N2caBZQU6dNbMyarz88mRAZlY2+9tOTp81axsHmhW0f3kTPyzNrEQGHGiaWUn5Jb1Z+znQrCA/LM2sjBo9BZ4MyMzKprfbbSezdnOgWUEONM2sjPamZ1KvA00zKxmnzpq1nwPNCtr/Vs4PSzMrkUY6v1Nnzaxs6p5I0aztHGhWUG+nH5ZmVj4eo2lmZeWl4czaz4FmBXXVRK1DfliaWansDzSdOmtmJdPr1FmztnOgWUGSqHfVGBz2WlBmVh6NBpwDTTMrG89vYdZ+DjQrqrer5oelmZXKgMdomllJ7V8azm0ns7ZxoFlR9e4Or6NpZqUyMDxKZ4foqvmfFjMrF886a9Z+bg1UVN09mmYtI2m1pEclPdBk37slhaRj07YkXS1ps6T7JL08d+wKSZvSZ0Wu/FRJ96ffXC1JqXyepLXp+LWS5rbjfmfLwPCoezPNrJT2j9H0sCOztplRoDnVRlKrGl+SfiM17O6XdLekU3J1/TiV3ytp43SvsWocaJq11PXAsvGFko4Hzgb+M1d8LrA4fVYC16Rj5wGrgNOB04BVuefNNcAlud81znUZsD4iFgPr03ZlDQ6Peg1NMyulns4OJI/RNGunmfZoHrKR1OLG14+AV0fES4ErgGvHne41EbEkIvqnc41V1NtVc/qHWYtExF3Aria7Pgz8MRC5suXADZHZABwj6TjgHGBtROyKiMeAtcCytO/oiNgQEQHcAJyXq2tN+r4mV15JA0Oj9DnQNLMSOjCRottOZu0y00BzKo2kljW+IuLuVAfABmBRi66xcurdfliazSZJy4GtEfGtcbsWAg/ntrekssnKtzQpB1gQEdvS9+3AgtZcfTH2Djl11szKq+6X9GZtNdNAcyqNpNlqfF0E3J7bDuCLkr4haeU0rxEASSslbZS0cceOHRMdVgpOnTWbPZL6gD8F3tuuc6YXbtFsX1WeTQPDo/vHQZmZlY1n7Ddrr85DHSBpHfDsJrv+LL8RESGpaSNpJprVK+k1ZIHmq3LFr4qIrZKeBayV9L2UDjfla4yIa0npuP39/S2/l1bq9TqaZrPpBcDzgG+loeOLgG9KOg3YChyfO3ZRKtsKnDmu/M5UvqjJ8QCPSDouIralLI9Hm11MVZ5Ng54MyMxKrN7tQNOsnQ7ZoxkRSyPi5CafW0iNJIBJGkmTNcombXw1q1fSy4DrgOURsTN3nVvT30eBm8nGg05aV5X5rZzZ7ImI+yPiWRFxYkScSJZx8fKI2A7cClyYZp89A3giZU3cAZwtaW4ah342cEfat1vSGWnCswuBW9KpbgUaE6StyJVX0sDw6P616szMyqbeVfPScGZtNNPU2ak0klrW+JJ0AvA54C0R8YPGCSTNkfRzje/pHA9MVlfV+WFp1jqSPgV8DXiRpC2SLprk8NuAB4HNwCeASwEiYhfZJGX3pM/lqYx0zHXpNz/kQNr/lcDrJG0ClqbtyhrwGE0zKzEPOzJrr0Omzh7ClcBNqVH2EPBmAEn9wNsj4uKI2CWp0fiCpza+rgfqZA2v2yerl2y81DOBj6d0tpE0w+wC4OZU1gn8Y0T8yyHqqrR6d4cflmYtEhEXHGL/ibnvAbxjguNWA6ublG8ETm5SvhM4a5qXW1oDQ+7RNLPy6u2u8bPB4aIvw+xpY0aB5kSNpNSouji33ZLGV0RcnK83V/4gcMr48snqqrp6V42RsWB4dIyu2kw7ps3MZi6bDMjPIzMrp3pXB4/u9kt6s3Zxi6CiGjM7ulfTzMpi79Aoc7pnmihjZjY7vI6mWXs50KyoRnqax2maWRmMjgX7RsacOmtmpeVZZ83ay4FmRTUm3PASJ2ZWBnuHRgDco2lmpdXbVWPAL+jN2saBZkXVnTprZiXSaLy5R9PMysprkJu1lwPNivIYTTMrkz0p0OxzoGlmJVXvqjE0OsbIqINNs3ZwoFlR+wNNp4CYWQk0UmcdaJpZWe0fdjTiQNOsHRxoVlQjPW1geKTgKzEzO/DSq89jNM2spHq7/ZLerJ0caFaUJwMyszLZ69RZMyu5A20nB5pm7eBAs6Iai6L7YWlmZdBInfVkQGZWVp5I0ay9HGhWlCcDMrMyafRoenkTMyurenfW7HXqrFl7ONCsqN5Op86aWXk4ddbMys4v6c3ay4FmRfV2O3XWzMrDqbNmVnZOnTVrLweaFdVd60ByoGlm5bDXs86aWck1XoQNOnXWrC0caFaUJHo7aw40zawUBoZG6ensoNahoi/FzKwp92iatZcDzQqrd9c8RtPMSmHP0IjHZ5pZqTnQNGsvB5oV1tvZ4YelmZXC3qFRp82aWan1ppdhnnXWrD0caFZYb5dTZ82sHAaGRt2jaTZDkuZJWitpU/o7d4LjVqRjNklakSs/VdL9kjZLulqSplKvpFdIGpH0plzZqKR70+fW2brndmr0aLrtZNYeDjQrzIGmmZXFHgeaZq1wGbA+IhYD69P2QSTNA1YBpwOnAatygeM1wCXA4vRZdqh6JdWAq4AvjjvVQEQsSZ83tOj+CtVV66CzQ84GM2sTB5oV1tvV4TGaZlYKA0MjXtrEbOaWA2vS9zXAeU2OOQdYGxG7IuIxYC2wTNJxwNERsSEiArgh9/vJ6v1d4LPAoy29k5Kqd9UYGHLbyawdZhRotjvFQ9JvSLov/eZuSaek8hfl0jvulbRb0rvSvvdJ2prb9/qZ3HOZ9HbV/FbOzEph79AoczxG02ymFkTEtvR9O7CgyTELgYdz21tS2cL0fXz5hPVKWgi8kawndLxeSRslbZDULOAl1bEyHbdxx44dk99dCfR2u+1k1i4zbRU0UjGulHRZ2n5P/oBcikc/EMA3JN2a3sI1Ujy+DtxGluJx+yT1/gh4dUQ8Julc4Frg9Ij4PrAkna8GbAVuzl3GhyPigzO819Lp7arxxMBw0ZdhZsbA0Kh7NM2mYOnSpWzfvr3ZrmPyGxERkqLV5x9X70eA90TEWHrXn/fciNgq6fnAlyTdHxE/bFLftWTtMfr7+1t+va1W97Ajs7aZaaC5HDgzfV8D3Mm4QJNcigeApEaKx52kFI9U3kjxuH2ieiPi7ly9G4BFTa7pLOCHEfHQ4d9WNfhhaWZl4eVNzKZm3bp1TcslPQ6MSjouIralVNhm6axbOdBGgqwtdGcqXzSufGv6/sgE9fYDN6Yg81jg9ZJGIuLzEbEVICIeTG22XwSeEmhWTZY667aTWTvMdIxmW1M8xrmILCgd73zgU+PK3plSbldPlN4L1Uv/6PEYTTMrCS9vYtYStwKNIUYrgFuaHHMHcLakualNczZwR2o37ZZ0RhqKdGHu903rjYjnRcSJEXEi8Bng0oj4fKq7B0DSscArge+0+F4L4dRZs/Y5ZKApaZ2kB5p8luePSwPPZyXFY3y9kl5DFmiOT9PtBt4A/FOu+BrgBWSptduAD01yrmsjoj8i+ufPn9+aG5hFvV019o34YWlmxYoIL29i1hpXAq+TtAlYmraR1C/pOoCUIXYFcE/6XN7IGgMuBa4DNpP1Pt4+Wb2T+AVgo6RvAV8GroyIIyLQrHd5DXKzdjnk6+eIWDrRPkkTpWLktTLFA0kvI3uInhsRO8ed61zgmxHxSO76H8n99hPAFya6n6rp7ay5R9PMCjc0OsbIWDjQNJuh1K45q0n5RuDi3PZqYPUEx5081XrHHfPW3Pe7gZdO49Iro7erxmN7hoq+DLOnhZmmzrY1xUPSCcDngLdExA+anOsCxqXNpkC14Y3AA9O7xfLq9Vs5MyuBxninulNnzazk/JLerH1m2iq4ErhJ0kXAQ8CbIUvxAN4eERdHxC5JjRQPeGqKx/VAnSy94/bJ6gXeCzwT+HgauD4SEf3pnHOA1wG/Pe4aPyBpCVn67Y+b7K+seleN0bFgeHSMrpqXRDWzYuxNgeYc92iaWcn5Jb1Z+8wo0Gx3ikdEXJyvd9y+PWRB6Pjyt0x6ExXW25U16gaHRx1omllh9g6NAHh5EzMrvV7P2G/WNo5OKqy3K/ufzykgZlakRo+mZ501s7JzoGnWPg40K6wn16NpZlYUp86aWVX0dtUYHPELerN2cKBZYXUHmmZWAgcmA3KgaWbl1tvVwdDIGGNjLV+Rz8zGcaBZYQfGaPrNnJkVZ08ao+nUWTMru0bbaZ97Nc1mnQPNCts/RnPEPZpmVpwDYzTdo2lm5dbb2Zjfwm0ns9nmQLPCep06a2YlMOBA08wqotF28hInZrPPgWaFNcZoNhp5ZmZFcOqsmVWFX9KbtY8DzQo7kDrrcQZmMyFptaRHJT2QK/ufkr4n6T5JN0s6JrfvTyRtlvR9Sefkypelss2SLsuVP0/S11P5pyV1p/KetL057T+xPXfcWgNDo0gHnklmZmXlpeHM2setggrr6fRbObMWuR5YNq5sLXByRLwM+AHwJwCSTgLOB16SfvNxSTVJNeBjwLnAScAF6ViAq4APR8QLgceAi1L5RcBjqfzD6bjK2Ts0Sl9XDUlFX4qZ2aT2Lw3n+S3MZp0DzQrbP3OaA02zGYmIu4Bd48q+GBEjaXMDsCh9Xw7cGBH7IuJHwGbgtPTZHBEPRsQQcCOwXFn09VrgM+n3a4DzcnWtSd8/A5ylCkZre4dGqDtt1swqwEvDmbWPA80Ka6xZ5wHtZrPubcDt6ftC4OHcvi2pbKLyZwKP54LWRvlBdaX9T6TjDyJppaSNkjbu2LGjJTfUSnuHRj0RkJlVwoGX9E6dNZttDjQr7MAU3X5Yms0WSX8GjAD/UNQ1RMS1EdEfEf3z588v6jIm5EDTzKriwBhNv6Q3m23OdaqwzloHnR3yw9Jslkh6K/ArwFkREal4K3B87rBFqYwJyncCx0jqTL2W+eMbdW2R1Ak8Ix1fKQMONM2sIno7nQ1m1i7u0ay43q6aezTNZoGkZcAfA2+IiL25XbcC56cZY58HLAb+HbgHWJxmmO0mmzDo1hSgfhl4U/r9CuCWXF0r0vc3AV/KBbSVsWdoxEubmFklHFjexG0ns9nmlkHF9XbVPHOa2QxJ+hRwJnCspC3AKrJZZnuAtWl+ng0R8faI+Lakm4DvkKXUviMiRlM97wTuAGrA6oj4djrFe4AbJf0F8B/AJ1P5J4G/k7SZbDKi82f9ZmfBwNAo84/qKfoyzMwOyamzZu3jQLPiers6GBzyw9JsJiLigibFn2xS1jj+/cD7m5TfBtzWpPxBsllpx5cPAr82rYstIY/RNLOq6PXyJmZt49TZinOPppkVzcubmFlV9HgiRbO2caBZcb1dHX5Ymlmh9uwb5age92iaWflJorerw2uQm7WBA82Kq3fVPM7AzAozOhYMDI96MiAzq4xet53M2mLGgaakeZLWStqU/s6d4LgV6ZhNklbkyk+VdL+kzZKuVpp1Y6J6JS2XdJ+ke9MC5q863HMcCXq7ap6i28wKs3doBICjehxomlk19Ha67WTWDq3o0bwMWB8Ri4H1afsgkuaRzeJ4OtmEGKtyAek1wCVkSwQsBpYdot71wCkRsQR4G3DdDM5ReT2dXt7EzIqzZ1/WWOtz6qyZVYSHHZm1RysCzeXAmvR9DXBek2POAdZGxK6IeAxYCyyTdBxwdERsSGvH3ZD7fdN6I+LJ3Dpzc4CYwTkqz+MMzKxIT+5zj6aZVYtTZ83aoxWB5oKI2Ja+bwcWNDlmIfBwbntLKluYvo8vn7ReSW+U9D3gn8l6NQ/3HAeRtDKl427csWNHs0NKxw9LMytSI3V2jsdomllF9HTVGBxxj6bZbJtSoClpnaQHmnyW549LPYYxQTWHbXy9EXFzRLyYrGfyihae59qI6I+I/vnz57eq2llV98PSzArU6NF06qyZVUVvZ4df0pu1wZReQUfE0on2SXpE0nERsS2lqT7a5LCtwJm57UXAnal80bjyren7IeuNiLskPV/SsYd5jsrr7epgYMgPSzMrxt40RtOps2ZWFb1dNR7fO1T0ZZgd8VqROnsr0JjhdQVwS5Nj7gDOljQ3TdBzNnBHSo3dLemMNBPshbnfN61X0gtzM9O+HOgBdh7mOSqvt6vG4MgoB4atmpm1z56UOuvlTcysKrKl4ZwNZjbbWtEyuBK4SdJFwEPAmwEk9QNvj4iLI2KXpCuAe9JvLo+IXen7pcD1QB24PX0mrBf4VeBCScPAAPDrKbX2cM5Reb1dNSJgaHSMnk6nrplZe3kyIDOrmt6uDi9vYtYGM24ZRMRO4Kwm5RuBi3Pbq4HVExx38jTqvQq4aoJrmdY5jgS9XVlwOTjsQNPM2q+ROjvHYzTNrCI8kaJZe7QiddYK1NuV/U/oB6aZFWH/ZEBOnTWzinCgadYeDjQrrrez0aPpB6aZtd/eoRHqXTVqHSr6UszMpqSnq8Mz9pu1gQPNisunzpqZtduT+0aZ4/GZZlYhvZ01hkbGGBvzRIpms8mBZsXVu506a2bF2bNvxOMzzaxSGi/p97lX02xWOdCsOKfOmlmR9g6NMMfjM82sQuqe38KsLRxoVlxPeivnabrNrAhPukfTzCqm120ns7ZwoFlxB2addfqHmbXfHo/RNLOKOTC/hQNNs9nkQLPi6vvHGfhhaWbtt2doxIGmWYtImidpraRN6e/cCY5bkY7ZJGlFrvxUSfdL2izpakmarF5JZ0p6QtK96fPeXF3LJH0/1XXZbN97O/klvVl7ONCsOL+VM7Mi7dk3wpxup86atchlwPqIWAysT9sHkTQPWAWcDpwGrMoFpNcAlwCL02fZFOr9SkQsSZ/L0zlqwMeAc4GTgAskndTSOy1QY9jRoF/Sm80qB5oVt3+cwZAflmbWfnudOmvWSsuBNen7GuC8JsecA6yNiF0R8RiwFlgm6Tjg6IjYEBEB3JD7/VTqzTsN2BwRD0bEEHBjquOI4IkUzdrDgWbF7U//8BTdZtZmEZGlznrWWbNWWRAR29L37cCCJscsBB7ObW9JZQvT9/Hlh6r3v0j6lqTbJb3kEOc4IjTaTvucOms2q9w6qDi/lTOzogwMjzIWuEfTbBqWLl3K9u3bm+06Jr8RESEpWn3+cfV+E3huRDwp6fXA58lSbqdM0kpgJcAJJ5zQ0mudLR52ZNYebh1UXEeH6O7s8IB2M2u7PfuyRtpRXt7EbMrWrVvXtFzS48CopOMiYltKhX20yaFbgTNz24uAO1P5onHlW9P3R5rVGxG7GwdHxG2SPi7p2PS74yeo6yARcS1wLUB/f3/LA+PZUPfyJmZt4dTZI0BvZ4ffyplZ2+3ZNwJAn1NnzVrlVqAxi+wK4JYmx9wBnC1pbpoE6GzgjpQau1vSGWm22Qtzv29ar6Rn52amPY2sXbgTuAdYLOl5krqB81MdR4QDPZp+SW82m9w6OAL0dtUcaJpZ2+0ZygJNp86atcyVwE2SLgIeAt4MIKkfeHtEXBwRuyRdQRYMAlweEbvS90uB64E6cHv6TFgv8CbgdySNAAPA+WkioRFJ7yQLamvA6oj49mzddLsdWN7EbSez2eTWwRHAgaaZFeFA6qz/KTFrhYjYCZzVpHwjcHFuezWweoLjTp5GvR8FPjrBtdwG3DaNy6+MXi9vYtYWTp09AtS7ak7/MLO225866zGaZlYhPZ2NHk23ncxmkwPNI0BvV4ffyplZ2zVSZ92jaWZVIomezg72ORvMbFY50DwC9HTVGBjyw9LM2uvAZEDu0TSzavGwI7PZN6NAU9I8SWslbUp/505w3Ip0zCZJK3Llp0q6X9JmSVfnZj5rWq+k5ZLuk3SvpI2SXpXKl0j6mqRvp/2/njvH9ZJ+lH5zr6QlM7nnMurtqjE44vQPM2uvG709RQAAIABJREFUJz1G08wqqrerw8ubmM2ymfZoXgasj4jFwPq0fRBJ84BVwOnAacCqXEB6DXAJ2eLAi4Flh6h3PXBKRCwB3gZcl8r3AhdGxEtSHR+RlF/4+P+2d/+xlp/1feDfHzwYJ9RAFg9Z5BmwUYbAxKkW965LFG0gC6VjR/J0RcXaEkqIXCwIRl2RjeqIiiCjlZZGIRKSWzpVvfzogjFIbUfCrNVQI68QAx4EGNus2Ykh9Rg2Hozj3dTFZsKzf5yv4fpy78yZmeec8z3nvF7Skc6PZ+58nnvuvDXvc77fc/+gtfbfDJevneOeR+fnnu3wD2D+nvDrTYAl5fMtYPbOtWgeTPKR4fpHkvyDbdb8/ST/obX2g9baY0n+Q5IDwy8Mfl5r7cjwUdof3fTnt/26rbW/HtYmyXOTtOH+b7XW/u/h+ncz+UXEu89xb0vD4R/AIvz1Uydz/nnPyvm7nIUBLBf/d4LZO9f/Hfzi8AuCk+T/SfKL26y5OMlDm24fH+67eLi+9f5Tft2q+h+q6v9K8plM3tV8huEXDp+f5M833f2/DIfU/mlVPWenzVTV9cMhuUdPnDix07LRuWDXeQ7/AObuiSf/Js/1ibPAEnqO045g5k5bNKvqz6rq3m0uBzevG95pbDt8mbO29eu21v5ta+0VmbzL+b4ts744yceS/G5r7en0+MMkr0jy3yb5r5L8k1P8XYdaaxuttY3du5fnDdELnv0sh3/AOaiqW6rqkaq6d9N9O50rXsM55ceGF7Au3/RnupyPviz+85MnHTYLLKULdj3LO5owY6ctmq2117fWLtvm8u+T/OVQ7p4ueY9s8yUeTrJ30+09w30PD9e33p9pvm5r7a4kL6uqi4Z1z8vkXc53t9aObFr3vTbxZJL/LZPzRFfKBec7/APO0Yfz03PEn7bTueJX5qfnlV+fybnmvc9HXwp//eRJHwQELKULnn2ez7eAGTvXQ2cPJ3n6VfvfSfLvt1lzR5I3VNUvDP/pekOSO4ZDY//fqnr18Or+b2/689t+3ar6pU3vBFye5DlJHq2q85P82yQfba19evNfvqmwVibvgt6bFXPBrvPy5Mkf56enrwJnYnjh6gdb7t7pHPSDmWRNG17UesGQM93OR18WTzzl0FlgOTkaDGbvXF+K/l+T3FZV1yX5iyRvSpKq2kjyttbaP2qt/aCq3pfk7uHP3NRae/o/dL+XyTsJP5fks8Nlx6+b5I1JfruqfpTkvyT5H1trrarelOQ3krywqt4yrH3L8Amz/3tV7U5SSb6W5G3nuOfRueDZk//oPXnyxz+5Dpyznc4VP9V5593OR9+sqq7P5N3TvOQlLzmbvczEXz95Mhde4B1NYPlc8GyfbwGzdk7/Q2itPZrkddvcfzTJP9p0+5Ykt+yw7rIz+LrvT/L+be7/N0n+zQ4z/ven3MQKuODZkzem/8tTf6NowgwML2jN9JCBU/0drbVDSQ4lycbGxmgOXXjiqZP5r593waLHADhjF+xy2hHMms+kXwE/N5TLH54UmNDRTueKn+q88+7no4/Zf37yb/Jc52gCS+jnfL4FzJyiuQL+wasuztff84b84oXeWYCOdjoH/XAmh/BXVb06yePD4a/dzkdfFv/H//Tf5Y+u3r/oMQDO2P/89385/+c/WfmD3mChvBS9Ai549nkOmYVzUFWfSPLaJBdV1fFMPj12p3PFb09yVZJjSZ5I8rtJ0vl89KVw4QXPXvQIAGfFJ2bD7PlXBqy91tq1Ozy03bniLck7dvg6Xc5HBwBYdg6dBQAAoCtFEwAAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6qsmvhGOrqvr/kjyw6DmmdFGS7y96iCksy5zJ8sy6LHMm45j1pa213Que4ZzIpplZllmXZc7ErGdKPs3PGJ7vaZm1v2WZMxnHrGedTbt6T7JCHmitbSx6iGlU1dFlmHVZ5kyWZ9ZlmTNZrllHTjbNwLLMuixzJmZdU0uRT8v0fJu1v2WZM1muWbfj0FkAAAC6UjQBAADoStHc2aFFD3AGlmXWZZkzWZ5Zl2XOZLlmHbNl+j6atb9lmTMx6zpalu/jssyZmHUWlmXOZLlm/Rk+DAgAAICuvKMJAABAV4omAAAAXa190ayqA1X1QFUdq6obt3n8OVX1yeHxL1XVJfOfcqo531VV91fVPVX1uap66SLmHGY55ayb1r2xqlpVLexjm6eZtareNHxv76uqj897xmGG0z3/L6mqO6vqq8PPwFULmvOWqnqkqu7d4fGqqg8O+7inqi6f94zLYlmyaZhlKfJJNs2GfFo/y5JPy5JNwyxLkU+yaSZzrm42tdbW9pLkvCR/nuRlSc5P8vUk+7es+b0kHxquX5PkkyOd8zeT/Pxw/e2LmHPaWYd1Fya5K8mRJBtjnTXJviRfTfILw+0XjXTOQ0nePlzfn+Q7C/qe/kaSy5Pcu8PjVyX5bJJK8uokX1rEnGO/LEs2ncGsC88n2bTQWeXTCl2WJZ+WJZumnXVYt9B8kk0zm3Vls2nd39G8Ismx1tqDrbWnktya5OCWNQeTfGS4/ukkr6uqmuOMyRRzttbubK09Mdw8kmTPnGd82jTf0yR5X5L3J/nhPIfbYppZ35rk5tbaY0nSWntkzjMm083ZkjxvuP78JN+d43w/HaK1u5L84BRLDib5aJs4kuQFVfXi+Uy3VJYlm5LlySfZNBvyaf0sSz4tSzYly5NPsmkGVjmb1r1oXpzkoU23jw/3bbumtXYyyeNJXjiX6baZYbDdnJtdl8krH4tw2lmHt/z3ttY+M8/BtjHN9/XlSV5eVV+oqiNVdWBu0/3UNHO+N8mbq+p4ktuTvHM+o52xM/1ZXlfLkk3PmGMw1nySTbMhn9bPsuTTsmRTsjz5JJsWY2mzadeiB6Cvqnpzko0kr1n0LNupqmcl+UCStyx4lGntyuQwkNdm8krnXVX1q621v1roVD/r2iQfbq39SVX9WpKPVdVlrbUfL3oweNqY80k2zZR8YtTGnE3J0uWTbOIn1v0dzYeT7N10e89w37ZrqmpXJm+tPzqX6baZYbDdnKmq1yd5d5KrW2tPzmm2rU4364VJLkvy+ar6TibHmh9e0Ent03xfjyc53Fr7UWvt20m+lUmAztM0c16X5LYkaa19MckFSS6ay3RnZqqfZZYmm54xx2Cs+SSbZkM+rZ9lyadlyaZkefJJNi3G8mbTok8SXeQlk1ddHkxyaX56ovCvbFnzjjzzhPbbRjrnqzI56Xnf2L+nW9Z/Pov7wI1pvq8HknxkuH5RJocuvHCEc342yVuG66/M5DyDWtD39ZLsfEL7b+WZJ7R/eREzjv2yLNl0BrMuPJ9k00JnlU8rdFmWfFqWbJp21i3rF5JPsmmm865kNi18gEVfMvkkp28NQfPu4b6bMnllK5m8uvGpJMeSfDnJy0Y6558l+cskXxsuh8f6Pd2ydiFheQbf18rkcJX7k3wjyTUjnXN/ki8MQfq1JG9Y0JyfSPK9JD/K5FXN65K8LcnbNn0/bx728Y1FPvdjvyxLNk056yjySTYtbFb5tGKXZcmnZcmmaWbdsnZh+SSbZjLnymZTDRsAAACALtb9HE0AAAA6UzQBAADoStEEAACgK0UTAACArhRNAAAAulI0AQAA6ErRBAAAoCtFEwAAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6UjQBAADoStEEAACgK0UTAACArhRNAAAAulI0AQAA6ErRBAAAoCtFEwAAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6UjQBAADoStEEAACgK0UTAACArpa+aFbVLVX1SFXdu8PjVVUfrKpjVXVPVV0+7xmB9SSfgDGSTcA8LH3RTPLhJAdO8fiVSfYNl+uT/Is5zASQyCdgnD4c2QTM2NIXzdbaXUl+cIolB5N8tE0cSfKCqnrxfKYD1pl8AsZINgHzsGvRA8zBxUke2nT7+HDf97YurKrrM3nlLs997nP/zite8Yq5DAjMx1e+8pXvt9Z2L3qOTabKJ9kEq29k+eT/TkCSc8umdSiaU2utHUpyKEk2Njba0aNHFzwR0FNV/cWiZzgbsglWn3wCxuhcsmnpD52dwsNJ9m66vWe4D2DR5BMwRrIJOGfrUDQPJ/nt4RPUXp3k8dbazxz6AbAA8gkYI9kEnLOlP3S2qj6R5LVJLqqq40n+KMmzk6S19qEktye5KsmxJE8k+d3FTAqsG/kEjJFsAuZh6Ytma+3a0zzekrxjTuMA/IR8AsZINgHzsA6HzgIAADBHiiYAAABdKZoAAAB0pWgCAADQlaIJAABAV4omAAAAXSmaAAAAdKVoAgAA0JWiCQAAQFeKJgAAAF0pmgAAAHSlaAIAANCVogkAAEBXiiYAAABdKZoAAAB0pWgCAADQlaIJAABAV4omAAAAXSmaAAAAdKVoAgAA0JWiCQAAQFeKJgAAAF0pmgAAAHSlaAIAANCVogkAAEBXiiYAAABdKZoAAAB0pWgCAADQlaIJAABAV4omAAAAXSmaAAAAdKVoAgAA0JWiCQAAQFeKJgAAAF0pmgAAAHSlaAIAANCVogkAAEBXiiYAAABdKZoAAAB0tRJFs6oOVNUDVXWsqm7c5vGXVNWdVfXVqrqnqq5axJzAepFNwFjJJ2DWlr5oVtV5SW5OcmWS/Umurar9W5b90yS3tdZeleSaJP98vlMC60Y2AWMln4B5WPqimeSKJMdaaw+21p5KcmuSg1vWtCTPG64/P8l35zgfsJ5kEzBW8gmYuVUomhcneWjT7ePDfZu9N8mbq+p4ktuTvHO7L1RV11fV0ao6euLEiVnMCqwP2QSMlXwCZm4ViuY0rk3y4dbaniRXJflYVf3M3ltrh1prG621jd27d899SGDtyCZgrOQTcE5WoWg+nGTvptt7hvs2uy7JbUnSWvtikguSXDSX6YB1JZuAsZJPwMytQtG8O8m+qrq0qs7P5IT1w1vW/Kckr0uSqnplJmHp+A5glmQTMFbyCZi5pS+arbWTSW5IckeSb2byCWn3VdVNVXX1sOz3k7y1qr6e5BNJ3tJaa4uZGFgHsgkYK/kEzMOuRQ/QQ2vt9kxOVN9833s2Xb8/ya/Pey5gvckmYKzkEzBrS/+OJgAAAOOiaAIAANCVogkAAEBXiiYAAABdKZoAAAB0pWgCAADQlaIJAABAV4omAAAAXSmaAAAAdKVoAgAA0JWiCQAAQFeKJgAAAF0pmgAAAHSlaAIAANCVogkAAEBXiiYAAABdKZoAAAB0pWgCAADQlaIJAABAV4omAAAAXSmaAAAAdKVoAgAA0JWiCQAAQFeKJgAAAF0pmgAAAHSlaAIAANCVogkAAEBXiiYAAABdKZoAAAB0pWgCAADQlaIJAABAV4omAAAAXSmaAAAAdKVoAgAA0JWiCQAAQFeKJgAAAF0pmgAAAHSlaAIAANCVogkAAEBXK1E0q+pAVT1QVceq6sYd1rypqu6vqvuq6uPznhFYP7IJGCv5BMzarkUPcK6q6rwkNyf5e0mOJ7m7qg631u7ftGZfkj9M8uuttceq6kWLmRZYF7IJGCv5BMzDKryjeUWSY621B1trTyW5NcnBLWvemuTm1tpjSdJae2TOMwLrRzYBYyWfgJlbhaJ5cZKHNt0+Pty32cuTvLyqvlBVR6rqwHZfqKqur6qjVXX0xIkTMxoXWBOyCRgr+QTM3CoUzWnsSrIvyWuTXJvkX1XVC7Yuaq0daq1ttNY2du/ePecRgTUkm4Cxkk/AOVmFovlwkr2bbu8Z7tvseJLDrbUftda+neRbmYQnwKzIJmCs5BMwc6tQNO9Osq+qLq2q85Nck+TwljX/LpNX5FJVF2VyOMiD8xwSWDuyCRgr+QTM3NIXzdbaySQ3JLkjyTeT3NZau6+qbqqqq4dldyR5tKruT3Jnkj9orT26mImBdSCbgLGST8A8VGtt0TOM0sbGRjt69OiixwA6qqqvtNY2Fj3HuZBNsJrkEzBG55JNS/+OJgAAAOOiaAIAANCVogkAAEBXiiYAAABdKZoAAAB0pWgCAADQlaIJAABAV4omAAAAXSmaAAAAdKVoAgAA0JWiCQAAQFeKJgAAAF0pmgAAAHSlaAIAANCVogkAAEBXiiYAAABdKZoAAAB0pWgCAADQlaIJAABAV4omAAAAXSmaAAAAdKVoAgAA0JWiCQAAQFeKJgAAAF0pmgAAAHSlaAIAANCVogkAAEBXiiYAAABdKZoAAAB0pWgCAADQlaIJAABAV4omAAAAXSmaAAAAdKVoAgAA0JWiCQAAQFeKJgAAAF0pmgAAAHSlaAIAANCVogkAAEBXK1E0q+pAVT1QVceq6sZTrHtjVbWq2pjnfMB6kk3AWMknYNaWvmhW1XlJbk5yZZL9Sa6tqv3brLswyT9O8qX5TgisI9kEjJV8AuZh6YtmkiuSHGutPdhaeyrJrUkObrPufUnen+SH8xwOWFuyCRgr+QTM3CoUzYuTPLTp9vHhvp+oqsuT7G2tfeZUX6iqrq+qo1V19MSJE/0nBdaJbALGSj4BM7cKRfOUqupZST6Q5PdPt7a1dqi1ttFa29i9e/fshwPWlmwCxko+AT2sQtF8OMneTbf3DPc97cIklyX5fFV9J8mrkxx2UjswY7IJGCv5BMzcKhTNu5Psq6pLq+r8JNckOfz0g621x1trF7XWLmmtXZLkSJKrW2tHFzMusCZkEzBW8gmYuaUvmq21k0luSHJHkm8mua21dl9V3VRVVy92OmBdySZgrOQTMA+7Fj1AD62125PcvuW+9+yw9rXzmAlANgFjJZ+AWVv6dzQBAAAYF0UTAACArhRNAAAAulI0AQAA6ErRBAAAoCtFEwAAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6UjQBAADoStEEAACgK0UTAACArhRNAAAAulI0AQAA6ErRBAAAoCtFEwAAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6UjQBAADoStEEAACgK0UTAACArhRNAAAAulI0AQAA6ErRBAAAoCtFEwAAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6UjQBAADoStEEAACgK0UTAACArhRNAAAAulqJollVB6rqgao6VlU3bvP4u6rq/qq6p6o+V1UvXcScwHqRTcBYySdg1pa+aFbVeUluTnJlkv1Jrq2q/VuWfTXJRmvtbyf5dJJ/Nt8pgXUjm4Cxkk/APCx90UxyRZJjrbUHW2tPJbk1ycHNC1prd7bWnhhuHkmyZ84zAutHNgFjJZ+AmVuFonlxkoc23T4+3LeT65J8drsHqur6qjpaVUdPnDjRcURgDckmYKzkEzBzq1A0p1ZVb06ykeSPt3u8tXaotbbRWtvYvXv3fIcD1pZsAsZKPgFna9eiB+jg4SR7N93eM9z3DFX1+iTvTvKa1tqTc5oNWF+yCRgr+QTM3Cq8o3l3kn1VdWlVnZ/kmiSHNy+oqlcl+ZdJrm6tPbKAGYH1I5uAsZJPwMwtfdFsrZ1MckOSO5J8M8ltrbX7quqmqrp6WPbHSf5Wkk9V1deq6vAOXw6gC9kEjJV8AuZhFQ6dTWvt9iS3b7nvPZuuv37uQwFrTzYBYyWfgFlb+nc0AQAAGBdFEwAAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6UjQBAADoStEEAACgK0UTAACArhRNAAAAulI0AQAA6ErRBAAAoCtFEwAAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6UjQBAADoStEEAACgK0UTAACArhRNAAAAulI0AQAA6ErRBAAAoCtFEwAAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6UjQBAADoStEEAACgK0UTAACArhRNAAAAulI0AQAA6ErRBAAAoCtFEwAAgK4UTQAAALpaiaJZVQeq6oGqOlZVN27z+HOq6pPD41+qqkvmPyWwbmQTMFbyCZi1pS+aVXVekpuTXJlkf5Jrq2r/lmXXJXmstfZLSf40yfvnOyWwbmQTMFbyCZiHpS+aSa5Icqy19mBr7akktyY5uGXNwSQfGa5/OsnrqqrmOCOwfmQTMFbyCZi5XYseoIOLkzy06fbxJH93pzWttZNV9XiSFyb5/uZFVXV9kuuHm09W1b0zmXh+LsqWPS6hVdhDshr7WIU9/PIc/y7ZdGqr8PNkD+OwCntI5NNYrMLPkz2Mxyrs46yzaRWKZjettUNJDiVJVR1trW0seKRzYg/jsQr7WJU9LHqGs7Fq2ZSsxj7sYRxWYQ+JfBoLexiHVdhDshr7OJdsWoVDZx9OsnfT7T3DfduuqapdSZ6f5NG5TAesK9kEjJV8AmZuFYrm3Un2VdWlVXV+kmuSHN6y5nCS3xmu/8Mk/7G11uY4I7B+ZBMwVvIJmLmlP3R2OG/ghiR3JDkvyS2ttfuq6qYkR1trh5P86yQfq6pjSX6QSaCezqGZDT0/9jAeq7APezgDsum0VmEf9jAOq7CHRD6NhT2MwyrsIVmNfZz1HsqLUwAAAPS0CofOAgAAMCKKJgAAAF2tfdGsqgNV9UBVHauqG7d5/DlV9cnh8S9V1SXzn/LUptjDu6rq/qq6p6o+V1UvXcScp3K6PWxa98aqalU1uo+KnmYPVfWm4bm4r6o+Pu8ZpzHFz9NLqurOqvrq8DN11SLm3ElV3VJVj+z0u9xq4oPD/u6pqsvnPeM0ZNN4yKdxWPZsSuTTmKxCPsmmcZBNp9BaW9tLJifA/3mSlyU5P8nXk+zfsub3knxouH5Nkk8ueu6z2MNvJvn54frbl3EPw7oLk9yV5EiSjUXPfRbPw74kX03yC8PtFy167rPcx6Ekbx+u70/ynUXPvWW+30hyeZJ7d3j8qiSfTVJJXp3kS4ue+SyfB9k0kn0M6+TT4vcw6mwa5pJPI7isQj7JpnFcZNOpL+v+juYVSY611h5srT2V5NYkB7esOZjkI8P1Tyd5XVXVHGc8ndPuobV2Z2vtieHmkUx+X9aYTPM8JMn7krw/yQ/nOdyUptnDW5Pc3Fp7LElaa4/MecZpTLOPluR5w/XnJ/nuHOc7rdbaXZl8QuJODib5aJs4kuQFVfXi+Uw3Ndk0HvJpHJY+mxL5NMcZT2cV8kk2jYNsOoV1L5oXJ3lo0+3jw33brmmtnUzyeJIXzmW66Uyzh82uy+QViTE57R6Gt+j3ttY+M8/BzsA0z8PLk7y8qr5QVUeq6sDcppveNPt4b5I3V9XxJLcneed8RuvmTP/NLIJsGg/5NA7rkE2JfJqXVcgn2TQOsukUlv73aDK9qnpzko0kr1n0LGeiqp6V5ANJ3rLgUc7VrkwOAXltJq+M3lVVv9pa+6uFTnXmrk3y4dban1TVr2Xye9Yua639eNGDsZyWNZsS+TQysonuljWfZNOorG02rfs7mg8n2bvp9p7hvm3XVNWuTN7yfnQu001nmj2kql6f5N1Jrm6tPTmn2aZ1uj1cmOSyJJ+vqu9kcmz44ZGd1D7N83A8yeHW2o9aa99O8q1MwnNMptnHdUluS5LW2heTXJDkorlM18dU/2YWTDaNh3wah3XIpkQ+zcsq5JNsGgfZdCqzPrl0zJdMXiV5MMml+ekJvL+yZc078swT2m9b9NxnsYdXZXKi8r5Fz3u2e9iy/vMZ3wnt0zwPB5J8ZLh+USaHILxw0bOfxT4+m+Qtw/VXZnKuQS169i0zXpKdT2j/rTzzhPYvL3res3weZNNI9rFlvXxa3B5Gn03DbPJpOfYw6nySTYuf/wz2sLbZtPBNLfqSyacofWsIk3cP992UyatXyeRVh08lOZbky0letuiZz2IPf5bkL5N8bbgcXvTMZ7qHLWtHF5ZTPg+VyWEs9yf5RpJrFj3zWe5jf5IvDGH6tSRvWPTMW+b/RJLvJflRJq+EXpfkbUnetul5uHnY3zfG+LM05fMgm0ayjy1r5dPi9jDqbBpmlE8juaxCPsmmcVxk086XGv4wAAAAdLHu52gCAADQmaIJAABAV4omAAAAXSmaAAAAdKVoAgAA0JWiCQAAQFeKJgAAAF0pmgAAAHSlaAIAANCVogkAAEBXiiYAAABdKZoAAAB0pWgCAADQlaIJAABAV4omAAAAXSmaAAAAdKVoAgAA0JWiCQAAQFeKJgAAAF0pmgAAAHSlaAIAANCVogkAAEBXiiYAAABdKZoAAAB0pWgCAADQlaIJAABAV4omAAAAXSmaAAAAdLX0RbOqbqmqR6rq3h0er6r6YFUdq6p7quryec8IrCf5BIyRbALmYemLZpIPJzlwisevTLJvuFyf5F/MYSaARD4B4/ThyCZgxpa+aLbW7kryg1MsOZjko23iSJIXVNWL5zMdsM7kEzBGsgmYh12LHmAOLk7y0Kbbx4f7vrd1YVVdn8krd3nuc5/7d17xilfMZUBgPr7yla98v7W2e9FzbDJVPskmWH0jyyf/dwKSnFs2rUPRnFpr7VCSQ0mysbHRjh49uuCJgJ6q6i8WPcPZkE2w+uQTMEbnkk1Lf+jsFB5OsnfT7T3DfQCLJp+AMZJNwDlbh6J5OMlvD5+g9uokj7fWfubQD4AFkE/AGMkm4Jwt/aGzVfWJJK9NclFVHU/yR0menSSttQ8luT3JVUmOJXkiye8uZlJg3cgnYIxkEzAPS180W2vXnubxluQdcxoH4CfkEzBGsgmYh3U4dBYAAIA5UjQBAADoStEEAACgK0UTAACArhRNAAAAulI0AQAA6ErRBAAAoCtFEwAAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6UjQBAADoStEEAACgK0UTAACArhRNAAAAulI0AQAA6ErRBAAAoCtFEwA2fJCUAAAQnElEQVQAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6UjQBAADoStEEAACgK0UTAACArhRNAAAAulI0AQAA6ErRBAAAoCtFEwAAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6UjQBAADoStEEAACgq5UomlV1oKoeqKpjVXXjNo+/pKrurKqvVtU9VXXVIuYE1otsAsZKPgGztvRFs6rOS3JzkiuT7E9ybVXt37Lsnya5rbX2qiTXJPnn850SWDeyCRgr+QTMw9IXzSRXJDnWWnuwtfZUkluTHNyypiV53nD9+Um+O8f5gPUkm4Cxkk/AzK1C0bw4yUObbh8f7tvsvUneXFXHk9ye5J3bfaGqur6qjlbV0RMnTsxiVmB9yCZgrOQTMHOrUDSncW2SD7fW9iS5KsnHqupn9t5aO9Ra22itbezevXvuQwJrRzYBYyWfgHOyCkXz4SR7N93eM9y32XVJbkuS1toXk1yQ5KK5TAesK9kEjJV8AmZuFYrm3Un2VdWlVXV+JiesH96y5j8leV2SVNUrMwlLx3cAsySbgLGST8DMLX3RbK2dTHJDkjuSfDOTT0i7r6puqqqrh2W/n+StVfX1JJ9I8pbWWlvMxMA6kE3AWMknYB52LXqAHlprt2dyovrm+96z6fr9SX593nMB6002AWMln4BZW/p3NAEAABgXRRMAAICuFE0AAAC6UjQBAADoStEEAACgK0UTAACArhRNAAAAulI0AQAA6ErRBAAAoCtFEwAAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6UjQBAADoStEEAACgK0UTAACArhRNAAAAulI0AQAA6ErRBAAAoCtFEwAAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6UjQBAADoStEEAACgK0UTAACArhRNAAAAulI0AQAA6ErRBAAAoCtFEwAAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6WomiWVUHquqBqjpWVTfusOZNVXV/Vd1XVR+f94zA+pFNwFjJJ2DWdi16gHNVVecluTnJ30tyPMndVXW4tXb/pjX7kvxhkl9vrT1WVS9azLTAupBNwFjJJ2AeVuEdzSuSHGutPdhaeyrJrUkOblnz1iQ3t9YeS5LW2iNznhFYP7IJGCv5BMzcKhTNi5M8tOn28eG+zV6e5OVV9YWqOlJVB7b7QlV1fVUdraqjJ06cmNG4wJqQTcBYySdg5lahaE5jV5J9SV6b5Nok/6qqXrB1UWvtUGtto7W2sXv37jmPCKwh2QSMlXwCzskqFM2Hk+zddHvPcN9mx5Mcbq39qLX27STfyiQ8AWZFNgFjJZ+AmVuFonl3kn1VdWlVnZ/kmiSHt6z5d5m8IpequiiTw0EenOeQwNqRTcBYySdg5pa+aLbWTia5IckdSb6Z5LbW2n1VdVNVXT0suyPJo1V1f5I7k/xBa+3RxUwMrAPZBIyVfALmoVpri55hlDY2NtrRo0cXPQbQUVV9pbW2seg5zoVsgtUkn4AxOpdsWvp3NAEAABgXRRMAAICuFE0AAAC6UjQBAADoStEEAACgK0UTAACArhRNAAAAulI0AQAA6ErRBAAAoCtFEwAAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6UjQBAADoStEEAACgK0UTAACArhRNAAAAulI0AQAA6ErRBAAAoCtFEwAAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6UjQBAADoStEEAACgK0UTAACArhRNAAAAulI0AQAA6ErRBAAAoCtFEwAAgK4UTQAAALpSNAEAAOhK0QQAAKArRRMAAICuFE0AAAC6WomiWVUHquqBqjpWVTeeYt0bq6pV1cY85wPWk2wCxko+AbO29EWzqs5LcnOSK5PsT3JtVe3fZt2FSf5xki/Nd0JgHckmYKzkEzAPS180k1yR5Fhr7cHW2lNJbk1ycJt170vy/iQ/nOdwwNqSTcBYySdg5lahaF6c5KFNt48P9/1EVV2eZG9r7TOn+kJVdX1VHa2qoydOnOg/KbBOZBMwVvIJmLlVKJqnVFXPSvKBJL9/urWttUOttY3W2sbu3btnPxywtmQTMFbyCehhFYrmw0n2brq9Z7jvaRcmuSzJ56vqO0leneSwk9qBGZNNwFjJJ2DmVqFo3p1kX1VdWlXnJ7kmyeGnH2ytPd5au6i1dklr7ZIkR5Jc3Vo7uphxgTUhm4Cxkk/AzC190WytnUxyQ5I7knwzyW2ttfuq6qaqunqx0wHrSjYBYyWfgHnYtegBemit3Z7k9i33vWeHta+dx0wAsgkYK/kEzNrSv6MJAADAuCiaAAAAdKVoAgAA0JWiCQAAQFeKJgAAAF0pmgAAAHSlaAIAANCVogkAAEBXiiYAAABdKZoAAAB0pWgCAADQlaIJAABAV4omAAAAXSmaAAAAdKVoAgAA0JWiCQAAQFeKJgAAAF0pmgAAAHSlaAIAANCVogkAAEBXiiYAAABdKZoAAAB0pWgCAADQlaIJAABAV4omAAAAXSmaAAAAdKVoAgAA0JWiCQAAQFeKJgAAAF0pmgAAAHSlaAIAANCVogkAAEBXiiYAAABdKZoAAAB0pWgCAADQlaIJAABAV4omAAAAXSmaAAAAdKVoAgAA0NVKFM2qOlBVD1TVsaq6cZvH31VV91fVPVX1uap66SLmBNaLbALGSj4Bs7b0RbOqzktyc5Irk+xPcm1V7d+y7KtJNlprfzvJp5P8s/lOCawb2QSMlXwC5mHpi2aSK5Ica6092Fp7KsmtSQ5uXtBau7O19sRw80iSPXOeEVg/sgkYK/kEzNwqFM2Lkzy06fbx4b6dXJfks9s9UFXXV9XRqjp64sSJjiMCa0g2AWMln4CZW4WiObWqenOSjSR/vN3jrbVDrbWN1trG7t275zscsLZkEzBW8gk4W7sWPUAHDyfZu+n2nuG+Z6iq1yd5d5LXtNaenNNswPqSTcBYySdg5lbhHc27k+yrqkur6vwk1yQ5vHlBVb0qyb9McnVr7ZEFzAisH9kEjJV8AmZu6Ytma+1kkhuS3JHkm0lua63dV1U3VdXVw7I/TvK3knyqqr5WVYd3+HIAXcgmYKzkEzAPq3DobFprtye5fct979l0/fVzHwpYe7IJGCv5BMza0r+jCQAAwLgomgAAAHSlaAIAANCVogkAAEBXiiYAAABdKZoAAAB0pWgCAADQlaIJAABAV4omAAAAXSmaAAAAdKVoAgAA0JWiCQAAQFeKJgAAAF0pmgAAAHSlaAIAANCVogkAAEBXiiYAAABdKZoAAAB0pWgCAADQlaIJAABAV4omAAAAXSmaAAAAdKVoAgAA0JWiCQAAQFeKJgAAAF0pmgAAAHSlaAIAANCVogkAAEBXiiYAAABdKZoAAAB0pWgCAADQlaIJAABAV4omAAAAXSmaAAAAdKVoAgAA0JWiCQAAQFeKJgAAAF0pmgAAAHSlaAIAANDVShTNqjpQVQ9U1bGqunGbx59TVZ8cHv9SVV0y/ymBdSObgLGST8CsLX3RrKrzktyc5Mok+5NcW1X7tyy7LsljrbVfSvKnSd4/3ymBdSObgLGST8A8LH3RTHJFkmOttQdba08luTXJwS1rDib5yHD900leV1U1xxmB9SObgLGST8DM7Vr0AB1cnOShTbePJ/m7O61prZ2sqseTvDDJ9zcvqqrrk1w/3Hyyqu6dycTzc1G27HEJrcIektXYxyrs4Zfn+HfJplNbhZ8nexiHVdhDIp/GYhV+nuxhPFZhH2edTatQNLtprR1KcihJqupoa21jwSOdE3sYj1XYx6rsYdEznI1Vy6ZkNfZhD+OwCntI5NNY2MM4rMIektXYx7lk0yocOvtwkr2bbu8Z7tt2TVXtSvL8JI/OZTpgXckmYKzkEzBzq1A0706yr6ourarzk1yT5PCWNYeT/M5w/R8m+Y+ttTbHGYH1I5uAsZJPwMwt/aGzw3kDNyS5I8l5SW5prd1XVTclOdpaO5zkXyf5WFUdS/KDTAL1dA7NbOj5sYfxWIV92MMZkE2ntQr7sIdxWIU9JPJpLOxhHFZhD8lq7OOs91BenAIAAKCnVTh0FgAAgBFRNAEAAOhq7YtmVR2oqgeq6lhV3bjN48+pqk8Oj3+pqi6Z/5SnNsUe3lVV91fVPVX1uap66SLmPJXT7WHTujdWVauq0X1U9DR7qKo3Dc/FfVX18XnPOI0pfp5eUlV3VtVXh5+pqxYx506q6paqemSn3+VWEx8c9ndPVV0+7xmnIZvGQz6Nw7JnUyKfxmQV8kk2jYNsOoXW2tpeMjkB/s+TvCzJ+Um+nmT/ljW/l+RDw/Vrknxy0XOfxR5+M8nPD9ffvox7GNZdmOSuJEeSbCx67rN4HvYl+WqSXxhuv2jRc5/lPg4leftwfX+S7yx67i3z/UaSy5Pcu8PjVyX5bJJK8uokX1r0zGf5PMimkexjWCefFr+HUWfTMJd8GsFlFfJJNo3jIptOfVn3dzSvSHKstfZga+2pJLcmObhlzcEkHxmufzrJ66qq5jjj6Zx2D621O1trTww3j2Ty+7LGZJrnIUnel+T9SX44z+GmNM0e3prk5tbaY0nSWntkzjNOY5p9tCTPG64/P8l35zjfabXW7srkExJ3cjDJR9vEkSQvqKoXz2e6qcmm8ZBP47D02ZTIpznOeDqrkE+yaRxk0ymse9G8OMlDm24fH+7bdk1r7WSSx5O8cC7TTWeaPWx2XSavSIzJafcwvEW/t7X2mXkOdgameR5enuTlVfWFqjpSVQfmNt30ptnHe5O8uaqOJ7k9yTvnM1o3Z/pvZhFk03jIp3FYh2xK5NO8rEI+yaZxkE2nsPS/R5PpVdWbk2wkec2iZzkTVfWsJB9I8pYFj3KudmVyCMhrM3ll9K6q+tXW2l8tdKozd22SD7fW/qSqfi2T37N2WWvtx4sejOW0rNmUyKeRkU10t6z5JJtGZW2zad3f0Xw4yd5Nt/cM9227pqp2ZfKW96NzmW460+whVfX6JO9OcnVr7ck5zTat0+3hwiSXJfl8VX0nk2PDD4/spPZpnofjSQ631n7UWvt2km9lEp5jMs0+rktyW5K01r6Y5IIkF81luj6m+jezYLJpPOTTOKxDNiXyaV5WIZ9k0zjIplOZ9cmlY75k8irJg0kuzU9P4P2VLWvekWee0H7bouc+iz28KpMTlfctet6z3cOW9Z/P+E5on+Z5OJDkI8P1izI5BOGFi579LPbx2SRvGa6/MpNzDWrRs2+Z8ZLsfEL7b+WZJ7R/edHznuXzIJtGso8t6+XT4vYw+mwaZpNPy7GHUeeTbFr8/Gewh7XNpoVvatGXTD5F6VtDmLx7uO+mTF69SiavOnwqybEkX07yskXPfBZ7+LMkf5nka8Pl8KJnPtM9bFk7urCc8nmoTA5juT/JN5Jcs+iZz3If+5N8YQjTryV5w6Jn3jL/J5J8L8mPMnkl9Lokb0vytk3Pw83D/r4xxp+lKZ8H2TSSfWxZK58Wt4dRZ9Mwo3wayWUV8kk2jeMim3a+1PCHAQAAoIt1P0cTAACAzhRNAAAAulI0AQAA6ErRBAAAoCtFEwAAgK4UTQAAALpSNAEAAOjq/wdaoByeT80AywAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x1080 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# #copy output of Thompson et al1\n",
    "# merge solutions \n",
    "humanHG=os.path.join(fh,'temp','humanHG')\n",
    "humanHGplusI=os.path.join(fh,'temp','humanHGplusI')\n",
    "humanHG_withHairPC=os.path.join(fh,'temp','humanHG_withHairPC')\n",
    "t,sol,se,sOut,qt,lut,lutSE=runSolver.loadSolutionFromDir(targetDir)\n",
    "fig, axs = matplotlib.pyplot.subplots(3, 3,figsize=(15,15))\n",
    "cName=['liverI']\n",
    "cName=['hair']\n",
    "pName=['bodyWeight','kHScaled','gutPC']\n",
    "\n",
    "tscale=scale\n",
    "max=[-1]*len(name)\n",
    "for row in range(len(cName)):\n",
    "    for col in range(len(pName)):\n",
    "        #row=i//3\n",
    "        #col=i%3\n",
    "        try:\n",
    "            fy=sOut[:,lut[cName[row]],lutSE[pName[col]]]\n",
    "        except KeyError:\n",
    "            continue\n",
    "        ax=axs[row,col]\n",
    "        ax.plot(qt/tscale,fy)\n",
    "        #if max[i]>0:\n",
    "        #    axs[row,col].set_ylim([0,max[i]])\n",
    "        axs[row,col].set_xlim([0,1.1*tmax/tscale])\n",
    "        axs[row,col].set_title('{}/{}'.format(cName[row],pName[col]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1800 with 15 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# #copy output of Thompson et al1\n",
    "# merge solutions \n",
    "fig, axs = matplotlib.pyplot.subplots(5, 3,figsize=(15,25))\n",
    "name=['arterial','adipose','brain','heart','kidney','liver','lung','muscle','skin',\n",
    "      'splanchnic','stomach','testes','excrement']\n",
    "name=['plasma','gut','hair','kidney','liver','inorganicMercury','redBloodCells','slowlyPerfused']\n",
    "\n",
    "#diazepam\n",
    "max=[1.5,2.6,3,4,5,2.5,6.8,1.5,1.5,4,4.2,3,25]\n",
    "#cotinine\n",
    "max=[9]*13\n",
    "max[12]=90\n",
    "max[2]=2\n",
    "\n",
    "tscale=scale\n",
    "max=[1000*x for x in max]\n",
    "for i in range(len(name)):\n",
    "    row=i//3\n",
    "    col=i%3\n",
    "    fy=sol[:,model.lut[name[i]]]\n",
    "    fe=se[:,model.lut[name[i]]]\n",
    "    fy1=solOld[:,model.lut[name[i]]]\n",
    "    fe1=seOld[:,model.lut[name[i]]]\n",
    "    ax=axs[row,col]\n",
    "    ax.plot(t/tscale,fy)\n",
    "    ax.plot(tOld/tscale,fy1,color='black')\n",
    "    ax.fill_between(t/tscale, fy-fe, fy + fe, color='red',alpha=0.1)\n",
    "    ax.plot(t/tscale,fy-fe,color='red',linewidth=1,alpha=0.2)\n",
    "    ax.plot(t/tscale,fy+fe,color='red',linewidth=1,alpha=0.2)\n",
    "    ax.fill_between(tOld/tscale, fy1-fe1, fy1 + fe1, color='black',alpha=0.1)\n",
    "    ax.plot(tOld/tscale,fy1-fe1,color='black',linewidth=1,alpha=0.2)\n",
    "    ax.plot(tOld/tscale,fy1+fe1,color='black',linewidth=1,alpha=0.2)\n",
    "    axs[row,col].set_title(name[i])\n",
    "    #axs[row,col].set_ylim([0,max[i]])\n",
    "    axs[row,col].set_xlim([0,1.1*tmax/tscale])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# #copy output of Thompson et al1\n",
    "# draw just the errors\n",
    "fig, axs = matplotlib.pyplot.subplots(3, 3,figsize=(15,25))\n",
    "name=['arterial','adipose','brain','heart','kidney','liver','lung','muscle','skin',\n",
    "      'splanchnic','stomach','testes','excrement']\n",
    "name=['plasma','gut','hair','kidney','liver','inorganicMercury','redBloodCells','slowlyPerfused']\n",
    "\n",
    "#diazepam\n",
    "max=[1.5,2.6,3,4,5,2.5,6.8,1.5,1.5,4,4.2,3,25]\n",
    "#cotinine\n",
    "max=[9]*13\n",
    "max[12]=90\n",
    "max[2]=2\n",
    "\n",
    "tscale=scale\n",
    "max=[1000*x for x in max]\n",
    "for i in range(len(name)):\n",
    "    row=i//3\n",
    "    col=i%3\n",
    "    fe=se[:,model.lut[name[i]]]\n",
    "    fe1=seOld[:,model.lut[name[i]]]\n",
    "    ax=axs[row,col]\n",
    "    ax.plot(t/tscale,fe)\n",
    "    ax.plot(tOld/tscale,fe1,color='black')\n",
    "    axs[row,col].set_title(name[i])\n",
    "    #axs[row,col].set_ylim([0,max[i]])\n",
    "    axs[row,col].set_xlim([0,1.1*tmax/tscale])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Drawing kHScaled 6/6\n"
     ]
    },
    {
     "ename": "ValueError",
     "evalue": "x and y must have same first dimension, but have shapes (671,) and (1458,)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-120-4ee25e5921c5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     28\u001b[0m     \u001b[0mfe1\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0ms1Old\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlut\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlutSE\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mparName\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     29\u001b[0m     \u001b[0max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mrow\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcol\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 30\u001b[0;31m     \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mt\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mtscale\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mfe\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     31\u001b[0m     \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mqtOld\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mtscale\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mfe1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'black'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     32\u001b[0m     \u001b[0maxs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mrow\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcol\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_title\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.8/site-packages/matplotlib/axes/_axes.py\u001b[0m in \u001b[0;36mplot\u001b[0;34m(self, scalex, scaley, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1645\u001b[0m         \"\"\"\n\u001b[1;32m   1646\u001b[0m         \u001b[0mkwargs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcbook\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnormalize_kwargs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmlines\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mLine2D\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1647\u001b[0;31m         \u001b[0mlines\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_lines\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1648\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mline\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mlines\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1649\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_line\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mline\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.8/site-packages/matplotlib/axes/_base.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    214\u001b[0m                 \u001b[0mthis\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    215\u001b[0m                 \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 216\u001b[0;31m             \u001b[0;32myield\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_plot_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mthis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    217\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    218\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mget_next_color\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.8/site-packages/matplotlib/axes/_base.py\u001b[0m in \u001b[0;36m_plot_args\u001b[0;34m(self, tup, kwargs)\u001b[0m\n\u001b[1;32m    340\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    341\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 342\u001b[0;31m             raise ValueError(f\"x and y must have same first dimension, but \"\n\u001b[0m\u001b[1;32m    343\u001b[0m                              f\"have shapes {x.shape} and {y.shape}\")\n\u001b[1;32m    344\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m2\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: x and y must have same first dimension, but have shapes (671,) and (1458,)"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1800 with 15 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# #copy output of Thompson et al1\n",
    "#draw error contributions\n",
    "fig, axs = matplotlib.pyplot.subplots(5, 3,figsize=(15,25))\n",
    "name=['arterial','adipose','brain','heart','kidney','liver','lung','muscle','skin',\n",
    "      'splanchnic','stomach','testes','excrement']\n",
    "name=['plasma','gut','hair','kidney','liver','redBloodCells','slowlyPerfused']\n",
    "\n",
    "#diazepam\n",
    "max=[1.5,2.6,3,4,5,2.5,6.8,1.5,1.5,4,4.2,3,25]\n",
    "#cotinine\n",
    "max=[9]*13\n",
    "max[12]=90\n",
    "max[2]=2\n",
    "\n",
    "tscale=scale\n",
    "ipar=6\n",
    "\n",
    "for nm in model.lutSE:\n",
    "    if model.lutSE[nm]==ipar:\n",
    "        parName=nm\n",
    "print('Drawing {} {}/{}'.format(parName,model.lutSE[parName],lutSE[parName]))\n",
    "        \n",
    "max=[1000*x for x in max]\n",
    "for i in range(len(name)):\n",
    "    row=i//3\n",
    "    col=i%3\n",
    "    fe=s1[:,model.lut[name[i]],model.lutSE[parName]]\n",
    "    fe1=s1Old[:,lut[name[i]],lutSE[parName]]\n",
    "    ax=axs[row,col]\n",
    "    ax.plot(t/tscale,fe)\n",
    "    ax.plot(qtOld/tscale,fe1,color='black')\n",
    "    axs[row,col].set_title(name[i])\n",
    "    #axs[row,col].set_ylim([0,max[i]])\n",
    "    axs[row,col].set_xlim([0,1.1*tmax/tscale])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "7440"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#gD=sys.get(\"hairGrowthDuration\")\n",
    "#print(gD['value']/60/24/365)\n",
    "print(model.lut['slowlyPerfused'])\n",
    "ft=[sys.fSS(x)[0,8,7] for x in qt]\n",
    "#matplotlib.pyplot.imshow(sys.fSS(3e6)[0])\n",
    "matplotlib.pyplot.plot(qt/tscale,ft)\n",
    "30*248"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}