syntheticData_MM.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "# Module 0: Generation of synthetic metabolomics & proteomics time-series data based on predetermined models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preliminary settings\n",
    "All output files will be appended with shelve_name to distinguish different runs of the notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:21.099669Z",
     "start_time": "2023-11-23T05:38:21.089714Z"
    }
   },
   "outputs": [],
   "source": [
    "shelve_name= '12strains_initial_design_seed1_' #'MM_4ptPerHr_'\n",
    "all_enzymes = ['AtoB', 'HMGS', 'HMGR', 'MK', 'PMK', 'PMD', 'GPPS', 'Idi','Limonene Synthase']\n",
    "all_metabolites = ['Acetyl-CoA','Acetoacetyl-CoA','HMG-CoA','Mev','MevP','MevPP','IPP','DMAPP','GPP','Limonene']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If set to 'True', unnecessary evaluations & plots are skipped to facilitate codes development.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import needed libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:23.323089Z",
     "start_time": "2023-11-23T05:38:21.100738Z"
    }
   },
   "outputs": [],
   "source": [
    "from IPython.display import display\n",
    "import pandas as pd\n",
    "from plot import *\n",
    "import seaborn as sns\n",
    "import math"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Define kinetic model\n",
    "\n",
    "ODEs of limonene pathway reactions as provided by Costello et al. 2018 & in the same order. \n",
    "\n",
    "Provided here to facilitate understanding & reconstruction of ODEs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:25.807078Z",
     "start_time": "2023-11-23T05:38:23.323089Z"
    },
    "code_folding": [],
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from KineticLearning import leaky_hill_fcn, proteomicsData\n",
    "    \n",
    "def kinetic_model(e1,e2,e3,e4,e5,e6,e7,e8,e9, #HC: 9\n",
    "                  s1,s2,s3,s4,s5,s6,s7,s8,s9,s10, #HC: 10\n",
    "                  k11,k12,k13,k21,k22,k23,k24,k31,k32,k33,k34,k35, #HC: 12 \n",
    "                  k41,k42,k43,k44,k45,k51,k52,k61,k62,k63,k64,k65, #HC: 12\n",
    "                  k71,k72,k81,k82,k83,k84,k91,k92,Vin,ks3): #HC: 10\n",
    "    #HC: 53 parameters (9+10+12+12+10)\n",
    "    r1 = Vin - (k11*e1*s1)/(k12 + k13*s1) - k21*e2*s1*s2*ks3 / (k22*s2 + k23*s1 + k24*s1*s2)\n",
    "    r2 = (k11*e1*s1)/(k12 + k13*s1) - k21*e2*s1*s2*ks3 / (k22*s2 + k23*s1 + k24*s1*s2)\n",
    "    r3 = k21*e2*s1*s2*ks3 / (k22*s2 + k23*s1 + k24*s1*s2) - k31*e3*s3 / (k32*s1 + k33*s2 + k34*s3 + k35)\n",
    "    r4 = k31*e3*s3 / (k32*s1 + k33*s2 + k34*s3 + k35) - k41*e4*s4 / (k42*s9 + k43*s6 + k44*s4 + k45) # k43*s6 NOT s5\n",
    "    r5 = k41*e4*s4 / (k42*s9 + k43*s6 + k44*s4 + k45) - k51*e5*s5 / (k52 + s5) # k43*s6 NOT s5\n",
    "    r6 = k51*e5*s5 / (k52 + s5) - k61*e6*s6 / (k62*s5 + k63*s4 + k64*s6 + k65)\n",
    "    r7 = k61*e6*s6 / (k62*s5 + k63*s4 + k64*s6 + k65) - k71*e7*s7 / (k72 + s7) - k81*e8*s7*s8 / (k82 + k83*s7 + k84*s8 + s7*s8)\n",
    "    r8 = k71*e7*s7 / (k72 + s7) - k81*e8*s7*s8 / (k82 + k83*s7 + k84*s8 + s7*s8)\n",
    "    r9 = k81*e8*s7*s8 / (k82 + k83*s7 + k84*s8 + s7*s8) - k91*e9*s9 / (k92 + s9)\n",
    "    r10 = k91*e9*s9 / (k92 + s9)\n",
    "    return [r1,r2,r3,r4,r5,r6,r7,r8,r9,r10]\n",
    "\n",
    "def kinetic_model_xtk(s,t,k):\n",
    "\n",
    "    # Return rate of reaction vector (r1, r2, ..., r10) based on e,s,kr\n",
    "    # s: metabolites conc vector\n",
    "    # t: time point for getting enzymes conc\n",
    "    # k: rate law parameters vector ('ke' followed by 'kr')\n",
    "    \n",
    "    #print('len of param vec',len(k))\n",
    "    #print('KineticCoefficients',k[3*9:],len(k[3*9:]))\n",
    "    #print('Proteomics',k[:3*9],len(k[:3*9]))\n",
    "    \n",
    "    # get e\n",
    "    ke = k[:3*9] #HC: 3 ke values for each of 9 enzymes\n",
    "    e = proteomicsData(t,ke)\n",
    "    \n",
    "    # get kr\n",
    "    kr = k[3*9:] #HC: rest of k are krs\n",
    "    #HC: check e,s,kr\n",
    "    #print(len(e),len(x),len(kr))\n",
    "\n",
    "    return kinetic_model(*e,*s,*kr) # list of 'r' "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# * SET rate constant kr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:25.838574Z",
     "start_time": "2023-11-23T05:38:25.807078Z"
    },
    "code_folding": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "34 kr parameters in same order as their input into kinetic_model function:\n",
      "[10.0, 316227766.01683795, 316227766.01683795, 100.0, 1000000000, 1000000000, 1000000000, 100.0, 100000000.0, 100000000.0, 100000000.0, 100000000.0, 100.0, 100000000.0, 100000000.0, 100000000.0, 100000000.0, 100.0, 100000000.0, 10.0, 100000000.0, 100000000.0, 100000000.0, 10000000.0, 10.0, 10000000.0, 1000.0, 1000000.0, 100000000.0, 100000000.0, 10.0, 100000000.0, 0.05, 1.2589254117941673]\n"
     ]
    }
   ],
   "source": [
    "# Underlying Kr\n",
    "kr = [\n",
    "    1e+01, 10**8.5,10**8.5, # AtoB\n",
    "    1e+02, 10**9, 10**9, 10**9, # HMGS\n",
    "    1e+02, 1e+08, 1e+08, 1e+08, 1e+08, # HMGR\n",
    "    1e+02, 1e+08, 1e+08, 1e+08, 1e+08, # MK        \n",
    "    1e+02, 1e+08, # PMK\n",
    "    1e+01, 1e+08, 1e+08, 1e+08, 1e+07, # PMD\n",
    "    1e+01, 1e+07, # IDI \n",
    "    1e+03, 1e+06, 1e+08, 1e+08, # GPPS\n",
    "    1e+01, 1e+08, # LS\n",
    "    0.05, 10**0.1] # Vin set to 0.05, ks3\n",
    "\n",
    "#G3PCX_MM_predict_30mins_woAugment__Salvgo53\n",
    "# kr=[12.249794599814333,\n",
    "#  388160105.0004492,\n",
    "#  387342264.0062811,\n",
    "#  5.61505869031139,\n",
    "#  64669675.73631207,\n",
    "#  66235005.493073665,\n",
    "#  79078016.35809003,\n",
    "#  4.300351052654894,\n",
    "#  4595717.027647343,\n",
    "#  5612162.058193444,\n",
    "#  3192876.7174923127,\n",
    "#  4305152.23632164,\n",
    "#  28.438552235536594,\n",
    "#  22951893.497071993,\n",
    "#  9876994.45606166,\n",
    "#  61860774.53467485,\n",
    "#  30358276.81516579,\n",
    "#  100.26002148271701,\n",
    "#  102551693.53016345,\n",
    "#  13.696638286654746,\n",
    "#  141180608.69227558,\n",
    "#  144046458.9656884,\n",
    "#  137263542.61193705,\n",
    "#  13804982.909885291,\n",
    "#  5.688048882247,\n",
    "#  5784296.6345550185,\n",
    "#  408.90190136712806,\n",
    "#  412175.2784468551,\n",
    "#  41500104.15322663,\n",
    "#  41368452.63707604,\n",
    "#  35.117777805076216,\n",
    "#  353198746.2830949,\n",
    "#  0.05, 1.4801445145680407]\n",
    "\n",
    "# 1 hrly wo augment SRES\n",
    "# kr=[3.3460065747806413,\n",
    "#  106607884.80957624,\n",
    "#  105616258.08774601,\n",
    "#  7.887640652521176,\n",
    "#  232839014.9742311,\n",
    "#  220203178.4359031,\n",
    "#  255604934.28320915,\n",
    "#  16.448038353375427,\n",
    "#  22045631.478199195,\n",
    "#  18287345.077777237,\n",
    "#  28832071.081930477,\n",
    "#  16522319.39596863,\n",
    "#  24.108463548815127,\n",
    "#  24851393.72413213,\n",
    "#  2603466.137634414,\n",
    "#  71667572.8671974,\n",
    "#  27615099.773239322,\n",
    "#  34.94985004134655,\n",
    "#  41495783.26707436,\n",
    "#  10.711995214837025,\n",
    "#  115717764.02523664,\n",
    "#  100039100.16430274,\n",
    "#  125634703.74511391,\n",
    "#  12672672.844191585,\n",
    "#  123.26119674856432,\n",
    "#  138318506.18854618,\n",
    "#  517.0231547932697,\n",
    "#  600653.6539173877,\n",
    "#  62022549.82588269,\n",
    "#  51114549.01234213,\n",
    "#  14.22971035063916,\n",
    "#  149191451.75039512,\n",
    "#  0.05, 3.4710257325119693]\n",
    "\n",
    "# 2 hrly pt wo augment SRES\n",
    "# kr=[4.859661207102135,\n",
    "#  154100350.5524576,\n",
    "#  154008609.58602124,\n",
    "#  2.56442473189546,\n",
    "#  319486815.1241803,\n",
    "#  332423659.90555525,\n",
    "#  428351560.44408816,\n",
    "#  13.760514532872966,\n",
    "#  16292421.856681712,\n",
    "#  18956680.62576625,\n",
    "#  10495617.540607082,\n",
    "#  13676402.803062597,\n",
    "#  27.770325273522648,\n",
    "#  19326944.818106852,\n",
    "#  6120980.698139961,\n",
    "#  68191861.08629908,\n",
    "#  31267295.87848613,\n",
    "#  43.69365581641304,\n",
    "#  45810357.044467054,\n",
    "#  21.52776249025497,\n",
    "#  215320655.53288755,\n",
    "#  221625548.44371983,\n",
    "#  222863758.278775,\n",
    "#  22433444.072363377,\n",
    "#  12.222530978287159,\n",
    "#  12581771.491868041,\n",
    "#  99.7969158627641,\n",
    "#  104150.22759584729,\n",
    "#  10300233.10454042,\n",
    "#  9973346.779652592,\n",
    "#  19.138058891968434,\n",
    "#  193691558.36675698,\n",
    "#  0.05, 16.172891513087137]\n",
    "\n",
    "# 2 hrly point wo augment, 7.5% noise\n",
    "# kr=[14.484670380826332,\n",
    "#  472077182.89424485,\n",
    "#  393098711.23677003,\n",
    "#  2.4880023040868755,\n",
    "#  93233635.674739,\n",
    "#  75320270.8972964,\n",
    "#  63141621.421345085,\n",
    "#  7.58800223263346,\n",
    "#  8785310.727699077,\n",
    "#  10990024.06318993,\n",
    "#  16689101.142625613,\n",
    "#  7296983.2610182995,\n",
    "#  68.29512695255859,\n",
    "#  61792154.788160995,\n",
    "#  9149003.421285577,\n",
    "#  148484509.95372662,\n",
    "#  78733339.6377908,\n",
    "#  67.9350735611992,\n",
    "#  78406632.19884877,\n",
    "#  9.627170055943054,\n",
    "#  101762691.10489054,\n",
    "#  102711507.47953582,\n",
    "#  110447951.83828118,\n",
    "#  11064696.519263996,\n",
    "#  10.39688491385504,\n",
    "#  11644689.157511486,\n",
    "#  1749.3239817862923,\n",
    "#  1899582.55845713,\n",
    "#  176953199.6851323,\n",
    "#  205324669.9225323,\n",
    "#  30.316827314669233,\n",
    "#  329514047.21031386,\n",
    "#  0.05, 3.982006638057981]\n",
    "\n",
    "# 1 hrly point wo augment\n",
    "# kr=[5.503531205845771,\n",
    "#  175339926.4320538,\n",
    "#  173736370.0364849,\n",
    "#  4.991453657683082,\n",
    "#  289525499.8020759,\n",
    "#  272164643.92539525,\n",
    "#  315592259.9090763,\n",
    "#  3.611704719418988,\n",
    "#  4627261.854048733,\n",
    "#  4196003.676050386,\n",
    "#  5774401.222588112,\n",
    "#  3685963.6952084783,\n",
    "#  24.301360982322173,\n",
    "#  25320062.69287638,\n",
    "#  2880814.471459475,\n",
    "#  72199160.8633649,\n",
    "#  27763405.73987159,\n",
    "#  115.54554356802524,\n",
    "#  137203353.56874707,\n",
    "#  8.288232652884627,\n",
    "#  89545282.9975948,\n",
    "#  77457704.68530941,\n",
    "#  97196109.13543008,\n",
    "#  9805473.643497936,\n",
    "#  3.0891474852783043,\n",
    "#  3466751.48294808,\n",
    "#  636.3221680193803,\n",
    "#  739018.5335008572,\n",
    "#  76322211.04459672,\n",
    "#  62938400.74084778,\n",
    "#  38.91368956677703,\n",
    "#  408002035.7190128,\n",
    "#  0.05, 6.791756910802882]\n",
    "\n",
    "# 2 hourly datapoint wo augment\n",
    "# kr=[4.879762104150187,\n",
    "#  154798750.20216095,\n",
    "#  154436128.7630702,\n",
    "#  3.7213176261332634,\n",
    "#  36657707.64937024,\n",
    "#  38445244.45023595,\n",
    "#  50423991.781559214,\n",
    "#  10.460247166862807,\n",
    "#  12221523.76687265,\n",
    "#  14749621.984535148,\n",
    "#  7264455.203175714,\n",
    "#  10425484.81363926,\n",
    "#  23.064130322024457,\n",
    "#  15642265.391909445,\n",
    "#  4934529.314595252,\n",
    "#  56378839.22405732,\n",
    "#  26062831.724530958,\n",
    "#  20.166534638710576,\n",
    "#  21145193.967243124,\n",
    "#  18.038880989170703,\n",
    "#  180452858.78548685,\n",
    "#  185702276.04453078,\n",
    "#  186759633.64618975,\n",
    "#  18798585.84651011,\n",
    "#  13.83162799604501,\n",
    "#  14239017.922584126,\n",
    "#  1385.53184913475,\n",
    "#  1446110.146561394,\n",
    "#  143095033.2834513,\n",
    "#  138400210.289016,\n",
    "#  21.187785617388286,\n",
    "#  214441403.01536304,\n",
    "#  0.05, 1.2888976543818667]\n",
    "\n",
    "# CMAES 0%\n",
    "# kr=[24.341789735521008,\n",
    "#  770498125.8205624,\n",
    "#  770570407.5724835,\n",
    "#  12.908875333819209,\n",
    "#  132592743.46920629,\n",
    "#  133575801.8762858,\n",
    "#  141293006.60228273,\n",
    "#  424.93710028362716,\n",
    "#  442135703.5425901,\n",
    "#  456653562.42972904,\n",
    "#  419571638.0456757,\n",
    "#  423088262.0675533,\n",
    "#  418.4182512136561,\n",
    "#  399511667.0585313,\n",
    "#  295765924.2568549,\n",
    "#  630922748.6327578,\n",
    "#  425263543.22326005,\n",
    "#  52.30576320117826,\n",
    "#  52712159.6627699,\n",
    "#  41.87389502844566,\n",
    "#  423451241.0170319,\n",
    "#  429079540.3031055,\n",
    "#  418655405.8159361,\n",
    "#  41936478.920335196,\n",
    "#  14.986457048553103,\n",
    "#  15080654.257682588,\n",
    "#  96.41112339205266,\n",
    "#  96442.22396102108,\n",
    "#  9680414.94191425,\n",
    "#  9708703.393288838,\n",
    "#  7.524098862986353,\n",
    "#  75389602.47928162,\n",
    "#  0.05, 1.3006165019270226]\n",
    "\n",
    "# G3PCX 0%\n",
    "# kr=[3.6351947292324485,\n",
    "#  115040453.92273255,\n",
    "#  115163722.2248276,\n",
    "#  2.8063985890112697,\n",
    "#  46314456.28960049,\n",
    "#  46604964.696806125,\n",
    "#  49667174.39423882,\n",
    "#  9.673110746568891,\n",
    "#  9705570.75480753,\n",
    "#  10736195.471524585,\n",
    "#  8570941.482549246,\n",
    "#  9724493.715638496,\n",
    "#  19.556727000796013,\n",
    "#  18597193.07862987,\n",
    "#  13868044.822806895,\n",
    "#  29447279.82855708,\n",
    "#  19881770.362996854,\n",
    "#  102.9305736860309,\n",
    "#  103724537.41596366,\n",
    "#  12.636525652524107,\n",
    "#  127763677.3410062,\n",
    "#  129472298.09439813,\n",
    "#  126345450.03078298,\n",
    "#  12655637.402536748,\n",
    "#  11.771573085187299,\n",
    "#  11845204.69243916,\n",
    "#  709.714731592793,\n",
    "#  710034.7431967282,\n",
    "#  71268030.41474967,\n",
    "#  71450699.79451951,\n",
    "#  17.013729615883385,\n",
    "#  170468722.54810506,\n",
    "#  0.05, 2.0897902726400983]\n",
    "\n",
    "# ISRES 0%\n",
    "# kr=[4.015807902374604,\n",
    "#  127113600.40900286,\n",
    "#  127125517.348282,\n",
    "#  4.208826565487971,\n",
    "#  306752541.76707953,\n",
    "#  309026810.8468508,\n",
    "#  326880517.36875254,\n",
    "#  5.856264317444886,\n",
    "#  6093286.89266397,\n",
    "#  6293365.717145127,\n",
    "#  5782320.412682495,\n",
    "#  5830784.446852674,\n",
    "#  23.38143992757912,\n",
    "#  22324923.531763446,\n",
    "#  16527551.914786907,\n",
    "#  35256309.77033088,\n",
    "#  23763960.03511419,\n",
    "#  18.585110888456335,\n",
    "#  18729510.048372008,\n",
    "#  42.636525536138805,\n",
    "#  431163362.317284,\n",
    "#  436894167.2110984,\n",
    "#  426280195.878497,\n",
    "#  42700249.56817559,\n",
    "#  31.607230480519043,\n",
    "#  31805897.37623234,\n",
    "#  8278.871339176154,\n",
    "#  8281542.151262955,\n",
    "#  831262112.7116727,\n",
    "#  833691173.1119242,\n",
    "#  7.724826904418006,\n",
    "#  77400847.02240579,\n",
    "#  0.05, 9.228795444675196]\n",
    "\n",
    "# SRES 0%\n",
    "# kr=[2.080969971343917,\n",
    "#  65869580.36105407,\n",
    "#  65875755.148932,\n",
    "#  7.5065935849636345,\n",
    "#  315217081.22182375,\n",
    "#  317554104.1180506,\n",
    "#  335900466.2482879,\n",
    "#  32.25588014253787,\n",
    "#  33561383.59515718,\n",
    "#  34663403.82466921,\n",
    "#  31848606.131871734,\n",
    "#  32115538.612363648,\n",
    "#  16.655783486004715,\n",
    "#  15903172.876542434,\n",
    "#  11773410.77021682,\n",
    "#  25114854.511483587,\n",
    "#  16928272.185834568,\n",
    "#  46.010463329012026,\n",
    "#  46367947.99157464,\n",
    "#  15.291238425189105,\n",
    "#  154633179.82594472,\n",
    "#  156688491.6956186,\n",
    "#  152881878.36950904,\n",
    "#  15314092.641533779,\n",
    "#  25.031964256311316,\n",
    "#  25189302.38928925,\n",
    "#  827.3518010877931,\n",
    "#  827618.728651611,\n",
    "#  83072461.0287013,\n",
    "#  83315206.80590378,\n",
    "#  20.243637879636214,\n",
    "#  202836225.34361023,\n",
    "#  0.05, 5.317221024908019]\n",
    "\n",
    "#CMAES 2.5%\n",
    "# kr=[9.168268398656936,\n",
    "#  289959413.9662518,\n",
    "#  292562132.76786494,\n",
    "#  5.12732961543803,\n",
    "#  62090257.84062828,\n",
    "#  62111721.06158142,\n",
    "#  63812888.96934867,\n",
    "#  728.0302363181644,\n",
    "#  822047393.5458022,\n",
    "#  756605469.8211153,\n",
    "#  981934215.612558,\n",
    "#  717473398.1814942,\n",
    "#  9.153874479554217,\n",
    "#  9065248.4240556,\n",
    "#  3882582.7439654474,\n",
    "#  17900373.52033199,\n",
    "#  9521752.164864026,\n",
    "#  369.2212373015598,\n",
    "#  384607341.5667877,\n",
    "#  1.4181092407438438,\n",
    "#  14194598.407199621,\n",
    "#  14268849.151259892,\n",
    "#  14783552.003252624,\n",
    "#  1479091.3707540527,\n",
    "#  206.9407267777704,\n",
    "#  212320782.777641,\n",
    "#  23.487125443435552,\n",
    "#  24344.313381041153,\n",
    "#  2385985.0051716026,\n",
    "#  2368990.650143959,\n",
    "#  59.686282938929395,\n",
    "#  605745235.213676,\n",
    "#  0.05, 1.5120121850439698]\n",
    "\n",
    "#G3PCX 2.5%\n",
    "# kr=[5.114013459044473,\n",
    "#  161657253.74279726,\n",
    "#  163505470.1151922,\n",
    "#  5.402315453058239,\n",
    "#  165865905.2571188,\n",
    "#  165543163.41181207,\n",
    "#  172876805.95820245,\n",
    "#  13.13467738266598,\n",
    "#  13939747.163002105,\n",
    "#  14475238.008705467,\n",
    "#  15416109.863212792,\n",
    "#  13186376.247614527,\n",
    "#  34.729937626212376,\n",
    "#  34913452.99442153,\n",
    "#  15873658.275101893,\n",
    "#  67097248.83868542,\n",
    "#  35981679.70634683,\n",
    "#  163.4418037971583,\n",
    "#  170363882.95152897,\n",
    "#  8.059694926874732,\n",
    "#  80726648.67241962,\n",
    "#  81141120.36895455,\n",
    "#  84044571.38035451,\n",
    "#  8409364.425504059,\n",
    "#  7.226226221999506,\n",
    "#  7417259.83889776,\n",
    "#  3239.127600124352,\n",
    "#  3357829.111430553,\n",
    "#  328989878.30890876,\n",
    "#  326957236.0087967,\n",
    "#  6.52355943220348,\n",
    "#  66218271.477754384,\n",
    "#  0.05, 3.8339002565113756]\n",
    "\n",
    "# ISRES 2.5%\n",
    "# kr=[15.952005106778014,\n",
    "#  504504657.589211,\n",
    "#  509033111.69165105,\n",
    "#  3.0419209226133406,\n",
    "#  142528606.80549517,\n",
    "#  142577893.28356564,\n",
    "#  146482995.7886475,\n",
    "#  157.81527629561248,\n",
    "#  178195386.8104642,\n",
    "#  164009469.30190763,\n",
    "#  212854124.51413622,\n",
    "#  155526870.53151372,\n",
    "#  20.5769718445255,\n",
    "#  20377751.25641081,\n",
    "#  8727648.894763047,\n",
    "#  40238205.72077568,\n",
    "#  21403922.67424354,\n",
    "#  13.973371001825061,\n",
    "#  14555665.948464986,\n",
    "#  9.76659525141504,\n",
    "#  97758969.14202952,\n",
    "#  98270335.78095682,\n",
    "#  101815125.28420931,\n",
    "#  10186582.574132632,\n",
    "#  9.281122894129314,\n",
    "#  9522413.94671659,\n",
    "#  347.6234509949857,\n",
    "#  360310.3382355493,\n",
    "#  35314004.11888847,\n",
    "#  35062472.93244163,\n",
    "#  2.2335683827345547,\n",
    "#  22668079.303334482,\n",
    "#  0.05, 5.850287826577263]\n",
    "\n",
    "# SRES 2.5%\n",
    "# kr=[8.975158426378496,\n",
    "#  283852042.3231981,\n",
    "#  286399916.26888925,\n",
    "#  3.215650423019069,\n",
    "#  283084375.7167331,\n",
    "#  283182266.4643409,\n",
    "#  290938433.85724247,\n",
    "#  37.09933627952514,\n",
    "#  41890307.98018201,\n",
    "#  38555475.18083972,\n",
    "#  50037910.57864541,\n",
    "#  36561376.37669976,\n",
    "#  21.897005628345255,\n",
    "#  21685005.168676797,\n",
    "#  9287536.281546507,\n",
    "#  42819529.07601466,\n",
    "#  22777006.374168552,\n",
    "#  17.321747889104998,\n",
    "#  18043575.4514243,\n",
    "#  10.394819919779406,\n",
    "#  104047196.61428265,\n",
    "#  104591459.50495079,\n",
    "#  108364263.42219229,\n",
    "#  10841822.512655906,\n",
    "#  58.77967899592992,\n",
    "#  60307836.2106872,\n",
    "#  2558.2858770813655,\n",
    "#  2651653.1979826503,\n",
    "#  259888448.63251185,\n",
    "#  258037334.28627422,\n",
    "#  4.393884264226889,\n",
    "#  44592732.29379582,\n",
    "#  0.05, 10.991834565312654]\n",
    "\n",
    "# ISRES 5% noise\n",
    "# kr=[1.6748506006289392,\n",
    "#  51606646.259696074,\n",
    "#  60104778.359418094,\n",
    "#  6.861267739920871,\n",
    "#  185405303.6696277,\n",
    "#  193500128.0118483,\n",
    "#  224748328.25211096,\n",
    "#  5.256898761160931,\n",
    "#  5742423.6990770595,\n",
    "#  6070882.490829237,\n",
    "#  6029647.312061429,\n",
    "#  5344359.694237936,\n",
    "#  22.68902933732074,\n",
    "#  23713434.740501437,\n",
    "#  11972444.33962037,\n",
    "#  36636517.64834937,\n",
    "#  23783579.801765464,\n",
    "#  86.58494325597667,\n",
    "#  90840403.92693076,\n",
    "#  35.44440769501024,\n",
    "#  347361538.78029394,\n",
    "#  355194432.6593976,\n",
    "#  379018620.56220675,\n",
    "#  37488371.9299226,\n",
    "#  23.8355634851991,\n",
    "#  24940270.720816813,\n",
    "#  644.1567914652064,\n",
    "#  661010.8781615463,\n",
    "#  67511086.89954446,\n",
    "#  66708422.39042684,\n",
    "#  14.025723616410007,\n",
    "#  141915870.89014164,\n",
    "#  0.05, 3.48224296760188]\n",
    "\n",
    "# SRES 5% noise\n",
    "# kr=[6.313767374996461,\n",
    "#  194544132.39260918,\n",
    "#  226579976.10849997,\n",
    "#  2.541132808144382,\n",
    "#  154400556.0330337,\n",
    "#  161141735.4897673,\n",
    "#  187164461.90423548,\n",
    "#  97.56160132898954,\n",
    "#  106572350.22874478,\n",
    "#  112668140.495579,\n",
    "#  111902892.72778682,\n",
    "#  99184766.0625502,\n",
    "#  8.081021954668547,\n",
    "#  8445878.704250969,\n",
    "#  4264157.100823076,\n",
    "#  13048619.383493172,\n",
    "#  8470861.610294955,\n",
    "#  42.120404831711596,\n",
    "#  44190530.3073232,\n",
    "#  17.08435196466488,\n",
    "#  167429704.21391582,\n",
    "#  171205191.5920588,\n",
    "#  182688551.9025915,\n",
    "#  18069550.813116916,\n",
    "#  20.0697715947047,\n",
    "#  20999945.614363756,\n",
    "#  479.08967718443154,\n",
    "#  491624.8610447029,\n",
    "#  50211168.31470708,\n",
    "#  49614187.47123159,\n",
    "#  6.428273260832142,\n",
    "#  65042919.00243991,\n",
    "#  0.05, 7.830019554696783]\n",
    "\n",
    "# G3PCX 5% NOISE\n",
    "# kr=[4.786149829549998,\n",
    "#  147437042.29373872,\n",
    "#  171870495.8817357,\n",
    "#  2.1707662128581284,\n",
    "#  116261495.0291353,\n",
    "#  119448767.60319336,\n",
    "#  136593306.05656204,\n",
    "#  11.330143142214162,\n",
    "#  11485827.159572639,\n",
    "#  13821821.605029417,\n",
    "#  11149173.229527298,\n",
    "#  11751705.696216227,\n",
    "#  16.432034320390628,\n",
    "#  17579091.634837996,\n",
    "#  9277033.182417948,\n",
    "#  26307705.00339501,\n",
    "#  17125190.581462327,\n",
    "#  83.10645103586901,\n",
    "#  87238028.69596525,\n",
    "#  6.535298016664662,\n",
    "#  64050778.10033872,\n",
    "#  65501315.15894433,\n",
    "#  69919606.15588528,\n",
    "#  6915571.990767428,\n",
    "#  7.560646506062875,\n",
    "#  7913645.043998155,\n",
    "#  2146.1893395615425,\n",
    "#  2204939.088974819,\n",
    "#  225143541.54647103,\n",
    "#  222081065.9584635,\n",
    "#  36.929362163301676,\n",
    "#  373738596.19413805,\n",
    "#  0.05, 6.814378513197615]\n",
    "\n",
    "# CMAES 5% noise\n",
    "# kr=[25.272783093472082,\n",
    "#  778722303.0820987,\n",
    "#  906955606.8923908,\n",
    "#  5.007440693653092,\n",
    "#  596713902.9437848,\n",
    "#  648199805.9263284,\n",
    "#  697624905.4539112,\n",
    "#  42.128662531767894,\n",
    "#  49227941.97244647,\n",
    "#  146329.23169619267,\n",
    "#  74032.59512589528,\n",
    "#  43958850.43227558,\n",
    "#  86.72403778810393,\n",
    "#  91495432.97771057,\n",
    "#  43951899.5987797,\n",
    "#  141140033.65842223,\n",
    "#  90857422.01531622,\n",
    "#  77.02232410226699,\n",
    "#  80793862.95672566,\n",
    "#  42.115359931695195,\n",
    "#  412666796.5611622,\n",
    "#  421972614.46538323,\n",
    "#  450328610.86160576,\n",
    "#  44539230.55139495,\n",
    "#  275.9544912007556,\n",
    "#  288711834.75697154,\n",
    "#  52.273255145001585,\n",
    "#  53635.42546139851,\n",
    "#  5478140.038580738,\n",
    "#  5413022.388217978,\n",
    "#  18.844866274966776,\n",
    "#  190669481.98407868,\n",
    "#  0.05, 15.713351611335092]\n",
    "\n",
    "# ISRES 7.5% noise\n",
    "# kr = [4.257477158788692,\n",
    "#  130649999.78038883,\n",
    "#  158754798.10310704,\n",
    "#  6.253277523852371,\n",
    "#  193785648.20973185,\n",
    "#  223171538.13459128,\n",
    "#  276433733.9139358,\n",
    "#  26.16715699216635,\n",
    "#  32393932.780493215,\n",
    "#  30171927.813968264,\n",
    "#  30364174.364154868,\n",
    "#  26146716.018130008,\n",
    "#  13.841063464749922,\n",
    "#  10934854.701672897,\n",
    "#  5309550.999595971,\n",
    "#  20720873.05219635,\n",
    "#  15922842.524816092,\n",
    "#  37.628822929903144,\n",
    "#  40728618.572758056,\n",
    "#  69.12728710016015,\n",
    "#  759214394.0277916,\n",
    "#  769195591.8016431,\n",
    "#  713982510.127409,\n",
    "#  72101640.0304237,\n",
    "#  41.4133583169845,\n",
    "#  44111699.474764474,\n",
    "#  107.05853759057187,\n",
    "#  105392.16030313057,\n",
    "#  10754535.397291178,\n",
    "#  11845243.331507131,\n",
    "#  18.941936367501558,\n",
    "#  193513783.1316113,\n",
    "#  0.05, 4.280536684466626]\n",
    "\n",
    "# SRES 7.5% noise\n",
    "# kr= [2.5639814570473294,\n",
    "#  78681379.67778572,\n",
    "#  95606935.956585,\n",
    "#  2.2443680795331726,\n",
    "#  112994460.60658759,\n",
    "#  130129078.18909836,\n",
    "#  161185733.53776032,\n",
    "#  95.07089301756643,\n",
    "#  117694097.59007001,\n",
    "#  109621072.47514649,\n",
    "#  110319523.32998522,\n",
    "#  94996630.22086348,\n",
    "#  23.297709550273115,\n",
    "#  18405887.222478315,\n",
    "#  8937204.935157327,\n",
    "#  34878018.47066636,\n",
    "#  26801824.55691605,\n",
    "#  18.033426191253103,\n",
    "#  19518987.832060333,\n",
    "#  39.16240700957948,\n",
    "#  430114724.10589254,\n",
    "#  435769322.5205034,\n",
    "#  404489668.5184004,\n",
    "#  40847455.031265005,\n",
    "#  5.747722867473234,\n",
    "#  6122223.123310849,\n",
    "#  16.94340453372139,\n",
    "#  16679.678677546333,\n",
    "#  1702044.928992395,\n",
    "#  1874663.6279751095,\n",
    "#  6.301398133834775,\n",
    "#  64376067.447379224,\n",
    "#  0.05, 6.954203416108272]\n",
    "\n",
    "# mean kr from 3 CMAES seeds for 7.5% noise\n",
    "# kr=[18.90356434893431,\n",
    "#  580097223.2906843,\n",
    "#  704884936.9433186,\n",
    "#  4.52205695065174,\n",
    "#  330724686.409708,\n",
    "#  391227757.24708277,\n",
    "#  510077511.57174224,\n",
    "#  672.9625242082301,\n",
    "#  869067241.5079789,\n",
    "#  806964314.8400626,\n",
    "#  678455649.7290957,\n",
    "#  663102135.6838393,\n",
    "#  28.807845686060503,\n",
    "#  53543.882916650844,\n",
    "#  6037230.860112401,\n",
    "#  39756151.17238413,\n",
    "#  35045396.399643704,\n",
    "#  8.571992552194114,\n",
    "#  9275071.153922342,\n",
    "#  5.139177820669817,\n",
    "#  56424568.948431954,\n",
    "#  57165889.21570655,\n",
    "#  53075277.88465081,\n",
    "#  5359257.528018084,\n",
    "#  671.1667090773975,\n",
    "#  714745769.2300979,\n",
    "#  270.60774773412743,\n",
    "#  266347.4562008611,\n",
    "#  27180411.657585137,\n",
    "#  29936656.671371736,\n",
    "#  11.617458496755047,\n",
    "#  118676982.86143655,\n",
    "#  0.05, 10.369520471751004]\n",
    "\n",
    "# mean kr from 3 G3PCX seeds for 7.5% noise\n",
    "# kr=[3.479213047599239,\n",
    "#  106758862.22233589,\n",
    "#  129797262.58859053,\n",
    "#  2.4749354516858055,\n",
    "#  79223915.59274432,\n",
    "#  93008261.49994448,\n",
    "#  118195010.43646741,\n",
    "#  27.365303974946123,\n",
    "#  33840691.072298326,\n",
    "#  32047333.510049447,\n",
    "#  30184863.528538927,\n",
    "#  27354810.46497765,\n",
    "#  32.779699402180334,\n",
    "#  25096674.616974432,\n",
    "#  12082969.799536085,\n",
    "#  48291198.80365648,\n",
    "#  37889684.586829826,\n",
    "#  97.98633861461963,\n",
    "#  106089119.10664833,\n",
    "#  8.884065803438531,\n",
    "#  97580370.63350523,\n",
    "#  98862378.16390777,\n",
    "#  91774748.56308798,\n",
    "#  9269490.634694032,\n",
    "#  2.0995950006604196,\n",
    "#  2236780.9054112914,\n",
    "#  2236.7183635243364,\n",
    "#  2202161.3867165456,\n",
    "#  224613966.22270754,\n",
    "#  247579506.73360842,\n",
    "#  5.081828057020837,\n",
    "#  51922943.753446594,\n",
    "#  0.05, 4.497793439697595]\n",
    "\n",
    "print (str(len(kr))+' kr parameters in same order as their input into kinetic_model function:')\n",
    "print (kr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# * SET Ke parameters (kf, kl, km) for WT\n",
    "\n",
    "e = kf * t / (km + t)   + kl <br>\n",
    "where kf: maximum increase in enzyme conc <br>\n",
    "km: hours required to increase the enzyme conc by 1/2*kf <br>\n",
    "kl: enzyme conc at hour = 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. define km parameters\n",
    "\n",
    "- km: randomly SET between 0.1 t & 9 hours\n",
    "\n",
    "- kf: randomly initialized between 1e5 & 1e6                                              \n",
    "\n",
    "- kl: randomly initialized between 1e1 to 1e2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:25.853900Z",
     "start_time": "2023-11-23T05:38:25.839579Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "km values defined...\n",
      "\n",
      "kf, kl values initialized for 9 enzymes:\n",
      "[2.74397961e+06 1.23333609e-01 5.94696230e+01 2.74128957e+06\n",
      " 4.78331022e-01 3.97301339e+01 1.81859454e+06 6.57343870e-01\n",
      " 3.69689206e+01 2.06730910e+06 6.59020449e-01 5.76227885e+01\n",
      " 1.53831978e+06 5.62220309e-01 2.65995879e+01 4.14134059e+06\n",
      " 8.68577763e-01 5.44813154e+01 4.38624594e+06 1.71680929e-01\n",
      " 5.54721481e+01 1.26114602e+06 4.85310095e-01 1.86877824e+01\n",
      " 1.50863989e+06 6.37070778e-01 3.03410801e+01]\n"
     ]
    }
   ],
   "source": [
    "#--- set initial parameter bounds for each enzyme\n",
    "bounds = [(1e6,5e6),(0.1,1),(1e1,1e2)]*9\n",
    "lower_bound = [bound[0] for bound in bounds] # reformat bounds\n",
    "upper_bound = [bound[1] for bound in bounds]\n",
    "\n",
    "# For creating replicable WT template, NOT noise !!\n",
    "np.random.seed(2)\n",
    "\n",
    "# get random kf, km, kl values based on bounds\n",
    "ke = np.random.uniform(low=lower_bound,high=upper_bound)\n",
    "\n",
    "print('km values defined...\\n\\nkf, kl values initialized for ' + str(int(len(ke)/3)) + ' enzymes:')\n",
    "print (ke)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. define kl parameters\n",
    "- i.e., enzyme expression values at t =0 from the 3 empirical strains"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. define kf parameters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# --- SET data points requirement for synthetic data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:25.863306Z",
     "start_time": "2023-11-23T05:38:25.854895Z"
    }
   },
   "outputs": [],
   "source": [
    "# no. data points needed per hour\n",
    "datapointsPerHr = 4\n",
    "\n",
    "# no. hours required\n",
    "hr = 24\n",
    "\n",
    "# resulting total no. data points required\n",
    "noDataPts=hr*datapointsPerHr + 1 # include data for time=0\n",
    "\n",
    "# Generate array of evenly-spaced time points betw max & min time\n",
    "timePoints = np.linspace(0,hr,noDataPts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# --- SET biological noise\n",
    "\n",
    "For all strains, affects:\n",
    "- initial enzyme conc (kl values)\n",
    "- initial metabolite conc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:25.878767Z",
     "start_time": "2023-11-23T05:38:25.863306Z"
    },
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "biologicalNoise = 0.0 # 0.025: Gaussian noise with standard deviation of 2.5% of underlying value\n",
    "biologicalNoiseSeed = 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Explore synthetic time-series data for enzymes in WT\n",
    "\n",
    "to appreciate effects of kf, km, kl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:26.666648Z",
     "start_time": "2023-11-23T05:38:25.879444Z"
    },
    "code_folding": [],
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "no. time series: 9\n",
      "data points in each time series:97\n",
      "\n",
      "AtoB\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "HMGS\n"
     ]
    },
    {
     "data": {
      "image/png": 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QIsAzz0j33WfP/+xn0i23mK0HAIC+RkBxuL17pYUL7fnly6U77jBaDgAAYUFAcbATJ+w3EZ89KxUWSg8+aLoiAADCg4DiUK2t9qWcTz+VRo6UfvlLqR//tQAAMYKvPId69FHpt7+1bycuLZXS0kxXBABA+BBQHOiPf5TuvdeeX71a+upXzdYDAEC4EVAc5tgx+0mxra32u3Vuu810RQAAhB8BxWF+9CPpH/+Qxo2THn/cdDUAAJhBQHGQP/xB2rBBcrmkdeukxETTFQEAYAYBxSFOn5b+8z/t+SVLpKuuMlsPAAAmEVAc4sEH7VuKhw2THnrIdDUAAJhFQHGAv/xFWrHCnl+9WkpONlsPAACmEVAMa2mRbr/dns6dK33zm6YrAgDAPAKKYatXS++8I6WkSKtWma4GAABnIKAY5PFI999vzz/yiJSdbbQcAAAcg4Bi0KpV0hdfSKNHSz/4gelqAABwDgKKIXV10mOP2fP/7/9JcXFm6wEAwEkIKIaUlEgnTkhjxkjz5pmuBgAAZyGgGHDihPTTn9rz991H7wkAAOcjoBjw05/al3jGjpVuvNF0NQAAOA8BJcw+/9y+vCPZd/D0478AAAAd8PUYZitX2rcXX3GFdMMNpqsBAMCZCChhdPy49LOf2fP0ngAA0Dm+IsPoiSek+nrpyiulOXNMVwMAgHMRUMKkpUX6xS/s+R/9SHK5zNYDAICTEVDC5I9/lCorpYsusl8KCAAAOkdACZOf/9ye3nyzlJhothYAAJyOgBIGtbXSyy/b8wsWmK0FAIBIQEAJgw0bpKYmafJk+/ZiAADQtaACSnFxsSZPnqzk5GSlp6drzpw52r9/f7f7lZeXKy8vTwkJCbrkkku0Zs2aHhccaSyrfXDs7bebrQUAgEgRVEApLy/XokWL9Pbbb6usrEzNzc3Kz8/XqVOnOt3n0KFDKiws1PTp01VRUaF77rlHd9xxh0pLS3tdfCR44w1p/34pKUm66SbT1QAAEBn6B7Px73//e7/l9evXKz09XXv27NGMGTMC7rNmzRoNHz5cJeee7z5mzBjt3r1bK1as0NwYuJ3FOzj2ppuk5GSztQAAECl6NQalrq5OkpSWltbpNm+99Zby8/P91l133XXavXu3mpqaAu7T0NAgj8fj1yLRiRPSCy/Y8wyOBQDgwvU4oFiWpaKiIk2bNk3jxo3rdLuamhplZGT4rcvIyFBzc7OOHTsWcJ/i4mKlpqa2tZycnJ6WadTzz0tnzthvLb76atPVAAAQOXocUBYvXqz33ntPzz//fLfbus57bKplWQHXey1btkx1dXVtraqqqqdlGuW9vHP77Tw5FgCAYAQ1BsVryZIl2rJli3bt2qVhw4Z1uW1mZqZqamr81tXW1qp///4aPHhwwH3cbrfcbndPSnOMDz6QKiqk+Hjpu981XQ0AAJElqB4Uy7K0ePFibd68Wa+++qpyc3O73WfKlCkqKyvzW7d9+3ZNmjRJAwYMCK7aCPK739nTb3xD6iSHAQCATgQVUBYtWqSNGzfqueeeU3JysmpqalRTU6MzZ860bbNs2TLdcsstbcsLFy7U4cOHVVRUpH379umpp57SunXrtHTp0tD9FQ60das9/Zd/MVsHAACRKKiA8uSTT6qurk7XXnutsrKy2tqmTZvatqmurlZlZWXbcm5urrZt26adO3fqyiuv1I9//GOtWrUqqm8x/vxz6c037XkCCgAAwXNZ3hGrDubxeJSamqq6ujqlpKSYLqdbzz8vfec79t07H3xguhoAAMzozfc37+LpA1zeAQCgdwgoIdbSInkfuEtAAQCgZwgoIfanP0nHj0sXXSRNnWq6GgAAIhMBJcS8l3euu07q36OnzAAAAAJKiDH+BACA3iOghNDf/ib95S/2Y+2vv950NQAARC4CSght22ZPr75aGjrUbC0AAEQyAkoIcXkHAIDQIKCEyNmz0h/+YM8TUAAA6B0CSoiUl0unT0vZ2dKVV5quBgCAyEZACRHv5Z3CQnuQLAAA6DkCSoi88oo9LSw0WwcAANGAgBICX3whffyxPT9jhtlaAACIBgSUENi9255ecok0eLDZWgAAiAYElBB45x17etVVZusAACBaEFBC4M9/tqeTJ5utAwCAaEFACQFvDwoBBQCA0CCg9NLRo3br10/66ldNVwMAQHQgoPSSt/dk7FgpKclsLQAARAsCSi8x/gQAgNAjoPQS408AAAg9AkovWFb7M1AIKAAAhA4BpRcOHrSfIut2S+PHm64GAIDoQUDpBe/4kyuvlOLjjZYCAEBUIaD0AuNPAADoGwSUXuAR9wAA9A0CSg81N0vvvmvP04MCAEBoEVB66MMPpTNnpJQU6bLLTFcDAEB0IaD0kPfyTl6e/Zh7AAAQOny19hDjTwAA6DsElB7iEfcAAPQdAkoPnDkjvf++PU9AAQAg9AgoPbB3r9TSIqWnSzk5pqsBACD6EFB6wHf8ictlthYAAKIRAaUH3nvPnk6caLYOAACiFQGlBw4etKc8/wQAgL5BQOkBb0AZNcpsHQAARCsCSpDOnpX+9jd7noACAEDfIKAE6dAhybKkQYOkoUNNVwMAQHQioATJe3nny1/mDh4AAPoKASVIjD8BAKDvEVCCREABAKDvEVCC9Mkn9pSAAgBA3yGgBMl3DAoAAOgbBJQgtLTYd/FI9KAAANCXCChBqKqSmpqkAQOkYcNMVwMAQPQioATBe3knN1eKizNbCwAA0YyAEgTGnwAAEB4ElCBwizEAAOFBQAkCtxgDABAeBJQg0IMCAEB4EFAukGUxBgUAgHAJOqDs2rVLs2fPVnZ2tlwul1566aUut9+5c6dcLleH9tFHH/W0ZiP+8Q+pvt5+QWBurulqAACIbv2D3eHUqVOaMGGCbr31Vs2dO/eC99u/f79SUlLalocOHRrsrzbKO/5k2DDJ7TZbCwAA0S7ogFJQUKCCgoKgf1F6erouuuiioPdzCsafAAAQPmEbgzJx4kRlZWVp1qxZ2rFjR5fbNjQ0yOPx+DXTGH8CAED49HlAycrK0tq1a1VaWqrNmzdr9OjRmjVrlnbt2tXpPsXFxUpNTW1rOTk5fV1mt+hBAQAgfFyWZVk93tnl0osvvqg5c+YEtd/s2bPlcrm0ZcuWgJ83NDSooaGhbdnj8SgnJ0d1dXV+41jCacoU6e23pV//WrrxRiMlAAAQUTwej1JTU3v0/W3kNuNrrrlGBw4c6PRzt9utlJQUv2YaPSgAAISPkYBSUVGhrKwsE7+6Rzwe+zZjiYACAEA4BH0XT319vT7x3nMr6dChQ9q7d6/S0tI0fPhwLVu2TEeOHNGGDRskSSUlJRo5cqTGjh2rxsZGbdy4UaWlpSotLQ3dX9HHvL0nQ4ZIqalmawEAIBYEHVB2796tmTNnti0XFRVJkubPn6+nn35a1dXVqqysbPu8sbFRS5cu1ZEjR5SYmKixY8dq69atKiwsDEH54cHlHQAAwqtXg2TDpTeDbELh0Uelu++WvvMd6dlnw/7rAQCISBE3SDbS8AwUAADCi4ByAbxDbrjEAwBAeBBQLgBjUAAACC8CSjcaGqSqKnuegAIAQHgQULrx2WeSZUlJSVJGhulqAACIDQSUbhw+bE9HjpRcLqOlAAAQMwgo3aittaf0ngAAED4ElG54H3E/dKjZOgAAiCUElG4cO2ZPCSgAAIQPAaUb9KAAABB+BJRuEFAAAAg/Ako3CCgAAIQfAaUbBBQAAMKPgNINb0AZMsRsHQAAxBICSheamqQvvrDn6UEBACB8CChdOH7cnrpc0uDBZmsBACCWEFC64L28k5YmxcWZrQUAgFhCQOkCA2QBADCDgNIFniILAIAZBJQu0IMCAIAZBJQuEFAAADCDgNIFAgoAAGYQULpAQAEAwAwCShcIKAAAmEFA6QIBBQAAMwgoXeA9PAAAmEFA6URra/uj7ulBAQAgvAgonfjiC6mlxZ6nBwUAgPAioHTC+xTZlBTJ7TZbCwAAsYaA0gkGyAIAYA4BpRMEFAAAzCGgdIKAAgCAOQSUThBQAAAwh4DSCQIKAADmEFA6QUABAMAcAkonCCgAAJhDQOkEAQUAAHMIKJ3gPTwAAJhDQAnAstqfJEsPCgAA4UdACaC+XmposOcJKAAAhB8BJQDv5Z3ERCkpyWwtAADEIgJKAAyQBQDALAJKAAQUAADMIqAEQEABAMAsAkoABBQAAMwioARAQAEAwCwCSgAEFAAAzCKgBEBAAQDALAJKADxFFgAAswgoAdCDAgCAWQSUAHhRIAAAZgUdUHbt2qXZs2crOztbLpdLL730Urf7lJeXKy8vTwkJCbrkkku0Zs2antQaFmfP2u/ikehBAQDAlKADyqlTpzRhwgQ9/vjjF7T9oUOHVFhYqOnTp6uiokL33HOP7rjjDpWWlgZdbDh4e08GDJBSU83WAgBArOof7A4FBQUqKCi44O3XrFmj4cOHq6SkRJI0ZswY7d69WytWrNDcuXOD/fV9zvfyjstlthYAAGJVn49Beeutt5Sfn++37rrrrtPu3bvV1NQUcJ+GhgZ5PB6/Fi4MkAUAwLw+Dyg1NTXKyMjwW5eRkaHm5mYd897Pe57i4mKlpqa2tZycnL4usw0BBQAA88JyF4/rvGsllmUFXO+1bNky1dXVtbWqqqo+r9GLgAIAgHlBj0EJVmZmpmpqavzW1dbWqn///ho8eHDAfdxut9xud1+XFhAPaQMAwLw+70GZMmWKysrK/NZt375dkyZN0oABA/r61weNHhQAAMwLOqDU19dr79692rt3ryT7NuK9e/eqsrJSkn155pZbbmnbfuHChTp8+LCKioq0b98+PfXUU1q3bp2WLl0amr8gxAgoAACYF/Qlnt27d2vmzJlty0VFRZKk+fPn6+mnn1Z1dXVbWJGk3Nxcbdu2TXfddZdWr16t7OxsrVq1ypG3GEsEFAAAnMBleUesOpjH41Fqaqrq6uqUkpLSp79r9Gjp44+l8nJpxow+/VUAAES13nx/8y6e8/AeHgAAzCOgnOfkSXvKY+4BADCHgOKjqUlqbrbnk5LM1gIAQCwjoPg4fbp9fuBAc3UAABDrCCg+Tp2yp3Fx9tuMAQCAGQQUH94elIEDeZMxAAAmEVB8eAMK408AADCLgOLDtwcFAACYQ0Dx4R2DQkABAMAsAooPelAAAHAGAooPAgoAAM5AQPHBIFkAAJyBgOKDHhQAAJyBgOKDQbIAADgDAcUHPSgAADgDAcUHY1AAAHAGAooPelAAAHAGAooPxqAAAOAMBBQf9KAAAOAMBBQfBBQAAJyBgOKDQbIAADgDAcUHPSgAADgDAcUHg2QBAHAGAooPelAAAHAGAooPxqAAAOAMBBQf9KAAAOAMBBQfjEEBAMAZCCjnNDVJzc32PAEFAACzCCjneC/vSAQUAABMI6Cc4w0ocXFSfLzZWgAAiHUElHN8x5+4XGZrAQAg1hFQzuEOHgAAnIOAcg4BBQAA5yCgnMND2gAAcA4Cyjn0oAAA4BwElHN4SBsAAM5BQDmHHhQAAJyDgHIOAQUAAOcgoJzDIFkAAJyDgHIOY1AAAHAOAso5XOIBAMA5CCjnEFAAAHAOAso5jEEBAMA5CCjnMAYFAADnIKCcwyUeAACcg4ByDgEFAADnIKCcQ0ABAMA5CCjnMEgWAADnIKCcwyBZAACcg4ByDpd4AABwDgLKOQQUAACcg4ByDmNQAABwjh4FlCeeeEK5ublKSEhQXl6eXnvttU633blzp1wuV4f20Ucf9bjoUGtqsptEDwoAAE4QdEDZtGmT7rzzTi1fvlwVFRWaPn26CgoKVFlZ2eV++/fvV3V1dVu79NJLe1x0qHl7TyQCCgAAThB0QFm5cqVuu+02LViwQGPGjFFJSYlycnL05JNPdrlfenq6MjMz21pcXFyPiw41b0Dp10+KjzdbCwAACDKgNDY2as+ePcrPz/dbn5+frzfffLPLfSdOnKisrCzNmjVLO3bs6HLbhoYGeTwev9aXfAfIulx9+qsAAMAFCCqgHDt2TC0tLcrIyPBbn5GRoZqamoD7ZGVlae3atSotLdXmzZs1evRozZo1S7t27er09xQXFys1NbWt5eTkBFNm0BggCwCAs/TvyU6u87oZLMvqsM5r9OjRGj16dNvylClTVFVVpRUrVmjGjBkB91m2bJmKioralj0eT5+GFB7SBgCAswTVgzJkyBDFxcV16C2pra3t0KvSlWuuuUYHDhzo9HO3262UlBS/1pd4BgoAAM4SVECJj49XXl6eysrK/NaXlZVp6tSpF/xzKioqlJWVFcyv7lMEFAAAnCXoSzxFRUW6+eabNWnSJE2ZMkVr165VZWWlFi5cKMm+PHPkyBFt2LBBklRSUqKRI0dq7Nixamxs1MaNG1VaWqrS0tLQ/iW9wBgUAACcJeiAMm/ePB0/flwPPvigqqurNW7cOG3btk0jRoyQJFVXV/s9E6WxsVFLly7VkSNHlJiYqLFjx2rr1q0qLCwM3V/RS4xBAQDAWVyWZVmmi+iOx+NRamqq6urq+mQ8yurV0uLF0re/Lb3wQsh/PAAAMak339+8i0eMQQEAwGkIKCKgAADgNAQUtY9BYZAsAADOQEARPSgAADgNAUUEFAAAnIaAIgIKAABOQ0ARD2oDAMBpCCjiQW0AADgNAUVc4gEAwGkIKCKgAADgNAQUMQYFAACnIaCIMSgAADgNAUVc4gEAwGkIKCKgAADgNDEfUJqa7CYRUAAAcIqYDyhnzrTPM0gWAABniPmA4h0g26+fFB9vthYAAGCL+YDiO/7E5TJbCwAAsBFQGCALAIDjEFB4SBsAAI4T8wGFh7QBAOA8MR9QuMQDAIDzEFAIKAAAOA4BhYACAIDjxHxA8Y5BYZAsAADOEfMBhR4UAACch4BCQAEAwHEIKAQUAAAch4DCg9oAAHCcmA8oPKgNAADnifmAwiUeAACch4BCQAEAwHEIKAQUAAAcJ+YDCg9qAwDAeWI+oNCDAgCA8xBQCCgAADgOAYWAAgCA48R8QGEMCgAAzhPzAYUeFAAAnCemA0pTk90kAgoAAE4S0wHlzJn2eQIKAADOEdMBxXt5x+WS3G6ztQAAgHYxHVB8B8i6XGZrAQAA7WI6oDBAFgAAZyKgiIACAIDTEFBEQAEAwGliOqDwkDYAAJwppgMKPSgAADgTAUUEFAAAnIaAIgIKAABOQ0ARAQUAAKfpUUB54oknlJubq4SEBOXl5em1117rcvvy8nLl5eUpISFBl1xyidasWdOjYkONQbIAADhT0AFl06ZNuvPOO7V8+XJVVFRo+vTpKigoUGVlZcDtDx06pMLCQk2fPl0VFRW65557dMcdd6i0tLTXxfcWPSgAADhT0AFl5cqVuu2227RgwQKNGTNGJSUlysnJ0ZNPPhlw+zVr1mj48OEqKSnRmDFjtGDBAn3/+9/XihUrel18bxFQAABwpqACSmNjo/bs2aP8/Hy/9fn5+XrzzTcD7vPWW2912P66667T7t271dTUFHCfhoYGeTwev9YXCCgAADhTUAHl2LFjamlpUUZGht/6jIwM1dTUBNynpqYm4PbNzc06duxYwH2Ki4uVmpra1nJycoIp84IxBgUAAGfq0SBZ13mv/rUsq8O67rYPtN5r2bJlqqura2tVVVU9KbNbN9wgLVsmTZ7cJz8eAAD0UP9gNh4yZIji4uI69JbU1tZ26CXxyszMDLh9//79NXjw4ID7uN1uud3uYErrkX/7N7sBAABnCaoHJT4+Xnl5eSorK/NbX1ZWpqlTpwbcZ8qUKR223759uyZNmqQBAwYEWS4AAIgFQV/iKSoq0i9+8Qs99dRT2rdvn+666y5VVlZq4cKFkuzLM7fcckvb9gsXLtThw4dVVFSkffv26amnntK6deu0dOnS0P0VAAAgqgR1iUeS5s2bp+PHj+vBBx9UdXW1xo0bp23btmnEiBGSpOrqar9nouTm5mrbtm266667tHr1amVnZ2vVqlWaO3du6P4KAAAQVVyWd8Sqg3k8HqWmpqqurk4pKSmmywEAABegN9/fMf0uHgAA4EwEFAAA4DgEFAAA4DgEFAAA4DgEFAAA4DgEFAAA4DgEFAAA4DgEFAAA4DgEFAAA4DhBP+reBO/Dbj0ej+FKAADAhfJ+b/fkofUREVBOnjwpScrJyTFcCQAACNbJkyeVmpoa1D4R8S6e1tZWHT16VMnJyXK5XCH7uR6PRzk5OaqqquIdP2HEcTeD424Gx90MjrsZ5x93y7J08uRJZWdnq1+/4EaVREQPSr9+/TRs2LA++/kpKSmcwAZw3M3guJvBcTeD426G73EPtufEi0GyAADAcQgoAADAcWI6oLjdbt13331yu92mS4kpHHczOO5mcNzN4LibEcrjHhGDZAEAQGyJ6R4UAADgTAQUAADgOAQUAADgOAQUAADgODEdUJ544gnl5uYqISFBeXl5eu2110yXFNXuv/9+uVwuv5aZmWm6rKiza9cuzZ49W9nZ2XK5XHrppZf8PrcsS/fff7+ys7OVmJioa6+9Vh9++KGZYqNId8f9e9/7Xofz/5prrjFTbJQoLi7W5MmTlZycrPT0dM2ZM0f79+/324bzPfQu5LiH4nyP2YCyadMm3XnnnVq+fLkqKio0ffp0FRQUqLKy0nRpUW3s2LGqrq5ua++//77pkqLOqVOnNGHCBD3++OMBP//JT36ilStX6vHHH9c777yjzMxM/fM//3PbO6/QM90dd0m6/vrr/c7/bdu2hbHC6FNeXq5Fixbp7bffVllZmZqbm5Wfn69Tp061bcP5HnoXctylEJzvVoy66qqrrIULF/qtu/zyy627777bUEXR77777rMmTJhguoyYIsl68cUX25ZbW1utzMxM65FHHmlbd/bsWSs1NdVas2aNgQqj0/nH3bIsa/78+da3vvUtI/XEitraWkuSVV5eblkW53u4nH/cLSs053tM9qA0NjZqz549ys/P91ufn5+vN99801BVseHAgQPKzs5Wbm6ubrrpJn366aemS4ophw4dUk1Njd+573a79fWvf51zPwx27typ9PR0XXbZZbr99ttVW1truqSoUldXJ0lKS0uTxPkeLucfd6/enu8xGVCOHTumlpYWZWRk+K3PyMhQTU2Noaqi39VXX60NGzbolVde0c9//nPV1NRo6tSpOn78uOnSYob3/ObcD7+CggI9++yzevXVV/XYY4/pnXfe0T/90z+poaHBdGlRwbIsFRUVadq0aRo3bpwkzvdwCHTcpdCc7xHxNuO+4nK5/JYty+qwDqFTUFDQNj9+/HhNmTJFo0aN0jPPPKOioiKDlcUezv3wmzdvXtv8uHHjNGnSJI0YMUJbt27VDTfcYLCy6LB48WK99957ev311zt8xvnedzo77qE432OyB2XIkCGKi4vrkKBra2s7JG30naSkJI0fP14HDhwwXUrM8N41xblvXlZWlkaMGMH5HwJLlizRli1btGPHDg0bNqxtPed73+rsuAfSk/M9JgNKfHy88vLyVFZW5re+rKxMU6dONVRV7GloaNC+ffuUlZVlupSYkZubq8zMTL9zv7GxUeXl5Zz7YXb8+HFVVVVx/veCZVlavHixNm/erFdffVW5ubl+n3O+943ujnsgPTnfY/YST1FRkW6++WZNmjRJU6ZM0dq1a1VZWamFCxeaLi1qLV26VLNnz9bw4cNVW1urhx56SB6PR/PnzzddWlSpr6/XJ5980rZ86NAh7d27V2lpaRo+fLjuvPNOPfzww7r00kt16aWX6uGHH9bAgQP1ne98x2DVka+r456Wlqb7779fc+fOVVZWlj777DPdc889GjJkiP71X//VYNWRbdGiRXruuef08ssvKzk5ua2nJDU1VYmJiXK5XJzvfaC7415fXx+a871X9wBFuNWrV1sjRoyw4uPjra9+9at+t0gh9ObNm2dlZWVZAwYMsLKzs60bbrjB+vDDD02XFXV27NhhSerQ5s+fb1mWfevlfffdZ2VmZlput9uaMWOG9f7775stOgp0ddxPnz5t5efnW0OHDrUGDBhgDR8+3Jo/f75VWVlpuuyIFuh4S7LWr1/ftg3ne+h1d9xDdb67zv0yAAAAx4jJMSgAAMDZCCgAAMBxCCgAAMBxCCgAAMBxCCgAAMBxCCgAAMBxCCgAAMBxCCgAAMBxCCgAAMBxCCgAAMBxCCgAAMBxCCgAAMBx/j82rvJiTplaPQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "HMGR\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MK\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PMK\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PMD\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "GPPS\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Idi\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Limonene Synthase\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from KineticLearning import plotAllEnzymesTimeSeries, getAllEnzymesTimeSeries\n",
    "\n",
    "# Evaluate time-series data for the 9 enzymes in WT \n",
    "allEnzymesTimeSeries=getAllEnzymesTimeSeries(timePoints, ke)\n",
    "\n",
    "print('no. time series: ' + str(len(allEnzymesTimeSeries)))\n",
    "print('data points in each time series:' + str(len(allEnzymesTimeSeries[1])) + '\\n')\n",
    "\n",
    "# Plot enzyme time series profiles for sanity check of ke values \n",
    "plotAllEnzymesTimeSeries(all_enzymes, allEnzymesTimeSeries,timePoints)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# --- Read in recommended strains design\n",
    "1: WT\n",
    "2: over-expression\n",
    "0: knockdown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:26.681755Z",
     "start_time": "2023-11-23T05:38:26.667964Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ART design for Strain 1 read in:\n",
      "[2, 2, 0, 2, 0, 1, 0, 2, 0]\n",
      "\n",
      "\n",
      "ART design for Strain 2 read in:\n",
      "[0, 0, 2, 0, 2, 2, 1, 1, 0]\n",
      "\n",
      "\n",
      "ART design for Strain 3 read in:\n",
      "[2, 0, 0, 0, 1, 2, 1, 1, 0]\n",
      "\n",
      "\n",
      "ART design for Strain 4 read in:\n",
      "[0, 2, 2, 0, 2, 2, 0, 2, 2]\n",
      "\n",
      "\n",
      "ART design for Strain 5 read in:\n",
      "[2, 1, 2, 1, 0, 1, 2, 0, 1]\n",
      "\n",
      "\n",
      "ART design for Strain 6 read in:\n",
      "[1, 0, 1, 0, 1, 0, 2, 2, 1]\n",
      "\n",
      "\n",
      "ART design for Strain 7 read in:\n",
      "[2, 2, 0, 2, 0, 0, 1, 1, 2]\n",
      "\n",
      "\n",
      "ART design for Strain 8 read in:\n",
      "[0, 1, 1, 1, 1, 2, 2, 2, 1]\n",
      "\n",
      "\n",
      "ART design for Strain 9 read in:\n",
      "[1, 1, 1, 2, 0, 1, 0, 0, 1]\n",
      "\n",
      "\n",
      "ART design for Strain 10 read in:\n",
      "[1, 0, 2, 1, 2, 1, 2, 0, 2]\n",
      "\n",
      "\n",
      "ART design for Strain 11 read in:\n",
      "[0, 1, 1, 2, 2, 0, 0, 1, 0]\n",
      "\n",
      "\n",
      "Completed reading of\n",
      "12strains_initial_design_seed1.csv\n",
      "-------------------------------------------\n",
      "\n"
     ]
    }
   ],
   "source": [
    "\n",
    "#--- manual inclusion of strains recommendation\n",
    "design={} # dictionary using strain as key to hold a list of enzyme design in same order as their conc in kinetic_model\n",
    "design['WT']=[1]*9 # WT design for 9 enzymes\n",
    "# design['Strain_111']=[1]*4+[2]*5 # design of 1st four enzymes= 1, last five = 2\n",
    "# design['Strain_222']=[0,0,0,0,2,2,2,2,2] # design of 1st four enzymes= 0, last five = 2\n",
    "\n",
    "###--- include strain designs from ART\n",
    "# remember to remove last line from recommendation file\n",
    "from KineticLearning import readARTrecommendationFile\n",
    "design = readARTrecommendationFile (design, all_enzymes, '12strains_initial_design_seed1.csv')\n",
    "\n",
    "listStrains=design.keys()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Translate strains design to kf/m/l values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:26.697038Z",
     "start_time": "2023-11-23T05:38:26.684752Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Design parameter: kf\n"
     ]
    }
   ],
   "source": [
    "# Specify which enzyme expression parameter to design\n",
    "design_K = 'kf' # 'kf', 'km', 'kl'\n",
    "\n",
    "if design_K == 'kf':\n",
    "    ke_startPosition= 0\n",
    "    print ('Design parameter: kf')\n",
    "elif design_K == 'km':\n",
    "    ke_startPosition=1\n",
    "    print ('Design parameter: km')\n",
    "elif design_K == 'kl':\n",
    "    ke_startPosition == 2\n",
    "    print ('Design parameter: kl')\n",
    "else:\n",
    "    print ('WARNING; ENZYME PARAMETER K(f/l/m) TO DESIGN UNCLEAR.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:26.706229Z",
     "start_time": "2023-11-23T05:38:26.698034Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "kf for WT read in:\n",
      "[2743979.608568015, 2741289.5704731075, 1818594.53615137, 2067309.1004114666, 1538319.7813797342, 4141340.591266694, 4386245.941429872, 1261146.0175475124, 1508639.88680511]\n",
      "\n",
      "from WT ke:\n",
      "[2.74397961e+06 1.23333609e-01 5.94696230e+01 2.74128957e+06\n",
      " 4.78331022e-01 3.97301339e+01 1.81859454e+06 6.57343870e-01\n",
      " 3.69689206e+01 2.06730910e+06 6.59020449e-01 5.76227885e+01\n",
      " 1.53831978e+06 5.62220309e-01 2.65995879e+01 4.14134059e+06\n",
      " 8.68577763e-01 5.44813154e+01 4.38624594e+06 1.71680929e-01\n",
      " 5.54721481e+01 1.26114602e+06 4.85310095e-01 1.86877824e+01\n",
      " 1.50863989e+06 6.37070778e-01 3.03410801e+01]\n"
     ]
    }
   ],
   "source": [
    "#--- read enzyme conc in WT\n",
    "kl_WT=[]\n",
    "for i in range(ke_startPosition,len(ke),3): #every 3rd value in ke starting from ke_startPosition\n",
    "    kl_WT.append(ke[i])\n",
    "\n",
    "# PRINT OUT\n",
    "print ( design_K + ' for WT read in:')\n",
    "print (kl_WT)\n",
    "print ('\\nfrom WT ke:')\n",
    "print (ke)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:26.722210Z",
     "start_time": "2023-11-23T05:38:26.706229Z"
    },
    "code_folding": [
     25
    ],
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9 kf values translated for:\n",
      "\n",
      "WT\n",
      "[2743979.608568015, 2741289.5704731075, 1818594.53615137, 2067309.1004114666, 1538319.7813797342, 4141340.591266694, 4386245.941429872, 1261146.0175475124, 1508639.88680511]\n",
      "Strain 1\n",
      "[6821533.306900086, 6814845.872196146, 785632.8396173918, 5139330.423622906, 664554.1455560451, 4141340.591266694, 1894858.2466977048, 3135208.999623116, 651732.4310998075]\n",
      "Strain 2\n",
      "[1185399.1909013826, 1184237.0944443825, 4521026.016872306, 893077.5313777536, 3824262.9765100195, 10295372.709889002, 4386245.941429872, 1261146.0175475124, 651732.4310998075]\n",
      "Strain 3\n",
      "[6821533.306900086, 1184237.0944443825, 785632.8396173918, 893077.5313777536, 1538319.7813797342, 10295372.709889002, 4386245.941429872, 1261146.0175475124, 651732.4310998075]\n",
      "Strain 4\n",
      "[1185399.1909013826, 6814845.872196146, 4521026.016872306, 893077.5313777536, 3824262.9765100195, 10295372.709889002, 1894858.2466977048, 3135208.999623116, 3750478.7585975034]\n",
      "Strain 5\n",
      "[6821533.306900086, 2741289.5704731075, 4521026.016872306, 2067309.1004114666, 664554.1455560451, 4141340.591266694, 10904207.410394663, 544815.0795805254, 1508639.88680511]\n",
      "Strain 6\n",
      "[2743979.608568015, 1184237.0944443825, 1818594.53615137, 893077.5313777536, 1538319.7813797342, 1789059.1354272119, 10904207.410394663, 3135208.999623116, 1508639.88680511]\n",
      "Strain 7\n",
      "[6821533.306900086, 6814845.872196146, 785632.8396173918, 5139330.423622906, 664554.1455560451, 1789059.1354272119, 4386245.941429872, 1261146.0175475124, 3750478.7585975034]\n",
      "Strain 8\n",
      "[1185399.1909013826, 2741289.5704731075, 1818594.53615137, 2067309.1004114666, 1538319.7813797342, 10295372.709889002, 10904207.410394663, 3135208.999623116, 1508639.88680511]\n",
      "Strain 9\n",
      "[2743979.608568015, 2741289.5704731075, 1818594.53615137, 5139330.423622906, 664554.1455560451, 4141340.591266694, 1894858.2466977048, 544815.0795805254, 1508639.88680511]\n",
      "Strain 10\n",
      "[2743979.608568015, 1184237.0944443825, 4521026.016872306, 2067309.1004114666, 3824262.9765100195, 4141340.591266694, 10904207.410394663, 544815.0795805254, 3750478.7585975034]\n",
      "Strain 11\n",
      "[1185399.1909013826, 2741289.5704731075, 1818594.53615137, 5139330.423622906, 3824262.9765100195, 1789059.1354272119, 1894858.2466977048, 1261146.0175475124, 651732.4310998075]\n"
     ]
    }
   ],
   "source": [
    "#--- translate design to enzyme conc for recommended strains\n",
    "from KineticLearning import addNoise, addNoise2\n",
    "\n",
    "design_kl={}\n",
    "print ( '9 ' + design_K + ' values translated for:\\n')\n",
    "\n",
    "# biologicalNoise = 0.05\n",
    "\n",
    "for strain in listStrains: # go thru each strain\n",
    "\n",
    "    if len(design[strain]) == len (kl_WT):\n",
    "\n",
    "        designList=design[strain] # get design for all enzymes (1:unchanged, 2: upreg, 0: downreg)\n",
    "\n",
    "        # map to actual protein levels (% of WT)\n",
    "        for i in range(len(designList)): #go thru each enzyme design\n",
    "            if designList[i] == 2:\n",
    "                designList[i]= kl_WT[i]*2.486 # 92%/37% promoter strength, Shukal et al. 2019 virifloral paper\n",
    "            elif designList[i] == 0:\n",
    "                designList[i]= kl_WT[i]*0.432 # 16%/37% promoter strength\n",
    "            else:\n",
    "                designList[i]=kl_WT[i]*1.0 # All other design assumed to be 1 (unchanged)\n",
    "\n",
    "        # add biological noise to kl values (initial conc)\n",
    "        designList = addNoise2(designList, biologicalNoise, biologicalNoiseSeed) # 0 make biologically-noisy kl values replicable\n",
    "        \n",
    "        design_kl[strain]=designList # store designed kl (initial enzymes conc) for each strain\n",
    "        print (strain)\n",
    "        print (design_kl[strain])\n",
    "    else:\n",
    "        print ('Number of enzymes being accounted for in design dict for ' + strain + ' not matching kl_WT list')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# * SET initial metabolites conc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:26.737258Z",
     "start_time": "2023-11-23T05:38:26.724205Z"
    },
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INITIAL metabolite conc with their ordering following model reactions:\n",
      "[0.3, 0.2, 0.05, 0.3, 0.02, 0.2, 0.01, 0.04, 0.05, 0.0]\n"
     ]
    }
   ],
   "source": [
    "# initial conc -------- AcCoA,'AcAcCoA,HMG-CoA,Mev,MevP,MevPP,IPP,DMAPP,GPP,Limonene\n",
    "initialMetabolitesConc = [0.3,   0.2,  0.05,  0.3, 0.02, 0.2, 0.01, 0.04, 0.05, 0] # like empirical data\n",
    "\n",
    "# set initial limonene conc at 0, other 9 metabolites at 0.2\n",
    "#initialMetabolitesConc = [0.2]*(10-1) + [0]\n",
    "\n",
    "# biologicalNoise = 0.05\n",
    "# noiseSeed =2\n",
    "\n",
    "# add biological variations\n",
    "initialMetabolitesConc = addNoise2(initialMetabolitesConc, biologicalNoise, biologicalNoiseSeed)\n",
    "\n",
    "print ('INITIAL metabolite conc with their ordering following model reactions:\\n' +str(initialMetabolitesConc))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# --- SET technical noise\n",
    "\n",
    "Affects enzymes & conc measurements\n",
    "\n",
    "Technical replicates: change 'technicalNoiseSeed' variable & rerun this & next 3 sections."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:26.754831Z",
     "start_time": "2023-11-23T05:38:26.739069Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "technical noise:0.075\n"
     ]
    }
   ],
   "source": [
    "# Convention: technicalNoiseSeed = 0 -> no noise\n",
    "#             technicalNoiseSeed = 1 -> replicate 1 with noise\n",
    "#             technicalNoiseSeed = 2 -> replicate 2 with noise\n",
    "#             technicalNoiseSeed = 3 -> replicate 3 with noise\n",
    "# ENSURE technicalNoiseSeed & replicate variables CORRESPOND, i.e., 1 <-> '1'\n",
    "\n",
    "technicalNoiseSeed = 0 # Any different number to generate different replicate\n",
    "\n",
    "if technicalNoiseSeed == 0:\n",
    "    noiseLevel = 0 #\n",
    "else:\n",
    "    noiseLevel = 75 # to change\n",
    "\n",
    "technicalNoise = noiseLevel/1000 # Gaussian noise with standard deviation of 2.5% of underlying value\n",
    "    \n",
    "replicate = str(technicalNoiseSeed) + str('rep_') + str(noiseLevel) + 'noiseLevel' # Any different string to change output to a different file\n",
    "\n",
    "print ('technical noise:' + str(technicalNoise))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simulate metabolomics & proteomics time-series data for recommended strains"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:27.141141Z",
     "start_time": "2023-11-23T05:38:26.756946Z"
    },
    "code_folding": [
     10
    ],
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "ke of designed strain WT: \n",
      "[2.74397961e+06 1.23333609e-01 5.94696230e+01 2.74128957e+06\n",
      " 4.78331022e-01 3.97301339e+01 1.81859454e+06 6.57343870e-01\n",
      " 3.69689206e+01 2.06730910e+06 6.59020449e-01 5.76227885e+01\n",
      " 1.53831978e+06 5.62220309e-01 2.65995879e+01 4.14134059e+06\n",
      " 8.68577763e-01 5.44813154e+01 4.38624594e+06 1.71680929e-01\n",
      " 5.54721481e+01 1.26114602e+06 4.85310095e-01 1.86877824e+01\n",
      " 1.50863989e+06 6.37070778e-01 3.03410801e+01]\n",
      "Updated using designed kl\n",
      "[2743979.608568015, 2741289.5704731075, 1818594.53615137, 2067309.1004114666, 1538319.7813797342, 4141340.591266694, 4386245.941429872, 1261146.0175475124, 1508639.88680511]\n",
      "\n",
      "ke of designed strain Strain 1: \n",
      "[6.82153331e+06 1.23333609e-01 5.94696230e+01 6.81484587e+06\n",
      " 4.78331022e-01 3.97301339e+01 7.85632840e+05 6.57343870e-01\n",
      " 3.69689206e+01 5.13933042e+06 6.59020449e-01 5.76227885e+01\n",
      " 6.64554146e+05 5.62220309e-01 2.65995879e+01 4.14134059e+06\n",
      " 8.68577763e-01 5.44813154e+01 1.89485825e+06 1.71680929e-01\n",
      " 5.54721481e+01 3.13520900e+06 4.85310095e-01 1.86877824e+01\n",
      " 6.51732431e+05 6.37070778e-01 3.03410801e+01]\n",
      "Updated using designed kl\n",
      "[6821533.306900086, 6814845.872196146, 785632.8396173918, 5139330.423622906, 664554.1455560451, 4141340.591266694, 1894858.2466977048, 3135208.999623116, 651732.4310998075]\n",
      "\n",
      "ke of designed strain Strain 2: \n",
      "[1.18539919e+06 1.23333609e-01 5.94696230e+01 1.18423709e+06\n",
      " 4.78331022e-01 3.97301339e+01 4.52102602e+06 6.57343870e-01\n",
      " 3.69689206e+01 8.93077531e+05 6.59020449e-01 5.76227885e+01\n",
      " 3.82426298e+06 5.62220309e-01 2.65995879e+01 1.02953727e+07\n",
      " 8.68577763e-01 5.44813154e+01 4.38624594e+06 1.71680929e-01\n",
      " 5.54721481e+01 1.26114602e+06 4.85310095e-01 1.86877824e+01\n",
      " 6.51732431e+05 6.37070778e-01 3.03410801e+01]\n",
      "Updated using designed kl\n",
      "[1185399.1909013826, 1184237.0944443825, 4521026.016872306, 893077.5313777536, 3824262.9765100195, 10295372.709889002, 4386245.941429872, 1261146.0175475124, 651732.4310998075]\n",
      "\n",
      "ke of designed strain Strain 3: \n",
      "[6.82153331e+06 1.23333609e-01 5.94696230e+01 1.18423709e+06\n",
      " 4.78331022e-01 3.97301339e+01 7.85632840e+05 6.57343870e-01\n",
      " 3.69689206e+01 8.93077531e+05 6.59020449e-01 5.76227885e+01\n",
      " 1.53831978e+06 5.62220309e-01 2.65995879e+01 1.02953727e+07\n",
      " 8.68577763e-01 5.44813154e+01 4.38624594e+06 1.71680929e-01\n",
      " 5.54721481e+01 1.26114602e+06 4.85310095e-01 1.86877824e+01\n",
      " 6.51732431e+05 6.37070778e-01 3.03410801e+01]\n",
      "Updated using designed kl\n",
      "[6821533.306900086, 1184237.0944443825, 785632.8396173918, 893077.5313777536, 1538319.7813797342, 10295372.709889002, 4386245.941429872, 1261146.0175475124, 651732.4310998075]\n",
      "\n",
      "ke of designed strain Strain 4: \n",
      "[1.18539919e+06 1.23333609e-01 5.94696230e+01 6.81484587e+06\n",
      " 4.78331022e-01 3.97301339e+01 4.52102602e+06 6.57343870e-01\n",
      " 3.69689206e+01 8.93077531e+05 6.59020449e-01 5.76227885e+01\n",
      " 3.82426298e+06 5.62220309e-01 2.65995879e+01 1.02953727e+07\n",
      " 8.68577763e-01 5.44813154e+01 1.89485825e+06 1.71680929e-01\n",
      " 5.54721481e+01 3.13520900e+06 4.85310095e-01 1.86877824e+01\n",
      " 3.75047876e+06 6.37070778e-01 3.03410801e+01]\n",
      "Updated using designed kl\n",
      "[1185399.1909013826, 6814845.872196146, 4521026.016872306, 893077.5313777536, 3824262.9765100195, 10295372.709889002, 1894858.2466977048, 3135208.999623116, 3750478.7585975034]\n",
      "\n",
      "ke of designed strain Strain 5: \n",
      "[6.82153331e+06 1.23333609e-01 5.94696230e+01 2.74128957e+06\n",
      " 4.78331022e-01 3.97301339e+01 4.52102602e+06 6.57343870e-01\n",
      " 3.69689206e+01 2.06730910e+06 6.59020449e-01 5.76227885e+01\n",
      " 6.64554146e+05 5.62220309e-01 2.65995879e+01 4.14134059e+06\n",
      " 8.68577763e-01 5.44813154e+01 1.09042074e+07 1.71680929e-01\n",
      " 5.54721481e+01 5.44815080e+05 4.85310095e-01 1.86877824e+01\n",
      " 1.50863989e+06 6.37070778e-01 3.03410801e+01]\n",
      "Updated using designed kl\n",
      "[6821533.306900086, 2741289.5704731075, 4521026.016872306, 2067309.1004114666, 664554.1455560451, 4141340.591266694, 10904207.410394663, 544815.0795805254, 1508639.88680511]\n",
      "\n",
      "ke of designed strain Strain 6: \n",
      "[2.74397961e+06 1.23333609e-01 5.94696230e+01 1.18423709e+06\n",
      " 4.78331022e-01 3.97301339e+01 1.81859454e+06 6.57343870e-01\n",
      " 3.69689206e+01 8.93077531e+05 6.59020449e-01 5.76227885e+01\n",
      " 1.53831978e+06 5.62220309e-01 2.65995879e+01 1.78905914e+06\n",
      " 8.68577763e-01 5.44813154e+01 1.09042074e+07 1.71680929e-01\n",
      " 5.54721481e+01 3.13520900e+06 4.85310095e-01 1.86877824e+01\n",
      " 1.50863989e+06 6.37070778e-01 3.03410801e+01]\n",
      "Updated using designed kl\n",
      "[2743979.608568015, 1184237.0944443825, 1818594.53615137, 893077.5313777536, 1538319.7813797342, 1789059.1354272119, 10904207.410394663, 3135208.999623116, 1508639.88680511]\n",
      "\n",
      "ke of designed strain Strain 7: \n",
      "[6.82153331e+06 1.23333609e-01 5.94696230e+01 6.81484587e+06\n",
      " 4.78331022e-01 3.97301339e+01 7.85632840e+05 6.57343870e-01\n",
      " 3.69689206e+01 5.13933042e+06 6.59020449e-01 5.76227885e+01\n",
      " 6.64554146e+05 5.62220309e-01 2.65995879e+01 1.78905914e+06\n",
      " 8.68577763e-01 5.44813154e+01 4.38624594e+06 1.71680929e-01\n",
      " 5.54721481e+01 1.26114602e+06 4.85310095e-01 1.86877824e+01\n",
      " 3.75047876e+06 6.37070778e-01 3.03410801e+01]\n",
      "Updated using designed kl\n",
      "[6821533.306900086, 6814845.872196146, 785632.8396173918, 5139330.423622906, 664554.1455560451, 1789059.1354272119, 4386245.941429872, 1261146.0175475124, 3750478.7585975034]\n",
      "\n",
      "ke of designed strain Strain 8: \n",
      "[1.18539919e+06 1.23333609e-01 5.94696230e+01 2.74128957e+06\n",
      " 4.78331022e-01 3.97301339e+01 1.81859454e+06 6.57343870e-01\n",
      " 3.69689206e+01 2.06730910e+06 6.59020449e-01 5.76227885e+01\n",
      " 1.53831978e+06 5.62220309e-01 2.65995879e+01 1.02953727e+07\n",
      " 8.68577763e-01 5.44813154e+01 1.09042074e+07 1.71680929e-01\n",
      " 5.54721481e+01 3.13520900e+06 4.85310095e-01 1.86877824e+01\n",
      " 1.50863989e+06 6.37070778e-01 3.03410801e+01]\n",
      "Updated using designed kl\n",
      "[1185399.1909013826, 2741289.5704731075, 1818594.53615137, 2067309.1004114666, 1538319.7813797342, 10295372.709889002, 10904207.410394663, 3135208.999623116, 1508639.88680511]\n",
      "\n",
      "ke of designed strain Strain 9: \n",
      "[2.74397961e+06 1.23333609e-01 5.94696230e+01 2.74128957e+06\n",
      " 4.78331022e-01 3.97301339e+01 1.81859454e+06 6.57343870e-01\n",
      " 3.69689206e+01 5.13933042e+06 6.59020449e-01 5.76227885e+01\n",
      " 6.64554146e+05 5.62220309e-01 2.65995879e+01 4.14134059e+06\n",
      " 8.68577763e-01 5.44813154e+01 1.89485825e+06 1.71680929e-01\n",
      " 5.54721481e+01 5.44815080e+05 4.85310095e-01 1.86877824e+01\n",
      " 1.50863989e+06 6.37070778e-01 3.03410801e+01]\n",
      "Updated using designed kl\n",
      "[2743979.608568015, 2741289.5704731075, 1818594.53615137, 5139330.423622906, 664554.1455560451, 4141340.591266694, 1894858.2466977048, 544815.0795805254, 1508639.88680511]\n",
      "\n",
      "ke of designed strain Strain 10: \n",
      "[2.74397961e+06 1.23333609e-01 5.94696230e+01 1.18423709e+06\n",
      " 4.78331022e-01 3.97301339e+01 4.52102602e+06 6.57343870e-01\n",
      " 3.69689206e+01 2.06730910e+06 6.59020449e-01 5.76227885e+01\n",
      " 3.82426298e+06 5.62220309e-01 2.65995879e+01 4.14134059e+06\n",
      " 8.68577763e-01 5.44813154e+01 1.09042074e+07 1.71680929e-01\n",
      " 5.54721481e+01 5.44815080e+05 4.85310095e-01 1.86877824e+01\n",
      " 3.75047876e+06 6.37070778e-01 3.03410801e+01]\n",
      "Updated using designed kl\n",
      "[2743979.608568015, 1184237.0944443825, 4521026.016872306, 2067309.1004114666, 3824262.9765100195, 4141340.591266694, 10904207.410394663, 544815.0795805254, 3750478.7585975034]\n",
      "\n",
      "ke of designed strain Strain 11: \n",
      "[1.18539919e+06 1.23333609e-01 5.94696230e+01 2.74128957e+06\n",
      " 4.78331022e-01 3.97301339e+01 1.81859454e+06 6.57343870e-01\n",
      " 3.69689206e+01 5.13933042e+06 6.59020449e-01 5.76227885e+01\n",
      " 3.82426298e+06 5.62220309e-01 2.65995879e+01 1.78905914e+06\n",
      " 8.68577763e-01 5.44813154e+01 1.89485825e+06 1.71680929e-01\n",
      " 5.54721481e+01 1.26114602e+06 4.85310095e-01 1.86877824e+01\n",
      " 6.51732431e+05 6.37070778e-01 3.03410801e+01]\n",
      "Updated using designed kl\n",
      "[1185399.1909013826, 2741289.5704731075, 1818594.53615137, 5139330.423622906, 3824262.9765100195, 1789059.1354272119, 1894858.2466977048, 1261146.0175475124, 651732.4310998075]\n",
      "97 time-series datapoints solved for 10 metabolites for all strains\n"
     ]
    }
   ],
   "source": [
    "from scipy.integrate import odeint,ode\n",
    "import csv\n",
    "\n",
    "# headers for output files\n",
    "CSV = [ ['Strain','Time/hours'] + all_metabolites ]\n",
    "CSV2 = [ ['Strain','Time/hours'] + all_enzymes ]\n",
    "\n",
    "sol_strain={} # dict [strain] = a list with each element holding time-series conc for a metabolite\n",
    "noisy_sol_strain={} # include noise for above\n",
    "\n",
    "#listStrains =[]\n",
    "#listStrains.append('WT')\n",
    "\n",
    "\n",
    "\n",
    "for strain in listStrains: # for each of first 8 strains\n",
    "    \n",
    "    designKlList=design_kl[strain]  # get its kl value for enzymes\n",
    "    keList=ke # prepare its ke template\n",
    "\n",
    "    # update ke template with its kf/m/l values\n",
    "    count=0\n",
    "    for i in range(ke_startPosition,len(keList),3): # every 3rd value in keList starting from ke_startPosition\n",
    "        keList[i]= designKlList[count]\n",
    "        count=count+1\n",
    "    #'''\n",
    "    print ('\\nke of designed strain ' + strain + ': ')\n",
    "    print (keList)\n",
    "    print ('Updated using designed kl')\n",
    "    print (designKlList)\n",
    "    \n",
    "    \n",
    "    # Build customized model\n",
    "    ODE = lambda metabolites,t: kinetic_model_xtk( metabolites, t, np.append(keList, kr))\n",
    "    \n",
    "    # Solve for metabolite conc at various timePoints based on initialMetabolitesConc\n",
    "    sol = odeint(ODE,initialMetabolitesConc,timePoints).tolist()\n",
    "    sol_strain [strain]=sol\n",
    "    # print (sol_strain[strain])\n",
    "    \n",
    "    # Include measurement noise for metabolites\n",
    "    sol = addNoise(sol,technicalNoise, technicalNoiseSeed)\n",
    "    noisy_sol_strain [strain] = sol\n",
    "    # print (str(len(sol)) + ' time-series datapoints solved for '  + str(len(sol[0])) + ' metabolites in ' + strain + ' strain')\n",
    "    \n",
    "    # Metabolite print format\n",
    "    lines = [  [ strain,timePoints[i] ] + line for i,line in enumerate(sol)  ]\n",
    "    CSV = CSV + lines\n",
    "    \n",
    "    # Enzyme print format\n",
    "    sol2=[]\n",
    "    for t in timePoints:\n",
    "        e = proteomicsData(t,keList) # get vector of enzyme conc at time t\n",
    "        sol2.append(e)\n",
    "    # Include measurement noise for enzymes\n",
    "    sol2 = addNoise(sol2, technicalNoise, technicalNoiseSeed)\n",
    "    lines2 = [  [ strain,timePoints[i] ] + line for i,line in enumerate(sol2)  ]\n",
    "    CSV2 = CSV2 + lines2\n",
    "\n",
    "print (str(len(sol)) + ' time-series datapoints solved for '  + str(len(sol[0])) + ' metabolites for all strains')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ** Output simulated strain data to file\n",
    "\n",
    "\n",
    "Technical replicates: re-run previous two sections with this one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:27.288851Z",
     "start_time": "2023-11-23T05:38:27.143129Z"
    },
    "code_folding": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "data/0rep_75noiseLevel_12strains_initial_design_seed1_12strains_ENZYME.csv created.\n",
      "\n",
      "data/0rep_75noiseLevel_12strains_initial_design_seed1_12strains_METABOLITE.csv created.\n"
     ]
    }
   ],
   "source": [
    "# Output simulated enzyme data to file \n",
    "fileName2 = 'data/' + replicate + '_' + shelve_name + str(len(listStrains)) + 'strains_ENZYME.csv'\n",
    "with open(fileName2, 'w', newline='') as csvfile2:\n",
    "    writer2 = csv.writer(csvfile2)\n",
    "    writer2.writerows(CSV2)\n",
    "print ('\\n' + fileName2 + ' created.') \n",
    "\n",
    "# Output simulated metabolite data to file \n",
    "fileName =  'data/' + replicate + '_' + shelve_name + str(len(listStrains)) + 'strains_METABOLITE.csv'\n",
    "with open(fileName, 'w', newline='') as csvfile:\n",
    "    writer = csv.writer(csvfile)\n",
    "    writer.writerows(CSV)\n",
    "print ('\\n' + fileName + ' created.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# convert small negative metabolite conc. values ( magnitude < 10**-7) to e-12\n",
    "\n",
    "i.e., simulate machine error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:27.353557Z",
     "start_time": "2023-11-23T05:38:27.289846Z"
    },
    "code_folding": [
     2
    ]
   },
   "outputs": [],
   "source": [
    "df_1=pd.read_csv(fileName)\n",
    "\n",
    "# convert any value in file to 0 if < 0\n",
    "# df_1X=df_1.apply(lambda x: x.apply(lambda y: 0 if y < 0 else y) if np.issubdtype(x.dtype, np.number) else x)\n",
    "\n",
    "# convert any value in file to e-12 if <= 0\n",
    "df_1X=df_1.apply(lambda x: x.apply(lambda y: 10**-12 if y < 0.0 else y) if np.issubdtype(x.dtype, np.number) else x)\n",
    "df_1X.to_csv(fileName+'.csv', index=False)\n",
    "\n",
    "# remove earlier file\n",
    "import os\n",
    "os.remove(fileName)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Explore simulated metabolite kinetics in WT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-23T05:38:29.010945Z",
     "start_time": "2023-11-23T05:38:27.354990Z"
    },
    "code_folding": [],
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acetyl-CoA\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acetoacetyl-CoA\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "HMG-CoA\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mev\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MevP\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MevPP\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "IPP\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DMAPP\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "GPP\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Limonene\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from KineticLearning import plotSimulatedKinetics\n",
    "sol_WT = noisy_sol_strain['WT']\n",
    "plotSimulatedKinetics (all_metabolites, sol_WT,timePoints)"
   ]
  }
 ],
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