facs_data.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4fd5e071-ffce-4ce6-b4f1-adf0ba7b34bb",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [],
   "source": [
    "# uncomment install packages\n",
    "#! pip install FlowCal\n",
    "#! pip install pandas\n",
    "#! pip install numpy\n",
    "#! pip install scipy\n",
    "#! pip install seaborn\n",
    "#! pip install matplotlib\n",
    "#! pip install rpy2\n",
    "# need to install flan package in R"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "ab3b6997-808c-4951-9066-310e039e5f35",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from math import *\n",
    "import FlowCal as FC\n",
    "import seaborn as sns\n",
    "import os\n",
    "\n",
    "# variants from a common file\n",
    "import function_fcs as fc\n",
    "from importlib import reload\n",
    "reload(fc)\n",
    "\n",
    "from matplotlib import colormaps\n",
    "from scipy.stats import ttest_ind, t, skew\n",
    "\n",
    "random_seed = 12  # Choose any integer value\n",
    "np.random.seed(random_seed)\n",
    "\n",
    "file_dir=os.getcwd()+'/'\n",
    "mut_output='mutant_events/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "4365c441-a473-45fb-b72e-ece6820f7068",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.02\n"
     ]
    }
   ],
   "source": [
    "folder_='EvolvR/'\n",
    "pcn_=[3,5,9,17,25]\n",
    "'''\n",
    "files_=dict()\n",
    "for k in range(0,len(pcn_)):\n",
    "    flist_=[]\n",
    "    fname=[]\n",
    "    for i in range(0,8):\n",
    "        tmp=file_dir+folder_+folder_[:-1]+'_PCN'+str(pcn_[k])+'_trial'+str(i)+'.fcs'\n",
    "        fname.append(tmp)\n",
    "\n",
    "    flist_=fc.fcs_dataframe_(fname,print_=False)\n",
    "    files_[str(pcn_[k])]=flist_\n",
    "\n",
    "files_evolvR=files_\n",
    "'''\n",
    "#============================\n",
    "p_value= fc.alpha_\n",
    "print(p_value)\n",
    "\n",
    "dataset_boxplot=[]\n",
    "dataset_mut=[]\n",
    "dataset_events=[]\n",
    "\n",
    "for k in range(0,len(pcn_)):\n",
    "    PCN_=str(pcn_[k])\n",
    "    dataset=files_evolvR[PCN_]['fcs']\n",
    "\n",
    "    data_=[]   # total events count\n",
    "    mutant_=[] # mutant events count\n",
    "    arr_=[]    # ratio\n",
    "\n",
    "    for data in dataset:\n",
    "        mut_indx=fc.variants_(data, data, p_value)\n",
    "        mut_=data[mut_indx]\n",
    "        arr_.append(len(mut_)/len(data)*100)\n",
    "        mutant_.append(len(mut_))\n",
    "        data_.append(len(data))\n",
    "        \n",
    "    dataset_boxplot.append(arr_)\n",
    "    dataset_mut.append(mutant_)\n",
    "    dataset_events.append(data_)\n",
    "\n",
    "# save mutant and events count in 'mutant_events/' directory, can be run only at the beginning\n",
    "# the exact number may vary depending on python libraries\n",
    "\n",
    "#fc.write_mutant_file(dataset_mut, mut_output+folder_[:-1]+'_mut.txt')\n",
    "#fc.write_events_file(dataset_events, mut_output+folder_[:-1]+'_events.txt')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "6a0f16b9-5a01-48ce-b75b-4d9ee1730d4f",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mutant_events/EvolvR_mut.txt mutant_events/EvolvR_events.txt\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 850x250 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "folder_='EvolvR/'\n",
    "mut_file=mut_output+folder_[:-1]+'_mut.txt'\n",
    "event_file=mut_output+folder_[:-1]+'_events.txt'\n",
    "colors_=colormaps['coolwarm']\n",
    "print(mut_file,event_file)\n",
    "#=============================\n",
    "labellist=pcn_\n",
    "\n",
    "fig=plt.figure(figsize=(8.5,2.5))\n",
    "#---------------------\n",
    "ax1_= plt.subplot(131)\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "fc.fig_boxplot_N(dataset_boxplot,labellist,title='',ax=ax1_)\n",
    "plt.xlim([1,50])\n",
    "plt.ylim([-0.002,0.075])\n",
    "#plt.xticks([1,10,100],['$10^0$', '$10^1$','$10^2$'])\n",
    "\n",
    "#---------------------\n",
    "ax_= plt.subplot(132)\n",
    "\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "mutprob, sdmutprob=fc.read_mut_file(mut_file,event_file,'GF')\n",
    "fc.fig_mutprob(mutprob,sdmutprob,labellist,colors_,ax_)\n",
    "plt.xlim([1,50])\n",
    "plt.title('generating function', fontsize=10)\n",
    "plt.annotate('b',xy=(-0.5, 1), xycoords='axes fraction',fontsize=12, fontweight='bold')\n",
    "\n",
    "#----------------------\n",
    "ax_= plt.subplot(133)\n",
    "\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "mutprob, sdmutprob=fc.read_mut_file(mut_file,event_file,'ML')\n",
    "fc.fig_mutprob(mutprob,sdmutprob,labellist,colors_,ax_)\n",
    "plt.xlim([1,50])\n",
    "plt.title('maximum likelihood', fontsize=10)\n",
    "\n",
    "#=======================\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "01e76b61-0942-4f2a-91cf-0983b982c4bc",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.02\n"
     ]
    }
   ],
   "source": [
    "reload(fc)  #IFFL_gain\n",
    "\n",
    "folder_='IFFL_gain/'\n",
    "pcn_=[3,5,17,39,79]\n",
    "\n",
    "'''\n",
    "files_=dict()\n",
    "for k in range(0,len(pcn_)):\n",
    "    flist_=[]\n",
    "    fname=[]\n",
    "    for i in range(0,8):\n",
    "        tmp=file_dir+folder_+folder_[:-1]+'_PCN'+str(pcn_[k])+'_trial'+str(i)+'.fcs'\n",
    "        fname.append(tmp)\n",
    "\n",
    "    flist_=fc.fcs_dataframe_(fname,print_=False)\n",
    "    files_[str(pcn_[k])]=flist_\n",
    "\n",
    "files_gain=files_\n",
    "'''\n",
    "#============================\n",
    "p_value= fc.alpha_\n",
    "print(p_value)\n",
    "\n",
    "dataset_boxplot=[]\n",
    "dataset_mut=[]\n",
    "dataset_events=[]\n",
    "\n",
    "for k in range(0,len(pcn_)):\n",
    "    PCN_=str(pcn_[k])\n",
    "    dataset=files_gain[PCN_]['fcs']\n",
    "\n",
    "    data_=[]   # total events count\n",
    "    mutant_=[] # mutant events count\n",
    "    arr_=[]    # ratio\n",
    "\n",
    "    for data in dataset:\n",
    "        mut_indx=fc.variants_(data, data, p_value)\n",
    "        mut_=data[mut_indx]\n",
    "        arr_.append(len(mut_)/len(data)*100)\n",
    "        mutant_.append(len(mut_))\n",
    "        data_.append(len(data))\n",
    "        \n",
    "    dataset_boxplot.append(arr_)\n",
    "    dataset_mut.append(mutant_)\n",
    "    dataset_events.append(data_)\n",
    "\n",
    "# save mutant and events count in 'mutant_events/' directory, can be run only at the beginning\n",
    "# the exact number may vary depending on python libraries\n",
    "\n",
    "#fc.write_mutant_file(dataset_mut, mut_output+folder_[:-1]+'_mut.txt')\n",
    "#fc.write_events_file(dataset_events, mut_output+folder_[:-1]+'_events.txt')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "8906d6e5-2852-4fc5-9795-d42a2224082e",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mutant_events/IFFL_gain_mut.txt mutant_events/IFFL_gain_events.txt\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 850x250 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "folder_='IFFL_gain/'\n",
    "mut_file=mut_output+folder_[:-1]+'_mut.txt'\n",
    "event_file=mut_output+folder_[:-1]+'_events.txt'\n",
    "colors_=colormaps['coolwarm']\n",
    "print(mut_file,event_file)\n",
    "\n",
    "#====================================\n",
    "labellist=pcn_\n",
    "\n",
    "fig=plt.figure(figsize=(8.5,2.5))\n",
    "#---------------------\n",
    "ax1_= plt.subplot(131)\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "fc.fig_boxplot_N(dataset_boxplot,labellist,title='',ax=ax1_)\n",
    "plt.xlim([1,150])\n",
    "plt.ylim(-0.0015,0.055)\n",
    "plt.xticks([1,10,100],['$10^0$', '$10^1$','$10^2$'])\n",
    "\n",
    "#---------------------\n",
    "ax_= plt.subplot(132)\n",
    "\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "mutprob, sdmutprob=fc.read_mut_file(mut_file,event_file,'GF')\n",
    "fc.fig_mutprob(mutprob,sdmutprob,labellist,colors_,ax_)\n",
    "plt.xlim([1,150])\n",
    "plt.title('generating function', fontsize=10)\n",
    "plt.annotate('b',xy=(-0.5, 1), xycoords='axes fraction',fontsize=12, fontweight='bold')\n",
    "\n",
    "#----------------------\n",
    "ax_= plt.subplot(133)\n",
    "\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "mutprob, sdmutprob=fc.read_mut_file(mut_file,event_file,'ML')\n",
    "fc.fig_mutprob(mutprob,sdmutprob,labellist,colors_,ax_)\n",
    "plt.xlim([1,150])\n",
    "plt.title('maximum likelihood', fontsize=10)\n",
    "\n",
    "#=======================\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "2d7efd3d-420c-4126-9fd2-4c92ca732dd2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.02\n"
     ]
    }
   ],
   "source": [
    "reload(fc) # IFFL_loss\n",
    "\n",
    "folder_='IFFL_loss/'\n",
    "pcn_=[3,5,9,17,39]\n",
    "\n",
    "'''\n",
    "files_=dict()\n",
    "for k in range(0,len(pcn_)):\n",
    "    flist_=[]\n",
    "    fname=[]\n",
    "    for i in range(0,8):\n",
    "        tmp=file_dir+folder_+folder_[:-1]+'_PCN'+str(pcn_[k])+'_trial'+str(i)+'.fcs'\n",
    "        fname.append(tmp)\n",
    "\n",
    "    flist_=fc.fcs_dataframe_(fname,print_=False)\n",
    "    files_[str(pcn_[k])]=flist_\n",
    "\n",
    "files_loss=files_\n",
    "'''\n",
    "#============================\n",
    "p_value= fc.alpha_\n",
    "print(p_value)\n",
    "\n",
    "dataset_boxplot=[]\n",
    "dataset_mut=[]\n",
    "dataset_events=[]\n",
    "\n",
    "for k in range(0,len(pcn_)):\n",
    "    PCN_=str(pcn_[k])\n",
    "    dataset=files_loss[PCN_]['fcs']\n",
    "\n",
    "    data_=[]   # total events count\n",
    "    mutant_=[] # mutant events count\n",
    "    arr_=[]    # ratio\n",
    "\n",
    "    for data in dataset:\n",
    "        mut_indx=fc.variants_(data, data, p_value)\n",
    "        mut_=data[mut_indx]\n",
    "        arr_.append(len(mut_)/len(data)*100)\n",
    "        mutant_.append(len(mut_))\n",
    "        data_.append(len(data))\n",
    "        \n",
    "    dataset_boxplot.append(arr_)\n",
    "    dataset_mut.append(mutant_)\n",
    "    dataset_events.append(data_)\n",
    "\n",
    "# save mutant and events count in 'mutant_events/' directory, can be run only at the beginning\n",
    "# the exact number may vary depending on python libraries\n",
    "\n",
    "#fc.write_mutant_file(dataset_mut, mut_output+folder_[:-1]+'_mut.txt')\n",
    "#fc.write_events_file(dataset_events, mut_output+folder_[:-1]+'_events.txt')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "3541af73-6fbb-4d66-b4c5-300618c6072b",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mutant_events/IFFL_loss_mut.txt mutant_events/IFFL_loss_events.txt\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 850x250 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "folder_='IFFL_loss/'\n",
    "mut_file=mut_output+folder_[:-1]+'_mut.txt'\n",
    "event_file=mut_output+folder_[:-1]+'_events.txt'\n",
    "colors_=colormaps['coolwarm']\n",
    "print(mut_file,event_file)\n",
    "#====================================\n",
    "labellist=pcn_\n",
    "\n",
    "fig=plt.figure(figsize=(8.5,2.5))\n",
    "#---------------------\n",
    "ax1_= plt.subplot(131)\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "fc.fig_boxplot_N(dataset_boxplot,labellist,title='',ax=ax1_)\n",
    "plt.xlim([1,110])\n",
    "plt.ylim(-0.0015,0.055)\n",
    "plt.xticks([1,10,100],['$10^0$', '$10^1$','$10^2$'])\n",
    "\n",
    "#---------------------\n",
    "ax_= plt.subplot(132)\n",
    "\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "mutprob, sdmutprob=fc.read_mut_file(mut_file,event_file,'GF')\n",
    "fc.fig_mutprob(mutprob,sdmutprob,labellist,colors_,ax_)\n",
    "plt.xlim([1,110])\n",
    "plt.title('generating function', fontsize=10)\n",
    "plt.annotate('b',xy=(-0.5, 1), xycoords='axes fraction',fontsize=12, fontweight='bold')\n",
    "\n",
    "#----------------------\n",
    "ax_= plt.subplot(133)\n",
    "\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "mutprob, sdmutprob=fc.read_mut_file(mut_file,event_file,'ML')\n",
    "fc.fig_mutprob(mutprob,sdmutprob,labellist,colors_,ax_)\n",
    "plt.xlim([1,110])\n",
    "plt.title('maximum likelihood', fontsize=10)\n",
    "\n",
    "#=======================\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "9019f466-4b07-4226-b7db-f0203d8013af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.02\n"
     ]
    }
   ],
   "source": [
    "folder_='regulator_lacI/'\n",
    "pcn_=[3,5,9,17,39]\n",
    "\n",
    "'''\n",
    "files_=dict()\n",
    "for k in range(0,len(pcn_)):\n",
    "    flist_=[]\n",
    "    fname=[]\n",
    "    for i in range(0,8):\n",
    "        tmp=file_dir+folder_+folder_[:-1]+'_PCN'+str(pcn_[k])+'_trial'+str(i)+'.fcs'\n",
    "        fname.append(tmp)\n",
    "\n",
    "    flist_=fc.fcs_dataframe_(fname,print_=False)\n",
    "    files_[str(pcn_[k])]=flist_\n",
    "\n",
    "\n",
    "files_regulatorlacI=files_\n",
    "'''\n",
    "#============================\n",
    "p_value= fc.alpha_\n",
    "print(p_value)\n",
    "\n",
    "dataset_boxplot=[]\n",
    "dataset_mut=[]\n",
    "dataset_events=[]\n",
    "\n",
    "for k in range(0,len(pcn_)):\n",
    "    PCN_=str(pcn_[k])\n",
    "    dataset=files_regulatorlacI[PCN_]['fcs']\n",
    "\n",
    "    data_=[]   # total events count\n",
    "    mutant_=[] # mutant events count\n",
    "    arr_=[]    # ratio\n",
    "\n",
    "    for data in dataset:\n",
    "        mut_indx=fc.variants_(data, data, p_value)\n",
    "        mut_=data[mut_indx]\n",
    "        arr_.append(len(mut_)/len(data)*100)\n",
    "        mutant_.append(len(mut_))\n",
    "        data_.append(len(data))\n",
    "        \n",
    "    dataset_boxplot.append(arr_)\n",
    "    dataset_mut.append(mutant_)\n",
    "    dataset_events.append(data_)\n",
    "\n",
    "# save mutant and events count in 'mutant_events/' directory, can be run only at the beginning\n",
    "# the exact number may vary depending on python libraries\n",
    "\n",
    "#fc.write_mutant_file(dataset_mut, mut_output+folder_[:-1]+'_mut.txt')\n",
    "#fc.write_events_file(dataset_events, mut_output+folder_[:-1]+'_events.txt')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "1601e61f-020e-4eaf-bb95-3f51639e7f99",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mutant_events/regulator_lacI_mut.txt mutant_events/regulator_lacI_events.txt\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 850x250 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "folder_='regulator_lacI/'\n",
    "mut_file=mut_output+folder_[:-1]+'_mut.txt'\n",
    "event_file=mut_output+folder_[:-1]+'_events.txt'\n",
    "colors_=colormaps['coolwarm']\n",
    "print(mut_file,event_file)\n",
    "\n",
    "#===========================\n",
    "labellist=pcn_\n",
    "\n",
    "fig=plt.figure(figsize=(8.5,2.5))\n",
    "#--------------------------\n",
    "ax1_= plt.subplot(131)\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "fc.fig_boxplot_N(dataset_boxplot,labellist,title='',ax=ax1_)\n",
    "plt.xlim([1,110])\n",
    "plt.ylim(-0.001,0.035);\n",
    "plt.yticks([0,0.01, 0.02,0.03],['0','0.01','0.02','0.03'])\n",
    "plt.xticks([1,10,100],['$10^0$', '$10^1$','$10^2$'])\n",
    "\n",
    "#----------------\n",
    "ax_= plt.subplot(132)\n",
    "\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "mutprob, sdmutprob=fc.read_mut_file(mut_file,event_file,'GF')\n",
    "fc.fig_mutprob(mutprob,sdmutprob,labellist,colors_,ax_)\n",
    "plt.xlim([1,110])\n",
    "plt.title('generating function', fontsize=10)\n",
    "plt.annotate('b',xy=(-0.5, 1), xycoords='axes fraction',fontsize=12, fontweight='bold')\n",
    "\n",
    "#----------------------\n",
    "ax_= plt.subplot(133)\n",
    "\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "mutprob, sdmutprob=fc.read_mut_file(mut_file,event_file,'ML')\n",
    "fc.fig_mutprob(mutprob,sdmutprob,labellist,colors_,ax_)\n",
    "plt.xlim([1,110])\n",
    "plt.title('maximum likelihood', fontsize=10)\n",
    "\n",
    "#=======================\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "0979f2f1-eaae-4b1d-b212-f2de782d7859",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.02\n"
     ]
    }
   ],
   "source": [
    "folder_='regulator_lacO/'\n",
    "pcn_=[3,5,9,17,39]\n",
    "\n",
    "'''\n",
    "files_=dict()\n",
    "for k in range(0,len(pcn_)):\n",
    "    flist_=[]\n",
    "    fname=[]\n",
    "    for i in range(0,8):\n",
    "        tmp=file_dir+folder_+folder_[:-1]+'_PCN'+str(pcn_[k])+'_trial'+str(i)+'.fcs'\n",
    "        fname.append(tmp)\n",
    "\n",
    "    flist_=fc.fcs_dataframe_(fname,print_=False)\n",
    "    files_[str(pcn_[k])]=flist_\n",
    "\n",
    "files_regulatorlacO=files_\n",
    "'''\n",
    "#============================\n",
    "p_value= fc.alpha_\n",
    "print(p_value)\n",
    "\n",
    "dataset_boxplot=[]\n",
    "dataset_mut=[]\n",
    "dataset_events=[]\n",
    "\n",
    "for k in range(0,len(pcn_)):\n",
    "    PCN_=str(pcn_[k])\n",
    "    dataset=files_regulatorlacO[PCN_]['fcs']\n",
    "\n",
    "    data_=[]   # total events count\n",
    "    mutant_=[] # mutant events count\n",
    "    arr_=[]    # ratio\n",
    "\n",
    "    for data in dataset:\n",
    "        mut_indx=fc.variants_(data, data, p_value)\n",
    "        mut_=data[mut_indx]\n",
    "        arr_.append(len(mut_)/len(data)*100)\n",
    "        mutant_.append(len(mut_))\n",
    "        data_.append(len(data))\n",
    "        \n",
    "    dataset_boxplot.append(arr_)\n",
    "    dataset_mut.append(mutant_)\n",
    "    dataset_events.append(data_)\n",
    "\n",
    "# save mutant and events count in 'mutant_events/' directory, can be run only at the beginning\n",
    "# the exact number may vary depending on python libraries\n",
    "\n",
    "#fc.write_mutant_file(dataset_mut, mut_output+folder_[:-1]+'_mut.txt')\n",
    "#fc.write_events_file(dataset_events, mut_output+folder_[:-1]+'_events.txt')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "10c0b1c0-70d0-4492-a200-d62ec9f2362d",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mutant_events/regulator_lacO_mut.txt mutant_events/regulator_lacO_events.txt\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 850x250 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "folder_='regulator_lacO/'\n",
    "mut_file=mut_output+folder_[:-1]+'_mut.txt'\n",
    "event_file=mut_output+folder_[:-1]+'_events.txt'\n",
    "colors_=colormaps['coolwarm']\n",
    "print(mut_file,event_file)\n",
    "\n",
    "#====================================\n",
    "labellist=pcn_\n",
    "\n",
    "fig=plt.figure(figsize=(8.5,2.5))\n",
    "#---------------------\n",
    "ax1_= plt.subplot(131)\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "fc.fig_boxplot_N(dataset_boxplot,labellist,title='',ax=ax1_)\n",
    "plt.xlim([1,110])\n",
    "#plt.ylim(0, None)\n",
    "plt.ylim(0, 0.065)\n",
    "plt.yticks([0,0.02,0.04,0.06],['0','0.02','0.04','0.06'])\n",
    "plt.xticks([1,10,100],['$10^0$', '$10^1$','$10^2$'])\n",
    "\n",
    "#----------------\n",
    "ax_= plt.subplot(132)\n",
    "\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "mutprob, sdmutprob=fc.read_mut_file(mut_file,event_file,'GF')\n",
    "fc.fig_mutprob(mutprob,sdmutprob,labellist,colors_,ax_)\n",
    "plt.xlim([1,110])\n",
    "plt.title('generating function', fontsize=10)\n",
    "plt.annotate('b',xy=(-0.5, 1), xycoords='axes fraction',fontsize=12, fontweight='bold')\n",
    "\n",
    "#----------------------\n",
    "ax_= plt.subplot(133)\n",
    "\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "mutprob, sdmutprob=fc.read_mut_file(mut_file,event_file,'ML')\n",
    "fc.fig_mutprob(mutprob,sdmutprob,labellist,colors_,ax_)\n",
    "plt.xlim([1,110])\n",
    "plt.title('maximum likelihood', fontsize=10)\n",
    "\n",
    "#=======================\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "4e7f7392-3720-4697-b480-37379d8c6f0d",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.02\n"
     ]
    }
   ],
   "source": [
    "folder_='feedback_lacI/'\n",
    "pcn_=[3,5,9,17,39]\n",
    "\n",
    "'''\n",
    "files_=dict()\n",
    "for k in range(0,len(pcn_)):\n",
    "    flist_=[]\n",
    "    fname=[]\n",
    "    for i in range(0,8):\n",
    "        tmp=file_dir+folder_+folder_[:-1]+'_PCN'+str(pcn_[k])+'_trial'+str(i)+'.fcs'\n",
    "        fname.append(tmp)\n",
    "\n",
    "    flist_=fc.fcs_dataframe_(fname,print_=False)\n",
    "    files_[str(pcn_[k])]=flist_\n",
    "\n",
    "\n",
    "files_feedbacklacI=files_\n",
    "'''\n",
    "#============================\n",
    "p_value= fc.alpha_\n",
    "print(p_value)\n",
    "\n",
    "dataset_boxplot=[]\n",
    "dataset_mut=[]\n",
    "dataset_events=[]\n",
    "\n",
    "for k in range(0,len(pcn_)):\n",
    "    PCN_=str(pcn_[k])\n",
    "    dataset=files_feedbacklacI[PCN_]['fcs']\n",
    "\n",
    "    data_=[]   # total events count\n",
    "    mutant_=[] # mutant events count\n",
    "    arr_=[]    # ratio\n",
    "\n",
    "    for data in dataset:\n",
    "        mut_indx=fc.variants_(data, data, p_value)\n",
    "        mut_=data[mut_indx]\n",
    "        arr_.append(len(mut_)/len(data)*100)\n",
    "        mutant_.append(len(mut_))\n",
    "        data_.append(len(data))\n",
    "        \n",
    "    dataset_boxplot.append(arr_)\n",
    "    dataset_mut.append(mutant_)\n",
    "    dataset_events.append(data_)\n",
    "\n",
    "# save mutant and events count in 'mutant_events/' directory, can be run only at the beginning\n",
    "# the exact number may vary depending on python libraries\n",
    "\n",
    "#fc.write_mutant_file(dataset_mut, mut_output+folder_[:-1]+'_mut.txt')\n",
    "#fc.write_events_file(dataset_events, mut_output+folder_[:-1]+'_events.txt')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "b7333a40-269b-493f-9b82-601f57dee838",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mutant_events/feedback_lacI_mut.txt mutant_events/feedback_lacI_events.txt\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 850x250 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "folder_='feedback_lacI/'\n",
    "mut_file=mut_output+folder_[:-1]+'_mut.txt'\n",
    "event_file=mut_output+folder_[:-1]+'_events.txt'\n",
    "colors_=colormaps['coolwarm']\n",
    "print(mut_file,event_file)\n",
    "#====================================\n",
    "labellist=pcn_\n",
    "\n",
    "fig=plt.figure(figsize=(8.5,2.5))\n",
    "#---------------------\n",
    "ax1_= plt.subplot(131)\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "fc.fig_boxplot_N(dataset_boxplot,labellist,title='',ax=ax1_)\n",
    "plt.xlim([1,110])\n",
    "plt.ylim(0, 0.065)\n",
    "plt.yticks([0,0.02,0.04,0.06],['0','0.02','0.04','0.06'])\n",
    "plt.xticks([1,10,100],['$10^0$', '$10^1$','$10^2$'])\n",
    "\n",
    "#----------------\n",
    "ax_= plt.subplot(132)\n",
    "\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "mutprob, sdmutprob=fc.read_mut_file(mut_file,event_file,'GF')\n",
    "fc.fig_mutprob(mutprob,sdmutprob,labellist,colors_,ax_)\n",
    "plt.xlim([1,110])\n",
    "plt.title('generating function', fontsize=10)\n",
    "plt.annotate('b',xy=(-0.5, 1), xycoords='axes fraction',fontsize=12, fontweight='bold')\n",
    "\n",
    "#----------------------\n",
    "ax_= plt.subplot(133)\n",
    "\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "mutprob, sdmutprob=fc.read_mut_file(mut_file,event_file,'ML')\n",
    "fc.fig_mutprob(mutprob,sdmutprob,labellist,colors_,ax_)\n",
    "plt.xlim([1,110])\n",
    "plt.title('maximum likelihood', fontsize=10)\n",
    "\n",
    "#=======================\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "a19af8d6-f9ec-4fc4-9518-708c6903d92a",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.02\n"
     ]
    }
   ],
   "source": [
    "folder_='feedback_lacO/'\n",
    "pcn_=[3,5,9,17,39]\n",
    "'''\n",
    "files_=dict()\n",
    "for k in range(0,len(pcn_)):\n",
    "    flist_=[]\n",
    "    fname=[]\n",
    "    for i in range(0,8):\n",
    "        tmp=file_dir+folder_+folder_[:-1]+'_PCN'+str(pcn_[k])+'_trial'+str(i)+'.fcs'\n",
    "        fname.append(tmp)\n",
    "\n",
    "    flist_=fc.fcs_dataframe_(fname,print_=False)\n",
    "    files_[str(pcn_[k])]=flist_\n",
    "\n",
    "\n",
    "files_feedbacklacO=files_\n",
    "'''\n",
    "#=========================\n",
    "p_value= fc.alpha_\n",
    "print(p_value)\n",
    "\n",
    "dataset_boxplot=[]\n",
    "dataset_mut=[]\n",
    "dataset_events=[]\n",
    "\n",
    "for k in range(0,len(pcn_)):\n",
    "    PCN_=str(pcn_[k])\n",
    "    dataset=files_feedbacklacO[PCN_]['fcs']\n",
    "\n",
    "    data_=[]   # total events count\n",
    "    mutant_=[] # mutant events count\n",
    "    arr_=[]    # ratio\n",
    "\n",
    "    for data in dataset:\n",
    "        mut_indx=fc.variants_(data, data, p_value)\n",
    "        mut_=data[mut_indx]\n",
    "        arr_.append(len(mut_)/len(data)*100)\n",
    "        mutant_.append(len(mut_))\n",
    "        data_.append(len(data))\n",
    "        \n",
    "    dataset_boxplot.append(arr_)\n",
    "    dataset_mut.append(mutant_)\n",
    "    dataset_events.append(data_)\n",
    "\n",
    "# save mutant and events count in 'mutant_events/' directory, can be run only at the beginning\n",
    "# the exact number may vary depending on python libraries\n",
    "\n",
    "#fc.write_mutant_file(dataset_mut, mut_output+folder_[:-1]+'_mut.txt')\n",
    "#fc.write_events_file(dataset_events, mut_output+folder_[:-1]+'_events.txt')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "9c22c5f6-dd29-4486-9e1c-b36b8e5eb9aa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mutant_events/feedback_lacO_mut.txt mutant_events/feedback_lacO_events.txt\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 850x250 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "folder_='feedback_lacO/'\n",
    "mut_file=mut_output+folder_[:-1]+'_mut.txt'\n",
    "event_file=mut_output+folder_[:-1]+'_events.txt'\n",
    "colors_=colormaps['coolwarm']\n",
    "print(mut_file,event_file)\n",
    "\n",
    "#====================================\n",
    "labellist=pcn_\n",
    "fig=plt.figure(figsize=(8.5,2.5))\n",
    "#---------------------\n",
    "ax1_= plt.subplot(131)\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "fc.fig_boxplot_N(dataset_boxplot,labellist,title='',ax=ax1_)\n",
    "plt.xlim([1,110])\n",
    "#plt.ylim(0, 0.065)\n",
    "plt.yticks([0,0.04,0.08,0.12],['0','0.04','0.08','0.12'])\n",
    "plt.xticks([1,10,100],['$10^0$', '$10^1$','$10^2$'])\n",
    "\n",
    "#----------------\n",
    "ax_= plt.subplot(132)\n",
    "\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "mutprob, sdmutprob=fc.read_mut_file(mut_file,event_file,'GF')\n",
    "fc.fig_mutprob(mutprob,sdmutprob,labellist,colors_,ax_)\n",
    "plt.xlim([1,110])\n",
    "plt.title('generating function', fontsize=10)\n",
    "plt.annotate('b',xy=(-0.5, 1), xycoords='axes fraction',fontsize=12, fontweight='bold')\n",
    "\n",
    "#----------------------\n",
    "ax_= plt.subplot(133)\n",
    "\n",
    "plt.grid(which='major', color='lightgray'); plt.grid(which='minor', linestyle=':', linewidth='0.4', color='lightgray')\n",
    "mutprob, sdmutprob=fc.read_mut_file(mut_file,event_file,'ML')\n",
    "fc.fig_mutprob(mutprob,sdmutprob,labellist,colors_,ax_)\n",
    "plt.xlim([1,150])\n",
    "plt.title('maximum likelihood', fontsize=10)\n",
    "plt.ylim(0,3.1e-4); plt.yticks([0,0.5e-4,1e-4,1.5e-4,2e-4,2.5e-4,3e-4],['0','0.5','1.0','1.5','2.0','2.5','3.0'])\n",
    "#=============================\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "21e1953e-8049-4f45-a106-c3254253e71f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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