{

 "cells": [

  {

   "cell_type": "code",

   "execution_count": 1,

   "metadata": {

    "tags": []

   },

   "outputs": [],

   "source": [

    "%load_ext autoreload\n",

    "%autoreload 2\n",

    "\n",

    "%matplotlib inline"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 2,

   "metadata": {},

   "outputs": [],

   "source": [

    "import os, sys\n",

    "import subprocess"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 3,

   "metadata": {},

   "outputs": [],

   "source": [

    "import pylab as plt\n",

    "import matplotlib\n",

    "\n",

    "import numpy as np\n",

    "import pandas as pd"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 4,

   "metadata": {},

   "outputs": [],

   "source": [

    "import papermill as pm"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 5,

   "metadata": {},

   "outputs": [],

   "source": [

    "sys.path.append('..')"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 6,

   "metadata": {},

   "outputs": [],

   "source": [

    "from pyMultiOmics.common import create_if_not_exist"

   ]

  },

  {

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "# Execute notebook"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 7,

   "metadata": {},

   "outputs": [

    {

     "data": {

      "text/plain": [

       "'/Users/joewandy/Work/git/pyMultiOmics/templates/cic_template.ipynb'"

      ]

     },

     "execution_count": 7,

     "metadata": {},

     "output_type": "execute_result"

    }

   ],

   "source": [

    "input_notebook = os.path.abspath(os.path.join('..', 'templates', 'cic_template.ipynb'))\n",

    "input_notebook"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 8,

   "metadata": {},

   "outputs": [

    {

     "data": {

      "text/plain": [

       "('/Users/joewandy/Work/git/pyMultiOmics/notebooks/temp_results/cic_analysis.ipynb',\n",

       " '/Users/joewandy/Work/git/pyMultiOmics/notebooks/temp_results/cic_analysis.pdf')"

      ]

     },

     "execution_count": 8,

     "metadata": {},

     "output_type": "execute_result"

    }

   ],

   "source": [

    "output_dir = 'temp_results'\n",

    "create_if_not_exist(output_dir)\n",

    "\n",

    "output_notebook = os.path.abspath(os.path.join(output_dir, 'cic_analysis.ipynb'))\n",

    "output_pdf = os.path.abspath(os.path.join(output_dir, 'cic_analysis.pdf'))\n",

    "output_notebook, output_pdf"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 9,

   "metadata": {},

   "outputs": [],

   "source": [

    "params = {\n",

    "    \n",

    "    # the input file name (excel)\n",

    "    'file_name': '/Users/joewandy/Library/CloudStorage/OneDrive-UniversityofGlasgow/CiC_Affinity_Biomarkers/data_group_clustering.xlsx',\n",

    "    \n",

    "    # parameters for feature normalisation\n",

    "    'normalise': 'minmax',\n",

    "    'log': True,\n",

    "    \n",

    "    # parameters for case-control analysis\n",

    "    'case_group': 'disease',\n",

    "    'control_group': 'control',\n",

    "    \n",

    "    # parameters for case-control results\n",

    "    'p_value_thresh': 0.05,\n",

    "    'fc_iqr_thresh': 1.5,\n",

    "    'top_n': 10\n",

    "    \n",

    "}"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 10,

   "metadata": {},

   "outputs": [

    {

     "data": {

      "text/plain": [

       "{'file_name': '/Users/joewandy/Library/CloudStorage/OneDrive-UniversityofGlasgow/CiC_Affinity_Biomarkers/data_group_clustering.xlsx',\n",

       " 'normalise': 'minmax',\n",

       " 'log': True,\n",

       " 'case_group': 'disease',\n",

       " 'control_group': 'control',\n",

       " 'p_value_thresh': 0.05,\n",

       " 'fc_iqr_thresh': 1.5,\n",

       " 'top_n': 10}"

      ]

     },

     "execution_count": 10,

     "metadata": {},

     "output_type": "execute_result"

    }

   ],

   "source": [

    "params"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 11,

   "metadata": {},

   "outputs": [

    {

     "data": {

      "application/vnd.jupyter.widget-view+json": {

       "model_id": "7fc5f06355244b9b98dc3bf91ea5dafe",

       "version_major": 2,

       "version_minor": 0

      },

      "text/plain": [

       "Executing:   0%|          | 0/37 [00:00<?, ?cell/s]"

      ]

     },

     "metadata": {},

     "output_type": "display_data"

    }

   ],

   "source": [

    "_ = pm.execute_notebook(input_notebook, output_notebook, report_mode=True, parameters=params)"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 12,

   "metadata": {},

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "\n",

      "[NbConvertApp] Converting notebook /Users/joewandy/Work/git/pyMultiOmics/notebooks/temp_results/cic_analysis.ipynb to pdf\n",

      "[NbConvertApp] Support files will be in /Users/joewandy/Work/git/pyMultiOmics/notebooks/temp_results/cic_analysis_files/\n",

      "[NbConvertApp] Making directory /Users/joewandy/Work/git/pyMultiOmics/notebooks/temp_results\n",

      "[NbConvertApp] Making directory /Users/joewandy/Work/git/pyMultiOmics/notebooks/temp_results\n",

      "[NbConvertApp] Making directory /Users/joewandy/Work/git/pyMultiOmics/notebooks/temp_results\n",

      "[NbConvertApp] Making directory /Users/joewandy/Work/git/pyMultiOmics/notebooks/temp_results\n",

      "[NbConvertApp] Writing 26073 bytes to notebook.tex\n",

      "[NbConvertApp] Building PDF\n",

      "[NbConvertApp] Running xelatex 3 times: ['xelatex', 'notebook.tex', '-quiet']\n",

      "[NbConvertApp] Running bibtex 1 time: ['bibtex', 'notebook']\n",

      "[NbConvertApp] WARNING | bibtex had problems, most likely because there were no citations\n",

      "[NbConvertApp] PDF successfully created\n",

      "[NbConvertApp] Writing 887703 bytes to /Users/joewandy/Work/git/pyMultiOmics/notebooks/temp_results/cic_analysis.pdf\n",

      "\n"

     ]

    }

   ],

   "source": [

    "command = ['jupyter', 'nbconvert', '--TemplateExporter.exclude_input=True', '--output', output_pdf, '--to', 'pdf', output_notebook]\n",

    "result = subprocess.run(command, capture_output=True, text=True)\n",

    "print(result.stdout)\n",

    "print(result.stderr)"

   ]

  }

 ],

 "metadata": {

  "kernelspec": {

   "display_name": "Python 3 (ipykernel)",

   "language": "python",

   "name": "python3"

  },

  "language_info": {

   "codemirror_mode": {

    "name": "ipython",

    "version": 3

   },

   "file_extension": ".py",

   "mimetype": "text/x-python",

   "name": "python",

   "nbconvert_exporter": "python",

   "pygments_lexer": "ipython3",

   "version": "3.10.1"

  }

 },

 "nbformat": 4,

 "nbformat_minor": 4

}