STEP1_Parse.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# To specify the site-packages location:\n",
    "import sys\n",
    "sys.path.insert(0, '/home/.conda/envs/tensorflow/lib/python3.6/site-packages')\n",
    "\n",
    "import glob\n",
    "import os.path\n",
    "\n",
    "import bioformats\n",
    "import javabridge\n",
    "import numpy\n",
    "\n",
    "import deepometry.parse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "javabridge.start_vm(class_path=bioformats.JARS, max_heap_size=\"8G\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "src = \"/raw_cif/\"\n",
    "\n",
    "dest = \"/parsed_data/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "patients_path = glob.glob(os.path.join(src,\"*\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "patients = [os.path.basename(i) for i in patients_path]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "channels = [2,11,10,1,3,6,5,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "image_size = 48"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "paths = [j for path in patients_path for i in glob.glob(os.path.join(path,\"*\")) for j in glob.glob(os.path.join(i,\"*\")) ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for pathname in [paths[1]]:\n",
    "    \n",
    "    if 'normal' in pathname:\n",
    "        dest_dir = os.path.join(dest, 'Normal')\n",
    "    else:\n",
    "        if 'blasts' in pathname:\n",
    "            dest_dir = os.path.join(dest, 'Leukemic')\n",
    "        else:\n",
    "            if 'SSC' in pathname:\n",
    "                dest_dir = os.path.join(dest, 'Others')\n",
    "\n",
    "    if not os.path.exists(dest_dir):\n",
    "        os.makedirs(dest_dir)        \n",
    "\n",
    "    deepometry.parse.parse(pathname, dest_dir, image_size, channels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print('Done')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}