Calculate Descriptors.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-8-9cb7184d9e21>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     11\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     12\u001b[0m \u001b[1;31m#df = pd.read_csv(\"ChEMBL_21_MWTlt900_standardized.csv\")\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 13\u001b[1;33m \u001b[0mdf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"GAMO_PFdata_200115.csv\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     14\u001b[0m \u001b[0mdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'smiles'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     15\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "from rdkit import Chem, DataStructs\n",
    "from rdkit.Chem import AllChem\n",
    "import numpy as np\n",
    "from rdkit.Chem import PandasTools\n",
    "\n",
    "#file = pd.read_csv('hdac1.csv') # Reads data from CSV file\n",
    "#IC50 = file['STANDARD_VALUE']\n",
    "#SMILES = file['CANONICAL_SMILES']\n",
    "\n",
    "#df = pd.read_csv(\"ChEMBL_21_MWTlt900_standardized.csv\")\n",
    "df = pd.read_csv(\"GAMO_PFdata_200115.csv\")\n",
    "data = df['smiles']\n",
    "\n",
    "PandasTools.AddMoleculeColumnToFrame(df, smilesCol = 'smiles')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "can't pickle builtin_function_or_method objects",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-3-924f6a941fc1>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     17\u001b[0m \u001b[1;31m#fps = [AllChem.GetMorganFingerprintAsBitVect(m, 1) for m in df['ROMol']]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     18\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 19\u001b[1;33m \u001b[0mfps\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mParallel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mn_jobs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnum_cores\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdelayed\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mAllChem\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mGetMorganFingerprintAsBitVect\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mm\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mm\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'ROMol'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m/home/server2/anaconda2/envs/my-rdkit-env/lib/python2.7/site-packages/joblib/parallel.pyc\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, iterable)\u001b[0m\n\u001b[0;32m    798\u001b[0m             \u001b[1;31m# was dispatched. In particular this covers the edge\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    799\u001b[0m             \u001b[1;31m# case of Parallel used with an exhausted iterator.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 800\u001b[1;33m             \u001b[1;32mwhile\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdispatch_one_batch\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0miterator\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    801\u001b[0m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_iterating\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mTrue\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    802\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/server2/anaconda2/envs/my-rdkit-env/lib/python2.7/site-packages/joblib/parallel.pyc\u001b[0m in \u001b[0;36mdispatch_one_batch\u001b[1;34m(self, iterator)\u001b[0m\n\u001b[0;32m    651\u001b[0m             \u001b[0mbatch_size\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbatch_size\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    652\u001b[0m         \u001b[1;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_lock\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 653\u001b[1;33m             \u001b[0mtasks\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mBatchedCalls\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mitertools\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mislice\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0miterator\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbatch_size\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    654\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mtasks\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    655\u001b[0m                 \u001b[1;31m# No more tasks available in the iterator: tell caller to stop.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/server2/anaconda2/envs/my-rdkit-env/lib/python2.7/site-packages/joblib/parallel.pyc\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, iterator_slice)\u001b[0m\n\u001b[0;32m     66\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     67\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__init__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0miterator_slice\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 68\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0miterator_slice\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     69\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_size\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     70\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<ipython-input-3-924f6a941fc1>\u001b[0m in \u001b[0;36m<genexpr>\u001b[1;34m((m,))\u001b[0m\n\u001b[0;32m     17\u001b[0m \u001b[1;31m#fps = [AllChem.GetMorganFingerprintAsBitVect(m, 1) for m in df['ROMol']]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     18\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 19\u001b[1;33m \u001b[0mfps\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mParallel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mn_jobs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnum_cores\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdelayed\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mAllChem\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mGetMorganFingerprintAsBitVect\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mm\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mm\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'ROMol'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m/home/server2/anaconda2/envs/my-rdkit-env/lib/python2.7/site-packages/joblib/parallel.pyc\u001b[0m in \u001b[0;36mdelayed\u001b[1;34m(function, check_pickle)\u001b[0m\n\u001b[0;32m    156\u001b[0m     \u001b[1;31m# using with multiprocessing:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    157\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mcheck_pickle\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 158\u001b[1;33m         \u001b[0mpickle\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdumps\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfunction\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    159\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    160\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mdelayed_function\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/server2/anaconda2/envs/my-rdkit-env/lib/python2.7/copy_reg.pyc\u001b[0m in \u001b[0;36m_reduce_ex\u001b[1;34m(self, proto)\u001b[0m\n\u001b[0;32m     68\u001b[0m     \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     69\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mbase\u001b[0m \u001b[1;32mis\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 70\u001b[1;33m             \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"can't pickle %s objects\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0mbase\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     71\u001b[0m         \u001b[0mstate\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mbase\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     72\u001b[0m     \u001b[0margs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbase\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mTypeError\u001b[0m: can't pickle builtin_function_or_method objects"
     ]
    }
   ],
   "source": [
    "from joblib import Parallel, delayed\n",
    "\n",
    "    \n",
    "from joblib import Parallel, delayed\n",
    "import multiprocessing\n",
    "\n",
    "num_cores = multiprocessing.cpu_count()\n",
    "\n",
    "\n",
    "\n",
    "#PandasTools.AddMoleculeColumnToFrame(df, smilesCol = 'smiles')\n",
    "#def getfingerprint():\n",
    "#    [AllChem.GetMorganFingerprintAsBitVect(m,2,nBits=2048) for m in df['ROMol']]\n",
    "    \n",
    "#fps = [AllChem.GetMorganFingerprintAsBitVect(m, 1) for m in df['ROMol']]\n",
    "\n",
    "fps = Parallel(n_jobs = num_cores)(delayed(AllChem.GetMorganFingerprintAsBitVect)(m, 0) for m in df['ROMol'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 0 ns, sys: 0 ns, total: 0 ns\n",
      "Wall time: 16.9 µs\n"
     ]
    }
   ],
   "source": [
    "%time\n",
    "fps = [AllChem.GetMorganFingerprintAsBitVect(m, 1) for m in df['ROMol']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 0 ns, sys: 0 ns, total: 0 ns\n",
      "Wall time: 11 µs\n"
     ]
    }
   ],
   "source": [
    "\n",
    "%time\n",
    "df = pd.read_csv(\"ChEMBL_21_MWTlt900_standardized.csv\")\n",
    "#df = pd.read_csv(\"GAMO_PFdata_200115.csv\")\n",
    "data = df['smiles']\n",
    "\n",
    "PandasTools.AddMoleculeColumnToFrame(df, smilesCol = 'smiles')\n",
    "\n",
    "type(df)\n",
    "\n",
    "fps = [AllChem.GetMorganFingerprintAsBitVect(m, 1) for m in df['ROMol']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from joblib import Parallel, delayed\n",
    "\n",
    "    \n",
    "from joblib import Parallel, delayed\n",
    "import multiprocessing\n",
    "\n",
    "num_cores = multiprocessing.cpu_count()\n",
    "\n",
    "#df = pd.read_csv(\"ChEMBL_21_MWTlt900_standardized.csv\")\n",
    "#df = pd.read_csv(\"GAMO_PFdata_200115.csv\")\n",
    "#data = df['smiles']\n",
    "\n",
    "#PandasTools.AddMoleculeColumnToFrame(df, smilesCol = 'smiles')\n",
    "#def getfingerprint():\n",
    "#    [AllChem.GetMorganFingerprintAsBitVect(m,2,nBits=2048) for m in df['ROMol']]\n",
    "    \n",
    "#fps = [AllChem.GetMorganFingerprintAsBitVect(m, 1) for m in df['ROMol']]\n",
    "\n",
    "fps = Parallel(n_jobs = num_cores)(delayed(AllChem.GetMorganFingerprintAsBitVect)\n",
    "                                   (m, 0) for m in df['ROMol'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/server2/anaconda2/envs/my-rdkit-env/lib/python2.7/site-packages/IPython/parallel.py:13: ShimWarning: The `IPython.parallel` package has been deprecated. You should import from ipyparallel instead.\n",
      "  \"You should import from ipyparallel instead.\", ShimWarning)\n"
     ]
    }
   ],
   "source": [
    "import IPython.parallel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/server2/anaconda2/envs/my-rdkit-env/lib/python2.7/site-packages/IPython/parallel.py:13: ShimWarning: The `IPython.parallel` package has been deprecated. You should import from ipyparallel instead.\n",
      "  \"You should import from ipyparallel instead.\", ShimWarning)\n"
     ]
    }
   ],
   "source": [
    "from IPython import parallel\n",
    "c = parallel.Client()\n",
    "#c = parallel.Client()\n",
    "view = c.load_balanced_view()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "ImportError",
     "evalue": "No module named ipyparallel",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mImportError\u001b[0m                               Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-4-e9daf3d3b04d>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mos\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[1;32mimport\u001b[0m \u001b[0mipyparallel\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mipp\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mrc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mipp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mClient\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mar\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mrc\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply_async\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgetpid\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mImportError\u001b[0m: No module named ipyparallel"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import ipyparallel as ipp\n",
    "\n",
    "rc = ipp.Client()\n",
    "ar = rc[:].apply_async(os.getpid)\n",
    "pid_map = ar.get_dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2016-03-26 22:18:56.442 [IPClusterStart] Using existing profile dir: u'/home/server2/.ipython/profile_default'\n",
      "2016-03-26 22:18:56.473 [IPClusterStart] Removing pid file: /home/server2/.ipython/profile_default/pid/ipcluster.pid\n",
      "2016-03-26 22:18:56.473 [IPClusterStart] Starting ipcluster with [daemon=False]\n",
      "2016-03-26 22:18:56.474 [IPClusterStart] Creating pid file: /home/server2/.ipython/profile_default/pid/ipcluster.pid\n",
      "2016-03-26 22:18:56.474 [IPClusterStart] Starting Controller with LocalControllerLauncher\n",
      "2016-03-26 22:18:57.474 [IPClusterStart] Starting 24 Engines with LocalEngineSetLauncher\n"
     ]
    }
   ],
   "source": [
    "!ipcluster start\n",
    "%time\n",
    "#df = pd.read_csv(\"ChEMBL_21_MWTlt900_standardized.csv\")\n",
    "\n",
    "df = pd.read_csv(\"GAMO_PFdata_200115.csv\")\n",
    "data = df['smiles']\n",
    "\n",
    "PandasTools.AddMoleculeColumnToFrame(df, smilesCol = 'smiles')\n",
    "\n",
    "type(df)\n",
    "\n",
    "fps = [AllChem.GetMorganFingerprintAsBitVect(m, 1) for m in df['ROMol']]\n",
    "!ipcluster stop\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 0 ns, sys: 0 ns, total: 0 ns\n",
      "Wall time: 11.9 µs\n"
     ]
    }
   ],
   "source": [
    "%time\n",
    "#df = pd.read_csv(\"ChEMBL_21_MWTlt900_standardized.csv\")\n",
    "\n",
    "df = pd.read_csv(\"GAMO_PFdata_200115.csv\")\n",
    "data = df['smiles']\n",
    "\n",
    "PandasTools.AddMoleculeColumnToFrame(df, smilesCol = 'smiles')\n",
    "\n",
    "type(df)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/server2/anaconda2/envs/my-rdkit-env/lib/python2.7/site-packages/IPython/parallel.py:13: ShimWarning: The `IPython.parallel` package has been deprecated. You should import from ipyparallel instead.\n",
      "  \"You should import from ipyparallel instead.\", ShimWarning)\n"
     ]
    },
    {
     "ename": "ImportError",
     "evalue": "cannot import name Client",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mImportError\u001b[0m                               Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-27-ab40eae2c29b>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mIPython\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mparallel\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mClient\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[0mrc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mClient\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mu'time'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mu'px'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mjoblib\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mParallel\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdelayed\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mImportError\u001b[0m: cannot import name Client"
     ]
    }
   ],
   "source": [
    "from IPython.parallel import Client\n",
    "rc = Client()\n",
    "%time\n",
    "%px\n",
    "from joblib import Parallel, delayed\n",
    "\n",
    "    \n",
    "from joblib import Parallel, delayed\n",
    "import multiprocessing\n",
    "\n",
    "num_cores = multiprocessing.cpu_count()\n",
    "\n",
    "#def getfingerprint():\n",
    "#    [AllChem.GetMorganFingerprintAsBitVect(m,2,nBits=2048) for m in df['ROMol']]\n",
    "    \n",
    "fps = [AllChem.GetMorganFingerprintAsBitVect(m, 1) for m in df['ROMol']]\n",
    "\n",
    "fps = Parallel(n_jobs = num_cores)(delayed(AllChem.GetMorganFingerprintAsBitVect)\n",
    "                                   (m, 0) for m in df['ROMol'])\n",
    "\n",
    "#fps = Parallel(n_jobs = num_cores)(delayed(getfingerprint()))\n",
    "\n",
    "#fps = Parallel(n_jobs = num_cores)(delayted(AllChem.GetMorganFingerprintAsBitVect)(m, 2, \n",
    "#                                                                                 nBits = 1024)\n",
    "#                                           for m in df['ROMol'])\n",
    "\n",
    "#def test3():\n",
    "#   ...:     pass\n",
    "#if __name__ == \"__main__\":\n",
    "    \n",
    "#    import pandas as pd\n",
    "#    from rdkit import Chem, DataStructs\n",
    "#    from rdkit.Chem import AllChem\n",
    "#    import numpy as np\n",
    "#    from rdkit.Chem import PandasTools\n",
    "    \n",
    "\n",
    "\n",
    "    \n",
    "#    num_cores = multiprocessing.cpu_count()\n",
    "#    good = Parallel(n_jobs = num_cores)(delayed(AllChem.GetMorganFingerprintAsBitVect)(m,0,nBits=1024) \n",
    "#                                            for m in df['ROMol'])\n",
    "#    print(good)\n",
    "    \n",
    "\n",
    "#num_cores = multiprocessing.cpu_count()\n",
    "\n",
    "#good = Parallel(n_jobs = num_cores)(delayed(AllChem.GetMorganFingerprintAsBitVect)(m,0,nBits=1024) \n",
    "#                                            for m in df['ROMol'])\n",
    "\n",
    "#Parallel(n_jobs=2)(delayed(sqrt)(i ** 2) for i in range(10))\n",
    "#[0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]\n",
    "\n",
    "\n",
    "#fps = [AllChem.GetMorganFingerprintAsBitVect(m,0,nBits=1024) for m in df['ROMol']]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied (use --upgrade to upgrade): pyzmq in /home/server2/anaconda2/envs/my-rdkit-env/lib/python2.7/site-packages\r\n"
     ]
    }
   ],
   "source": [
    "!pip install pyzmq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'fps' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-9-c655d606d3af>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     19\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     20\u001b[0m \u001b[0mnp_fps\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 21\u001b[1;33m \u001b[1;32mfor\u001b[0m \u001b[0mfp\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mfps\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     22\u001b[0m   \u001b[0marr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzeros\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     23\u001b[0m   \u001b[0mDataStructs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mConvertToNumpyArray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfp\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0marr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'fps' is not defined"
     ]
    }
   ],
   "source": [
    "from joblib import Parallel, delayed  \n",
    "import multiprocessing\n",
    "\n",
    "\n",
    "#CPU times: user 0 ns, sys: 0 ns, total: 0 ns\n",
    "#Wall time: 17.2 µs\n",
    "\n",
    "# what are your inputs, and what operation do you want to \n",
    "# perform on each input. For example...\n",
    "inputs = range(10)  \n",
    "def processInput(i):  \n",
    "    return i * i\n",
    "\n",
    "num_cores = multiprocessing.cpu_count()\n",
    "\n",
    "results = Parallel(n_jobs=num_cores)(delayed(processInput)(i) for i in inputs) \n",
    "\n",
    "\n",
    "\n",
    "np_fps = []\n",
    "for fp in fps:\n",
    "  arr = np.zeros((1,))\n",
    "  DataStructs.ConvertToNumpyArray(fp, arr)\n",
    "  np_fps.append(arr)\n",
    "np.savetxt(\"Chembl-morgan-descriptors.csv\", np_fps, delimiter=\",\")\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from joblib import Parallel, delayed  \n",
    "import multiprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "inputs = range(10)  \n",
    "def processInput(i):  \n",
    "    return i * i\n",
    "\n",
    "num_cores = multiprocessing.cpu_count()\n",
    "\n",
    "results = Parallel(n_jobs=num_cores)(delayed(processInput)(i) for i in inputs) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "?delayed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "24"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_cores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'good' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-32-d7f986677d9f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mgood\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'good' is not defined"
     ]
    }
   ],
   "source": [
    "good"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from rdkit import Chem, DataStructs\n",
    "from rdkit.Chem import AllChem\n",
    "import numpy as np\n",
    "from rdkit.Chem import PandasTools\n",
    "    \n",
    "num_cores = multiprocessing.cpu_count()\n",
    "good = Parallel(n_jobs = num_cores)(delayed(AllChem.GetMorganFingerprintAsBitVect)(m,0,nBits=1024) \n",
    "                                            for m in df['ROMol'])    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "24"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_cores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "can't pickle builtin_function_or_method objects",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-11-8a94074770d0>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m good = Parallel(n_jobs = num_cores)(delayed(AllChem.GetMorganFingerprintAsBitVect)(m,0,nBits=1024) \n\u001b[1;32m----> 2\u001b[1;33m                                             for m in df['ROMol'])\n\u001b[0m",
      "\u001b[1;32m/home/server2/anaconda2/envs/my-rdkit-env/lib/python2.7/site-packages/joblib/parallel.pyc\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, iterable)\u001b[0m\n\u001b[0;32m    798\u001b[0m             \u001b[1;31m# was dispatched. In particular this covers the edge\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    799\u001b[0m             \u001b[1;31m# case of Parallel used with an exhausted iterator.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 800\u001b[1;33m             \u001b[1;32mwhile\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdispatch_one_batch\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0miterator\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    801\u001b[0m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_iterating\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mTrue\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    802\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/server2/anaconda2/envs/my-rdkit-env/lib/python2.7/site-packages/joblib/parallel.pyc\u001b[0m in \u001b[0;36mdispatch_one_batch\u001b[1;34m(self, iterator)\u001b[0m\n\u001b[0;32m    651\u001b[0m             \u001b[0mbatch_size\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbatch_size\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    652\u001b[0m         \u001b[1;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_lock\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 653\u001b[1;33m             \u001b[0mtasks\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mBatchedCalls\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mitertools\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mislice\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0miterator\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbatch_size\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    654\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mtasks\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    655\u001b[0m                 \u001b[1;31m# No more tasks available in the iterator: tell caller to stop.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/server2/anaconda2/envs/my-rdkit-env/lib/python2.7/site-packages/joblib/parallel.pyc\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, iterator_slice)\u001b[0m\n\u001b[0;32m     66\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     67\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__init__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0miterator_slice\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 68\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0miterator_slice\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     69\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_size\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     70\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<ipython-input-11-8a94074770d0>\u001b[0m in \u001b[0;36m<genexpr>\u001b[1;34m((m,))\u001b[0m\n\u001b[0;32m      1\u001b[0m good = Parallel(n_jobs = num_cores)(delayed(AllChem.GetMorganFingerprintAsBitVect)(m,0,nBits=1024) \n\u001b[1;32m----> 2\u001b[1;33m                                             for m in df['ROMol'])\n\u001b[0m",
      "\u001b[1;32m/home/server2/anaconda2/envs/my-rdkit-env/lib/python2.7/site-packages/joblib/parallel.pyc\u001b[0m in \u001b[0;36mdelayed\u001b[1;34m(function, check_pickle)\u001b[0m\n\u001b[0;32m    156\u001b[0m     \u001b[1;31m# using with multiprocessing:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    157\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mcheck_pickle\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 158\u001b[1;33m         \u001b[0mpickle\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdumps\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfunction\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    159\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    160\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mdelayed_function\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/server2/anaconda2/envs/my-rdkit-env/lib/python2.7/copy_reg.pyc\u001b[0m in \u001b[0;36m_reduce_ex\u001b[1;34m(self, proto)\u001b[0m\n\u001b[0;32m     68\u001b[0m     \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     69\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mbase\u001b[0m \u001b[1;32mis\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 70\u001b[1;33m             \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"can't pickle %s objects\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0mbase\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     71\u001b[0m         \u001b[0mstate\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mbase\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     72\u001b[0m     \u001b[0margs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbase\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mTypeError\u001b[0m: can't pickle builtin_function_or_method objects"
     ]
    }
   ],
   "source": [
    "good = Parallel(n_jobs = num_cores)(delayed(AllChem.GetMorganFingerprintAsBitVect)(m,0,nBits=1024) \n",
    "                                            for m in df['ROMol'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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   },
   "outputs": [],
   "source": []
  }
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