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   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Looking at bit collisions in Morgan fingerprints\n",
      "\n",
      "In the group over the past few days we've had a few conversations about bit collisions in Morgan fingerprints. These happen when we fold the fingerprints to be a particular size if two different bits (corresponding to two different atom environments) end up folding onto the same bit.\n",
      "\n",
      "This post is an exploration of how often that happens. I will look at fingerprints with different radii -- 1, 2, and 3 -- folded to a set of different sizes -- 1K, 2K, 4K, 8K.\n",
      "\n",
      "TL;DR version: There are a fair number of collisions at fingerprint sizes below 4K. As expected, higher radii have more collisions. The collisions don't end up making much difference in terms of calculated similarity, but we have observed (not shown here) that it can make a measurable difference in the performance of some machine-learning algorithms.\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from rdkit import Chem,DataStructs\n",
      "import time,random\n",
      "import numpy as np\n",
      "from collections import defaultdict\n",
      "from rdkit.Chem import Draw\n",
      "from rdkit.Chem import rdMolDescriptors as rdmd\n",
      "from rdkit.Chem.Draw import IPythonConsole\n",
      "from rdkit import DataStructs\n",
      "from rdkit import rdBase\n",
      "from __future__ import print_function\n",
      "\n",
      "print(rdBase.rdkitVersion)\n",
      "import time\n",
      "print(time.asctime())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "2014.03.1pre\n",
        "Fri Feb 28 07:44:17 2014\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "For test data I'll use the ChEMBL compounds from 2010-2012 that I built in an earlier post. This is a set of about 230K compounds."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "filen='../data/chembl16_2010-2012.smi'\n",
      "!wc -l $filen\n",
      "!head $filen"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  234681 ../data/chembl16_2010-2012.smi\r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Br\\C=C\\1/CCC(C(=O)O1)c2cccc3ccccc23\t23\r\n",
        "COc1cc2nc(nc(N)c2cc1OC)N3CCN(CC3)C(=O)c4occc4\t97\r\n",
        "CN1CCC[C@H]1c2cccnc2\t115\r\n",
        "CC1COc2c(N3CCN(C)CC3)c(F)cc4C(=O)C(=CN1c24)C(=O)O\t146\r\n",
        "CCN1C=C(C(=O)O)C(=O)c2ccc(C)nc12\t147\r\n",
        "Oc1cc2C(=O)Oc3c(O)c(O)cc4C(=O)Oc(c1O)c2c34\t148\r\n",
        "COc1ccc2c(c1)c(CC(=O)O)c(C)n2C(=O)c3ccc(Cl)cc3\t173\r\n",
        "CC1(C)[C@@H](N2[C@@H](CC2=O)S1(=O)=O)C(=O)O\t194\r\n",
        "Cn1cc(C2=C(C(=O)NC2=O)c3cn(CCCSC(=N)N)c4ccccc34)c5ccccc15\t213\r\n",
        "CN1CCN(CC1)c2cc3N(C=C(C(=O)O)C(=O)c3cc2F)c4ccc(F)cc4\t205\r\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Loop over the molecules and build fingerprints of multiple radii and folded lengths."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "counts=defaultdict(list)\n",
      "for i,line in enumerate(file(filen)):\n",
      "    m = Chem.MolFromSmiles(line.split()[0])\n",
      "    if not m: continue\n",
      "    for v in 1,2,3:\n",
      "        counts[(v,-1)].append(len(rdmd.GetMorganFingerprint(m,v).GetNonzeroElements()))\n",
      "        for l in 1024,2048,4096,8192:\n",
      "            counts[(v,l)].append(rdmd.GetMorganFingerprintAsBitVect(m,v,l).GetNumOnBits())\n",
      "    if not (i+1)%5000:\n",
      "        print(\"Done {0}\".format(i+1))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Done 5000\n",
        "Done 10000"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Done 15000"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Done 20000"
       ]
      },
      {
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       "text": [
        "\n",
        "Done 25000"
       ]
      },
      {
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       "text": [
        "\n",
        "Done 30000"
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      {
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        "\n",
        "Done 35000"
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        "\n",
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      {
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      {
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        "\n"
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     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now plot histograms of the numbers of collisions along with the fractions of collisions.\n",
      "\n",
      "The two plots in each row show the same data, the left one uses counts of collisions, the right is the fraction of bits that are collisions. The right plots also include lines showing what fraction of fingerprints have at least that fraction of collisions."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "figure(figsize=(16,20))\n",
      "\n",
      "pidx=1\n",
      "#----------------------------\n",
      "for nbits in (8192,4096,2048,1024):\n",
      "    subplot(4,2,pidx)\n",
      "    pidx+=1\n",
      "    v1=np.array(counts[1,-1])\n",
      "    v2=np.array(counts[1,nbits])\n",
      "    d1 = v1-v2\n",
      "    d1p=np.array(d1,np.float)\n",
      "    d1p/=v1\n",
      "    v1=np.array(counts[2,-1])\n",
      "    v2=np.array(counts[2,nbits])\n",
      "    d2 = v1-v2\n",
      "    d2p=np.array(d2,np.float)\n",
      "    d2p/=v1\n",
      "    v1=np.array(counts[3,-1])\n",
      "    v2=np.array(counts[3,nbits])\n",
      "    d3 = v1-v2\n",
      "    d3p=np.array(d3,np.float)\n",
      "    d3p/=v1\n",
      "    \n",
      "    _=hist((d1,d2,d3),bins=20,log=True,label=(\"r=1\",\"r=2\",\"r=3\"))\n",
      "    title('%d bits'%nbits)\n",
      "    _=legend()\n",
      "    \n",
      "    subplot(4,2,pidx)\n",
      "    pidx+=1\n",
      "    _=hist((d1p,d2p,d3p),bins=20,log=True,label=(\"r=1\",\"r=2\",\"r=3\"))\n",
      "    _=hist((d1p,d2p,d3p),bins=20,histtype='step',cumulative=-1,normed=True, color=['b','g','r'])\n",
      "    _=legend()\n",
      "\n",
      "\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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auHGjUlNTtWzZMr/a6MoS3CLJJclx8AIAoG+hOBs9rAPWrqRLueEMAQAQ5ULR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Jsn3v9tAUCw4v3zM5wzrCwJBoAoE++fnywJDh/eQwAITrx/frIkGAAAAAAQdywdsLJP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\nkfpACgAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10e656090>"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "So, there are definitely some collisions.\n",
      "\n",
      "Do they make a difference in similarity values? Look at 10K random molecule pairs to find out."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "random.seed(0xF00D)\n",
      "smis = [x.split()[0] for x in file(filen)]\n",
      "ivs=[random.randint(0,len(smis)-1) for x in range(10000)]\n",
      "jvs=[random.randint(0,len(smis)-1) for x in range(10000)]\n",
      "pairs=zip(ivs,jvs)\n",
      "\n",
      "sims=defaultdict(list)\n",
      "for i,j in pairs:\n",
      "    mi = Chem.MolFromSmiles(smis[i])\n",
      "    if not mi:\n",
      "        continue\n",
      "    mj = Chem.MolFromSmiles(smis[j])\n",
      "    if not mj:\n",
      "        continue\n",
      "    for r in 0,1,2,3:\n",
      "        fpi=rdmd.GetMorganFingerprint(mi,r)\n",
      "        for k,v in fpi.GetNonzeroElements().items():\n",
      "            fpi[k]=1\n",
      "        fpj=rdmd.GetMorganFingerprint(mj,r)\n",
      "        for k,v in fpj.GetNonzeroElements().items():\n",
      "            fpj[k]=1\n",
      "        sims[(r,-1)].append(DataStructs.TanimotoSimilarity(fpi,fpj))\n",
      "        for l in 1024,2048,4096,8192:\n",
      "            fpi=rdmd.GetMorganFingerprintAsBitVect(mi,r,l)\n",
      "            fpj=rdmd.GetMorganFingerprintAsBitVect(mj,r,l)\n",
      "            sims[(r,l)].append(DataStructs.TanimotoSimilarity(fpi,fpj))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "figure(figsize=(12,20))\n",
      "\n",
      "pidx=1\n",
      "#----------------------------\n",
      "for nbits in (8192,4096,2048,1024):\n",
      "    subplot(4,1,pidx)\n",
      "    pidx+=1\n",
      "    v1=np.array(sims[1,-1])\n",
      "    v2=np.array(sims[1,nbits])\n",
      "    d1 = v1-v2\n",
      "    d1p=np.array(d1,np.float)\n",
      "    d1p/=v1\n",
      "    v1=np.array(sims[2,-1])\n",
      "    v2=np.array(sims[2,nbits])\n",
      "    d2 = v1-v2\n",
      "    d2p=np.array(d2,np.float)\n",
      "    d2p/=v1\n",
      "    v1=np.array(sims[3,-1])\n",
      "    v2=np.array(sims[3,nbits])\n",
      "    d3 = v1-v2\n",
      "    d3p=np.array(d3,np.float)\n",
      "    d3p/=v1\n",
      "    \n",
      "    _=hist((d1,d2,d3),bins=20,log=True,label=(\"r=1\",\"r=2\",\"r=3\"))\n",
      "    title('%d bits'%nbits)\n",
      "    _=legend()\n",
      "    \n",
      "\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "-c:12: RuntimeWarning: invalid value encountered in divide\n",
        "-c:17: RuntimeWarning: divide by zero encountered in divide\n",
        "-c:17: RuntimeWarning: invalid value encountered in divide\n",
        "-c:22: RuntimeWarning: divide by zero encountered in divide\n",
        "-c:22: RuntimeWarning: invalid value encountered in divide\n",
        "-c:12: RuntimeWarning: divide by zero encountered in divide\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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pmTNnaty4cVqwYIHGjh0b73oBAACAhIsoNNfW1urdd9/VJ598oubmZlVVVUmS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\nlZXav3+/vvrqKzU0NGjOnDmSpOLiYn344YfavXu37rrrrk7nHDp0SBM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dLafTqZdeekkD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       "text": [
        "<matplotlib.figure.Figure at 0x10e57e810>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The changes in similarity are very minimal."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}