{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Assessing feature performance\n",
    "\n",
    "DWPC = 0.4, computed on a subset of non-indications"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import re\n",
    "\n",
    "import matplotlib.pyplot\n",
    "import pandas\n",
    "import mpld3\n",
    "import mpld3.plugins\n",
    "import seaborn\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>metapath</th>\n",
       "      <th>nonzero</th>\n",
       "      <th>seconds_per_query</th>\n",
       "      <th>auroc</th>\n",
       "      <th>auroc_permuted</th>\n",
       "      <th>delta_auroc</th>\n",
       "      <th>pval_auroc</th>\n",
       "      <th>length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CbGaD</td>\n",
       "      <td>0.312</td>\n",
       "      <td>0.0145</td>\n",
       "      <td>0.715</td>\n",
       "      <td>0.580</td>\n",
       "      <td>0.13500</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CbGdD</td>\n",
       "      <td>0.149</td>\n",
       "      <td>0.0136</td>\n",
       "      <td>0.512</td>\n",
       "      <td>0.515</td>\n",
       "      <td>-0.00332</td>\n",
       "      <td>0.921000</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  metapath  nonzero  seconds_per_query  auroc  auroc_permuted  delta_auroc  \\\n",
       "0    CbGaD    0.312             0.0145  0.715           0.580      0.13500   \n",
       "1    CbGdD    0.149             0.0136  0.512           0.515     -0.00332   \n",
       "\n",
       "   pval_auroc  length  \n",
       "0    0.000003       2  \n",
       "1    0.921000       2  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auroc_df = pandas.read_table('data/all-features/auroc.tsv')\n",
    "auroc_df.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Performance by path length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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l4MH9bNnyAlu3vsDRo0carxmdQcwFEQJ9EfSOwKw8sZmdoXO/6QIFFkcBUKZGYEGEwIII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\nYPBErNkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2c96d27048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = seaborn.violinplot(x='auroc', y='length', data=auroc_df, cut=0, orient='h', inner='quartile')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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VzhIfTL5LQo8TipBPl77o3alYfofD+Z3LWjyprjUXOLMeLUhvUEf3F3hv4u19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\naUO089doNJo25P8D8SNmZjqRfdoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2c94cb4f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = seaborn.stripplot(x='auroc', y='length', data=auroc_df, jitter=0.25, orient='h', alpha = 0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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BLbFE9bmpabw1liSs6XznO9/itdf2NixeIUT9SSLwkc7OTr75zfsBiGgaIW3g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\nY/Z0PUre4gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2ccc46fa58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = seaborn.violinplot(x='delta_auroc', y='length', data=auroc_df, cut=0, orient='h', inner='quartile')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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LUV69gRd6ZGMZ7tZmQEA2lmHdqaIoChOZQ/TFC9xen+4EAdrnH0gU+Wj0WFdb43qc032n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\np0+T+873cBcXowtgsXsVZ+q111EtC29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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2c94bb7518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = seaborn.stripplot(x='delta_auroc', y='length', data=auroc_df, jitter=0.25, orient='h', alpha=0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Feature AUROC versus non-zero fraction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "   }(mpld3);\n",
       "}else if(typeof define === \"function\" && define.amd){\n",
       "   // require.js is available: use it to load d3/mpld3\n",
       "   require.config({paths: {d3: \"https://mpld3.github.io/js/d3.v3.min\"}});\n",
       "   require([\"d3\"], function(d3){\n",
       "      window.d3 = d3;\n",
       "      mpld3_load_lib(\"https://mpld3.github.io/js/mpld3.v0.2.js\", function(){\n",
       "         \n",
       "         mpld3.draw_figure(\"fig_el279741398294500124329546616205\", {\"axes\": [{\"sharex\": [\"el27974139829449889888\"], \"texts\": [{\"coordinates\": \"axes\", \"text\": \"nonzero\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"middle\", \"fontsize\": 11.0, \"zorder\": 3, \"position\": [0.5, -0.06662678124660067], \"v_baseline\": \"hanging\", \"rotation\": -0.0, \"id\": \"el27974139829451693696\"}, {\"coordinates\": \"axes\", \"text\": \"auroc\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"middle\", \"fontsize\": 11.0, \"zorder\": 3, \"position\": [-0.08380388684666558, 0.5], \"v_baseline\": \"auto\", \"rotation\": -90.0, \"id\": \"el27974139829449673976\"}, {\"coordinates\": \"axes\", \"text\": \"None\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"start\", \"fontsize\": 10.0, \"zorder\": 1000003.0, \"position\": [-0.14747072462370073, -0.12944631785053842], \"v_baseline\": \"auto\", \"rotation\": -0.0, \"id\": \"el27974139829448258672\"}, {\"coordinates\": \"axes\", \"text\": \"pearsonr = 0.59; p = 2e-58\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"start\", \"fontsize\": 10.0, \"zorder\": 1000003.0, \"position\": [0.5879742714315737, 0.9486021973240509], \"v_baseline\": \"auto\", \"rotation\": -0.0, \"id\": \"el27974139829448214680\"}], \"xdomain\": [-0.2, 1.2000000000000002], \"axesbg\": \"#EAEAF2\", \"bbox\": [0.10616319444444446, 0.09444444444444444, 0.7198933531746032, 0.7296031746031746], \"axesbgalpha\": null, \"id\": \"el27974139829451285280\", \"paths\": [{\"coordinates\": \"axes\", \"alpha\": 1, \"data\": \"data02\", \"dasharray\": \"10,0\", \"edgecolor\": \"#FFFFFF\", \"zorder\": 1000001.0, \"edgewidth\": 0.3, \"facecolor\": \"#EAEAF2\", \"pathcodes\": [\"M\", \"L\", \"L\", \"L\", \"Z\"], \"id\": \"el27974139829448213728\", \"yindex\": 1, \"xindex\": 0}], \"axes\": [{\"tickvalues\": null, \"scale\": \"linear\", \"grid\": {\"dasharray\": \"10,0\", \"color\": \"#FFFFFF\", \"alpha\": 1.0, \"gridOn\": 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[0.23076923076923078, 42.0, 0.985], [0.15534615384615386, 42.0, 0.9095769230769231]], \"data22\": [[0.0, 0.5501219512195121], [27.0, 0.5501219512195121], [27.0, 0.5598536585365853], [0.0, 0.5598536585365853]], \"data09\": [[0.4570384615384616, 0.0], [0.5324615384615385, 0.0], [0.5324615384615385, 83.0], [0.4570384615384616, 83.0]], \"data13\": [[0.7587307692307692, 0.0], [0.8341538461538461, 0.0], [0.8341538461538461, 10.0], [0.7587307692307692, 10.0]], \"data26\": [[0.0, 0.5890487804878048], [73.0, 0.5890487804878048], [73.0, 0.598780487804878], [0.0, 0.598780487804878]], \"data15\": [[0.0, 0.48200000000000004, 0.8128780487804876], [2.0, 0.48200000000000004, 0.8128780487804876], [2.0, 0.4917317073170732, 0.8226097560975608], [0.0, 0.4917317073170732, 0.8226097560975608]], \"data27\": [[0.0, 0.5987804878048779], [44.0, 0.5987804878048779], [44.0, 0.6085121951219511], [0.0, 0.6085121951219511]], \"data31\": [[0.0, 0.6669024390243903], [8.0, 0.6669024390243903], [8.0, 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       "      });\n",
       "    });\n",
       "}else{\n",
       "    // require.js not available: dynamically load d3 & mpld3\n",
       "    mpld3_load_lib(\"https://mpld3.github.io/js/d3.v3.min.js\", function(){\n",
       "         mpld3_load_lib(\"https://mpld3.github.io/js/mpld3.v0.2.js\", function(){\n",
       "                 \n",
       "                 mpld3.draw_figure(\"fig_el279741398294500124329546616205\", {\"axes\": [{\"sharex\": [\"el27974139829449889888\"], \"texts\": [{\"coordinates\": \"axes\", \"text\": \"nonzero\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"middle\", \"fontsize\": 11.0, \"zorder\": 3, \"position\": [0.5, -0.06662678124660067], \"v_baseline\": \"hanging\", \"rotation\": -0.0, \"id\": \"el27974139829451693696\"}, {\"coordinates\": \"axes\", \"text\": \"auroc\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"middle\", \"fontsize\": 11.0, \"zorder\": 3, \"position\": [-0.08380388684666558, 0.5], \"v_baseline\": \"auto\", \"rotation\": -90.0, \"id\": \"el27974139829449673976\"}, {\"coordinates\": \"axes\", \"text\": \"None\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"start\", \"fontsize\": 10.0, \"zorder\": 1000003.0, \"position\": [-0.14747072462370073, -0.12944631785053842], \"v_baseline\": \"auto\", \"rotation\": -0.0, \"id\": \"el27974139829448258672\"}, {\"coordinates\": \"axes\", \"text\": \"pearsonr = 0.59; p = 2e-58\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"start\", \"fontsize\": 10.0, \"zorder\": 1000003.0, \"position\": [0.5879742714315737, 0.9486021973240509], \"v_baseline\": \"auto\", \"rotation\": -0.0, \"id\": \"el27974139829448214680\"}], \"xdomain\": [-0.2, 1.2000000000000002], \"axesbg\": \"#EAEAF2\", \"bbox\": [0.10616319444444446, 0.09444444444444444, 0.7198933531746032, 0.7296031746031746], \"axesbgalpha\": null, \"id\": \"el27974139829451285280\", \"paths\": [{\"coordinates\": \"axes\", \"alpha\": 1, \"data\": \"data02\", \"dasharray\": \"10,0\", \"edgecolor\": \"#FFFFFF\", \"zorder\": 1000001.0, \"edgewidth\": 0.3, \"facecolor\": \"#EAEAF2\", \"pathcodes\": [\"M\", \"L\", \"L\", \"L\", \"Z\"], \"id\": \"el27974139829448213728\", \"yindex\": 1, \"xindex\": 0}], \"axes\": [{\"tickvalues\": null, \"scale\": \"linear\", \"grid\": {\"dasharray\": \"10,0\", \"color\": \"#FFFFFF\", 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     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "grid = seaborn.jointplot('nonzero', 'auroc', data=auroc_df, joint_kws={'alpha': 0.5})\n",
    "points = grid.ax_joint.collections[0]\n",
    "labels = auroc_df.metapath.tolist()\n",
    "tooltip = mpld3.plugins.PointLabelTooltip(points, labels)\n",
    "mpld3.plugins.connect(grid.fig, tooltip)\n",
    "mpld3.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Feature Permutation Hit versus AUROC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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\"CtDaGaD: 85.8% nonzero\", \"CtDaGdD: 40.8% nonzero\", \"CtDaGuD: 40.3% nonzero\", \"CtDdGaD: 46.2% nonzero\", \"CtDdGdD: 26.1% nonzero\", \"CtDdGuD: 25.3% nonzero\", \"CtDlAlD: 75.4% nonzero\", \"CtDpCpD: 6.7% nonzero\", \"CtDpCtD: 6.9% nonzero\", \"CtDpSpD: 75.4% nonzero\", \"CtDrDrD: 29.5% nonzero\", \"CtDtCpD: 5.3% nonzero\", \"CtDtCtD: 28.7% nonzero\", \"CtDuGaD: 50.4% nonzero\", \"CtDuGdD: 26.8% nonzero\", \"CtDuGuD: 26.8% nonzero\", \"CuG<rGaD: 64.4% nonzero\", \"CuG<rGdD: 31.3% nonzero\", \"CuG<rGuD: 31.0% nonzero\", \"CuGaDrD: 34.4% nonzero\", \"CuGbCpD: 4.4% nonzero\", \"CuGbCtD: 14.0% nonzero\", \"CuGcGaD: 24.2% nonzero\", \"CuGcGdD: 18.8% nonzero\", \"CuGcGuD: 18.8% nonzero\", \"CuGdAlD: 48.3% nonzero\", \"CuGdCpD: 7.4% nonzero\", \"CuGdCtD: 32.3% nonzero\", \"CuGdDrD: 31.0% nonzero\", \"CuGeAlD: 64.5% nonzero\", \"CuGiGaD: 49.1% nonzero\", \"CuGiGdD: 24.7% nonzero\", \"CuGiGuD: 26.1% nonzero\", \"CuGr>GaD: 54.9% nonzero\", \"CuGr>GdD: 27.5% nonzero\", \"CuGr>GuD: 29.0% 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\"CbGaDdGdD: 47.4% nonzero\", \"CbGaDdGuD: 48.4% nonzero\", \"CbGaDlAlD: 95.5% nonzero\", \"CbGaDpCpD: 25.9% nonzero\", \"CbGaDpCtD: 34.0% nonzero\", \"CbGaDpSpD: 96.1% nonzero\", \"CbGaDrDrD: 79.6% nonzero\", \"CbGaDtCpD: 17.6% nonzero\", \"CbGaDtCtD: 73.0% nonzero\", \"CbGaDuGaD: 94.0% nonzero\", \"CbGaDuGdD: 47.4% nonzero\", \"CbGaDuGuD: 47.8% nonzero\", \"CbGbCbGaD: 90.5% nonzero\", \"CbGbCbGdD: 40.1% nonzero\", \"CbGbCbGuD: 41.7% nonzero\", \"CbGbCdGaD: 89.0% nonzero\", \"CbGbCdGdD: 42.0% nonzero\", \"CbGbCdGuD: 47.0% nonzero\", \"CbGbCpDrD: 61.9% nonzero\", \"CbGbCrCpD: 35.9% nonzero\", \"CbGbCrCtD: 74.4% nonzero\", \"CbGbCtDrD: 79.1% nonzero\", \"CbGbCuGaD: 91.7% nonzero\", \"CbGbCuGdD: 44.8% nonzero\", \"CbGbCuGuD: 45.6% nonzero\", \"CbGcG<rGaD: 76.8% nonzero\", \"CbGcG<rGdD: 36.5% nonzero\", \"CbGcG<rGuD: 37.4% nonzero\", \"CbGcGaDrD: 47.2% nonzero\", \"CbGcGbCpD: 2.1% nonzero\", \"CbGcGbCtD: 15.5% nonzero\", \"CbGcGcGaD: 64.8% nonzero\", \"CbGcGcGdD: 37.0% nonzero\", \"CbGcGcGuD: 37.0% nonzero\", \"CbGcGdAlD: 74.6% nonzero\", \"CbGcGdCpD: 5.1% nonzero\", \"CbGcGdCtD: 30.9% nonzero\", \"CbGcGdDrD: 50.1% nonzero\", \"CbGcGeAlD: 91.7% nonzero\", \"CbGcGiGaD: 76.1% nonzero\", \"CbGcGiGdD: 36.2% nonzero\", \"CbGcGiGuD: 35.5% nonzero\", \"CbGcGr>GaD: 72.6% nonzero\", \"CbGcGr>GdD: 36.3% nonzero\", \"CbGcGr>GuD: 35.6% nonzero\", \"CbGcGuAlD: 75.3% nonzero\", \"CbGcGuCpD: 6.7% nonzero\", \"CbGcGuCtD: 43.0% nonzero\", \"CbGcGuDrD: 52.0% nonzero\", \"CbGdAdGaD: 97.1% nonzero\", \"CbGdAdGdD: 50.0% nonzero\", \"CbGdAdGuD: 51.0% nonzero\", \"CbGdAeGaD: 97.1% nonzero\", \"CbGdAeGdD: 50.1% nonzero\", \"CbGdAeGuD: 51.0% nonzero\", \"CbGdAlDrD: 87.2% nonzero\", \"CbGdAuGaD: 97.1% nonzero\", \"CbGdAuGdD: 50.1% nonzero\", \"CbGdAuGuD: 50.9% nonzero\", \"CbGdCbGaD: 43.9% nonzero\", \"CbGdCbGdD: 20.8% nonzero\", \"CbGdCbGuD: 23.2% nonzero\", \"CbGdCdGaD: 64.7% nonzero\", \"CbGdCdGdD: 31.2% nonzero\", \"CbGdCdGuD: 33.5% nonzero\", \"CbGdCpDrD: 4.4% nonzero\", \"CbGdCrCpD: 5.1% nonzero\", \"CbGdCrCtD: 19.7% nonzero\", \"CbGdCtDrD: 25.3% nonzero\", \"CbGdCuGaD: 66.8% nonzero\", \"CbGdCuGdD: 32.0% nonzero\", \"CbGdCuGuD: 33.1% nonzero\", \"CbGdDaGaD: 97.6% nonzero\", \"CbGdDaGdD: 45.9% nonzero\", \"CbGdDaGuD: 45.1% nonzero\", \"CbGdDdGaD: 98.0% nonzero\", \"CbGdDdGdD: 50.2% nonzero\", \"CbGdDdGuD: 50.9% nonzero\", \"CbGdDlAlD: 95.1% nonzero\", \"CbGdDpCpD: 19.7% nonzero\", \"CbGdDpCtD: 27.4% nonzero\", \"CbGdDpSpD: 94.8% nonzero\", \"CbGdDrDrD: 77.6% nonzero\", \"CbGdDtCpD: 10.8% nonzero\", \"CbGdDtCtD: 59.6% nonzero\", \"CbGdDuGaD: 98.0% nonzero\", \"CbGdDuGdD: 50.4% nonzero\", \"CbGdDuGuD: 49.8% nonzero\", \"CbGeAdGaD: 98.4% nonzero\", \"CbGeAdGdD: 50.7% nonzero\", \"CbGeAdGuD: 51.7% nonzero\", \"CbGeAeGaD: 98.4% nonzero\", \"CbGeAeGdD: 50.8% nonzero\", \"CbGeAeGuD: 51.7% nonzero\", \"CbGeAlDrD: 94.3% nonzero\", \"CbGeAuGaD: 98.4% nonzero\", \"CbGeAuGdD: 50.7% nonzero\", \"CbGeAuGuD: 51.7% nonzero\", \"CbGiG<rGaD: 94.1% nonzero\", \"CbGiG<rGdD: 45.2% nonzero\", \"CbGiG<rGuD: 44.7% nonzero\", \"CbGiGaDrD: 80.9% nonzero\", \"CbGiGbCpD: 19.4% nonzero\", \"CbGiGbCtD: 53.1% nonzero\", \"CbGiGcGaD: 70.1% nonzero\", \"CbGiGcGdD: 39.5% nonzero\", \"CbGiGcGuD: 41.6% nonzero\", \"CbGiGdAlD: 81.8% nonzero\", \"CbGiGdCpD: 15.0% nonzero\", \"CbGiGdCtD: 65.5% nonzero\", \"CbGiGdDrD: 63.8% nonzero\", \"CbGiGeAlD: 96.6% nonzero\", \"CbGiGiGaD: 96.8% nonzero\", \"CbGiGiGdD: 48.7% nonzero\", \"CbGiGiGuD: 48.9% nonzero\", \"CbGiGr>GaD: 92.4% nonzero\", \"CbGiGr>GdD: 43.7% nonzero\", \"CbGiGr>GuD: 45.4% nonzero\", \"CbGiGuAlD: 81.6% nonzero\", \"CbGiGuCpD: 16.3% nonzero\", \"CbGiGuCtD: 63.8% nonzero\", \"CbGiGuDrD: 64.1% nonzero\", \"CbGpBPpGaD: 98.5% nonzero\", \"CbGpBPpGdD: 49.1% nonzero\", \"CbGpBPpGuD: 48.7% nonzero\", \"CbGpCCpGaD: 95.4% nonzero\", \"CbGpCCpGdD: 47.9% nonzero\", \"CbGpCCpGuD: 46.0% nonzero\", \"CbGpMFpGaD: 97.0% nonzero\", \"CbGpMFpGdD: 48.1% nonzero\", \"CbGpMFpGuD: 48.5% nonzero\", \"CbGpPWpGaD: 96.4% nonzero\", \"CbGpPWpGdD: 46.0% nonzero\", \"CbGpPWpGuD: 46.1% nonzero\", \"CbGr>G<rGaD: 88.3% nonzero\", \"CbGr>G<rGdD: 42.3% nonzero\", \"CbGr>G<rGuD: 43.6% nonzero\", \"CbGr>GaDrD: 74.5% nonzero\", \"CbGr>GbCpD: 10.9% nonzero\", \"CbGr>GbCtD: 45.9% nonzero\", \"CbGr>GcGaD: 71.3% nonzero\", \"CbGr>GcGdD: 36.4% nonzero\", \"CbGr>GcGuD: 37.4% nonzero\", \"CbGr>GdAlD: 74.1% nonzero\", \"CbGr>GdCpD: 29.8% nonzero\", \"CbGr>GdCtD: 81.7% nonzero\", \"CbGr>GdDrD: 61.3% nonzero\", \"CbGr>GeAlD: 87.2% nonzero\", \"CbGr>GiGaD: 85.9% nonzero\", \"CbGr>GiGdD: 41.2% nonzero\", \"CbGr>GiGuD: 41.5% nonzero\", \"CbGr>Gr>GaD: 87.1% nonzero\", \"CbGr>Gr>GdD: 41.4% nonzero\", \"CbGr>Gr>GuD: 43.3% nonzero\", \"CbGr>GuAlD: 74.1% nonzero\", \"CbGr>GuCpD: 30.0% nonzero\", \"CbGr>GuCtD: 78.0% nonzero\", \"CbGr>GuDrD: 61.9% nonzero\", \"CbGrPBrGaD: 98.5% nonzero\", \"CbGrPBrGdD: 49.8% nonzero\", \"CbGrPBrGuD: 51.2% nonzero\", \"CbGuAdGaD: 97.2% nonzero\", \"CbGuAdGdD: 50.1% nonzero\", \"CbGuAdGuD: 51.0% nonzero\", \"CbGuAeGaD: 97.2% nonzero\", \"CbGuAeGdD: 50.1% nonzero\", \"CbGuAeGuD: 51.0% nonzero\", \"CbGuAlDrD: 86.3% nonzero\", \"CbGuAuGaD: 97.2% nonzero\", \"CbGuAuGdD: 50.1% nonzero\", \"CbGuAuGuD: 50.9% nonzero\", \"CbGuCbGaD: 52.4% nonzero\", \"CbGuCbGdD: 23.7% nonzero\", \"CbGuCbGuD: 25.3% nonzero\", \"CbGuCdGaD: 70.4% nonzero\", \"CbGuCdGdD: 34.3% nonzero\", \"CbGuCdGuD: 36.9% nonzero\", \"CbGuCpDrD: 6.6% nonzero\", \"CbGuCrCpD: 6.7% nonzero\", \"CbGuCrCtD: 25.1% nonzero\", \"CbGuCtDrD: 32.1% nonzero\", \"CbGuCuGaD: 73.0% nonzero\", \"CbGuCuGdD: 35.3% nonzero\", \"CbGuCuGuD: 36.1% nonzero\", \"CbGuDaGaD: 95.9% nonzero\", \"CbGuDaGdD: 43.4% nonzero\", \"CbGuDaGuD: 43.6% nonzero\", \"CbGuDdGaD: 98.0% nonzero\", \"CbGuDdGdD: 49.9% nonzero\", \"CbGuDdGuD: 50.5% nonzero\", \"CbGuDlAlD: 91.3% nonzero\", \"CbGuDpCpD: 16.4% nonzero\", \"CbGuDpCtD: 23.0% nonzero\", \"CbGuDpSpD: 91.8% nonzero\", \"CbGuDrDrD: 69.4% nonzero\", \"CbGuDtCpD: 11.7% nonzero\", \"CbGuDtCtD: 54.1% nonzero\", \"CbGuDuGaD: 98.0% nonzero\", \"CbGuDuGdD: 50.1% nonzero\", \"CbGuDuGuD: 49.7% nonzero\", \"CcSEcCbGaD: 96.1% nonzero\", \"CcSEcCbGdD: 45.7% nonzero\", \"CcSEcCbGuD: 42.8% nonzero\", \"CcSEcCdGaD: 94.9% nonzero\", \"CcSEcCdGdD: 44.3% nonzero\", \"CcSEcCdGuD: 47.3% nonzero\", \"CcSEcCpDrD: 74.8% nonzero\", \"CcSEcCrCpD: 46.4% nonzero\", \"CcSEcCrCtD: 86.9% nonzero\", \"CcSEcCtDrD: 91.5% nonzero\", \"CcSEcCuGaD: 95.2% nonzero\", \"CcSEcCuGdD: 46.0% nonzero\", \"CcSEcCuGuD: 48.6% nonzero\", \"CdG<rG<rGaD: 68.2% nonzero\", \"CdG<rG<rGdD: 33.4% nonzero\", \"CdG<rG<rGuD: 34.5% nonzero\", \"CdG<rGaDrD: 65.6% nonzero\", \"CdG<rGbCpD: 29.2% nonzero\", \"CdG<rGbCtD: 61.2% nonzero\", \"CdG<rGcGaD: 67.4% nonzero\", \"CdG<rGcGdD: 33.1% nonzero\", \"CdG<rGcGuD: 34.3% nonzero\", \"CdG<rGdAlD: 57.3% nonzero\", \"CdG<rGdCpD: 28.4% nonzero\", \"CdG<rGdCtD: 65.7% nonzero\", \"CdG<rGdDrD: 51.8% nonzero\", \"CdG<rGeAlD: 67.3% nonzero\", \"CdG<rGiGaD: 68.3% nonzero\", \"CdG<rGiGdD: 35.4% nonzero\", \"CdG<rGiGuD: 36.0% nonzero\", \"CdG<rGr>GaD: 68.3% nonzero\", \"CdG<rGr>GdD: 33.5% nonzero\", \"CdG<rGr>GuD: 35.3% nonzero\", \"CdG<rGuAlD: 57.3% nonzero\", \"CdG<rGuCpD: 26.3% nonzero\", \"CdG<rGuCtD: 64.9% nonzero\", \"CdG<rGuDrD: 51.9% nonzero\", \"CdGaDaGaD: 59.6% nonzero\", \"CdGaDaGdD: 28.8% nonzero\", \"CdGaDaGuD: 28.7% nonzero\", \"CdGaDdGaD: 55.8% nonzero\", \"CdGaDdGdD: 28.9% nonzero\", \"CdGaDdGuD: 29.0% nonzero\", \"CdGaDlAlD: 56.5% nonzero\", \"CdGaDpCpD: 14.9% nonzero\", \"CdGaDpCtD: 16.9% nonzero\", \"CdGaDpSpD: 56.7% nonzero\", \"CdGaDrDrD: 45.2% nonzero\", \"CdGaDtCpD: 10.3% nonzero\", \"CdGaDtCtD: 41.5% nonzero\", \"CdGaDuGaD: 56.4% nonzero\", \"CdGaDuGdD: 28.8% nonzero\", \"CdGaDuGuD: 28.9% nonzero\", \"CdGbCbGaD: 31.5% nonzero\", \"CdGbCbGdD: 15.3% nonzero\", \"CdGbCbGuD: 15.9% nonzero\", \"CdGbCdGaD: 28.1% nonzero\", \"CdGbCdGdD: 15.0% nonzero\", \"CdGbCdGuD: 16.1% nonzero\", \"CdGbCpDrD: 3.1% nonzero\", \"CdGbCrCpD: 3.4% nonzero\", \"CdGbCrCtD: 15.9% nonzero\", \"CdGbCtDrD: 19.1% nonzero\", \"CdGbCuGaD: 29.4% nonzero\", \"CdGbCuGdD: 15.5% nonzero\", \"CdGbCuGuD: 15.5% nonzero\", \"CdGcG<rGaD: 52.5% nonzero\", \"CdGcG<rGdD: 26.8% nonzero\", \"CdGcG<rGuD: 26.6% nonzero\", \"CdGcGaDrD: 35.8% nonzero\", \"CdGcGbCpD: 7.1% nonzero\", \"CdGcGbCtD: 17.9% nonzero\", \"CdGcGcGaD: 49.4% nonzero\", \"CdGcGcGdD: 27.5% nonzero\", \"CdGcGcGuD: 28.0% nonzero\", \"CdGcGdAlD: 52.2% nonzero\", \"CdGcGdCpD: 7.9% nonzero\", \"CdGcGdCtD: 31.9% nonzero\", \"CdGcGdDrD: 37.7% nonzero\", \"CdGcGeAlD: 63.9% nonzero\", \"CdGcGiGaD: 53.2% nonzero\", \"CdGcGiGdD: 27.2% nonzero\", \"CdGcGiGuD: 27.3% nonzero\", \"CdGcGr>GaD: 48.2% nonzero\", \"CdGcGr>GdD: 25.3% nonzero\", \"CdGcGr>GuD: 26.4% nonzero\", \"CdGcGuAlD: 50.8% nonzero\", \"CdGcGuCpD: 8.0% nonzero\", \"CdGcGuCtD: 32.1% nonzero\", \"CdGcGuDrD: 38.3% nonzero\", \"CdGdAdGaD: 67.2% nonzero\", \"CdGdAdGdD: 35.1% nonzero\", \"CdGdAdGuD: 35.9% nonzero\", \"CdGdAeGaD: 67.2% nonzero\", \"CdGdAeGdD: 35.2% nonzero\", \"CdGdAeGuD: 35.9% nonzero\", \"CdGdAlDrD: 60.3% nonzero\", \"CdGdAuGaD: 67.2% nonzero\", \"CdGdAuGdD: 35.2% nonzero\", \"CdGdAuGuD: 35.9% nonzero\", \"CdGdCbGaD: 66.0% nonzero\", \"CdGdCbGdD: 29.8% nonzero\", \"CdGdCbGuD: 30.5% nonzero\", \"CdGdCdGaD: 66.9% nonzero\", \"CdGdCdGdD: 32.1% nonzero\", \"CdGdCdGuD: 34.7% nonzero\", \"CdGdCpDrD: 38.8% nonzero\", \"CdGdCrCpD: 25.4% nonzero\", \"CdGdCrCtD: 53.0% nonzero\", \"CdGdCtDrD: 61.0% nonzero\", \"CdGdCuGaD: 67.3% nonzero\", \"CdGdCuGdD: 33.1% nonzero\", \"CdGdCuGuD: 34.9% nonzero\", \"CdGdDaGaD: 67.3% nonzero\", \"CdGdDaGdD: 31.8% nonzero\", \"CdGdDaGuD: 32.3% nonzero\", \"CdGdDdGaD: 67.7% nonzero\", \"CdGdDdGdD: 35.2% nonzero\", \"CdGdDdGuD: 36.0% nonzero\", \"CdGdDlAlD: 65.7% nonzero\", \"CdGdDpCpD: 15.8% nonzero\", \"CdGdDpCtD: 21.6% nonzero\", \"CdGdDpSpD: 65.4% nonzero\", \"CdGdDrDrD: 55.3% nonzero\", \"CdGdDtCpD: 9.8% nonzero\", \"CdGdDtCtD: 43.0% nonzero\", \"CdGdDuGaD: 67.7% nonzero\", \"CdGdDuGdD: 35.2% nonzero\", \"CdGdDuGuD: 35.0% nonzero\", \"CdGeAdGaD: 68.3% nonzero\", \"CdGeAdGdD: 35.8% nonzero\", \"CdGeAdGuD: 36.5% nonzero\", \"CdGeAeGaD: 68.3% nonzero\", \"CdGeAeGdD: 35.8% nonzero\", \"CdGeAeGuD: 36.5% nonzero\", \"CdGeAlDrD: 65.7% nonzero\", \"CdGeAuGaD: 68.3% nonzero\", \"CdGeAuGdD: 35.8% nonzero\", \"CdGeAuGuD: 36.5% nonzero\", \"CdGiG<rGaD: 66.0% nonzero\", \"CdGiG<rGdD: 32.7% nonzero\", \"CdGiG<rGuD: 33.1% nonzero\", \"CdGiGaDrD: 59.4% nonzero\", \"CdGiGbCpD: 15.6% nonzero\", \"CdGiGbCtD: 39.2% nonzero\", \"CdGiGcGaD: 54.0% nonzero\", \"CdGiGcGdD: 29.3% nonzero\", \"CdGiGcGuD: 30.2% nonzero\", \"CdGiGdAlD: 57.2% nonzero\", \"CdGiGdCpD: 16.0% nonzero\", \"CdGiGdCtD: 53.3% nonzero\", \"CdGiGdDrD: 47.6% nonzero\", \"CdGiGeAlD: 67.3% nonzero\", \"CdGiGiGaD: 68.3% nonzero\", \"CdGiGiGdD: 35.5% nonzero\", \"CdGiGiGuD: 35.6% nonzero\", \"CdGiGr>GaD: 66.8% nonzero\", \"CdGiGr>GdD: 32.5% nonzero\", \"CdGiGr>GuD: 33.9% nonzero\", \"CdGiGuAlD: 56.9% nonzero\", \"CdGiGuCpD: 15.6% nonzero\", \"CdGiGuCtD: 51.5% nonzero\", \"CdGiGuDrD: 48.1% nonzero\", \"CdGpBPpGaD: 67.7% nonzero\", \"CdGpBPpGdD: 34.3% nonzero\", \"CdGpBPpGuD: 34.5% nonzero\", \"CdGpCCpGaD: 64.6% nonzero\", \"CdGpCCpGdD: 32.5% nonzero\", \"CdGpCCpGuD: 31.9% nonzero\", \"CdGpMFpGaD: 65.0% nonzero\", \"CdGpMFpGdD: 33.1% nonzero\", \"CdGpMFpGuD: 32.8% nonzero\", \"CdGpPWpGaD: 63.0% nonzero\", \"CdGpPWpGdD: 31.4% nonzero\", \"CdGpPWpGuD: 31.3% nonzero\", \"CdGr>G<rGaD: 67.2% nonzero\", \"CdGr>G<rGdD: 33.0% nonzero\", \"CdGr>G<rGuD: 34.0% nonzero\", \"CdGr>GaDrD: 62.7% nonzero\", \"CdGr>GbCpD: 18.8% nonzero\", \"CdGr>GbCtD: 48.2% nonzero\", \"CdGr>GcGaD: 62.4% nonzero\", \"CdGr>GcGdD: 31.1% nonzero\", \"CdGr>GcGuD: 31.7% nonzero\", \"CdGr>GdAlD: 56.6% nonzero\", \"CdGr>GdCpD: 26.5% nonzero\", \"CdGr>GdCtD: 64.9% nonzero\", \"CdGr>GdDrD: 49.8% nonzero\", \"CdGr>GeAlD: 66.4% nonzero\", \"CdGr>GiGaD: 67.1% nonzero\", \"CdGr>GiGdD: 33.5% nonzero\", \"CdGr>GiGuD: 34.2% nonzero\", \"CdGr>Gr>GaD: 67.0% nonzero\", \"CdGr>Gr>GdD: 32.6% nonzero\", \"CdGr>Gr>GuD: 34.6% nonzero\", \"CdGr>GuAlD: 56.6% nonzero\", \"CdGr>GuCpD: 25.7% nonzero\", \"CdGr>GuCtD: 62.7% nonzero\", \"CdGr>GuDrD: 50.0% nonzero\", \"CdGrPBrGaD: 68.3% nonzero\", \"CdGrPBrGdD: 35.3% nonzero\", \"CdGrPBrGuD: 35.5% nonzero\", \"CdGuAdGaD: 67.2% nonzero\", \"CdGuAdGdD: 35.1% nonzero\", \"CdGuAdGuD: 35.9% nonzero\", \"CdGuAeGaD: 67.2% nonzero\", \"CdGuAeGdD: 35.2% nonzero\", \"CdGuAeGuD: 35.9% nonzero\", \"CdGuAlDrD: 59.7% nonzero\", \"CdGuAuGaD: 67.2% nonzero\", \"CdGuAuGdD: 35.1% nonzero\", \"CdGuAuGuD: 35.8% nonzero\", \"CdGuCbGaD: 57.5% nonzero\", \"CdGuCbGdD: 26.1% nonzero\", \"CdGuCbGuD: 26.8% nonzero\", \"CdGuCdGaD: 64.5% nonzero\", \"CdGuCdGdD: 30.9% nonzero\", \"CdGuCdGuD: 33.4% nonzero\", \"CdGuCpDrD: 19.6% nonzero\", \"CdGuCrCpD: 14.1% nonzero\", \"CdGuCrCtD: 37.4% nonzero\", \"CdGuCtDrD: 48.8% nonzero\", \"CdGuCuGaD: 65.4% nonzero\", \"CdGuCuGdD: 32.1% nonzero\", \"CdGuCuGuD: 33.5% nonzero\", \"CdGuDaGaD: 67.7% nonzero\", \"CdGuDaGdD: 32.9% nonzero\", \"CdGuDaGuD: 32.6% nonzero\", \"CdGuDdGaD: 68.1% nonzero\", \"CdGuDdGdD: 35.5% nonzero\", \"CdGuDdGuD: 36.1% nonzero\", \"CdGuDlAlD: 66.2% nonzero\", \"CdGuDpCpD: 17.0% nonzero\", \"CdGuDpCtD: 21.7% nonzero\", \"CdGuDpSpD: 66.1% nonzero\", \"CdGuDrDrD: 55.6% nonzero\", \"CdGuDtCpD: 10.5% nonzero\", \"CdGuDtCtD: 45.1% nonzero\", \"CdGuDuGaD: 68.1% nonzero\", \"CdGuDuGdD: 35.5% nonzero\", \"CdGuDuGuD: 35.1% nonzero\", \"CpDaG<rGaD: 15.2% nonzero\", \"CpDaG<rGdD: 7.0% nonzero\", \"CpDaG<rGuD: 7.1% nonzero\", \"CpDaGaDrD: 14.9% nonzero\", \"CpDaGbCpD: 6.2% nonzero\", \"CpDaGbCtD: 12.7% nonzero\", \"CpDaGcGaD: 13.2% nonzero\", \"CpDaGcGdD: 7.4% nonzero\"], \"id\": \"el27974139829450483752\"}], \"width\": 480.0, \"data\": {\"data38\": [[0.0, 0.03474000000000001, 0.040982000000000005], [13.0, 0.03474000000000001, 0.040982000000000005], [13.0, 0.040982000000000005, 0.047224], [0.0, 0.040982000000000005, 0.047224]], \"data29\": [[0.0, -0.021438], [18.0, -0.021438], [18.0, -0.015196000000000001], [0.0, -0.015196000000000001]], \"data40\": [[0.0, 0.07219199999999999, 0.16582199999999997], [3.0, 0.07219199999999999, 0.16582199999999997], [3.0, 0.07843400000000002, 0.172064], [0.0, 0.07843400000000002, 0.172064]], \"data39\": [[0.0, 0.053466], [5.0, 0.053466], [5.0, 0.059708], [0.0, 0.059708]], \"data03\": [[0.48200000000000004, 0.0, 0.8128780487804876], [0.4917317073170732, 0.0, 0.8226097560975608], [0.4917317073170732, 2.0, 0.8226097560975608], [0.48200000000000004, 2.0, 0.8128780487804876]], \"data23\": [[0.0, -0.0901, -0.05889, -0.046405999999999996, 0.09091800000000001, 0.10340200000000001, 0.109644], [2.0, -0.0901, -0.05889, -0.046405999999999996, 0.09091800000000001, 0.10340200000000001, 0.109644], [2.0, -0.083858, -0.052648, -0.040164, 0.09716000000000001, 0.109644, 0.115886], [0.0, -0.083858, -0.052648, -0.040164, 0.09716000000000001, 0.109644, 0.115886]], \"data21\": [[0.7058292682926828, 0.0, 0.7155609756097561, 0.7252926829268291, 0.8518048780487804, 0.8712682926829267], [0.715560975609756, 0.0, 0.7252926829268292, 0.7350243902439023, 0.8615365853658535, 0.8809999999999999], [0.715560975609756, 1.0, 0.7252926829268292, 0.7350243902439023, 0.8615365853658535, 0.8809999999999999], [0.7058292682926828, 1.0, 0.7155609756097561, 0.7252926829268291, 0.8518048780487804, 0.8712682926829267]], \"data33\": [[0.0, 0.0035300000000000054], [122.0, 0.0035300000000000054], [122.0, 0.009772000000000003], [0.0, 0.009772000000000003]], \"data02\": [[0.4578866843510161, 0.9302005148845137], [0.9839207084191314, 0.9302005148845137], [0.9839207084191314, 0.9841364806555714], [0.4578866843510161, 0.9841364806555714]], \"data25\": [[0.0, -0.052648, 0.07843400000000002], [4.0, -0.052648, 0.07843400000000002], [4.0, -0.046405999999999996, 0.08467600000000002], [0.0, -0.046405999999999996, 0.08467600000000002]], \"data17\": [[0.6182439024390243, 0.0, 0.6863658536585364], [0.6279756097560975, 0.0, 0.6960975609756096], [0.6279756097560975, 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       "   }(mpld3);\n",
       "}else if(typeof define === \"function\" && define.amd){\n",
       "   // require.js is available: use it to load d3/mpld3\n",
       "   require.config({paths: {d3: \"https://mpld3.github.io/js/d3.v3.min\"}});\n",
       "   require([\"d3\"], function(d3){\n",
       "      window.d3 = d3;\n",
       "      mpld3_load_lib(\"https://mpld3.github.io/js/mpld3.v0.2.js\", function(){\n",
       "         \n",
       "         mpld3.draw_figure(\"fig_el279741398294490864008960807460\", {\"axes\": [{\"sharex\": [\"el27974139829438941336\"], \"texts\": [{\"coordinates\": \"axes\", \"text\": \"auroc\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"middle\", \"fontsize\": 11.0, \"zorder\": 3, \"position\": [0.5, -0.06662678124660067], \"v_baseline\": \"hanging\", \"rotation\": -0.0, \"id\": \"el27974139829448031144\"}, {\"coordinates\": \"axes\", \"text\": \"delta_auroc\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"middle\", \"fontsize\": 11.0, \"zorder\": 3, \"position\": [-0.1207152815433708, 0.5], \"v_baseline\": \"auto\", \"rotation\": -90.0, \"id\": \"el27974139829447623008\"}, {\"coordinates\": \"axes\", \"text\": \"None\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"start\", \"fontsize\": 10.0, \"zorder\": 1000003.0, \"position\": [-0.14762297104823055, -0.12944631785053842], \"v_baseline\": \"auto\", \"rotation\": -0.0, \"id\": \"el27974139829353202744\"}, 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[], \"ylim\": [-0.15000000000000002, 0.25], \"sharey\": [\"el27974139829448446976\"], \"lines\": [], \"images\": [], \"xlim\": [0.0, 140.0], \"ydomain\": [-0.15000000000000002, 0.25]}], \"plugins\": [{\"type\": \"reset\"}, {\"button\": true, \"type\": \"zoom\", \"enabled\": false}, {\"button\": true, \"type\": \"boxzoom\", \"enabled\": false}, {\"type\": \"tooltip\", \"voffset\": 10, \"hoffset\": 0, \"location\": \"mouse\", \"labels\": [\"CbGaD: 31.2% nonzero\", \"CbGdD: 14.9% nonzero\", \"CbGuD: 13.5% nonzero\", \"CdGaD: 19.9% nonzero\", \"CdGdD: 14.2% nonzero\", \"CdGuD: 16.2% nonzero\", \"CpDrD: 1.4% nonzero\", \"CrCpD: 1.1% nonzero\", \"CrCtD: 12.6% nonzero\", \"CtDrD: 14.0% nonzero\", \"CuGaD: 20.5% nonzero\", \"CuGdD: 14.1% nonzero\", \"CuGuD: 15.0% nonzero\", \"CbG<rGaD: 55.2% nonzero\", \"CbG<rGdD: 30.5% nonzero\", \"CbG<rGuD: 30.1% nonzero\", \"CbGaDrD: 58.2% nonzero\", \"CbGbCpD: 31.7% nonzero\", \"CbGbCtD: 72.7% nonzero\", \"CbGcGaD: 22.2% nonzero\", \"CbGcGdD: 22.1% nonzero\", \"CbGcGuD: 23.2% nonzero\", \"CbGdAlD: 71.0% nonzero\", \"CbGdCpD: 1.3% nonzero\", \"CbGdCtD: 15.0% nonzero\", \"CbGdDrD: 42.8% nonzero\", \"CbGeAlD: 93.5% nonzero\", \"CbGiGaD: 60.5% nonzero\", \"CbGiGdD: 33.0% nonzero\", \"CbGiGuD: 33.4% nonzero\", \"CbGr>GaD: 58.5% nonzero\", \"CbGr>GdD: 31.3% nonzero\", \"CbGr>GuD: 33.2% nonzero\", \"CbGuAlD: 69.2% nonzero\", \"CbGuCpD: 2.1% nonzero\", \"CbGuCtD: 19.4% nonzero\", \"CbGuDrD: 36.1% nonzero\", \"CcSEcCpD: 47.1% nonzero\", \"CcSEcCtD: 95.7% nonzero\", \"CdG<rGaD: 66.1% nonzero\", \"CdG<rGdD: 32.3% nonzero\", \"CdG<rGuD: 32.5% nonzero\", \"CdGaDrD: 32.5% nonzero\", \"CdGbCpD: 1.0% nonzero\", \"CdGbCtD: 13.2% nonzero\", \"CdGcGaD: 23.1% nonzero\", \"CdGcGdD: 18.2% nonzero\", \"CdGcGuD: 18.9% nonzero\", \"CdGdAlD: 49.9% nonzero\", \"CdGdCpD: 16.0% nonzero\", \"CdGdCtD: 51.5% nonzero\", \"CdGdDrD: 31.8% nonzero\", \"CdGeAlD: 66.4% nonzero\", \"CdGiGaD: 51.2% nonzero\", \"CdGiGdD: 27.3% nonzero\", \"CdGiGuD: 26.9% nonzero\", \"CdGr>GaD: 56.8% nonzero\", \"CdGr>GdD: 29.0% nonzero\", \"CdGr>GuD: 30.2% nonzero\", \"CdGuAlD: 50.0% nonzero\", \"CdGuCpD: 7.0% nonzero\", \"CdGuCtD: 33.5% nonzero\", \"CdGuDrD: 34.7% nonzero\", \"CpDaGaD: 13.9% nonzero\", \"CpDaGdD: 5.6% nonzero\", \"CpDaGuD: 5.5% nonzero\", \"CpDdGaD: 9.1% nonzero\", \"CpDdGdD: 4.6% nonzero\", \"CpDdGuD: 4.5% nonzero\", \"CpDlAlD: 13.1% nonzero\", \"CpDpCpD: 1.7% nonzero\", \"CpDpCtD: 3.6% nonzero\", \"CpDpSpD: 13.4% nonzero\", \"CpDrDrD: 4.0% nonzero\", \"CpDtCpD: 0.4% nonzero\", \"CpDtCtD: 3.6% nonzero\", \"CpDuGaD: 9.1% nonzero\", \"CpDuGdD: 4.5% nonzero\", \"CpDuGuD: 4.5% nonzero\", \"CrCbGaD: 41.2% nonzero\", \"CrCbGdD: 17.6% nonzero\", \"CrCbGuD: 18.5% nonzero\", \"CrCdGaD: 32.9% nonzero\", \"CrCdGdD: 19.9% nonzero\", \"CrCdGuD: 22.1% nonzero\", \"CrCpDrD: 5.4% nonzero\", \"CrCrCpD: 4.0% nonzero\", \"CrCrCtD: 15.5% nonzero\", \"CrCtDrD: 13.6% nonzero\", \"CrCuGaD: 36.2% nonzero\", \"CrCuGdD: 19.1% nonzero\", \"CrCuGuD: 21.1% nonzero\", \"CtDaGaD: 85.8% nonzero\", \"CtDaGdD: 40.8% nonzero\", \"CtDaGuD: 40.3% nonzero\", \"CtDdGaD: 46.2% nonzero\", \"CtDdGdD: 26.1% nonzero\", \"CtDdGuD: 25.3% nonzero\", \"CtDlAlD: 75.4% nonzero\", \"CtDpCpD: 6.7% nonzero\", \"CtDpCtD: 6.9% nonzero\", \"CtDpSpD: 75.4% nonzero\", \"CtDrDrD: 29.5% nonzero\", \"CtDtCpD: 5.3% nonzero\", \"CtDtCtD: 28.7% nonzero\", \"CtDuGaD: 50.4% nonzero\", \"CtDuGdD: 26.8% nonzero\", \"CtDuGuD: 26.8% nonzero\", \"CuG<rGaD: 64.4% nonzero\", \"CuG<rGdD: 31.3% nonzero\", \"CuG<rGuD: 31.0% nonzero\", \"CuGaDrD: 34.4% nonzero\", \"CuGbCpD: 4.4% nonzero\", \"CuGbCtD: 14.0% nonzero\", \"CuGcGaD: 24.2% nonzero\", \"CuGcGdD: 18.8% nonzero\", \"CuGcGuD: 18.8% nonzero\", \"CuGdAlD: 48.3% nonzero\", \"CuGdCpD: 7.4% nonzero\", \"CuGdCtD: 32.3% nonzero\", \"CuGdDrD: 31.0% nonzero\", \"CuGeAlD: 64.5% nonzero\", \"CuGiGaD: 49.1% nonzero\", \"CuGiGdD: 24.7% nonzero\", \"CuGiGuD: 26.1% nonzero\", \"CuGr>GaD: 54.9% nonzero\", \"CuGr>GdD: 27.5% nonzero\", \"CuGr>GuD: 29.0% nonzero\", \"CuGuAlD: 48.3% nonzero\", \"CuGuCpD: 14.4% nonzero\", \"CuGuCtD: 46.3% nonzero\", \"CuGuDrD: 32.2% nonzero\", \"CbG<rG<rGaD: 86.9% nonzero\", \"CbG<rG<rGdD: 41.6% nonzero\", \"CbG<rG<rGuD: 42.1% nonzero\", \"CbG<rGaDrD: 71.6% nonzero\", \"CbG<rGbCpD: 12.3% nonzero\", \"CbG<rGbCtD: 40.3% nonzero\", \"CbG<rGcGaD: 60.2% nonzero\", \"CbG<rGcGdD: 35.3% nonzero\", \"CbG<rGcGuD: 34.9% nonzero\", \"CbG<rGdAlD: 73.3% nonzero\", \"CbG<rGdCpD: 20.5% nonzero\", \"CbG<rGdCtD: 69.0% nonzero\", \"CbG<rGdDrD: 58.0% nonzero\", \"CbG<rGeAlD: 86.4% nonzero\", \"CbG<rGiGaD: 85.5% nonzero\", \"CbG<rGiGdD: 42.0% nonzero\", \"CbG<rGiGuD: 41.6% nonzero\", \"CbG<rGr>GaD: 87.9% nonzero\", \"CbG<rGr>GdD: 42.4% nonzero\", \"CbG<rGr>GuD: 44.8% nonzero\", \"CbG<rGuAlD: 73.2% nonzero\", \"CbG<rGuCpD: 19.0% nonzero\", \"CbG<rGuCtD: 66.8% nonzero\", \"CbG<rGuDrD: 57.7% nonzero\", \"CbGaDaGaD: 97.5% nonzero\", \"CbGaDaGdD: 47.3% nonzero\", \"CbGaDaGuD: 47.2% nonzero\", \"CbGaDdGaD: 94.0% nonzero\", \"CbGaDdGdD: 47.4% nonzero\", \"CbGaDdGuD: 48.4% nonzero\", \"CbGaDlAlD: 95.5% nonzero\", \"CbGaDpCpD: 25.9% nonzero\", \"CbGaDpCtD: 34.0% nonzero\", \"CbGaDpSpD: 96.1% nonzero\", \"CbGaDrDrD: 79.6% nonzero\", \"CbGaDtCpD: 17.6% nonzero\", \"CbGaDtCtD: 73.0% nonzero\", \"CbGaDuGaD: 94.0% nonzero\", \"CbGaDuGdD: 47.4% nonzero\", \"CbGaDuGuD: 47.8% nonzero\", \"CbGbCbGaD: 90.5% nonzero\", \"CbGbCbGdD: 40.1% nonzero\", \"CbGbCbGuD: 41.7% nonzero\", \"CbGbCdGaD: 89.0% nonzero\", \"CbGbCdGdD: 42.0% nonzero\", \"CbGbCdGuD: 47.0% nonzero\", \"CbGbCpDrD: 61.9% nonzero\", \"CbGbCrCpD: 35.9% nonzero\", \"CbGbCrCtD: 74.4% nonzero\", \"CbGbCtDrD: 79.1% nonzero\", \"CbGbCuGaD: 91.7% nonzero\", \"CbGbCuGdD: 44.8% nonzero\", \"CbGbCuGuD: 45.6% nonzero\", \"CbGcG<rGaD: 76.8% nonzero\", \"CbGcG<rGdD: 36.5% nonzero\", \"CbGcG<rGuD: 37.4% nonzero\", \"CbGcGaDrD: 47.2% nonzero\", \"CbGcGbCpD: 2.1% nonzero\", \"CbGcGbCtD: 15.5% nonzero\", \"CbGcGcGaD: 64.8% nonzero\", \"CbGcGcGdD: 37.0% nonzero\", \"CbGcGcGuD: 37.0% nonzero\", \"CbGcGdAlD: 74.6% nonzero\", \"CbGcGdCpD: 5.1% nonzero\", \"CbGcGdCtD: 30.9% nonzero\", \"CbGcGdDrD: 50.1% nonzero\", \"CbGcGeAlD: 91.7% nonzero\", \"CbGcGiGaD: 76.1% nonzero\", \"CbGcGiGdD: 36.2% nonzero\", \"CbGcGiGuD: 35.5% nonzero\", \"CbGcGr>GaD: 72.6% nonzero\", \"CbGcGr>GdD: 36.3% nonzero\", \"CbGcGr>GuD: 35.6% nonzero\", \"CbGcGuAlD: 75.3% nonzero\", \"CbGcGuCpD: 6.7% nonzero\", \"CbGcGuCtD: 43.0% nonzero\", \"CbGcGuDrD: 52.0% nonzero\", \"CbGdAdGaD: 97.1% nonzero\", \"CbGdAdGdD: 50.0% nonzero\", \"CbGdAdGuD: 51.0% nonzero\", \"CbGdAeGaD: 97.1% nonzero\", \"CbGdAeGdD: 50.1% nonzero\", \"CbGdAeGuD: 51.0% nonzero\", \"CbGdAlDrD: 87.2% nonzero\", \"CbGdAuGaD: 97.1% nonzero\", \"CbGdAuGdD: 50.1% nonzero\", \"CbGdAuGuD: 50.9% nonzero\", \"CbGdCbGaD: 43.9% nonzero\", \"CbGdCbGdD: 20.8% nonzero\", \"CbGdCbGuD: 23.2% nonzero\", \"CbGdCdGaD: 64.7% nonzero\", \"CbGdCdGdD: 31.2% nonzero\", \"CbGdCdGuD: 33.5% nonzero\", \"CbGdCpDrD: 4.4% nonzero\", \"CbGdCrCpD: 5.1% nonzero\", \"CbGdCrCtD: 19.7% nonzero\", \"CbGdCtDrD: 25.3% nonzero\", \"CbGdCuGaD: 66.8% nonzero\", \"CbGdCuGdD: 32.0% nonzero\", \"CbGdCuGuD: 33.1% nonzero\", \"CbGdDaGaD: 97.6% nonzero\", \"CbGdDaGdD: 45.9% nonzero\", \"CbGdDaGuD: 45.1% nonzero\", \"CbGdDdGaD: 98.0% nonzero\", \"CbGdDdGdD: 50.2% nonzero\", \"CbGdDdGuD: 50.9% nonzero\", \"CbGdDlAlD: 95.1% nonzero\", \"CbGdDpCpD: 19.7% nonzero\", \"CbGdDpCtD: 27.4% nonzero\", \"CbGdDpSpD: 94.8% nonzero\", \"CbGdDrDrD: 77.6% nonzero\", \"CbGdDtCpD: 10.8% nonzero\", \"CbGdDtCtD: 59.6% nonzero\", \"CbGdDuGaD: 98.0% nonzero\", \"CbGdDuGdD: 50.4% nonzero\", \"CbGdDuGuD: 49.8% nonzero\", \"CbGeAdGaD: 98.4% nonzero\", \"CbGeAdGdD: 50.7% nonzero\", \"CbGeAdGuD: 51.7% nonzero\", \"CbGeAeGaD: 98.4% nonzero\", \"CbGeAeGdD: 50.8% nonzero\", \"CbGeAeGuD: 51.7% nonzero\", \"CbGeAlDrD: 94.3% nonzero\", \"CbGeAuGaD: 98.4% nonzero\", \"CbGeAuGdD: 50.7% nonzero\", \"CbGeAuGuD: 51.7% nonzero\", \"CbGiG<rGaD: 94.1% nonzero\", \"CbGiG<rGdD: 45.2% nonzero\", \"CbGiG<rGuD: 44.7% nonzero\", \"CbGiGaDrD: 80.9% nonzero\", \"CbGiGbCpD: 19.4% nonzero\", \"CbGiGbCtD: 53.1% nonzero\", \"CbGiGcGaD: 70.1% nonzero\", \"CbGiGcGdD: 39.5% nonzero\", \"CbGiGcGuD: 41.6% nonzero\", \"CbGiGdAlD: 81.8% nonzero\", \"CbGiGdCpD: 15.0% nonzero\", \"CbGiGdCtD: 65.5% nonzero\", \"CbGiGdDrD: 63.8% nonzero\", \"CbGiGeAlD: 96.6% nonzero\", \"CbGiGiGaD: 96.8% nonzero\", \"CbGiGiGdD: 48.7% nonzero\", \"CbGiGiGuD: 48.9% nonzero\", \"CbGiGr>GaD: 92.4% nonzero\", \"CbGiGr>GdD: 43.7% nonzero\", \"CbGiGr>GuD: 45.4% nonzero\", \"CbGiGuAlD: 81.6% nonzero\", \"CbGiGuCpD: 16.3% nonzero\", \"CbGiGuCtD: 63.8% nonzero\", \"CbGiGuDrD: 64.1% nonzero\", \"CbGpBPpGaD: 98.5% nonzero\", \"CbGpBPpGdD: 49.1% nonzero\", \"CbGpBPpGuD: 48.7% nonzero\", \"CbGpCCpGaD: 95.4% nonzero\", \"CbGpCCpGdD: 47.9% nonzero\", \"CbGpCCpGuD: 46.0% nonzero\", \"CbGpMFpGaD: 97.0% nonzero\", \"CbGpMFpGdD: 48.1% nonzero\", \"CbGpMFpGuD: 48.5% nonzero\", \"CbGpPWpGaD: 96.4% nonzero\", \"CbGpPWpGdD: 46.0% nonzero\", \"CbGpPWpGuD: 46.1% nonzero\", \"CbGr>G<rGaD: 88.3% nonzero\", \"CbGr>G<rGdD: 42.3% nonzero\", \"CbGr>G<rGuD: 43.6% nonzero\", \"CbGr>GaDrD: 74.5% nonzero\", \"CbGr>GbCpD: 10.9% nonzero\", \"CbGr>GbCtD: 45.9% nonzero\", \"CbGr>GcGaD: 71.3% nonzero\", \"CbGr>GcGdD: 36.4% nonzero\", \"CbGr>GcGuD: 37.4% nonzero\", \"CbGr>GdAlD: 74.1% nonzero\", \"CbGr>GdCpD: 29.8% nonzero\", \"CbGr>GdCtD: 81.7% nonzero\", \"CbGr>GdDrD: 61.3% nonzero\", \"CbGr>GeAlD: 87.2% nonzero\", \"CbGr>GiGaD: 85.9% nonzero\", \"CbGr>GiGdD: 41.2% nonzero\", \"CbGr>GiGuD: 41.5% nonzero\", \"CbGr>Gr>GaD: 87.1% nonzero\", \"CbGr>Gr>GdD: 41.4% nonzero\", \"CbGr>Gr>GuD: 43.3% nonzero\", \"CbGr>GuAlD: 74.1% nonzero\", \"CbGr>GuCpD: 30.0% nonzero\", \"CbGr>GuCtD: 78.0% nonzero\", \"CbGr>GuDrD: 61.9% nonzero\", \"CbGrPBrGaD: 98.5% nonzero\", \"CbGrPBrGdD: 49.8% nonzero\", \"CbGrPBrGuD: 51.2% nonzero\", \"CbGuAdGaD: 97.2% nonzero\", \"CbGuAdGdD: 50.1% nonzero\", \"CbGuAdGuD: 51.0% nonzero\", \"CbGuAeGaD: 97.2% nonzero\", \"CbGuAeGdD: 50.1% nonzero\", \"CbGuAeGuD: 51.0% nonzero\", \"CbGuAlDrD: 86.3% nonzero\", \"CbGuAuGaD: 97.2% nonzero\", \"CbGuAuGdD: 50.1% nonzero\", \"CbGuAuGuD: 50.9% nonzero\", \"CbGuCbGaD: 52.4% nonzero\", \"CbGuCbGdD: 23.7% nonzero\", \"CbGuCbGuD: 25.3% nonzero\", \"CbGuCdGaD: 70.4% nonzero\", \"CbGuCdGdD: 34.3% nonzero\", \"CbGuCdGuD: 36.9% nonzero\", \"CbGuCpDrD: 6.6% nonzero\", \"CbGuCrCpD: 6.7% nonzero\", \"CbGuCrCtD: 25.1% nonzero\", \"CbGuCtDrD: 32.1% nonzero\", \"CbGuCuGaD: 73.0% nonzero\", \"CbGuCuGdD: 35.3% nonzero\", \"CbGuCuGuD: 36.1% nonzero\", \"CbGuDaGaD: 95.9% nonzero\", \"CbGuDaGdD: 43.4% nonzero\", \"CbGuDaGuD: 43.6% nonzero\", \"CbGuDdGaD: 98.0% nonzero\", \"CbGuDdGdD: 49.9% nonzero\", \"CbGuDdGuD: 50.5% nonzero\", \"CbGuDlAlD: 91.3% nonzero\", \"CbGuDpCpD: 16.4% nonzero\", \"CbGuDpCtD: 23.0% nonzero\", \"CbGuDpSpD: 91.8% nonzero\", \"CbGuDrDrD: 69.4% nonzero\", \"CbGuDtCpD: 11.7% nonzero\", \"CbGuDtCtD: 54.1% nonzero\", \"CbGuDuGaD: 98.0% nonzero\", \"CbGuDuGdD: 50.1% nonzero\", \"CbGuDuGuD: 49.7% nonzero\", \"CcSEcCbGaD: 96.1% nonzero\", \"CcSEcCbGdD: 45.7% nonzero\", \"CcSEcCbGuD: 42.8% nonzero\", \"CcSEcCdGaD: 94.9% nonzero\", \"CcSEcCdGdD: 44.3% nonzero\", \"CcSEcCdGuD: 47.3% nonzero\", \"CcSEcCpDrD: 74.8% nonzero\", \"CcSEcCrCpD: 46.4% nonzero\", \"CcSEcCrCtD: 86.9% nonzero\", \"CcSEcCtDrD: 91.5% nonzero\", \"CcSEcCuGaD: 95.2% nonzero\", \"CcSEcCuGdD: 46.0% nonzero\", \"CcSEcCuGuD: 48.6% nonzero\", \"CdG<rG<rGaD: 68.2% nonzero\", \"CdG<rG<rGdD: 33.4% nonzero\", \"CdG<rG<rGuD: 34.5% nonzero\", \"CdG<rGaDrD: 65.6% nonzero\", \"CdG<rGbCpD: 29.2% nonzero\", \"CdG<rGbCtD: 61.2% nonzero\", \"CdG<rGcGaD: 67.4% nonzero\", \"CdG<rGcGdD: 33.1% nonzero\", \"CdG<rGcGuD: 34.3% nonzero\", \"CdG<rGdAlD: 57.3% nonzero\", \"CdG<rGdCpD: 28.4% nonzero\", \"CdG<rGdCtD: 65.7% nonzero\", \"CdG<rGdDrD: 51.8% nonzero\", \"CdG<rGeAlD: 67.3% nonzero\", \"CdG<rGiGaD: 68.3% nonzero\", \"CdG<rGiGdD: 35.4% nonzero\", \"CdG<rGiGuD: 36.0% nonzero\", \"CdG<rGr>GaD: 68.3% nonzero\", \"CdG<rGr>GdD: 33.5% nonzero\", \"CdG<rGr>GuD: 35.3% nonzero\", \"CdG<rGuAlD: 57.3% nonzero\", \"CdG<rGuCpD: 26.3% nonzero\", \"CdG<rGuCtD: 64.9% nonzero\", \"CdG<rGuDrD: 51.9% nonzero\", \"CdGaDaGaD: 59.6% nonzero\", \"CdGaDaGdD: 28.8% nonzero\", \"CdGaDaGuD: 28.7% nonzero\", \"CdGaDdGaD: 55.8% nonzero\", \"CdGaDdGdD: 28.9% nonzero\", \"CdGaDdGuD: 29.0% nonzero\", \"CdGaDlAlD: 56.5% nonzero\", \"CdGaDpCpD: 14.9% nonzero\", \"CdGaDpCtD: 16.9% nonzero\", \"CdGaDpSpD: 56.7% nonzero\", \"CdGaDrDrD: 45.2% nonzero\", \"CdGaDtCpD: 10.3% nonzero\", \"CdGaDtCtD: 41.5% nonzero\", \"CdGaDuGaD: 56.4% nonzero\", \"CdGaDuGdD: 28.8% nonzero\", \"CdGaDuGuD: 28.9% nonzero\", \"CdGbCbGaD: 31.5% nonzero\", \"CdGbCbGdD: 15.3% nonzero\", \"CdGbCbGuD: 15.9% nonzero\", \"CdGbCdGaD: 28.1% nonzero\", \"CdGbCdGdD: 15.0% nonzero\", \"CdGbCdGuD: 16.1% nonzero\", \"CdGbCpDrD: 3.1% nonzero\", \"CdGbCrCpD: 3.4% nonzero\", \"CdGbCrCtD: 15.9% nonzero\", \"CdGbCtDrD: 19.1% nonzero\", \"CdGbCuGaD: 29.4% nonzero\", \"CdGbCuGdD: 15.5% nonzero\", \"CdGbCuGuD: 15.5% nonzero\", \"CdGcG<rGaD: 52.5% nonzero\", \"CdGcG<rGdD: 26.8% nonzero\", \"CdGcG<rGuD: 26.6% nonzero\", \"CdGcGaDrD: 35.8% nonzero\", \"CdGcGbCpD: 7.1% nonzero\", \"CdGcGbCtD: 17.9% nonzero\", \"CdGcGcGaD: 49.4% nonzero\", \"CdGcGcGdD: 27.5% nonzero\", \"CdGcGcGuD: 28.0% nonzero\", \"CdGcGdAlD: 52.2% nonzero\", \"CdGcGdCpD: 7.9% nonzero\", \"CdGcGdCtD: 31.9% nonzero\", \"CdGcGdDrD: 37.7% nonzero\", \"CdGcGeAlD: 63.9% nonzero\", \"CdGcGiGaD: 53.2% nonzero\", \"CdGcGiGdD: 27.2% nonzero\", \"CdGcGiGuD: 27.3% nonzero\", \"CdGcGr>GaD: 48.2% nonzero\", \"CdGcGr>GdD: 25.3% nonzero\", \"CdGcGr>GuD: 26.4% nonzero\", \"CdGcGuAlD: 50.8% nonzero\", \"CdGcGuCpD: 8.0% nonzero\", \"CdGcGuCtD: 32.1% nonzero\", \"CdGcGuDrD: 38.3% nonzero\", \"CdGdAdGaD: 67.2% nonzero\", \"CdGdAdGdD: 35.1% nonzero\", \"CdGdAdGuD: 35.9% nonzero\", \"CdGdAeGaD: 67.2% nonzero\", \"CdGdAeGdD: 35.2% nonzero\", \"CdGdAeGuD: 35.9% nonzero\", \"CdGdAlDrD: 60.3% nonzero\", \"CdGdAuGaD: 67.2% nonzero\", \"CdGdAuGdD: 35.2% nonzero\", \"CdGdAuGuD: 35.9% nonzero\", \"CdGdCbGaD: 66.0% nonzero\", \"CdGdCbGdD: 29.8% nonzero\", \"CdGdCbGuD: 30.5% nonzero\", \"CdGdCdGaD: 66.9% nonzero\", \"CdGdCdGdD: 32.1% nonzero\", \"CdGdCdGuD: 34.7% nonzero\", \"CdGdCpDrD: 38.8% nonzero\", \"CdGdCrCpD: 25.4% nonzero\", \"CdGdCrCtD: 53.0% nonzero\", \"CdGdCtDrD: 61.0% nonzero\", \"CdGdCuGaD: 67.3% nonzero\", \"CdGdCuGdD: 33.1% nonzero\", \"CdGdCuGuD: 34.9% nonzero\", \"CdGdDaGaD: 67.3% nonzero\", \"CdGdDaGdD: 31.8% nonzero\", \"CdGdDaGuD: 32.3% nonzero\", \"CdGdDdGaD: 67.7% nonzero\", \"CdGdDdGdD: 35.2% nonzero\", \"CdGdDdGuD: 36.0% nonzero\", \"CdGdDlAlD: 65.7% nonzero\", \"CdGdDpCpD: 15.8% nonzero\", \"CdGdDpCtD: 21.6% nonzero\", \"CdGdDpSpD: 65.4% nonzero\", \"CdGdDrDrD: 55.3% nonzero\", \"CdGdDtCpD: 9.8% nonzero\", \"CdGdDtCtD: 43.0% nonzero\", \"CdGdDuGaD: 67.7% nonzero\", \"CdGdDuGdD: 35.2% nonzero\", \"CdGdDuGuD: 35.0% nonzero\", \"CdGeAdGaD: 68.3% nonzero\", \"CdGeAdGdD: 35.8% nonzero\", \"CdGeAdGuD: 36.5% nonzero\", \"CdGeAeGaD: 68.3% nonzero\", \"CdGeAeGdD: 35.8% nonzero\", \"CdGeAeGuD: 36.5% nonzero\", \"CdGeAlDrD: 65.7% nonzero\", \"CdGeAuGaD: 68.3% nonzero\", \"CdGeAuGdD: 35.8% nonzero\", \"CdGeAuGuD: 36.5% nonzero\", \"CdGiG<rGaD: 66.0% nonzero\", \"CdGiG<rGdD: 32.7% nonzero\", \"CdGiG<rGuD: 33.1% nonzero\", \"CdGiGaDrD: 59.4% nonzero\", \"CdGiGbCpD: 15.6% nonzero\", \"CdGiGbCtD: 39.2% nonzero\", \"CdGiGcGaD: 54.0% nonzero\", \"CdGiGcGdD: 29.3% nonzero\", \"CdGiGcGuD: 30.2% nonzero\", \"CdGiGdAlD: 57.2% nonzero\", \"CdGiGdCpD: 16.0% nonzero\", \"CdGiGdCtD: 53.3% nonzero\", \"CdGiGdDrD: 47.6% nonzero\", \"CdGiGeAlD: 67.3% nonzero\", \"CdGiGiGaD: 68.3% nonzero\", \"CdGiGiGdD: 35.5% nonzero\", \"CdGiGiGuD: 35.6% nonzero\", \"CdGiGr>GaD: 66.8% nonzero\", \"CdGiGr>GdD: 32.5% nonzero\", \"CdGiGr>GuD: 33.9% nonzero\", \"CdGiGuAlD: 56.9% nonzero\", \"CdGiGuCpD: 15.6% nonzero\", \"CdGiGuCtD: 51.5% nonzero\", \"CdGiGuDrD: 48.1% nonzero\", \"CdGpBPpGaD: 67.7% nonzero\", \"CdGpBPpGdD: 34.3% nonzero\", \"CdGpBPpGuD: 34.5% nonzero\", \"CdGpCCpGaD: 64.6% nonzero\", \"CdGpCCpGdD: 32.5% nonzero\", \"CdGpCCpGuD: 31.9% nonzero\", \"CdGpMFpGaD: 65.0% nonzero\", \"CdGpMFpGdD: 33.1% nonzero\", \"CdGpMFpGuD: 32.8% nonzero\", \"CdGpPWpGaD: 63.0% nonzero\", \"CdGpPWpGdD: 31.4% nonzero\", \"CdGpPWpGuD: 31.3% nonzero\", \"CdGr>G<rGaD: 67.2% nonzero\", \"CdGr>G<rGdD: 33.0% nonzero\", \"CdGr>G<rGuD: 34.0% nonzero\", \"CdGr>GaDrD: 62.7% nonzero\", \"CdGr>GbCpD: 18.8% nonzero\", \"CdGr>GbCtD: 48.2% nonzero\", \"CdGr>GcGaD: 62.4% nonzero\", \"CdGr>GcGdD: 31.1% nonzero\", \"CdGr>GcGuD: 31.7% nonzero\", \"CdGr>GdAlD: 56.6% nonzero\", \"CdGr>GdCpD: 26.5% nonzero\", \"CdGr>GdCtD: 64.9% nonzero\", \"CdGr>GdDrD: 49.8% nonzero\", \"CdGr>GeAlD: 66.4% nonzero\", \"CdGr>GiGaD: 67.1% nonzero\", \"CdGr>GiGdD: 33.5% nonzero\", \"CdGr>GiGuD: 34.2% nonzero\", \"CdGr>Gr>GaD: 67.0% nonzero\", \"CdGr>Gr>GdD: 32.6% nonzero\", \"CdGr>Gr>GuD: 34.6% nonzero\", \"CdGr>GuAlD: 56.6% nonzero\", \"CdGr>GuCpD: 25.7% nonzero\", \"CdGr>GuCtD: 62.7% nonzero\", \"CdGr>GuDrD: 50.0% nonzero\", \"CdGrPBrGaD: 68.3% nonzero\", \"CdGrPBrGdD: 35.3% nonzero\", \"CdGrPBrGuD: 35.5% nonzero\", \"CdGuAdGaD: 67.2% nonzero\", \"CdGuAdGdD: 35.1% nonzero\", \"CdGuAdGuD: 35.9% nonzero\", \"CdGuAeGaD: 67.2% nonzero\", \"CdGuAeGdD: 35.2% nonzero\", \"CdGuAeGuD: 35.9% nonzero\", \"CdGuAlDrD: 59.7% nonzero\", \"CdGuAuGaD: 67.2% nonzero\", \"CdGuAuGdD: 35.1% nonzero\", \"CdGuAuGuD: 35.8% nonzero\", \"CdGuCbGaD: 57.5% nonzero\", \"CdGuCbGdD: 26.1% nonzero\", \"CdGuCbGuD: 26.8% nonzero\", \"CdGuCdGaD: 64.5% nonzero\", \"CdGuCdGdD: 30.9% nonzero\", \"CdGuCdGuD: 33.4% nonzero\", \"CdGuCpDrD: 19.6% nonzero\", \"CdGuCrCpD: 14.1% nonzero\", \"CdGuCrCtD: 37.4% nonzero\", \"CdGuCtDrD: 48.8% nonzero\", \"CdGuCuGaD: 65.4% nonzero\", \"CdGuCuGdD: 32.1% nonzero\", \"CdGuCuGuD: 33.5% nonzero\", \"CdGuDaGaD: 67.7% nonzero\", \"CdGuDaGdD: 32.9% nonzero\", \"CdGuDaGuD: 32.6% nonzero\", \"CdGuDdGaD: 68.1% nonzero\", \"CdGuDdGdD: 35.5% nonzero\", \"CdGuDdGuD: 36.1% nonzero\", \"CdGuDlAlD: 66.2% nonzero\", \"CdGuDpCpD: 17.0% nonzero\", \"CdGuDpCtD: 21.7% nonzero\", \"CdGuDpSpD: 66.1% nonzero\", \"CdGuDrDrD: 55.6% nonzero\", \"CdGuDtCpD: 10.5% nonzero\", \"CdGuDtCtD: 45.1% nonzero\", \"CdGuDuGaD: 68.1% nonzero\", \"CdGuDuGdD: 35.5% nonzero\", \"CdGuDuGuD: 35.1% nonzero\", \"CpDaG<rGaD: 15.2% nonzero\", \"CpDaG<rGdD: 7.0% nonzero\", \"CpDaG<rGuD: 7.1% nonzero\", \"CpDaGaDrD: 14.9% nonzero\", \"CpDaGbCpD: 6.2% nonzero\", \"CpDaGbCtD: 12.7% nonzero\", \"CpDaGcGaD: 13.2% nonzero\", \"CpDaGcGdD: 7.4% nonzero\"], \"id\": \"el27974139829450483752\"}], \"width\": 480.0, \"data\": {\"data38\": [[0.0, 0.03474000000000001, 0.040982000000000005], [13.0, 0.03474000000000001, 0.040982000000000005], [13.0, 0.040982000000000005, 0.047224], [0.0, 0.040982000000000005, 0.047224]], \"data29\": [[0.0, -0.021438], [18.0, -0.021438], [18.0, -0.015196000000000001], [0.0, -0.015196000000000001]], \"data40\": [[0.0, 0.07219199999999999, 0.16582199999999997], [3.0, 0.07219199999999999, 0.16582199999999997], [3.0, 0.07843400000000002, 0.172064], [0.0, 0.07843400000000002, 0.172064]], \"data39\": [[0.0, 0.053466], [5.0, 0.053466], [5.0, 0.059708], [0.0, 0.059708]], \"data03\": [[0.48200000000000004, 0.0, 0.8128780487804876], [0.4917317073170732, 0.0, 0.8226097560975608], [0.4917317073170732, 2.0, 0.8226097560975608], [0.48200000000000004, 2.0, 0.8128780487804876]], \"data23\": [[0.0, -0.0901, -0.05889, -0.046405999999999996, 0.09091800000000001, 0.10340200000000001, 0.109644], [2.0, -0.0901, -0.05889, -0.046405999999999996, 0.09091800000000001, 0.10340200000000001, 0.109644], [2.0, -0.083858, -0.052648, -0.040164, 0.09716000000000001, 0.109644, 0.115886], [0.0, -0.083858, -0.052648, -0.040164, 0.09716000000000001, 0.109644, 0.115886]], \"data21\": [[0.7058292682926828, 0.0, 0.7155609756097561, 0.7252926829268291, 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8.0], [0.6669024390243903, 8.0]], \"data16\": [[0.6085121951219512, 0.0], [0.6182439024390244, 0.0], [0.6182439024390244, 42.0], [0.6085121951219512, 42.0]]}, \"height\": 480.0, \"id\": \"el27974139829449086400\"});\n",
       "      });\n",
       "    });\n",
       "}else{\n",
       "    // require.js not available: dynamically load d3 & mpld3\n",
       "    mpld3_load_lib(\"https://mpld3.github.io/js/d3.v3.min.js\", function(){\n",
       "         mpld3_load_lib(\"https://mpld3.github.io/js/mpld3.v0.2.js\", function(){\n",
       "                 \n",
       "                 mpld3.draw_figure(\"fig_el279741398294490864008960807460\", {\"axes\": [{\"sharex\": [\"el27974139829438941336\"], \"texts\": [{\"coordinates\": \"axes\", \"text\": \"auroc\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"middle\", \"fontsize\": 11.0, \"zorder\": 3, \"position\": [0.5, -0.06662678124660067], \"v_baseline\": \"hanging\", \"rotation\": -0.0, \"id\": \"el27974139829448031144\"}, {\"coordinates\": \"axes\", \"text\": \"delta_auroc\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"middle\", \"fontsize\": 11.0, \"zorder\": 3, \"position\": [-0.1207152815433708, 0.5], \"v_baseline\": \"auto\", \"rotation\": -90.0, \"id\": \"el27974139829447623008\"}, {\"coordinates\": \"axes\", \"text\": \"None\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"start\", \"fontsize\": 10.0, \"zorder\": 1000003.0, \"position\": [-0.14762297104823055, -0.12944631785053842], \"v_baseline\": \"auto\", \"rotation\": -0.0, \"id\": \"el27974139829353202744\"}, {\"coordinates\": \"axes\", \"text\": \"pearsonr = 0.58; p = 1.3e-55\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"start\", \"fontsize\": 10.0, \"zorder\": 1000003.0, \"position\": [0.560794150468575, 0.9486021973240509], \"v_baseline\": \"auto\", \"rotation\": -0.0, \"id\": \"el27974139829353187424\"}], \"xdomain\": [0.4, 1.0], \"axesbg\": \"#EAEAF2\", \"bbox\": [0.10626085069444445, 0.09444444444444444, 0.7198124379960318, 0.7296031746031746], \"axesbgalpha\": null, \"id\": \"el27974139829448446976\", \"paths\": [{\"coordinates\": \"axes\", \"alpha\": 1, \"data\": \"data02\", \"dasharray\": \"10,0\", \"edgecolor\": \"#FFFFFF\", \"zorder\": 1000001.0, \"edgewidth\": 0.3, \"facecolor\": \"#EAEAF2\", \"pathcodes\": [\"M\", \"L\", \"L\", \"L\", \"Z\"], \"id\": \"el27974139829353186472\", \"yindex\": 1, \"xindex\": 0}], \"axes\": [{\"tickvalues\": null, \"scale\": \"linear\", \"grid\": {\"dasharray\": \"10,0\", \"color\": \"#FFFFFF\", \"alpha\": 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\"CuGr>GdD: 27.5% nonzero\", \"CuGr>GuD: 29.0% nonzero\", \"CuGuAlD: 48.3% nonzero\", \"CuGuCpD: 14.4% nonzero\", \"CuGuCtD: 46.3% nonzero\", \"CuGuDrD: 32.2% nonzero\", \"CbG<rG<rGaD: 86.9% nonzero\", \"CbG<rG<rGdD: 41.6% nonzero\", \"CbG<rG<rGuD: 42.1% nonzero\", \"CbG<rGaDrD: 71.6% nonzero\", \"CbG<rGbCpD: 12.3% nonzero\", \"CbG<rGbCtD: 40.3% nonzero\", \"CbG<rGcGaD: 60.2% nonzero\", \"CbG<rGcGdD: 35.3% nonzero\", \"CbG<rGcGuD: 34.9% nonzero\", \"CbG<rGdAlD: 73.3% nonzero\", \"CbG<rGdCpD: 20.5% nonzero\", \"CbG<rGdCtD: 69.0% nonzero\", \"CbG<rGdDrD: 58.0% nonzero\", \"CbG<rGeAlD: 86.4% nonzero\", \"CbG<rGiGaD: 85.5% nonzero\", \"CbG<rGiGdD: 42.0% nonzero\", \"CbG<rGiGuD: 41.6% nonzero\", \"CbG<rGr>GaD: 87.9% nonzero\", \"CbG<rGr>GdD: 42.4% nonzero\", \"CbG<rGr>GuD: 44.8% nonzero\", \"CbG<rGuAlD: 73.2% nonzero\", \"CbG<rGuCpD: 19.0% nonzero\", \"CbG<rGuCtD: 66.8% nonzero\", \"CbG<rGuDrD: 57.7% nonzero\", \"CbGaDaGaD: 97.5% nonzero\", \"CbGaDaGdD: 47.3% nonzero\", \"CbGaDaGuD: 47.2% nonzero\", \"CbGaDdGaD: 94.0% nonzero\", \"CbGaDdGdD: 47.4% nonzero\", \"CbGaDdGuD: 48.4% nonzero\", \"CbGaDlAlD: 95.5% nonzero\", \"CbGaDpCpD: 25.9% nonzero\", \"CbGaDpCtD: 34.0% nonzero\", \"CbGaDpSpD: 96.1% nonzero\", \"CbGaDrDrD: 79.6% nonzero\", \"CbGaDtCpD: 17.6% nonzero\", \"CbGaDtCtD: 73.0% nonzero\", \"CbGaDuGaD: 94.0% nonzero\", \"CbGaDuGdD: 47.4% nonzero\", \"CbGaDuGuD: 47.8% nonzero\", \"CbGbCbGaD: 90.5% nonzero\", \"CbGbCbGdD: 40.1% nonzero\", \"CbGbCbGuD: 41.7% nonzero\", \"CbGbCdGaD: 89.0% nonzero\", \"CbGbCdGdD: 42.0% nonzero\", \"CbGbCdGuD: 47.0% nonzero\", \"CbGbCpDrD: 61.9% nonzero\", \"CbGbCrCpD: 35.9% nonzero\", \"CbGbCrCtD: 74.4% nonzero\", \"CbGbCtDrD: 79.1% nonzero\", \"CbGbCuGaD: 91.7% nonzero\", \"CbGbCuGdD: 44.8% nonzero\", \"CbGbCuGuD: 45.6% nonzero\", \"CbGcG<rGaD: 76.8% nonzero\", \"CbGcG<rGdD: 36.5% nonzero\", \"CbGcG<rGuD: 37.4% nonzero\", \"CbGcGaDrD: 47.2% nonzero\", \"CbGcGbCpD: 2.1% nonzero\", \"CbGcGbCtD: 15.5% nonzero\", \"CbGcGcGaD: 64.8% nonzero\", \"CbGcGcGdD: 37.0% nonzero\", \"CbGcGcGuD: 37.0% nonzero\", \"CbGcGdAlD: 74.6% nonzero\", \"CbGcGdCpD: 5.1% nonzero\", \"CbGcGdCtD: 30.9% nonzero\", \"CbGcGdDrD: 50.1% nonzero\", \"CbGcGeAlD: 91.7% nonzero\", \"CbGcGiGaD: 76.1% nonzero\", \"CbGcGiGdD: 36.2% nonzero\", \"CbGcGiGuD: 35.5% nonzero\", \"CbGcGr>GaD: 72.6% nonzero\", \"CbGcGr>GdD: 36.3% nonzero\", \"CbGcGr>GuD: 35.6% nonzero\", \"CbGcGuAlD: 75.3% nonzero\", \"CbGcGuCpD: 6.7% nonzero\", \"CbGcGuCtD: 43.0% nonzero\", \"CbGcGuDrD: 52.0% nonzero\", \"CbGdAdGaD: 97.1% nonzero\", \"CbGdAdGdD: 50.0% nonzero\", \"CbGdAdGuD: 51.0% nonzero\", \"CbGdAeGaD: 97.1% nonzero\", \"CbGdAeGdD: 50.1% nonzero\", \"CbGdAeGuD: 51.0% nonzero\", \"CbGdAlDrD: 87.2% nonzero\", \"CbGdAuGaD: 97.1% nonzero\", \"CbGdAuGdD: 50.1% nonzero\", \"CbGdAuGuD: 50.9% nonzero\", \"CbGdCbGaD: 43.9% nonzero\", \"CbGdCbGdD: 20.8% nonzero\", \"CbGdCbGuD: 23.2% nonzero\", \"CbGdCdGaD: 64.7% nonzero\", \"CbGdCdGdD: 31.2% nonzero\", \"CbGdCdGuD: 33.5% nonzero\", \"CbGdCpDrD: 4.4% nonzero\", \"CbGdCrCpD: 5.1% nonzero\", \"CbGdCrCtD: 19.7% nonzero\", \"CbGdCtDrD: 25.3% nonzero\", \"CbGdCuGaD: 66.8% nonzero\", \"CbGdCuGdD: 32.0% nonzero\", \"CbGdCuGuD: 33.1% nonzero\", \"CbGdDaGaD: 97.6% nonzero\", \"CbGdDaGdD: 45.9% nonzero\", \"CbGdDaGuD: 45.1% nonzero\", \"CbGdDdGaD: 98.0% nonzero\", \"CbGdDdGdD: 50.2% nonzero\", \"CbGdDdGuD: 50.9% nonzero\", \"CbGdDlAlD: 95.1% nonzero\", \"CbGdDpCpD: 19.7% nonzero\", \"CbGdDpCtD: 27.4% nonzero\", \"CbGdDpSpD: 94.8% nonzero\", \"CbGdDrDrD: 77.6% nonzero\", \"CbGdDtCpD: 10.8% nonzero\", \"CbGdDtCtD: 59.6% nonzero\", \"CbGdDuGaD: 98.0% nonzero\", \"CbGdDuGdD: 50.4% nonzero\", \"CbGdDuGuD: 49.8% nonzero\", \"CbGeAdGaD: 98.4% nonzero\", \"CbGeAdGdD: 50.7% nonzero\", \"CbGeAdGuD: 51.7% nonzero\", \"CbGeAeGaD: 98.4% nonzero\", \"CbGeAeGdD: 50.8% nonzero\", \"CbGeAeGuD: 51.7% nonzero\", \"CbGeAlDrD: 94.3% nonzero\", \"CbGeAuGaD: 98.4% nonzero\", \"CbGeAuGdD: 50.7% nonzero\", \"CbGeAuGuD: 51.7% nonzero\", \"CbGiG<rGaD: 94.1% nonzero\", \"CbGiG<rGdD: 45.2% nonzero\", \"CbGiG<rGuD: 44.7% nonzero\", \"CbGiGaDrD: 80.9% nonzero\", \"CbGiGbCpD: 19.4% nonzero\", \"CbGiGbCtD: 53.1% nonzero\", \"CbGiGcGaD: 70.1% nonzero\", \"CbGiGcGdD: 39.5% nonzero\", \"CbGiGcGuD: 41.6% nonzero\", \"CbGiGdAlD: 81.8% nonzero\", \"CbGiGdCpD: 15.0% nonzero\", \"CbGiGdCtD: 65.5% nonzero\", \"CbGiGdDrD: 63.8% nonzero\", \"CbGiGeAlD: 96.6% nonzero\", \"CbGiGiGaD: 96.8% nonzero\", \"CbGiGiGdD: 48.7% nonzero\", \"CbGiGiGuD: 48.9% nonzero\", \"CbGiGr>GaD: 92.4% nonzero\", \"CbGiGr>GdD: 43.7% nonzero\", \"CbGiGr>GuD: 45.4% nonzero\", \"CbGiGuAlD: 81.6% nonzero\", \"CbGiGuCpD: 16.3% nonzero\", \"CbGiGuCtD: 63.8% nonzero\", \"CbGiGuDrD: 64.1% nonzero\", \"CbGpBPpGaD: 98.5% nonzero\", \"CbGpBPpGdD: 49.1% nonzero\", \"CbGpBPpGuD: 48.7% nonzero\", \"CbGpCCpGaD: 95.4% nonzero\", \"CbGpCCpGdD: 47.9% nonzero\", \"CbGpCCpGuD: 46.0% nonzero\", \"CbGpMFpGaD: 97.0% nonzero\", \"CbGpMFpGdD: 48.1% nonzero\", \"CbGpMFpGuD: 48.5% nonzero\", \"CbGpPWpGaD: 96.4% nonzero\", \"CbGpPWpGdD: 46.0% nonzero\", \"CbGpPWpGuD: 46.1% nonzero\", \"CbGr>G<rGaD: 88.3% nonzero\", \"CbGr>G<rGdD: 42.3% nonzero\", \"CbGr>G<rGuD: 43.6% nonzero\", \"CbGr>GaDrD: 74.5% nonzero\", \"CbGr>GbCpD: 10.9% nonzero\", \"CbGr>GbCtD: 45.9% nonzero\", \"CbGr>GcGaD: 71.3% nonzero\", \"CbGr>GcGdD: 36.4% nonzero\", \"CbGr>GcGuD: 37.4% nonzero\", \"CbGr>GdAlD: 74.1% nonzero\", \"CbGr>GdCpD: 29.8% nonzero\", \"CbGr>GdCtD: 81.7% nonzero\", \"CbGr>GdDrD: 61.3% nonzero\", \"CbGr>GeAlD: 87.2% nonzero\", \"CbGr>GiGaD: 85.9% nonzero\", \"CbGr>GiGdD: 41.2% nonzero\", \"CbGr>GiGuD: 41.5% nonzero\", \"CbGr>Gr>GaD: 87.1% nonzero\", \"CbGr>Gr>GdD: 41.4% nonzero\", \"CbGr>Gr>GuD: 43.3% nonzero\", \"CbGr>GuAlD: 74.1% nonzero\", \"CbGr>GuCpD: 30.0% nonzero\", \"CbGr>GuCtD: 78.0% nonzero\", \"CbGr>GuDrD: 61.9% nonzero\", \"CbGrPBrGaD: 98.5% nonzero\", \"CbGrPBrGdD: 49.8% nonzero\", \"CbGrPBrGuD: 51.2% nonzero\", \"CbGuAdGaD: 97.2% nonzero\", \"CbGuAdGdD: 50.1% nonzero\", \"CbGuAdGuD: 51.0% nonzero\", \"CbGuAeGaD: 97.2% nonzero\", \"CbGuAeGdD: 50.1% nonzero\", \"CbGuAeGuD: 51.0% nonzero\", \"CbGuAlDrD: 86.3% nonzero\", \"CbGuAuGaD: 97.2% nonzero\", \"CbGuAuGdD: 50.1% nonzero\", \"CbGuAuGuD: 50.9% nonzero\", \"CbGuCbGaD: 52.4% nonzero\", \"CbGuCbGdD: 23.7% nonzero\", \"CbGuCbGuD: 25.3% nonzero\", \"CbGuCdGaD: 70.4% nonzero\", \"CbGuCdGdD: 34.3% nonzero\", \"CbGuCdGuD: 36.9% nonzero\", \"CbGuCpDrD: 6.6% nonzero\", \"CbGuCrCpD: 6.7% nonzero\", \"CbGuCrCtD: 25.1% nonzero\", \"CbGuCtDrD: 32.1% nonzero\", \"CbGuCuGaD: 73.0% nonzero\", \"CbGuCuGdD: 35.3% nonzero\", \"CbGuCuGuD: 36.1% nonzero\", \"CbGuDaGaD: 95.9% nonzero\", \"CbGuDaGdD: 43.4% nonzero\", \"CbGuDaGuD: 43.6% nonzero\", \"CbGuDdGaD: 98.0% nonzero\", \"CbGuDdGdD: 49.9% nonzero\", \"CbGuDdGuD: 50.5% nonzero\", \"CbGuDlAlD: 91.3% nonzero\", \"CbGuDpCpD: 16.4% nonzero\", \"CbGuDpCtD: 23.0% nonzero\", \"CbGuDpSpD: 91.8% nonzero\", \"CbGuDrDrD: 69.4% nonzero\", \"CbGuDtCpD: 11.7% nonzero\", \"CbGuDtCtD: 54.1% nonzero\", \"CbGuDuGaD: 98.0% nonzero\", \"CbGuDuGdD: 50.1% nonzero\", \"CbGuDuGuD: 49.7% nonzero\", \"CcSEcCbGaD: 96.1% nonzero\", \"CcSEcCbGdD: 45.7% nonzero\", \"CcSEcCbGuD: 42.8% nonzero\", \"CcSEcCdGaD: 94.9% nonzero\", \"CcSEcCdGdD: 44.3% nonzero\", \"CcSEcCdGuD: 47.3% nonzero\", \"CcSEcCpDrD: 74.8% nonzero\", \"CcSEcCrCpD: 46.4% nonzero\", \"CcSEcCrCtD: 86.9% nonzero\", \"CcSEcCtDrD: 91.5% nonzero\", \"CcSEcCuGaD: 95.2% nonzero\", \"CcSEcCuGdD: 46.0% nonzero\", \"CcSEcCuGuD: 48.6% nonzero\", \"CdG<rG<rGaD: 68.2% nonzero\", \"CdG<rG<rGdD: 33.4% nonzero\", \"CdG<rG<rGuD: 34.5% nonzero\", \"CdG<rGaDrD: 65.6% nonzero\", \"CdG<rGbCpD: 29.2% nonzero\", \"CdG<rGbCtD: 61.2% nonzero\", \"CdG<rGcGaD: 67.4% nonzero\", \"CdG<rGcGdD: 33.1% nonzero\", \"CdG<rGcGuD: 34.3% nonzero\", \"CdG<rGdAlD: 57.3% nonzero\", \"CdG<rGdCpD: 28.4% nonzero\", \"CdG<rGdCtD: 65.7% nonzero\", \"CdG<rGdDrD: 51.8% nonzero\", \"CdG<rGeAlD: 67.3% nonzero\", \"CdG<rGiGaD: 68.3% nonzero\", \"CdG<rGiGdD: 35.4% nonzero\", \"CdG<rGiGuD: 36.0% nonzero\", \"CdG<rGr>GaD: 68.3% nonzero\", \"CdG<rGr>GdD: 33.5% nonzero\", \"CdG<rGr>GuD: 35.3% nonzero\", \"CdG<rGuAlD: 57.3% nonzero\", \"CdG<rGuCpD: 26.3% nonzero\", \"CdG<rGuCtD: 64.9% nonzero\", \"CdG<rGuDrD: 51.9% nonzero\", \"CdGaDaGaD: 59.6% nonzero\", \"CdGaDaGdD: 28.8% nonzero\", \"CdGaDaGuD: 28.7% nonzero\", \"CdGaDdGaD: 55.8% nonzero\", \"CdGaDdGdD: 28.9% nonzero\", \"CdGaDdGuD: 29.0% nonzero\", \"CdGaDlAlD: 56.5% nonzero\", \"CdGaDpCpD: 14.9% nonzero\", \"CdGaDpCtD: 16.9% nonzero\", \"CdGaDpSpD: 56.7% nonzero\", \"CdGaDrDrD: 45.2% nonzero\", \"CdGaDtCpD: 10.3% nonzero\", \"CdGaDtCtD: 41.5% nonzero\", \"CdGaDuGaD: 56.4% nonzero\", \"CdGaDuGdD: 28.8% nonzero\", \"CdGaDuGuD: 28.9% nonzero\", \"CdGbCbGaD: 31.5% nonzero\", \"CdGbCbGdD: 15.3% nonzero\", \"CdGbCbGuD: 15.9% nonzero\", \"CdGbCdGaD: 28.1% nonzero\", \"CdGbCdGdD: 15.0% nonzero\", \"CdGbCdGuD: 16.1% nonzero\", \"CdGbCpDrD: 3.1% nonzero\", \"CdGbCrCpD: 3.4% nonzero\", \"CdGbCrCtD: 15.9% nonzero\", \"CdGbCtDrD: 19.1% nonzero\", \"CdGbCuGaD: 29.4% nonzero\", \"CdGbCuGdD: 15.5% nonzero\", \"CdGbCuGuD: 15.5% nonzero\", \"CdGcG<rGaD: 52.5% nonzero\", \"CdGcG<rGdD: 26.8% nonzero\", \"CdGcG<rGuD: 26.6% nonzero\", \"CdGcGaDrD: 35.8% nonzero\", \"CdGcGbCpD: 7.1% nonzero\", \"CdGcGbCtD: 17.9% nonzero\", \"CdGcGcGaD: 49.4% nonzero\", \"CdGcGcGdD: 27.5% nonzero\", \"CdGcGcGuD: 28.0% nonzero\", \"CdGcGdAlD: 52.2% nonzero\", \"CdGcGdCpD: 7.9% nonzero\", \"CdGcGdCtD: 31.9% nonzero\", \"CdGcGdDrD: 37.7% nonzero\", \"CdGcGeAlD: 63.9% nonzero\", \"CdGcGiGaD: 53.2% nonzero\", \"CdGcGiGdD: 27.2% nonzero\", \"CdGcGiGuD: 27.3% nonzero\", \"CdGcGr>GaD: 48.2% nonzero\", \"CdGcGr>GdD: 25.3% nonzero\", \"CdGcGr>GuD: 26.4% nonzero\", \"CdGcGuAlD: 50.8% nonzero\", \"CdGcGuCpD: 8.0% nonzero\", \"CdGcGuCtD: 32.1% nonzero\", \"CdGcGuDrD: 38.3% nonzero\", \"CdGdAdGaD: 67.2% nonzero\", \"CdGdAdGdD: 35.1% nonzero\", \"CdGdAdGuD: 35.9% nonzero\", \"CdGdAeGaD: 67.2% nonzero\", \"CdGdAeGdD: 35.2% nonzero\", \"CdGdAeGuD: 35.9% nonzero\", \"CdGdAlDrD: 60.3% nonzero\", \"CdGdAuGaD: 67.2% nonzero\", \"CdGdAuGdD: 35.2% nonzero\", \"CdGdAuGuD: 35.9% nonzero\", \"CdGdCbGaD: 66.0% nonzero\", \"CdGdCbGdD: 29.8% nonzero\", \"CdGdCbGuD: 30.5% nonzero\", \"CdGdCdGaD: 66.9% nonzero\", \"CdGdCdGdD: 32.1% nonzero\", \"CdGdCdGuD: 34.7% nonzero\", \"CdGdCpDrD: 38.8% nonzero\", \"CdGdCrCpD: 25.4% nonzero\", \"CdGdCrCtD: 53.0% nonzero\", \"CdGdCtDrD: 61.0% nonzero\", \"CdGdCuGaD: 67.3% nonzero\", \"CdGdCuGdD: 33.1% nonzero\", \"CdGdCuGuD: 34.9% nonzero\", \"CdGdDaGaD: 67.3% nonzero\", \"CdGdDaGdD: 31.8% nonzero\", \"CdGdDaGuD: 32.3% nonzero\", \"CdGdDdGaD: 67.7% nonzero\", \"CdGdDdGdD: 35.2% nonzero\", \"CdGdDdGuD: 36.0% nonzero\", \"CdGdDlAlD: 65.7% nonzero\", \"CdGdDpCpD: 15.8% nonzero\", \"CdGdDpCtD: 21.6% nonzero\", \"CdGdDpSpD: 65.4% nonzero\", \"CdGdDrDrD: 55.3% nonzero\", \"CdGdDtCpD: 9.8% nonzero\", \"CdGdDtCtD: 43.0% nonzero\", \"CdGdDuGaD: 67.7% nonzero\", \"CdGdDuGdD: 35.2% nonzero\", \"CdGdDuGuD: 35.0% nonzero\", \"CdGeAdGaD: 68.3% nonzero\", \"CdGeAdGdD: 35.8% nonzero\", \"CdGeAdGuD: 36.5% nonzero\", \"CdGeAeGaD: 68.3% nonzero\", \"CdGeAeGdD: 35.8% nonzero\", \"CdGeAeGuD: 36.5% nonzero\", \"CdGeAlDrD: 65.7% nonzero\", \"CdGeAuGaD: 68.3% nonzero\", \"CdGeAuGdD: 35.8% nonzero\", \"CdGeAuGuD: 36.5% nonzero\", \"CdGiG<rGaD: 66.0% nonzero\", \"CdGiG<rGdD: 32.7% nonzero\", \"CdGiG<rGuD: 33.1% nonzero\", \"CdGiGaDrD: 59.4% nonzero\", \"CdGiGbCpD: 15.6% nonzero\", \"CdGiGbCtD: 39.2% nonzero\", \"CdGiGcGaD: 54.0% nonzero\", \"CdGiGcGdD: 29.3% nonzero\", \"CdGiGcGuD: 30.2% nonzero\", \"CdGiGdAlD: 57.2% nonzero\", \"CdGiGdCpD: 16.0% nonzero\", \"CdGiGdCtD: 53.3% nonzero\", \"CdGiGdDrD: 47.6% nonzero\", \"CdGiGeAlD: 67.3% nonzero\", \"CdGiGiGaD: 68.3% nonzero\", \"CdGiGiGdD: 35.5% nonzero\", \"CdGiGiGuD: 35.6% nonzero\", \"CdGiGr>GaD: 66.8% nonzero\", \"CdGiGr>GdD: 32.5% nonzero\", \"CdGiGr>GuD: 33.9% nonzero\", \"CdGiGuAlD: 56.9% nonzero\", \"CdGiGuCpD: 15.6% nonzero\", \"CdGiGuCtD: 51.5% nonzero\", \"CdGiGuDrD: 48.1% nonzero\", \"CdGpBPpGaD: 67.7% nonzero\", \"CdGpBPpGdD: 34.3% nonzero\", \"CdGpBPpGuD: 34.5% nonzero\", \"CdGpCCpGaD: 64.6% nonzero\", \"CdGpCCpGdD: 32.5% nonzero\", \"CdGpCCpGuD: 31.9% nonzero\", \"CdGpMFpGaD: 65.0% nonzero\", \"CdGpMFpGdD: 33.1% nonzero\", \"CdGpMFpGuD: 32.8% nonzero\", \"CdGpPWpGaD: 63.0% nonzero\", \"CdGpPWpGdD: 31.4% nonzero\", \"CdGpPWpGuD: 31.3% nonzero\", \"CdGr>G<rGaD: 67.2% nonzero\", \"CdGr>G<rGdD: 33.0% nonzero\", \"CdGr>G<rGuD: 34.0% nonzero\", \"CdGr>GaDrD: 62.7% nonzero\", \"CdGr>GbCpD: 18.8% nonzero\", \"CdGr>GbCtD: 48.2% nonzero\", \"CdGr>GcGaD: 62.4% nonzero\", \"CdGr>GcGdD: 31.1% nonzero\", \"CdGr>GcGuD: 31.7% nonzero\", \"CdGr>GdAlD: 56.6% nonzero\", \"CdGr>GdCpD: 26.5% nonzero\", \"CdGr>GdCtD: 64.9% nonzero\", \"CdGr>GdDrD: 49.8% nonzero\", \"CdGr>GeAlD: 66.4% nonzero\", \"CdGr>GiGaD: 67.1% nonzero\", \"CdGr>GiGdD: 33.5% nonzero\", \"CdGr>GiGuD: 34.2% nonzero\", \"CdGr>Gr>GaD: 67.0% nonzero\", \"CdGr>Gr>GdD: 32.6% nonzero\", \"CdGr>Gr>GuD: 34.6% nonzero\", \"CdGr>GuAlD: 56.6% nonzero\", \"CdGr>GuCpD: 25.7% nonzero\", \"CdGr>GuCtD: 62.7% nonzero\", \"CdGr>GuDrD: 50.0% nonzero\", \"CdGrPBrGaD: 68.3% nonzero\", \"CdGrPBrGdD: 35.3% nonzero\", \"CdGrPBrGuD: 35.5% nonzero\", \"CdGuAdGaD: 67.2% nonzero\", \"CdGuAdGdD: 35.1% nonzero\", \"CdGuAdGuD: 35.9% nonzero\", \"CdGuAeGaD: 67.2% nonzero\", \"CdGuAeGdD: 35.2% nonzero\", \"CdGuAeGuD: 35.9% nonzero\", \"CdGuAlDrD: 59.7% nonzero\", \"CdGuAuGaD: 67.2% nonzero\", \"CdGuAuGdD: 35.1% nonzero\", \"CdGuAuGuD: 35.8% nonzero\", \"CdGuCbGaD: 57.5% nonzero\", \"CdGuCbGdD: 26.1% nonzero\", \"CdGuCbGuD: 26.8% nonzero\", \"CdGuCdGaD: 64.5% nonzero\", \"CdGuCdGdD: 30.9% nonzero\", \"CdGuCdGuD: 33.4% nonzero\", \"CdGuCpDrD: 19.6% nonzero\", \"CdGuCrCpD: 14.1% nonzero\", \"CdGuCrCtD: 37.4% nonzero\", \"CdGuCtDrD: 48.8% nonzero\", \"CdGuCuGaD: 65.4% nonzero\", \"CdGuCuGdD: 32.1% nonzero\", \"CdGuCuGuD: 33.5% nonzero\", \"CdGuDaGaD: 67.7% nonzero\", \"CdGuDaGdD: 32.9% nonzero\", \"CdGuDaGuD: 32.6% nonzero\", \"CdGuDdGaD: 68.1% nonzero\", \"CdGuDdGdD: 35.5% nonzero\", \"CdGuDdGuD: 36.1% nonzero\", \"CdGuDlAlD: 66.2% nonzero\", \"CdGuDpCpD: 17.0% nonzero\", \"CdGuDpCtD: 21.7% nonzero\", \"CdGuDpSpD: 66.1% nonzero\", \"CdGuDrDrD: 55.6% nonzero\", \"CdGuDtCpD: 10.5% nonzero\", \"CdGuDtCtD: 45.1% nonzero\", \"CdGuDuGaD: 68.1% nonzero\", \"CdGuDuGdD: 35.5% nonzero\", \"CdGuDuGuD: 35.1% nonzero\", \"CpDaG<rGaD: 15.2% nonzero\", \"CpDaG<rGdD: 7.0% nonzero\", \"CpDaG<rGuD: 7.1% nonzero\", \"CpDaGaDrD: 14.9% nonzero\", \"CpDaGbCpD: 6.2% nonzero\", \"CpDaGbCtD: 12.7% nonzero\", \"CpDaGcGaD: 13.2% nonzero\", \"CpDaGcGdD: 7.4% nonzero\"], \"id\": \"el27974139829450483752\"}], \"width\": 480.0, \"data\": {\"data38\": [[0.0, 0.03474000000000001, 0.040982000000000005], [13.0, 0.03474000000000001, 0.040982000000000005], [13.0, 0.040982000000000005, 0.047224], [0.0, 0.040982000000000005, 0.047224]], \"data29\": [[0.0, -0.021438], [18.0, -0.021438], [18.0, -0.015196000000000001], [0.0, -0.015196000000000001]], \"data40\": [[0.0, 0.07219199999999999, 0.16582199999999997], [3.0, 0.07219199999999999, 0.16582199999999997], [3.0, 0.07843400000000002, 0.172064], [0.0, 0.07843400000000002, 0.172064]], \"data39\": [[0.0, 0.053466], [5.0, 0.053466], [5.0, 0.059708], [0.0, 0.059708]], \"data03\": [[0.48200000000000004, 0.0, 0.8128780487804876], [0.4917317073170732, 0.0, 0.8226097560975608], [0.4917317073170732, 2.0, 0.8226097560975608], [0.48200000000000004, 2.0, 0.8128780487804876]], \"data23\": [[0.0, -0.0901, -0.05889, -0.046405999999999996, 0.09091800000000001, 0.10340200000000001, 0.109644], [2.0, -0.0901, -0.05889, -0.046405999999999996, 0.09091800000000001, 0.10340200000000001, 0.109644], [2.0, -0.083858, -0.052648, -0.040164, 0.09716000000000001, 0.109644, 0.115886], [0.0, -0.083858, -0.052648, -0.040164, 0.09716000000000001, 0.109644, 0.115886]], \"data21\": [[0.7058292682926828, 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       "            })\n",
       "         });\n",
       "}\n",
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       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid = seaborn.jointplot('auroc', 'delta_auroc', data=auroc_df, joint_kws={'alpha': 0.5})\n",
    "points = grid.ax_joint.collections[0]\n",
    "labels = auroc_df.apply(lambda x: '{}: {:.1%} nonzero'.format(x['metapath'], x['nonzero']), axis=1).tolist()\n",
    "tooltip = mpld3.plugins.PointLabelTooltip(points, labels)\n",
    "mpld3.plugins.connect(grid.fig, tooltip)\n",
    "mpld3.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Time per query"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "   }(mpld3);\n",
       "}else if(typeof define === \"function\" && define.amd){\n",
       "   // require.js is available: use it to load d3/mpld3\n",
       "   require.config({paths: {d3: \"https://mpld3.github.io/js/d3.v3.min\"}});\n",
       "   require([\"d3\"], function(d3){\n",
       "      window.d3 = d3;\n",
       "      mpld3_load_lib(\"https://mpld3.github.io/js/mpld3.v0.2.js\", function(){\n",
       "         \n",
       "         mpld3.draw_figure(\"fig_el2797413982944877689650158691\", {\"axes\": [{\"sharex\": [\"el27974139829352788544\"], \"texts\": [{\"coordinates\": \"axes\", \"text\": \"seconds_per_query\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"middle\", \"fontsize\": 11.0, \"zorder\": 3, \"position\": [0.5, -0.06662678124660067], \"v_baseline\": \"hanging\", \"rotation\": -0.0, \"id\": \"el27974139829353977056\"}, {\"coordinates\": \"axes\", \"text\": \"auroc\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"middle\", \"fontsize\": 11.0, \"zorder\": 3, \"position\": [-0.08380388684666558, 0.5], \"v_baseline\": \"auto\", \"rotation\": -90.0, \"id\": \"el27974139829352950528\"}, {\"coordinates\": \"axes\", \"text\": \"None\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"start\", \"fontsize\": 10.0, \"zorder\": 1000003.0, \"position\": [-0.14747072462370073, -0.12944631785053842], \"v_baseline\": \"auto\", \"rotation\": -0.0, \"id\": 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       "      });\n",
       "    });\n",
       "}else{\n",
       "    // require.js not available: dynamically load d3 & mpld3\n",
       "    mpld3_load_lib(\"https://mpld3.github.io/js/d3.v3.min.js\", function(){\n",
       "         mpld3_load_lib(\"https://mpld3.github.io/js/mpld3.v0.2.js\", function(){\n",
       "                 \n",
       "                 mpld3.draw_figure(\"fig_el2797413982944877689650158691\", {\"axes\": [{\"sharex\": [\"el27974139829352788544\"], \"texts\": [{\"coordinates\": \"axes\", \"text\": \"seconds_per_query\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"middle\", \"fontsize\": 11.0, \"zorder\": 3, \"position\": [0.5, -0.06662678124660067], \"v_baseline\": \"hanging\", \"rotation\": -0.0, \"id\": \"el27974139829353977056\"}, {\"coordinates\": \"axes\", \"text\": \"auroc\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"middle\", \"fontsize\": 11.0, \"zorder\": 3, \"position\": [-0.08380388684666558, 0.5], \"v_baseline\": \"auto\", \"rotation\": -90.0, \"id\": \"el27974139829352950528\"}, {\"coordinates\": \"axes\", \"text\": \"None\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"start\", \"fontsize\": 10.0, \"zorder\": 1000003.0, \"position\": [-0.14747072462370073, -0.12944631785053842], \"v_baseline\": \"auto\", \"rotation\": -0.0, \"id\": \"el27974139829448319160\"}, {\"coordinates\": \"axes\", \"text\": \"pearsonr = 0.027; p = 0.51\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"start\", \"fontsize\": 10.0, \"zorder\": 1000003.0, \"position\": [0.5894212450174153, 0.9486021973240509], \"v_baseline\": \"auto\", \"rotation\": -0.0, \"id\": \"el27974139829448259176\"}], \"xdomain\": [-5.0, 40.0], \"axesbg\": \"#EAEAF2\", \"bbox\": [0.10616319444444446, 0.09444444444444444, 0.7198933531746032, 0.7296031746031746], \"axesbgalpha\": null, \"id\": \"el27974139829438636944\", \"paths\": [{\"coordinates\": \"axes\", \"alpha\": 1, \"data\": \"data02\", \"dasharray\": \"10,0\", \"edgecolor\": \"#FFFFFF\", \"zorder\": 1000001.0, \"edgewidth\": 0.3, \"facecolor\": \"#EAEAF2\", \"pathcodes\": [\"M\", \"L\", \"L\", \"L\", \"Z\"], \"id\": \"el27974139829448257832\", \"yindex\": 1, \"xindex\": 0}], \"axes\": [{\"tickvalues\": null, \"scale\": \"linear\", \"grid\": {\"dasharray\": \"10,0\", \"color\": \"#FFFFFF\", \"alpha\": 1.0, \"gridOn\": true}, \"nticks\": 10, \"fontsize\": 10.0, \"position\": \"bottom\", \"tickformat\": null}, {\"tickvalues\": null, \"scale\": \"linear\", \"grid\": {\"dasharray\": \"10,0\", \"color\": \"#FFFFFF\", \"alpha\": 1.0, \"gridOn\": true}, \"nticks\": 7, \"fontsize\": 10.0, \"position\": \"left\", \"tickformat\": null}], \"collections\": [{\"id\": \"el27974139829351868624\", \"offsetcoordinates\": \"data\", \"pathtransforms\": [[4.969039949999533, 0.0, 0.0, 4.969039949999533, 0.0, 0.0]], \"facecolors\": [\"#4C72B0\"], \"zorder\": 1, \"edgewidths\": [0.3], \"pathcoordinates\": \"display\", \"edgecolors\": [\"#4C72B0\"], \"alphas\": [0.5], \"offsets\": \"data01\", \"yindex\": 1, \"xindex\": 0, \"paths\": [[[[0.0, -0.5], [0.13260155, -0.5], [0.25978993539242673, -0.44731684579412084], [0.3535533905932738, -0.3535533905932738], [0.44731684579412084, -0.25978993539242673], [0.5, -0.13260155], [0.5, 0.0], [0.5, 0.13260155], [0.44731684579412084, 0.25978993539242673], 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     "execution_count": 11,
     "metadata": {},
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   ],
   "source": [
    "grid = seaborn.jointplot('seconds_per_query', 'auroc', data=auroc_df, joint_kws={'alpha': 0.5})\n",
    "points = grid.ax_joint.collections[0]\n",
    "labels = auroc_df.metapath.tolist()\n",
    "tooltip = mpld3.plugins.PointLabelTooltip(points, labels)\n",
    "mpld3.plugins.connect(grid.fig, tooltip)\n",
    "mpld3.display()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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-0.008954000000000004], [101.0, -0.002711999999999992], [0.0, -0.002711999999999992]], \"data16\": [[0.0, -0.027679999999999996], [10.0, -0.027679999999999996], [10.0, -0.021438], [0.0, -0.021438]]}, \"height\": 480.0, \"id\": \"el27974139829448375880\"});\n",
       "   }(mpld3);\n",
       "}else if(typeof define === \"function\" && define.amd){\n",
       "   // require.js is available: use it to load d3/mpld3\n",
       "   require.config({paths: {d3: \"https://mpld3.github.io/js/d3.v3.min\"}});\n",
       "   require([\"d3\"], function(d3){\n",
       "      window.d3 = d3;\n",
       "      mpld3_load_lib(\"https://mpld3.github.io/js/mpld3.v0.2.js\", function(){\n",
       "         \n",
       "         mpld3.draw_figure(\"fig_el279741398294483758804308474764\", {\"axes\": [{\"sharex\": [\"el27974139829450484648\"], \"texts\": [{\"coordinates\": \"axes\", \"text\": \"seconds_per_query\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"middle\", \"fontsize\": 11.0, \"zorder\": 3, \"position\": [0.5, -0.06662678124660067], \"v_baseline\": \"hanging\", \"rotation\": -0.0, \"id\": \"el27974139829448668608\"}, {\"coordinates\": \"axes\", \"text\": \"delta_auroc\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"middle\", \"fontsize\": 11.0, \"zorder\": 3, \"position\": [-0.1207152815433708, 0.5], \"v_baseline\": \"auto\", \"rotation\": -90.0, \"id\": \"el27974139829450991768\"}, {\"coordinates\": \"axes\", \"text\": \"None\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"start\", \"fontsize\": 10.0, \"zorder\": 1000003.0, \"position\": [-0.14762297104823055, -0.12944631785053842], \"v_baseline\": \"auto\", \"rotation\": -0.0, \"id\": 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-0.008954000000000004], [101.0, -0.002711999999999992], [0.0, -0.002711999999999992]], \"data16\": [[0.0, -0.027679999999999996], [10.0, -0.027679999999999996], [10.0, -0.021438], [0.0, -0.021438]]}, \"height\": 480.0, \"id\": \"el27974139829448375880\"});\n",
       "      });\n",
       "    });\n",
       "}else{\n",
       "    // require.js not available: dynamically load d3 & mpld3\n",
       "    mpld3_load_lib(\"https://mpld3.github.io/js/d3.v3.min.js\", function(){\n",
       "         mpld3_load_lib(\"https://mpld3.github.io/js/mpld3.v0.2.js\", function(){\n",
       "                 \n",
       "                 mpld3.draw_figure(\"fig_el279741398294483758804308474764\", {\"axes\": [{\"sharex\": [\"el27974139829450484648\"], \"texts\": [{\"coordinates\": \"axes\", \"text\": \"seconds_per_query\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"middle\", \"fontsize\": 11.0, \"zorder\": 3, \"position\": [0.5, -0.06662678124660067], \"v_baseline\": \"hanging\", \"rotation\": -0.0, \"id\": \"el27974139829448668608\"}, {\"coordinates\": \"axes\", \"text\": \"delta_auroc\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"middle\", \"fontsize\": 11.0, \"zorder\": 3, \"position\": [-0.1207152815433708, 0.5], \"v_baseline\": \"auto\", \"rotation\": -90.0, \"id\": \"el27974139829450991768\"}, {\"coordinates\": \"axes\", \"text\": \"None\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"start\", \"fontsize\": 10.0, \"zorder\": 1000003.0, \"position\": [-0.14762297104823055, -0.12944631785053842], \"v_baseline\": \"auto\", \"rotation\": -0.0, \"id\": \"el27974139829351226112\"}, {\"coordinates\": \"axes\", \"text\": \"pearsonr = -0.039; p = 0.33\", \"color\": \"#262626\", \"alpha\": 1, \"h_anchor\": \"start\", \"fontsize\": 10.0, \"zorder\": 1000003.0, \"position\": [0.5785215694364826, 0.9486021973240509], \"v_baseline\": \"auto\", \"rotation\": -0.0, \"id\": \"el27974139829351194408\"}], \"xdomain\": [-5.0, 40.0], \"axesbg\": \"#EAEAF2\", \"bbox\": [0.10626085069444445, 0.09444444444444444, 0.7198124379960318, 0.7296031746031746], \"axesbgalpha\": null, \"id\": \"el27974139829448544096\", \"paths\": [{\"coordinates\": \"axes\", \"alpha\": 1, \"data\": \"data02\", \"dasharray\": \"10,0\", \"edgecolor\": \"#FFFFFF\", \"zorder\": 1000001.0, \"edgewidth\": 0.3, \"facecolor\": \"#EAEAF2\", \"pathcodes\": [\"M\", \"L\", \"L\", \"L\", \"Z\"], \"id\": \"el27974139829351193456\", \"yindex\": 1, \"xindex\": 0}], \"axes\": [{\"tickvalues\": null, \"scale\": \"linear\", \"grid\": {\"dasharray\": \"10,0\", \"color\": \"#FFFFFF\", \"alpha\": 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-0.008954000000000004], [101.0, -0.002711999999999992], [0.0, -0.002711999999999992]], \"data16\": [[0.0, -0.027679999999999996], [10.0, -0.027679999999999996], [10.0, -0.021438], [0.0, -0.021438]]}, \"height\": 480.0, \"id\": \"el27974139829448375880\"});\n",
       "            })\n",
       "         });\n",
       "}\n",
       "</script>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid = seaborn.jointplot('seconds_per_query', 'delta_auroc', data=auroc_df, joint_kws={'alpha': 0.5})\n",
    "points = grid.ax_joint.collections[0]\n",
    "labels = auroc_df.metapath.tolist()\n",
    "tooltip = mpld3.plugins.PointLabelTooltip(points, labels)\n",
    "mpld3.plugins.connect(grid.fig, tooltip)\n",
    "mpld3.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Performance by Metaedge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import hetio.readwrite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "url = 'https://github.com/dhimmel/integrate/raw/d68b823bf2167e7ab7f0e784d1280200c33fb3bf/data/metagraph.json'\n",
    "metagraph = hetio.readwrite.read_metagraph(url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "rows = list()\n",
    "for abbreviation in auroc_df.metapath:\n",
    "    metapath = metagraph.metapath_from_abbrev(abbreviation)\n",
    "    for edge in metapath.edges:\n",
    "        edge = edge.inverse if edge.inverted else edge\n",
    "        rows.append((abbreviation, str(edge), edge.get_standard_abbrev()))\n",
    "metaedge_df = pandas.DataFrame(rows, columns=['metapath', 'metaedge', 'metaedge_abbrev'])\n",
    "metaedge_df = metaedge_df.merge(auroc_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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vgGuXsn6Yoa2YoS2YgRGEFJj2TuKefkzPAKZveE0/zrK04H7oEyEkqhVEcZ7M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AzwD9wJaW498A3gIMAx8G6kAZeC2628wngLNQd/g2a+29IvIa4GZ0nh3wS8nzn0cFbB640Vr7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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2c8e2b0780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "matplotlib.pyplot.figure(figsize=(8, 7))\n",
    "order = metaedge_df.sort_values('auroc', ascending=False).drop_duplicates('metaedge').metaedge\n",
    "ax = seaborn.stripplot(x='auroc', y='metaedge', data=metaedge_df, jitter=0.25, orient='h', alpha = 0.5, order=order)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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RqF/1ENs/TDp2EFfowHZ2k+493HKf08yOi4o48EK6uoSIm4ikSbA4RzA74a12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Dm2KiZmacRL6ucPnwdWSykfAP4AqETH3w18UUr5EPDHwNYFrp39K/D7wEeiPv5hkbanQi/wegRw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Gdi/Kl6A65cB5ulewW8pB+3aW5U4YXJsxOWpubLEjo38Vcy7uYiQJrF7vqUx5vIeOnqM3RSMS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\no6qY4DQMwzAMwzCqyv8HJoN+ZEnPgeYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2c8ddf6860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "matplotlib.pyplot.figure(figsize=(8, 7))\n",
    "order = metaedge_df.sort_values('delta_auroc', ascending=False).drop_duplicates('metaedge').metaedge\n",
    "ax = seaborn.stripplot(x='delta_auroc', y='metaedge', data=metaedge_df, jitter=0.25, orient='h', alpha = 0.5, order=order)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>metapath</th>\n",
       "      <th>nonzero</th>\n",
       "      <th>seconds_per_query</th>\n",
       "      <th>auroc</th>\n",
       "      <th>auroc_permuted</th>\n",
       "      <th>delta_auroc</th>\n",
       "      <th>pval_auroc</th>\n",
       "      <th>length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>251</th>\n",
       "      <td>CbGeAeGaD</td>\n",
       "      <td>0.984</td>\n",
       "      <td>0.837</td>\n",
       "      <td>0.685</td>\n",
       "      <td>0.649</td>\n",
       "      <td>0.03640</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>252</th>\n",
       "      <td>CbGeAeGdD</td>\n",
       "      <td>0.508</td>\n",
       "      <td>3.100</td>\n",
       "      <td>0.580</td>\n",
       "      <td>0.573</td>\n",
       "      <td>0.00711</td>\n",
       "      <td>0.008250</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253</th>\n",
       "      <td>CbGeAeGuD</td>\n",
       "      <td>0.517</td>\n",
       "      <td>3.350</td>\n",
       "      <td>0.594</td>\n",
       "      <td>0.590</td>\n",
       "      <td>0.00388</td>\n",
       "      <td>0.071900</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>CdGeAeGaD</td>\n",
       "      <td>0.683</td>\n",
       "      <td>9.550</td>\n",
       "      <td>0.612</td>\n",
       "      <td>0.614</td>\n",
       "      <td>-0.00199</td>\n",
       "      <td>0.869000</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>CdGeAeGdD</td>\n",
       "      <td>0.358</td>\n",
       "      <td>35.600</td>\n",
       "      <td>0.588</td>\n",
       "      <td>0.581</td>\n",
       "      <td>0.00699</td>\n",
       "      <td>0.031400</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>CdGeAeGuD</td>\n",
       "      <td>0.365</td>\n",
       "      <td>36.900</td>\n",
       "      <td>0.596</td>\n",
       "      <td>0.598</td>\n",
       "      <td>-0.00145</td>\n",
       "      <td>0.691000</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      metapath  nonzero  seconds_per_query  auroc  auroc_permuted  \\\n",
       "251  CbGeAeGaD    0.984              0.837  0.685           0.649   \n",
       "252  CbGeAeGdD    0.508              3.100  0.580           0.573   \n",
       "253  CbGeAeGuD    0.517              3.350  0.594           0.590   \n",
       "492  CdGeAeGaD    0.683              9.550  0.612           0.614   \n",
       "493  CdGeAeGdD    0.358             35.600  0.588           0.581   \n",
       "494  CdGeAeGuD    0.365             36.900  0.596           0.598   \n",
       "\n",
       "     delta_auroc  pval_auroc  length  \n",
       "251      0.03640    0.000007       4  \n",
       "252      0.00711    0.008250       4  \n",
       "253      0.00388    0.071900       4  \n",
       "492     -0.00199    0.869000       4  \n",
       "493      0.00699    0.031400       4  \n",
       "494     -0.00145    0.691000       4  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auroc_df[auroc_df.metapath.str.contains('GeAeG')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "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": "3.5.1"
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