{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Canarium GBS: *structure* analyses\n",
    "### *Federman et al.*\n",
    "\n",
    "This notebook provides all code necessary to reproduce the structure analyses. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Required software"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "## conda install ipyrad -c ipyrad\n",
    "## conda install toytree -c eaton-lab\n",
    "## conda install structure -c ipyrad\n",
    "## conda install clumpp -c ipyrad"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ipyrad v.0.7.22\n"
     ]
    }
   ],
   "source": [
    "import toytree\n",
    "import toyplot.svg\n",
    "import numpy as np\n",
    "import ipyrad as ip\n",
    "import ipyrad.analysis as ipa\n",
    "print \"ipyrad v.{}\".format(ip.__version__)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Connect to cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "host compute node: [40 cores] on sacra\n"
     ]
    }
   ],
   "source": [
    "import ipyparallel as ipp\n",
    "ipyclient = ipp.Client()\n",
    "ip.cluster_info(ipyclient)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Population structure "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "## define k vals to test\n",
    "tests = [2, 3, 4, 5, 6, 7, 8, 9, 10]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "## init structure analysis object\n",
    "s = ipa.structure(\n",
    "    name=\"Canarium-min30-nout\", \n",
    "    data=\"analysis-ipyrad/Canarium-min30-nout_outfiles/Canarium-min30-nout.str\",\n",
    "    mapfile=\"analysis-ipyrad/Canarium-min30-nout_outfiles/Canarium-min30-nout.snps.map\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "## set mainparams for object\n",
    "s.mainparams.burnin = 50000\n",
    "s.mainparams.numreps = 100000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "submitted 20 structure jobs [Canarium-min30-nout-K-2]\n",
      "submitted 20 structure jobs [Canarium-min30-nout-K-3]\n",
      "submitted 20 structure jobs [Canarium-min30-nout-K-4]\n",
      "submitted 20 structure jobs [Canarium-min30-nout-K-5]\n",
      "submitted 20 structure jobs [Canarium-min30-nout-K-6]\n",
      "submitted 20 structure jobs [Canarium-min30-nout-K-7]\n",
      "submitted 20 structure jobs [Canarium-min30-nout-K-8]\n",
      "submitted 20 structure jobs [Canarium-min30-nout-K-9]\n",
      "submitted 20 structure jobs [Canarium-min30-nout-K-10]\n"
     ]
    }
   ],
   "source": [
    "## submit batches of 20 replicate jobs for each value of K \n",
    "for kpop in tests:\n",
    "    s.run(\n",
    "        kpop=kpop, \n",
    "        nreps=20, \n",
    "        seed=12345,\n",
    "        ipyclient=ipyclient,\n",
    "        )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Run some jobs longer\n",
    "For the high K values it seems that some of them had few or no reps that converged, so we ran an additional 20 reps for each K from 6-10 for a longer number of generations to get better convergence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "## set longer run times for additional reps on large Ks\n",
    "s.mainparams.burnin = 100000\n",
    "s.mainparams.numreps = 500000\n",
    "moretests = [6, 7, 8, 9, 10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "submitted 20 structure jobs [Canarium-min30-nout-K-6]\n",
      "submitted 20 structure jobs [Canarium-min30-nout-K-7]\n",
      "submitted 20 structure jobs [Canarium-min30-nout-K-8]\n",
      "submitted 20 structure jobs [Canarium-min30-nout-K-9]\n",
      "submitted 20 structure jobs [Canarium-min30-nout-K-10]\n"
     ]
    }
   ],
   "source": [
    "## submit batches of 20 replicate jobs for each high value of K \n",
    "for kpop in moretests:\n",
    "    s.run(\n",
    "        kpop=kpop, \n",
    "        nreps=20, \n",
    "        seed=12345,\n",
    "        ipyclient=ipyclient,\n",
    "        )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Summarize results\n",
    "\n",
    "### Get Evanno table for best fitting K\n",
    "Below are Evanno tables calculated for several different values of the filtering parameter `max_var_multiple`, which is used to exclude replicates that have a variance of LnLik N times greater than the rep with minimum variance for that value of K. We find that with `max_var_multiple=100` we get approximately 20 reps in every test that passes filtering. The goal here is to exclude reps that may not have converged and therefore would otherwise lower the score for that value of K. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Nreps</th>\n",
       "      <th>deltaK</th>\n",
       "      <th>estLnProbMean</th>\n",
       "      <th>estLnProbStdev</th>\n",
       "      <th>lnPK</th>\n",
       "      <th>lnPPK</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-1.537e+05</td>\n",
       "      <td>2.406e+03</td>\n",
       "      <td>0.000e+00</td>\n",
       "      <td>0.000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20</td>\n",
       "      <td>2.029</td>\n",
       "      <td>-1.373e+05</td>\n",
       "      <td>1.043e+04</td>\n",
       "      <td>1.638e+04</td>\n",
       "      <td>2.116e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20</td>\n",
       "      <td>1235.503</td>\n",
       "      <td>-1.421e+05</td>\n",
       "      <td>1.556e+03</td>\n",
       "      <td>-4.773e+03</td>\n",
       "      <td>1.923e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>20</td>\n",
       "      <td>0.847</td>\n",
       "      <td>-2.069e+06</td>\n",
       "      <td>3.035e+06</td>\n",
       "      <td>-1.927e+06</td>\n",
       "      <td>2.569e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>39</td>\n",
       "      <td>0.674</td>\n",
       "      <td>-1.427e+06</td>\n",
       "      <td>3.116e+06</td>\n",
       "      <td>6.420e+05</td>\n",
       "      <td>2.099e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>39</td>\n",
       "      <td>0.284</td>\n",
       "      <td>-2.884e+06</td>\n",
       "      <td>5.253e+06</td>\n",
       "      <td>-1.457e+06</td>\n",
       "      <td>1.493e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>39</td>\n",
       "      <td>0.143</td>\n",
       "      <td>-2.848e+06</td>\n",
       "      <td>5.440e+06</td>\n",
       "      <td>3.654e+04</td>\n",
       "      <td>7.805e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>39</td>\n",
       "      <td>0.308</td>\n",
       "      <td>-3.592e+06</td>\n",
       "      <td>5.755e+06</td>\n",
       "      <td>-7.440e+05</td>\n",
       "      <td>1.775e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>39</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-2.561e+06</td>\n",
       "      <td>3.312e+06</td>\n",
       "      <td>1.031e+06</td>\n",
       "      <td>0.000e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Nreps    deltaK  estLnProbMean  estLnProbStdev       lnPK      lnPPK\n",
       "2      20     0.000     -1.537e+05       2.406e+03  0.000e+00  0.000e+00\n",
       "3      20     2.029     -1.373e+05       1.043e+04  1.638e+04  2.116e+04\n",
       "4      20  1235.503     -1.421e+05       1.556e+03 -4.773e+03  1.923e+06\n",
       "5      20     0.847     -2.069e+06       3.035e+06 -1.927e+06  2.569e+06\n",
       "6      39     0.674     -1.427e+06       3.116e+06  6.420e+05  2.099e+06\n",
       "7      39     0.284     -2.884e+06       5.253e+06 -1.457e+06  1.493e+06\n",
       "8      39     0.143     -2.848e+06       5.440e+06  3.654e+04  7.805e+05\n",
       "9      39     0.308     -3.592e+06       5.755e+06 -7.440e+05  1.775e+06\n",
       "10     39     0.000     -2.561e+06       3.312e+06  1.031e+06  0.000e+00"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.get_evanno_table(tests, max_var_multiple=0, quiet=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Nreps</th>\n",
       "      <th>deltaK</th>\n",
       "      <th>estLnProbMean</th>\n",
       "      <th>estLnProbStdev</th>\n",
       "      <th>lnPK</th>\n",
       "      <th>lnPPK</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-153726.185</td>\n",
       "      <td>2405.508</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20</td>\n",
       "      <td>2.029</td>\n",
       "      <td>-137343.785</td>\n",
       "      <td>10428.473</td>\n",
       "      <td>16382.400</td>\n",
       "      <td>21155.730</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20</td>\n",
       "      <td>4.618</td>\n",
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       "      <th>5</th>\n",
       "      <td>13</td>\n",
       "      <td>0.792</td>\n",
       "      <td>-139703.592</td>\n",
       "      <td>2555.662</td>\n",
       "      <td>2413.523</td>\n",
       "      <td>2025.005</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>24</td>\n",
       "      <td>1.780</td>\n",
       "      <td>-139315.075</td>\n",
       "      <td>7703.825</td>\n",
       "      <td>388.517</td>\n",
       "      <td>13710.965</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>13</td>\n",
       "      <td>0.581</td>\n",
       "      <td>-152637.523</td>\n",
       "      <td>36075.618</td>\n",
       "      <td>-13322.448</td>\n",
       "      <td>20948.565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>17</td>\n",
       "      <td>0.646</td>\n",
       "      <td>-145011.406</td>\n",
       "      <td>32030.165</td>\n",
       "      <td>7626.117</td>\n",
       "      <td>20693.599</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>8</td>\n",
       "      <td>0.218</td>\n",
       "      <td>-158078.888</td>\n",
       "      <td>35401.179</td>\n",
       "      <td>-13067.482</td>\n",
       "      <td>7730.769</td>\n",
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       "      <th>10</th>\n",
       "      <td>4</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-163415.600</td>\n",
       "      <td>31602.319</td>\n",
       "      <td>-5336.712</td>\n",
       "      <td>0.000</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Nreps  deltaK  estLnProbMean  estLnProbStdev       lnPK      lnPPK\n",
       "2      20   0.000    -153726.185        2405.508      0.000      0.000\n",
       "3      20   2.029    -137343.785       10428.473  16382.400  21155.730\n",
       "4      20   4.618    -142117.115        1556.118  -4773.330   7186.853\n",
       "5      13   0.792    -139703.592        2555.662   2413.523   2025.005\n",
       "6      24   1.780    -139315.075        7703.825    388.517  13710.965\n",
       "7      13   0.581    -152637.523       36075.618 -13322.448  20948.565\n",
       "8      17   0.646    -145011.406       32030.165   7626.117  20693.599\n",
       "9       8   0.218    -158078.888       35401.179 -13067.482   7730.769\n",
       "10      4   0.000    -163415.600       31602.319  -5336.712      0.000"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.get_evanno_table(tests, max_var_multiple=10, quiet=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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       "      <th>Nreps</th>\n",
       "      <th>deltaK</th>\n",
       "      <th>estLnProbMean</th>\n",
       "      <th>estLnProbStdev</th>\n",
       "      <th>lnPK</th>\n",
       "      <th>lnPPK</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20</td>\n",
       "      <td>0.000</td>\n",
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       "      <th>4</th>\n",
       "      <td>20</td>\n",
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       "      <th>5</th>\n",
       "      <td>13</td>\n",
       "      <td>9.085</td>\n",
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       "      <td>2555.662</td>\n",
       "      <td>2413.523</td>\n",
       "      <td>23218.227</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>26</td>\n",
       "      <td>0.645</td>\n",
       "      <td>-160508.296</td>\n",
       "      <td>82413.941</td>\n",
       "      <td>-20804.704</td>\n",
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       "      <th>7</th>\n",
       "      <td>17</td>\n",
       "      <td>0.594</td>\n",
       "      <td>-234492.488</td>\n",
       "      <td>168026.173</td>\n",
       "      <td>-73984.192</td>\n",
       "      <td>99840.352</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>21</td>\n",
       "      <td>1.320</td>\n",
       "      <td>-208636.329</td>\n",
       "      <td>152555.065</td>\n",
       "      <td>25856.160</td>\n",
       "      <td>201418.181</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>20</td>\n",
       "      <td>0.423</td>\n",
       "      <td>-384198.350</td>\n",
       "      <td>230926.987</td>\n",
       "      <td>-175562.021</td>\n",
       "      <td>97648.791</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>20</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-462111.580</td>\n",
       "      <td>221353.039</td>\n",
       "      <td>-77913.230</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Nreps  deltaK  estLnProbMean  estLnProbStdev        lnPK       lnPPK\n",
       "2      20   0.000    -153726.185        2405.508       0.000       0.000\n",
       "3      20   2.029    -137343.785       10428.473   16382.400   21155.730\n",
       "4      20   4.618    -142117.115        1556.118   -4773.330    7186.853\n",
       "5      13   9.085    -139703.592        2555.662    2413.523   23218.227\n",
       "6      26   0.645    -160508.296       82413.941  -20804.704   53179.488\n",
       "7      17   0.594    -234492.488      168026.173  -73984.192   99840.352\n",
       "8      21   1.320    -208636.329      152555.065   25856.160  201418.181\n",
       "9      20   0.423    -384198.350      230926.987 -175562.021   97648.791\n",
       "10     20   0.000    -462111.580      221353.039  -77913.230       0.000"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.get_evanno_table(tests, max_var_multiple=50, quiet=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Nreps</th>\n",
       "      <th>deltaK</th>\n",
       "      <th>estLnProbMean</th>\n",
       "      <th>estLnProbStdev</th>\n",
       "      <th>lnPK</th>\n",
       "      <th>lnPPK</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-153726.185</td>\n",
       "      <td>2405.508</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20</td>\n",
       "      <td>2.029</td>\n",
       "      <td>-137343.785</td>\n",
       "      <td>10428.473</td>\n",
       "      <td>16382.400</td>\n",
       "      <td>21155.730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20</td>\n",
       "      <td>4.618</td>\n",
       "      <td>-142117.115</td>\n",
       "      <td>1556.118</td>\n",
       "      <td>-4773.330</td>\n",
       "      <td>7186.853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>13</td>\n",
       "      <td>40.533</td>\n",
       "      <td>-139703.592</td>\n",
       "      <td>2555.662</td>\n",
       "      <td>2413.523</td>\n",
       "      <td>103589.589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>29</td>\n",
       "      <td>0.894</td>\n",
       "      <td>-240879.659</td>\n",
       "      <td>254325.896</td>\n",
       "      <td>-101176.066</td>\n",
       "      <td>227331.040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>26</td>\n",
       "      <td>1.045</td>\n",
       "      <td>-569386.765</td>\n",
       "      <td>506552.755</td>\n",
       "      <td>-328507.107</td>\n",
       "      <td>529423.850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>27</td>\n",
       "      <td>1.071</td>\n",
       "      <td>-368470.022</td>\n",
       "      <td>342168.594</td>\n",
       "      <td>200916.743</td>\n",
       "      <td>366448.612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>23</td>\n",
       "      <td>0.343</td>\n",
       "      <td>-534001.891</td>\n",
       "      <td>450635.181</td>\n",
       "      <td>-165531.869</td>\n",
       "      <td>154559.665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>22</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-544974.095</td>\n",
       "      <td>341123.401</td>\n",
       "      <td>-10972.204</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Nreps  deltaK  estLnProbMean  estLnProbStdev        lnPK       lnPPK\n",
       "2      20   0.000    -153726.185        2405.508       0.000       0.000\n",
       "3      20   2.029    -137343.785       10428.473   16382.400   21155.730\n",
       "4      20   4.618    -142117.115        1556.118   -4773.330    7186.853\n",
       "5      13  40.533    -139703.592        2555.662    2413.523  103589.589\n",
       "6      29   0.894    -240879.659      254325.896 -101176.066  227331.040\n",
       "7      26   1.045    -569386.765      506552.755 -328507.107  529423.850\n",
       "8      27   1.071    -368470.022      342168.594  200916.743  366448.612\n",
       "9      23   0.343    -534001.891      450635.181 -165531.869  154559.665\n",
       "10     22   0.000    -544974.095      341123.401  -10972.204       0.000"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.get_evanno_table(tests, max_var_multiple=100, quiet=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        text-align: right;\n",
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       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Nreps</th>\n",
       "      <th>deltaK</th>\n",
       "      <th>estLnProbMean</th>\n",
       "      <th>estLnProbStdev</th>\n",
       "      <th>lnPK</th>\n",
       "      <th>lnPPK</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-1.537e+05</td>\n",
       "      <td>2.406e+03</td>\n",
       "      <td>0.000e+00</td>\n",
       "      <td>0.000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20</td>\n",
       "      <td>2.029</td>\n",
       "      <td>-1.373e+05</td>\n",
       "      <td>1.043e+04</td>\n",
       "      <td>1.638e+04</td>\n",
       "      <td>2.116e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20</td>\n",
       "      <td>983.330</td>\n",
       "      <td>-1.421e+05</td>\n",
       "      <td>1.556e+03</td>\n",
       "      <td>-4.773e+03</td>\n",
       "      <td>1.530e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>19</td>\n",
       "      <td>0.967</td>\n",
       "      <td>-1.677e+06</td>\n",
       "      <td>2.544e+06</td>\n",
       "      <td>-1.535e+06</td>\n",
       "      <td>2.461e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>37</td>\n",
       "      <td>2.031</td>\n",
       "      <td>-7.510e+05</td>\n",
       "      <td>1.030e+06</td>\n",
       "      <td>9.261e+05</td>\n",
       "      <td>2.093e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>37</td>\n",
       "      <td>0.413</td>\n",
       "      <td>-1.918e+06</td>\n",
       "      <td>2.972e+06</td>\n",
       "      <td>-1.167e+06</td>\n",
       "      <td>1.227e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>37</td>\n",
       "      <td>0.250</td>\n",
       "      <td>-1.858e+06</td>\n",
       "      <td>3.142e+06</td>\n",
       "      <td>5.974e+04</td>\n",
       "      <td>7.863e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>37</td>\n",
       "      <td>0.199</td>\n",
       "      <td>-2.585e+06</td>\n",
       "      <td>3.780e+06</td>\n",
       "      <td>-7.265e+05</td>\n",
       "      <td>7.504e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>39</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-2.561e+06</td>\n",
       "      <td>3.312e+06</td>\n",
       "      <td>2.385e+04</td>\n",
       "      <td>0.000e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Nreps   deltaK  estLnProbMean  estLnProbStdev       lnPK      lnPPK\n",
       "2      20    0.000     -1.537e+05       2.406e+03  0.000e+00  0.000e+00\n",
       "3      20    2.029     -1.373e+05       1.043e+04  1.638e+04  2.116e+04\n",
       "4      20  983.330     -1.421e+05       1.556e+03 -4.773e+03  1.530e+06\n",
       "5      19    0.967     -1.677e+06       2.544e+06 -1.535e+06  2.461e+06\n",
       "6      37    2.031     -7.510e+05       1.030e+06  9.261e+05  2.093e+06\n",
       "7      37    0.413     -1.918e+06       2.972e+06 -1.167e+06  1.227e+06\n",
       "8      37    0.250     -1.858e+06       3.142e+06  5.974e+04  7.863e+05\n",
       "9      37    0.199     -2.585e+06       3.780e+06 -7.265e+05  7.504e+05\n",
       "10     39    0.000     -2.561e+06       3.312e+06  2.385e+04  0.000e+00"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.get_evanno_table(tests, max_var_multiple=1000, quiet=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get permuted reps with CLUMPP\n",
    "We calculate a permuted table of results across replicate runs for each value of K while excluding reps based on the max_var_multiple parameter (see above for description). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "## summarize results\n",
    "s.clumppparams.m = 3                ## use largegreedy algorithm\n",
    "s.clumppparams.greedy_option = 2    ## test nrepeat possible orders\n",
    "s.clumppparams.repeats = 100000     ## number of repeats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[K2] 20/20 results permuted across replicates (max_var=100.0).\n",
      "[K3] 20/20 results permuted across replicates (max_var=100.0).\n",
      "[K4] 20/20 results permuted across replicates (max_var=100.0).\n",
      "[K5] 13/20 results permuted across replicates (max_var=100.0).\n",
      "[K6] 29/39 results permuted across replicates (max_var=100.0).\n",
      "[K7] 26/39 results permuted across replicates (max_var=100.0).\n",
      "[K8] 27/39 results permuted across replicates (max_var=100.0).\n",
      "[K9] 23/39 results permuted across replicates (max_var=100.0).\n",
      "[K10] 22/39 results permuted across replicates (max_var=100.0).\n"
     ]
    }
   ],
   "source": [
    "qtable = s.get_clumpp_table(tests, max_var_multiple=100.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[K2] 20/20 results permuted across replicates (max_var=100.0).\n",
      "[K3] 20/20 results permuted across replicates (max_var=100.0).\n",
      "[K4] 20/20 results permuted across replicates (max_var=100.0).\n",
      "[K5] 13/20 results permuted across replicates (max_var=100.0).\n",
      "[K6] 29/39 results permuted across replicates (max_var=100.0).\n",
      "[K7] 26/39 results permuted across replicates (max_var=100.0).\n",
      "[K8] 27/39 results permuted across replicates (max_var=100.0).\n",
      "[K9] 23/39 results permuted across replicates (max_var=100.0).\n",
      "[K10] 22/39 results permuted across replicates (max_var=100.0).\n"
     ]
    }
   ],
   "source": [
    "qtable = s.get_clumpp_table(tests, max_var_multiple=100.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Barplots of population structure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "## load a tree topology for ordering tips on barplot\n",
    "tre = toytree.tree(\"./analysis-raxml/RAxML_bipartitions.Canarium-min20\")\n",
    "\n",
    "## root on outgroups and then drop outgroups from the tree\n",
    "outs = [\"D14269\", \"D13374\", \"D13852\", \"SFC1988\"]\n",
    "rtre = tre.root(outs).drop_tips(outs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for kpop in tests:\n",
    "    c = toyplot.Canvas(width=550, height=110)\n",
    "    a = c.cartesian(margin=25)   \n",
    "    minpos = np.linspace(0, 38, 38)\n",
    "    maxpos = np.linspace(0.9, 38.9, 38)\n",
    "    m = a.bars(minpos, maxpos,\n",
    "               qtable[kpop].loc[rtre.get_tip_labels()[::-1],],\n",
    "               color = toyplot.color.brewer.map(\"Set3\"),\n",
    "               style={\"stroke-width\": 0.5},\n",
    "               )\n",
    "    a.show = False\n",
    "    \n",
    "    ## save figure\n",
    "    import toyplot.svg\n",
    "    toyplot.svg.render(c, \"figures/structure-k{}.svg\".format(kpop))   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
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       "{\n",
       "var modules={};\n",
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       "        var tables = [];\n",
       "\n",
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       "\n",
       "        module.set = function(owner, key, names, columns)\n",
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       "            tables.push({owner: owner, key: key, names: names, columns: columns});\n",
       "        }\n",
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       "            for(var i = 0; i != tables.length; ++i)\n",
       "            {\n",
       "                var table = tables[i];\n",
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       "                if(table.key != key)\n",
       "                    continue;\n",
       "                return {names: table.names, columns: table.columns};\n",
       "            }\n",
       "        }\n",
       "\n",
       "        module.get_csv = function(owner, key)\n",
       "        {\n",
       "            var table = module.get(owner, key);\n",
       "            if(table != undefined)\n",
       "            {\n",
       "                var csv = \"\";\n",
       "                csv += table.names.join(\",\") + \"\\n\";\n",
       "                for(var i = 0; i != table.columns[0].length; ++i)\n",
       "                {\n",
       "                  for(var j = 0; j != table.columns.length; ++j)\n",
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       "                    if(j)\n",
       "                      csv += \",\";\n",
       "                    csv += table.columns[j][i];\n",
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       "                  csv += \"\\n\";\n",
       "                }\n",
       "                return csv;\n",
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       "\n",
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       "modules[\"toyplot/root/id\"] = \"t01fcbcf4d62d4fea8fbebf3be330afef\";\n",
       "modules[\"toyplot/root\"] = (function(root_id)\n",
       "    {\n",
       "        return document.querySelector(\"#\" + root_id);\n",
       "    })(modules[\"toyplot/root/id\"]);\n",
       "modules[\"toyplot/canvas/id\"] = \"t2a02250263844dcf9b28af46ee86ae8c\";\n",
       "modules[\"toyplot/canvas\"] = (function(canvas_id)\n",
       "    {\n",
       "        return document.querySelector(\"#\" + canvas_id);\n",
       "    })(modules[\"toyplot/canvas/id\"]);\n",
       "modules[\"toyplot/menus/context\"] = (function(root, canvas)\n",
       "    {\n",
       "        var wrapper = document.createElement(\"div\");\n",
       "        wrapper.innerHTML = \"<ul class='toyplot-context-menu' style='background:#eee; border:1px solid #b8b8b8; border-radius:5px; box-shadow: 0px 0px 8px rgba(0%,0%,0%,0.25); margin:0; padding:3px 0; position:fixed; visibility:hidden;'></ul>\"\n",
       "        var menu = wrapper.firstChild;\n",
       "\n",
       "        root.appendChild(menu);\n",
       "\n",
       "        var items = [];\n",
       "\n",
       "        var ignore_mouseup = null;\n",
       "        function open_menu(e)\n",
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       "                e.stopPropagation();\n",
       "                e.preventDefault();\n",
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       "\n",
       "        function close_menu()\n",
       "        {\n",
       "            menu.style.visibility = \"hidden\";\n",
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       "\n",
       "        function contextmenu(e)\n",
       "        {\n",
       "            open_menu(e);\n",
       "        }\n",
       "\n",
       "        function mousemove(e)\n",
       "        {\n",
       "            ignore_mouseup = false;\n",
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       "\n",
       "        function mouseup(e)\n",
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       "            if(ignore_mouseup)\n",
       "            {\n",
       "                ignore_mouseup = false;\n",
       "                return;\n",
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       "            close_menu();\n",
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       "\n",
       "        canvas.addEventListener(\"contextmenu\", contextmenu);\n",
       "        canvas.addEventListener(\"mousemove\", mousemove);\n",
       "        document.addEventListener(\"mouseup\", mouseup);\n",
       "        document.addEventListener(\"keydown\", keydown);\n",
       "\n",
       "        var module = {};\n",
       "        module.add_item = function(label, show, activate)\n",
       "        {\n",
       "            var wrapper = document.createElement(\"div\");\n",
       "            wrapper.innerHTML = \"<li class='toyplot-context-menu-item' style='background:#eee; color:#333; padding:2px 20px; list-style:none; margin:0; text-align:left;'>\" + label + \"</li>\"\n",
       "            var item = wrapper.firstChild;\n",
       "\n",
       "            items.push({item: item, show: show});\n",
       "\n",
       "            function mouseover()\n",
       "            {\n",
       "                this.style.background = \"steelblue\";\n",
       "                this.style.color = \"white\";\n",
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       "\n",
       "            function mouseout()\n",
       "            {\n",
       "                this.style.background = \"#eee\";\n",
       "                this.style.color = \"#333\";\n",
       "            }\n",
       "\n",
       "            function choose_item(e)\n",
       "            {\n",
       "                close_menu();\n",
       "                activate();\n",
       "\n",
       "                e.stopPropagation();\n",
       "                e.preventDefault();\n",
       "            }\n",
       "\n",
       "            item.addEventListener(\"mouseover\", mouseover);\n",
       "            item.addEventListener(\"mouseout\", mouseout);\n",
       "            item.addEventListener(\"mouseup\", choose_item);\n",
       "            item.addEventListener(\"contextmenu\", choose_item);\n",
       "\n",
       "            menu.appendChild(item);\n",
       "        };\n",
       "        return module;\n",
       "    })(modules[\"toyplot/root\"],modules[\"toyplot/canvas\"]);\n",
       "modules[\"toyplot/io\"] = (function()\n",
       "    {\n",
       "        var module = {};\n",
       "        module.save_file = function(mime_type, charset, data, filename)\n",
       "        {\n",
       "            var uri = \"data:\" + mime_type + \";charset=\" + charset + \",\" + data;\n",
       "            uri = encodeURI(uri);\n",
       "\n",
       "            var link = document.createElement(\"a\");\n",
       "            if(typeof link.download != \"undefined\")\n",
       "            {\n",
       "              link.href = uri;\n",
       "              link.style = \"visibility:hidden\";\n",
       "              link.download = filename;\n",
       "\n",
       "              document.body.appendChild(link);\n",
       "              link.click();\n",
       "              document.body.removeChild(link);\n",
       "            }\n",
       "            else\n",
       "            {\n",
       "              window.open(uri);\n",
       "            }\n",
       "        };\n",
       "        return module;\n",
       "    })();\n",
       "(function(tables, context_menu, io, owner_id, key, label, names, columns, filename)\n",
       "        {\n",
       "            tables.set(owner_id, key, names, columns);\n",
       "\n",
       "            var owner = document.querySelector(\"#\" + owner_id);\n",
       "            function show_item(e)\n",
       "            {\n",
       "                return owner.contains(e.target);\n",
       "            }\n",
       "\n",
       "            function choose_item()\n",
       "            {\n",
       "                io.save_file(\"text/csv\", \"utf-8\", tables.get_csv(owner_id, key), filename + \".csv\");\n",
       "            }\n",
       "\n",
       "            context_menu.add_item(\"Save \" + label + \" as CSV\", show_item, choose_item);\n",
       "        })(modules[\"toyplot/tables\"],modules[\"toyplot/menus/context\"],modules[\"toyplot/io\"],\"tdec5e97f5685467e94a7aed28aeb47eb\",\"data\",\"bar data\",[\"left\", \"right\", \"baseline\", \"magnitude0\", \"magnitude1\", \"magnitude2\", \"magnitude3\", \"magnitude4\", \"magnitude5\", \"magnitude6\", \"magnitude7\"],[[0.0, 1.027027027027027, 2.054054054054054, 3.0810810810810807, 4.108108108108108, 5.135135135135135, 6.162162162162161, 7.189189189189189, 8.216216216216216, 9.243243243243242, 10.27027027027027, 11.297297297297296, 12.324324324324323, 13.35135135135135, 14.378378378378377, 15.405405405405405, 16.43243243243243, 17.45945945945946, 18.486486486486484, 19.513513513513512, 20.54054054054054, 21.567567567567565, 22.594594594594593, 23.62162162162162, 24.648648648648646, 25.675675675675674, 26.7027027027027, 27.72972972972973, 28.756756756756754, 29.783783783783782, 30.81081081081081, 31.837837837837835, 32.86486486486486, 33.89189189189189, 34.91891891891892, 35.945945945945944, 36.97297297297297, 38.0], [0.9, 1.927027027027027, 2.954054054054054, 3.9810810810810806, 5.008108108108108, 6.035135135135135, 7.062162162162162, 8.089189189189188, 9.116216216216216, 10.143243243243242, 11.17027027027027, 12.197297297297297, 13.224324324324323, 14.251351351351351, 15.278378378378378, 16.305405405405406, 17.33243243243243, 18.35945945945946, 19.386486486486483, 20.41351351351351, 21.44054054054054, 22.467567567567563, 23.49459459459459, 24.52162162162162, 25.548648648648644, 26.575675675675672, 27.6027027027027, 28.62972972972973, 29.656756756756753, 30.68378378378378, 31.71081081081081, 32.73783783783784, 33.76486486486486, 34.791891891891886, 35.81891891891892, 36.84594594594594, 37.87297297297297, 38.9], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.9402, 0.9387, 0.9371, 0.955, 0.9447, 0.9254, 0.9278, 0.9176, 0.8889, 0.8863, 0.912, 0.8965, 0.9136, 0.8799, 0.3235, 0.3856, 0.0, 0.0742, 0.0007, 0.0006, 0.0031, 0.0002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0047, 0.0, 0.0178, 0.0, 0.3624, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0003, 1.0, 0.9822, 0.9627, 0.5841, 0.9887, 0.9985, 0.9431, 0.9478, 0.9387], [0.0004, 0.0003, 0.0012, 0.0, 0.0003, 0.0007, 0.0009, 0.0, 0.0035, 0.0034, 0.0014, 0.001, 0.0015, 0.005, 0.001, 0.0, 0.002, 0.0001, 0.0, 0.0001, 0.0, 0.0, 0.0005, 0.0012, 0.002, 0.7822, 0.7725, 0.5974, 0.5209, 0.0, 0.0, 0.0016, 0.0011, 0.0006, 0.0014, 0.0024, 0.0025, 0.0022], [0.0, 0.0, 0.0002, 0.0, 0.0, 0.0001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0001, 0.0395, 0.0216, 0.7482, 0.7545, 0.7692, 0.7383, 0.7751, 0.7908, 0.2771, 0.2696, 0.2913, 0.2121, 0.2226, 0.328, 0.3846, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0001, 0.0, 0.0, 0.0], [0.0059, 0.0078, 0.0044, 0.0069, 0.0079, 0.006, 0.0077, 0.0079, 0.0048, 0.0029, 0.0051, 0.0023, 0.0061, 0.0098, 0.0001, 0.0001, 0.0705, 0.0113, 0.0122, 0.01, 0.0074, 0.0126, 0.7219, 0.7227, 0.6818, 0.0015, 0.0013, 0.0074, 0.0069, 0.0, 0.0, 0.0033, 0.0072, 0.0011, 0.0, 0.0062, 0.0054, 0.0079], [0.0004, 0.001, 0.0014, 0.001, 0.0002, 0.0027, 0.0019, 0.0042, 0.0, 0.0001, 0.0, 0.0002, 0.0022, 0.0019, 0.6358, 0.5927, 0.0022, 0.0001, 0.002, 0.002, 0.0032, 0.002, 0.0, 0.0001, 0.0002, 0.0, 0.0001, 0.0001, 0.031, 0.0, 0.0, 0.0012, 0.0007, 0.0002, 0.0, 0.0023, 0.0013, 0.0021], [0.0345, 0.0326, 0.0286, 0.0256, 0.0346, 0.0388, 0.0429, 0.0524, 0.0893, 0.0909, 0.0592, 0.0736, 0.0648, 0.0617, 0.0, 0.0, 0.0373, 0.03, 0.0111, 0.0083, 0.0197, 0.0054, 0.0004, 0.0038, 0.0146, 0.0015, 0.0015, 0.0357, 0.0274, 0.0, 0.0, 0.0158, 0.0275, 0.0048, 0.0, 0.0233, 0.0241, 0.0252], [0.0186, 0.0197, 0.027, 0.0114, 0.0123, 0.0263, 0.0189, 0.0179, 0.0134, 0.0165, 0.0223, 0.0265, 0.0118, 0.0416, 0.0, 0.0, 0.1396, 0.1297, 0.2048, 0.2406, 0.1915, 0.189, 0.0, 0.0026, 0.0102, 0.0026, 0.0019, 0.0313, 0.0242, 0.0, 0.0, 0.0154, 0.0171, 0.0047, 0.0, 0.0227, 0.0189, 0.0239]],\"toyplot\");\n",
       "})();</script></div></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import toyplot\n",
    "import numpy as np\n",
    "\n",
    "## create canvas\n",
    "c = toyplot.Canvas(width=600, height=160)\n",
    "a = c.cartesian()\n",
    "\n",
    "## order of colors\n",
    "order = [2, 7, 0, 5, 4, 1, 6, 3][::-1]\n",
    "\n",
    "## space between bars\n",
    "minpos = np.linspace(0, 38, 38)\n",
    "maxpos = np.linspace(0.9, 38.9, 38)\n",
    "\n",
    "## plot bars\n",
    "m = a.bars(minpos, maxpos, \n",
    "           qtable[8].loc[rtre.get_tip_labels()[::-1], order],\n",
    "           color = toyplot.color.brewer.map(\"Set3\"),\n",
    "           style={\"stroke-width\": 0})\n",
    "a.show = False\n",
    "\n",
    "## save figure\n",
    "import toyplot.svg\n",
    "toyplot.svg.render(c, \"figures/structure-final.svg\")\n",
    "c"
   ]
  }
 ],
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