tests/cookbook-structure-pedicularis.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Cookbook: Parallelized *STRUCTURE* analyses on unlinked SNPs\n",
    "\n",
    "As part of the `ipyrad.analysis` toolkit we've created convenience functions for easily distributing *STRUCTURE* analysis jobs on an HPC cluster, and for doing so in a programmatic and reproducible way. Importantly, *our workflow allows you to easily sample different distributions of unlinked SNPs among replicate analyses*, with the final inferred population structure summarized from a distribution of replicates. We also provide some simple examples of interactive plotting functions to make barplots. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Why structure?\n",
    "Although there are many newer and faster implementations of STRUCTURE, such as `faststructure` or `admixture`, the original structure works much better with missing data, which is of course a common feature of RAD-seq data sets. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### A note on Jupyter/IPython\n",
    "This is a Jupyter notebook, a reproducible and executable document. The code in this notebook is Python (2.7), and should be executed either in a jupyter-notebook, like this one, or in an IPython terminal. Execute each cell in order to reproduce our entire analysis. We make use of the `ipyparallel` Python library to distribute *STRUCTURE* jobs across processers in parallel ([more can be found about that here](http://nbviewer.jupyter.org/github/dereneaton/ipyrad/blob/master/tests/ipyparallel-tutorial.ipynb)). The example data set used in this analysis is from the [empirical example ipyrad tutorial](http://ipyrad.readthedocs.io/pedicularis_.html)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Required software\n",
    "You can easily install the required software for this notebook with a locally installed `conda` environment. Just run the commented code below in a terminal. If you are working on an HPC cluster you **do not need** administrator privileges to install the software in this way, since it is only installed locally."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "## conda install ipyrad -c ipyrad\n",
    "## conda install structure -c ipyrad\n",
    "## conda install clumpp -c ipyrad\n",
    "## conda install toytree -c eaton-lab"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import Python libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ipyrad.analysis as ipa      ## ipyrad analysis toolkit\n",
    "import ipyparallel as ipp          ## parallel processing\n",
    "import toyplot                     ## plotting library"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Parallel cluster setup\n",
    "Start an `ipcluster` instance in a separate terminal. An easy way to do this in a jupyter-notebook running on an HPC cluster is to go to your Jupyter dashboard, and click [new], and then [terminal], and run '`ipcluster start`' in that terminal. This will start a local cluster on the compute node you are connected to. See our [ipyparallel tutorial] (coming soon) for further details. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "##\n",
    "## ipcluster start --n=4\n",
    "##"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connected to 4 cores\n"
     ]
    }
   ],
   "source": [
    "## get parallel client\n",
    "ipyclient = ipp.Client()\n",
    "print \"Connected to {} cores\".format(len(ipyclient))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quick guide (tldr;)\n",
    "The following cell shows the quickest way to results. Further explanation of all of the features and options is provided further below. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "## set N values of K to test across\n",
    "kvalues = [2, 3, 4, 5, 6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "submitted 4 structure jobs [quick-K-2]\n",
      "submitted 4 structure jobs [quick-K-3]\n",
      "submitted 4 structure jobs [quick-K-4]\n",
      "submitted 4 structure jobs [quick-K-5]\n",
      "submitted 4 structure jobs [quick-K-6]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## init an analysis object\n",
    "s = ipa.structure(\n",
    "    name=\"quick\",\n",
    "    workdir=\"./analysis-structure\",\n",
    "    data=\"./analysis-ipyrad/pedic-full_outfiles/pedic-full.ustr\",\n",
    "    )\n",
    "\n",
    "## set main params (use much larger values in a real analysis)\n",
    "s.mainparams.burnin = 1000\n",
    "s.mainparams.numreps = 5000\n",
    "\n",
    "## submit N replicates of each test to run on parallel client\n",
    "for kpop in kvalues:\n",
    "    s.run(kpop=kpop, nreps=4, ipyclient=ipyclient)\n",
    "\n",
    "## wait for parallel jobs to finish\n",
    "ipyclient.wait()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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>4</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-337925.500</td>\n",
       "      <td>374729.242</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>67.961</td>\n",
       "      <td>-16777.575</td>\n",
       "      <td>4697.207</td>\n",
       "      <td>321147.925</td>\n",
       "      <td>319225.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>12.556</td>\n",
       "      <td>-14855.100</td>\n",
       "      <td>1505.766</td>\n",
       "      <td>1922.475</td>\n",
       "      <td>18906.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>4</td>\n",
       "      <td>9.997</td>\n",
       "      <td>-31838.875</td>\n",
       "      <td>35252.979</td>\n",
       "      <td>-16983.775</td>\n",
       "      <td>352432.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>4</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-401254.800</td>\n",
       "      <td>307272.233</td>\n",
       "      <td>-369415.925</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Nreps  deltaK  estLnProbMean  estLnProbStdev        lnPK      lnPPK\n",
       "2      4   0.000    -337925.500      374729.242       0.000       0.00\n",
       "3      4  67.961     -16777.575        4697.207  321147.925  319225.45\n",
       "4      4  12.556     -14855.100        1505.766    1922.475   18906.25\n",
       "5      4   9.997     -31838.875       35252.979  -16983.775  352432.15\n",
       "6      4   0.000    -401254.800      307272.233 -369415.925       0.00"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## return the evanno table (deltaK) for best K \n",
    "etable = s.get_evanno_table(kvalues)\n",
    "etable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "## get admixture proportion tables avg'd across reps\n",
    "tables = s.get_clumpp_table(kvalues, quiet=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## plot bars for a k-test in tables w/ hover labels\n",
    "table = tables[3].sort_values(by=[0, 1, 2])\n",
    "\n",
    "toyplot.bars(\n",
    "    table,\n",
    "    width=500, \n",
    "    height=200,\n",
    "    title=[[i] for i in table.index.tolist()],\n",
    "    xshow=False,\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Full guide"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Enter input and output file locations\n",
    "The `.str` file is a structure formatted file output by ipyrad. It includes all SNPs present in the data set. The `.snps.map` file is an optional file that maps which loci each SNP is from. If this file is used then each replicate analysis will *randomly* sample a single SNP from each locus in reach rep. The results from many reps therefore will represent variation across unlinked SNP data sets, as well as variation caused by uncertainty. The `workdir` is the location where you want output files to be written and will be created if it does not already exist. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "## the structure formatted file\n",
    "strfile = \"./analysis-ipyrad/pedic-full_outfiles/pedic-full.str\"\n",
    "\n",
    "## an optional mapfile, to sample unlinked SNPs\n",
    "mapfile = \"./analysis-ipyrad/pedic-full_outfiles/pedic-full.snps.map\"\n",
    "\n",
    "## the directory where outfiles should be written\n",
    "workdir = \"./analysis-structure/\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create a *Structure* Class object\n",
    "Structure is kind of an old fashioned program that requires creating quite a few input files to run, which makes it not very convenient to use in a programmatic and reproducible way. To work around this we've created a convenience wrapper object to make it easy to submit Structure jobs and to summarize their results. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "## create a Structure object\n",
    "struct = ipa.structure(name=\"structure-test\",\n",
    "                       data=strfile, \n",
    "                       mapfile=mapfile,\n",
    "                       workdir=workdir)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set parameter options for this object\n",
    "Our Structure object will be used to submit jobs to the cluster. It has associated with it a name, a set of input files, and a large number of parameter settings. You can modify the parameters by setting them like below. You can also use tab-completion to see all of the available options, or print them like below. See the [full structure docs here](https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=3&ved=0ahUKEwjt9tjpkszYAhWineAKHZ4-BxAQFgg4MAI&url=https%3A%2F%2Fwww.researchgate.net%2Ffile.PostFileLoader.html%3Fid%3D591c636cdc332d78a46a1948%26assetKey%3DAS%253A495017111953409%25401495032684846&usg=AOvVaw0WjG0uD0MXrs5ResMIHnik) for further details on the function of each parameter. In support of reproducibility, it is good practice to print both the mainparams and extraparams so it is clear which options you used. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "burnin             10000               \n",
      "extracols          0                   \n",
      "label              1                   \n",
      "locdata            0                   \n",
      "mapdistances       0                   \n",
      "markernames        0                   \n",
      "markovphase        0                   \n",
      "missing            -9                  \n",
      "notambiguous       -999                \n",
      "numreps            100000              \n",
      "onerowperind       0                   \n",
      "phased             0                   \n",
      "phaseinfo          0                   \n",
      "phenotype          0                   \n",
      "ploidy             2                   \n",
      "popdata            0                   \n",
      "popflag            0                   \n",
      "recessivealleles   0                   \n",
      "\n",
      "admburnin           500                 \n",
      "alpha               1.0                 \n",
      "alphamax            10.0                \n",
      "alphapriora         1.0                 \n",
      "alphapriorb         2.0                 \n",
      "alphapropsd         0.025               \n",
      "ancestdist          0                   \n",
      "ancestpint          0.9                 \n",
      "computeprob         1                   \n",
      "echodata            0                   \n",
      "fpriormean          0.01                \n",
      "fpriorsd            0.05                \n",
      "freqscorr           1                   \n",
      "gensback            2                   \n",
      "inferalpha          1                   \n",
      "inferlambda         0                   \n",
      "intermedsave        0                   \n",
      "lambda_             1.0                 \n",
      "linkage             0                   \n",
      "locispop            0                   \n",
      "locprior            0                   \n",
      "locpriorinit        1.0                 \n",
      "log10rmax           1.0                 \n",
      "log10rmin           -4.0                \n",
      "log10rpropsd        0.1                 \n",
      "log10rstart         -2.0                \n",
      "maxlocprior         20.0                \n",
      "metrofreq           10                  \n",
      "migrprior           0.01                \n",
      "noadmix             0                   \n",
      "numboxes            1000                \n",
      "onefst              0                   \n",
      "pfrompopflagonly    0                   \n",
      "popalphas           0                   \n",
      "popspecificlambda   0                   \n",
      "printlambda         1                   \n",
      "printlikes          0                   \n",
      "printnet            1                   \n",
      "printqhat           0                   \n",
      "printqsum           1                   \n",
      "randomize           0                   \n",
      "reporthitrate       0                   \n",
      "seed                12345               \n",
      "sitebysite          0                   \n",
      "startatpopinfo      0                   \n",
      "unifprioralpha      1                   \n",
      "updatefreq          10000               \n",
      "usepopinfo          0                   \n",
      "\n"
     ]
    }
   ],
   "source": [
    "## set mainparams for object\n",
    "struct.mainparams.burnin = 10000\n",
    "struct.mainparams.numreps = 100000\n",
    "\n",
    "## see all mainparams\n",
    "print struct.mainparams\n",
    "\n",
    "## see or set extraparams\n",
    "print struct.extraparams"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Submit jobs to run on the cluster\n",
    "The function `run()` distributes jobs to run on the cluster and load-balances the parallel workload. It takes a number of arguments. The first, `kpop`, is the number of populations. The second, `nreps`, is the number of replicated runs to perform. Each rep has a different random seed, and if you entered a mapfile for your Structure object then it will subsample unlinked snps independently in each replicate. The `seed` argument can be used to make the replicate analyses reproducible. The `extraparams.seed` parameter will be generated from this for each replicate. And finally, provide it the `ipyclient` object that we created above. The structure object will store an *asynchronous results object* for each job that is submitted so that we can query whether the jobs are finished yet or not. Using a simple for-loop we'll submit 20 replicate jobs to run at four different values of K. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "## a range of K-values to test\n",
    "tests = [3, 4, 5, 6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "submitted 20 structure jobs [structure-test-K-3]\n",
      "submitted 20 structure jobs [structure-test-K-4]\n",
      "submitted 20 structure jobs [structure-test-K-5]\n",
      "submitted 20 structure jobs [structure-test-K-6]\n"
     ]
    }
   ],
   "source": [
    "## submit batches of 20 replicate jobs for each value of K \n",
    "for kpop in tests:\n",
    "    struct.run(\n",
    "        kpop=kpop, \n",
    "        nreps=20, \n",
    "        seed=12345,\n",
    "        ipyclient=ipyclient,\n",
    "        )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Track progress until finished\n",
    "You can check for finished results by using the `get_clumpp_table()` function, which tries to summarize the finished results files. If no results are ready it will simply print a warning message telling you to wait. If you want the notebook to block/wait until all jobs are finished then execute the `wait()` function of the ipyclient object, like below. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<AsyncResult: _call_structure>,\n",
       " <AsyncResult: _call_structure>,\n",
       " <AsyncResult: _call_structure>,\n",
       " <AsyncResult: _call_structure>,\n",
       " <AsyncResult: _call_structure>,\n",
       " <AsyncResult: _call_structure>,\n",
       " <AsyncResult: _call_structure>,\n",
       " <AsyncResult: _call_structure>,\n",
       " <AsyncResult: _call_structure>,\n",
       " <AsyncResult: _call_structure>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## see submitted jobs (we query first 10 here)\n",
    "struct.asyncs[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "## query a specific job result by index\n",
    "if struct.asyncs[0].ready():\n",
    "    print struct.asyncs[0].result()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "## block/wait until all jobs finished\n",
    "ipyclient.wait() "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Summarize replicates with CLUMPP\n",
    "We ran 20 replicates per K-value hypothesis. We now need to concatenate and purmute those results so they can be summarized. For this we use the software clumpp. The default arguments to clumpp are generally good, but you can modify them the same as structure params, by accessing the `.clumppparams` attribute of your structure object. See the [clumpp documentation](https://web.stanford.edu/group/rosenberglab/software/CLUMPP_Manual.pdf) for more details. If you have a large number of samples (>50) you may wish to use the `largeKgreedy` algorithm (m=3) for faster runtimes. Below we run clumpp for each value of K that we ran structure on. You only need to tell the `get_clumpp_table()` function the value of K and it will find all of the result files given the Structure object's `name` and `workdir`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datatype                  0                   \n",
       "every_permfile            0                   \n",
       "greedy_option             2                   \n",
       "indfile                   0                   \n",
       "m                         3                   \n",
       "miscfile                  0                   \n",
       "order_by_run              1                   \n",
       "outfile                   0                   \n",
       "override_warnings         0                   \n",
       "permfile                  0                   \n",
       "permutationsfile          0                   \n",
       "permuted_datafile         0                   \n",
       "popfile                   0                   \n",
       "print_every_perm          0                   \n",
       "print_permuted_data       0                   \n",
       "print_random_inputorder   0                   \n",
       "random_inputorderfile     0                   \n",
       "repeats                   10000               \n",
       "s                         2                   \n",
       "w                         1                   "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## set some clumpp params\n",
    "struct.clumppparams.m = 3               ## use largegreedy algorithm\n",
    "struct.clumppparams.greedy_option = 2   ## test nrepeat possible orders\n",
    "struct.clumppparams.repeats = 10000     ## number of repeats\n",
    "struct.clumppparams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[K3] 20/20 results permuted across replicates (max_var=0).\n",
      "[K4] 20/20 results permuted across replicates (max_var=0).\n",
      "[K5] 20/20 results permuted across replicates (max_var=0).\n",
      "[K6] 20/20 results permuted across replicates (max_var=0).\n"
     ]
    }
   ],
   "source": [
    "## run clumpp for each value of K\n",
    "tables = struct.get_clumpp_table(tests)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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>3</th>\n",
       "      <td>20</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-146836.325</td>\n",
       "      <td>445572.806</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20</td>\n",
       "      <td>0.218</td>\n",
       "      <td>-151762.425</td>\n",
       "      <td>316342.669</td>\n",
       "      <td>-4926.100</td>\n",
       "      <td>69040.195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>20</td>\n",
       "      <td>0.288</td>\n",
       "      <td>-225728.720</td>\n",
       "      <td>242763.400</td>\n",
       "      <td>-73966.295</td>\n",
       "      <td>70036.825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>20</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-369731.840</td>\n",
       "      <td>300321.531</td>\n",
       "      <td>-144003.120</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Nreps  deltaK  estLnProbMean  estLnProbStdev        lnPK      lnPPK\n",
       "3     20   0.000    -146836.325      445572.806       0.000      0.000\n",
       "4     20   0.218    -151762.425      316342.669   -4926.100  69040.195\n",
       "5     20   0.288    -225728.720      242763.400  -73966.295  70036.825\n",
       "6     20   0.000    -369731.840      300321.531 -144003.120      0.000"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## return the evanno table w/ deltaK\n",
    "struct.get_evanno_table(tests)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sort the table order how you like it\n",
    "This can be useful if, for example, you want to order the names to be in the same order as tips on your phylogeny. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "custom ordering\n",
      "                          0      1          2      3\n",
      "32082_przewalskii       1.0  0.000  0.000e+00  0.000\n",
      "33588_przewalskii       1.0  0.000  0.000e+00  0.000\n",
      "41478_cyathophylloides  0.0  0.005  9.948e-01  0.000\n",
      "41954_cyathophylloides  0.0  0.005  9.948e-01  0.000\n",
      "29154_superba           0.0  0.019  6.731e-01  0.308\n",
      "30686_cyathophylla      0.0  0.020  6.820e-01  0.298\n",
      "33413_thamno            0.0  0.845  0.000e+00  0.155\n",
      "30556_thamno            0.0  0.892  7.000e-04  0.107\n",
      "35236_rex               0.0  0.908  1.000e-04  0.092\n",
      "40578_rex               0.0  0.989  2.000e-04  0.010\n",
      "35855_rex               0.0  0.990  0.000e+00  0.010\n",
      "39618_rex               0.0  1.000  0.000e+00  0.000\n",
      "38362_rex               0.0  1.000  0.000e+00  0.000\n"
     ]
    }
   ],
   "source": [
    "## custom sorting order\n",
    "myorder = [\n",
    "    \"32082_przewalskii\", \n",
    "    \"33588_przewalskii\",\n",
    "    \"41478_cyathophylloides\", \n",
    "    \"41954_cyathophylloides\", \n",
    "    \"29154_superba\",\n",
    "    \"30686_cyathophylla\", \n",
    "    \"33413_thamno\", \n",
    "    \"30556_thamno\", \n",
    "    \"35236_rex\", \n",
    "    \"40578_rex\", \n",
    "    \"35855_rex\",\n",
    "    \"39618_rex\", \n",
    "    \"38362_rex\",\n",
    "]\n",
    "\n",
    "print \"custom ordering\"\n",
    "print tables[4].ix[myorder]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### A function for adding an interactive hover to our plots\n",
    "The function automatically parses the table above for you. It can reorder the individuals based on their membership in each group, or based on an input list of ordered names. It returns the table of data as well as a list with information for making interactive hover boxes, which you can see below by hovering over the plots.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "def hover(table):\n",
    "    hover = []\n",
    "    for row in range(table.shape[0]):\n",
    "        stack = []\n",
    "        for col in range(table.shape[1]):\n",
    "            label = \"Name: {}\\nGroup: {}\\nProp: {}\"\\\n",
    "                .format(table.index[row], \n",
    "                        table.columns[col],\n",
    "                        table.ix[row, col])\n",
    "            stack.append(label)\n",
    "        hover.append(stack)\n",
    "    return list(hover)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize population structure in barplots \n",
    "Hover over the plot to see sample names and info in the hover box. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "Group: 0\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.07692307692308\" x=\"73.07692307692308\" y=\"150.0\"><title>Name: 33588_przewalskii\n",
       "Group: 0\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"2.109789021097896\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923066\" x=\"96.15384615384616\" y=\"147.8902109789021\"><title>Name: 41478_cyathophylloides\n",
       "Group: 0\n",
       "Prop: 0.0211</title></rect><rect class=\"toyplot-Datum\" height=\"2.109789021097896\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923094\" x=\"119.23076923076923\" y=\"147.8902109789021\"><title>Name: 41954_cyathophylloides\n",
       "Group: 0\n",
       "Prop: 0.0211</title></rect><rect class=\"toyplot-Datum\" height=\"5.5294470552944404\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923066\" x=\"142.30769230769232\" y=\"144.47055294470556\"><title>Name: 29154_superba\n",
       "Group: 0\n",
       "Prop: 0.0553</title></rect><rect class=\"toyplot-Datum\" height=\"5.5594440555944402\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923094\" x=\"165.38461538461539\" y=\"144.44055594440556\"><title>Name: 30686_cyathophylla\n",
       "Group: 0\n",
       "Prop: 0.0556</title></rect><rect class=\"toyplot-Datum\" height=\"99.550044995500457\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923038\" x=\"188.46153846153848\" y=\"50.44995500449955\"><title>Name: 33413_thamno\n",
       "Group: 0\n",
       "Prop: 0.9956</title></rect><rect class=\"toyplot-Datum\" height=\"99.730026997300271\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923094\" x=\"211.53846153846152\" y=\"50.269973002699729\"><title>Name: 30556_thamno\n",
       "Group: 0\n",
       "Prop: 0.9974</title></rect><rect class=\"toyplot-Datum\" height=\"99.780021997800219\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923066\" x=\"234.61538461538461\" y=\"50.219978002199781\"><title>Name: 35236_rex\n",
       "Group: 0\n",
       "Prop: 0.9979</title></rect><rect class=\"toyplot-Datum\" height=\"99.850014998500157\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923094\" x=\"257.69230769230768\" y=\"50.149985001499843\"><title>Name: 40578_rex\n",
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       "Prop: 0.9986</title></rect><rect class=\"toyplot-Datum\" height=\"99.870012998700133\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923038\" x=\"280.76923076923077\" y=\"50.129987001299874\"><title>Name: 35855_rex\n",
       "Group: 0\n",
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       "Group: 0\n",
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       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(98.8%,55.3%,38.4%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.07692307692308\" x=\"73.07692307692308\" y=\"150.0\"><title>Name: 33588_przewalskii\n",
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       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"97.880211978802123\" style=\"fill:rgb(98.8%,55.3%,38.4%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923066\" x=\"96.15384615384616\" y=\"50.009999000099988\"><title>Name: 41478_cyathophylloides\n",
       "Group: 1\n",
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       "Group: 1\n",
       "Prop: 0.9789</title></rect><rect class=\"toyplot-Datum\" height=\"94.47055294470556\" style=\"fill:rgb(98.8%,55.3%,38.4%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923066\" x=\"142.30769230769232\" y=\"50.0\"><title>Name: 29154_superba\n",
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       "                {\n",
       "                    var segment = projection[i];\n",
       "                    if(in_range(segment.range.bounds.min, range, segment.range.bounds.max))\n",
       "                    {\n",
       "                        if(segment.scale == \"linear\")\n",
       "                        {\n",
       "                            var amount = (range - segment.range.min) / (segment.range.max - segment.range.min);\n",
       "                            return mix(segment.domain.min, segment.domain.max, amount)\n",
       "                        }\n",
       "                        else if(segment.scale[0] == \"log\")\n",
       "                        {\n",
       "                            var amount = (range - segment.range.min) / (segment.range.max - segment.range.min);\n",
       "                            var base = segment.scale[1];\n",
       "                            return sign(segment.domain.min) * Math.pow(base, mix(log(segment.domain.min, base), log(segment.domain.max, base), amount));\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            var axes = {};\n",
       "\n",
       "            function display_coordinates(e)\n",
       "            {\n",
       "                var current = canvas.createSVGPoint();\n",
       "                current.x = e.clientX;\n",
       "                current.y = e.clientY;\n",
       "\n",
       "                for(var axis_id in axes)\n",
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       "                    var axis = document.querySelector(\"#\" + axis_id);\n",
       "                    var coordinates = axis.querySelector(\".toyplot-coordinates-Axis-coordinates\");\n",
       "                    if(coordinates)\n",
       "                    {\n",
       "                        var projection = axes[axis_id];\n",
       "                        var local = current.matrixTransform(axis.getScreenCTM().inverse());\n",
       "                        if(inside(local.x, projection))\n",
       "                        {\n",
       "                            var domain = to_domain(local.x, projection);\n",
       "                            coordinates.style.visibility = \"visible\";\n",
       "                            coordinates.setAttribute(\"transform\", \"translate(\" + local.x + \")\");\n",
       "                            var text = coordinates.querySelector(\"text\");\n",
       "                            text.textContent = domain.toFixed(2);\n",
       "                        }\n",
       "                        else\n",
       "                        {\n",
       "                            coordinates.style.visibility= \"hidden\";\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            canvas.addEventListener(\"click\", display_coordinates);\n",
       "\n",
       "            var module = {};\n",
       "            module.show_coordinates = function(axis_id, projection)\n",
       "            {\n",
       "                axes[axis_id] = projection;\n",
       "            }\n",
       "\n",
       "            return module;\n",
       "        })(modules[\"toyplot/canvas\"]);\n",
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       "        {\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\"],\"t4e32b6fc0f4045d0ba6239214f9779c2\",\"data\",\"bar data\",[\"left\", \"right\", \"baseline\", \"magnitude0\", \"magnitude1\", \"magnitude2\"],[[-0.5, 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5, 11.5], [0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5, 11.5, 12.5], [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, 0.0211, 0.0211, 0.0553, 0.0556, 0.9956, 0.9974, 0.9979, 0.9986, 0.9988, 1.0, 1.0], [0.0, 0.0, 0.9789, 0.9789, 0.9448, 0.9444, 0.0044, 0.0026, 0.0021, 0.0015, 0.0013, 0.0, 0.0], [1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]],\"toyplot\");\n",
       "(function(axis, axis_id, projection)\n",
       "        {\n",
       "            axis.show_coordinates(axis_id, projection);\n",
       "        })(modules[\"toyplot.coordinates.Axis\"],\"t428fc56b1955428192c10363d467f693\",[{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 1.0001, \"min\": 0.0}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 100.0, \"min\": 0.0}, \"scale\": \"linear\"}]);\n",
       "})();</script></div></div>"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(55.3%,62.7%,79.6%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923038\" x=\"326.92307692307696\" y=\"50.009999000099988\"><title>Name: 38362_rex\n",
       "Group: 2\n",
       "Prop: 0.0</title></rect></g><g class=\"toyplot-Series\"><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.07692307692308\" x=\"50.0\" y=\"50.009999000099988\"><title>Name: 32082_przewalskii\n",
       "Group: 3\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.07692307692308\" x=\"73.07692307692308\" y=\"50.009999000099988\"><title>Name: 33588_przewalskii\n",
       "Group: 3\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923066\" x=\"96.15384615384616\" y=\"50.009999000099988\"><title>Name: 41478_cyathophylloides\n",
       "Group: 3\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923094\" x=\"119.23076923076923\" y=\"50.009999000099988\"><title>Name: 41954_cyathophylloides\n",
       "Group: 3\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"30.836916308369169\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923066\" x=\"142.30769230769232\" y=\"50.0\"><title>Name: 29154_superba\n",
       "Group: 3\n",
       "Prop: 0.3084</title></rect><rect class=\"toyplot-Datum\" height=\"29.827017298270157\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923094\" x=\"165.38461538461539\" y=\"50.009999000099988\"><title>Name: 30686_cyathophylla\n",
       "Group: 3\n",
       "Prop: 0.2983</title></rect><rect class=\"toyplot-Datum\" height=\"15.458454154584537\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923038\" x=\"188.46153846153848\" y=\"50.009999000099988\"><title>Name: 33413_thamno\n",
       "Group: 3\n",
       "Prop: 0.1546</title></rect><rect class=\"toyplot-Datum\" height=\"10.708929107089283\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923094\" x=\"211.53846153846152\" y=\"50.009999000099988\"><title>Name: 30556_thamno\n",
       "Group: 3\n",
       "Prop: 0.1071</title></rect><rect class=\"toyplot-Datum\" height=\"9.1890810918908059\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923066\" x=\"234.61538461538461\" y=\"50.0\"><title>Name: 35236_rex\n",
       "Group: 3\n",
       "Prop: 0.0919</title></rect><rect class=\"toyplot-Datum\" height=\"1.0398960103989552\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923094\" x=\"257.69230769230768\" y=\"50.009999000100002\"><title>Name: 40578_rex\n",
       "Group: 3\n",
       "Prop: 0.0104</title></rect><rect class=\"toyplot-Datum\" height=\"0.98990100989901464\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923038\" x=\"280.76923076923077\" y=\"50.009999000099988\"><title>Name: 35855_rex\n",
       "Group: 3\n",
       "Prop: 0.0099</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923151\" x=\"303.84615384615381\" y=\"50.009999000099988\"><title>Name: 39618_rex\n",
       "Group: 3\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923038\" x=\"326.92307692307696\" y=\"50.009999000099988\"><title>Name: 38362_rex\n",
       "Group: 3\n",
       "Prop: 0.0</title></rect></g></g></g><g class=\"toyplot-coordinates-Axis\" id=\"t349ba3694d264b4ba05ccc3d3f73da4c\" transform=\"translate(50.0,150.0)rotate(-90.0)translate(0,-10.0)\"><line style=\"\" x1=\"0\" x2=\"100.0\" y1=\"0\" y2=\"0\"></line><g><g transform=\"translate(0.0,-6)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:10.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-6.95\" y=\"-4.4408920985e-16\">0.0</text></g><g transform=\"translate(49.99500049995,-6)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:10.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-6.95\" y=\"-4.4408920985e-16\">0.5</text></g><g transform=\"translate(99.9900009999,-6)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:10.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-6.95\" y=\"-4.4408920985e-16\">1.0</text></g></g><g class=\"toyplot-coordinates-Axis-coordinates\" style=\"visibility:hidden\" transform=\"\"><line style=\"stroke:rgb(43.9%,50.2%,56.5%);stroke-opacity:1.0;stroke-width:1.0\" x1=\"0\" x2=\"0\" y1=\"3.0\" y2=\"-4.5\"></line><text style=\"alignment-baseline:hanging;fill:rgb(43.9%,50.2%,56.5%);fill-opacity:1.0;font-size:10px;font-weight:normal;stroke:none;text-anchor:middle\" x=\"0\" y=\"6\"></text></g></g></g></svg><div class=\"toyplot-behavior\"><script>(function()\n",
       "{\n",
       "var modules={};\n",
       "modules[\"toyplot/tables\"] = (function()\n",
       "    {\n",
       "        var tables = [];\n",
       "\n",
       "        var module = {};\n",
       "\n",
       "        module.set = function(owner, key, names, columns)\n",
       "        {\n",
       "            tables.push({owner: owner, key: key, names: names, columns: columns});\n",
       "        }\n",
       "\n",
       "        module.get = function(owner, key)\n",
       "        {\n",
       "            for(var i = 0; i != tables.length; ++i)\n",
       "            {\n",
       "                var table = tables[i];\n",
       "                if(table.owner != owner)\n",
       "                    continue;\n",
       "                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",
       "                  {\n",
       "                    if(j)\n",
       "                      csv += \",\";\n",
       "                    csv += table.columns[j][i];\n",
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       "                  csv += \"\\n\";\n",
       "                }\n",
       "                return csv;\n",
       "            }\n",
       "        }\n",
       "\n",
       "        return module;\n",
       "    })();\n",
       "modules[\"toyplot/root/id\"] = \"t9a49e6d1d96e489ab11521a42a8251d7\";\n",
       "modules[\"toyplot/root\"] = (function(root_id)\n",
       "    {\n",
       "        return document.querySelector(\"#\" + root_id);\n",
       "    })(modules[\"toyplot/root/id\"]);\n",
       "modules[\"toyplot/canvas/id\"] = \"t2cb94b8db96b4194a733191f0a120ad8\";\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",
       "        {\n",
       "            var show_menu = false;\n",
       "            for(var index=0; index != items.length; ++index)\n",
       "            {\n",
       "                var item = items[index];\n",
       "                if(item.show(e))\n",
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       "                    item.item.style.display = \"block\";\n",
       "                    show_menu = true;\n",
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       "                {\n",
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       "\n",
       "            if(show_menu)\n",
       "            {\n",
       "                ignore_mouseup = true;\n",
       "                menu.style.left = (e.clientX + 1) + \"px\";\n",
       "                menu.style.top = (e.clientY - 5) + \"px\";\n",
       "                menu.style.visibility = \"visible\";\n",
       "                e.stopPropagation();\n",
       "                e.preventDefault();\n",
       "            }\n",
       "        }\n",
       "\n",
       "        function close_menu()\n",
       "        {\n",
       "            menu.style.visibility = \"hidden\";\n",
       "        }\n",
       "\n",
       "        function contextmenu(e)\n",
       "        {\n",
       "            open_menu(e);\n",
       "        }\n",
       "\n",
       "        function mousemove(e)\n",
       "        {\n",
       "            ignore_mouseup = false;\n",
       "        }\n",
       "\n",
       "        function mouseup(e)\n",
       "        {\n",
       "            if(ignore_mouseup)\n",
       "            {\n",
       "                ignore_mouseup = false;\n",
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       "            close_menu();\n",
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       "\n",
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       "            if(e.key == \"Escape\" || e.key == \"Esc\" || e.keyCode == 27)\n",
       "            {\n",
       "                close_menu();\n",
       "            }\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",
       "            }\n",
       "\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",
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       "            if(typeof link.download != \"undefined\")\n",
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       "              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",
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       "        return module;\n",
       "    })();\n",
       "modules[\"toyplot.coordinates.Axis\"] = (\n",
       "        function(canvas)\n",
       "        {\n",
       "            function sign(x)\n",
       "            {\n",
       "                return x < 0 ? -1 : x > 0 ? 1 : 0;\n",
       "            }\n",
       "\n",
       "            function mix(a, b, amount)\n",
       "            {\n",
       "                return ((1.0 - amount) * a) + (amount * b);\n",
       "            }\n",
       "\n",
       "            function log(x, base)\n",
       "            {\n",
       "                return Math.log(Math.abs(x)) / Math.log(base);\n",
       "            }\n",
       "\n",
       "            function in_range(a, x, b)\n",
       "            {\n",
       "                var left = Math.min(a, b);\n",
       "                var right = Math.max(a, b);\n",
       "                return left <= x && x <= right;\n",
       "            }\n",
       "\n",
       "            function inside(range, projection)\n",
       "            {\n",
       "                for(var i = 0; i != projection.length; ++i)\n",
       "                {\n",
       "                    var segment = projection[i];\n",
       "                    if(in_range(segment.range.min, range, segment.range.max))\n",
       "                        return true;\n",
       "                }\n",
       "                return false;\n",
       "            }\n",
       "\n",
       "            function to_domain(range, projection)\n",
       "            {\n",
       "                for(var i = 0; i != projection.length; ++i)\n",
       "                {\n",
       "                    var segment = projection[i];\n",
       "                    if(in_range(segment.range.bounds.min, range, segment.range.bounds.max))\n",
       "                    {\n",
       "                        if(segment.scale == \"linear\")\n",
       "                        {\n",
       "                            var amount = (range - segment.range.min) / (segment.range.max - segment.range.min);\n",
       "                            return mix(segment.domain.min, segment.domain.max, amount)\n",
       "                        }\n",
       "                        else if(segment.scale[0] == \"log\")\n",
       "                        {\n",
       "                            var amount = (range - segment.range.min) / (segment.range.max - segment.range.min);\n",
       "                            var base = segment.scale[1];\n",
       "                            return sign(segment.domain.min) * Math.pow(base, mix(log(segment.domain.min, base), log(segment.domain.max, base), amount));\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            var axes = {};\n",
       "\n",
       "            function display_coordinates(e)\n",
       "            {\n",
       "                var current = canvas.createSVGPoint();\n",
       "                current.x = e.clientX;\n",
       "                current.y = e.clientY;\n",
       "\n",
       "                for(var axis_id in axes)\n",
       "                {\n",
       "                    var axis = document.querySelector(\"#\" + axis_id);\n",
       "                    var coordinates = axis.querySelector(\".toyplot-coordinates-Axis-coordinates\");\n",
       "                    if(coordinates)\n",
       "                    {\n",
       "                        var projection = axes[axis_id];\n",
       "                        var local = current.matrixTransform(axis.getScreenCTM().inverse());\n",
       "                        if(inside(local.x, projection))\n",
       "                        {\n",
       "                            var domain = to_domain(local.x, projection);\n",
       "                            coordinates.style.visibility = \"visible\";\n",
       "                            coordinates.setAttribute(\"transform\", \"translate(\" + local.x + \")\");\n",
       "                            var text = coordinates.querySelector(\"text\");\n",
       "                            text.textContent = domain.toFixed(2);\n",
       "                        }\n",
       "                        else\n",
       "                        {\n",
       "                            coordinates.style.visibility= \"hidden\";\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            canvas.addEventListener(\"click\", display_coordinates);\n",
       "\n",
       "            var module = {};\n",
       "            module.show_coordinates = function(axis_id, projection)\n",
       "            {\n",
       "                axes[axis_id] = projection;\n",
       "            }\n",
       "\n",
       "            return module;\n",
       "        })(modules[\"toyplot/canvas\"]);\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\"],\"tb3a43e5fbe0e41b2b62f4ea527139702\",\"data\",\"bar data\",[\"left\", \"right\", \"baseline\", \"magnitude0\", \"magnitude1\", \"magnitude2\", \"magnitude3\"],[[-0.5, 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5, 11.5], [0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5, 11.5, 12.5], [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], [1.0, 1.0, 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, 0.0052, 0.0052, 0.0186, 0.0197, 0.8454, 0.8922, 0.9081, 0.9894, 0.9901, 1.0, 1.0], [0.0, 0.0, 0.9948, 0.9948, 0.6731, 0.682, 0.0, 0.0007, 0.0001, 0.0002, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.3084, 0.2983, 0.1546, 0.1071, 0.0919, 0.0104, 0.0099, 0.0, 0.0]],\"toyplot\");\n",
       "(function(axis, axis_id, projection)\n",
       "        {\n",
       "            axis.show_coordinates(axis_id, projection);\n",
       "        })(modules[\"toyplot.coordinates.Axis\"],\"t349ba3694d264b4ba05ccc3d3f73da4c\",[{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 1.0001, \"min\": 0.0}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 100.0, \"min\": 0.0}, \"scale\": \"linear\"}]);\n",
       "})();</script></div></div>"
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       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923151\" x=\"303.84615384615381\" y=\"50.009999000099988\"><title>Name: 39618_rex\n",
       "Group: 3\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923038\" x=\"326.92307692307696\" y=\"50.009999000099988\"><title>Name: 38362_rex\n",
       "Group: 3\n",
       "Prop: 0.0</title></rect></g><g class=\"toyplot-Series\"><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.07692307692308\" x=\"50.0\" y=\"50.009999000099988\"><title>Name: 32082_przewalskii\n",
       "Group: 4\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.07692307692308\" x=\"73.07692307692308\" y=\"50.009999000099988\"><title>Name: 33588_przewalskii\n",
       "Group: 4\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923066\" x=\"96.15384615384616\" y=\"50.009999000099988\"><title>Name: 41478_cyathophylloides\n",
       "Group: 4\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923094\" x=\"119.23076923076923\" y=\"50.009999000099988\"><title>Name: 41954_cyathophylloides\n",
       "Group: 4\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.079992000799926188\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923066\" x=\"142.30769230769232\" y=\"50.009999000099988\"><title>Name: 29154_superba\n",
       "Group: 4\n",
       "Prop: 0.0008</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923094\" x=\"165.38461538461539\" y=\"50.009999000099988\"><title>Name: 30686_cyathophylla\n",
       "Group: 4\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"28.467153284671546\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923038\" x=\"188.46153846153848\" y=\"50.009999000099988\"><title>Name: 33413_thamno\n",
       "Group: 4\n",
       "Prop: 0.2847</title></rect><rect class=\"toyplot-Datum\" height=\"19.228077192280772\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923094\" x=\"211.53846153846152\" y=\"50.009999000099988\"><title>Name: 30556_thamno\n",
       "Group: 4\n",
       "Prop: 0.1923</title></rect><rect class=\"toyplot-Datum\" height=\"13.578642135786417\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923066\" x=\"234.61538461538461\" y=\"50.009999000099988\"><title>Name: 35236_rex\n",
       "Group: 4\n",
       "Prop: 0.1358</title></rect><rect class=\"toyplot-Datum\" height=\"2.0297970202979627\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923094\" x=\"257.69230769230768\" y=\"50.0\"><title>Name: 40578_rex\n",
       "Group: 4\n",
       "Prop: 0.0203</title></rect><rect class=\"toyplot-Datum\" height=\"2.0897910208979198\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923038\" x=\"280.76923076923077\" y=\"50.009999000099988\"><title>Name: 35855_rex\n",
       "Group: 4\n",
       "Prop: 0.0209</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923151\" x=\"303.84615384615381\" y=\"50.009999000099988\"><title>Name: 39618_rex\n",
       "Group: 4\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923038\" x=\"326.92307692307696\" y=\"50.009999000099988\"><title>Name: 38362_rex\n",
       "Group: 4\n",
       "Prop: 0.0</title></rect></g></g></g><g class=\"toyplot-coordinates-Axis\" id=\"t6f0a3e10be0345afb053764015d8ca6a\" transform=\"translate(50.0,150.0)rotate(-90.0)translate(0,-10.0)\"><line style=\"\" x1=\"0\" x2=\"100.0\" y1=\"0\" y2=\"0\"></line><g><g transform=\"translate(0.0,-6)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:10.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-6.95\" y=\"-4.4408920985e-16\">0.0</text></g><g transform=\"translate(49.99500049995,-6)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:10.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-6.95\" y=\"-4.4408920985e-16\">0.5</text></g><g transform=\"translate(99.9900009999,-6)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:10.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-6.95\" y=\"-4.4408920985e-16\">1.0</text></g></g><g class=\"toyplot-coordinates-Axis-coordinates\" style=\"visibility:hidden\" transform=\"\"><line style=\"stroke:rgb(43.9%,50.2%,56.5%);stroke-opacity:1.0;stroke-width:1.0\" x1=\"0\" x2=\"0\" y1=\"3.0\" y2=\"-4.5\"></line><text style=\"alignment-baseline:hanging;fill:rgb(43.9%,50.2%,56.5%);fill-opacity:1.0;font-size:10px;font-weight:normal;stroke:none;text-anchor:middle\" x=\"0\" y=\"6\"></text></g></g></g></svg><div class=\"toyplot-behavior\"><script>(function()\n",
       "{\n",
       "var modules={};\n",
       "modules[\"toyplot/tables\"] = (function()\n",
       "    {\n",
       "        var tables = [];\n",
       "\n",
       "        var module = {};\n",
       "\n",
       "        module.set = function(owner, key, names, columns)\n",
       "        {\n",
       "            tables.push({owner: owner, key: key, names: names, columns: columns});\n",
       "        }\n",
       "\n",
       "        module.get = function(owner, key)\n",
       "        {\n",
       "            for(var i = 0; i != tables.length; ++i)\n",
       "            {\n",
       "                var table = tables[i];\n",
       "                if(table.owner != owner)\n",
       "                    continue;\n",
       "                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",
       "                  {\n",
       "                    if(j)\n",
       "                      csv += \",\";\n",
       "                    csv += table.columns[j][i];\n",
       "                  }\n",
       "                  csv += \"\\n\";\n",
       "                }\n",
       "                return csv;\n",
       "            }\n",
       "        }\n",
       "\n",
       "        return module;\n",
       "    })();\n",
       "modules[\"toyplot/root/id\"] = \"te1ed9615c428472497a0b3851e126af3\";\n",
       "modules[\"toyplot/root\"] = (function(root_id)\n",
       "    {\n",
       "        return document.querySelector(\"#\" + root_id);\n",
       "    })(modules[\"toyplot/root/id\"]);\n",
       "modules[\"toyplot/canvas/id\"] = \"t539cad6f025747beb978f8db8ac1e763\";\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",
       "        {\n",
       "            var show_menu = false;\n",
       "            for(var index=0; index != items.length; ++index)\n",
       "            {\n",
       "                var item = items[index];\n",
       "                if(item.show(e))\n",
       "                {\n",
       "                    item.item.style.display = \"block\";\n",
       "                    show_menu = true;\n",
       "                }\n",
       "                else\n",
       "                {\n",
       "                    item.item.style.display = \"none\";\n",
       "                }\n",
       "            }\n",
       "\n",
       "            if(show_menu)\n",
       "            {\n",
       "                ignore_mouseup = true;\n",
       "                menu.style.left = (e.clientX + 1) + \"px\";\n",
       "                menu.style.top = (e.clientY - 5) + \"px\";\n",
       "                menu.style.visibility = \"visible\";\n",
       "                e.stopPropagation();\n",
       "                e.preventDefault();\n",
       "            }\n",
       "        }\n",
       "\n",
       "        function close_menu()\n",
       "        {\n",
       "            menu.style.visibility = \"hidden\";\n",
       "        }\n",
       "\n",
       "        function contextmenu(e)\n",
       "        {\n",
       "            open_menu(e);\n",
       "        }\n",
       "\n",
       "        function mousemove(e)\n",
       "        {\n",
       "            ignore_mouseup = false;\n",
       "        }\n",
       "\n",
       "        function mouseup(e)\n",
       "        {\n",
       "            if(ignore_mouseup)\n",
       "            {\n",
       "                ignore_mouseup = false;\n",
       "                return;\n",
       "            }\n",
       "            close_menu();\n",
       "        }\n",
       "\n",
       "        function keydown(e)\n",
       "        {\n",
       "            if(e.key == \"Escape\" || e.key == \"Esc\" || e.keyCode == 27)\n",
       "            {\n",
       "                close_menu();\n",
       "            }\n",
       "        }\n",
       "\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",
       "            }\n",
       "\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",
       "modules[\"toyplot.coordinates.Axis\"] = (\n",
       "        function(canvas)\n",
       "        {\n",
       "            function sign(x)\n",
       "            {\n",
       "                return x < 0 ? -1 : x > 0 ? 1 : 0;\n",
       "            }\n",
       "\n",
       "            function mix(a, b, amount)\n",
       "            {\n",
       "                return ((1.0 - amount) * a) + (amount * b);\n",
       "            }\n",
       "\n",
       "            function log(x, base)\n",
       "            {\n",
       "                return Math.log(Math.abs(x)) / Math.log(base);\n",
       "            }\n",
       "\n",
       "            function in_range(a, x, b)\n",
       "            {\n",
       "                var left = Math.min(a, b);\n",
       "                var right = Math.max(a, b);\n",
       "                return left <= x && x <= right;\n",
       "            }\n",
       "\n",
       "            function inside(range, projection)\n",
       "            {\n",
       "                for(var i = 0; i != projection.length; ++i)\n",
       "                {\n",
       "                    var segment = projection[i];\n",
       "                    if(in_range(segment.range.min, range, segment.range.max))\n",
       "                        return true;\n",
       "                }\n",
       "                return false;\n",
       "            }\n",
       "\n",
       "            function to_domain(range, projection)\n",
       "            {\n",
       "                for(var i = 0; i != projection.length; ++i)\n",
       "                {\n",
       "                    var segment = projection[i];\n",
       "                    if(in_range(segment.range.bounds.min, range, segment.range.bounds.max))\n",
       "                    {\n",
       "                        if(segment.scale == \"linear\")\n",
       "                        {\n",
       "                            var amount = (range - segment.range.min) / (segment.range.max - segment.range.min);\n",
       "                            return mix(segment.domain.min, segment.domain.max, amount)\n",
       "                        }\n",
       "                        else if(segment.scale[0] == \"log\")\n",
       "                        {\n",
       "                            var amount = (range - segment.range.min) / (segment.range.max - segment.range.min);\n",
       "                            var base = segment.scale[1];\n",
       "                            return sign(segment.domain.min) * Math.pow(base, mix(log(segment.domain.min, base), log(segment.domain.max, base), amount));\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            var axes = {};\n",
       "\n",
       "            function display_coordinates(e)\n",
       "            {\n",
       "                var current = canvas.createSVGPoint();\n",
       "                current.x = e.clientX;\n",
       "                current.y = e.clientY;\n",
       "\n",
       "                for(var axis_id in axes)\n",
       "                {\n",
       "                    var axis = document.querySelector(\"#\" + axis_id);\n",
       "                    var coordinates = axis.querySelector(\".toyplot-coordinates-Axis-coordinates\");\n",
       "                    if(coordinates)\n",
       "                    {\n",
       "                        var projection = axes[axis_id];\n",
       "                        var local = current.matrixTransform(axis.getScreenCTM().inverse());\n",
       "                        if(inside(local.x, projection))\n",
       "                        {\n",
       "                            var domain = to_domain(local.x, projection);\n",
       "                            coordinates.style.visibility = \"visible\";\n",
       "                            coordinates.setAttribute(\"transform\", \"translate(\" + local.x + \")\");\n",
       "                            var text = coordinates.querySelector(\"text\");\n",
       "                            text.textContent = domain.toFixed(2);\n",
       "                        }\n",
       "                        else\n",
       "                        {\n",
       "                            coordinates.style.visibility= \"hidden\";\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            canvas.addEventListener(\"click\", display_coordinates);\n",
       "\n",
       "            var module = {};\n",
       "            module.show_coordinates = function(axis_id, projection)\n",
       "            {\n",
       "                axes[axis_id] = projection;\n",
       "            }\n",
       "\n",
       "            return module;\n",
       "        })(modules[\"toyplot/canvas\"]);\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\"],\"t3473a7cb22f44a1f9c3ee2248acc07cc\",\"data\",\"bar data\",[\"left\", \"right\", \"baseline\", \"magnitude0\", \"magnitude1\", \"magnitude2\", \"magnitude3\", \"magnitude4\"],[[-0.5, 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5, 11.5], [0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5, 11.5, 12.5], [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, 0.0263, 0.0346, 0.7078, 0.7924, 0.8263, 0.9469, 0.9486, 1.0, 1.0], [0.0, 0.0, 0.0, 0.0, 0.4769, 0.4415, 0.0075, 0.0153, 0.0379, 0.0329, 0.0305, 0.0, 0.0], [1.0, 1.0, 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, 1.0, 1.0, 0.496, 0.5239, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0008, 0.0, 0.2847, 0.1923, 0.1358, 0.0203, 0.0209, 0.0, 0.0]],\"toyplot\");\n",
       "(function(axis, axis_id, projection)\n",
       "        {\n",
       "            axis.show_coordinates(axis_id, projection);\n",
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       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923038\" x=\"280.76923076923077\" y=\"66.08839116088393\"><title>Name: 35855_rex\n",
       "Group: 3\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923151\" x=\"303.84615384615381\" y=\"50.009999000099988\"><title>Name: 39618_rex\n",
       "Group: 3\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(90.6%,54.1%,76.5%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923038\" x=\"326.92307692307696\" y=\"50.009999000099988\"><title>Name: 38362_rex\n",
       "Group: 3\n",
       "Prop: 0.0</title></rect></g><g class=\"toyplot-Series\"><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.07692307692308\" x=\"50.0\" y=\"50.009999000099988\"><title>Name: 32082_przewalskii\n",
       "Group: 4\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.07692307692308\" x=\"73.07692307692308\" y=\"50.009999000099988\"><title>Name: 33588_przewalskii\n",
       "Group: 4\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923066\" x=\"96.15384615384616\" y=\"150.0\"><title>Name: 41478_cyathophylloides\n",
       "Group: 4\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923094\" x=\"119.23076923076923\" y=\"150.0\"><title>Name: 41954_cyathophylloides\n",
       "Group: 4\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.089991000899885876\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923066\" x=\"142.30769230769232\" y=\"101.62483751624839\"><title>Name: 29154_superba\n",
       "Group: 4\n",
       "Prop: 0.0009</title></rect><rect class=\"toyplot-Datum\" height=\"0.099990000999895301\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923094\" x=\"165.38461538461539\" y=\"104.28457154284571\"><title>Name: 30686_cyathophylla\n",
       "Group: 4\n",
       "Prop: 0.001</title></rect><rect class=\"toyplot-Datum\" height=\"0.30996900309968112\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923038\" x=\"188.46153846153848\" y=\"50.019998000199998\"><title>Name: 33413_thamno\n",
       "Group: 4\n",
       "Prop: 0.0031</title></rect><rect class=\"toyplot-Datum\" height=\"8.0791920807919269\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923094\" x=\"211.53846153846152\" y=\"50.0\"><title>Name: 30556_thamno\n",
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       "Prop: 0.0808</title></rect><rect class=\"toyplot-Datum\" height=\"14.42855714428557\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923066\" x=\"234.61538461538461\" y=\"50.009999000099988\"><title>Name: 35236_rex\n",
       "Group: 4\n",
       "Prop: 0.1443</title></rect><rect class=\"toyplot-Datum\" height=\"16.558344165583442\" style=\"fill:rgb(65.1%,84.7%,32.9%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:1.0\" width=\"23.076923076923094\" x=\"257.69230769230768\" y=\"50.009999000099988\"><title>Name: 40578_rex\n",
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       "Group: 5\n",
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       "            function in_range(a, x, b)\n",
       "            {\n",
       "                var left = Math.min(a, b);\n",
       "                var right = Math.max(a, b);\n",
       "                return left <= x && x <= right;\n",
       "            }\n",
       "\n",
       "            function inside(range, projection)\n",
       "            {\n",
       "                for(var i = 0; i != projection.length; ++i)\n",
       "                {\n",
       "                    var segment = projection[i];\n",
       "                    if(in_range(segment.range.min, range, segment.range.max))\n",
       "                        return true;\n",
       "                }\n",
       "                return false;\n",
       "            }\n",
       "\n",
       "            function to_domain(range, projection)\n",
       "            {\n",
       "                for(var i = 0; i != projection.length; ++i)\n",
       "                {\n",
       "                    var segment = projection[i];\n",
       "                    if(in_range(segment.range.bounds.min, range, segment.range.bounds.max))\n",
       "                    {\n",
       "                        if(segment.scale == \"linear\")\n",
       "                        {\n",
       "                            var amount = (range - segment.range.min) / (segment.range.max - segment.range.min);\n",
       "                            return mix(segment.domain.min, segment.domain.max, amount)\n",
       "                        }\n",
       "                        else if(segment.scale[0] == \"log\")\n",
       "                        {\n",
       "                            var amount = (range - segment.range.min) / (segment.range.max - segment.range.min);\n",
       "                            var base = segment.scale[1];\n",
       "                            return sign(segment.domain.min) * Math.pow(base, mix(log(segment.domain.min, base), log(segment.domain.max, base), amount));\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            var axes = {};\n",
       "\n",
       "            function display_coordinates(e)\n",
       "            {\n",
       "                var current = canvas.createSVGPoint();\n",
       "                current.x = e.clientX;\n",
       "                current.y = e.clientY;\n",
       "\n",
       "                for(var axis_id in axes)\n",
       "                {\n",
       "                    var axis = document.querySelector(\"#\" + axis_id);\n",
       "                    var coordinates = axis.querySelector(\".toyplot-coordinates-Axis-coordinates\");\n",
       "                    if(coordinates)\n",
       "                    {\n",
       "                        var projection = axes[axis_id];\n",
       "                        var local = current.matrixTransform(axis.getScreenCTM().inverse());\n",
       "                        if(inside(local.x, projection))\n",
       "                        {\n",
       "                            var domain = to_domain(local.x, projection);\n",
       "                            coordinates.style.visibility = \"visible\";\n",
       "                            coordinates.setAttribute(\"transform\", \"translate(\" + local.x + \")\");\n",
       "                            var text = coordinates.querySelector(\"text\");\n",
       "                            text.textContent = domain.toFixed(2);\n",
       "                        }\n",
       "                        else\n",
       "                        {\n",
       "                            coordinates.style.visibility= \"hidden\";\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            canvas.addEventListener(\"click\", display_coordinates);\n",
       "\n",
       "            var module = {};\n",
       "            module.show_coordinates = function(axis_id, projection)\n",
       "            {\n",
       "                axes[axis_id] = projection;\n",
       "            }\n",
       "\n",
       "            return module;\n",
       "        })(modules[\"toyplot/canvas\"]);\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\"],\"ta251e63de1b74925a41bb55a7e15d9af\",\"data\",\"bar data\",[\"left\", \"right\", \"baseline\", \"magnitude0\", \"magnitude1\", \"magnitude2\", \"magnitude3\", \"magnitude4\", \"magnitude5\"],[[-0.5, 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5, 11.5], [0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5, 11.5, 12.5], [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, 0.4604, 0.4249, 0.0015, 0.0039, 0.0289, 0.0024, 0.003, 0.0001, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0225, 0.0313, 0.647, 0.7293, 0.7636, 0.81, 0.8138, 0.9999, 1.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.3483, 0.1861, 0.0632, 0.022, 0.0224, 0.0, 0.0], [1.0, 1.0, 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, 0.0009, 0.001, 0.0031, 0.0808, 0.1443, 0.1656, 0.1609, 0.0, 0.0], [0.0, 0.0, 1.0, 1.0, 0.5162, 0.5428, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]],\"toyplot\");\n",
       "(function(axis, axis_id, projection)\n",
       "        {\n",
       "            axis.show_coordinates(axis_id, projection);\n",
       "        })(modules[\"toyplot.coordinates.Axis\"],\"tef9686a78d9749138c3414927e83054c\",[{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 1.0001, \"min\": 0.0}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 100.0, \"min\": 0.0}, \"scale\": \"linear\"}]);\n",
       "})();</script></div></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for kpop in tests:\n",
    "    ## parse outfile to a table and re-order it\n",
    "    table = tables[kpop]\n",
    "    table = table.ix[myorder]\n",
    "    \n",
    "    ## plot barplot w/ hover\n",
    "    canvas, axes, mark = toyplot.bars(\n",
    "                            table, \n",
    "                            title=hover(table),\n",
    "                            width=400, \n",
    "                            height=200, \n",
    "                            xshow=False,                            \n",
    "                            style={\"stroke\": toyplot.color.near_black},\n",
    "                            )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Make a slightly fancier plot and save to file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "mean scores across 20 replicates.\n"
     ]
    }
   ],
   "source": [
    "## save plots for your favorite value of K\n",
    "table = struct.get_clumpp_table(kpop=3)\n",
    "table = table.ix[myorder]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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UZTjBQgghhBDqMpxgIYQQQgh1GU6wEEIIIYS6DCdYCCGEEEJdhhMshBBCCKEuwwkWQggh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\nMPuN+OnZW/NP12r1i7Qu1jE/z481LOu1mdytp7z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       "Prop: 0.0211</title></rect><rect class=\"toyplot-Datum\" height=\"2.1097890210978818\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461547\" x=\"154.61538461538461\" y=\"110.39021097890212\"><title>Name: 41954_cyathophylloides\n",
       "Group: 0\n",
       "Prop: 0.0211</title></rect><rect class=\"toyplot-Datum\" height=\"5.5294470552944688\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461547\" x=\"196.15384615384616\" y=\"106.97055294470553\"><title>Name: 29154_superba\n",
       "Group: 0\n",
       "Prop: 0.0553</title></rect><rect class=\"toyplot-Datum\" height=\"5.5594440555944402\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461519\" x=\"237.69230769230771\" y=\"106.94055594440556\"><title>Name: 30686_cyathophylla\n",
       "Group: 0\n",
       "Prop: 0.0556</title></rect><rect class=\"toyplot-Datum\" height=\"99.550044995500457\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461547\" x=\"279.23076923076923\" y=\"12.949955004499547\"><title>Name: 33413_thamno\n",
       "Group: 0\n",
       "Prop: 0.9956</title></rect><rect class=\"toyplot-Datum\" height=\"99.730026997300271\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461547\" x=\"320.76923076923077\" y=\"12.76997300269973\"><title>Name: 30556_thamno\n",
       "Group: 0\n",
       "Prop: 0.9974</title></rect><rect class=\"toyplot-Datum\" height=\"99.780021997800219\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.53846153846149\" x=\"362.30769230769232\" y=\"12.719978002199783\"><title>Name: 35236_rex\n",
       "Group: 0\n",
       "Prop: 0.9979</title></rect><rect class=\"toyplot-Datum\" height=\"99.850014998500157\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461604\" x=\"403.84615384615381\" y=\"12.649985001499841\"><title>Name: 40578_rex\n",
       "Group: 0\n",
       "Prop: 0.9986</title></rect><rect class=\"toyplot-Datum\" height=\"99.870012998700133\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461547\" x=\"445.38461538461542\" y=\"12.62998700129987\"><title>Name: 35855_rex\n",
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       "Prop: 0.9988</title></rect><rect class=\"toyplot-Datum\" height=\"99.990000999900005\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.53846153846149\" x=\"486.92307692307696\" y=\"12.509999000099992\"><title>Name: 39618_rex\n",
       "Group: 0\n",
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       "Group: 0\n",
       "Prop: 1.0</title></rect></g><g class=\"toyplot-Series\"><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(98.8%,55.3%,38.4%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461547\" x=\"30.0\" y=\"112.5\"><title>Name: 32082_przewalskii\n",
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       "Group: 1\n",
       "Prop: 0.9789</title></rect><rect class=\"toyplot-Datum\" height=\"94.470552944705531\" style=\"fill:rgb(98.8%,55.3%,38.4%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461547\" x=\"196.15384615384616\" y=\"12.5\"><title>Name: 29154_superba\n",
       "Group: 1\n",
       "Prop: 0.9448</title></rect><rect class=\"toyplot-Datum\" height=\"94.430556944305565\" style=\"fill:rgb(98.8%,55.3%,38.4%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461519\" x=\"237.69230769230771\" y=\"12.509999000099992\"><title>Name: 30686_cyathophylla\n",
       "Group: 1\n",
       "Prop: 0.9444</title></rect><rect class=\"toyplot-Datum\" height=\"0.43995600439955496\" style=\"fill:rgb(98.8%,55.3%,38.4%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461547\" x=\"279.23076923076923\" y=\"12.509999000099992\"><title>Name: 33413_thamno\n",
       "Group: 1\n",
       "Prop: 0.0044</title></rect><rect class=\"toyplot-Datum\" height=\"0.2599740025997388\" style=\"fill:rgb(98.8%,55.3%,38.4%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461547\" x=\"320.76923076923077\" y=\"12.509999000099992\"><title>Name: 30556_thamno\n",
       "Group: 1\n",
       "Prop: 0.0026</title></rect><rect class=\"toyplot-Datum\" height=\"0.20997900209979115\" style=\"fill:rgb(98.8%,55.3%,38.4%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.53846153846149\" x=\"362.30769230769232\" y=\"12.509999000099992\"><title>Name: 35236_rex\n",
       "Group: 1\n",
       "Prop: 0.0021</title></rect><rect class=\"toyplot-Datum\" height=\"0.14998500149984118\" style=\"fill:rgb(98.8%,55.3%,38.4%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461604\" x=\"403.84615384615381\" y=\"12.5\"><title>Name: 40578_rex\n",
       "Group: 1\n",
       "Prop: 0.0015</title></rect><rect class=\"toyplot-Datum\" height=\"0.12998700129987029\" style=\"fill:rgb(98.8%,55.3%,38.4%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461547\" x=\"445.38461538461542\" y=\"12.5\"><title>Name: 35855_rex\n",
       "Group: 1\n",
       "Prop: 0.0013</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(98.8%,55.3%,38.4%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.53846153846149\" x=\"486.92307692307696\" y=\"12.509999000099992\"><title>Name: 39618_rex\n",
       "Group: 1\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(98.8%,55.3%,38.4%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461547\" x=\"528.46153846153845\" y=\"12.509999000099992\"><title>Name: 38362_rex\n",
       "Group: 1\n",
       "Prop: 0.0</title></rect></g><g class=\"toyplot-Series\"><rect class=\"toyplot-Datum\" height=\"99.990000999900005\" style=\"fill:rgb(55.3%,62.7%,79.6%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461547\" x=\"30.0\" y=\"12.509999000099992\"><title>Name: 32082_przewalskii\n",
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       "Prop: 1.0</title></rect><rect class=\"toyplot-Datum\" height=\"99.990000999900005\" style=\"fill:rgb(55.3%,62.7%,79.6%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461533\" x=\"71.538461538461547\" y=\"12.509999000099992\"><title>Name: 33588_przewalskii\n",
       "Group: 2\n",
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       "Group: 2\n",
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       "Group: 2\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(55.3%,62.7%,79.6%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461547\" x=\"196.15384615384616\" y=\"12.5\"><title>Name: 29154_superba\n",
       "Group: 2\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(55.3%,62.7%,79.6%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461519\" x=\"237.69230769230771\" y=\"12.509999000099992\"><title>Name: 30686_cyathophylla\n",
       "Group: 2\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(55.3%,62.7%,79.6%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461547\" x=\"279.23076923076923\" y=\"12.509999000099992\"><title>Name: 33413_thamno\n",
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       "Group: 2\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(55.3%,62.7%,79.6%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461547\" x=\"445.38461538461542\" y=\"12.5\"><title>Name: 35855_rex\n",
       "Group: 2\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(55.3%,62.7%,79.6%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.53846153846149\" x=\"486.92307692307696\" y=\"12.509999000099992\"><title>Name: 39618_rex\n",
       "Group: 2\n",
       "Prop: 0.0</title></rect><rect class=\"toyplot-Datum\" height=\"0.0\" style=\"fill:rgb(55.3%,62.7%,79.6%);fill-opacity:1.0;opacity:1.0;stroke:rgb(16.1%,15.3%,14.1%);stroke-opacity:1.0;stroke-width:2\" width=\"41.538461538461547\" x=\"528.46153846153845\" y=\"12.509999000099992\"><title>Name: 38362_rex\n",
       "Group: 2\n",
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style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:12.0;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"0\" y=\"3.066\">29154_superba</text></g><g transform=\"translate(228.46153846153845,10.0)rotate(60)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:12.0;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"0\" y=\"3.066\">30686_cyathophylla</text></g><g transform=\"translate(270.0,10.0)rotate(60)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:12.0;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"0\" y=\"3.066\">33413_thamno</text></g><g transform=\"translate(311.5384615384615,10.0)rotate(60)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:12.0;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"0\" y=\"3.066\">30556_thamno</text></g><g transform=\"translate(353.0769230769231,10.0)rotate(60)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:12.0;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"0\" y=\"3.066\">35236_rex</text></g><g transform=\"translate(394.6153846153846,10.0)rotate(60)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:12.0;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"0\" y=\"3.066\">40578_rex</text></g><g transform=\"translate(436.1538461538462,10.0)rotate(60)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:12.0;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"0\" y=\"3.066\">35855_rex</text></g><g transform=\"translate(477.6923076923077,10.0)rotate(60)\"><text 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       "                Save as .csv\n",
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       "        </ul><script>\n",
       "        (function()\n",
       "        {\n",
       "          var data_tables = [{\"title\": \"Bar Data\", \"names\": [\"left\", \"right\", \"baseline\", \"magnitude0\", \"magnitude1\", \"magnitude2\"], \"id\": \"t9830c01736c54660bbf60fba7afff9c4\", \"columns\": [[-0.5, 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5, 11.5], [0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5, 11.5, 12.5], [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, 0.0211, 0.0211, 0.0553, 0.0556, 0.9956, 0.9974, 0.9979, 0.9986, 0.9988, 1.0, 1.0], [0.0, 0.0, 0.9789, 0.9789, 0.9448, 0.9444, 0.0044, 0.0026, 0.0021, 0.0015, 0.0013, 0.0, 0.0], [1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]], \"filename\": \"toyplot\"}];\n",
       "\n",
       "          function save_csv(data_table)\n",
       "          {\n",
       "            var uri = \"data:text/csv;charset=utf-8,\";\n",
       "            uri += data_table.names.join(\",\") + \"\\n\";\n",
       "            for(var i = 0; i != data_table.columns[0].length; ++i)\n",
       "            {\n",
       "              for(var j = 0; j != data_table.columns.length; ++j)\n",
       "              {\n",
       "                if(j)\n",
       "                  uri += \",\";\n",
       "                uri += data_table.columns[j][i];\n",
       "              }\n",
       "              uri += \"\\n\";\n",
       "            }\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 = data_table.filename + \".csv\";\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",
       "\n",
       "          function open_popup(data_table)\n",
       "          {\n",
       "            return function(e)\n",
       "            {\n",
       "              var popup = document.querySelector(\"#t153a18e65d9940d39a87bb26079b96ec .toyplot-mark-popup\");\n",
       "              popup.querySelector(\".toyplot-mark-popup-title\").innerHTML = data_table.title;\n",
       "              popup.querySelector(\".toyplot-mark-popup-save-csv\").onclick = function() { popup.style.visibility = \"hidden\"; save_csv(data_table); }\n",
       "              popup.style.left = (e.clientX - 50) + \"px\";\n",
       "              popup.style.top = (e.clientY - 20) + \"px\";\n",
       "              popup.style.visibility = \"visible\";\n",
       "              e.stopPropagation();\n",
       "              e.preventDefault();\n",
       "            }\n",
       "\n",
       "          }\n",
       "\n",
       "          for(var i = 0; i != data_tables.length; ++i)\n",
       "          {\n",
       "            var data_table = data_tables[i];\n",
       "            var event_target = document.querySelector(\"#\" + data_table.id);\n",
       "            event_target.oncontextmenu = open_popup(data_table);\n",
       "          }\n",
       "        })();\n",
       "        </script><script>\n",
       "        (function()\n",
       "        {\n",
       "            function _sign(x)\n",
       "            {\n",
       "                return x < 0 ? -1 : x > 0 ? 1 : 0;\n",
       "            }\n",
       "\n",
       "            function _mix(a, b, amount)\n",
       "            {\n",
       "                return ((1.0 - amount) * a) + (amount * b);\n",
       "            }\n",
       "\n",
       "            function _log(x, base)\n",
       "            {\n",
       "                return Math.log(Math.abs(x)) / Math.log(base);\n",
       "            }\n",
       "\n",
       "            function _in_range(a, x, b)\n",
       "            {\n",
       "                var left = Math.min(a, b);\n",
       "                var right = Math.max(a, b);\n",
       "                return left <= x && x <= right;\n",
       "            }\n",
       "\n",
       "            function inside(range, projection)\n",
       "            {\n",
       "                for(var i = 0; i != projection.length; ++i)\n",
       "                {\n",
       "                    var segment = projection[i];\n",
       "                    if(_in_range(segment.range.min, range, segment.range.max))\n",
       "                        return true;\n",
       "                }\n",
       "                return false;\n",
       "            }\n",
       "\n",
       "            function to_domain(range, projection)\n",
       "            {\n",
       "                for(var i = 0; i != projection.length; ++i)\n",
       "                {\n",
       "                    var segment = projection[i];\n",
       "                    if(_in_range(segment.range.bounds.min, range, segment.range.bounds.max))\n",
       "                    {\n",
       "                        if(segment.scale == \"linear\")\n",
       "                        {\n",
       "                            var amount = (range - segment.range.min) / (segment.range.max - segment.range.min);\n",
       "                            return _mix(segment.domain.min, segment.domain.max, amount)\n",
       "                        }\n",
       "                        else if(segment.scale[0] == \"log\")\n",
       "                        {\n",
       "                            var amount = (range - segment.range.min) / (segment.range.max - segment.range.min);\n",
       "                            var base = segment.scale[1];\n",
       "                            return _sign(segment.domain.min) * Math.pow(base, _mix(_log(segment.domain.min, base), _log(segment.domain.max, base), amount));\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            function display_coordinates(e)\n",
       "            {\n",
       "                var current = svg.createSVGPoint();\n",
       "                current.x = e.clientX;\n",
       "                current.y = e.clientY;\n",
       "\n",
       "                for(var axis_id in axes)\n",
       "                {\n",
       "                    var axis = document.querySelector(\"#\" + axis_id);\n",
       "                    var coordinates = axis.querySelector(\".toyplot-coordinates-Axis-coordinates\");\n",
       "                    if(coordinates)\n",
       "                    {\n",
       "                        var projection = axes[axis_id];\n",
       "                        var local = current.matrixTransform(axis.getScreenCTM().inverse());\n",
       "                        if(inside(local.x, projection))\n",
       "                        {\n",
       "                            var domain = to_domain(local.x, projection);\n",
       "                            coordinates.style.visibility = \"visible\";\n",
       "                            coordinates.setAttribute(\"transform\", \"translate(\" + local.x + \")\");\n",
       "                            var text = coordinates.querySelector(\"text\");\n",
       "                            text.textContent = domain.toFixed(2);\n",
       "                        }\n",
       "                        else\n",
       "                        {\n",
       "                            coordinates.style.visibility= \"hidden\";\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            var root_id = \"t153a18e65d9940d39a87bb26079b96ec\";\n",
       "            var axes = {\"te1ab7d90bef641dba905b99c9164f524\": [{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 12.5, \"min\": -0.5}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 540.0, \"min\": 0.0}, \"scale\": \"linear\"}]};\n",
       "\n",
       "            var svg = document.querySelector(\"#\" + root_id + \" svg\");\n",
       "            svg.addEventListener(\"click\", display_coordinates);\n",
       "        })();\n",
       "        </script></div></div>"
      ],
      "text/plain": [
       "<toyplot.canvas.Canvas at 0x7fc0b504ed10>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## further styling of plot with css \n",
    "style = {\"stroke\":toyplot.color.near_black, \n",
    "         \"stroke-width\": 2}\n",
    "\n",
    "## build barplot\n",
    "canvas = toyplot.Canvas(width=600, height=250)\n",
    "axes = canvas.cartesian(bounds=(\"5%\", \"95%\", \"5%\", \"45%\"))\n",
    "axes.bars(table, title=hover(table), style=style)\n",
    "\n",
    "## add names to x-axis\n",
    "ticklabels = [i for i in table.index.tolist()]\n",
    "axes.x.ticks.locator = toyplot.locator.Explicit(labels=ticklabels)\n",
    "axes.x.ticks.labels.angle = -60\n",
    "axes.x.ticks.show = True\n",
    "axes.x.ticks.labels.offset = 10\n",
    "axes.x.ticks.labels.style = {\"font-size\": \"12px\"}\n",
    "axes.x.spine.style = style\n",
    "axes.y.show = False\n",
    "    \n",
    "## options: uncomment to save plots. Only html retains hover.\n",
    "import toyplot.svg\n",
    "import toyplot.pdf\n",
    "import toyplot.html\n",
    "toyplot.svg.render(canvas, \"struct.svg\")\n",
    "toyplot.pdf.render(canvas, \"struct.pdf\")\n",
    "toyplot.html.render(canvas, \"struct.html\")\n",
    "\n",
    "## show in notebook\n",
    "canvas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculating the best K \n",
    "Use the `.get_evanno_table()` function. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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>3</th>\n",
       "      <td>20</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-146836.325</td>\n",
       "      <td>445572.806</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20</td>\n",
       "      <td>0.218</td>\n",
       "      <td>-151762.425</td>\n",
       "      <td>316342.669</td>\n",
       "      <td>-4926.100</td>\n",
       "      <td>69040.195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>20</td>\n",
       "      <td>0.288</td>\n",
       "      <td>-225728.720</td>\n",
       "      <td>242763.400</td>\n",
       "      <td>-73966.295</td>\n",
       "      <td>70036.825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>20</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-369731.840</td>\n",
       "      <td>300321.531</td>\n",
       "      <td>-144003.120</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Nreps  deltaK  estLnProbMean  estLnProbStdev        lnPK      lnPPK\n",
       "3     20   0.000    -146836.325      445572.806       0.000      0.000\n",
       "4     20   0.218    -151762.425      316342.669   -4926.100  69040.195\n",
       "5     20   0.288    -225728.720      242763.400  -73966.295  70036.825\n",
       "6     20   0.000    -369731.840      300321.531 -144003.120      0.000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "struct.get_evanno_table([3, 4, 5, 6])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Testing for convergence\n",
    "The `.get_evanno_table()` and `.get_clumpp_table()` functions each take an optional argument called `max_var_multiple`, which is the max multiple by which you'll allow the variance in a 'replicate' run to exceed the minimum variance among replicates for a specific test. In the example below you can see that many reps were excluded for the higher values of K, such that fewer reps were analyzed for the final results. By excluding the reps that had much higher variance than other (one criterion for asking if they converged) this can increase the support for higher K values. If you apply this method take care to think about what it is doing and how to interpret the K values. Also take care to consider whether your replicates are using the same input SNP data but just different random seeds, or if you used a `map` file, in which case your replicates represent different sampled SNPs and different random seeds. I'm of the mind that there is no true K value, and sampling across a distribution of SNPs across many replicates gives you a better idea of the variance in population structure in your data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[K3] 4 reps excluded (not converged) see 'max_var_multiple'.\n",
      "[K4] 11 reps excluded (not converged) see 'max_var_multiple'.\n",
      "[K5] 1 reps excluded (not converged) see 'max_var_multiple'.\n",
      "[K6] 17 reps excluded (not converged) see 'max_var_multiple'.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\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>3</th>\n",
       "      <td>16</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-13292.675</td>\n",
       "      <td>183.466</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9</td>\n",
       "      <td>8.886</td>\n",
       "      <td>-24653.167</td>\n",
       "      <td>17188.640</td>\n",
       "      <td>-11360.492</td>\n",
       "      <td>152730.426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>19</td>\n",
       "      <td>1.759</td>\n",
       "      <td>-188744.084</td>\n",
       "      <td>182567.986</td>\n",
       "      <td>-164090.918</td>\n",
       "      <td>321182.668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>3</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-31652.333</td>\n",
       "      <td>19012.073</td>\n",
       "      <td>157091.751</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Nreps  deltaK  estLnProbMean  estLnProbStdev        lnPK       lnPPK\n",
       "3     16   0.000     -13292.675         183.466       0.000       0.000\n",
       "4      9   8.886     -24653.167       17188.640  -11360.492  152730.426\n",
       "5     19   1.759    -188744.084      182567.986 -164090.918  321182.668\n",
       "6      3   0.000     -31652.333       19012.073  157091.751       0.000"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "struct.get_evanno_table([3, 4, 5, 6], max_var_multiple=50.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Copying this notebook to your computer/cluster\n",
    "You can easily copy this notebook and then just replace my file names with your filenames to run your analysis. Just click on the [Download Notebook] link at the top of this page. Then run `jupyter-notebook` from a terminal and open this notebook from the dashboard."
   ]
  }
 ],
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