newdocs/API-analysis/cookbook-tetrad.ipynb

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    "# <span style=\"color:gray\">ipyrad-analysis toolkit:</span> tetrad\n",
    "\n",
    "`tetrad` is a species tree inference tool based on the SVDQuartets algorithm of Chifman and Kubatko. It uses the theory of phylogenetic invariants to resolve quartet trees from SNPs for all sets of quartets in a larger tree, and then joins the quartets together into a supertree using QMC. Here I demonstrate how to call tetrad from the ipyrad-analysis tools, which is convenient for keeping all of your analyses in jupyter notebooks.  Alternatively, you could also call tetrad as a command-line tool (see the [tetrad docs](https://github.com/eaton-lab/tetrad)). \n",
    "\n",
    "The following features of `tetrad` are highlighted:\n",
    "\n",
    "**Parallelization**: tetrad can be massively parallelized on an HPC cluster. It approximately scales linearly with the number of available cores. Using the flexible ipyparallel backend, you can even parallelize over multiple nodes using MPI ([more details coming soon]). \n",
    "\n",
    "**Bootstrap sampling**: In contrast to SVDquartets, tetrad is designed particularly to work well with RAD-seq data, though it can apply to any SNP data set. Bootstrap replicates resample the number of loci with replacement to the same size as the original data set. \n",
    "\n",
    "**SNP subsampling**: The underlying model assumes that the examined SNPs are unlinked, and tetrad uses a very efficient method to maximize the number of unlinked SNPs used in the analysis. A very crude way to achieve unlinked SNPs would be to sample one SNP per locus before beginning the analysis. However, a site that is variable in the context of all your samples is not necessarily informative for any given quartet of samples. Instead, tetrad subsamples a single SNP from every locus separately for every quartet set in the analysis, and repeats this independently in every bootstrap replicate. This way the maximum amount of unlinked SNP information is used in every quartet inference. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Required software"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# conda install ipyrad -c bioconda\n",
    "# conda install tetrad -c eaton-lab -c conda-forge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ipyrad.analysis as ipa\n",
    "import toytree"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Input data\n",
    "\n",
    "The input data file should be the `.snps.hdf5` file produced by ipyrad (v.0.9.13 or newer). If  you did not assemble your data in ipyrad then you can convert your SNPs data to this format from any VCF using the [vcf_to_hdf5 tool](https://ipyrad.readthedocs.io/en/latest/API-analysis/cookbook-vcf2hdf5.html). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# the path to your sequence data in HDF5 format\n",
    "data = \"/home/deren/Documents/virentes-reference/analysis-ipyrad/ref_min4_outfiles/ref_min4.snps.hdf5\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Initialize the analysis object\n",
    "Here you can enter parameters for the analysis. By default only a subsample of the total quartets will be inferred. To instead infer all quartets simply enter a very large number for the `nquartets` parameter and it will use the maximum. When you initialize the object it will print the size of your dataset, the number of loci, and the number of quartets. The number of loci is of interest because this is the maximum number of SNPs that will be used in an analysis. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading snps array [37 taxa x 1182005 snps]\n",
      "max unlinked SNPs per quartet [nloci]: 88938\n",
      "quartet sampler [full]: 66045 / 66045\n"
     ]
    }
   ],
   "source": [
    "# init analysis object with input data and (optional) parameter options\n",
    "tet = ipa.tetrad(\n",
    "    name=\"virentes-min4\",\n",
    "    data=data,\n",
    "    nquartets=1e6,\n",
    "    nboots=16,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Call run"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parallel connection | d9118d19223a: 40 cores\n",
      "initializing quartet sets database\n",
      "[####################] 100% 0:01:48 | inferring full tree * | mean SNPs/quartet: 78381  \n",
      "[####################] 100% 0:01:32 | bootstrap inference 1 | mean SNPs/quartet: 77664 \n",
      "[####################] 100% 0:01:33 | bootstrap inference 2 | mean SNPs/quartet: 78121 \n",
      "[####################] 100% 0:01:33 | bootstrap inference 3 | mean SNPs/quartet: 78356 \n",
      "[####################] 100% 0:01:33 | bootstrap inference 4 | mean SNPs/quartet: 78399 \n",
      "[####################] 100% 0:01:32 | bootstrap inference 5 | mean SNPs/quartet: 77797 \n",
      "[####################] 100% 0:01:33 | bootstrap inference 6 | mean SNPs/quartet: 78836 \n",
      "[####################] 100% 0:01:32 | bootstrap inference 7 | mean SNPs/quartet: 78550 \n",
      "[####################] 100% 0:01:32 | bootstrap inference 8 | mean SNPs/quartet: 77943 \n",
      "[####################] 100% 0:01:32 | bootstrap inference 9 | mean SNPs/quartet: 77753 \n",
      "[####################] 100% 0:01:33 | bootstrap inference 10 | mean SNPs/quartet: 78646 \n",
      "[####################] 100% 0:01:33 | bootstrap inference 11 | mean SNPs/quartet: 78200 \n",
      "[####################] 100% 0:01:32 | bootstrap inference 12 | mean SNPs/quartet: 78073 \n",
      "[####################] 100% 0:01:32 | bootstrap inference 13 | mean SNPs/quartet: 78056 \n",
      "[####################] 100% 0:01:33 | bootstrap inference 14 | mean SNPs/quartet: 78491 \n",
      "[####################] 100% 0:01:32 | bootstrap inference 15 | mean SNPs/quartet: 78709 \n",
      "[####################] 100% 0:01:32 | bootstrap inference 16 | mean SNPs/quartet: 78777 \n"
     ]
    }
   ],
   "source": [
    "tet.run(auto=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Show the full tree with bootstrap supports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
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style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:rgb(40%,76.1%,64.7%);stroke-opacity:1.0\" transform=\"translate(172.25705329153607, 609.5504143646409)\"><circle r=\"0.0\"></circle></g></g></g><g class=\"toyplot-mark-Text\" id=\"tcb22b90d0cd1490dbb155a7adc6f44ee\"><g class=\"toyplot-Series\"><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,609.5504143646409)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLSF33</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,594.1865024554942)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">SCCU3</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,578.8225905463474)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLBA140</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,563.4586786372007)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">TXWV2</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,548.094766728054)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">LALC2</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,532.7308548189073)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLSA185</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,517.3669429097606)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLCK216</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,502.0030310006139)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLMO62</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,486.6391190914672)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLSF54</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,471.27520718232046)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLAB109</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,455.9112952731737)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLWO6</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,440.54738336402704)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLCK18</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,425.1834714548803)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLSF47</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,409.81955954573357)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">HNDA09</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,394.45564763658683)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">CRL0030</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,379.09173572744015)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">BZBB1</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,363.7278238182935)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">MXSA3017</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,348.3639119091468)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">CUVN10</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,333.00000000000006)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">CRL0001</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,317.6360880908533)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">CUCA4</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,302.27217618170664)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">CUSV6</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,286.9082642725599)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">CUMM5</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,271.54435236341317)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">BJVL19</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,256.1804404542665)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">BJSL25</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,240.81652854511975)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">BJSB3</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,225.45261663597304)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">MXED8</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,210.0887047268264)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">MXGT4</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,194.72479281767966)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">TXMD3</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,179.36088090853298)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">TXGR3</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,163.99696899938624)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">EN</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,148.6330570902395)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">AR</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,133.2691451810928)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">DO</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,117.90523327194607)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">DU</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,102.54132136279935)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">reference</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,87.17740945365264)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">CH</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,71.81349754450594)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">HE</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,56.449585635359206)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">NI</text></g></g></g><g class=\"toyplot-mark-Point\" id=\"t4a18a08f21a74937aba3da556c36940c\"><g class=\"toyplot-Series\"><g class=\"toyplot-Datum\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:none;stroke-width:1\" transform=\"translate(172.25705329153607, 601.8684584100675)\"><circle r=\"9.0\"></circle><g><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:9.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-5.0040000000000004\" y=\"2.2995\">18</text></g></g><g class=\"toyplot-Datum\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:none;stroke-width:1\" transform=\"translate(172.25705329153607, 402.1376035911602)\"><circle r=\"9.0\"></circle><g><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:9.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-7.506\" y=\"2.2995\">100</text></g></g><g class=\"toyplot-Datum\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:none;stroke-width:1\" transform=\"translate(160.03134796238245, 590.3455244782075)\"><circle r=\"9.0\"></circle><g><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:9.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-5.0040000000000004\" y=\"2.2995\">18</text></g></g><g class=\"toyplot-Datum\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:none;stroke-width:1\" transform=\"translate(172.25705329153607, 478.9571631368938)\"><circle r=\"9.0\"></circle><g><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:9.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-5.0040000000000004\" y=\"2.2995\">25</text></g></g><g class=\"toyplot-Datum\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:none;stroke-width:1\" transform=\"translate(160.03134796238245, 390.61466965930015)\"><circle r=\"9.0\"></circle><g><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:9.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-7.506\" y=\"2.2995\">100</text></g></g><g class=\"toyplot-Datum\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:none;stroke-width:1\" transform=\"translate(147.80564263322884, 576.9021015577041)\"><circle r=\"9.0\"></circle><g><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:9.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-5.0040000000000004\" y=\"2.2995\">37</text></g></g><g class=\"toyplot-Datum\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:none;stroke-width:1\" transform=\"translate(172.25705329153607, 525.048898864334)\"><circle r=\"9.0\"></circle><g><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:9.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-5.0040000000000004\" y=\"2.2995\">37</text></g></g><g class=\"toyplot-Datum\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:none;stroke-width:1\" transform=\"translate(160.03134796238245, 467.4342292050337)\"><circle r=\"9.0\"></circle><g><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:9.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-5.0040000000000004\" y=\"2.2995\">75</text></g></g><g class=\"toyplot-Datum\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:none;stroke-width:1\" transform=\"translate(147.80564263322884, 377.17124673879687)\"><circle r=\"9.0\"></circle><g><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:9.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-5.0040000000000004\" y=\"2.2995\">43</text></g></g><g class=\"toyplot-Datum\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:none;stroke-width:1\" transform=\"translate(172.25705329153607, 340.6819559545734)\"><circle r=\"9.0\"></circle><g><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:9.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-5.0040000000000004\" y=\"2.2995\">43</text></g></g><g class=\"toyplot-Datum\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:none;stroke-width:1\" transform=\"translate(172.25705329153607, 263.86239640883986)\"><circle r=\"9.0\"></circle><g><text 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style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:9.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-7.506\" y=\"2.2995\">100</text></g></g><g class=\"toyplot-Datum\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:none;stroke-width:1\" transform=\"translate(147.80564263322884, 121.74621124923276)\"><circle r=\"9.0\"></circle><g><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:9.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-7.506\" y=\"2.2995\">100</text></g></g><g class=\"toyplot-Datum\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:none;stroke-width:1\" transform=\"translate(74.45141065830721, 212.2492548390501)\"><circle r=\"9.0\"></circle><g><text 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style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:9.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-7.506\" y=\"2.2995\">100</text></g></g><g class=\"toyplot-Datum\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:none;stroke-width:1\" transform=\"translate(50.0, 106.92243686814199)\"><circle r=\"9.0\"></circle><g><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:9.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-7.506\" y=\"2.2995\">100</text></g></g></g></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\"] = \"tcc9ca78cbbf546c1877ecf9554bc7ef7\";\n",
       "modules[\"toyplot/root\"] = (function(root_id)\n",
       "    {\n",
       "        return document.querySelector(\"#\" + root_id);\n",
       "    })(modules[\"toyplot/root/id\"]);\n",
       "modules[\"toyplot/canvas/id\"] = \"tdb8dea637c9e4919afe4a6990163a73b\";\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",
       "(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",
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       "(function(tables, context_menu, io, owner_id, key, label, names, columns, filename)\n",
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       "\n",
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       "})();</script></div></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tre = toytree.tree(tet.trees.tree).root([\"HE\", \"NI\"])\n",
    "tre.draw(node_labels=\"support\", use_edge_lengths=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Show the majority-rule consensus tree with bootstrap supports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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transform=\"translate(184.48275862068968,532.7308548189073)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLCK216</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,517.3669429097606)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLMO62</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,502.0030310006139)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLSA185</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,486.6391190914672)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLWO6</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,471.27520718232046)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLSF54</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,455.9112952731737)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLAB109</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,440.54738336402704)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLCK18</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,425.1834714548803)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">FLSF47</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,409.81955954573357)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">CRL0030</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,394.45564763658683)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">HNDA09</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,379.09173572744015)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">BZBB1</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,363.7278238182935)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">MXSA3017</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,348.3639119091468)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">CRL0001</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,333.00000000000006)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">CUVN10</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,317.6360880908533)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">CUCA4</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,302.27217618170664)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">CUSV6</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,286.9082642725599)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">CUMM5</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,271.54435236341317)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">BJVL19</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,256.1804404542665)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">BJSL25</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,240.81652854511975)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">BJSB3</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,225.45261663597304)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">MXED8</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,210.0887047268264)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">MXGT4</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,194.72479281767966)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">TXGR3</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,179.36088090853298)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">TXMD3</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,163.99696899938624)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">EN</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,148.6330570902395)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">AR</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,133.2691451810928)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">DO</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,117.90523327194607)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">DU</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,102.54132136279935)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">reference</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,87.17740945365264)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">CH</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,71.81349754450594)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">NI</text></g><g class=\"toyplot-Datum\" transform=\"translate(184.48275862068968,56.449585635359206)\"><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:11.0px;font-weight:normal;opacity:1;stroke:none;vertical-align:baseline;white-space:pre\" x=\"15.0\" y=\"2.8104999999999993\">HE</text></g></g></g><g class=\"toyplot-mark-Point\" id=\"t735cc7fda77f4f558858dec4f98e53c1\"><g class=\"toyplot-Series\"><g class=\"toyplot-Datum\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:none;stroke-width:1\" transform=\"translate(172.25705329153607, 601.8684584100675)\"><circle r=\"9.0\"></circle><g><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:9.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-5.0040000000000004\" y=\"2.2995\">38</text></g></g><g class=\"toyplot-Datum\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:none;stroke-width:1\" transform=\"translate(160.03134796238245, 590.3455244782075)\"><circle r=\"9.0\"></circle><g><text style=\"fill:rgb(14.9%,14.9%,14.9%);fill-opacity:1.0;font-family:helvetica;font-size:9.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-5.0040000000000004\" y=\"2.2995\">25</text></g></g><g class=\"toyplot-Datum\" style=\"fill:rgb(40%,76.1%,64.7%);fill-opacity:1.0;opacity:1.0;stroke:none;stroke-width:1\" transform=\"translate(172.25705329153607, 478.9571631368938)\"><circle r=\"9.0\"></circle><g><text 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       "{\n",
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       "        var module = {};\n",
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       "\n",
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       "\n",
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       "            {\n",
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       "                activate();\n",
       "\n",
       "                e.stopPropagation();\n",
       "                e.preventDefault();\n",
       "            }\n",
       "\n",
       "            item.addEventListener(\"mouseover\", mouseover);\n",
       "            item.addEventListener(\"mouseout\", mouseout);\n",
       "            item.addEventListener(\"mouseup\", choose_item);\n",
       "            item.addEventListener(\"contextmenu\", choose_item);\n",
       "\n",
       "            menu.appendChild(item);\n",
       "        };\n",
       "        return module;\n",
       "    })(modules[\"toyplot/root\"],modules[\"toyplot/canvas\"]);\n",
       "modules[\"toyplot/io\"] = (function()\n",
       "    {\n",
       "        var module = {};\n",
       "        module.save_file = function(mime_type, charset, data, filename)\n",
       "        {\n",
       "            var uri = \"data:\" + mime_type + \";charset=\" + charset + \",\" + data;\n",
       "            uri = encodeURI(uri);\n",
       "\n",
       "            var link = document.createElement(\"a\");\n",
       "            if(typeof link.download != \"undefined\")\n",
       "            {\n",
       "              link.href = uri;\n",
       "              link.style = \"visibility:hidden\";\n",
       "              link.download = filename;\n",
       "\n",
       "              document.body.appendChild(link);\n",
       "              link.click();\n",
       "              document.body.removeChild(link);\n",
       "            }\n",
       "            else\n",
       "            {\n",
       "              window.open(uri);\n",
       "            }\n",
       "        };\n",
       "        return module;\n",
       "    })();\n",
       "(function(tables, context_menu, io, owner_id, key, label, names, columns, filename)\n",
       "        {\n",
       "            tables.set(owner_id, key, names, columns);\n",
       "\n",
       "            var owner = document.querySelector(\"#\" + owner_id);\n",
       "            function show_item(e)\n",
       "            {\n",
       "                return owner.contains(e.target);\n",
       "            }\n",
       "\n",
       "            function choose_item()\n",
       "            {\n",
       "                io.save_file(\"text/csv\", \"utf-8\", tables.get_csv(owner_id, key), filename + \".csv\");\n",
       "            }\n",
       "\n",
       "            context_menu.add_item(\"Save \" + label + \" as CSV\", show_item, choose_item);\n",
       "        })(modules[\"toyplot/tables\"],modules[\"toyplot/menus/context\"],modules[\"toyplot/io\"],\"t8a1bccaaf9484f6aa05a328a86798b92\",\"vertex_data\",\"graph vertex data\",[\"x\", \"y\"],[[-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -1.0, -2.0, -1.0, -1.0, -3.0, -1.0, -2.0, -2.0, -1.0, -1.0, -4.0, -2.0, -3.0, -3.0, -1.0, -2.0, -5.0, -4.0, -4.0, -2.0, -3.0, -6.0, -5.0, -4.0, -1.0, -1.0, -1.0, -7.0, -5.0, -2.0, -8.0, -3.0, -9.0, -10.0, -1.0, -11.0, -11.0, -11.0, -1.0, -1.0, -10.0, -10.0, -9.0, -9.0, -3.0, -3.0, -8.0, -8.0, -2.0, -2.0, -5.0, -5.0, -7.0, -7.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -4.0, -4.0, -5.0, -5.0, -6.0, -6.0, -3.0, -3.0, -2.0, -2.0, -4.0, -4.0, -4.0, -4.0, -5.0, -5.0, -2.0, -2.0, -1.0, -1.0, -3.0, -3.0, -3.0, -3.0, -2.0, -2.0, -4.0, -4.0, -1.0, -1.0, -1.0, -1.0, -2.0, -2.0, -2.0, -2.0, -1.0, -1.0, -3.0, -3.0, -1.0, -1.0, -1.0, -1.0, -2.0, -2.0, -1.0, -1.0], [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0, 32.0, 33.0, 34.0, 35.0, 36.0, 0.5, 1.25, 8.5, 13.5, 2.125, 5.5, 9.25, 14.25, 16.5, 22.5, 3.0625, 6.25, 10.125, 15.375, 19.5, 23.25, 4.65625, 11.0625, 16.6875, 20.25, 24.125, 7.859375, 18.46875, 25.0625, 27.5, 29.5, 31.5, 13.1640625, 26.28125, 30.5, 19.72265625, 31.75, 25.736328125, 29.8681640625, 35.5, 32.68408203125, 35.5, 29.8681640625, 36.0, 35.0, 34.0, 25.736328125, 31.75, 19.72265625, 33.0, 30.5, 26.28125, 13.1640625, 31.5, 29.5, 27.5, 25.0625, 18.46875, 7.859375, 32.0, 31.0, 30.0, 29.0, 28.0, 27.0, 26.0, 24.125, 20.25, 16.6875, 11.0625, 4.65625, 25.0, 23.25, 21.0, 19.5, 18.0, 15.375, 12.0, 10.125, 6.25, 3.0625, 24.0, 22.5, 20.0, 19.0, 16.5, 14.25, 11.0, 9.25, 7.0, 5.5, 4.0, 2.125, 23.0, 22.0, 17.0, 16.0, 15.0, 13.5, 10.0, 8.5, 6.0, 5.0, 3.0, 1.25, 14.0, 13.0, 9.0, 8.0, 2.0, 0.5, 1.0, 0.0]],\"toyplot\");\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\"],\"t8a1bccaaf9484f6aa05a328a86798b92\",\"edge_data\",\"graph edge data\",[\"source\", \"target\"],[[73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 72, 72, 71, 71, 70, 70, 69, 69, 68, 68, 67, 67, 66, 66, 65, 65, 64, 64, 63, 63, 62, 62, 61, 61, 60, 60, 59, 59, 58, 58, 57, 57, 56, 56, 55, 55, 54, 54, 53, 53, 52, 52, 51, 51, 50, 50, 49, 49, 48, 48, 47, 47, 46, 46, 45, 45, 44, 44, 43, 43, 42, 42, 41, 41, 40, 40, 39, 39, 38, 38, 37, 37], [71, 70, 36, 35, 34, 69, 68, 67, 33, 66, 65, 64, 63, 62, 61, 60, 59, 58, 32, 31, 30, 29, 28, 27, 26, 57, 56, 55, 54, 53, 25, 52, 21, 51, 18, 50, 12, 49, 48, 47, 24, 46, 20, 19, 45, 44, 11, 43, 7, 42, 4, 41, 23, 22, 17, 16, 15, 40, 10, 39, 6, 5, 3, 38, 14, 13, 9, 8, 2, 37, 1, 0, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144]],\"toyplot\");\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\"],\"t735cc7fda77f4f558858dec4f98e53c1\",\"data\",\"point\",[\"x\", \"y0\"],[[-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -1.0, -2.0, -1.0, -1.0, -3.0, -1.0, -2.0, -2.0, -1.0, -1.0, -4.0, -2.0, -3.0, -3.0, -1.0, -2.0, -5.0, -4.0, -4.0, -2.0, -3.0, -6.0, -5.0, -4.0, -1.0, -1.0, -1.0, -7.0, -5.0, -2.0, -8.0, -3.0, -9.0, -10.0, -1.0, -11.0], [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0, 32.0, 33.0, 34.0, 35.0, 36.0, 0.5, 1.25, 8.5, 13.5, 2.125, 5.5, 9.25, 14.25, 16.5, 22.5, 3.0625, 6.25, 10.125, 15.375, 19.5, 23.25, 4.65625, 11.0625, 16.6875, 20.25, 24.125, 7.859375, 18.46875, 25.0625, 27.5, 29.5, 31.5, 13.1640625, 26.28125, 30.5, 19.72265625, 31.75, 25.736328125, 29.8681640625, 35.5, 32.68408203125]],\"toyplot\");\n",
       "})();</script></div></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tre = toytree.tree(tet.trees.cons).root([\"HE\", \"NI\"])\n",
    "tre.draw(node_labels=\"support\", use_edge_lengths=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Show variation over the bootstrap replicates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "{\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",
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       "\n",
       "        return module;\n",
       "    })();\n",
       "modules[\"toyplot/root/id\"] = \"t2bd902656f2e4aab90388dd4ffc40078\";\n",
       "modules[\"toyplot/root\"] = (function(root_id)\n",
       "    {\n",
       "        return document.querySelector(\"#\" + root_id);\n",
       "    })(modules[\"toyplot/root/id\"]);\n",
       "modules[\"toyplot/canvas/id\"] = \"t552de9970010432d8d4f8ea8b2f3ff84\";\n",
       "modules[\"toyplot/canvas\"] = (function(canvas_id)\n",
       "    {\n",
       "        return document.querySelector(\"#\" + canvas_id);\n",
       "    })(modules[\"toyplot/canvas/id\"]);\n",
       "modules[\"toyplot/menus/context\"] = (function(root, canvas)\n",
       "    {\n",
       "        var wrapper = document.createElement(\"div\");\n",
       "        wrapper.innerHTML = \"<ul class='toyplot-context-menu' style='background:#eee; border:1px solid #b8b8b8; border-radius:5px; box-shadow: 0px 0px 8px rgba(0%,0%,0%,0.25); margin:0; padding:3px 0; position:fixed; visibility:hidden;'></ul>\"\n",
       "        var menu = wrapper.firstChild;\n",
       "\n",
       "        root.appendChild(menu);\n",
       "\n",
       "        var items = [];\n",
       "\n",
       "        var ignore_mouseup = null;\n",
       "        function open_menu(e)\n",
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       "            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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       "                else\n",
       "                {\n",
       "                    item.item.style.display = \"none\";\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",
       "                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",
       "(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\"],\"t65d21a7eb4154fc8a360dd9a18f57d14\",\"vertex_data\",\"graph vertex data\",[\"x\", \"y\"],[[-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -1.0, -1.0, -2.0, -1.0, -2.0, -3.0, -1.0, -2.0, -3.0, -1.0, -1.0, -4.0, -2.0, -3.0, -4.0, -1.0, -2.0, -5.0, -4.0, -5.0, -3.0, -6.0, -6.0, -4.0, -1.0, -1.0, -1.0, -7.0, -5.0, -2.0, -8.0, -3.0, -9.0, -10.0, -1.0, -11.0], [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0, 32.0, 33.0, 34.0, 35.0, 36.0, 0.5, 13.5, 1.25, 8.5, 14.25, 2.125, 5.5, 9.25, 15.125, 17.5, 22.5, 3.0625, 6.25, 10.125, 16.3125, 19.5, 23.25, 4.65625, 11.0625, 17.90625, 24.125, 7.859375, 19.453125, 25.0625, 27.5, 29.5, 31.5, 13.65625, 26.28125, 30.5, 19.96875, 31.75, 25.859375, 29.9296875, 35.5, 32.71484375]],\"toyplot\");\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\"],\"t65d21a7eb4154fc8a360dd9a18f57d14\",\"edge_data\",\"graph edge data\",[\"source\", \"target\"],[[71, 71, 72, 70, 68, 63, 63, 66, 62, 62, 66, 68, 69, 61, 61, 65, 60, 57, 53, 47, 47, 53, 57, 60, 65, 67, 59, 52, 52, 56, 46, 46, 51, 45, 41, 38, 38, 41, 45, 51, 56, 59, 64, 55, 50, 44, 40, 40, 44, 50, 55, 58, 49, 43, 43, 49, 54, 48, 42, 39, 37, 37, 39, 42, 48, 54, 58, 64, 67, 69, 70, 72], [36, 35, 71, 34, 33, 32, 31, 63, 30, 29, 62, 66, 68, 28, 27, 61, 26, 25, 24, 23, 22, 47, 53, 57, 60, 65, 21, 20, 19, 52, 18, 17, 46, 16, 15, 14, 13, 38, 41, 45, 51, 56, 59, 12, 11, 10, 9, 8, 40, 44, 50, 55, 7, 6, 5, 43, 49, 4, 3, 2, 1, 0, 37, 39, 42, 48, 54, 58, 64, 67, 69, 70]],\"toyplot\");\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\"],\"t9bea0cf7f58c432d8f82aed61b75be4f\",\"vertex_data\",\"graph vertex data\",[\"x\", \"y\"],[[-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -1.0, -2.0, -1.0, -1.0, -3.0, -1.0, -2.0, -2.0, -1.0, -4.0, -2.0, -3.0, -3.0, -1.0, -1.0, -2.0, -5.0, -4.0, -4.0, -2.0, -3.0, -6.0, -5.0, -4.0, -1.0, -1.0, -1.0, -7.0, -5.0, -2.0, -8.0, -3.0, -9.0, -10.0, -1.0, -11.0], [3.0, 0.0, 2.0, 4.0, 1.0, 7.0, 6.0, 5.0, 8.0, 10.0, 11.0, 9.0, 12.0, 14.0, 13.0, 15.0, 16.0, 17.0, 18.0, 19.0, 21.0, 20.0, 22.0, 24.0, 23.0, 25.0, 26.0, 28.0, 27.0, 31.0, 32.0, 29.0, 30.0, 33.0, 34.0, 36.0, 35.0, 1.5, 1.75, 9.0, 13.5, 2.875, 6.5, 10.0, 14.25, 23.0, 1.9375, 5.75, 9.5, 15.125, 17.5, 20.0, 23.0, 3.84375, 10.75, 16.3125, 20.0, 24.0, 7.296875, 18.15625, 25.0, 27.5, 31.5, 29.5, 12.7265625, 26.25, 30.5, 19.48828125, 31.75, 25.619140625, 29.8095703125, 35.5, 32.65478515625]],\"toyplot\");\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\"],\"t9bea0cf7f58c432d8f82aed61b75be4f\",\"edge_data\",\"graph edge data\",[\"source\", \"target\"],[[71, 71, 72, 70, 68, 63, 63, 66, 62, 62, 66, 68, 69, 61, 61, 65, 60, 57, 52, 45, 45, 52, 57, 60, 65, 67, 56, 51, 51, 56, 59, 50, 50, 55, 49, 44, 40, 40, 44, 49, 55, 59, 64, 54, 48, 43, 39, 39, 43, 48, 54, 58, 47, 42, 42, 47, 53, 46, 41, 38, 37, 37, 38, 41, 46, 53, 58, 64, 67, 69, 70, 72], [36, 35, 71, 34, 33, 32, 31, 63, 30, 29, 62, 66, 68, 28, 27, 61, 26, 25, 24, 23, 22, 45, 52, 57, 60, 65, 21, 20, 19, 51, 56, 18, 17, 50, 16, 15, 14, 13, 40, 44, 49, 55, 59, 12, 11, 10, 9, 8, 39, 43, 48, 54, 7, 6, 5, 42, 47, 4, 3, 2, 1, 0, 37, 38, 41, 46, 53, 58, 64, 67, 69, 70]],\"toyplot\");\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\"],\"tf4966c1b4c2849ed98238550449ccdad\",\"vertex_data\",\"graph vertex data\",[\"x\", \"y\"],[[-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -1.0, -1.0, -1.0, -2.0, -1.0, -2.0, -1.0, -1.0, -2.0, -3.0, -1.0, -3.0, -2.0, -3.0, -4.0, -2.0, -4.0, -4.0, -5.0, -1.0, -3.0, -5.0, -6.0, -4.0, -1.0, -1.0, -1.0, -7.0, -5.0, -2.0, -8.0, -3.0, -9.0, -10.0, -1.0, -11.0], [3.0, 2.0, 1.0, 4.0, 0.0, 6.0, 5.0, 7.0, 8.0, 10.0, 11.0, 9.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 21.0, 19.0, 20.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0, 32.0, 33.0, 34.0, 36.0, 35.0, 13.5, 2.5, 9.0, 14.25, 16.5, 1.75, 2.0, 5.5, 10.0, 15.375, 22.5, 1.875, 6.25, 9.5, 16.6875, 23.25, 4.0625, 10.75, 18.84375, 19.5, 24.125, 7.40625, 19.171875, 25.0625, 27.5, 29.5, 31.5, 13.2890625, 26.28125, 30.5, 19.78515625, 31.75, 25.767578125, 29.8837890625, 35.5, 32.69189453125]],\"toyplot\");\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\"],\"tf4966c1b4c2849ed98238550449ccdad\",\"edge_data\",\"graph edge data\",[\"source\", \"target\"],[[71, 71, 72, 70, 68, 63, 63, 66, 62, 62, 66, 68, 69, 61, 61, 65, 60, 57, 52, 47, 47, 52, 57, 60, 65, 67, 56, 56, 59, 55, 51, 41, 41, 46, 40, 37, 37, 40, 46, 51, 55, 59, 64, 54, 50, 45, 39, 39, 45, 50, 54, 58, 49, 44, 44, 49, 53, 43, 43, 48, 42, 38, 38, 42, 48, 53, 58, 64, 67, 69, 70, 72], [36, 35, 71, 34, 33, 32, 31, 63, 30, 29, 62, 66, 68, 28, 27, 61, 26, 25, 24, 23, 22, 47, 52, 57, 60, 65, 21, 20, 56, 19, 18, 17, 16, 41, 15, 14, 13, 37, 40, 46, 51, 55, 59, 12, 11, 10, 9, 8, 39, 45, 50, 54, 7, 6, 5, 44, 49, 4, 3, 43, 2, 1, 0, 38, 42, 48, 53, 58, 64, 67, 69, 70]],\"toyplot\");\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\"],\"t9190e86128504e2fb09ebfd9238bb5e0\",\"vertex_data\",\"graph vertex data\",[\"x\", \"y\"],[[-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -1.0, -2.0, -1.0, -1.0, -3.0, -1.0, -2.0, -2.0, -1.0, -1.0, -4.0, -2.0, -3.0, -3.0, -1.0, -2.0, -5.0, -4.0, -4.0, -1.0, -3.0, -6.0, -5.0, -4.0, -1.0, -1.0, -1.0, -7.0, -5.0, -2.0, -8.0, -3.0, -9.0, -10.0, -1.0, -11.0], [2.0, 3.0, 0.0, 4.0, 1.0, 7.0, 6.0, 5.0, 10.0, 11.0, 8.0, 9.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 20.0, 19.0, 21.0, 22.0, 24.0, 23.0, 25.0, 26.0, 28.0, 27.0, 30.0, 29.0, 31.0, 32.0, 33.0, 34.0, 35.0, 36.0, 2.5, 1.25, 10.5, 13.5, 2.625, 6.5, 9.25, 14.25, 16.5, 23.0, 1.8125, 5.75, 9.125, 15.375, 19.0, 23.0, 3.78125, 10.5625, 17.1875, 20.0, 24.0, 7.171875, 18.59375, 25.0, 27.5, 29.5, 31.5, 12.8828125, 26.25, 30.5, 19.56640625, 31.75, 25.658203125, 29.8291015625, 35.5, 32.66455078125]],\"toyplot\");\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\"],\"t9190e86128504e2fb09ebfd9238bb5e0\",\"edge_data\",\"graph edge data\",[\"source\", \"target\"],[[71, 71, 72, 70, 68, 63, 63, 66, 62, 62, 66, 68, 69, 61, 61, 65, 60, 57, 52, 46, 46, 52, 57, 60, 65, 67, 56, 56, 59, 51, 51, 55, 45, 45, 50, 44, 40, 40, 44, 50, 55, 59, 64, 54, 49, 43, 39, 39, 43, 49, 54, 58, 48, 42, 42, 48, 53, 47, 41, 38, 37, 37, 38, 41, 47, 53, 58, 64, 67, 69, 70, 72], [36, 35, 71, 34, 33, 32, 31, 63, 30, 29, 62, 66, 68, 28, 27, 61, 26, 25, 24, 23, 22, 46, 52, 57, 60, 65, 21, 20, 56, 19, 18, 51, 17, 16, 45, 15, 14, 13, 40, 44, 50, 55, 59, 12, 11, 10, 9, 8, 39, 43, 49, 54, 7, 6, 5, 42, 48, 4, 3, 2, 1, 0, 37, 38, 41, 47, 53, 58, 64, 67, 69, 70]],\"toyplot\");\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\"],\"tca196e26f4a64deb9a90cd9fc8db7834\",\"vertex_data\",\"graph vertex data\",[\"x\", \"y\"],[[-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -1.0, -1.0, -1.0, -2.0, -1.0, -1.0, -2.0, -2.0, -1.0, -1.0, -3.0, -2.0, -3.0, -3.0, -1.0, -2.0, -4.0, -4.0, -4.0, -1.0, -3.0, -5.0, -5.0, -4.0, -1.0, -1.0, -1.0, -6.0, -5.0, -2.0, -7.0, -3.0, -8.0, -9.0, -1.0, -10.0], [3.0, 0.0, 4.0, 1.0, 2.0, 5.0, 6.0, 7.0, 8.0, 10.0, 11.0, 9.0, 12.0, 14.0, 13.0, 15.0, 16.0, 17.0, 20.0, 18.0, 19.0, 21.0, 23.0, 24.0, 22.0, 25.0, 26.0, 28.0, 27.0, 30.0, 29.0, 31.0, 32.0, 33.0, 34.0, 36.0, 35.0, 1.5, 9.0, 13.5, 2.75, 1.5, 5.5, 10.0, 14.25, 16.5, 23.5, 2.125, 6.25, 9.5, 15.375, 19.0, 22.75, 4.1875, 10.75, 17.1875, 20.0, 23.875, 7.46875, 18.59375, 24.9375, 27.5, 29.5, 31.5, 13.03125, 26.21875, 30.5, 19.625, 31.75, 25.6875, 29.84375, 35.5, 32.671875]],\"toyplot\");\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\"],\"tca196e26f4a64deb9a90cd9fc8db7834\",\"edge_data\",\"graph edge data\",[\"source\", \"target\"],[[71, 71, 72, 70, 68, 63, 63, 66, 62, 62, 66, 68, 69, 61, 61, 65, 60, 57, 52, 46, 46, 52, 57, 60, 65, 67, 56, 56, 59, 51, 51, 55, 45, 45, 50, 44, 39, 39, 44, 50, 55, 59, 64, 54, 49, 43, 38, 38, 43, 49, 54, 58, 48, 42, 42, 48, 53, 41, 41, 47, 40, 37, 37, 40, 47, 53, 58, 64, 67, 69, 70, 72], [36, 35, 71, 34, 33, 32, 31, 63, 30, 29, 62, 66, 68, 28, 27, 61, 26, 25, 24, 23, 22, 46, 52, 57, 60, 65, 21, 20, 56, 19, 18, 51, 17, 16, 45, 15, 14, 13, 39, 44, 50, 55, 59, 12, 11, 10, 9, 8, 38, 43, 49, 54, 7, 6, 5, 42, 48, 4, 3, 41, 2, 1, 0, 37, 40, 47, 53, 58, 64, 67, 69, 70]],\"toyplot\");\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\"],\"tf61b06fc4faa46f086575ceeb055017b\",\"vertex_data\",\"graph vertex data\",[\"x\", \"y\"],[[-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -1.0, -1.0, -1.0, -2.0, -1.0, -1.0, -2.0, -2.0, -1.0, -3.0, -2.0, -3.0, -3.0, -1.0, -1.0, -4.0, -4.0, -4.0, -2.0, -2.0, -1.0, -5.0, -5.0, -3.0, -1.0, -1.0, -1.0, -6.0, -4.0, -2.0, -7.0, -3.0, -8.0, -9.0, -1.0, -10.0], [1.0, 2.0, 3.0, 0.0, 4.0, 6.0, 5.0, 7.0, 10.0, 8.0, 11.0, 9.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 20.0, 21.0, 19.0, 24.0, 22.0, 23.0, 25.0, 26.0, 27.0, 28.0, 31.0, 32.0, 29.0, 30.0, 33.0, 34.0, 36.0, 35.0, 1.5, 9.0, 13.5, 2.25, 2.0, 5.5, 10.0, 14.25, 16.5, 2.125, 6.25, 9.5, 15.375, 20.5, 23.0, 4.1875, 10.75, 16.6875, 19.75, 23.0, 25.5, 7.46875, 18.21875, 24.25, 27.5, 31.5, 29.5, 12.84375, 25.875, 30.5, 19.359375, 31.75, 25.5546875, 29.77734375, 35.5, 32.638671875]],\"toyplot\");\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\"],\"tf61b06fc4faa46f086575ceeb055017b\",\"edge_data\",\"graph edge data\",[\"source\", \"target\"],[[71, 71, 72, 70, 68, 63, 63, 66, 62, 62, 66, 68, 69, 61, 61, 65, 57, 57, 60, 56, 51, 51, 56, 60, 65, 67, 55, 50, 50, 55, 59, 54, 45, 45, 49, 44, 39, 39, 44, 49, 54, 59, 64, 53, 48, 43, 38, 38, 43, 48, 53, 58, 47, 42, 42, 47, 52, 41, 41, 46, 40, 37, 37, 40, 46, 52, 58, 64, 67, 69, 70, 72], [36, 35, 71, 34, 33, 32, 31, 63, 30, 29, 62, 66, 68, 28, 27, 61, 26, 25, 57, 24, 23, 22, 51, 56, 60, 65, 21, 20, 19, 50, 55, 18, 17, 16, 45, 15, 14, 13, 39, 44, 49, 54, 59, 12, 11, 10, 9, 8, 38, 43, 48, 53, 7, 6, 5, 42, 47, 4, 3, 41, 2, 1, 0, 37, 40, 46, 52, 58, 64, 67, 69, 70]],\"toyplot\");\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\"],\"t263c5ee938f94c9887147e16b41dd9ad\",\"vertex_data\",\"graph vertex data\",[\"x\", \"y\"],[[-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -1.0, -2.0, -1.0, -1.0, -3.0, -1.0, -2.0, -2.0, -1.0, -4.0, -2.0, -3.0, -3.0, -1.0, -1.0, -2.0, -5.0, -4.0, -4.0, -2.0, -3.0, -6.0, -5.0, -4.0, -1.0, -1.0, -1.0, -7.0, -5.0, -2.0, -8.0, -3.0, -9.0, -10.0, -1.0, -11.0], [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 9.0, 8.0, 10.0, 11.0, 12.0, 14.0, 13.0, 15.0, 16.0, 18.0, 17.0, 20.0, 21.0, 19.0, 22.0, 24.0, 23.0, 25.0, 26.0, 27.0, 28.0, 31.0, 32.0, 29.0, 30.0, 33.0, 34.0, 35.0, 36.0, 0.5, 1.25, 8.5, 13.5, 2.125, 5.5, 9.25, 14.25, 23.0, 3.0625, 6.25, 10.125, 15.125, 17.5, 20.5, 23.0, 4.65625, 11.0625, 16.3125, 19.75, 24.0, 7.859375, 18.03125, 25.0, 27.5, 31.5, 29.5, 12.9453125, 26.25, 30.5, 19.59765625, 31.75, 25.673828125, 29.8369140625, 35.5, 32.66845703125]],\"toyplot\");\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\"],\"t263c5ee938f94c9887147e16b41dd9ad\",\"edge_data\",\"graph edge data\",[\"source\", \"target\"],[[71, 71, 72, 70, 68, 63, 63, 66, 62, 62, 66, 68, 69, 61, 61, 65, 60, 57, 52, 45, 45, 52, 57, 60, 65, 67, 56, 51, 51, 56, 59, 50, 50, 55, 49, 44, 40, 40, 44, 49, 55, 59, 64, 54, 48, 43, 39, 39, 43, 48, 54, 58, 47, 42, 42, 47, 53, 46, 41, 38, 37, 37, 38, 41, 46, 53, 58, 64, 67, 69, 70, 72], [36, 35, 71, 34, 33, 32, 31, 63, 30, 29, 62, 66, 68, 28, 27, 61, 26, 25, 24, 23, 22, 45, 52, 57, 60, 65, 21, 20, 19, 51, 56, 18, 17, 50, 16, 15, 14, 13, 40, 44, 49, 55, 59, 12, 11, 10, 9, 8, 39, 43, 48, 54, 7, 6, 5, 42, 47, 4, 3, 2, 1, 0, 37, 38, 41, 46, 53, 58, 64, 67, 69, 70]],\"toyplot\");\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\"],\"te37608669c484f0585bb0d6b8876fb57\",\"vertex_data\",\"graph vertex data\",[\"x\", \"y\"],[[-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -1.0, -1.0, -2.0, -1.0, -2.0, -3.0, -1.0, -2.0, -3.0, -1.0, -1.0, -4.0, -2.0, -3.0, -4.0, -2.0, -5.0, -4.0, -5.0, -1.0, -3.0, -6.0, -6.0, -4.0, -1.0, -1.0, -1.0, -7.0, -5.0, -2.0, -8.0, -3.0, -9.0, -10.0, -1.0, -11.0], [1.0, 2.0, 0.0, 3.0, 4.0, 7.0, 6.0, 5.0, 8.0, 11.0, 10.0, 9.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 17.0, 20.0, 21.0, 19.0, 24.0, 22.0, 23.0, 25.0, 26.0, 27.0, 28.0, 31.0, 32.0, 30.0, 29.0, 33.0, 34.0, 35.0, 36.0, 1.5, 13.5, 0.75, 9.5, 14.25, 1.875, 6.5, 9.75, 15.125, 17.5, 23.0, 2.9375, 5.75, 9.375, 16.3125, 23.0, 4.34375, 10.6875, 18.15625, 20.0, 24.0, 7.515625, 19.078125, 25.0, 27.5, 31.5, 29.5, 13.296875, 26.25, 30.5, 19.7734375, 31.75, 25.76171875, 29.880859375, 35.5, 32.6904296875]],\"toyplot\");\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\"],\"te37608669c484f0585bb0d6b8876fb57\",\"edge_data\",\"graph edge data\",[\"source\", \"target\"],[[71, 71, 72, 70, 68, 63, 63, 66, 62, 62, 66, 68, 69, 61, 61, 65, 60, 57, 52, 47, 47, 52, 57, 60, 65, 67, 56, 56, 59, 55, 46, 46, 51, 45, 41, 38, 38, 41, 45, 51, 55, 59, 64, 54, 50, 44, 40, 40, 44, 50, 54, 58, 49, 43, 43, 49, 53, 48, 42, 39, 37, 37, 39, 42, 48, 53, 58, 64, 67, 69, 70, 72], [36, 35, 71, 34, 33, 32, 31, 63, 30, 29, 62, 66, 68, 28, 27, 61, 26, 25, 24, 23, 22, 47, 52, 57, 60, 65, 21, 20, 56, 19, 18, 17, 46, 16, 15, 14, 13, 38, 41, 45, 51, 55, 59, 12, 11, 10, 9, 8, 40, 44, 50, 54, 7, 6, 5, 43, 49, 4, 3, 2, 1, 0, 37, 39, 42, 48, 53, 58, 64, 67, 69, 70]],\"toyplot\");\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\"],\"tfcff525929ba43799d4cf34dbf4ead64\",\"vertex_data\",\"graph vertex data\",[\"x\", \"y\"],[[-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -1.0, -1.0, -2.0, -2.0, -1.0, -3.0, -1.0, -1.0, -1.0, -3.0, -1.0, -4.0, -2.0, -2.0, -4.0, -2.0, -5.0, -3.0, -5.0, -1.0, -3.0, -6.0, -6.0, -4.0, -1.0, -1.0, -1.0, -7.0, -5.0, -2.0, -8.0, -3.0, -9.0, -10.0, -1.0, -11.0], [1.0, 3.0, 2.0, 0.0, 4.0, 6.0, 7.0, 5.0, 10.0, 9.0, 8.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 21.0, 19.0, 20.0, 24.0, 22.0, 23.0, 25.0, 26.0, 28.0, 27.0, 31.0, 32.0, 30.0, 29.0, 33.0, 34.0, 36.0, 35.0, 2.0, 13.5, 2.0, 14.25, 16.5, 1.0, 6.5, 9.5, 9.5, 15.375, 23.0, 2.5, 5.75, 9.5, 16.6875, 23.0, 4.125, 10.75, 18.84375, 19.5, 24.0, 7.4375, 19.171875, 25.0, 27.5, 31.5, 29.5, 13.3046875, 26.25, 30.5, 19.77734375, 31.75, 25.763671875, 29.8818359375, 35.5, 32.69091796875]],\"toyplot\");\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\"],\"tfcff525929ba43799d4cf34dbf4ead64\",\"edge_data\",\"graph edge data\",[\"source\", \"target\"],[[71, 71, 72, 70, 68, 63, 63, 66, 62, 62, 66, 68, 69, 61, 61, 65, 60, 57, 52, 47, 47, 52, 57, 60, 65, 67, 56, 56, 59, 55, 51, 41, 41, 46, 40, 38, 38, 40, 46, 51, 55, 59, 64, 54, 45, 45, 50, 44, 44, 50, 54, 58, 49, 43, 43, 49, 53, 48, 42, 39, 37, 37, 39, 42, 48, 53, 58, 64, 67, 69, 70, 72], [36, 35, 71, 34, 33, 32, 31, 63, 30, 29, 62, 66, 68, 28, 27, 61, 26, 25, 24, 23, 22, 47, 52, 57, 60, 65, 21, 20, 56, 19, 18, 17, 16, 41, 15, 14, 13, 38, 40, 46, 51, 55, 59, 12, 11, 10, 45, 9, 8, 44, 50, 54, 7, 6, 5, 43, 49, 4, 3, 2, 1, 0, 37, 39, 42, 48, 53, 58, 64, 67, 69, 70]],\"toyplot\");\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\"],\"t3c1b63a01e8849579867a0854b29c679\",\"vertex_data\",\"graph vertex data\",[\"x\", \"y\"],[[-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -1.0, -2.0, -1.0, -3.0, -1.0, -2.0, -1.0, -1.0, -4.0, -2.0, -3.0, -2.0, -1.0, -1.0, -1.0, -2.0, -5.0, -4.0, -3.0, -2.0, -3.0, -6.0, -4.0, -4.0, -1.0, -1.0, -1.0, -7.0, -5.0, -2.0, -8.0, -3.0, -9.0, -10.0, -1.0, -11.0], [0.0, 4.0, 3.0, 2.0, 1.0, 6.0, 5.0, 7.0, 10.0, 8.0, 11.0, 9.0, 12.0, 14.0, 13.0, 15.0, 16.0, 17.0, 18.0, 19.0, 21.0, 20.0, 24.0, 22.0, 23.0, 25.0, 26.0, 28.0, 27.0, 31.0, 32.0, 29.0, 30.0, 33.0, 34.0, 35.0, 36.0, 2.0, 2.5, 9.0, 2.25, 5.5, 10.0, 13.5, 23.0, 1.625, 6.25, 9.5, 14.25, 16.5, 18.5, 20.5, 23.0, 3.9375, 10.75, 15.375, 19.5, 24.0, 7.34375, 17.4375, 25.0, 27.5, 31.5, 29.5, 12.390625, 26.25, 30.5, 19.3203125, 31.75, 25.53515625, 29.767578125, 35.5, 32.6337890625]],\"toyplot\");\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\"],\"t3c1b63a01e8849579867a0854b29c679\",\"edge_data\",\"graph edge data\",[\"source\", \"target\"],[[71, 71, 72, 70, 68, 63, 63, 66, 62, 62, 66, 68, 69, 61, 61, 65, 60, 57, 52, 44, 44, 52, 57, 60, 65, 67, 51, 51, 56, 50, 50, 56, 59, 49, 49, 55, 48, 43, 43, 48, 55, 59, 64, 54, 47, 42, 39, 39, 42, 47, 54, 58, 46, 41, 41, 46, 53, 45, 40, 38, 37, 37, 38, 40, 45, 53, 58, 64, 67, 69, 70, 72], [36, 35, 71, 34, 33, 32, 31, 63, 30, 29, 62, 66, 68, 28, 27, 61, 26, 25, 24, 23, 22, 44, 52, 57, 60, 65, 21, 20, 51, 19, 18, 50, 56, 17, 16, 49, 15, 14, 13, 43, 48, 55, 59, 12, 11, 10, 9, 8, 39, 42, 47, 54, 7, 6, 5, 41, 46, 4, 3, 2, 1, 0, 37, 38, 40, 45, 53, 58, 64, 67, 69, 70]],\"toyplot\");\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\"],\"tfab27689d7014bcb85a1fecc228c3978\",\"vertex_data\",\"graph vertex data\",[\"x\", \"y\"],[[-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -1.0, -1.0, -1.0, -1.0, -2.0, -1.0, -2.0, -1.0, -2.0, -3.0, -1.0, -1.0, -3.0, -2.0, -3.0, -4.0, -2.0, -4.0, -4.0, -5.0, -3.0, -5.0, -6.0, -4.0, -1.0, -1.0, -1.0, -7.0, -5.0, -2.0, -8.0, -3.0, -9.0, -10.0, -1.0, -11.0], [4.0, 0.0, 2.0, 3.0, 1.0, 5.0, 6.0, 7.0, 10.0, 11.0, 8.0, 9.0, 12.0, 13.0, 14.0, 15.0, 17.0, 16.0, 18.0, 19.0, 21.0, 20.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 31.0, 32.0, 29.0, 30.0, 33.0, 34.0, 35.0, 36.0, 13.5, 2.0, 2.5, 10.5, 14.25, 16.5, 2.25, 5.5, 9.25, 15.375, 18.5, 22.5, 1.625, 6.25, 9.125, 16.9375, 23.25, 3.9375, 10.5625, 18.96875, 24.125, 7.25, 19.484375, 25.0625, 27.5, 31.5, 29.5, 13.3671875, 26.28125, 30.5, 19.82421875, 31.75, 25.787109375, 29.8935546875, 35.5, 32.69677734375]],\"toyplot\");\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\"],\"tfab27689d7014bcb85a1fecc228c3978\",\"edge_data\",\"graph edge data\",[\"source\", \"target\"],[[71, 71, 72, 70, 68, 63, 63, 66, 62, 62, 66, 68, 69, 61, 61, 65, 60, 57, 53, 48, 48, 53, 57, 60, 65, 67, 59, 56, 47, 47, 52, 42, 42, 46, 41, 37, 37, 41, 46, 52, 56, 59, 64, 55, 51, 45, 40, 40, 45, 51, 55, 58, 50, 44, 44, 50, 54, 49, 39, 39, 43, 38, 38, 43, 49, 54, 58, 64, 67, 69, 70, 72], [36, 35, 71, 34, 33, 32, 31, 63, 30, 29, 62, 66, 68, 28, 27, 61, 26, 25, 24, 23, 22, 48, 53, 57, 60, 65, 21, 20, 19, 18, 47, 17, 16, 42, 15, 14, 13, 37, 41, 46, 52, 56, 59, 12, 11, 10, 9, 8, 40, 45, 51, 55, 7, 6, 5, 44, 50, 4, 3, 2, 39, 1, 0, 38, 43, 49, 54, 58, 64, 67, 69, 70]],\"toyplot\");\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\"],\"t69dac4ddc8f847ed85a292e5e086fb3c\",\"vertex_data\",\"graph vertex data\",[\"x\", \"y\"],[[-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -1.0, -2.0, -1.0, -1.0, -3.0, -1.0, -2.0, -2.0, -1.0, -4.0, -2.0, -3.0, -3.0, -1.0, -1.0, -2.0, -5.0, -4.0, -4.0, -2.0, -3.0, -1.0, -6.0, -5.0, -4.0, -1.0, -1.0, -7.0, -5.0, -2.0, -8.0, -3.0, -9.0, -10.0, -1.0, -11.0], [2.0, 1.0, 0.0, 3.0, 4.0, 6.0, 7.0, 5.0, 10.0, 11.0, 8.0, 9.0, 12.0, 14.0, 13.0, 15.0, 16.0, 17.0, 18.0, 20.0, 19.0, 21.0, 22.0, 24.0, 23.0, 25.0, 27.0, 28.0, 26.0, 31.0, 32.0, 30.0, 29.0, 33.0, 34.0, 35.0, 36.0, 1.5, 0.75, 10.5, 13.5, 1.875, 6.5, 9.25, 14.25, 23.0, 2.9375, 5.75, 9.125, 15.125, 17.5, 19.5, 23.0, 4.34375, 10.5625, 16.3125, 20.25, 24.0, 27.5, 7.453125, 18.28125, 25.75, 31.5, 29.5, 12.8671875, 25.875, 30.5, 19.37109375, 31.75, 25.560546875, 29.7802734375, 35.5, 32.64013671875]],\"toyplot\");\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\"],\"t69dac4ddc8f847ed85a292e5e086fb3c\",\"edge_data\",\"graph edge data\",[\"source\", \"target\"],[[71, 71, 72, 70, 68, 63, 63, 66, 62, 62, 66, 68, 69, 65, 58, 58, 61, 57, 52, 45, 45, 52, 57, 61, 65, 67, 56, 51, 51, 56, 60, 50, 50, 55, 49, 44, 40, 40, 44, 49, 55, 60, 64, 54, 48, 43, 39, 39, 43, 48, 54, 59, 47, 42, 42, 47, 53, 46, 41, 38, 37, 37, 38, 41, 46, 53, 59, 64, 67, 69, 70, 72], [36, 35, 71, 34, 33, 32, 31, 63, 30, 29, 62, 66, 68, 28, 27, 26, 58, 25, 24, 23, 22, 45, 52, 57, 61, 65, 21, 20, 19, 51, 56, 18, 17, 50, 16, 15, 14, 13, 40, 44, 49, 55, 60, 12, 11, 10, 9, 8, 39, 43, 48, 54, 7, 6, 5, 42, 47, 4, 3, 2, 1, 0, 37, 38, 41, 46, 53, 59, 64, 67, 69, 70]],\"toyplot\");\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\"],\"t7dbdccf433274500923619e1c1b0f8f9\",\"vertex_data\",\"graph vertex data\",[\"x\", \"y\"],[[-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -1.0, -2.0, -1.0, -1.0, -3.0, -1.0, -2.0, -2.0, -1.0, -4.0, -2.0, -3.0, -3.0, -1.0, -1.0, -2.0, -5.0, -4.0, -4.0, -2.0, -3.0, -6.0, -5.0, -4.0, -1.0, -1.0, -1.0, -7.0, -5.0, -2.0, -8.0, -3.0, -9.0, -10.0, -1.0, -11.0], [0.0, 2.0, 4.0, 3.0, 1.0, 6.0, 5.0, 7.0, 10.0, 11.0, 8.0, 9.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 17.0, 21.0, 19.0, 20.0, 24.0, 22.0, 23.0, 25.0, 26.0, 28.0, 27.0, 31.0, 32.0, 30.0, 29.0, 33.0, 34.0, 35.0, 36.0, 1.0, 2.5, 10.5, 13.5, 2.75, 5.5, 9.25, 14.25, 23.0, 1.875, 6.25, 9.125, 15.125, 17.5, 20.0, 23.0, 4.0625, 10.5625, 16.3125, 20.0, 24.0, 7.3125, 18.15625, 25.0, 27.5, 31.5, 29.5, 12.734375, 26.25, 30.5, 19.4921875, 31.75, 25.62109375, 29.810546875, 35.5, 32.6552734375]],\"toyplot\");\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\"],\"t7dbdccf433274500923619e1c1b0f8f9\",\"edge_data\",\"graph edge data\",[\"source\", \"target\"],[[71, 71, 72, 70, 68, 63, 63, 66, 62, 62, 66, 68, 69, 61, 61, 65, 60, 57, 52, 45, 45, 52, 57, 60, 65, 67, 56, 51, 51, 56, 59, 50, 50, 55, 49, 44, 40, 40, 44, 49, 55, 59, 64, 54, 48, 43, 39, 39, 43, 48, 54, 58, 47, 42, 42, 47, 53, 46, 41, 38, 37, 37, 38, 41, 46, 53, 58, 64, 67, 69, 70, 72], [36, 35, 71, 34, 33, 32, 31, 63, 30, 29, 62, 66, 68, 28, 27, 61, 26, 25, 24, 23, 22, 45, 52, 57, 60, 65, 21, 20, 19, 51, 56, 18, 17, 50, 16, 15, 14, 13, 40, 44, 49, 55, 59, 12, 11, 10, 9, 8, 39, 43, 48, 54, 7, 6, 5, 42, 47, 4, 3, 2, 1, 0, 37, 38, 41, 46, 53, 58, 64, 67, 69, 70]],\"toyplot\");\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\"],\"t733dd9f29c3b47a98148943b627301cd\",\"vertex_data\",\"graph vertex data\",[\"x\", \"y\"],[[-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -1.0, -1.0, -2.0, -1.0, -2.0, -3.0, -1.0, -2.0, -3.0, -1.0, -4.0, -2.0, -3.0, -4.0, -1.0, -1.0, -1.0, -5.0, -4.0, -5.0, -2.0, -2.0, -6.0, -6.0, -3.0, -1.0, -1.0, -7.0, -4.0, -2.0, -8.0, -3.0, -9.0, -10.0, -1.0, -11.0], [0.0, 3.0, 2.0, 4.0, 1.0, 7.0, 6.0, 5.0, 11.0, 8.0, 10.0, 9.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 20.0, 19.0, 21.0, 27.0, 28.0, 25.0, 22.0, 23.0, 24.0, 26.0, 29.0, 30.0, 31.0, 32.0, 33.0, 34.0, 36.0, 35.0, 1.5, 13.5, 1.75, 9.5, 14.25, 2.875, 6.5, 9.75, 15.125, 17.5, 1.9375, 5.75, 9.375, 16.3125, 19.5, 27.5, 22.5, 3.84375, 10.6875, 17.90625, 26.25, 23.25, 7.265625, 19.453125, 24.75, 29.5, 31.5, 13.359375, 25.375, 30.5, 19.3671875, 31.75, 25.55859375, 29.779296875, 35.5, 32.6396484375]],\"toyplot\");\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\"],\"t733dd9f29c3b47a98148943b627301cd\",\"edge_data\",\"graph edge data\",[\"source\", \"target\"],[[71, 71, 72, 70, 68, 63, 63, 66, 62, 62, 66, 68, 69, 65, 58, 53, 53, 58, 61, 57, 52, 52, 57, 61, 65, 67, 60, 51, 51, 56, 46, 46, 50, 45, 41, 38, 38, 41, 45, 50, 56, 60, 64, 55, 49, 44, 40, 40, 44, 49, 55, 59, 48, 43, 43, 48, 54, 47, 42, 39, 37, 37, 39, 42, 47, 54, 59, 64, 67, 69, 70, 72], [36, 35, 71, 34, 33, 32, 31, 63, 30, 29, 62, 66, 68, 28, 27, 26, 25, 53, 58, 24, 23, 22, 52, 57, 61, 65, 21, 20, 19, 51, 18, 17, 46, 16, 15, 14, 13, 38, 41, 45, 50, 56, 60, 12, 11, 10, 9, 8, 40, 44, 49, 55, 7, 6, 5, 43, 48, 4, 3, 2, 1, 0, 37, 39, 42, 47, 54, 59, 64, 67, 69, 70]],\"toyplot\");\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\"],\"te55584c5a73e47ee9ed82daaf280b5f0\",\"vertex_data\",\"graph vertex data\",[\"x\", \"y\"],[[-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -1.0, -1.0, -1.0, -2.0, -1.0, -1.0, -2.0, -2.0, -1.0, -1.0, -3.0, -2.0, -3.0, -3.0, -1.0, -2.0, -4.0, -4.0, -4.0, -1.0, -3.0, -5.0, -5.0, -4.0, -1.0, -1.0, -1.0, -6.0, -5.0, -2.0, -7.0, -3.0, -8.0, -9.0, -1.0, -10.0], [1.0, 2.0, 3.0, 4.0, 0.0, 5.0, 6.0, 7.0, 11.0, 8.0, 9.0, 10.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 20.0, 18.0, 19.0, 21.0, 22.0, 24.0, 23.0, 25.0, 26.0, 27.0, 28.0, 30.0, 29.0, 31.0, 32.0, 33.0, 34.0, 35.0, 36.0, 1.5, 9.5, 13.5, 2.25, 2.0, 5.5, 9.25, 14.25, 16.5, 23.0, 2.125, 6.25, 9.625, 15.375, 19.0, 23.0, 4.1875, 10.8125, 17.1875, 20.0, 24.0, 7.5, 18.59375, 25.0, 27.5, 29.5, 31.5, 13.046875, 26.25, 30.5, 19.6484375, 31.75, 25.69921875, 29.849609375, 35.5, 32.6748046875]],\"toyplot\");\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\"],\"te55584c5a73e47ee9ed82daaf280b5f0\",\"edge_data\",\"graph edge data\",[\"source\", \"target\"],[[71, 71, 72, 70, 68, 63, 63, 66, 62, 62, 66, 68, 69, 61, 61, 65, 60, 57, 52, 46, 46, 52, 57, 60, 65, 67, 56, 56, 59, 51, 51, 55, 45, 45, 50, 44, 39, 39, 44, 50, 55, 59, 64, 54, 49, 43, 38, 38, 43, 49, 54, 58, 48, 42, 42, 48, 53, 41, 41, 47, 40, 37, 37, 40, 47, 53, 58, 64, 67, 69, 70, 72], [36, 35, 71, 34, 33, 32, 31, 63, 30, 29, 62, 66, 68, 28, 27, 61, 26, 25, 24, 23, 22, 46, 52, 57, 60, 65, 21, 20, 56, 19, 18, 51, 17, 16, 45, 15, 14, 13, 39, 44, 50, 55, 59, 12, 11, 10, 9, 8, 38, 43, 49, 54, 7, 6, 5, 42, 48, 4, 3, 41, 2, 1, 0, 37, 40, 47, 53, 58, 64, 67, 69, 70]],\"toyplot\");\n",
       "(function(tables, context_menu, io, owner_id, key, label, names, columns, filename)\n",
       "        {\n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mtre = toytree.mtree(tet.trees.boots)\n",
    "mtre.treelist = [i.root([\"HE\", \"NI\"]) for i in mtre.treelist]\n",
    "mtre.draw_cloud_tree(\n",
    "    height=600, \n",
    "    width=400,\n",
    "    use_edge_lengths=False, \n",
    "    html=True,\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Continuing from a checkpoint\n",
    "If you want to run more bootstrap replicates you can simply reinit an analysis object with the same `name` and set the number of bootstrap replicates to a higher value and call `.run()` again. If you try calling `.run()` again and you have already completed all of the requested results then it will simply print that it is finished. If you want it to overwrite existing results with the same name then you can use the `force` arg in run. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "16 bootstrap result trees already exist for virentes-min4.\n"
     ]
    }
   ],
   "source": [
    "# analysis is finished so it will not run\n",
    "tet.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here I set the number of requested bootstrap replicates to 20 and call `.run()` again. You can see that the analysis continues from 17, since we already completed 16 bootstrap replicates earlier, and will go until it completes 20 bootstraps. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parallel connection | d9118d19223a: 40 cores\n",
      "[####################] 100% 0:01:49 | bootstrap inference 17 | mean SNPs/quartet: 78350  \n",
      "[####################] 100% 0:01:34 | bootstrap inference 18 | mean SNPs/quartet: 77653 \n",
      "[####################] 100% 0:01:32 | bootstrap inference 19 | mean SNPs/quartet: 78560 \n",
      "[####################] 100% 0:01:32 | bootstrap inference 20 | mean SNPs/quartet: 78380 \n"
     ]
    }
   ],
   "source": [
    "# increase nboots and continue from existing analysis object\n",
    "tet.params.nboots = 20\n",
    "tet.run(auto=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternatively, maybe you are returning to this analysis after a while and decide you want to do more bootstraps. You can re-load the analysis object by entering the same `name` and `working_dir` as in the original analysis, and adding the `load=True` argument. I set the number of bootstraps to 25 now. This will load the results from before and add new results when you call `.run()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # re-init analysis object (will load existing results at this name)\n",
    "# tet = ipa.tetrad(\n",
    "#     name=\"virentes-min4\",\n",
    "#     data=data,\n",
    "#     nquartets=1e6,\n",
    "#     nboots=25,\n",
    "#     load=True,\n",
    "# )\n",
    "# tet.run(auto=True)"
   ]
  }
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