testdocs/analysis/cookbook-bpp-00-ipcoal.ipynb

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    "\n",
    "# <span style=\"color:gray\">ipyrad-analysis toolkit:</span> bpp (alg 00)\n",
    "\n",
    "The ipyrad-analysis `bpp` tool w/ algorithm 00 can be used infer parameters on a fixed species tree. Please see the [full BPP documentation](https://github.com/bpp/bpp/blob/master/bppDOC.pdf) for details about BPP analyses. The ipyrad-analysis wrapper is intended to make it easy to auomate many BPP analyses on large RAD-seq datasets. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# conda install ipyrad -c conda-forge -c bioconda\n",
    "# conda install ipcoal -c conda-forge \n",
    "# conda install bpp -c conda-forge -c eaton-lab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ipyrad.analysis as ipa\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import toytree\n",
    "import toyplot\n",
    "import ipcoal"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simulate data under a specified model\n",
    "We are interested in estimating the Ne and divergence time values on this tree."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
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   "source": [
    "# generate a tree with divergence times in generations\n",
    "TREE = toytree.rtree.unittree(ntips=5, treeheight=3e6, seed=123)\n",
    "\n",
    "# set larger Ne on one lineage than the other\n",
    "TREE = TREE.set_node_values(\"Ne\", {i: 5e5 for i in (0, 1, 2, 5, 6)}, default=2e5)\n",
    "\n",
    "# draw in 'p' style to show Ne\n",
    "TREE.draw(ts='p', node_hover=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a simulation model for this tree/network with 3 diploids per spp.\n",
    "model = ipcoal.Model(tree=TREE, nsamples=6, mut=1e-8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "wrote 1000 loci to /tmp/test-bpp.seqs.hdf5\n"
     ]
    }
   ],
   "source": [
    "# simulate N loci\n",
    "model.sim_loci(nloci=1000, nsites=150)\n",
    "\n",
    "# write result to a database file\n",
    "model.write_loci_to_hdf5(name=\"test-bpp\", outdir=\"/tmp\", diploid=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### *True* measurements that will inform our priors\n",
    "In BPP we can set a prior on the percent divergence $\\tau$ (pronounced Tau) between the root and tips of the tree. When combined with an estimate of the per-site-per-generation mutation rate ($\\mu$) and generation time (g) this can be converted into units of years. In our `ipcoal` simulation we actually have access to the root ancestral sequence as well as the tip sequences, so we can measure the true percent sequence divergence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.034186666666666664"
      ]
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     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# concatenate seqs into single alignment\n",
    "concat = np.concatenate(model.seqs, axis=1)\n",
    "\n",
    "# get ancestral root node sequence\n",
    "rootseq = np.concatenate(model.ancestral_seq)\n",
    "\n",
    "# what is sequence divergence relative to root?\n",
    "np.sum(rootseq != concat[0]) / rootseq.size"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In addition to setting a prior on Tau we must also set a prior on $\\theta$ (pronounced theta), the population mutation rate ($\\theta$=4Ne$\\mu$). Here we know the Ne and $\\mu$ used in the simulation scenario, so again we can calculate it exactly. For real data we will not know these prior values precisely, and so we will want to put a wide prior to incorporate our uncertainty. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.008"
      ]
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     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "# theta in simulation\n",
    "4 * TREE.treenode.Ne * 1e-8"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### BPP analysis setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "SEQS = \"/tmp/test-bpp.seqs.hdf5\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "IMAP = {\n",
    "    \"r0\": [\"r0-0\", \"r0-1\", \"r0-2\"],\n",
    "    \"r1\": [\"r1-0\", \"r1-1\", \"r1-2\"],\n",
    "    \"r2\": [\"r2-0\", \"r2-1\", \"r2-2\"],\n",
    "    \"r3\": [\"r3-0\", \"r3-1\", \"r3-2\"],\n",
    "    \"r4\": [\"r4-0\", \"r4-1\", \"r4-2\"],\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a bpp object to run algorithm 00\n",
    "tool = ipa.bpp(\n",
    "    name=\"test-bpp\",\n",
    "    workdir=\"/tmp\",\n",
    "    data=SEQS,\n",
    "    guidetree=TREE,\n",
    "    imap=IMAP,\n",
    "    infer_sptree=0,\n",
    "    infer_delimit=0,\n",
    "    maxloci=1000,\n",
    "    burnin=2e3,\n",
    "    nsample=2e4,\n",
    "    sampfreq=5,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The parameters of the object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'binary': '/tmp/bpp-4.1.4-linux-x86_64/bin/bpp',\n",
       " 'infer_sptree': 0,\n",
       " 'infer_delimit': 0,\n",
       " 'infer_delimit_args': (0, 2),\n",
       " 'speciesmodelprior': 1,\n",
       " 'seed': 12345,\n",
       " 'burnin': 2000,\n",
       " 'nsample': 20000,\n",
       " 'sampfreq': 5,\n",
       " 'thetaprior': (3, 0.002),\n",
       " 'tauprior': (3, 0.002),\n",
       " 'phiprior': (1, 1),\n",
       " 'usedata': 1,\n",
       " 'cleandata': 0,\n",
       " 'finetune': (0.01, 0.02, 0.03, 0.04, 0.05, 0.01, 0.01),\n",
       " 'copied': False}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tool.kwargs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set priors and plot priors of transformed values\n",
    "\n",
    "Here we will enter our expectations on the generation time and mutation rate of our simulated organisms so that we can toggle the theta and tau priors until the resulting prior distributions on Ne and T seem reasonable. \n",
    "\n",
    "In our simulation the root divergence time was 3M generations. Assuming a generation time of 1 and prior on root tau of ~3% (as we measured above) yields a prior on the root divergence time with 95% CI from about 0.5-6.5 Ma. So this is a pretty good but not highly informative prior. \n",
    "\n",
    "Similarly, our simulation used Ne=200K or 500K on different lineages. If we assume a wide prior on the per-site per-generation mutation rate ($\\mu$) with highest density of 1e-8 (as used in our simulations) and a prior on $\\theta$ with highest density at about 0.01 (we calculated 0.008 from the simulated data above) yields a 95% CI on Ne that is again accurate but not highly informative. \n",
    "\n",
    "These priors incorporate *estimated* knowledge about our organisms, by describing gentime and mutrate as distributions, and puts informative but wide priors on the parameters we hope to infer (theta and tau). \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
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702.1533717386778,91.70938992832218 701.6228336435221,90.73050379050689 701.0922955483663,89.76612986919503 700.5617574532107,88.81703616753566 700.0312193580551,87.88401072104509 699.5006812628993,86.96786194903079 698.9701431677437,86.06941900664359 698.4396050725879,85.18953213717444 697.9090669774323,84.32907302417911 697.3785288822767,83.48893514297976 696.847990787121,82.67003411105615 696.3174526919652,81.87330803679673 695.7869145968095,81.09971786603928 695.2563765016539,80.35024772578248 694.7258384064982,79.6259052644022 694.1953003113424,78.92772198764963 693.6647622161868,78.25675358965303 693.1342241210311,77.6140802780813 692.6036860258754,77.00080709256069 692.0731479307196,76.41806421536288 691.542609835564,75.86700727330475 691.0120717404084,75.34881762971453 690.4815336452526,74.86470266522865 689.950995550097,74.41589604608205 689.4204574549414,74.0036579784493 688.8899193597856,73.62927544727506 688.3593812646299,73.29406243790784 687.8288431694742,72.99936013870978 687.2983050743185,72.7465371226695 686.7677669791628,72.53698950587841 686.2372288840072,72.37214108055437 685.7066907888516,72.25344342010239 685.1761526936958,72.18237595348984 684.6456145985402,72.16044600598165 684.1150765033844,72.18918880302606 683.5845384082287,72.27016743380399 683.0540003130731,72.40497277064894 682.5234622179173,72.59522334020558 681.9929241227617,72.8425651418282\" style=\"fill:rgb(55.3%,62.7%,79.6%);fill-opacity:1.0;opacity:0.25;stroke:none\"></polygon></g></g><g class=\"toyplot-coordinates-Axis\" id=\"td1517c5366a04206bf31ac8d9fb29a2c\" transform=\"translate(650.0,250.0)translate(0,10.0)\"><line style=\"\" x1=\"4.097222511367704\" x2=\"223.84957222501328\" y1=\"0\" y2=\"0\"></line><g><g transform=\"translate(0.0,6)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:10.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-2.78\" y=\"8.555\">0</text></g><g transform=\"translate(75.0,6)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:10.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-16.68\" y=\"8.555\">250000</text></g><g transform=\"translate(150.0,6)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:10.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-16.68\" y=\"8.555\">500000</text></g><g transform=\"translate(225.0,6)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:10.0px;font-weight:normal;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-16.68\" y=\"8.555\">750000</text></g></g><g transform=\"translate(112.5,22)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:12.0px;font-weight:bold;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-32.004000000000005\" y=\"10.265999999999998\">prior on Ne</text></g><g class=\"toyplot-coordinates-Axis-coordinates\" style=\"visibility:hidden\" transform=\"\"><line style=\"stroke:rgb(43.9%,50.2%,56.5%);stroke-opacity:1.0;stroke-width:1.0\" x1=\"0\" x2=\"0\" y1=\"-3.0\" y2=\"4.5\"></line><text style=\"alignment-baseline:alphabetic;fill:rgb(43.9%,50.2%,56.5%);fill-opacity:1.0;font-size:10px;font-weight:normal;stroke:none;text-anchor:middle\" x=\"0\" y=\"-6\"></text></g></g><g class=\"toyplot-coordinates-Axis\" id=\"tcd493f9d52604d539e2a8ab7e6bc15ae\" transform=\"translate(650.0,250.0)rotate(-90.0)translate(0,-10.0)\"><line style=\"\" x1=\"0\" x2=\"177.83955399401833\" y1=\"0\" y2=\"0\"></line><g class=\"toyplot-coordinates-Axis-coordinates\" style=\"visibility:hidden\" transform=\"\"><line style=\"stroke:rgb(43.9%,50.2%,56.5%);stroke-opacity:1.0;stroke-width:1.0\" x1=\"0\" x2=\"0\" y1=\"3.0\" y2=\"-4.5\"></line><text style=\"alignment-baseline:hanging;fill:rgb(43.9%,50.2%,56.5%);fill-opacity:1.0;font-size:10px;font-weight:normal;stroke:none;text-anchor:middle\" x=\"0\" y=\"6\"></text></g></g><g transform=\"translate(762.5,42.0)\"><text style=\"fill:rgb(16.1%,15.3%,14.1%);fill-opacity:1.0;font-family:helvetica;font-size:14.0px;font-weight:bold;stroke:none;vertical-align:baseline;white-space:pre\" x=\"-76.265\" y=\"-4.823\">95% CI: 29742 - 565130</text></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\"] = \"t563f006b85534b1998120a9152de98a1\";\n",
       "modules[\"toyplot/root\"] = (function(root_id)\n",
       "    {\n",
       "        return document.querySelector(\"#\" + root_id);\n",
       "    })(modules[\"toyplot/root/id\"]);\n",
       "modules[\"toyplot/canvas/id\"] = \"t2b4412efcca14f2289d8399871ea33b3\";\n",
       "modules[\"toyplot/canvas\"] = (function(canvas_id)\n",
       "    {\n",
       "        return document.querySelector(\"#\" + canvas_id);\n",
       "    })(modules[\"toyplot/canvas/id\"]);\n",
       "modules[\"toyplot/menus/context\"] = (function(root, canvas)\n",
       "    {\n",
       "        var wrapper = document.createElement(\"div\");\n",
       "        wrapper.innerHTML = \"<ul class='toyplot-context-menu' style='background:#eee; border:1px solid #b8b8b8; border-radius:5px; box-shadow: 0px 0px 8px rgba(0%,0%,0%,0.25); margin:0; padding:3px 0; position:fixed; visibility:hidden;'></ul>\"\n",
       "        var menu = wrapper.firstChild;\n",
       "\n",
       "        root.appendChild(menu);\n",
       "\n",
       "        var items = [];\n",
       "\n",
       "        var ignore_mouseup = null;\n",
       "        function open_menu(e)\n",
       "        {\n",
       "            var show_menu = false;\n",
       "            for(var index=0; index != items.length; ++index)\n",
       "            {\n",
       "                var item = items[index];\n",
       "                if(item.show(e))\n",
       "                {\n",
       "                    item.item.style.display = \"block\";\n",
       "                    show_menu = true;\n",
       "                }\n",
       "                else\n",
       "                {\n",
       "                    item.item.style.display = \"none\";\n",
       "                }\n",
       "            }\n",
       "\n",
       "            if(show_menu)\n",
       "            {\n",
       "                ignore_mouseup = true;\n",
       "                menu.style.left = (e.clientX + 1) + \"px\";\n",
       "                menu.style.top = (e.clientY - 5) + \"px\";\n",
       "                menu.style.visibility = \"visible\";\n",
       "                e.stopPropagation();\n",
       "                e.preventDefault();\n",
       "            }\n",
       "        }\n",
       "\n",
       "        function close_menu()\n",
       "        {\n",
       "            menu.style.visibility = \"hidden\";\n",
       "        }\n",
       "\n",
       "        function contextmenu(e)\n",
       "        {\n",
       "            open_menu(e);\n",
       "        }\n",
       "\n",
       "        function mousemove(e)\n",
       "        {\n",
       "            ignore_mouseup = false;\n",
       "        }\n",
       "\n",
       "        function mouseup(e)\n",
       "        {\n",
       "            if(ignore_mouseup)\n",
       "            {\n",
       "                ignore_mouseup = false;\n",
       "                return;\n",
       "            }\n",
       "            close_menu();\n",
       "        }\n",
       "\n",
       "        function keydown(e)\n",
       "        {\n",
       "            if(e.key == \"Escape\" || e.key == \"Esc\" || e.keyCode == 27)\n",
       "            {\n",
       "                close_menu();\n",
       "            }\n",
       "        }\n",
       "\n",
       "        canvas.addEventListener(\"contextmenu\", contextmenu);\n",
       "        canvas.addEventListener(\"mousemove\", mousemove);\n",
       "        document.addEventListener(\"mouseup\", mouseup);\n",
       "        document.addEventListener(\"keydown\", keydown);\n",
       "\n",
       "        var module = {};\n",
       "        module.add_item = function(label, show, activate)\n",
       "        {\n",
       "            var wrapper = document.createElement(\"div\");\n",
       "            wrapper.innerHTML = \"<li class='toyplot-context-menu-item' style='background:#eee; color:#333; padding:2px 20px; list-style:none; margin:0; text-align:left;'>\" + label + \"</li>\"\n",
       "            var item = wrapper.firstChild;\n",
       "\n",
       "            items.push({item: item, show: show});\n",
       "\n",
       "            function mouseover()\n",
       "            {\n",
       "                this.style.background = \"steelblue\";\n",
       "                this.style.color = \"white\";\n",
       "            }\n",
       "\n",
       "            function mouseout()\n",
       "            {\n",
       "                this.style.background = \"#eee\";\n",
       "                this.style.color = \"#333\";\n",
       "            }\n",
       "\n",
       "            function choose_item(e)\n",
       "            {\n",
       "                close_menu();\n",
       "                activate();\n",
       "\n",
       "                e.stopPropagation();\n",
       "                e.preventDefault();\n",
       "            }\n",
       "\n",
       "            item.addEventListener(\"mouseover\", mouseover);\n",
       "            item.addEventListener(\"mouseout\", mouseout);\n",
       "            item.addEventListener(\"mouseup\", choose_item);\n",
       "            item.addEventListener(\"contextmenu\", choose_item);\n",
       "\n",
       "            menu.appendChild(item);\n",
       "        };\n",
       "        return module;\n",
       "    })(modules[\"toyplot/root\"],modules[\"toyplot/canvas\"]);\n",
       "modules[\"toyplot/io\"] = (function()\n",
       "    {\n",
       "        var module = {};\n",
       "        module.save_file = function(mime_type, charset, data, filename)\n",
       "        {\n",
       "            var uri = \"data:\" + mime_type + \";charset=\" + charset + \",\" + data;\n",
       "            uri = encodeURI(uri);\n",
       "\n",
       "            var link = document.createElement(\"a\");\n",
       "            if(typeof link.download != \"undefined\")\n",
       "            {\n",
       "              link.href = uri;\n",
       "              link.style = \"visibility:hidden\";\n",
       "              link.download = filename;\n",
       "\n",
       "              document.body.appendChild(link);\n",
       "              link.click();\n",
       "              document.body.removeChild(link);\n",
       "            }\n",
       "            else\n",
       "            {\n",
       "              window.open(uri);\n",
       "            }\n",
       "        };\n",
       "        return module;\n",
       "    })();\n",
       "modules[\"toyplot.coordinates.Axis\"] = (\n",
       "        function(canvas)\n",
       "        {\n",
       "            function sign(x)\n",
       "            {\n",
       "                return x < 0 ? -1 : x > 0 ? 1 : 0;\n",
       "            }\n",
       "\n",
       "            function mix(a, b, amount)\n",
       "            {\n",
       "                return ((1.0 - amount) * a) + (amount * b);\n",
       "            }\n",
       "\n",
       "            function log(x, base)\n",
       "            {\n",
       "                return Math.log(Math.abs(x)) / Math.log(base);\n",
       "            }\n",
       "\n",
       "            function in_range(a, x, b)\n",
       "            {\n",
       "                var left = Math.min(a, b);\n",
       "                var right = Math.max(a, b);\n",
       "                return left <= x && x <= right;\n",
       "            }\n",
       "\n",
       "            function inside(range, projection)\n",
       "            {\n",
       "                for(var i = 0; i != projection.length; ++i)\n",
       "                {\n",
       "                    var segment = projection[i];\n",
       "                    if(in_range(segment.range.min, range, segment.range.max))\n",
       "                        return true;\n",
       "                }\n",
       "                return false;\n",
       "            }\n",
       "\n",
       "            function to_domain(range, projection)\n",
       "            {\n",
       "                for(var i = 0; i != projection.length; ++i)\n",
       "                {\n",
       "                    var segment = projection[i];\n",
       "                    if(in_range(segment.range.bounds.min, range, segment.range.bounds.max))\n",
       "                    {\n",
       "                        if(segment.scale == \"linear\")\n",
       "                        {\n",
       "                            var amount = (range - segment.range.min) / (segment.range.max - segment.range.min);\n",
       "                            return mix(segment.domain.min, segment.domain.max, amount)\n",
       "                        }\n",
       "                        else if(segment.scale[0] == \"log\")\n",
       "                        {\n",
       "                            var amount = (range - segment.range.min) / (segment.range.max - segment.range.min);\n",
       "                            var base = segment.scale[1];\n",
       "                            return sign(segment.domain.min) * Math.pow(base, mix(log(segment.domain.min, base), log(segment.domain.max, base), amount));\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            var axes = {};\n",
       "\n",
       "            function display_coordinates(e)\n",
       "            {\n",
       "                var current = canvas.createSVGPoint();\n",
       "                current.x = e.clientX;\n",
       "                current.y = e.clientY;\n",
       "\n",
       "                for(var axis_id in axes)\n",
       "                {\n",
       "                    var axis = document.querySelector(\"#\" + axis_id);\n",
       "                    var coordinates = axis.querySelector(\".toyplot-coordinates-Axis-coordinates\");\n",
       "                    if(coordinates)\n",
       "                    {\n",
       "                        var projection = axes[axis_id];\n",
       "                        var local = current.matrixTransform(axis.getScreenCTM().inverse());\n",
       "                        if(inside(local.x, projection))\n",
       "                        {\n",
       "                            var domain = to_domain(local.x, projection);\n",
       "                            coordinates.style.visibility = \"visible\";\n",
       "                            coordinates.setAttribute(\"transform\", \"translate(\" + local.x + \")\");\n",
       "                            var text = coordinates.querySelector(\"text\");\n",
       "                            text.textContent = domain.toFixed(2);\n",
       "                        }\n",
       "                        else\n",
       "                        {\n",
       "                            coordinates.style.visibility= \"hidden\";\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            canvas.addEventListener(\"click\", display_coordinates);\n",
       "\n",
       "            var module = {};\n",
       "            module.show_coordinates = function(axis_id, projection)\n",
       "            {\n",
       "                axes[axis_id] = projection;\n",
       "            }\n",
       "\n",
       "            return module;\n",
       "        })(modules[\"toyplot/canvas\"]);\n",
       "(function(tables, context_menu, io, owner_id, key, label, names, columns, filename)\n",
       "        {\n",
       "            tables.set(owner_id, key, names, columns);\n",
       "\n",
       "            var owner = document.querySelector(\"#\" + owner_id);\n",
       "            function show_item(e)\n",
       "            {\n",
       "                return owner.contains(e.target);\n",
       "            }\n",
       "\n",
       "            function choose_item()\n",
       "            {\n",
       "                io.save_file(\"text/csv\", \"utf-8\", tables.get_csv(owner_id, key), filename + \".csv\");\n",
       "            }\n",
       "\n",
       "            context_menu.add_item(\"Save \" + label + \" as CSV\", show_item, choose_item);\n",
       "        })(modules[\"toyplot/tables\"],modules[\"toyplot/menus/context\"],modules[\"toyplot/io\"],\"t6ff564dd991a42beb112cc8814773e9a\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[0.4938332574742169, 0.5133361359927945, 0.5328390145113721, 0.5523418930299496, 0.5718447715485273, 0.5913476500671048, 0.6108505285856825, 0.63035340710426, 0.6498562856228376, 0.6693591641414152, 0.6888620426599927, 0.7083649211785703, 0.7278677996971479, 0.7473706782157254, 0.7668735567343031, 0.7863764352528807, 0.8058793137714582, 0.8253821922900358, 0.8448850708086134, 0.8643879493271909, 0.8838908278457686, 0.9033937063643461, 0.9228965848829238, 0.9423994634015014, 0.9619023419200788, 0.9814052204386565, 1.0009080989572339, 1.0204109774758117, 1.0399138559943892, 1.0594167345129668, 1.0789196130315444, 1.098422491550122, 1.1179253700686995, 1.1374282485872769, 1.1569311271058547, 1.1764340056244322, 1.1959368841430098, 1.2154397626615874, 1.2349426411801652, 1.2544455196987427, 1.27394839821732, 1.2934512767358977, 1.3129541552544752, 1.3324570337730528, 1.3519599122916306, 1.3714627908102082, 1.3909656693287857, 1.4104685478473633, 1.4299714263659407, 1.4494743048845182, 1.468977183403096, 1.4884800619216736, 1.5079829404402512, 1.5274858189588287, 1.5469886974774065, 1.5664915759959837, 1.5859944545145614, 1.605497333033139, 1.6250002115517166, 1.6445030900702942, 1.664005968588872, 1.6835088471074495, 1.703011725626027, 1.7225146041446044, 1.742017482663182, 1.7615203611817596, 1.7810232397003374, 1.800526118218915, 1.8200289967374925, 1.83953187525607, 1.8590347537746474, 1.878537632293225, 1.8980405108118026, 1.9175433893303804, 1.937046267848958, 1.9565491463675355, 1.976052024886113, 1.9955549034046909, 2.0150577819232685, 2.034560660441846, 2.054063538960423, 2.073566417479001, 2.0930692959975787, 2.1125721745161563, 2.132075053034734, 2.1515779315533115, 2.171080810071889, 2.1905836885904666, 2.210086567109044, 2.2295894456276217, 2.2490923241461993, 2.268595202664777, 2.2880980811833544, 2.307600959701932, 2.3271038382205096, 2.346606716739087, 2.3661095952576647, 2.3856124737762423, 2.40511535229482, 2.4246182308133974], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [7321732.91354191, 9107708.965652278, 11165070.42639679, 13502897.907129925, 16125542.380367957, 19032288.731942393, 22217171.560918752, 25668945.270756107, 29371204.21790602, 33302643.197091136, 37437444.00880394, 41745770.36269832, 46194350.94338504, 50747129.070415564, 55365956.9462488, 60011312.89707656, 64643021.143008314, 69220955.34663029, 73705709.34004048, 78059220.88207743, 82245336.92104043, 86230311.51858558, 89983230.22833312, 93476357.23579139, 96685403.88960724, 99589719.33994307, 102172405.81565523, 104420362.59992915, 106324263.9984282, 107878477.53966758, 109080929.31745042, 109932923.79966076, 110438925.61094096, 110606310.77651791, 110445094.71993254, 109967643.96845774, 109188378.06577262, 108123467.64978606, 106790534.05032374, 105208355.12004784, 103396581.35339478, 101375465.69036134, 99165609.75980692, 96787728.70291959, 94262436.14133325, 91610050.32326663, 88850422.00011097, 86002784.15802276, 83085623.35573016, 80116572.10065909, 77112321.429364, 74088552.64269952, 71059886.97815314, 68039851.87757993, 65040862.42430769, 62074216.47489268, 59150101.9934776, 56277615.10642117, 53464787.42746731, 50718621.255279884, 48045131.31194197, 45449391.7695829, 42935587.39956151, 40507067.771771096, 38166403.52822753, 35915443.85296009, 33755374.357586734, 31686774.697242614, 29709675.323518947, 27823612.86877057, 26027683.738791425, 24320595.56789707, 22700716.261525746, 21166120.41635896, 19714632.966614477, 18343869.957610384, 17051276.394092254, 15834161.151368115, 14689728.972293785, 13615109.60290944, 12607384.144415548, 11663608.719560724, 10780835.567784583, 9956131.696012823, 9186595.221213214, 8469369.547076378, 7801655.520836768, 7180721.71764159, 6603912.999332027, 6068657.492317097, 5572472.125672574, 5112966.865937894, 4687847.779538729, 4294919.04753616, 3932084.0506764287, 3597345.635647156, 3288805.6661762185, 3004663.955256793, 2743216.6674482673, 2502854.2729749875]],\"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\"],\"t02be16a01ebd49e5903c356ed6742e46\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[0.6265512527549928, 0.6412844137358982, 0.6560175747168034, 0.6707507356977088, 0.6854838966786142, 0.7002170576595196, 0.7149502186404249, 0.7296833796213302, 0.7444165406022356, 0.7591497015831411, 0.7738828625640464, 0.7886160235449516, 0.8033491845258571, 0.8180823455067624, 0.8328155064876679, 0.8475486674685732, 0.8622818284494784, 0.8770149894303839, 0.8917481504112894, 0.9064813113921947, 0.9212144723731, 0.9359476333540054, 0.9506807943349107, 0.9654139553158161, 0.9801471162967215, 0.9948802772776267, 1.0096134382585322, 1.0243465992394376, 1.039079760220343, 1.0538129212012481, 1.0685460821821535, 1.083279243163059, 1.0980124041439643, 1.1127455651248697, 1.127478726105775, 1.1422118870866804, 1.1569450480675858, 1.1716782090484912, 1.1864113700293966, 1.2011445310103017, 1.215877691991207, 1.2306108529721127, 1.2453440139530179, 1.2600771749339232, 1.2748103359148286, 1.289543496895734, 1.3042766578766394, 1.3190098188575448, 1.33374297983845, 1.3484761408193555, 1.363209301800261, 1.3779424627811663, 1.3926756237620714, 1.4074087847429768, 1.4221419457238824, 1.4368751067047876, 1.451608267685693, 1.4663414286665983, 1.4810745896475035, 1.495807750628409, 1.5105409116093145, 1.5252740725902199, 1.540007233571125, 1.5547403945520306, 1.569473555532936, 1.5842067165138412, 1.5989398774947465, 1.613673038475652, 1.6284061994565575, 1.6431393604374627, 1.657872521418368, 1.6726056823992732, 1.6873388433801788, 1.7020720043610842, 1.7168051653419896, 1.7315383263228947, 1.7462714873038, 1.7610046482847057, 1.7757378092656109, 1.7904709702465162, 1.8052041312274216, 1.8199372922083268, 1.8346704531892324, 1.8494036141701378, 1.8641367751510431, 1.8788699361319483, 1.893603097112854, 1.9083362580937593, 1.9230694190746644, 1.9378025800555698, 1.9525357410364752, 1.9672689020173808, 1.982002062998286, 1.9967352239791913, 2.0114683849600965, 2.026201545941002, 2.0409347069219077, 2.055667867902813, 2.070401028883718, 2.0851341898646236], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [24975769.60646568, 27714397.19700585, 30589585.660753053, 33591263.85868285, 36707935.88542662, 39926807.886233784, 43233931.00622135, 46614357.433264725, 50052306.43417308, 53531337.2931973, 57034526.134972945, 60544643.74255155, 64044331.65663045, 67516274.055767, 70943363.16068277, 74308856.17050257, 77596522.01718265, 80790776.50936677, 83876804.72203867, 86840669.7680087, 89669407.35663341, 92351105.80017224, 94874971.36561055, 97231379.08712465, 99411909.34979576, 101409370.72765006, 103217809.7079198, 104832508.05870251, 106249968.69921495, 107467891.01148653, 108485136.59067814, 109301686.46959779, 109918590.87301481, 110337912.56064358, 110562664.80603932, 110596745.03385964, 110444865.1018355, 110112479.1681409, 109605710.03136072, 108931274.77057746, 108096410.44874386, 107108800.57495663, 105976502.9517039, 104707879.46291329, 103311528.2886214, 101796218.96328239, 100170830.62789921, 98444293.76199138, 96625535.62033886, 94723429.54207467, 92746748.24617192, 90704121.1780571, 88603995.92706345, 86454603.6937974, 84263928.7502339, 82039681.80342819, 79789277.14602874, 77519813.45312303, 75238058.0652163, 72950434.58105807, 70663013.57142368, 68381506.21551417, 66111260.65518554, 63857260.85839841, 61624127.78193071, 59416122.62416706, 57237151.96149128, 55090774.56617196, 52980209.70941926, 50908346.760300465, 48877755.89920216, 46890699.77332514, 44949145.931128785, 43054779.88252121, 41209018.64178694, 39413024.62059451, 37667719.74884695, 35973799.711489506, 34331748.19959637, 32741851.0840313, 31204210.429664113, 29718758.277445965, 28285270.130573474, 26903378.08946606, 25572583.588303346, 24292269.693418805, 23061712.93088778, 21880094.617205728, 20746511.67298851, 19659986.90518363, 18619478.748341244, 17623890.46007745, 16672078.769994449, 15762861.985000739, 14895027.557242354, 14067339.123714259, 13278543.029107606, 12527374.345574101, 11812562.404889733, 11132835.859985523]],\"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\"],\"taff90d70c352415e898ede378e0068a5\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[0.9809380288845478, 0.9859638665853735, 0.9909897042861993, 0.9960155419870251, 1.0010413796878508, 1.0060672173886764, 1.011093055089502, 1.0161188927903277, 1.0211447304911536, 1.0261705681919795, 1.0311964058928051, 1.0362222435936308, 1.0412480812944565, 1.046273918995282, 1.051299756696108, 1.0563255943969336, 1.0613514320977593, 1.0663772697985852, 1.0714031074994108, 1.0764289452002367, 1.0814547829010623, 1.086480620601888, 1.0915064583027136, 1.0965322960035393, 1.101558133704365, 1.1065839714051908, 1.1116098091060167, 1.1166356468068424, 1.121661484507668, 1.1266873222084937, 1.1317131599093195, 1.1367389976101452, 1.1417648353109708, 1.1467906730117965, 1.1518165107126224, 1.156842348413448, 1.161868186114274, 1.1668940238150995, 1.1719198615159252, 1.1769456992167509, 1.1819715369175765, 1.1869973746184024, 1.192023212319228, 1.197049050020054, 1.2020748877208796, 1.2071007254217052, 1.2121265631225309, 1.2171524008233567, 1.2221782385241824, 1.227204076225008, 1.232229913925834, 1.2372557516266596, 1.2422815893274854, 1.247307427028311, 1.2523332647291368, 1.2573591024299624, 1.262384940130788, 1.2674107778316137, 1.2724366155324396, 1.2774624532332652, 1.2824882909340911, 1.2875141286349168, 1.2925399663357426, 1.2975658040365683, 1.302591641737394, 1.3076174794382196, 1.3126433171390453, 1.3176691548398711, 1.3226949925406968, 1.3277208302415227, 1.3327466679423483, 1.337772505643174, 1.3427983433439996, 1.3478241810448255, 1.3528500187456511, 1.3578758564464768, 1.3629016941473027, 1.3679275318481283, 1.372953369548954, 1.3779792072497796, 1.3830050449506053, 1.3880308826514312, 1.3930567203522568, 1.3980825580530825, 1.4031083957539083, 1.4081342334547342, 1.4131600711555599, 1.4181859088563855, 1.4232117465572112, 1.4282375842580368, 1.4332634219588625, 1.4382892596596881, 1.443315097360514, 1.4483409350613399, 1.4533667727621655, 1.4583926104629914, 1.463418448163817, 1.4684442858646427, 1.4734701235654684, 1.478495961266294], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [99523846.52943501, 100222749.46268244, 100900048.09035979, 101555509.31600001, 102188916.81851299, 102800071.01717559, 103388789.01858264, 103954904.54606494, 104498267.8520825, 105018745.61411406, 105516220.81457905, 105990592.60532883, 106441776.15725844, 106869702.49559912, 107274318.32144566, 107655585.82008557, 108013482.45670511, 108348000.76003337, 108659148.0945011, 108946946.42148772, 109211432.05022123, 109452655.37890361, 109670680.62662928, 109865585.55665374, 110037461.19157615, 110186411.52098548, 110312553.20211807, 110416015.25406928, 110496938.74608524, 110555476.48047596, 110591792.67064591, 110606062.61477068, 110598472.36560483, 110569218.39691824, 110518507.26703428, 110446555.279944, 110353588.14444949, 110239840.63178086, 110105556.23213069, 109950986.81051521, 109776392.2623845, 109582040.16937, 109368205.45556591, 109135170.04470725, 108883222.51860835, 108612657.7772174, 108323776.7006052, 108016885.81322688, 107692296.95075266, 107350326.9297744, 106991297.22065867, 106615533.62382841, 106223365.94972149, 105815127.70267716, 105391155.7689777, 104951790.10926564, 104497373.45554765, 104028251.01297398, 103544770.16657916, 103047280.19315663, 102536131.97842066, 102011677.73961256, 101474270.753676, 100924265.09113556, 100362015.35579011, 99787876.43032365, 99202203.22792722, 98605350.45001563, 97997672.35011415, 97379522.50397179, 96751253.58596782, 96113217.1518402, 95465763.42778753, 94809241.10596344, 94143997.14638469, 93470376.58526354, 92788722.34977232, 92099375.07922733, 91402672.95269084, 90698951.52296685, 89988543.55696726, 89271778.88241763, 88548984.24086508, 87820483.14694588, 87086595.75386263, 86347638.7250185, 85603925.11174762, 84855764.23707882, 84103461.58546676, 83347318.69841157, 82587633.07589747, 81824698.08356331, 81058802.86552759, 80290232.26277158, 79519266.7370009, 78746182.2998849, 77971250.44757651, 77194738.10042177, 76416907.54774946, 75638016.39764535]],\"toyplot\");\n",
       "(function(axis, axis_id, projection)\n",
       "        {\n",
       "            axis.show_coordinates(axis_id, projection);\n",
       "        })(modules[\"toyplot.coordinates.Axis\"],\"t0c3cad44fa9a47f490d92db8624c8f7b\",[{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 2.5, \"min\": 0.4938332574742169}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 225.0, \"min\": 0.0}, \"scale\": \"linear\"}]);\n",
       "(function(axis, axis_id, projection)\n",
       "        {\n",
       "            axis.show_coordinates(axis_id, projection);\n",
       "        })(modules[\"toyplot.coordinates.Axis\"],\"t8209e1ffdb4546cabf20e73a975e3a0e\",[{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 120000000.0, \"min\": 0.0}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 200.0, \"min\": 0.0}, \"scale\": \"linear\"}]);\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\"],\"t1aef600eb6e847ad8c5f03eda41e34cf\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[0.000823483807664998, 0.0011535415943277564, 0.0014835993809905147, 0.0018136571676532734, 0.0021437149543160317, 0.00247377274097879, 0.0028038305276415487, 0.003133888314304307, 0.0034639461009670653, 0.0037940038876298236, 0.004124061674292582, 0.00445411946095534, 0.004784177247618099, 0.005114235034280858, 0.005444292820943616, 0.005774350607606374, 0.0061044083942691325, 0.006434466180931891, 0.006764523967594649, 0.007094581754257407, 0.007424639540920166, 0.007754697327582925, 0.008084755114245683, 0.00841481290090844, 0.0087448706875712, 0.009074928474233957, 0.009404986260896716, 0.009735044047559474, 0.010065101834222233, 0.01039515962088499, 0.01072521740754775, 0.011055275194210507, 0.011385332980873266, 0.011715390767536025, 0.012045448554198783, 0.012375506340861542, 0.0127055641275243, 0.013035621914187058, 0.013365679700849816, 0.013695737487512575, 0.014025795274175332, 0.014355853060838092, 0.01468591084750085, 0.015015968634163608, 0.015346026420826367, 0.015676084207489126, 0.016006141994151884, 0.01633619978081464, 0.016666257567477402, 0.01699631535414016, 0.017326373140802917, 0.017656430927465674, 0.017986488714128435, 0.018316546500791193, 0.01864660428745395, 0.018976662074116708, 0.01930671986077947, 0.019636777647442226, 0.019966835434104983, 0.020296893220767744, 0.0206269510074305, 0.02095700879409326, 0.021287066580756017, 0.021617124367418777, 0.021947182154081535, 0.022277239940744292, 0.022607297727407053, 0.02293735551406981, 0.023267413300732568, 0.023597471087395325, 0.023927528874058086, 0.024257586660720844, 0.0245876444473836, 0.024917702234046362, 0.02524776002070912, 0.025577817807371877, 0.025907875594034634, 0.026237933380697395, 0.026567991167360153, 0.02689804895402291, 0.027228106740685667, 0.02755816452734843, 0.027888222314011186, 0.028218280100673943, 0.028548337887336704, 0.02887839567399946, 0.02920845346066222, 0.029538511247324976, 0.029868569033987737, 0.030198626820650495, 0.030528684607313252, 0.030858742393976013, 0.03118880018063877, 0.03151885796730153, 0.031848915753964285, 0.03217897354062704, 0.03250903132728981, 0.032839089113952565, 0.03316914690061532, 0.03349920468727808], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [14.298411757973746, 21.828280352526207, 29.31629147566, 36.486423257111745, 43.173124908765736, 49.27958690985584, 54.75445118461617, 59.577392813218985, 63.74958197014047, 67.28708915730375, 70.21618701105203, 72.56993551929041, 74.3856682979143, 75.70312941956452, 76.56309003062856, 77.0063245571463, 77.07285965674977, 76.80143182526221, 76.22910553069849, 75.39101522260603, 74.3202029847885, 73.04752988738666, 71.60164386088849, 70.0089905743894, 68.29385664091784, 66.4784366974986, 64.58291766363496, 62.62557487663023, 60.62287591564971, 58.589588818955825, 56.538892116343874, 54.482484676947976, 52.430693838911786, 50.392580663639734, 48.376041460651706, 46.387904973169846, 44.43402481046648, 42.519366869574625, 40.6480916133996, 38.823631170431725, 37.04876129792889, 35.32566830953964, 33.656011113095374, 32.04097853736708, 30.481342150150176, 28.97750478591765, 27.52954501095943, 26.1372577586437, 24.800191368210772, 23.51768125818741, 22.288880460784092, 21.112787237081815, 19.988269984898807, 18.91408964233683, 17.888919780454167, 16.91136456855346, 15.979974785413214, 15.093262039593768, 14.249711351844992, 13.447792242732948, 12.685968458965926, 11.962706462593678, 11.276482798321505, 10.625790445651342, 10.009144254453888, 9.425085554899425, 8.872186025433246, 8.349050895670947, 7.854321554703287, 7.386677629328477, 6.944838591158911, 6.527564946364096, 6.133659056995521, 5.761965638375536, 5.411371972902058, 5.080807876806979, 4.769245452890264, 4.475698659015326, 4.199222719177873, 3.938913401232408, 3.693906182861808, 3.4633753250901056, 3.2465328705514596, 3.042627581825764, 2.850943833418834, 2.6708004693903664, 2.5015496372039308, 2.3425756070782766, 2.1932935849477233, 2.0531485260817104, 1.9216139554598253, 1.7981908001405382, 1.682406238091232, 1.5738125672563081, 1.471986098022546, 1.376526071689525, 1.2870536070624528, 1.203210676849153, 1.124659115157422, 1.051079657048965]],\"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\"],\"ta5aba23ba1d74f09bd777451fc112fd2\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[0.0016624232269733259, 0.0019048735376913737, 0.0021473238484094213, 0.002389774159127469, 0.002632224469845517, 0.0028746747805635645, 0.0031171250912816126, 0.00335957540199966, 0.003602025712717708, 0.0038444760234357554, 0.004086926334153803, 0.004329376644871851, 0.004571826955589899, 0.004814277266307947, 0.005056727577025994, 0.005299177887744042, 0.0055416281984620895, 0.005784078509180138, 0.0060265288198981855, 0.006268979130616233, 0.006511429441334281, 0.006753879752052328, 0.006996330062770376, 0.007238780373488424, 0.007481230684206472, 0.00772368099492452, 0.007966131305642566, 0.008208581616360615, 0.008451031927078662, 0.00869348223779671, 0.008935932548514759, 0.009178382859232805, 0.009420833169950854, 0.0096632834806689, 0.009905733791386949, 0.010148184102104996, 0.010390634412823044, 0.010633084723541091, 0.01087553503425914, 0.011117985344977188, 0.011360435655695235, 0.011602885966413283, 0.01184533627713133, 0.012087786587849378, 0.012330236898567425, 0.012572687209285473, 0.012815137520003522, 0.013057587830721569, 0.013300038141439617, 0.013542488452157664, 0.013784938762875712, 0.014027389073593759, 0.014269839384311808, 0.014512289695029856, 0.014754740005747903, 0.014997190316465951, 0.015239640627183998, 0.015482090937902046, 0.015724541248620095, 0.01596699155933814, 0.016209441870056192, 0.01645189218077424, 0.016694342491492285, 0.016936792802210332, 0.017179243112928382, 0.01742169342364643, 0.017664143734364476, 0.017906594045082522, 0.018149044355800573, 0.01839149466651862, 0.018633944977236666, 0.018876395287954716, 0.019118845598672763, 0.01936129590939081, 0.019603746220108857, 0.019846196530826907, 0.020088646841544953, 0.020331097152263, 0.02057354746298105, 0.020815997773699097, 0.021058448084417144, 0.02130089839513519, 0.02154334870585324, 0.021785799016571288, 0.022028249327289334, 0.022270699638007384, 0.02251314994872543, 0.022755600259443478, 0.022998050570161525, 0.023240500880879575, 0.02348295119159762, 0.02372540150231567, 0.02396785181303372, 0.024210302123751765, 0.024452752434469812, 0.02469520274518786, 0.02493765305590591, 0.025180103366623956, 0.025422553677342002, 0.025665003988060053], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [33.25300599207764, 38.387871149857126, 43.243159600669806, 47.784019667042585, 51.98859306232165, 55.84484009622611, 59.34820823423578, 62.499874673464284, 65.30539524512422, 67.7736501244772, 69.91601193343581, 71.74568396860944, 73.2771707995642, 74.52585330579991, 75.50764706205123, 76.23872786518375, 76.73531175921771, 77.01347956555622, 77.08903793116896, 76.97741044846673, 76.6935536007224, 76.25189323290869, 75.6662780016153, 74.94994686412937, 74.11550815882251, 73.17492823130226, 72.13952789196433, 71.01998526483999, 69.8263438159701, 68.56802454053081, 67.25384144835367, 65.89201962270252, 64.49021524150236, 63.055537047141726, 61.59456883332626, 60.113392587557534, 58.61761198756649, 57.112376001016244, 55.60240238132856, 54.09200088967712, 52.58509610495678, 51.085249710659696, 49.59568217072729, 48.11929372616259, 46.65868466095859, 45.21617480013308, 43.79382221470986, 42.3934411186499, 41.016618951273855, 39.66473264585193, 38.3389640909603, 37.040314796084964, 35.76961977693338, 34.52756067912299, 33.3146781614564, 32.13138356196492, 30.97796987138392, 29.854622039788676, 28.76142664282867, 27.698380934406273, 26.665401312799222, 25.662331227165808, 24.688948551132107, 23.744972449775364, 22.830069765807576, 21.943860950159593, 21.08592556147994, 20.25580735831882, 19.45301900697549, 18.677046427163106, 17.927352796796583, 17.203382236349707, 16.504563192359925, 15.830311538795213, 15.180033414138377, 14.553127811197761, 13.948988935820925, 13.36700834987511, 12.806576913065484, 12.267086537392768, 11.747931767306254, 11.248511197889309, 10.768228742720224, 10.306494762385519, 9.862727063982753, 9.436351781338079, 9.02680414507796, 8.633529151135928, 8.255982135742759, 7.893629264441792, 7.545947942189117, 7.212427151141609, 6.892567722301948, 6.58588254677946, 6.291896732036996, 6.010147708127342, 5.740185288575797, 5.48157169023901, 5.23388151616197, 4.996701705165232]],\"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\"],\"t0689c184f6c246ce98025e14867c2475\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[0.005349205618864327, 0.005429025355316793, 0.00550884509176926, 0.005588664828221726, 0.0056684845646741925, 0.005748304301126658, 0.005828124037579125, 0.005907943774031591, 0.005987763510484058, 0.006067583246936524, 0.006147402983388991, 0.0062272227198414565, 0.006307042456293923, 0.006386862192746389, 0.006466681929198855, 0.006546501665651322, 0.006626321402103789, 0.006706141138556255, 0.006785960875008721, 0.006865780611461187, 0.006945600347913654, 0.00702542008436612, 0.007105239820818586, 0.007185059557271053, 0.007264879293723519, 0.007344699030175985, 0.0074245187666284514, 0.007504338503080918, 0.007584158239533384, 0.00766397797598585, 0.007743797712438317, 0.007823617448890784, 0.00790343718534325, 0.007983256921795715, 0.008063076658248182, 0.008142896394700649, 0.008222716131153114, 0.008302535867605581, 0.008382355604058048, 0.008462175340510514, 0.008541995076962981, 0.008621814813415446, 0.008701634549867913, 0.008781454286320378, 0.008861274022772845, 0.008941093759225312, 0.009020913495677779, 0.009100733232130245, 0.00918055296858271, 0.009260372705035177, 0.009340192441487642, 0.009420012177940109, 0.009499831914392576, 0.009579651650845043, 0.00965947138729751, 0.009739291123749976, 0.009819110860202441, 0.009898930596654908, 0.009978750333107373, 0.01005857006955984, 0.010138389806012307, 0.010218209542464773, 0.01029802927891724, 0.010377849015369707, 0.010457668751822172, 0.010537488488274637, 0.010617308224727104, 0.01069712796117957, 0.010776947697632037, 0.010856767434084504, 0.010936587170536971, 0.011016406906989436, 0.011096226643441903, 0.011176046379894368, 0.011255866116346835, 0.011335685852799302, 0.011415505589251768, 0.011495325325704235, 0.011575145062156702, 0.011654964798609167, 0.011734784535061634, 0.011814604271514099, 0.011894424007966566, 0.011974243744419032, 0.0120540634808715, 0.012133883217323966, 0.012213702953776431, 0.012293522690228898, 0.012373342426681363, 0.01245316216313383, 0.012532981899586296, 0.012612801636038763, 0.01269262137249123, 0.012772441108943697, 0.012852260845396162, 0.012932080581848629, 0.013011900318301094, 0.01309172005475356, 0.013171539791206027, 0.013251359527658494], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [76.35986280242523, 76.53281512734533, 76.68128923573755, 76.80585786556307, 76.90709067890671, 76.9855537930377, 77.04180934803564, 77.07641510874731, 77.08992409898215, 77.08288426598742, 77.05583817336668, 77.00932272071944, 76.9438688883853, 76.860001505775, 76.75823904186217, 76.63909341649467, 76.50306983126511, 76.35066661875315, 76.18237510902311, 75.99867951232412, 75.80005681700165, 75.58697670168614, 75.35990146087734, 75.11928594309357, 74.86557750080179, 74.59921595138833, 74.32063354847243, 74.03025496290225, 73.72849727281111, 73.41576996214557, 73.09247492710924, 72.75900648999759, 72.41575141992702, 72.06308895998974, 71.70139086039025, 71.33102141714546, 70.9523375159514, 70.56568868084226, 70.17141712728832, 69.76985781939706, 69.36133853090222, 68.94617990964078, 68.52469554523596, 68.09719203971873, 67.66396908083547, 67.22531951780336, 66.7815294392881, 66.33287825339103, 65.87963876944505, 65.42207728142917, 64.96045365282282, 64.495021402731, 64.0260277931206, 63.55371391701797, 63.078314787525606, 62.600059427524805, 62.119170959938444, 61.635866698435485, 61.15035823846594, 60.662851548521374, 60.17354706152298, 59.68263976624433, 59.1903192986824, 58.69677003329538, 58.202171174031214, 57.70669684507551, 57.21051618125187, 56.71379341801285, 56.21668798096283, 55.719354574859004, 55.22194327203985, 54.724599600234306, 54.227464629708024, 53.73067505970664, 53.23436330415869, 52.73865757660365, 52.243681974313965, 51.74955656158149, 51.25639745214229, 50.764316890715214, 50.27342333363256, 49.783821528542745, 49.29561259316707, 48.80889409309469, 48.3237601186014, 47.84030136047975, 47.35860518486962, 46.878755707079506, 46.40083386439098, 45.92491748783899, 45.451081372963245, 44.979397349526124, 44.50993435019388, 44.042758478179735, 43.57793307384712, 43.11551878027354, 42.655573607775786, 42.198152997397884, 41.74330988336482, 41.291094754504535]],\"toyplot\");\n",
       "(function(axis, axis_id, projection)\n",
       "        {\n",
       "            axis.show_coordinates(axis_id, projection);\n",
       "        })(modules[\"toyplot.coordinates.Axis\"],\"te357003540f24c258bf85169127c6192\",[{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 0.03349920468727808, \"min\": 0.0}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 225.0, \"min\": 0.0}, \"scale\": \"linear\"}]);\n",
       "(function(axis, axis_id, projection)\n",
       "        {\n",
       "            axis.show_coordinates(axis_id, projection);\n",
       "        })(modules[\"toyplot.coordinates.Axis\"],\"t0ec3fa802eed481c89e23c197778c3b9\",[{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 77.08992409898215, \"min\": 0.0}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 200.0, \"min\": 0.0}, \"scale\": \"linear\"}]);\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\"],\"t8521c2fed0b243448e3eaf95b0be5f21\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[13657.40837122568, 21056.47738515314, 28455.546399080602, 35854.61541300806, 43253.68442693552, 50652.75344086299, 58051.82245479044, 65450.891468717906, 72849.96048264536, 80249.02949657282, 87648.09851050029, 95047.16752442774, 102446.23653835521, 109845.30555228266, 117244.37456621013, 124643.44358013758, 132042.51259406505, 139441.5816079925, 146840.65062191995, 154239.7196358474, 161638.78864977488, 169037.85766370234, 176436.9266776298, 183835.99569155724, 191235.06470548472, 198634.13371941217, 206033.20273333963, 213432.2717472671, 220831.34076119456, 228230.409775122, 235629.47878904946, 243028.54780297694, 250427.6168169044, 257826.68583083185, 265225.75484475936, 272624.8238586868, 280023.89287261426, 287422.96188654174, 294822.03090046917, 302221.09991439665, 309620.1689283241, 317019.23794225155, 324418.30695617903, 331817.3759701065, 339216.44498403394, 346615.5139979614, 354014.58301188884, 361413.6520258163, 368812.7210397438, 376211.7900536712, 383610.8590675987, 391009.9280815262, 398408.9970954536, 405808.0661093811, 413207.1351233086, 420606.204137236, 428005.2731511635, 435404.34216509096, 442803.4111790184, 450202.48019294586, 457601.5492068733, 465000.61822080077, 472399.68723472825, 479798.75624865567, 487197.82526258315, 494596.89427651063, 501995.96329043806, 509395.03230436554, 516794.101318293, 524193.17033222044, 531592.2393461479, 538991.3083600753, 546390.3773740028, 553789.4463879303, 561188.5154018578, 568587.5844157853, 575986.6534297126, 583385.7224436401, 590784.7914575676, 598183.8604714951, 605582.9294854226, 612981.9984993499, 620381.0675132774, 627780.1365272049, 635179.2055411324, 642578.2745550598, 649977.3435689873, 657376.4125829147, 664775.4815968422, 672174.5506107697, 679573.6196246971, 686972.6886386246, 694371.757652552, 701770.8266664795, 709169.895680407, 716568.9646943344, 723968.0337082619, 731367.1027221894, 738766.1717361168, 746165.2407500442], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [7.751079642351868e-07, 1.2134849250685857e-06, 1.6186851118642827e-06, 1.9831221111250775e-06, 2.3044760142130882e-06, 2.582993149534428e-06, 2.820284158427591e-06, 3.018698929646187e-06, 3.1809700865830477e-06, 3.3099977891607393e-06, 3.4087154806195994e-06, 3.4800049124634547e-06, 3.5266425319283986e-06, 3.5512664837942317e-06, 3.556357472765544e-06, 3.544229083048778e-06, 3.5170245982341614e-06, 3.4767182887508324e-06, 3.4251197434942875e-06, 3.3638802347969006e-06, 3.2945003916011408e-06, 3.2183386573001174e-06, 3.136620153250046e-06, 3.050445673954397e-06, 2.9608006170055397e-06, 2.8685637079409906e-06, 2.7745154226874173e-06, 2.6793460420679285e-06, 2.583663296681342e-06, 2.487999578315267e-06, 2.3928187073866125e-06, 2.2985222557962025e-06, 2.20545543184937e-06, 2.1139125391449337e-06, 2.024142025037681e-06, 1.936351136792731e-06, 1.8507102051501093e-06, 1.7673565759188513e-06, 1.6863982105885307e-06, 1.6079169769125525e-06, 1.531971650083564e-06, 1.4586006445666929e-06, 1.387824495943503e-06, 1.3196481112974352e-06, 1.2540628057782e-06, 1.1910481420478847e-06, 1.1305735883583256e-06, 1.0726000100552106e-06, 1.0170810083628692e-06, 9.63964119384644e-07, 9.131918853645978e-07, 8.647028094021477e-07, 8.18432203995609e-07, 7.743129430157344e-07, 7.322761259772957e-07, 6.922516627858254e-07, 6.541687864876412e-07, 6.179565009432829e-07, 5.835439697764861e-07, 5.50860852421309e-07, 5.198375925975193e-07, 4.904056640870282e-07, 4.624977782603895e-07, 4.360480574101999e-07, 4.1099217758597815e-07, 3.8726748429084727e-07, 3.6481308409242894e-07, 3.435699149170329e-07, 3.2348079753585434e-07, 3.0449047051291165e-07, 2.86545610665355e-07, 2.695948408861285e-07, 2.5358872699543076e-07, 2.384797651196969e-07, 2.2422236094375491e-07, 2.107728020422257e-07, 1.9808922436911717e-07, 1.8613157386890975e-07, 1.748615640673263e-07, 1.6424263040457187e-07, 1.5423988198732138e-07, 1.4482005135739538e-07, 1.359514428041921e-07, 1.2760387968393942e-07, 1.1974865115106232e-07, 1.1235845865493542e-07, 1.0540736250847274e-07, 9.887072879295433e-08, 9.272517682577529e-08, 8.694852738403619e-08, 8.15197518467163e-08, 7.641892239125456e-08, 7.162716335640904e-08, 6.71266038619869e-08, 6.290033175719732e-08, 5.893234895272483e-08, 5.520752817696346e-08, 5.171157118397599e-08, 4.843096842948753e-08, 4.535296022141574e-08]],\"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\"],\"t7ffbc2e89e7645749a3658fe6dd4b843\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[29742.133612069607, 35150.087630728936, 40558.041649388266, 45965.9956680476, 51373.949686706925, 56781.90370536626, 62189.85772402559, 67597.81174268492, 73005.76576134426, 78413.71978000358, 83821.6737986629, 89229.62781732224, 94637.58183598157, 100045.5358546409, 105453.48987330023, 110861.44389195956, 116269.39791061889, 121677.35192927823, 127085.30594793755, 132493.2599665969, 137901.2139852562, 143309.16800391555, 148717.12202257488, 154125.0760412342, 159533.03005989356, 164940.98407855286, 170348.93809721217, 175756.89211587154, 181164.84613453085, 186572.8001531902, 191980.75417184952, 197388.70819050883, 202796.6622091682, 208204.6162278275, 213612.57024648687, 219020.52426514617, 224428.47828380548, 229836.43230246485, 235244.38632112416, 240652.34033978346, 246060.29435844283, 251468.24837710214, 256876.2023957615, 262284.1564144208, 267692.1104330801, 273100.0644517395, 278508.0184703988, 283915.97248905816, 289323.92650771746, 294731.8805263768, 300139.83454503614, 305547.78856369545, 310955.74258235475, 316363.6966010141, 321771.6506196734, 327179.60463833273, 332587.5586569921, 337995.5126756514, 343403.4666943108, 348811.4207129701, 354219.3747316294, 359627.32875028875, 365035.28276894806, 370443.2367876074, 375851.19080626674, 381259.14482492604, 386667.0988435854, 392075.0528622447, 397483.0068809041, 402890.9608995634, 408298.9149182227, 413706.86893688206, 419114.8229555414, 424522.77697420074, 429930.73099286004, 435338.68501151935, 440746.6390301787, 446154.593048838, 451562.54706749733, 456970.5010861567, 462378.455104816, 467786.4091234754, 473194.3631421347, 478602.317160794, 484010.27117945335, 489418.22519811266, 494826.179216772, 500234.13323543133, 505642.08725409064, 511050.04127275, 516457.9952914093, 521865.9493100687, 527273.903328728, 532681.8573473874, 538089.8113660467, 543497.765384706, 548905.7194033654, 554313.6734220247, 559721.627440684, 565129.5814593433], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.6850944195701944e-06, 1.9502647724083867e-06, 2.1924110554628022e-06, 2.4114828848578422e-06, 2.6079019410253384e-06, 2.782392576301298e-06, 2.9358724745087128e-06, 3.0693791957672583e-06, 3.1840194108327857e-06, 3.2809331277522684e-06, 3.361268176489787e-06, 3.42616191038145e-06, 3.4767280992006664e-06, 3.5140476237161145e-06, 3.539161992821515e-06, 3.553068978722353e-06, 3.5567198536677733e-06, 3.5510178435237683e-06, 3.536817507785113e-06, 3.5149248243088895e-06, 3.4860978078782962e-06, 3.4510475298466806e-06, 3.410439435091966e-06, 3.3648948747746277e-06, 3.3149927906619977e-06, 3.261271500292855e-06, 3.2042305429061e-06, 3.1443325545065717e-06, 3.0820051471814667e-06, 3.0176427731834506e-06, 2.9516085586433e-06, 2.884236095282783e-06, 2.815831181335507e-06, 2.746673505180988e-06, 2.677018267058762e-06, 2.607097735736919e-06, 2.5371227382285358e-06, 2.4672840816327305e-06, 2.3977539069667577e-06, 2.3286869754863326e-06, 2.2602218884912132e-06, 2.19248224200489e-06, 2.125577718020049e-06, 2.0596051142308155e-06, 1.994649314341422e-06, 1.930784201159752e-06, 1.8680735147619085e-06, 1.8065716580579596e-06, 1.7463244521056393e-06, 1.6873698435129108e-06, 1.6297385662465442e-06, 1.573454760125583e-06, 1.51853654822894e-06, 1.4649965753878118e-06, 1.4128425098683076e-06, 1.3620775102793415e-06, 1.312700659666967e-06, 1.26470736868015e-06, 1.2180897496154124e-06, 1.1728369630698222e-06, 1.1289355388539664e-06, 1.0863696727395243e-06, 1.0451215005402137e-06, 1.0051713509506109e-06, 9.664979784949788e-07, 9.29078777867847e-07, 8.92889980880053e-07, 8.579068371581998e-07, 8.241037796821751e-07, 7.914545761846409e-07, 7.599324673780503e-07, 7.295102929190296e-07, 7.001606059666647e-07, 6.718557771404326e-07, 6.445680886351215e-07, 6.182698192040595e-07, 5.929333206782481e-07, 5.685310866474928e-07, 5.450358138903149e-07, 5.22420457102161e-07, 5.006582774362069e-07, 4.79722885337737e-07, 4.595882781216339e-07, 4.4022887271280936e-07, 4.216195339414483e-07, 4.037355987585248e-07, 3.865528967122456e-07, 3.7004776700268833e-07, 3.5419707240994113e-07, 3.389782103703878e-07, 3.2436912145640547e-07, 3.103482954965244e-07, 2.968947755560476e-07, 2.8398815998210165e-07, 2.71608602702121e-07, 2.5973681195070956e-07, 2.4835404758670223e-07, 2.374421171499541e-07, 2.2698337079590295e-07, 2.1696069523523316e-07]],\"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\"],\"t048d706985a048f4b4ca33df77a23cd0\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[106643.08040920559, 108411.54072639122, 110180.00104357683, 111948.46136076246, 113716.92167794808, 115485.3819951337, 117253.84231231932, 119022.30262950495, 120790.76294669058, 122559.22326387619, 124327.6835810618, 126096.14389824744, 127864.60421543306, 129633.06453261868, 131401.5248498043, 133169.98516698994, 134938.44548417555, 136706.90580136116, 138475.3661185468, 140243.82643573242, 142012.28675291804, 143780.74707010365, 145549.2073872893, 147317.6677044749, 149086.12802166052, 150854.58833884617, 152623.04865603178, 154391.5089732174, 156159.969290403, 157928.42960758865, 159696.88992477427, 161465.35024195988, 163233.81055914552, 165002.27087633114, 166770.73119351675, 168539.19151070237, 170307.65182788798, 172076.11214507362, 173844.57246225924, 175613.03277944488, 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       "            {\n",
       "                return x < 0 ? -1 : x > 0 ? 1 : 0;\n",
       "            }\n",
       "\n",
       "            function mix(a, b, amount)\n",
       "            {\n",
       "                return ((1.0 - amount) * a) + (amount * b);\n",
       "            }\n",
       "\n",
       "            function log(x, base)\n",
       "            {\n",
       "                return Math.log(Math.abs(x)) / Math.log(base);\n",
       "            }\n",
       "\n",
       "            function in_range(a, x, b)\n",
       "            {\n",
       "                var left = Math.min(a, b);\n",
       "                var right = Math.max(a, b);\n",
       "                return left <= x && x <= right;\n",
       "            }\n",
       "\n",
       "            function inside(range, projection)\n",
       "            {\n",
       "                for(var i = 0; i != projection.length; ++i)\n",
       "                {\n",
       "                    var segment = projection[i];\n",
       "                    if(in_range(segment.range.min, range, segment.range.max))\n",
       "                        return true;\n",
       "                }\n",
       "                return false;\n",
       "            }\n",
       "\n",
       "            function to_domain(range, projection)\n",
       "            {\n",
       "                for(var i = 0; i != projection.length; ++i)\n",
       "                {\n",
       "                    var segment = projection[i];\n",
       "                    if(in_range(segment.range.bounds.min, range, segment.range.bounds.max))\n",
       "                    {\n",
       "                        if(segment.scale == \"linear\")\n",
       "                        {\n",
       "                            var amount = (range - segment.range.min) / (segment.range.max - segment.range.min);\n",
       "                            return mix(segment.domain.min, segment.domain.max, amount)\n",
       "                        }\n",
       "                        else if(segment.scale[0] == \"log\")\n",
       "                        {\n",
       "                            var amount = (range - segment.range.min) / (segment.range.max - segment.range.min);\n",
       "                            var base = segment.scale[1];\n",
       "                            return sign(segment.domain.min) * Math.pow(base, mix(log(segment.domain.min, base), log(segment.domain.max, base), amount));\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            var axes = {};\n",
       "\n",
       "            function display_coordinates(e)\n",
       "            {\n",
       "                var current = canvas.createSVGPoint();\n",
       "                current.x = e.clientX;\n",
       "                current.y = e.clientY;\n",
       "\n",
       "                for(var axis_id in axes)\n",
       "                {\n",
       "                    var axis = document.querySelector(\"#\" + axis_id);\n",
       "                    var coordinates = axis.querySelector(\".toyplot-coordinates-Axis-coordinates\");\n",
       "                    if(coordinates)\n",
       "                    {\n",
       "                        var projection = axes[axis_id];\n",
       "                        var local = current.matrixTransform(axis.getScreenCTM().inverse());\n",
       "                        if(inside(local.x, projection))\n",
       "                        {\n",
       "                            var domain = to_domain(local.x, projection);\n",
       "                            coordinates.style.visibility = \"visible\";\n",
       "                            coordinates.setAttribute(\"transform\", \"translate(\" + local.x + \")\");\n",
       "                            var text = coordinates.querySelector(\"text\");\n",
       "                            text.textContent = domain.toFixed(2);\n",
       "                        }\n",
       "                        else\n",
       "                        {\n",
       "                            coordinates.style.visibility= \"hidden\";\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            canvas.addEventListener(\"click\", display_coordinates);\n",
       "\n",
       "            var module = {};\n",
       "            module.show_coordinates = function(axis_id, projection)\n",
       "            {\n",
       "                axes[axis_id] = projection;\n",
       "            }\n",
       "\n",
       "            return module;\n",
       "        })(modules[\"toyplot/canvas\"]);\n",
       "(function(tables, context_menu, io, owner_id, key, label, names, columns, filename)\n",
       "        {\n",
       "            tables.set(owner_id, key, names, columns);\n",
       "\n",
       "            var owner = document.querySelector(\"#\" + owner_id);\n",
       "            function show_item(e)\n",
       "            {\n",
       "                return owner.contains(e.target);\n",
       "            }\n",
       "\n",
       "            function choose_item()\n",
       "            {\n",
       "                io.save_file(\"text/csv\", \"utf-8\", tables.get_csv(owner_id, key), filename + \".csv\");\n",
       "            }\n",
       "\n",
       "            context_menu.add_item(\"Save \" + label + \" as CSV\", show_item, choose_item);\n",
       "        })(modules[\"toyplot/tables\"],modules[\"toyplot/menus/context\"],modules[\"toyplot/io\"],\"t0ea22c11a1ce49618c463d0e1e07fa29\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[0.987167814093623, 0.9874279988057979, 0.9876881835179728, 0.9879483682301476, 0.9882085529423226, 0.9884687376544975, 0.9887289223666724, 0.9889891070788474, 0.9892492917910223, 0.9895094765031971, 0.989769661215372, 0.990029845927547, 0.9902900306397219, 0.9905502153518968, 0.9908104000640716, 0.9910705847762465, 0.9913307694884215, 0.9915909542005964, 0.9918511389127713, 0.9921113236249463, 0.9923715083371211, 0.992631693049296, 0.9928918777614709, 0.9931520624736458, 0.9934122471858208, 0.9936724318979956, 0.9939326166101705, 0.9941928013223454, 0.9944529860345204, 0.9947131707466953, 0.9949733554588702, 0.995233540171045, 0.99549372488322, 0.9957539095953949, 0.9960140943075698, 0.9962742790197447, 0.9965344637319196, 0.9967946484440945, 0.9970548331562694, 0.9973150178684443, 0.9975752025806193, 0.9978353872927942, 0.998095572004969, 0.9983557567171439, 0.9986159414293189, 0.9988761261414938, 0.9991363108536687, 0.9993964955658435, 0.9996566802780185, 0.9999168649901934, 1.0001770497023683, 1.0004372344145431, 1.0006974191267182, 1.000957603838893, 1.001217788551068, 1.0014779732632428, 1.0017381579754177, 1.0019983426875927, 1.0022585273997675, 1.0025187121119425, 1.0027788968241174, 1.0030390815362922, 1.0032992662484672, 1.003559450960642, 1.003819635672817, 1.0040798203849919, 1.0043400050971667, 1.0046001898093417, 1.0048603745215166, 1.0051205592336916, 1.0053807439458664, 1.0056409286580414, 1.0059011133702163, 1.006161298082391, 1.0064214827945661, 1.006681667506741, 1.006941852218916, 1.0072020369310908, 1.0074622216432656, 1.0077224063554406, 1.0079825910676155, 1.0082427757797905, 1.0085029604919653, 1.0087631452041401, 1.0090233299163152, 1.00928351462849, 1.009543699340665, 1.0098038840528398, 1.0100640687650149, 1.0103242534771897, 1.0105844381893645, 1.0108446229015395, 1.0111048076137144, 1.0113649923258894, 1.0116251770380642, 1.011885361750239, 1.012145546462414, 1.0124057311745889, 1.012665915886764, 1.0129261005989387], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [2.9169677259290143, 3.3340158625703427, 3.800122456967493, 4.319386327769494, 4.896002931659498, 5.534228490722447, 6.238338452800308, 7.012580251994703, 7.861120481172316, 8.787986673833036, 9.797004059226378, 10.891727788379567, 12.075371274547432, 13.350731453589551, 14.720111896439006, 16.18524490774454, 17.747213793531856, 19.406376685335616, 21.162293378650627, 23.013656690894578, 24.958229953581252, 26.99279224754052, 29.1130929599412, 31.31381721543488, 33.58856363132992, 35.92983573730336, 38.329048175312025, 40.77654866915865, 43.261656417238285, 45.77271735515518, 48.29717644583025, 50.82166669706065, 53.33211444064239, 55.813859966105724, 58.25179223763452, 60.63049616378833, 62.93441051295064, 65.14799429835163, 67.25589918546822, 69.2431453712726, 71.09529801631648, 72.79864144623475, 74.34034814668298, 75.70863962348946, 76.89293632975617, 77.88399402581892, 78.67402401988451, 79.25679516820625, 79.627715780534, 79.78389382378339, 79.72417446560229, 79.44915415388554, 78.96117104039493, 78.26427196735717, 77.36415666721604, 76.26810023645757, 74.9848553350452, 73.52453602315369, 71.89848529051665, 70.11912878727834, 68.19981731739871, 66.15466092242052, 63.9983574122561, 61.746018192279834, 59.41299432352341, 57.01470546254088, 54.566474416457645, 52.083369553909506, 49.58005739500008, 47.070667121084256, 44.56866865508701, 42.08676553222082, 39.6368034856822, 37.229695280401614, 34.87536213211411, 32.582691522625275, 30.359511157002697, 28.21257835839548, 26.14758405382679, 24.16917026877372, 22.280959907890246, 20.485597389972, 18.784798745890384, 17.17940958490283, 15.669469458230424, 14.254281028957719, 12.93248261724788, 11.702122679682425, 10.560734915152427, 9.505412793224673, 8.532882417192155, 7.639572779961831, 6.821682605998773, 6.075243123823923, 5.396176234650694, 4.780347713592325, 4.22361517092985, 3.721870656213878, 3.2710778691237663, 2.867304063675747]],\"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\"],\"tb7f27461b3c248d1918911e160e183a2\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[0.9902238803533677, 0.9904218560791773, 0.9906198318049869, 0.9908178075307965, 0.9910157832566061, 0.9912137589824157, 0.9914117347082253, 0.991609710434035, 0.9918076861598446, 0.9920056618856542, 0.9922036376114638, 0.9924016133372734, 0.992599589063083, 0.9927975647888926, 0.9929955405147022, 0.9931935162405118, 0.9933914919663214, 0.993589467692131, 0.9937874434179406, 0.9939854191437503, 0.9941833948695599, 0.9943813705953695, 0.9945793463211791, 0.9947773220469887, 0.9949752977727983, 0.9951732734986078, 0.9953712492244174, 0.995569224950227, 0.9957672006760366, 0.9959651764018462, 0.9961631521276558, 0.9963611278534655, 0.9965591035792751, 0.9967570793050847, 0.9969550550308943, 0.9971530307567039, 0.9973510064825135, 0.9975489822083231, 0.9977469579341327, 0.9979449336599423, 0.9981429093857519, 0.9983408851115615, 0.9985388608373711, 0.9987368365631807, 0.9989348122889904, 0.9991327880148, 0.9993307637406096, 0.9995287394664192, 0.9997267151922288, 0.9999246909180384, 1.000122666643848, 1.0003206423696576, 1.0005186180954673, 1.0007165938212768, 1.0009145695470865, 1.001112545272896, 1.0013105209987057, 1.0015084967245151, 1.0017064724503248, 1.0019044481761343, 1.002102423901944, 1.0023003996277535, 1.0024983753535632, 1.002696351079373, 1.0028943268051824, 1.0030923025309921, 1.0032902782568016, 1.0034882539826113, 1.0036862297084208, 1.0038842054342305, 1.00408218116004, 1.0042801568858497, 1.0044781326116592, 1.004676108337469, 1.0048740840632784, 1.005072059789088, 1.0052700355148978, 1.0054680112407073, 1.005665986966517, 1.0058639626923265, 1.0060619384181362, 1.0062599141439457, 1.0064578898697554, 1.0066558655955649, 1.0068538413213746, 1.007051817047184, 1.0072497927729938, 1.0074477684988035, 1.007645744224613, 1.0078437199504227, 1.0080416956762321, 1.0082396714020418, 1.0084376471278513, 1.008635622853661, 1.0088335985794705, 1.0090315743052802, 1.0092295500310897, 1.0094275257568994, 1.009625501482709, 1.0098234772085186], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [11.765845558540834, 12.70992689098816, 13.707835046464341, 14.760493319169024, 15.868626498261747, 17.032741048445015, 18.253105595030124, 19.52973193505958, 20.862356780774146, 22.250424495624365, 23.693071022293715, 25.189109276580105, 26.737016216964175, 28.334921835846522, 29.980600303141802, 31.671463460032648, 33.404556896331385, 35.17655873815323, 36.98378138266842, 38.822176268358334, 40.687341779456, 42.5745344368831, 44.47868334481052, 46.394407951371896, 48.31603909079886, 50.23764324948397, 52.1530499484467, 54.05588212120659, 55.939589267359736, 57.79748324300109, 59.62277636059167, 61.408621518142425, 63.14815413734236, 64.83453540054876, 66.46099654602803, 68.02088377614962, 69.50770335281103, 70.9151664896631, 72.2372335444105, 73.46815719512217, 74.60252404015311, 75.63529426344866, 76.56183896388973, 77.3779747448367, 78.07999522419256, 78.66469906523857, 79.12941434778469, 79.47201888034108, 79.69095635899414, 79.78524815164612, 79.75450056411185, 79.5989075078415, 79.31924862780006, 78.91688282709211, 78.39373724994259, 77.75229194422754, 76.99556032718918, 76.12706559778371, 75.15081345387418, 74.07126140267071, 72.89328490098161, 71.622140790158, 70.26342835480209, 68.82304840431546, 67.30716081491359, 65.72214095971867, 64.07453541196708, 62.37101741431062, 60.61834247374892, 58.823304526799745, 56.992693038022495, 55.133251405195736, 53.25163705261796, 51.35438344420058, 49.44786439676357, 47.53826084476588, 45.63153038530398, 43.73337963405406, 41.84923965585309, 39.98424452741078, 38.14321305919067, 36.33063375365156, 34.550652960161784, 32.80706621112999, 31.10331260578463, 29.442472235671772, 27.827266404760127, 26.260060596893638, 24.74286994999757, 23.277367052677622, 21.864891903675236, 20.506463764816036, 19.202794706384335, 17.9543046324818, 16.761137536031633, 15.623178761966162, 14.540073062340348, 13.511243238826111, 12.535909130657554, 11.613106781485206]],\"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\"],\"tbc053dcf891742189d0af2d48d12c2c1\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[0.996623024390369, 0.9966911543585016, 0.9967592843266343, 0.996827414294767, 0.9968955442628996, 0.9969636742310323, 0.9970318041991649, 0.9970999341672976, 0.9971680641354302, 0.9972361941035629, 0.9973043240716956, 0.9973724540398282, 0.9974405840079609, 0.9975087139760935, 0.9975768439442262, 0.9976449739123588, 0.9977131038804915, 0.9977812338486242, 0.9978493638167568, 0.9979174937848895, 0.9979856237530221, 0.9980537537211548, 0.9981218836892874, 0.9981900136574201, 0.9982581436255528, 0.9983262735936854, 0.9983944035618181, 0.9984625335299507, 0.9985306634980834, 0.998598793466216, 0.9986669234343487, 0.9987350534024814, 0.998803183370614, 0.9988713133387467, 0.9989394433068793, 0.999007573275012, 0.9990757032431447, 0.9991438332112773, 0.99921196317941, 0.9992800931475426, 0.9993482231156753, 0.9994163530838079, 0.9994844830519406, 0.9995526130200733, 0.9996207429882059, 0.9996888729563386, 0.9997570029244712, 0.9998251328926039, 0.9998932628607365, 0.9999613928288692, 1.0000295227970017, 1.0000976527651344, 1.000165782733267, 1.0002339127013997, 1.0003020426695324, 1.000370172637665, 1.0004383026057977, 1.0005064325739303, 1.000574562542063, 1.0006426925101957, 1.0007108224783283, 1.000778952446461, 1.0008470824145936, 1.0009152123827263, 1.000983342350859, 1.0010514723189916, 1.0011196022871243, 1.001187732255257, 1.0012558622233896, 1.0013239921915222, 1.001392122159655, 1.0014602521277876, 1.0015283820959202, 1.0015965120640529, 1.0016646420321855, 1.0017327720003182, 1.0018009019684508, 1.0018690319365835, 1.0019371619047162, 1.0020052918728488, 1.0020734218409815, 1.0021415518091141, 1.0022096817772468, 1.0022778117453794, 1.002345941713512, 1.0024140716816448, 1.0024822016497774, 1.00255033161791, 1.0026184615860427, 1.0026865915541754, 1.002754721522308, 1.0028228514904407, 1.0028909814585734, 1.002959111426706, 1.0030272413948387, 1.0030953713629713, 1.003163501331104, 1.0032316312992366, 1.0032997612673693, 1.003367891235502], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [63.69877759622106, 64.27930103619491, 64.85299310709898, 65.41957912275227, 65.9787860198407, 66.53034258381906, 67.07397964013859, 67.60943029908643, 68.1364301499841, 68.65471749359388, 69.16403356228773, 69.66412272302036, 70.15473267837964, 70.63561471895025, 71.10652388854892, 71.56721922048375, 72.0174639348475, 72.45702564129182, 72.88567653468752, 73.3031936003264, 73.70935880319512, 74.10395926920214, 74.48678748833446, 74.85764148380737, 75.21632499406175, 75.56264764600718, 75.8964251191456, 76.21747932241799, 76.52563853508995, 76.82073757766322, 77.10261793730847, 77.37112792764971, 77.62612282499988, 77.86746499401386, 78.09502400250273, 78.30867675253118, 78.50830759610248, 78.69380840302371, 78.86507872248106, 79.02202580976368, 79.16456473272503, 79.29261848526671, 79.40611799224804, 79.50500221295509, 79.58921819584485, 79.65872109798975, 79.71347425718842, 79.75344921024175, 79.77862571285053, 79.78899175187895, 79.78454357320341, 79.76528567868566, 79.73123080155044, 79.68239991591234, 79.61882221079533, 79.54053503803583, 79.44758391289484, 79.34002243302047, 79.21791225480662, 79.08132303911987, 78.9303323482971, 78.76502560512408, 78.58549599400297, 78.39184439642129, 78.18417926912558, 77.9626165794819, 77.72727964761141, 77.47829906409795, 77.21581258279366, 76.93996494890528, 76.65090781124252, 76.3487995653987, 76.03380519606496, 75.70609616265841, 75.36585018659585, 75.01325115725558, 74.64848892257167, 74.27175914101069, 73.88326308540131, 73.4832074731056, 73.07180430889068, 72.6492706596628, 72.21582847735625, 71.77170443055937, 71.31712967394618, 70.8523396408109, 70.37757390294595, 69.89307588728823, 69.39909272285455, 68.8958750113555, 68.38367662485402, 67.8627544858317, 67.3333683621048, 66.79578063709916, 66.25025611102983, 65.69706179704694, 65.1364666710744, 64.56874147980821, 63.9941585254544, 63.41299145095858]],\"toyplot\");\n",
       "(function(axis, axis_id, projection)\n",
       "        {\n",
       "            axis.show_coordinates(axis_id, projection);\n",
       "        })(modules[\"toyplot.coordinates.Axis\"],\"tabae07c20f5a4ad1bfbc7f76762159bd\",[{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 1.0129261005989387, \"min\": 0.987167814093623}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 225.0, \"min\": 0.0}, \"scale\": \"linear\"}]);\n",
       "(function(axis, axis_id, projection)\n",
       "        {\n",
       "            axis.show_coordinates(axis_id, projection);\n",
       "        })(modules[\"toyplot.coordinates.Axis\"],\"tcc61a26c473249d7b4864c6b03ada851\",[{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 79.78899175187895, \"min\": 0.0}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 200.0, \"min\": 0.0}, \"scale\": \"linear\"}]);\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\"],\"t71f44cca55b64de4bd0d374df23249e0\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[0.0033786338872773347, 0.004281252947936709, 0.005183872008596084, 0.0060864910692554584, 0.006989110129914834, 0.00789172919057421, 0.008794348251233583, 0.009696967311892957, 0.010599586372552332, 0.011502205433211708, 0.012404824493871081, 0.013307443554530455, 0.014210062615189832, 0.015112681675849206, 0.01601530073650858, 0.016917919797167953, 0.01782053885782733, 0.018723157918486704, 0.019625776979146078, 0.02052839603980545, 0.02143101510046483, 0.022333634161124202, 0.023236253221783576, 0.02413887228244295, 0.025041491343102327, 0.0259441104037617, 0.026846729464421074, 0.02774934852508045, 0.028651967585739825, 0.0295545866463992, 0.030457205707058572, 0.03135982476771795, 0.03226244382837733, 0.0331650628890367, 0.034067681949696074, 0.03497030101035545, 0.03587292007101482, 0.036775539131674195, 0.03767815819233357, 0.03858077725299294, 0.03948339631365232, 0.0403860153743117, 0.04128863443497107, 0.042191253495630444, 0.04309387255628982, 0.04399649161694919, 0.044899110677608566, 0.045801729738267946, 0.04670434879892732, 0.047606967859586694, 0.04850958692024607, 0.04941220598090544, 0.050314825041564815, 0.05121744410222419, 0.05212006316288357, 0.05302268222354294, 0.053925301284202316, 0.05482792034486169, 0.055730539405521064, 0.05663315846618044, 0.05753577752683981, 0.05843839658749919, 0.059341015648158565, 0.06024363470881794, 0.06114625376947731, 0.062048872830136687, 0.06295149189079606, 0.06385411095145543, 0.06475673001211482, 0.0656593490727742, 0.06656196813343357, 0.06746458719409294, 0.06836720625475232, 0.06926982531541169, 0.07017244437607106, 0.07107506343673044, 0.07197768249738981, 0.07288030155804918, 0.07378292061870856, 0.07468553967936795, 0.07558815874002732, 0.0764907778006867, 0.07739339686134607, 0.07829601592200544, 0.07919863498266481, 0.08010125404332419, 0.08100387310398356, 0.08190649216464294, 0.08280911122530231, 0.08371173028596168, 0.08461434934662106, 0.08551696840728043, 0.0864195874679398, 0.08732220652859919, 0.08822482558925857, 0.08912744464991794, 0.09003006371057731, 0.09093268277123669, 0.09183530183189606, 0.09273792089255543], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [4.07117776839562, 5.972818627178461, 8.001028986100554, 10.077922957828125, 12.1417301312144, 14.144282045271039, 16.048839413477758, 17.82821767940643, 19.463173469101925, 20.94101892840409, 22.25443485573916, 23.40045701765208, 24.379613114439756, 25.195190590389938, 25.85261789635122, 26.35894394648291, 26.722402397127276, 26.952049041522844, 27.057462084241774, 27.048496355807195, 26.935083670546955, 26.727072536841323, 26.434101314081172, 26.06549968871289, 25.630214025023147, 25.13675274576172, 24.59314842304669, 24.006933719890792, 23.385128724810766, 22.73423757314619, 22.060252554969512, 21.368664176173315, 20.664475871226465, 19.9522222674048, 19.235990074748486, 18.519440826871985, 17.805834827966297, 17.098055773459116, 16.398635608109483, 15.70977926781158, 15.033389021835895, 14.371088192198581, 13.724244077692498, 13.09398995303867, 12.481246049682127, 11.886739454889934, 11.311022890823507, 10.754492355865896, 10.217403627308265, 9.69988763808424, 9.201964751058743, 8.723557962843737, 8.264505075585529, 7.824569879958992, 7.403452395983359, 7.0007982204762165, 6.616207031187485, 6.249240298078818, 5.899428251982969, 5.566276160121675, 5.249269956787176, 4.947881275994523, 4.661571931168326, 4.389797885003381, 4.132012750590828, 3.8876708627747627, 3.6562299565380663, 3.437153487041246, 3.2299126237804323, 3.0339879492104562, 2.848870890112548, 2.6740649079863728, 2.5090864728218967, 2.353465842765308, 2.2067476704392903, 2.068491455014226, 1.938271857554971, 1.8156788956874128, 1.7003180322396696, 1.591810171212319, 1.4897915732185854, 1.3939137014056866, 1.3038430078198162, 1.2192606692054975, 1.1398622803322134, 1.0653575121130594, 0.9954697410181735, 0.9299356555859626, 0.8685048451938453, 0.8109393756638344, 0.7570133557430294, 0.7065124980116146, 0.6592336773278835, 0.6149844895178995, 0.5735828126537306, 0.5348563729356408, 0.49864231689773225, 0.46478679139043794, 0.4331445325547768, 0.403578464789918]],\"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\"],\"tf989c447be8747328c00fc60b6c49a54\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[0.006186721228956015, 0.006853995526413425, 0.007521269823870835, 0.008188544121328245, 0.008855818418785655, 0.009523092716243065, 0.010190367013700474, 0.010857641311157885, 0.011524915608615294, 0.012192189906072706, 0.012859464203530114, 0.013526738500987526, 0.014194012798444934, 0.014861287095902344, 0.015528561393359754, 0.016195835690817166, 0.016863109988274574, 0.017530384285731983, 0.018197658583189395, 0.018864932880646806, 0.019532207178104215, 0.020199481475561623, 0.020866755773019035, 0.021534030070476447, 0.022201304367933855, 0.022868578665391263, 0.023535852962848672, 0.024203127260306087, 0.024870401557763495, 0.025537675855220904, 0.026204950152678312, 0.026872224450135727, 0.027539498747593136, 0.028206773045050544, 0.028874047342507952, 0.02954132163996536, 0.030208595937422776, 0.030875870234880184, 0.03154314453233759, 0.032210418829795, 0.032877693127252416, 0.033544967424709825, 0.03421224172216723, 0.03487951601962464, 0.03554679031708206, 0.036214064614539465, 0.036881338911996873, 0.03754861320945428, 0.03821588750691169, 0.0388831618043691, 0.039550436101826514, 0.04021771039928392, 0.04088498469674133, 0.04155225899419874, 0.042219533291656154, 0.04288680758911356, 0.04355408188657097, 0.04422135618402838, 0.044888630481485794, 0.0455559047789432, 0.04622317907640061, 0.04689045337385802, 0.047557727671315435, 0.04822500196877284, 0.04889227626623025, 0.04955955056368766, 0.05022682486114507, 0.050894099158602484, 0.05156137345605989, 0.0522286477535173, 0.05289592205097471, 0.053563196348432124, 0.05423047064588953, 0.05489774494334694, 0.05556501924080435, 0.056232293538261764, 0.05689956783571917, 0.05756684213317658, 0.05823411643063399, 0.058901390728091405, 0.05956866502554881, 0.06023593932300622, 0.06090321362046363, 0.06157048791792104, 0.06223776221537845, 0.06290503651283587, 0.06357231081029327, 0.06423958510775069, 0.0649068594052081, 0.0655741337026655, 0.06624140800012292, 0.06690868229758032, 0.06757595659503773, 0.06824323089249515, 0.06891050518995255, 0.06957777948740997, 0.07024505378486737, 0.07091232808232478, 0.07157960237978218, 0.0722468766772396], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [10.308731066474998, 11.835657634102498, 13.332381875747762, 14.782893172332194, 16.17424820453624, 17.496185228271525, 18.740779010333462, 19.902132547007064, 20.97610203471164, 21.96005187854972, 22.852636814303615, 23.65360848423967, 24.363644049090762, 24.984194639687633, 25.51735165363559, 25.965729086787693, 26.332360257515063, 26.620607435272813, 26.83408302494474, 26.97658108606236, 27.052018082279794, 27.064381862406616, 27.017687970737935, 26.91594247218467, 26.763110557539065, 26.563090266793743, 26.31969073439071, 26.036614420183902, 25.71744284427981, 25.365625393257663, 24.984470810003987, 24.577141019931485, 24.14664698305846, 23.695846294641623, 23.22744228709274, 22.743984413052026, 22.247869713997407, 21.741345200878417, 21.226510993190757, 20.705324080854492, 20.179602589403324, 19.651030443503373, 19.121162336845686, 18.59142892813819, 18.063142193383467, 17.537500873985348, 17.01559596858366, 16.498416223968384, 15.986853587058691, 15.481708585828255, 14.983695612287958, 14.493448085265781, 14.011523474811547, 13.538408173654767, 13.074522204306883, 12.62022375316887, 12.17581352542237, 11.74153891658389, 11.31759799842017, 10.904143318488977, 10.501285513910693, 10.109096741116455, 9.727613924280643, 9.356841825949598, 8.996755944042334, 8.647305239939316, 8.308414702806344, 7.979987755636477, 7.661908508744171, 7.354043866624335, 7.056245494203771, 6.768351648572088, 6.490188882291313, 6.2215736243550115, 5.962313644804748, 5.712209408919576, 5.471055326777697, 5.238640903852907, 5.0147517981554905, 4.799170789261288, 4.591678664396548, 4.392055026562594, 4.20007902949532, 4.015530044062207, 3.838188260505377, 3.6678352307449735, 3.5042543547636447, 3.3472313149016037, 3.1965544617033372, 3.052015154772145, 2.9134080619082803, 2.7805314196307562, 2.6531872580122164, 2.5311815925914254, 2.414324585968405, 2.302430681533982, 2.1953187116380444, 2.092811982359382, 1.9947383369047698, 1.90093019953564]],\"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\"],\"t7169a7e366814d76a8e0b331ef5a24a0\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[0.017272994178605193, 0.017494519698042773, 0.017716045217480353, 0.017937570736917933, 0.018159096256355513, 0.018380621775793093, 0.018602147295230673, 0.018823672814668253, 0.019045198334105833, 0.019266723853543413, 0.019488249372980992, 0.019709774892418572, 0.019931300411856152, 0.020152825931293732, 0.020374351450731312, 0.020595876970168892, 0.020817402489606472, 0.021038928009044052, 0.021260453528481632, 0.021481979047919212, 0.021703504567356792, 0.021925030086794372, 0.022146555606231952, 0.022368081125669532, 0.022589606645107112, 0.02281113216454469, 0.02303265768398227, 0.02325418320341985, 0.02347570872285743, 0.02369723424229501, 0.02391875976173259, 0.02414028528117017, 0.02436181080060775, 0.02458333632004533, 0.02480486183948291, 0.02502638735892049, 0.02524791287835807, 0.025469438397795655, 0.02569096391723323, 0.025912489436670814, 0.02613401495610839, 0.026355540475545974, 0.02657706599498355, 0.026798591514421134, 0.02702011703385871, 0.027241642553296294, 0.02746316807273387, 0.027684693592171454, 0.02790621911160903, 0.028127744631046614, 0.02834927015048419, 0.028570795669921774, 0.02879232118935935, 0.029013846708796934, 0.02923537222823451, 0.029456897747672094, 0.02967842326710967, 0.029899948786547254, 0.03012147430598483, 0.030342999825422413, 0.03056452534485999, 0.030786050864297573, 0.03100757638373515, 0.031229101903172733, 0.03145062742261031, 0.03167215294204789, 0.03189367846148547, 0.03211520398092305, 0.03233672950036063, 0.03255825501979821, 0.03277978053923579, 0.03300130605867337, 0.033222831578110956, 0.03344435709754853, 0.03366588261698611, 0.03388740813642369, 0.034108933655861276, 0.03433045917529885, 0.03455198469473643, 0.03477351021417401, 0.034995035733611596, 0.03521656125304917, 0.03543808677248675, 0.03565961229192433, 0.035881137811361916, 0.03610266333079949, 0.03632418885023707, 0.03654571436967465, 0.036767239889112235, 0.03698876540854981, 0.03721029092798739, 0.03743181644742497, 0.037653341966862555, 0.03787486748630013, 0.03809639300573771, 0.03831791852517529, 0.038539444044612875, 0.03876096956405045, 0.03898249508348803, 0.03920402060292561], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [26.518481498687258, 26.60704933258654, 26.687352779451643, 26.759528614856396, 26.823715593926277, 26.880054211181786, 26.928686471877466, 26.969755674406297, 27.00340620335299, 27.029783332793706, 27.049033039453164, 27.061301825343197, 27.06673654951895, 27.065484268601903, 27.057692085729823, 27.04350700760592, 27.023075809330265, 26.99654490670727, 26.964060235733516, 26.925767138980394, 26.881810258595547, 26.832333435656853, 26.777479615621797, 26.717390759623605, 26.652207761374807, 26.582070369446587, 26.507117114700577, 26.4274852426578, 26.343310650596546, 26.25472782917871, 26.161869808411037, 26.064868107754542, 25.96385269020205, 25.858951920150385, 25.75029252489958, 25.637999559617995, 25.522196375617643, 25.403004591789816, 25.28054406905667, 25.154932887699466, 25.026287327429465, 24.894721850072393, 24.76034908474204, 24.623279815383196, 24.483622970568955, 24.34148561544097, 24.19697294568638, 24.050188283448293, 23.901233075071268, 23.750206890586476, 23.5972074248455, 23.442330500214464, 23.28567007074443, 23.127318227736513, 22.967365206624073, 22.80589939509678, 22.643007342394746, 22.47877376970356, 22.31328158158407, 22.146611878372994, 21.978843969493596, 21.810055387617695, 21.64032190362291, 21.469717542291257, 21.298314598697665, 21.126183655238776, 20.953393599254856, 20.780011641199522, 20.606103333313765, 20.43173258876294, 20.25696170119691, 20.081851364695556, 19.906460694063256, 19.730847245437772, 19.555067037180475, 19.379174571016353, 19.203222853393658, 19.027263417034536, 18.851346342649236, 18.67552028078784, 18.499832473804766, 18.32432877791238, 18.149053685301194, 17.974050346305546, 17.799360591594276, 17.625024954367273, 17.45108269253969, 17.277571810896468, 17.10452908320096, 16.93199007424199, 16.759989161804896, 16.588559558552664, 16.41773333380424, 16.247541435197544, 16.078013710225918, 15.909178927636951, 15.741064798683649, 15.573697998218275, 15.407104185620051, 15.241308025548394]],\"toyplot\");\n",
       "(function(axis, axis_id, projection)\n",
       "        {\n",
       "            axis.show_coordinates(axis_id, projection);\n",
       "        })(modules[\"toyplot.coordinates.Axis\"],\"t06028e56af084506994241837262c778\",[{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 0.09273792089255543, \"min\": 0.0}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 225.0, \"min\": 0.0}, \"scale\": \"linear\"}]);\n",
       "(function(axis, axis_id, projection)\n",
       "        {\n",
       "            axis.show_coordinates(axis_id, projection);\n",
       "        })(modules[\"toyplot.coordinates.Axis\"],\"t0dc13b693f604e97b22aaf6d9bddeac2\",[{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 30.0, \"min\": 0.0}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 200.0, \"min\": 0.0}, \"scale\": \"linear\"}]);\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\"],\"t11032cdbccd14a389d519a7a1f56d9ea\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[0.2090550374391447, 0.2933895373875875, 0.37772403733603027, 0.4620585372844731, 0.5463930372329159, 0.6307275371813587, 0.7150620371298014, 0.7993965370782442, 0.883731037026687, 0.9680655369751298, 1.0524000369235726, 1.1367345368720154, 1.2210690368204582, 1.305403536768901, 1.3897380367173437, 1.4740725366657865, 1.5584070366142293, 1.642741536562672, 1.7270760365111149, 1.8114105364595576, 1.8957450364080004, 1.9800795363564432, 2.064414036304886, 2.1487485362533287, 2.233083036201772, 2.3174175361502147, 2.4017520360986575, 2.4860865360471003, 2.570421035995543, 2.654755535943986, 2.7390900358924286, 2.8234245358408714, 2.907759035789314, 2.992093535737757, 3.0764280356861997, 3.1607625356346425, 3.2450970355830853, 3.329431535531528, 3.413766035479971, 3.4981005354284136, 3.5824350353768564, 3.666769535325299, 3.751104035273742, 3.8354385352221847, 3.9197730351706275, 4.00410753511907, 4.088442035067513, 4.172776535015956, 4.257111034964399, 4.341445534912841, 4.425780034861284, 4.510114534809727, 4.59444903475817, 4.6787835347066125, 4.763118034655055, 4.847452534603498, 4.931787034551941, 5.016121534500384, 5.100456034448826, 5.184790534397269, 5.269125034345712, 5.353459534294155, 5.437794034242597, 5.52212853419104, 5.606463034139483, 5.690797534087926, 5.7751320340363685, 5.859466533984811, 5.943801033933254, 6.028135533881697, 6.11247003383014, 6.196804533778582, 6.281139033727025, 6.365473533675468, 6.449808033623911, 6.5341425335723535, 6.618477033520796, 6.702811533469239, 6.787146033417682, 6.871480533366125, 6.955815033314567, 7.04014953326301, 7.124484033211453, 7.208818533159896, 7.2931530331083385, 7.377487533056781, 7.461822033005224, 7.546156532953667, 7.63049103290211, 7.714825532850552, 7.799160032798995, 7.883494532747438, 7.967829032695881, 8.052163532644323, 8.136498032592767, 8.220832532541209, 8.305167032489653, 8.389501532438095, 8.473836032386538, 8.55817053233498], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.05618961477625432, 0.08583116842376552, 0.11526760867914661, 0.14341971901012482, 0.16964419947825932, 0.19356773513154515, 0.21499484676133854, 0.23385106276095385, 0.2501454457462372, 0.2639447544508621, 0.2753550821537024, 0.2845085419982118, 0.2915534877761624, 0.2966472820781938, 0.29995093959765345, 0.3016251733003924, 0.3018275028290132, 0.30071017416021, 0.29841870234021783, 0.29509089420188267, 0.29085624099668655, 0.28583559550723153, 0.2801410668537368, 0.2738760805078118, 0.2671355621118815, 0.2600062123749316, 0.2525668471521084, 0.24488878223986457, 0.23703624674383042, 0.22906681233992152, 0.22103182853058656, 0.21297685623643223, 0.20494209386678877, 0.19696279146588458, 0.1890696497013071, 0.18128920140175347, 0.17364417410459548, 0.16615383267502903, 0.15883430153551728, 0.15169886641964803, 0.14475825585697033, 0.13802090282007975, 0.1314931871346823, 0.1251796593778524, 0.11908324707769714, 0.11320544408612959, 0.10754648403120712, 0.10210549877128765, 0.09688066277401398, 0.09186932433211763, 0.08706812450790495, 0.08247310467125372, 0.07807980346381264, 0.07388334398633509, 0.06987851196789333, 0.06605982563608365, 0.062421597967031575, 0.058957991953659715, 0.055663069490788225, 0.05253083443657821, 0.04955527037189868, 0.0467303735426159, 0.04405018143472845, 0.0415087973988096, 0.0391004117084374, 0.03681931940722309, 0.03465993527070393, 0.03261680618272073, 0.030684621200936874, 0.0288582195628146, 0.027132596861606417, 0.02550290960167236, 0.023964478323637635, 0.02251278947248946, 0.021143496165603345, 0.01985241800281898, 0.01863554004698042, 0.017489011090745056, 0.016409141313882245, 0.015392399424657624, 0.014435409369169467, 0.013534946683607434, 0.012687934556281229, 0.01189143965886321, 0.011142667799548995, 0.0104389594447156, 0.009777785150099414, 0.00915674093748126, 0.008573543648312464, 0.008026026301604263, 0.007512133479697352, 0.007029916762194258, 0.006577530225343834, 0.0061532260214845055, 0.005755350050754349, 0.0053823377351362835, 0.0050327099030022015, 0.004705068790630353, 0.00439809416567388, 0.0041105395762400555]],\"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\"],\"t061dce1d5605433cab0be619af075447\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[0.422709146930687, 0.48465215639792436, 0.5465951658651618, 0.6085381753323991, 0.6704811847996364, 0.7324241942668738, 0.7943672037341112, 0.8563102132013485, 0.9182532226685858, 0.9801962321358231, 1.0421392416030606, 1.104082251070298, 1.1660252605375352, 1.2279682700047725, 1.28991127947201, 1.3518542889392473, 1.4137972984064846, 1.475740307873722, 1.5376833173409592, 1.5996263268081967, 1.661569336275434, 1.7235123457426713, 1.7854553552099088, 1.8473983646771461, 1.9093413741443834, 1.9712843836116207, 2.033227393078858, 2.0951704025460955, 2.157113412013333, 2.21905642148057, 2.2809994309478077, 2.342942440415045, 2.4048854498822823, 2.4668284593495198, 2.528771468816757, 2.5907144782839944, 2.6526574877512314, 2.714600497218469, 2.7765435066857065, 2.8384865161529436, 2.900429525620181, 2.9623725350874186, 3.0243155445546557, 3.086258554021893, 3.1482015634891307, 3.210144572956368, 3.2720875824236053, 3.3340305918908424, 3.39597360135808, 3.4579166108253174, 3.5198596202925545, 3.581802629759792, 3.643745639227029, 3.7056886486942666, 3.767631658161504, 3.829574667628741, 3.8915176770959787, 3.9534606865632163, 4.015403696030454, 4.077346705497691, 4.139289714964929, 4.201232724432166, 4.263175733899403, 4.32511874336664, 4.387061752833878, 4.449004762301115, 4.510947771768353, 4.57289078123559, 4.634833790702827, 4.696776800170065, 4.758719809637302, 4.820662819104539, 4.882605828571776, 4.944548838039014, 5.006491847506251, 5.0684348569734885, 5.1303778664407265, 5.1923208759079635, 5.254263885375201, 5.316206894842439, 5.378149904309676, 5.440092913776913, 5.502035923244151, 5.563978932711388, 5.625921942178625, 5.687864951645863, 5.7498079611131, 5.811750970580337, 5.873693980047575, 5.935636989514812, 5.997579998982049, 6.059523008449286, 6.121466017916524, 6.183409027383761, 6.245352036850998, 6.307295046318236, 6.369238055785473, 6.43118106525271, 6.493124074719948, 6.555067084187185], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.13049275212880285, 0.1506538079073765, 0.16970439696667086, 0.1875097230812666, 0.20398596430542199, 0.21908771775942545, 0.23279880438930017, 0.24512535402454483, 0.25609050047108745, 0.26573025000609296, 0.27409022727715604, 0.2812230911390033, 0.2871864708520803, 0.29204131218334356, 0.2958505501422822, 0.29867804446582946, 0.3005877280849214, 0.3016429292928079, 0.30190583626011536, 0.30143707862246466, 0.30029540559624696, 0.29853744380202063, 0.2962175209387751, 0.29338754383400695, 0.2900969213250422, 0.2863925240038099, 0.28231867415394674, 0.27791716028190755, 0.2732272715360752, 0.2682858480535848, 0.2631273439003595, 0.2577838997968825, 0.25228542326747133, 0.24665967422797225, 0.2409323543469627, 0.23512719878786098, 0.22926606917126474, 0.22336904679457786, 0.217454525314698, 0.21153930224351508, 0.20563866872885475, 0.19976649719831605, 0.19393532653279183, 0.1881564445125096, 0.18243996734304915, 0.1767949161235845, 0.1712292901659121, 0.16575013711184577, 0.16036361982928382, 0.1550750800945512, 0.14988909909124198, 0.14480955477438068, 0.13983967616384527, 0.1349820946431347, 0.1302388923491457, 0.1256116477460041, 0.1211014784815058, 0.1167090816286203, 0.112434771417055, 0.10827851456126174, 0.10423996329168043, 0.10031848619561332, 0.09651319697303742, 0.09282298121102317, 0.08924652127831915, 0.08578231943919494, 0.08242871928286258, 0.07918392556180746, 0.07604602252918932, 0.07301299086219072, 0.07008272325481982, 0.06725303876026115, 0.06452169595944078, 0.0618864050290521, 0.059344838778903335, 0.0568946427251077, 0.054533444262365297, 0.05225886099538407, 0.050068508286373735, 0.04796000607252527, 0.045930985004461716, 0.043979091953825766, 0.042101994935450505, 0.04029738748694853, 0.038562992546050744, 0.03689656586362878, 0.035295898988045506, 0.03375882185429099, 0.032283205009281175, 0.030866961502714618, 0.0295080484710006, 0.0282044684399871, 0.026954270370522632, 0.025755550469284565, 0.02460645278578959, 0.023505169615070057, 0.022449941724148416, 0.021439058419165852, 0.020470857468821727, 0.019543724898648494]],\"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\"],\"ta2f32d76b3d24ae7acf712d832b46d68\",\"data\",\"fill data\",[\"x\", \"y0\", \"y1\"],[[1.3632904565001591, 1.3836805414783233, 1.4040706264564875, 1.4244607114346517, 1.4448507964128159, 1.46524088139098, 1.4856309663691443, 1.5060210513473082, 1.5264111363254724, 1.5468012213036366, 1.5671913062818008, 1.587581391259965, 1.6079714762381292, 1.6283615612162934, 1.6487516461944576, 1.6691417311726218, 1.689531816150786, 1.7099219011289502, 1.7303119861071141, 1.7507020710852785, 1.7710921560634425, 1.7914822410416067, 1.8118723260197709, 1.832262410997935, 1.8526524959760993, 1.8730425809542635, 1.8934326659324276, 1.9138227509105918, 1.934212835888756, 1.95460292086692, 1.9749930058450844, 1.9953830908232484, 2.015773175801413, 2.0361632607795768, 2.056553345757741, 2.076943430735905, 2.0973335157140696, 2.1177236006922335, 2.1381136856703975, 2.158503770648562, 2.1788938556267263, 2.1992839406048903, 2.2196740255830543, 2.2400641105612187, 2.2604541955393826, 2.280844280517547, 2.301234365495711, 2.3216244504738754, 2.3420145354520394, 2.362404620430204, 2.382794705408368, 2.4031847903865318, 2.423574875364696, 2.4439649603428606, 2.4643550453210246, 2.4847451302991885, 2.505135215277353, 2.5255253002555174, 2.5459153852336813, 2.5663054702118453, 2.5866955551900093, 2.6070856401681737, 2.627475725146338, 2.647865810124502, 2.668255895102666, 2.6886459800808304, 2.709036065058995, 2.729426150037159, 2.749816235015323, 2.770206319993487, 2.7905964049716516, 2.8109864899498156, 2.8313765749279796, 2.8517666599061435, 2.872156744884308, 2.8925468298624724, 2.9129369148406363, 2.9333269998188003, 2.9537170847969647, 2.974107169775129, 2.994497254753293, 3.014887339731457, 3.0352774247096215, 3.055667509687786, 3.07605759466595, 3.096447679644114, 3.116837764622278, 3.137227849600442, 3.1576179345786066, 3.1780080195567706, 3.1983981045349346, 3.218788189513099, 3.2391782744912634, 3.2595683594694274, 3.2799584444475913, 3.3003485294257557, 3.3207386144039197, 3.341128699382084, 3.361518784360248, 3.3819088693384125], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.29909780672465996, 0.29976986436302766, 0.30034601679453704, 0.3008285188594945, 0.30121961269220826, 0.3015215259081918, 0.3017364699341526, 0.3018666384719843, 0.3019142060885453, 0.3018813269235311, 0.30177013350823284, 0.3015827356884248, 0.30132121964504144, 0.30098764700669434, 0.30058405404843863, 0.30011245097153794, 0.2995748212592887, 0.2989731211042598, 0.2983092789025747, 0.2975851948111207, 0.29680274036380966, 0.29596375814323533, 0.29507006150428655, 0.2941234343464694, 0.29312563093187605, 0.2920783757459132, 0.2909833633980631, 0.28984225856010576, 0.288656695939372, 0.2874282802847359, 0.2861585864231783, 0.2848491593248777, 0.2835015141948935, 0.2821171365896175, 0.2806974825562668, 0.2792439787937884, 0.27775802283363477, 0.27624098323895324, 0.27469419982081505, 0.2731189838701817, 0.2715166184043818, 0.2698883584269355, 0.2682354311996303, 0.2665590365258117, 0.2648603470439094, 0.2631405085302745, 0.26140064021045323, 0.259641835078074, 0.2578651602205693, 0.25607165715099584, 0.2542623421452628, 0.2524382065841115, 0.2506002172992323, 0.24874931692293678, 0.24688642424083673, 0.24501243454701654, 0.24312822000121162, 0.24123462998753778, 0.23933249147433996, 0.23742260937475926, 0.23550576690763728, 0.2335827259584024, 0.23165422743960504, 0.22972099165078766, 0.22778371863739774, 0.22584308854846985, 0.22389976199281952, 0.22195438039351176, 0.22000756634037916, 0.21805992394038426, 0.21611203916563146, 0.21416448019885057, 0.21221779777618452, 0.21027252552712944, 0.20832918031148293, 0.206388262553173, 0.20445025657084373, 0.20251563090509098, 0.20058483864224574, 0.1986583177346144, 0.19673649131709353, 0.1948197680200819, 0.1929085422786268, 0.19100319463774046, 0.1891040920538368, 0.18721158819223976, 0.1853260237207249, 0.18344772659905778, 0.18157701236450186, 0.17971418441327017, 0.17785953427790413, 0.17601334190056264, 0.17417587590221392, 0.17234739384772224, 0.17052814250682835, 0.16871835811102573, 0.16691826660633702, 0.1651280839019986, 0.16334801611506594, 0.16157825981095197]],\"toyplot\");\n",
       "(function(axis, axis_id, projection)\n",
       "        {\n",
       "            axis.show_coordinates(axis_id, projection);\n",
       "        })(modules[\"toyplot.coordinates.Axis\"],\"t5c40088c43f94873b3c04d2377484c5c\",[{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 9.0, \"min\": 0.0}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 225.0, \"min\": 0.0}, \"scale\": \"linear\"}]);\n",
       "(function(axis, axis_id, projection)\n",
       "        {\n",
       "            axis.show_coordinates(axis_id, projection);\n",
       "        })(modules[\"toyplot.coordinates.Axis\"],\"t3cf8a41c084e45f9b1d94cee36fe1bbd\",[{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 0.3019142060885453, \"min\": 0.0}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 200.0, \"min\": 0.0}, \"scale\": \"linear\"}]);\n",
       "})();</script></div></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# toggle these prior settings \n",
    "tool.kwargs[\"thetaprior\"] = (2.5, 0.004)\n",
    "tool.kwargs[\"tauprior\"] = (3, 0.01)\n",
    "\n",
    "# draw the distributions when using our assumptions for transforming\n",
    "tool.draw_priors(\n",
    "    gentime_min=0.99, gentime_max=1.01, \n",
    "    mutrate_min=5e-9, mutrate_max=2e-8,\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Run inference\n",
    "Distribute jobs in parallel and run replicate jobs that start MCMC from different random seeds. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parallel connection | latituba: 8 cores\n",
      "[locus filter] full data: 1000\n",
      "[locus filter] post filter: 1000\n",
      "[ipa bpp] bpp v4.1.4\n",
      "[ipa.bpp] distributed 2 bpp jobs (name=test-bpp, nloci=1000)\n",
      "[####################] 100% 3:36:37 | progress on all reps \n",
      "Parallel connection closed.\n"
     ]
    }
   ],
   "source": [
    "tool.run(auto=True, nreps=2, force=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Re-load results\n",
    "You can load your results anytime later after your runs have finished by providing the name and workdir for the job to ipa.bpp. This allows you to mess around with plotting and comparing distributions later. You also have the option here to combine the posteriors from multiple replicate runs (that used the same data and priors), or to analyze each separately. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ipyrad.analysis as ipa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ipa.bpp] found 2 existing result files\n",
      "[ipa.bpp] summarizing algorithm '00' results\n",
      "[ipa.bpp] combining mcmc files\n"
     ]
    }
   ],
   "source": [
    "# reload results by creating object with a given name and workdir\n",
    "tool = ipa.bpp(name=\"test-bpp\", workdir=\"/tmp\")\n",
    "\n",
    "# call summarize on the tool\n",
    "table, mcmc = tool.summarize_results(\"00\", individual_results=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The \"00\" tables result\n",
    "\n",
    "The main result of the \"00\" algorithm is a dataframe with the inferred parameters of the multispecies coalescent model. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>theta_1r0</th>\n",
       "      <th>theta_2r1</th>\n",
       "      <th>theta_3r2</th>\n",
       "      <th>theta_4r3</th>\n",
       "      <th>theta_5r4</th>\n",
       "      <th>theta_6r4r3r2r1r0</th>\n",
       "      <th>theta_7r4r3</th>\n",
       "      <th>theta_8r2r1r0</th>\n",
       "      <th>theta_9r1r0</th>\n",
       "      <th>tau_6r4r3r2r1r0</th>\n",
       "      <th>tau_7r4r3</th>\n",
       "      <th>tau_8r2r1r0</th>\n",
       "      <th>tau_9r1r0</th>\n",
       "      <th>lnL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.027995</td>\n",
       "      <td>0.028212</td>\n",
       "      <td>0.025590</td>\n",
       "      <td>0.009736</td>\n",
       "      <td>0.009295</td>\n",
       "      <td>0.007839</td>\n",
       "      <td>0.005385</td>\n",
       "      <td>0.022274</td>\n",
       "      <td>0.017841</td>\n",
       "      <td>0.034456</td>\n",
       "      <td>0.024037</td>\n",
       "      <td>0.026410</td>\n",
       "      <td>0.016234</td>\n",
       "      <td>-418047.448228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>median</th>\n",
       "      <td>0.027980</td>\n",
       "      <td>0.028194</td>\n",
       "      <td>0.025576</td>\n",
       "      <td>0.009733</td>\n",
       "      <td>0.009287</td>\n",
       "      <td>0.007836</td>\n",
       "      <td>0.005425</td>\n",
       "      <td>0.022171</td>\n",
       "      <td>0.017826</td>\n",
       "      <td>0.034457</td>\n",
       "      <td>0.024008</td>\n",
       "      <td>0.026409</td>\n",
       "      <td>0.016230</td>\n",
       "      <td>-418046.894000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S.D</th>\n",
       "      <td>0.000885</td>\n",
       "      <td>0.000904</td>\n",
       "      <td>0.000717</td>\n",
       "      <td>0.000304</td>\n",
       "      <td>0.000296</td>\n",
       "      <td>0.000704</td>\n",
       "      <td>0.001142</td>\n",
       "      <td>0.002391</td>\n",
       "      <td>0.001121</td>\n",
       "      <td>0.000394</td>\n",
       "      <td>0.000616</td>\n",
       "      <td>0.000444</td>\n",
       "      <td>0.000313</td>\n",
       "      <td>79.616227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.024424</td>\n",
       "      <td>0.024989</td>\n",
       "      <td>0.022996</td>\n",
       "      <td>0.008656</td>\n",
       "      <td>0.008194</td>\n",
       "      <td>0.005509</td>\n",
       "      <td>0.002602</td>\n",
       "      <td>0.014451</td>\n",
       "      <td>0.013855</td>\n",
       "      <td>0.032841</td>\n",
       "      <td>0.021608</td>\n",
       "      <td>0.024757</td>\n",
       "      <td>0.015049</td>\n",
       "      <td>-418388.687000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.032145</td>\n",
       "      <td>0.032099</td>\n",
       "      <td>0.028488</td>\n",
       "      <td>0.011026</td>\n",
       "      <td>0.010516</td>\n",
       "      <td>0.010827</td>\n",
       "      <td>0.009983</td>\n",
       "      <td>0.032692</td>\n",
       "      <td>0.023367</td>\n",
       "      <td>0.036106</td>\n",
       "      <td>0.026211</td>\n",
       "      <td>0.028206</td>\n",
       "      <td>0.017480</td>\n",
       "      <td>-417729.014000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.5%</th>\n",
       "      <td>0.026300</td>\n",
       "      <td>0.026481</td>\n",
       "      <td>0.024243</td>\n",
       "      <td>0.009154</td>\n",
       "      <td>0.008728</td>\n",
       "      <td>0.006511</td>\n",
       "      <td>0.003146</td>\n",
       "      <td>0.017910</td>\n",
       "      <td>0.015693</td>\n",
       "      <td>0.033689</td>\n",
       "      <td>0.022892</td>\n",
       "      <td>0.025541</td>\n",
       "      <td>0.015626</td>\n",
       "      <td>-418202.863000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97.5%</th>\n",
       "      <td>0.029785</td>\n",
       "      <td>0.030023</td>\n",
       "      <td>0.027033</td>\n",
       "      <td>0.010342</td>\n",
       "      <td>0.009899</td>\n",
       "      <td>0.009229</td>\n",
       "      <td>0.007568</td>\n",
       "      <td>0.027284</td>\n",
       "      <td>0.020108</td>\n",
       "      <td>0.035223</td>\n",
       "      <td>0.025280</td>\n",
       "      <td>0.027283</td>\n",
       "      <td>0.016861</td>\n",
       "      <td>-417892.551000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.5%HPD</th>\n",
       "      <td>0.026283</td>\n",
       "      <td>0.026471</td>\n",
       "      <td>0.024219</td>\n",
       "      <td>0.009152</td>\n",
       "      <td>0.008691</td>\n",
       "      <td>0.006477</td>\n",
       "      <td>0.002991</td>\n",
       "      <td>0.017773</td>\n",
       "      <td>0.015733</td>\n",
       "      <td>0.033673</td>\n",
       "      <td>0.022859</td>\n",
       "      <td>0.025528</td>\n",
       "      <td>0.015623</td>\n",
       "      <td>-418201.078000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97.5%HPD</th>\n",
       "      <td>0.029757</td>\n",
       "      <td>0.030004</td>\n",
       "      <td>0.027007</td>\n",
       "      <td>0.010338</td>\n",
       "      <td>0.009860</td>\n",
       "      <td>0.009190</td>\n",
       "      <td>0.007314</td>\n",
       "      <td>0.027099</td>\n",
       "      <td>0.020134</td>\n",
       "      <td>0.035200</td>\n",
       "      <td>0.025239</td>\n",
       "      <td>0.027268</td>\n",
       "      <td>0.016855</td>\n",
       "      <td>-417891.188000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ESS*</th>\n",
       "      <td>12262.897304</td>\n",
       "      <td>11997.844527</td>\n",
       "      <td>13891.059855</td>\n",
       "      <td>6974.445253</td>\n",
       "      <td>6525.824045</td>\n",
       "      <td>436.125051</td>\n",
       "      <td>123.289724</td>\n",
       "      <td>1897.302231</td>\n",
       "      <td>3587.614817</td>\n",
       "      <td>579.708878</td>\n",
       "      <td>147.436912</td>\n",
       "      <td>2641.537188</td>\n",
       "      <td>4378.739376</td>\n",
       "      <td>2087.556267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eff*</th>\n",
       "      <td>0.613145</td>\n",
       "      <td>0.599892</td>\n",
       "      <td>0.694553</td>\n",
       "      <td>0.348722</td>\n",
       "      <td>0.326291</td>\n",
       "      <td>0.021806</td>\n",
       "      <td>0.006164</td>\n",
       "      <td>0.094865</td>\n",
       "      <td>0.179381</td>\n",
       "      <td>0.028985</td>\n",
       "      <td>0.007372</td>\n",
       "      <td>0.132077</td>\n",
       "      <td>0.218937</td>\n",
       "      <td>0.104378</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             theta_1r0     theta_2r1     theta_3r2    theta_4r3    theta_5r4  \\\n",
       "mean          0.027995      0.028212      0.025590     0.009736     0.009295   \n",
       "median        0.027980      0.028194      0.025576     0.009733     0.009287   \n",
       "S.D           0.000885      0.000904      0.000717     0.000304     0.000296   \n",
       "min           0.024424      0.024989      0.022996     0.008656     0.008194   \n",
       "max           0.032145      0.032099      0.028488     0.011026     0.010516   \n",
       "2.5%          0.026300      0.026481      0.024243     0.009154     0.008728   \n",
       "97.5%         0.029785      0.030023      0.027033     0.010342     0.009899   \n",
       "2.5%HPD       0.026283      0.026471      0.024219     0.009152     0.008691   \n",
       "97.5%HPD      0.029757      0.030004      0.027007     0.010338     0.009860   \n",
       "ESS*      12262.897304  11997.844527  13891.059855  6974.445253  6525.824045   \n",
       "Eff*          0.613145      0.599892      0.694553     0.348722     0.326291   \n",
       "\n",
       "         theta_6r4r3r2r1r0 theta_7r4r3 theta_8r2r1r0  theta_9r1r0  \\\n",
       "mean              0.007839    0.005385      0.022274     0.017841   \n",
       "median            0.007836    0.005425      0.022171     0.017826   \n",
       "S.D               0.000704    0.001142      0.002391     0.001121   \n",
       "min               0.005509    0.002602      0.014451     0.013855   \n",
       "max               0.010827    0.009983      0.032692     0.023367   \n",
       "2.5%              0.006511    0.003146      0.017910     0.015693   \n",
       "97.5%             0.009229    0.007568      0.027284     0.020108   \n",
       "2.5%HPD           0.006477    0.002991      0.017773     0.015733   \n",
       "97.5%HPD          0.009190    0.007314      0.027099     0.020134   \n",
       "ESS*            436.125051  123.289724   1897.302231  3587.614817   \n",
       "Eff*              0.021806    0.006164      0.094865     0.179381   \n",
       "\n",
       "         tau_6r4r3r2r1r0   tau_7r4r3  tau_8r2r1r0    tau_9r1r0             lnL  \n",
       "mean            0.034456    0.024037     0.026410     0.016234  -418047.448228  \n",
       "median          0.034457    0.024008     0.026409     0.016230  -418046.894000  \n",
       "S.D             0.000394    0.000616     0.000444     0.000313       79.616227  \n",
       "min             0.032841    0.021608     0.024757     0.015049  -418388.687000  \n",
       "max             0.036106    0.026211     0.028206     0.017480  -417729.014000  \n",
       "2.5%            0.033689    0.022892     0.025541     0.015626  -418202.863000  \n",
       "97.5%           0.035223    0.025280     0.027283     0.016861  -417892.551000  \n",
       "2.5%HPD         0.033673    0.022859     0.025528     0.015623  -418201.078000  \n",
       "97.5%HPD        0.035200    0.025239     0.027268     0.016855  -417891.188000  \n",
       "ESS*          579.708878  147.436912  2641.537188  4378.739376     2087.556267  \n",
       "Eff*            0.028985    0.007372     0.132077     0.218937        0.104378  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# tables is a summary of the posteriors\n",
    "table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Converting units from the table results\n",
    "The results are often difficult to interpret without converting the units into a more easily interpretable type. For example, the theta parameters represent the population effective mutation rate (`4*Ne*u`), but we are typically more interested in just knowing `N`. Similarly, the tau parameters are in units of percent sequence divergence (u/gen) but we instead like to know the divergence time estimates in units of years, or millions of years.\n",
    "\n",
    "To convert these units we need an estimate of the per-site per-generation mutation-rate (u) and the generation time of our organism (g). Rather than offering a point estimate it is more appropriate in the Bayesian context to provide these values a statistical distribution. This is similar to how we described our priors using a gamma or inverse-gamma distribution earlier, and how we used a distribution of u and g to check the reasonable conversion of the units.\n",
    "\n",
    "In the example below the converted units can be compared with the true simulation scenario at the beginning of this notebook where we set the divergence times and Ne values on the tree. Among the tip-level taxa we can see that mean Ne estimates are around 2e5 or ~6e5, which is pretty accurate, and the root divergence time is at 3e6, which is correct. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "df = tool.transform(mcmc, 0.99, 1.01, 5e-9, 2e-8).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
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       "      <th>Ne_1r0</th>\n",
       "      <td>6.16e+05</td>\n",
       "      <td>5.78e+05</td>\n",
       "      <td>2.05e+05</td>\n",
       "      <td>1.89e+05</td>\n",
       "      <td>2.55e+06</td>\n",
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       "    <tr>\n",
       "      <th>Ne_2r1</th>\n",
       "      <td>6.2e+05</td>\n",
       "      <td>5.83e+05</td>\n",
       "      <td>2.06e+05</td>\n",
       "      <td>1.9e+05</td>\n",
       "      <td>2.57e+06</td>\n",
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       "    <tr>\n",
       "      <th>Ne_3r2</th>\n",
       "      <td>5.63e+05</td>\n",
       "      <td>5.29e+05</td>\n",
       "      <td>1.87e+05</td>\n",
       "      <td>1.72e+05</td>\n",
       "      <td>2.28e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ne_4r3</th>\n",
       "      <td>2.14e+05</td>\n",
       "      <td>2.01e+05</td>\n",
       "      <td>7.12e+04</td>\n",
       "      <td>6.57e+04</td>\n",
       "      <td>8.87e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ne_5r4</th>\n",
       "      <td>2.04e+05</td>\n",
       "      <td>1.92e+05</td>\n",
       "      <td>6.8e+04</td>\n",
       "      <td>6.26e+04</td>\n",
       "      <td>8.47e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ne_6r4r3r2r1r0</th>\n",
       "      <td>1.73e+05</td>\n",
       "      <td>1.62e+05</td>\n",
       "      <td>5.93e+04</td>\n",
       "      <td>5.47e+04</td>\n",
       "      <td>7.23e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ne_7r4r3</th>\n",
       "      <td>1.2e+05</td>\n",
       "      <td>1.11e+05</td>\n",
       "      <td>4.54e+04</td>\n",
       "      <td>2.8e+04</td>\n",
       "      <td>5.7e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ne_8r2r1r0</th>\n",
       "      <td>4.91e+05</td>\n",
       "      <td>4.59e+05</td>\n",
       "      <td>1.71e+05</td>\n",
       "      <td>1.45e+05</td>\n",
       "      <td>2.17e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ne_9r1r0</th>\n",
       "      <td>3.92e+05</td>\n",
       "      <td>3.68e+05</td>\n",
       "      <td>1.32e+05</td>\n",
       "      <td>1.3e+05</td>\n",
       "      <td>1.71e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>div_6r4r3r2r1r0</th>\n",
       "      <td>3.03e+06</td>\n",
       "      <td>2.85e+06</td>\n",
       "      <td>1e+06</td>\n",
       "      <td>9.51e+05</td>\n",
       "      <td>1.24e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>div_7r4r3</th>\n",
       "      <td>2.11e+06</td>\n",
       "      <td>1.98e+06</td>\n",
       "      <td>7.01e+05</td>\n",
       "      <td>6.42e+05</td>\n",
       "      <td>8.56e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>div_8r2r1r0</th>\n",
       "      <td>2.32e+06</td>\n",
       "      <td>2.18e+06</td>\n",
       "      <td>7.7e+05</td>\n",
       "      <td>7.2e+05</td>\n",
       "      <td>9.46e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>div_9r1r0</th>\n",
       "      <td>1.43e+06</td>\n",
       "      <td>1.34e+06</td>\n",
       "      <td>4.74e+05</td>\n",
       "      <td>4.4e+05</td>\n",
       "      <td>5.81e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lnL</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     mean    median       S.D       min       max\n",
       "Ne_1r0           6.16e+05  5.78e+05  2.05e+05  1.89e+05  2.55e+06\n",
       "Ne_2r1            6.2e+05  5.83e+05  2.06e+05   1.9e+05  2.57e+06\n",
       "Ne_3r2           5.63e+05  5.29e+05  1.87e+05  1.72e+05  2.28e+06\n",
       "Ne_4r3           2.14e+05  2.01e+05  7.12e+04  6.57e+04  8.87e+05\n",
       "Ne_5r4           2.04e+05  1.92e+05   6.8e+04  6.26e+04  8.47e+05\n",
       "Ne_6r4r3r2r1r0   1.73e+05  1.62e+05  5.93e+04  5.47e+04  7.23e+05\n",
       "Ne_7r4r3          1.2e+05  1.11e+05  4.54e+04   2.8e+04   5.7e+05\n",
       "Ne_8r2r1r0       4.91e+05  4.59e+05  1.71e+05  1.45e+05  2.17e+06\n",
       "Ne_9r1r0         3.92e+05  3.68e+05  1.32e+05   1.3e+05  1.71e+06\n",
       "div_6r4r3r2r1r0  3.03e+06  2.85e+06     1e+06  9.51e+05  1.24e+07\n",
       "div_7r4r3        2.11e+06  1.98e+06  7.01e+05  6.42e+05  8.56e+06\n",
       "div_8r2r1r0      2.32e+06  2.18e+06   7.7e+05   7.2e+05  9.46e+06\n",
       "div_9r1r0        1.43e+06  1.34e+06  4.74e+05   4.4e+05  5.81e+06\n",
       "lnL                   NaN       NaN       NaN       NaN       NaN"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot posteriors\n",
    "You can plot several posterior distributions on a shared axis using the `.draw_posteriors()` function. This takes a list of tuples as input, where each tuple is the (mean, variance) of a parameter estimate. You can draw the posteriors from a single analysis using this function or combine results from several different analyses if you wish. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
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     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "# get only the divergence time result\n",
    "subd = df.loc[[i for i in df.index if \"div_\" in i], :]\n",
    "\n",
    "# get results as tuple pairs with (mean, var)\n",
    "tuples = [\n",
    "    (i, j) for (i, j) in \n",
    "    zip(subd[\"mean\"], subd.loc[:, \"S.D\"] ** 2)\n",
    "]\n",
    "\n",
    "# draw the results\n",
    "c, a, m = tool.draw_posteriors(\n",
    "    gamma_tuples=tuples,\n",
    "    labels=subd.index,\n",
    ");\n",
    "\n",
    "# style the axes\n",
    "a.y.ticks.labels.angle = -90"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot results on a tree\n",
    "\n",
    "... coming"
   ]
  }
 ],
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