testdocs/analysis/cookbook-distance.ipynb

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    "<h1><span style=\"color:gray\">ipyrad-analysis toolkit:</span> distance</h1>\n",
    "\n",
    "Genetic distance matrices are used in many contexts to study the evolutionary divergence of samples or populations. The `ipa.distance` module provides a simple and convenient framework to implement several distance based metrics. \n",
    "\n",
    "Key features:\n",
    "\n",
    "1. Filter SNPs to reduce missing data. \n",
    "2. Impute missing data using population allele frequencies.\n",
    "3. Calculate pairwise genetic distances between samples (e.g., p-dist, JC, HKY, Fst)\n",
    "4. (coming soon) sliding window measurements along chromosomes. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### required software"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# conda install ipyrad -c conda-forge -c bioconda\n",
    "# conda install ipcoal -c conda-forge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ipyrad.analysis as ipa\n",
    "import ipcoal\n",
    "import toyplot\n",
    "import toytree"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Species tree model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# generate and draw an imbalanced 5 tip tree\n",
    "tree = toytree.rtree.imbtree(ntips=5, treeheight=500000)\n",
    "tree.draw(ts='p');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Coalescent simulations \n",
    "The SNPs output is saved to an HDF5 database file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "wrote 1044 SNPs to /tmp/test-dist.snps.hdf5\n"
     ]
    }
   ],
   "source": [
    "# setup a model to simulate 8 haploid samples per species\n",
    "model = ipcoal.Model(tree=tree, Ne=1e4, nsamples=8)\n",
    "model.sim_loci(1000, 50)\n",
    "model.write_snps_to_hdf5(name=\"test-dist\", outdir=\"/tmp\", diploid=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# the path to the HDF5 formatted snps file\n",
    "SNPS = \"/tmp/test-dist.snps.hdf5\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### [optional] Build an IMAP dictionary\n",
    "A dictionary mapping of population names to sample names. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'r0': ['r0-0', 'r0-1', 'r0-2', 'r0-3'],\n",
       " 'r1': ['r1-0', 'r1-1', 'r1-2', 'r1-3'],\n",
       " 'r2': ['r2-0', 'r2-1', 'r2-2', 'r2-3'],\n",
       " 'r3': ['r3-0', 'r3-1', 'r3-2', 'r3-3'],\n",
       " 'r4': ['r4-0', 'r4-1', 'r4-2', 'r4-3']}"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from itertools import groupby\n",
    "\n",
    "# load sample names from SNPs file\n",
    "tool = ipa.snps_extracter(SNPS)\n",
    "\n",
    "# group names by prefix before '-'\n",
    "groups = groupby(tool.names, key=lambda x: x.split(\"-\")[0])\n",
    "\n",
    "# arrange into a dictionary\n",
    "IMAP = {i[0]: list(i[1]) for i in groups}\n",
    "\n",
    "# show the dict\n",
    "IMAP"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### calculate distances with missing values filtered and/or imputed, and *corrected*\n",
    "The correction applies a model of sequence substitution where more complex models can apply a greater penalty for unobserved changes (e.g., HKY or GTR). This allows you to use either SNPs or SEQUENCES as input. Here we are using SNPs. More on this later... (TODO). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "dist = ipa.distance(\n",
    "    data=SNPS, \n",
    "    imap=IMAP, \n",
    "    minmap={i: 1 for i in IMAP},\n",
    "    mincov=0.5,\n",
    "    impute_method=None,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Samples: 20\n",
      "Sites before filtering: 1044\n",
      "Filtered (indels): 0\n",
      "Filtered (bi-allel): 9\n",
      "Filtered (mincov): 0\n",
      "Filtered (minmap): 0\n",
      "Filtered (subsample invariant): 0\n",
      "Filtered (combined): 9\n",
      "Sites after filtering: 1035\n",
      "Sites containing missing values: 0 (0.00%)\n",
      "Missing values in SNP matrix: 0 (0.00%)\n",
      "Imputation: 'None'; (0, 1, 2) = 100.0%, 0.0%, 0.0%\n"
     ]
    }
   ],
   "source": [
    "# infer the distance matrix from sequence data\n",
    "dist.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
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       "      <td>0.910</td>\n",
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       "      <td>0.994</td>\n",
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       "r0-0  0.000  0.033  0.045  0.036  0.510  0.499  0.510  0.518  0.911  0.915   \n",
       "r0-1  0.033  0.000  0.032  0.024  0.508  0.497  0.508  0.516  0.909  0.913   \n",
       "r0-2  0.045  0.032  0.000  0.031  0.509  0.498  0.509  0.517  0.910  0.914   \n",
       "r0-3  0.036  0.024  0.031  0.000  0.505  0.494  0.505  0.513  0.906  0.910   \n",
       "r1-0  0.510  0.508  0.509  0.505  0.000  0.043  0.050  0.046  0.990  0.994   \n",
       "\n",
       "       r2-2   r2-3  \n",
       "r0-0  0.892  0.908  \n",
       "r0-1  0.890  0.906  \n",
       "r0-2  0.891  0.907  \n",
       "r0-3  0.887  0.903  \n",
       "r1-0  0.969  0.984  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# show the first few data cells\n",
    "dist.dists.iloc[:5, :12]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Infer a tree from distance matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "ename": "ToytreeError",
     "evalue": "node idx or name 6 not in tree",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mToytreeError\u001b[0m                              Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-37-963bfc412bc1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtool\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mipa\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mneighbor_joining\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmatrix\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdist\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdists\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/home/deren/Documents/ipyrad/ipyrad/analysis/neighbor_joining.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, matrix, steps)\u001b[0m\n\u001b[1;32m     69\u001b[0m             \u001b[0;31m# relabel tips\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     70\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmatrix\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 71\u001b[0;31m \t\t    tree = tree.set_node_values(\n\u001b[0m\u001b[1;32m     72\u001b[0m                         \u001b[0mfeature\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"name\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     73\u001b[0m                         \u001b[0mvalues\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mj\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmatrix\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/deren/miniconda3/envs/py38/lib/python3.7/site-packages/toytree/Toytree.py\u001b[0m in \u001b[0;36mset_node_values\u001b[0;34m(self, feature, values, default)\u001b[0m\n\u001b[1;32m    613\u001b[0m                     \u001b[0;32mif\u001b[0m \u001b[0mnidx\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mndict\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    614\u001b[0m                         raise ToytreeError(\n\u001b[0;32m--> 615\u001b[0;31m                             \"node idx or name {} not in tree\".format(nidx))\n\u001b[0m\u001b[1;32m    616\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    617\u001b[0m                 \u001b[0;31m# or, set everyone to a null value\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mToytreeError\u001b[0m: node idx or name 6 not in tree"
     ]
    }
   ],
   "source": [
    "tool = ipa.neighbor_joining(matrix=dist.dists)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Draw tree and distance matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
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       "{\n",
       "var modules={};\n",
       "modules[\"toyplot/canvas/id\"] = \"t19afc0e9e9b04240ba7729b7204f739b\";\n",
       "modules[\"toyplot/canvas\"] = (function(canvas_id)\n",
       "    {\n",
       "        return document.querySelector(\"#\" + canvas_id);\n",
       "    })(modules[\"toyplot/canvas/id\"]);\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",
       "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\"] = \"tfec8bdad85904961b4ee5535037e5d57\";\n",
       "modules[\"toyplot/root\"] = (function(root_id)\n",
       "    {\n",
       "        return document.querySelector(\"#\" + root_id);\n",
       "    })(modules[\"toyplot/root/id\"]);\n",
       "modules[\"toyplot/menus/context\"] = (function(root, canvas)\n",
       "    {\n",
       "        var wrapper = document.createElement(\"div\");\n",
       "        wrapper.innerHTML = \"<ul class='toyplot-context-menu' style='background:#eee; border:1px solid #b8b8b8; border-radius:5px; box-shadow: 0px 0px 8px rgba(0%,0%,0%,0.25); margin:0; padding:3px 0; position:fixed; visibility:hidden;'></ul>\"\n",
       "        var menu = wrapper.firstChild;\n",
       "\n",
       "        root.appendChild(menu);\n",
       "\n",
       "        var items = [];\n",
       "\n",
       "        var ignore_mouseup = null;\n",
       "        function open_menu(e)\n",
       "        {\n",
       "            var show_menu = false;\n",
       "            for(var index=0; index != items.length; ++index)\n",
       "            {\n",
       "                var item = items[index];\n",
       "                if(item.show(e))\n",
       "                {\n",
       "                    item.item.style.display = \"block\";\n",
       "                    show_menu = true;\n",
       "                }\n",
       "                else\n",
       "                {\n",
       "                    item.item.style.display = \"none\";\n",
       "                }\n",
       "            }\n",
       "\n",
       "            if(show_menu)\n",
       "            {\n",
       "                ignore_mouseup = true;\n",
       "                menu.style.left = (e.clientX + 1) + \"px\";\n",
       "                menu.style.top = (e.clientY - 5) + \"px\";\n",
       "                menu.style.visibility = \"visible\";\n",
       "                e.stopPropagation();\n",
       "                e.preventDefault();\n",
       "            }\n",
       "        }\n",
       "\n",
       "        function close_menu()\n",
       "        {\n",
       "            menu.style.visibility = \"hidden\";\n",
       "        }\n",
       "\n",
       "        function contextmenu(e)\n",
       "        {\n",
       "            open_menu(e);\n",
       "        }\n",
       "\n",
       "        function mousemove(e)\n",
       "        {\n",
       "            ignore_mouseup = false;\n",
       "        }\n",
       "\n",
       "        function mouseup(e)\n",
       "        {\n",
       "            if(ignore_mouseup)\n",
       "            {\n",
       "                ignore_mouseup = false;\n",
       "                return;\n",
       "            }\n",
       "            close_menu();\n",
       "        }\n",
       "\n",
       "        function keydown(e)\n",
       "        {\n",
       "            if(e.key == \"Escape\" || e.key == \"Esc\" || e.keyCode == 27)\n",
       "            {\n",
       "                close_menu();\n",
       "            }\n",
       "        }\n",
       "\n",
       "        canvas.addEventListener(\"contextmenu\", contextmenu);\n",
       "        canvas.addEventListener(\"mousemove\", mousemove);\n",
       "        document.addEventListener(\"mouseup\", mouseup);\n",
       "        document.addEventListener(\"keydown\", keydown);\n",
       "\n",
       "        var module = {};\n",
       "        module.add_item = function(label, show, activate)\n",
       "        {\n",
       "            var wrapper = document.createElement(\"div\");\n",
       "            wrapper.innerHTML = \"<li class='toyplot-context-menu-item' style='background:#eee; color:#333; padding:2px 20px; list-style:none; margin:0; text-align:left;'>\" + label + \"</li>\"\n",
       "            var item = wrapper.firstChild;\n",
       "\n",
       "            items.push({item: item, show: show});\n",
       "\n",
       "            function mouseover()\n",
       "            {\n",
       "                this.style.background = \"steelblue\";\n",
       "                this.style.color = \"white\";\n",
       "            }\n",
       "\n",
       "            function mouseout()\n",
       "            {\n",
       "                this.style.background = \"#eee\";\n",
       "                this.style.color = \"#333\";\n",
       "            }\n",
       "\n",
       "            function choose_item(e)\n",
       "            {\n",
       "                close_menu();\n",
       "                activate();\n",
       "\n",
       "                e.stopPropagation();\n",
       "                e.preventDefault();\n",
       "            }\n",
       "\n",
       "            item.addEventListener(\"mouseover\", mouseover);\n",
       "            item.addEventListener(\"mouseout\", mouseout);\n",
       "            item.addEventListener(\"mouseup\", choose_item);\n",
       "            item.addEventListener(\"contextmenu\", choose_item);\n",
       "\n",
       "            menu.appendChild(item);\n",
       "        };\n",
       "        return module;\n",
       "    })(modules[\"toyplot/root\"],modules[\"toyplot/canvas\"]);\n",
       "modules[\"toyplot/io\"] = (function()\n",
       "    {\n",
       "        var module = {};\n",
       "        module.save_file = function(mime_type, charset, data, filename)\n",
       "        {\n",
       "            var uri = \"data:\" + mime_type + \";charset=\" + charset + \",\" + data;\n",
       "            uri = encodeURI(uri);\n",
       "\n",
       "            var link = document.createElement(\"a\");\n",
       "            if(typeof link.download != \"undefined\")\n",
       "            {\n",
       "              link.href = uri;\n",
       "              link.style = \"visibility:hidden\";\n",
       "              link.download = filename;\n",
       "\n",
       "              document.body.appendChild(link);\n",
       "              link.click();\n",
       "              document.body.removeChild(link);\n",
       "            }\n",
       "            else\n",
       "            {\n",
       "              window.open(uri);\n",
       "            }\n",
       "        };\n",
       "        return module;\n",
       "    })();\n",
       "(function(axis, axis_id, projection)\n",
       "        {\n",
       "            axis.show_coordinates(axis_id, projection);\n",
       "        })(modules[\"toyplot.coordinates.Axis\"],\"tcc23daf1a80244a6995f22811d584327\",[{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 51554.518175999976, \"min\": -175355.50400000002}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 125.00000000000003, \"min\": 0.0}, \"scale\": \"linear\"}]);\n",
       "(function(axis, axis_id, projection)\n",
       "        {\n",
       "            axis.show_coordinates(axis_id, projection);\n",
       "        })(modules[\"toyplot.coordinates.Axis\"],\"t6957619d7af844ea94675d1ebf1eaa99\",[{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 32.08500000000001, \"min\": -1.085000000000002}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 360.0, \"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\"],\"t4931c98b30b848e2b5c974c880505d6a\",\"data\",\"table data\",[null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null],[[null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null]],\"toyplot\");\n",
       "})();</script></div></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create a canvas\n",
    "canvas = toyplot.Canvas(width=500, height=450);\n",
    "\n",
    "# add tree\n",
    "axes = canvas.cartesian(bounds=(\"10%\", \"35%\", \"10%\", \"90%\"))\n",
    "gtree.draw(axes=axes, tip_labels=True, tip_labels_align=True)\n",
    "\n",
    "# add matrix\n",
    "table = canvas.table(\n",
    "    rows=matrix.shape[0],\n",
    "    columns=matrix.shape[1],\n",
    "    margin=0,\n",
    "    bounds=(\"40%\", \"95%\", \"9%\", \"91%\"),\n",
    ")\n",
    "\n",
    "colormap = toyplot.color.brewer.map(\"BlueRed\")\n",
    "\n",
    "# apply a color to each cell in the table\n",
    "for ridx in range(matrix.shape[0]):\n",
    "    for cidx in range(matrix.shape[1]):\n",
    "        cell = table.cells.cell[ridx, cidx]\n",
    "        cell.style = {\n",
    "            \"fill\": colormap.colors(matrix.iloc[ridx, cidx], 0, 1),\n",
    "        }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>r0-0</th>\n",
       "      <th>r0-1</th>\n",
       "      <th>r1-0</th>\n",
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       "    <tr>\n",
       "      <th>r6-0</th>\n",
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       "      <td>0.111</td>\n",
       "      <td>0.667</td>\n",
       "      <td>0.762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>r6-1</th>\n",
       "      <td>0.730</td>\n",
       "      <td>0.683</td>\n",
       "      <td>0.683</td>\n",
       "      <td>0.714</td>\n",
       "      <td>0.746</td>\n",
       "      <td>0.651</td>\n",
       "      <td>0.587</td>\n",
       "      <td>0.667</td>\n",
       "      <td>0.286</td>\n",
       "      <td>0.286</td>\n",
       "      <td>0.381</td>\n",
       "      <td>0.333</td>\n",
       "      <td>0.111</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.556</td>\n",
       "      <td>0.651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>r7-0</th>\n",
       "      <td>0.746</td>\n",
       "      <td>0.698</td>\n",
       "      <td>0.698</td>\n",
       "      <td>0.730</td>\n",
       "      <td>0.762</td>\n",
       "      <td>0.667</td>\n",
       "      <td>0.603</td>\n",
       "      <td>0.683</td>\n",
       "      <td>0.492</td>\n",
       "      <td>0.492</td>\n",
       "      <td>0.587</td>\n",
       "      <td>0.540</td>\n",
       "      <td>0.667</td>\n",
       "      <td>0.556</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>r7-1</th>\n",
       "      <td>0.841</td>\n",
       "      <td>0.794</td>\n",
       "      <td>0.794</td>\n",
       "      <td>0.825</td>\n",
       "      <td>0.857</td>\n",
       "      <td>0.762</td>\n",
       "      <td>0.698</td>\n",
       "      <td>0.778</td>\n",
       "      <td>0.587</td>\n",
       "      <td>0.587</td>\n",
       "      <td>0.683</td>\n",
       "      <td>0.635</td>\n",
       "      <td>0.762</td>\n",
       "      <td>0.651</td>\n",
       "      <td>0.063</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       r0-0   r0-1   r1-0   r1-1   r2-0   r2-1   r3-0   r3-1   r4-0   r4-1  \\\n",
       "r0-0  0.000  0.079  0.556  0.587  0.873  0.778  0.714  0.794  0.730  0.730   \n",
       "r0-1  0.079  0.000  0.508  0.540  0.825  0.730  0.667  0.746  0.683  0.683   \n",
       "r1-0  0.556  0.508  0.000  0.063  0.825  0.730  0.667  0.746  0.683  0.683   \n",
       "r1-1  0.587  0.540  0.063  0.000  0.857  0.762  0.698  0.778  0.714  0.714   \n",
       "r2-0  0.873  0.825  0.825  0.857  0.000  0.063  0.476  0.556  0.746  0.746   \n",
       "r2-1  0.778  0.730  0.730  0.762  0.063  0.000  0.381  0.460  0.651  0.651   \n",
       "r3-0  0.714  0.667  0.667  0.698  0.476  0.381  0.000  0.079  0.587  0.587   \n",
       "r3-1  0.794  0.746  0.746  0.778  0.556  0.460  0.079  0.000  0.667  0.667   \n",
       "r4-0  0.730  0.683  0.683  0.714  0.746  0.651  0.587  0.667  0.000  0.095   \n",
       "r4-1  0.730  0.683  0.683  0.714  0.746  0.651  0.587  0.667  0.095  0.000   \n",
       "r5-0  0.825  0.778  0.778  0.810  0.841  0.746  0.683  0.762  0.317  0.254   \n",
       "r5-1  0.778  0.730  0.730  0.762  0.794  0.698  0.635  0.714  0.270  0.206   \n",
       "r6-0  0.778  0.730  0.730  0.762  0.794  0.698  0.635  0.714  0.397  0.397   \n",
       "r6-1  0.730  0.683  0.683  0.714  0.746  0.651  0.587  0.667  0.286  0.286   \n",
       "r7-0  0.746  0.698  0.698  0.730  0.762  0.667  0.603  0.683  0.492  0.492   \n",
       "r7-1  0.841  0.794  0.794  0.825  0.857  0.762  0.698  0.778  0.587  0.587   \n",
       "\n",
       "       r5-0   r5-1   r6-0   r6-1   r7-0   r7-1  \n",
       "r0-0  0.825  0.778  0.778  0.730  0.746  0.841  \n",
       "r0-1  0.778  0.730  0.730  0.683  0.698  0.794  \n",
       "r1-0  0.778  0.730  0.730  0.683  0.698  0.794  \n",
       "r1-1  0.810  0.762  0.762  0.714  0.730  0.825  \n",
       "r2-0  0.841  0.794  0.794  0.746  0.762  0.857  \n",
       "r2-1  0.746  0.698  0.698  0.651  0.667  0.762  \n",
       "r3-0  0.683  0.635  0.635  0.587  0.603  0.698  \n",
       "r3-1  0.762  0.714  0.714  0.667  0.683  0.778  \n",
       "r4-0  0.317  0.270  0.397  0.286  0.492  0.587  \n",
       "r4-1  0.254  0.206  0.397  0.286  0.492  0.587  \n",
       "r5-0  0.000  0.016  0.492  0.381  0.587  0.683  \n",
       "r5-1  0.016  0.000  0.444  0.333  0.540  0.635  \n",
       "r6-0  0.492  0.444  0.000  0.111  0.667  0.762  \n",
       "r6-1  0.381  0.333  0.111  0.000  0.556  0.651  \n",
       "r7-0  0.587  0.540  0.667  0.556  0.000  0.063  \n",
       "r7-1  0.683  0.635  0.762  0.651  0.063  0.000  "
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dist.dists"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "(0, 0)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m/home/deren/miniconda3/envs/py38/lib/python3.7/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2888\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2889\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2890\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: (0, 0)",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-39-fbc956fc29f0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     21\u001b[0m         \u001b[0mcell\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtable\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcells\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcell\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mridx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcidx\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     22\u001b[0m         cell.style = {\n\u001b[0;32m---> 23\u001b[0;31m             \u001b[0;34m\"fill\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mcolormap\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolors\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmatrix\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mridx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcidx\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m100\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     24\u001b[0m         }\n\u001b[1;32m     25\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/deren/miniconda3/envs/py38/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2897\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2898\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2899\u001b[0;31m             \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2900\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2901\u001b[0m                 \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/deren/miniconda3/envs/py38/lib/python3.7/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2889\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2890\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2891\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2892\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2893\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mtolerance\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: (0, 0)"
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    },
    {
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "# style the gaps between cells\n",
    "table.body.gaps.columns[:] = 3\n",
    "table.body.gaps.rows[:] = 3\n",
    "\n",
    "# hide axes coordinates\n",
    "axes.show = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Samples: 29\n",
      "Sites before filtering: 349914\n",
      "Filtered (indels): 0\n",
      "Filtered (bi-allel): 13379\n",
      "Filtered (mincov): 30459\n",
      "Filtered (minmap): 111825\n",
      "Filtered (combined): 120177\n",
      "Sites after filtering: 229737\n",
      "Sites containing missing values: 219551 (95.57%)\n",
      "Missing values in SNP matrix: 814369 (12.22%)\n",
      "Imputation: 'sampled'; (0, 1, 2) = 77.3%, 10.7%, 12.0%\n"
     ]
    }
   ],
   "source": [
    "# load the snp data into distance tool with arguments\n",
    "dist = Distance(\n",
    "    data=data, \n",
    "    imap=imap,\n",
    "    minmap=minmap,\n",
    "    mincov=0.5,\n",
    "    impute_method=\"sample\",\n",
    "    subsample_snps=False,\n",
    ")\n",
    "dist.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### save results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# save to a CSV file\n",
    "dist.dists.to_csv(\"distances.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
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       "      <td>0.579937</td>\n",
       "      <td>...</td>\n",
       "      <td>0.594005</td>\n",
       "      <td>0.582000</td>\n",
       "      <td>0.568137</td>\n",
       "      <td>0.464618</td>\n",
       "      <td>0.443942</td>\n",
       "      <td>0.579789</td>\n",
       "      <td>0.603638</td>\n",
       "      <td>0.487945</td>\n",
       "      <td>0.487936</td>\n",
       "      <td>0.590440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BJSL25</th>\n",
       "      <td>0.250447</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.235900</td>\n",
       "      <td>0.558630</td>\n",
       "      <td>0.494291</td>\n",
       "      <td>0.537193</td>\n",
       "      <td>0.566156</td>\n",
       "      <td>0.559675</td>\n",
       "      <td>0.554665</td>\n",
       "      <td>0.542768</td>\n",
       "      <td>...</td>\n",
       "      <td>0.558769</td>\n",
       "      <td>0.548897</td>\n",
       "      <td>0.532239</td>\n",
       "      <td>0.435050</td>\n",
       "      <td>0.412694</td>\n",
       "      <td>0.547182</td>\n",
       "      <td>0.567323</td>\n",
       "      <td>0.453606</td>\n",
       "      <td>0.457105</td>\n",
       "      <td>0.554882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BJVL19</th>\n",
       "      <td>0.253472</td>\n",
       "      <td>0.235900</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.567897</td>\n",
       "      <td>0.502775</td>\n",
       "      <td>0.547391</td>\n",
       "      <td>0.576355</td>\n",
       "      <td>0.569360</td>\n",
       "      <td>0.563000</td>\n",
       "      <td>0.554621</td>\n",
       "      <td>...</td>\n",
       "      <td>0.564728</td>\n",
       "      <td>0.555927</td>\n",
       "      <td>0.539913</td>\n",
       "      <td>0.441844</td>\n",
       "      <td>0.417060</td>\n",
       "      <td>0.556449</td>\n",
       "      <td>0.575336</td>\n",
       "      <td>0.464118</td>\n",
       "      <td>0.465476</td>\n",
       "      <td>0.562278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BZBB1</th>\n",
       "      <td>0.592255</td>\n",
       "      <td>0.558630</td>\n",
       "      <td>0.567897</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.280691</td>\n",
       "      <td>0.280569</td>\n",
       "      <td>0.422670</td>\n",
       "      <td>0.422962</td>\n",
       "      <td>0.426266</td>\n",
       "      <td>0.394242</td>\n",
       "      <td>...</td>\n",
       "      <td>0.559152</td>\n",
       "      <td>0.285883</td>\n",
       "      <td>0.532918</td>\n",
       "      <td>0.525701</td>\n",
       "      <td>0.542381</td>\n",
       "      <td>0.317450</td>\n",
       "      <td>0.576455</td>\n",
       "      <td>0.552554</td>\n",
       "      <td>0.551579</td>\n",
       "      <td>0.563571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CRL0001</th>\n",
       "      <td>0.530145</td>\n",
       "      <td>0.494291</td>\n",
       "      <td>0.502775</td>\n",
       "      <td>0.280691</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.239596</td>\n",
       "      <td>0.347859</td>\n",
       "      <td>0.322277</td>\n",
       "      <td>0.342836</td>\n",
       "      <td>0.213266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.470064</td>\n",
       "      <td>0.262217</td>\n",
       "      <td>0.451717</td>\n",
       "      <td>0.466429</td>\n",
       "      <td>0.477764</td>\n",
       "      <td>0.299538</td>\n",
       "      <td>0.492224</td>\n",
       "      <td>0.487327</td>\n",
       "      <td>0.484123</td>\n",
       "      <td>0.482726</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            BJSB3    BJSL25    BJVL19     BZBB1   CRL0001   CRL0030     CUCA4  \\\n",
       "BJSB3    0.000000  0.250447  0.253472  0.592255  0.530145  0.572576  0.601853   \n",
       "BJSL25   0.250447  0.000000  0.235900  0.558630  0.494291  0.537193  0.566156   \n",
       "BJVL19   0.253472  0.235900  0.000000  0.567897  0.502775  0.547391  0.576355   \n",
       "BZBB1    0.592255  0.558630  0.567897  0.000000  0.280691  0.280569  0.422670   \n",
       "CRL0001  0.530145  0.494291  0.502775  0.280691  0.000000  0.239596  0.347859   \n",
       "\n",
       "            CUMM5     CUSV6    CUVN10  ...     FLWO6    HNDA09     LALC2  \\\n",
       "BJSB3    0.597044  0.591990  0.579937  ...  0.594005  0.582000  0.568137   \n",
       "BJSL25   0.559675  0.554665  0.542768  ...  0.558769  0.548897  0.532239   \n",
       "BJVL19   0.569360  0.563000  0.554621  ...  0.564728  0.555927  0.539913   \n",
       "BZBB1    0.422962  0.426266  0.394242  ...  0.559152  0.285883  0.532918   \n",
       "CRL0001  0.322277  0.342836  0.213266  ...  0.470064  0.262217  0.451717   \n",
       "\n",
       "            MXED8     MXGT4  MXSA3017     SCCU3     TXGR3     TXMD3     TXWV2  \n",
       "BJSB3    0.464618  0.443942  0.579789  0.603638  0.487945  0.487936  0.590440  \n",
       "BJSL25   0.435050  0.412694  0.547182  0.567323  0.453606  0.457105  0.554882  \n",
       "BJVL19   0.441844  0.417060  0.556449  0.575336  0.464118  0.465476  0.562278  \n",
       "BZBB1    0.525701  0.542381  0.317450  0.576455  0.552554  0.551579  0.563571  \n",
       "CRL0001  0.466429  0.477764  0.299538  0.492224  0.487327  0.484123  0.482726  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# show the upper corner \n",
    "dist.dists.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Draw the matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "            context_menu.add_item(\"Save \" + label + \" as CSV\", show_item, choose_item);\n",
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       "})();</script></div></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "toyplot.matrix(\n",
    "    dist.dists, \n",
    "    bshow=False,\n",
    "    tshow=False,\n",
    "    rlocator=toyplot.locator.Explicit(\n",
    "        range(len(dist.names)),\n",
    "        sorted(dist.names),\n",
    "));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Draw matrix reordered to match groups in imap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get list of concatenated names from each group\n",
    "ordered_names = []\n",
    "for group in dist.imap.values():\n",
    "    ordered_names += group\n",
    "\n",
    "# reorder matrix to match name order    \n",
    "ordered_matrix = dist.dists[ordered_names].T[ordered_names]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "{\n",
       "var modules={};\n",
       "modules[\"toyplot/tables\"] = (function()\n",
       "    {\n",
       "        var tables = [];\n",
       "\n",
       "        var module = {};\n",
       "\n",
       "        module.set = function(owner, key, names, columns)\n",
       "        {\n",
       "            tables.push({owner: owner, key: key, names: names, columns: columns});\n",
       "        }\n",
       "\n",
       "        module.get = function(owner, key)\n",
       "        {\n",
       "            for(var i = 0; i != tables.length; ++i)\n",
       "            {\n",
       "                var table = tables[i];\n",
       "                if(table.owner != owner)\n",
       "                    continue;\n",
       "                if(table.key != key)\n",
       "                    continue;\n",
       "                return {names: table.names, columns: table.columns};\n",
       "            }\n",
       "        }\n",
       "\n",
       "        module.get_csv = function(owner, key)\n",
       "        {\n",
       "            var table = module.get(owner, key);\n",
       "            if(table != undefined)\n",
       "            {\n",
       "                var csv = \"\";\n",
       "                csv += table.names.join(\",\") + \"\\n\";\n",
       "                for(var i = 0; i != table.columns[0].length; ++i)\n",
       "                {\n",
       "                  for(var j = 0; j != table.columns.length; ++j)\n",
       "                  {\n",
       "                    if(j)\n",
       "                      csv += \",\";\n",
       "                    csv += table.columns[j][i];\n",
       "                  }\n",
       "                  csv += \"\\n\";\n",
       "                }\n",
       "                return csv;\n",
       "            }\n",
       "        }\n",
       "\n",
       "        return module;\n",
       "    })();\n",
       "modules[\"toyplot/root/id\"] = \"t1065ec6b94a7445498e6c03d5a043443\";\n",
       "modules[\"toyplot/root\"] = (function(root_id)\n",
       "    {\n",
       "        return document.querySelector(\"#\" + root_id);\n",
       "    })(modules[\"toyplot/root/id\"]);\n",
       "modules[\"toyplot/canvas/id\"] = \"te56369b7ffaf44ae952e6df25bc58784\";\n",
       "modules[\"toyplot/canvas\"] = (function(canvas_id)\n",
       "    {\n",
       "        return document.querySelector(\"#\" + canvas_id);\n",
       "    })(modules[\"toyplot/canvas/id\"]);\n",
       "modules[\"toyplot/menus/context\"] = (function(root, canvas)\n",
       "    {\n",
       "        var wrapper = document.createElement(\"div\");\n",
       "        wrapper.innerHTML = \"<ul class='toyplot-context-menu' style='background:#eee; border:1px solid #b8b8b8; border-radius:5px; box-shadow: 0px 0px 8px rgba(0%,0%,0%,0.25); margin:0; padding:3px 0; position:fixed; visibility:hidden;'></ul>\"\n",
       "        var menu = wrapper.firstChild;\n",
       "\n",
       "        root.appendChild(menu);\n",
       "\n",
       "        var items = [];\n",
       "\n",
       "        var ignore_mouseup = null;\n",
       "        function open_menu(e)\n",
       "        {\n",
       "            var show_menu = false;\n",
       "            for(var index=0; index != items.length; ++index)\n",
       "            {\n",
       "                var item = items[index];\n",
       "                if(item.show(e))\n",
       "                {\n",
       "                    item.item.style.display = \"block\";\n",
       "                    show_menu = true;\n",
       "                }\n",
       "                else\n",
       "                {\n",
       "                    item.item.style.display = \"none\";\n",
       "                }\n",
       "            }\n",
       "\n",
       "            if(show_menu)\n",
       "            {\n",
       "                ignore_mouseup = true;\n",
       "                menu.style.left = (e.clientX + 1) + \"px\";\n",
       "                menu.style.top = (e.clientY - 5) + \"px\";\n",
       "                menu.style.visibility = \"visible\";\n",
       "                e.stopPropagation();\n",
       "                e.preventDefault();\n",
       "            }\n",
       "        }\n",
       "\n",
       "        function close_menu()\n",
       "        {\n",
       "            menu.style.visibility = \"hidden\";\n",
       "        }\n",
       "\n",
       "        function contextmenu(e)\n",
       "        {\n",
       "            open_menu(e);\n",
       "        }\n",
       "\n",
       "        function mousemove(e)\n",
       "        {\n",
       "            ignore_mouseup = false;\n",
       "        }\n",
       "\n",
       "        function mouseup(e)\n",
       "        {\n",
       "            if(ignore_mouseup)\n",
       "            {\n",
       "                ignore_mouseup = false;\n",
       "                return;\n",
       "            }\n",
       "            close_menu();\n",
       "        }\n",
       "\n",
       "        function keydown(e)\n",
       "        {\n",
       "            if(e.key == \"Escape\" || e.key == \"Esc\" || e.keyCode == 27)\n",
       "            {\n",
       "                close_menu();\n",
       "            }\n",
       "        }\n",
       "\n",
       "        canvas.addEventListener(\"contextmenu\", contextmenu);\n",
       "        canvas.addEventListener(\"mousemove\", mousemove);\n",
       "        document.addEventListener(\"mouseup\", mouseup);\n",
       "        document.addEventListener(\"keydown\", keydown);\n",
       "\n",
       "        var module = {};\n",
       "        module.add_item = function(label, show, activate)\n",
       "        {\n",
       "            var wrapper = document.createElement(\"div\");\n",
       "            wrapper.innerHTML = \"<li class='toyplot-context-menu-item' style='background:#eee; color:#333; padding:2px 20px; list-style:none; margin:0; text-align:left;'>\" + label + \"</li>\"\n",
       "            var item = wrapper.firstChild;\n",
       "\n",
       "            items.push({item: item, show: show});\n",
       "\n",
       "            function mouseover()\n",
       "            {\n",
       "                this.style.background = \"steelblue\";\n",
       "                this.style.color = \"white\";\n",
       "            }\n",
       "\n",
       "            function mouseout()\n",
       "            {\n",
       "                this.style.background = \"#eee\";\n",
       "                this.style.color = \"#333\";\n",
       "            }\n",
       "\n",
       "            function choose_item(e)\n",
       "            {\n",
       "                close_menu();\n",
       "                activate();\n",
       "\n",
       "                e.stopPropagation();\n",
       "                e.preventDefault();\n",
       "            }\n",
       "\n",
       "            item.addEventListener(\"mouseover\", mouseover);\n",
       "            item.addEventListener(\"mouseout\", mouseout);\n",
       "            item.addEventListener(\"mouseup\", choose_item);\n",
       "            item.addEventListener(\"contextmenu\", choose_item);\n",
       "\n",
       "            menu.appendChild(item);\n",
       "        };\n",
       "        return module;\n",
       "    })(modules[\"toyplot/root\"],modules[\"toyplot/canvas\"]);\n",
       "modules[\"toyplot/io\"] = (function()\n",
       "    {\n",
       "        var module = {};\n",
       "        module.save_file = function(mime_type, charset, data, filename)\n",
       "        {\n",
       "            var uri = \"data:\" + mime_type + \";charset=\" + charset + \",\" + data;\n",
       "            uri = encodeURI(uri);\n",
       "\n",
       "            var link = document.createElement(\"a\");\n",
       "            if(typeof link.download != \"undefined\")\n",
       "            {\n",
       "              link.href = uri;\n",
       "              link.style = \"visibility:hidden\";\n",
       "              link.download = filename;\n",
       "\n",
       "              document.body.appendChild(link);\n",
       "              link.click();\n",
       "              document.body.removeChild(link);\n",
       "            }\n",
       "            else\n",
       "            {\n",
       "              window.open(uri);\n",
       "            }\n",
       "        };\n",
       "        return module;\n",
       "    })();\n",
       "(function(tables, context_menu, io, owner_id, key, label, names, columns, filename)\n",
       "        {\n",
       "            tables.set(owner_id, key, names, columns);\n",
       "\n",
       "            var owner = document.querySelector(\"#\" + owner_id);\n",
       "            function show_item(e)\n",
       "            {\n",
       "                return owner.contains(e.target);\n",
       "            }\n",
       "\n",
       "            function choose_item()\n",
       "            {\n",
       "                io.save_file(\"text/csv\", \"utf-8\", tables.get_csv(owner_id, key), filename + \".csv\");\n",
       "            }\n",
       "\n",
       "            context_menu.add_item(\"Save \" + label + \" as CSV\", show_item, choose_item);\n",
       "        })(modules[\"toyplot/tables\"],modules[\"toyplot/menus/context\"],modules[\"toyplot/io\"],\"t43b156db23d342a18a7cdfda3e76b088\",\"data\",\"table data\",[null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null],[[null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], [null, \"0\", \"1\", \"2\", \"3\", \"4\", \"5\", \"6\", \"7\", \"8\", \"9\", \"10\", \"11\", \"12\", \"13\", \"14\", \"15\", \"16\", \"17\", \"18\", \"19\", \"20\", \"21\", \"22\", \"23\", \"24\", \"25\", \"26\", \"27\", \"28\", null, null], [null, 0.0, 0.2993858194370084, 0.322760373818758, 0.3187296778490187, 0.30106164875488056, 0.4550986562895833, 0.4568528360690703, 0.4938516651649495, 0.4685792884907525, 0.45445008857954966, 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       "})();</script></div></div>"
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     "metadata": {},
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    }
   ],
   "source": [
    "toyplot.matrix(\n",
    "    ordered_matrix,\n",
    "    bshow=False,\n",
    "    tshow=False,\n",
    "    rlocator=toyplot.locator.Explicit(\n",
    "        range(len(ordered_names)),\n",
    "        ordered_names,\n",
    "));"
   ]
  }
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