{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# Mads Notebooks: Contamination"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import Mads in Julia"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import Mads"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Change the working directory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "cd(joinpath(Pkg.dir(\"Mads\"), \"examples\", \"contamination\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load Mads input file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
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       "     xmlns:xlink=\"http://www.w3.org/1999/xlink\"\n",
       "     xmlns:gadfly=\"http://www.gadflyjl.org/ns\"\n",
       "     version=\"1.2\"\n",
       "     width=\"141.42mm\" height=\"100mm\" viewBox=\"0 0 141.42 100\"\n",
       "     stroke=\"none\"\n",
       "     fill=\"#000000\"\n",
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       "                        this.mouseover(fn2, scope);\n",
       "                    } else {\n",
       "                        this.mouseout(fn2, scope);\n",
       "                    }\n",
       "                }\n",
       "                return this;\n",
       "            };\n",
       "        })(events[i]);\n",
       "    }\n",
       "\n",
       "\n",
       "    Element.prototype.mousewheel = function (fn, scope) {\n",
       "        if (Snap.is(fn, \"function\")) {\n",
       "            var el = this;\n",
       "            var fn2 = function (event) {\n",
       "                fn.apply(el, [event]);\n",
       "            };\n",
       "        }\n",
       "\n",
       "        this.node.addEventListener(\n",
       "            /Firefox/i.test(navigator.userAgent) ? \"DOMMouseScroll\" : \"mousewheel\",\n",
       "            fn2);\n",
       "\n",
       "        return this;\n",
       "    };\n",
       "\n",
       "\n",
       "    // Snap's attr function can be too slow for things like panning/zooming.\n",
       "    // This is a function to directly update element attributes without going\n",
       "    // through eve.\n",
       "    Element.prototype.attribute = function(key, val) {\n",
       "        if (val === undefined) {\n",
       "            return this.node.getAttribute(key);\n",
       "        } else {\n",
       "            this.node.setAttribute(key, val);\n",
       "            return this;\n",
       "        }\n",
       "    };\n",
       "\n",
       "    Element.prototype.init_gadfly = function() {\n",
       "        this.mouseenter(Gadfly.plot_mouseover)\n",
       "            .mouseleave(Gadfly.plot_mouseout)\n",
       "            .dblclick(Gadfly.plot_dblclick)\n",
       "            .mousewheel(Gadfly.guide_background_scroll)\n",
       "            .drag(Gadfly.guide_background_drag_onmove,\n",
       "                  Gadfly.guide_background_drag_onstart,\n",
       "                  Gadfly.guide_background_drag_onend);\n",
       "        this.mouseenter(function (event) {\n",
       "            init_pan_zoom(this.plotroot());\n",
       "        });\n",
       "        return this;\n",
       "    };\n",
       "});\n",
       "\n",
       "\n",
       "// When the plot is moused over, emphasize the grid lines.\n",
       "Gadfly.plot_mouseover = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    var keyboard_zoom = function(event) {\n",
       "        if (event.which == 187) { // plus\n",
       "            increase_zoom_by_position(root, 0.1, true);\n",
       "        } else if (event.which == 189) { // minus\n",
       "            increase_zoom_by_position(root, -0.1, true);\n",
       "        }\n",
       "    };\n",
       "    root.data(\"keyboard_zoom\", keyboard_zoom);\n",
       "    window.addEventListener(\"keyup\", keyboard_zoom);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    xgridlines.data(\"unfocused_strokedash\",\n",
       "                    xgridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "    ygridlines.data(\"unfocused_strokedash\",\n",
       "                    ygridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "\n",
       "    // emphasize grid lines\n",
       "    var destcolor = root.data(\"focused_xgrid_color\");\n",
       "    xgridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"focused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // reveal zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 1.0}, 250);\n",
       "};\n",
       "\n",
       "// Reset pan and zoom on double click\n",
       "Gadfly.plot_dblclick = function(event) {\n",
       "  set_plot_pan_zoom(this.plotroot(), 0.0, 0.0, 1.0);\n",
       "};\n",
       "\n",
       "// Unemphasize grid lines on mouse out.\n",
       "Gadfly.plot_mouseout = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    window.removeEventListener(\"keyup\", root.data(\"keyboard_zoom\"));\n",
       "    root.data(\"keyboard_zoom\", undefined);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    var destcolor = root.data(\"unfocused_xgrid_color\");\n",
       "\n",
       "    xgridlines.attribute(\"stroke-dasharray\", xgridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"unfocused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", ygridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // hide zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 0.0}, 250);\n",
       "};\n",
       "\n",
       "\n",
       "var set_geometry_transform = function(root, tx, ty, scale) {\n",
       "    var xscalable = root.hasClass(\"xscalable\"),\n",
       "        yscalable = root.hasClass(\"yscalable\");\n",
       "\n",
       "    var old_scale = root.data(\"scale\");\n",
       "\n",
       "    var xscale = xscalable ? scale : 1.0,\n",
       "        yscale = yscalable ? scale : 1.0;\n",
       "\n",
       "    tx = xscalable ? tx : 0.0;\n",
       "    ty = yscalable ? ty : 0.0;\n",
       "\n",
       "    var t = new Snap.Matrix().translate(tx, ty).scale(xscale, yscale);\n",
       "\n",
       "    root.selectAll(\".geometry, image\")\n",
       "        .forEach(function (element, i) {\n",
       "            element.transform(t);\n",
       "        });\n",
       "\n",
       "    bounds = root.plotbounds();\n",
       "\n",
       "    if (yscalable) {\n",
       "        var xfixed_t = new Snap.Matrix().translate(0, ty).scale(1.0, yscale);\n",
       "        root.selectAll(\".xfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(xfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".ylabels\")\n",
       "            .transform(xfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1, 1/scale, cx, cy).add(st);\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var y = cy * scale + ty;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.y0 <= y && y <= bounds.y1 ? \"visible\" : \"hidden\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (xscalable) {\n",
       "        var yfixed_t = new Snap.Matrix().translate(tx, 0).scale(xscale, 1.0);\n",
       "        var xtrans = new Snap.Matrix().translate(tx, 0);\n",
       "        root.selectAll(\".yfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(yfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".xlabels\")\n",
       "            .transform(yfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1/scale, 1, cx, cy).add(st);\n",
       "\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var x = cx * scale + tx;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.x0 <= x && x <= bounds.x1 ? \"visible\" : \"hidden\");\n",
       "                    }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // we must unscale anything that is scale invariance: widths, raiduses, etc.\n",
       "    var size_attribs = [\"font-size\"];\n",
       "    var unscaled_selection = \".geometry, .geometry *\";\n",
       "    if (xscalable) {\n",
       "        size_attribs.push(\"rx\");\n",
       "        unscaled_selection += \", .xgridlines\";\n",
       "    }\n",
       "    if (yscalable) {\n",
       "        size_attribs.push(\"ry\");\n",
       "        unscaled_selection += \", .ygridlines\";\n",
       "    }\n",
       "\n",
       "    root.selectAll(unscaled_selection)\n",
       "        .forEach(function (element, i) {\n",
       "            // circle need special help\n",
       "            if (element.node.nodeName == \"circle\") {\n",
       "                var cx = element.attribute(\"cx\"),\n",
       "                    cy = element.attribute(\"cy\");\n",
       "                unscale_t = new Snap.Matrix().scale(1/xscale, 1/yscale,\n",
       "                                                        cx, cy);\n",
       "                element.transform(unscale_t);\n",
       "                return;\n",
       "            }\n",
       "\n",
       "            for (i in size_attribs) {\n",
       "                var key = size_attribs[i];\n",
       "                var val = parseFloat(element.attribute(key));\n",
       "                if (val !== undefined && val != 0 && !isNaN(val)) {\n",
       "                    element.attribute(key, val * old_scale / scale);\n",
       "                }\n",
       "            }\n",
       "        });\n",
       "};\n",
       "\n",
       "\n",
       "// Find the most appropriate tick scale and update label visibility.\n",
       "var update_tickscale = function(root, scale, axis) {\n",
       "    if (!root.hasClass(axis + \"scalable\")) return;\n",
       "\n",
       "    var tickscales = root.data(axis + \"tickscales\");\n",
       "    var best_tickscale = 1.0;\n",
       "    var best_tickscale_dist = Infinity;\n",
       "    for (tickscale in tickscales) {\n",
       "        var dist = Math.abs(Math.log(tickscale) - Math.log(scale));\n",
       "        if (dist < best_tickscale_dist) {\n",
       "            best_tickscale_dist = dist;\n",
       "            best_tickscale = tickscale;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    if (best_tickscale != root.data(axis + \"tickscale\")) {\n",
       "        root.data(axis + \"tickscale\", best_tickscale);\n",
       "        var mark_inscale_gridlines = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        var mark_inscale_labels = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        root.select(\".\" + axis + \"gridlines\").selectAll(\"path\").forEach(mark_inscale_gridlines);\n",
       "        root.select(\".\" + axis + \"labels\").selectAll(\"text\").forEach(mark_inscale_labels);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "var set_plot_pan_zoom = function(root, tx, ty, scale) {\n",
       "    var old_scale = root.data(\"scale\");\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    // compute the viewport derived from tx, ty, and scale\n",
       "    var x_min = -width * scale - (scale * width - width),\n",
       "        x_max = width * scale,\n",
       "        y_min = -height * scale - (scale * height - height),\n",
       "        y_max = height * scale;\n",
       "\n",
       "    var x0 = bounds.x0 - scale * bounds.x0,\n",
       "        y0 = bounds.y0 - scale * bounds.y0;\n",
       "\n",
       "    var tx = Math.max(Math.min(tx - x0, x_max), x_min),\n",
       "        ty = Math.max(Math.min(ty - y0, y_max), y_min);\n",
       "\n",
       "    tx += x0;\n",
       "    ty += y0;\n",
       "\n",
       "    // when the scale change, we may need to alter which set of\n",
       "    // ticks is being displayed\n",
       "    if (scale != old_scale) {\n",
       "        update_tickscale(root, scale, \"x\");\n",
       "        update_tickscale(root, scale, \"y\");\n",
       "    }\n",
       "\n",
       "    set_geometry_transform(root, tx, ty, scale);\n",
       "\n",
       "    root.data(\"scale\", scale);\n",
       "    root.data(\"tx\", tx);\n",
       "    root.data(\"ty\", ty);\n",
       "};\n",
       "\n",
       "\n",
       "var scale_centered_translation = function(root, scale) {\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    var tx0 = root.data(\"tx\"),\n",
       "        ty0 = root.data(\"ty\");\n",
       "\n",
       "    var scale0 = root.data(\"scale\");\n",
       "\n",
       "    // how off from center the current view is\n",
       "    var xoff = tx0 - (bounds.x0 * (1 - scale0) + (width * (1 - scale0)) / 2),\n",
       "        yoff = ty0 - (bounds.y0 * (1 - scale0) + (height * (1 - scale0)) / 2);\n",
       "\n",
       "    // rescale offsets\n",
       "    xoff = xoff * scale / scale0;\n",
       "    yoff = yoff * scale / scale0;\n",
       "\n",
       "    // adjust for the panel position being scaled\n",
       "    var x_edge_adjust = bounds.x0 * (1 - scale),\n",
       "        y_edge_adjust = bounds.y0 * (1 - scale);\n",
       "\n",
       "    return {\n",
       "        x: xoff + x_edge_adjust + (width - width * scale) / 2,\n",
       "        y: yoff + y_edge_adjust + (height - height * scale) / 2\n",
       "    };\n",
       "};\n",
       "\n",
       "\n",
       "// Initialize data for panning zooming if it isn't already.\n",
       "var init_pan_zoom = function(root) {\n",
       "    if (root.data(\"zoompan-ready\")) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    // The non-scaling-stroke trick. Rather than try to correct for the\n",
       "    // stroke-width when zooming, we force it to a fixed value.\n",
       "    var px_per_mm = root.node.getCTM().a;\n",
       "\n",
       "    // Drag events report deltas in pixels, which we'd like to convert to\n",
       "    // millimeters.\n",
       "    root.data(\"px_per_mm\", px_per_mm);\n",
       "\n",
       "    root.selectAll(\"path\")\n",
       "        .forEach(function (element, i) {\n",
       "        sw = element.asPX(\"stroke-width\") * px_per_mm;\n",
       "        if (sw > 0) {\n",
       "            element.attribute(\"stroke-width\", sw);\n",
       "            element.attribute(\"vector-effect\", \"non-scaling-stroke\");\n",
       "        }\n",
       "    });\n",
       "\n",
       "    // Store ticks labels original tranformation\n",
       "    root.selectAll(\".xlabels > text, .ylabels > text\")\n",
       "        .forEach(function (element, i) {\n",
       "            var lm = element.transform().localMatrix;\n",
       "            element.data(\"static_transform\",\n",
       "                new Snap.Matrix(lm.a, lm.b, lm.c, lm.d, lm.e, lm.f));\n",
       "        });\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\");\n",
       "    var ygridlines = root.select(\".ygridlines\");\n",
       "    var xlabels = root.select(\".xlabels\");\n",
       "    var ylabels = root.select(\".ylabels\");\n",
       "\n",
       "    if (root.data(\"tx\") === undefined) root.data(\"tx\", 0);\n",
       "    if (root.data(\"ty\") === undefined) root.data(\"ty\", 0);\n",
       "    if (root.data(\"scale\") === undefined) root.data(\"scale\", 1.0);\n",
       "    if (root.data(\"xtickscales\") === undefined) {\n",
       "\n",
       "        // index all the tick scales that are listed\n",
       "        var xtickscales = {};\n",
       "        var ytickscales = {};\n",
       "        var add_x_tick_scales = function (element, i) {\n",
       "            xtickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "        var add_y_tick_scales = function (element, i) {\n",
       "            ytickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "\n",
       "        if (xgridlines) xgridlines.selectAll(\"path\").forEach(add_x_tick_scales);\n",
       "        if (ygridlines) ygridlines.selectAll(\"path\").forEach(add_y_tick_scales);\n",
       "        if (xlabels) xlabels.selectAll(\"text\").forEach(add_x_tick_scales);\n",
       "        if (ylabels) ylabels.selectAll(\"text\").forEach(add_y_tick_scales);\n",
       "\n",
       "        root.data(\"xtickscales\", xtickscales);\n",
       "        root.data(\"ytickscales\", ytickscales);\n",
       "        root.data(\"xtickscale\", 1.0);\n",
       "    }\n",
       "\n",
       "    var min_scale = 1.0, max_scale = 1.0;\n",
       "    for (scale in xtickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    for (scale in ytickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    root.data(\"min_scale\", min_scale);\n",
       "    root.data(\"max_scale\", max_scale);\n",
       "\n",
       "    // store the original positions of labels\n",
       "    if (xlabels) {\n",
       "        xlabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"x\", element.asPX(\"x\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    if (ylabels) {\n",
       "        ylabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"y\", element.asPX(\"y\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    // mark grid lines and ticks as in or out of scale.\n",
       "    var mark_inscale = function (element, i) {\n",
       "        element.attribute(\"gadfly:inscale\", element.attribute(\"gadfly:scale\") == 1.0);\n",
       "    };\n",
       "\n",
       "    if (xgridlines) xgridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (ygridlines) ygridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (xlabels) xlabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "    if (ylabels) ylabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "\n",
       "    // figure out the upper ond lower bounds on panning using the maximum\n",
       "    // and minum grid lines\n",
       "    var bounds = root.plotbounds();\n",
       "    var pan_bounds = {\n",
       "        x0: 0.0,\n",
       "        y0: 0.0,\n",
       "        x1: 0.0,\n",
       "        y1: 0.0\n",
       "    };\n",
       "\n",
       "    if (xgridlines) {\n",
       "        xgridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.x1 - bbox.x < pan_bounds.x0) {\n",
       "                        pan_bounds.x0 = bounds.x1 - bbox.x;\n",
       "                    }\n",
       "                    if (bounds.x0 - bbox.x > pan_bounds.x1) {\n",
       "                        pan_bounds.x1 = bounds.x0 - bbox.x;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (ygridlines) {\n",
       "        ygridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.y1 - bbox.y < pan_bounds.y0) {\n",
       "                        pan_bounds.y0 = bounds.y1 - bbox.y;\n",
       "                    }\n",
       "                    if (bounds.y0 - bbox.y > pan_bounds.y1) {\n",
       "                        pan_bounds.y1 = bounds.y0 - bbox.y;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // nudge these values a little\n",
       "    pan_bounds.x0 -= 5;\n",
       "    pan_bounds.x1 += 5;\n",
       "    pan_bounds.y0 -= 5;\n",
       "    pan_bounds.y1 += 5;\n",
       "    root.data(\"pan_bounds\", pan_bounds);\n",
       "\n",
       "    root.data(\"zoompan-ready\", true)\n",
       "};\n",
       "\n",
       "\n",
       "// drag actions, i.e. zooming and panning\n",
       "var pan_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        root.data(\"dx\", 0);\n",
       "        root.data(\"dy\", 0);\n",
       "        root.data(\"tx0\", root.data(\"tx\"));\n",
       "        root.data(\"ty0\", root.data(\"ty\"));\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        dx /= px_per_mm;\n",
       "        dy /= px_per_mm;\n",
       "\n",
       "        var tx0 = root.data(\"tx\"),\n",
       "            ty0 = root.data(\"ty\");\n",
       "\n",
       "        var dx0 = root.data(\"dx\"),\n",
       "            dy0 = root.data(\"dy\");\n",
       "\n",
       "        root.data(\"dx\", dx);\n",
       "        root.data(\"dy\", dy);\n",
       "\n",
       "        dx = dx - dx0;\n",
       "        dy = dy - dy0;\n",
       "\n",
       "        var tx = tx0 + dx,\n",
       "            ty = ty0 + dy;\n",
       "\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\"));\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        set_plot_pan_zoom(root, root.data(\"tx0\"), root.data(\"ty0\"), root.data(\"scale\"));\n",
       "    }\n",
       "};\n",
       "\n",
       "var zoom_box;\n",
       "var zoom_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        var bounds = root.plotbounds();\n",
       "        var width = bounds.x1 - bounds.x0,\n",
       "            height = bounds.y1 - bounds.y0;\n",
       "        var ratio = width / height;\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        x = xscalable ? x / px_per_mm : bounds.x0;\n",
       "        y = yscalable ? y / px_per_mm : bounds.y0;\n",
       "        var w = xscalable ? 0 : width;\n",
       "        var h = yscalable ? 0 : height;\n",
       "        zoom_box = root.rect(x, y, w, h).attr({\n",
       "            \"fill\": \"#000\",\n",
       "            \"opacity\": 0.25\n",
       "        });\n",
       "        zoom_box.data(\"ratio\", ratio);\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        var bounds = root.plotbounds();\n",
       "        if (yscalable) {\n",
       "            y /= px_per_mm;\n",
       "            y = Math.max(bounds.y0, y);\n",
       "            y = Math.min(bounds.y1, y);\n",
       "        } else {\n",
       "            y = bounds.y1;\n",
       "        }\n",
       "        if (xscalable) {\n",
       "            x /= px_per_mm;\n",
       "            x = Math.max(bounds.x0, x);\n",
       "            x = Math.min(bounds.x1, x);\n",
       "        } else {\n",
       "            x = bounds.x1;\n",
       "        }\n",
       "\n",
       "        dx = x - zoom_box.attr(\"x\");\n",
       "        dy = y - zoom_box.attr(\"y\");\n",
       "        if (xscalable && yscalable) {\n",
       "            var ratio = zoom_box.data(\"ratio\");\n",
       "            var width = Math.min(Math.abs(dx), ratio * Math.abs(dy));\n",
       "            var height = Math.min(Math.abs(dy), Math.abs(dx) / ratio);\n",
       "            dx = width * dx / Math.abs(dx);\n",
       "            dy = height * dy / Math.abs(dy);\n",
       "        }\n",
       "        var xoffset = 0,\n",
       "            yoffset = 0;\n",
       "        if (dx < 0) {\n",
       "            xoffset = dx;\n",
       "            dx = -1 * dx;\n",
       "        }\n",
       "        if (dy < 0) {\n",
       "            yoffset = dy;\n",
       "            dy = -1 * dy;\n",
       "        }\n",
       "        if (isNaN(dy)) {\n",
       "            dy = 0.0;\n",
       "        }\n",
       "        if (isNaN(dx)) {\n",
       "            dx = 0.0;\n",
       "        }\n",
       "        zoom_box.transform(\"T\" + xoffset + \",\" + yoffset);\n",
       "        zoom_box.attr(\"width\", dx);\n",
       "        zoom_box.attr(\"height\", dy);\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var zoom_bounds = zoom_box.getBBox();\n",
       "        if (zoom_bounds.width * zoom_bounds.height <= 0) {\n",
       "            return;\n",
       "        }\n",
       "        var plot_bounds = root.plotbounds();\n",
       "        var zoom_factor = 1.0;\n",
       "        if (yscalable) {\n",
       "            zoom_factor = (plot_bounds.y1 - plot_bounds.y0) / zoom_bounds.height;\n",
       "        } else {\n",
       "            zoom_factor = (plot_bounds.x1 - plot_bounds.x0) / zoom_bounds.width;\n",
       "        }\n",
       "        var tx = (root.data(\"tx\") - zoom_bounds.x) * zoom_factor + plot_bounds.x0,\n",
       "            ty = (root.data(\"ty\") - zoom_bounds.y) * zoom_factor + plot_bounds.y0;\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\") * zoom_factor);\n",
       "        zoom_box.remove();\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        zoom_box.remove();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onstart = function(x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var scalable = root.hasClass(\"xscalable\") || root.hasClass(\"yscalable\");\n",
       "    var zoomable = !event.altKey && !event.ctrlKey && event.shiftKey && scalable;\n",
       "    var panable = !event.altKey && !event.ctrlKey && !event.shiftKey && scalable;\n",
       "    var drag_action = zoomable ? zoom_action :\n",
       "                      panable  ? pan_action :\n",
       "                                 undefined;\n",
       "    root.data(\"drag_action\", drag_action);\n",
       "    if (drag_action) {\n",
       "        var cancel_drag_action = function(event) {\n",
       "            if (event.which == 27) { // esc key\n",
       "                drag_action.cancel(root);\n",
       "                root.data(\"drag_action\", undefined);\n",
       "            }\n",
       "        };\n",
       "        window.addEventListener(\"keyup\", cancel_drag_action);\n",
       "        root.data(\"cancel_drag_action\", cancel_drag_action);\n",
       "        drag_action.start(root, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.update(root, dx, dy, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onend = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    window.removeEventListener(\"keyup\", root.data(\"cancel_drag_action\"));\n",
       "    root.data(\"cancel_drag_action\", undefined);\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.end(root, event);\n",
       "    }\n",
       "    root.data(\"drag_action\", undefined);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_scroll = function(event) {\n",
       "    if (event.shiftKey) {\n",
       "        increase_zoom_by_position(this.plotroot(), 0.001 * event.wheelDelta);\n",
       "        event.preventDefault();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseover = function(event) {\n",
       "    this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseout = function(event) {\n",
       "     this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomout_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), -0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomin_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), 0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_track_click = function(event) {\n",
       "    // TODO\n",
       "};\n",
       "\n",
       "\n",
       "// Map slider position x to scale y using the function y = a*exp(b*x)+c.\n",
       "// The constants a, b, and c are solved using the constraint that the function\n",
       "// should go through the points (0; min_scale), (0.5; 1), and (1; max_scale).\n",
       "var scale_from_slider_position = function(position, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return a * Math.exp(b * position) + c;\n",
       "}\n",
       "\n",
       "// inverse of scale_from_slider_position\n",
       "var slider_position_from_scale = function(scale, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return 1 / b * Math.log((scale - c) / a);\n",
       "}\n",
       "\n",
       "var increase_zoom_by_position = function(root, delta_position, animate) {\n",
       "    var scale = root.data(\"scale\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\");\n",
       "    var position = slider_position_from_scale(scale, min_scale, max_scale);\n",
       "    position += delta_position;\n",
       "    scale = scale_from_slider_position(position, min_scale, max_scale);\n",
       "    set_zoom(root, scale, animate);\n",
       "}\n",
       "\n",
       "var set_zoom = function(root, scale, animate) {\n",
       "    var min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"scale\");\n",
       "    var new_scale = Math.max(min_scale, Math.min(scale, max_scale));\n",
       "    if (animate) {\n",
       "        Snap.animate(\n",
       "            old_scale,\n",
       "            new_scale,\n",
       "            function (new_scale) {\n",
       "                update_plot_scale(root, new_scale);\n",
       "            },\n",
       "            200);\n",
       "    } else {\n",
       "        update_plot_scale(root, new_scale);\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "var update_plot_scale = function(root, new_scale) {\n",
       "    var trans = scale_centered_translation(root, new_scale);\n",
       "    set_plot_pan_zoom(root, trans.x, trans.y, new_scale);\n",
       "\n",
       "    root.selectAll(\".zoomslider_thumb\")\n",
       "        .forEach(function (element, i) {\n",
       "            var min_pos = element.data(\"min_pos\"),\n",
       "                max_pos = element.data(\"max_pos\"),\n",
       "                min_scale = root.data(\"min_scale\"),\n",
       "                max_scale = root.data(\"max_scale\");\n",
       "            var xmid = (min_pos + max_pos) / 2;\n",
       "            var xpos = slider_position_from_scale(new_scale, min_scale, max_scale);\n",
       "            element.transform(new Snap.Matrix().translate(\n",
       "                Math.max(min_pos, Math.min(\n",
       "                         max_pos, min_pos + (max_pos - min_pos) * xpos)) - xmid, 0));\n",
       "    });\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var min_pos = this.data(\"min_pos\"),\n",
       "        max_pos = this.data(\"max_pos\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"old_scale\");\n",
       "\n",
       "    var px_per_mm = root.data(\"px_per_mm\");\n",
       "    dx /= px_per_mm;\n",
       "    dy /= px_per_mm;\n",
       "\n",
       "    var xmid = (min_pos + max_pos) / 2;\n",
       "    var xpos = slider_position_from_scale(old_scale, min_scale, max_scale) +\n",
       "                   dx / (max_pos - min_pos);\n",
       "\n",
       "    // compute the new scale\n",
       "    var new_scale = scale_from_slider_position(xpos, min_scale, max_scale);\n",
       "    new_scale = Math.min(max_scale, Math.max(min_scale, new_scale));\n",
       "\n",
       "    update_plot_scale(root, new_scale);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragstart = function(x, y, event) {\n",
       "    this.animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    // keep track of what the scale was when we started dragging\n",
       "    root.data(\"old_scale\", root.data(\"scale\"));\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragend = function(event) {\n",
       "    this.animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "var toggle_color_class = function(root, color_class, ison) {\n",
       "    var guides = root.selectAll(\".guide.\" + color_class + \",.guide .\" + color_class);\n",
       "    var geoms = root.selectAll(\".geometry.\" + color_class + \",.geometry .\" + color_class);\n",
       "    if (ison) {\n",
       "        guides.animate({opacity: 0.5}, 250);\n",
       "        geoms.animate({opacity: 0.0}, 250);\n",
       "    } else {\n",
       "        guides.animate({opacity: 1.0}, 250);\n",
       "        geoms.animate({opacity: 1.0}, 250);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.colorkey_swatch_click = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    var color_class = this.data(\"color_class\");\n",
       "\n",
       "    if (event.shiftKey) {\n",
       "        root.selectAll(\".colorkey text\")\n",
       "            .forEach(function (element) {\n",
       "                var other_color_class = element.data(\"color_class\");\n",
       "                if (other_color_class != color_class) {\n",
       "                    toggle_color_class(root, other_color_class,\n",
       "                                       element.attr(\"opacity\") == 1.0);\n",
       "                }\n",
       "            });\n",
       "    } else {\n",
       "        toggle_color_class(root, color_class, this.attr(\"opacity\") == 1.0);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "return Gadfly;\n",
       "\n",
       "}));\n",
       "\n",
       "\n",
       "//@ sourceURL=gadfly.js\n",
       "\n",
       "(function (glob, factory) {\n",
       "    // AMD support\n",
       "      if (typeof require === \"function\" && typeof define === \"function\" && define.amd) {\n",
       "        require([\"Snap.svg\", \"Gadfly\"], function (Snap, Gadfly) {\n",
       "            factory(Snap, Gadfly);\n",
       "        });\n",
       "      } else {\n",
       "          factory(glob.Snap, glob.Gadfly);\n",
       "      }\n",
       "})(window, function (Snap, Gadfly) {\n",
       "    var fig = Snap(\"#img-9f1a637e\");\n",
       "fig.select(\"#img-9f1a637e-4\")\n",
       "   .drag(function() {}, function() {}, function() {});\n",
       "fig.select(\"#img-9f1a637e-5\")\n",
       "   .data(\"color_class\", \"color_Wells\")\n",
       ".click(Gadfly.colorkey_swatch_click)\n",
       ";\n",
       "fig.select(\"#img-9f1a637e-10\")\n",
       "   .init_gadfly();\n",
       "fig.select(\"#img-9f1a637e-12\")\n",
       "   .plotroot().data(\"unfocused_xgrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-9f1a637e-12\")\n",
       "   .plotroot().data(\"focused_xgrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-9f1a637e-13\")\n",
       "   .plotroot().data(\"unfocused_ygrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-9f1a637e-13\")\n",
       "   .plotroot().data(\"focused_ygrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-9f1a637e-20\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-9f1a637e-20\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-9f1a637e-20\")\n",
       "   .click(Gadfly.zoomslider_zoomin_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "fig.select(\"#img-9f1a637e-22\")\n",
       "   .data(\"max_pos\", 106.39)\n",
       ";\n",
       "fig.select(\"#img-9f1a637e-22\")\n",
       "   .data(\"min_pos\", 89.39)\n",
       ";\n",
       "fig.select(\"#img-9f1a637e-22\")\n",
       "   .click(Gadfly.zoomslider_track_click);\n",
       "fig.select(\"#img-9f1a637e-23\")\n",
       "   .data(\"max_pos\", 106.39)\n",
       ";\n",
       "fig.select(\"#img-9f1a637e-23\")\n",
       "   .data(\"min_pos\", 89.39)\n",
       ";\n",
       "fig.select(\"#img-9f1a637e-23\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-9f1a637e-23\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-9f1a637e-23\")\n",
       "   .drag(Gadfly.zoomslider_thumb_dragmove,\n",
       "     Gadfly.zoomslider_thumb_dragstart,\n",
       "     Gadfly.zoomslider_thumb_dragend)\n",
       ";\n",
       "fig.select(\"#img-9f1a637e-24\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-9f1a637e-24\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-9f1a637e-24\")\n",
       "   .click(Gadfly.zoomslider_zoomout_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "    });\n",
       "]]> </script>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "Plot(...)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md = Mads.loadmadsfile(\"w01.mads\") # load Mads input file into Mads Dictionary\n",
    "Mads.plotmadsproblem(md, keyword=\"all_wells\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are 20 monitoring wells.\n",
    "Each well has 2 measurement ports: shallow (3 m below the water table labeled `a`) and deep (33 m below the water table labeled `b`).\n",
    "Contaminant concentrations are observed for 50 years at each well.\n",
    "The contaminant transport is solved using the `Anasol` package in Mads."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Unknown model parameters\n",
    "\n",
    "* Start time of contaminant release $t_0$\n",
    "* End time of contaminant release $t_1$\n",
    "* Advective pore velocity $v$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reduced model setup \n",
    "\n",
    "Analysis of the data from only 2 monitoring locations: `w13a` and `w20a`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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       "f:e,unbind:b(this.node||document,d,e,f||this)}));return this};a[\"un\"+d]=A[\"un\"+d]=function(a){for(var b=this.events||[],e=b.length;e--;)if(b[e].name==d&&(b[e].f==a||!a)){b[e].unbind();b.splice(e,1);!b.length&&delete this.events;break}return this}})(v[y]);A.hover=function(a,b,d,e){return this.mouseover(a,d).mouseout(b,e||d)};A.unhover=function(a,b){return this.unmouseover(a).unmouseout(b)};var r=[];A.drag=function(b,d,f,h,n,p){function u(r,v,w){(r.originalEvent||r).preventDefault();this._drag.x=v;\n",
       "this._drag.y=w;this._drag.id=r.identifier;!q.length&&a.mousemove(e).mouseup(l);q.push({el:this,move_scope:h,start_scope:n,end_scope:p});d&&k.on(\"snap.drag.start.\"+this.id,d);b&&k.on(\"snap.drag.move.\"+this.id,b);f&&k.on(\"snap.drag.end.\"+this.id,f);k(\"snap.drag.start.\"+this.id,n||h||this,v,w,r)}if(!arguments.length){var v;return this.drag(function(a,b){this.attr({transform:v+(v?\"T\":\"t\")+[a,b]})},function(){v=this.transform().local})}this._drag={};r.push({el:this,start:u});this.mousedown(u);return this};\n",
       "A.undrag=function(){for(var b=r.length;b--;)r[b].el==this&&(this.unmousedown(r[b].start),r.splice(b,1),k.unbind(\"snap.drag.*.\"+this.id));!r.length&&a.unmousemove(e).unmouseup(l);return this}});C.plugin(function(a,v,y,C){y=y.prototype;var A=/^\\s*url\\((.+)\\)/,w=String,z=a._.$;a.filter={};y.filter=function(d){var f=this;\"svg\"!=f.type&&(f=f.paper);d=a.parse(w(d));var k=a._.id(),u=z(\"filter\");z(u,{id:k,filterUnits:\"userSpaceOnUse\"});u.appendChild(d.node);f.defs.appendChild(u);return new v(u)};k.on(\"snap.util.getattr.filter\",\n",
       "function(){k.stop();var d=z(this.node,\"filter\");if(d)return(d=w(d).match(A))&&a.select(d[1])});k.on(\"snap.util.attr.filter\",function(d){if(d instanceof v&&\"filter\"==d.type){k.stop();var f=d.node.id;f||(z(d.node,{id:d.id}),f=d.id);z(this.node,{filter:a.url(f)})}d&&\"none\"!=d||(k.stop(),this.node.removeAttribute(\"filter\"))});a.filter.blur=function(d,f){null==d&&(d=2);return a.format('<feGaussianBlur stdDeviation=\"{def}\"/>',{def:null==f?d:[d,f]})};a.filter.blur.toString=function(){return this()};a.filter.shadow=\n",
       "function(d,f,k,u,p){\"string\"==typeof k&&(p=u=k,k=4);\"string\"!=typeof u&&(p=u,u=\"#000\");null==k&&(k=4);null==p&&(p=1);null==d&&(d=0,f=2);null==f&&(f=d);u=a.color(u||\"#000\");return a.format('<feGaussianBlur in=\"SourceAlpha\" stdDeviation=\"{blur}\"/><feOffset dx=\"{dx}\" dy=\"{dy}\" result=\"offsetblur\"/><feFlood flood-color=\"{color}\"/><feComposite in2=\"offsetblur\" operator=\"in\"/><feComponentTransfer><feFuncA type=\"linear\" slope=\"{opacity}\"/></feComponentTransfer><feMerge><feMergeNode/><feMergeNode in=\"SourceGraphic\"/></feMerge>',\n",
       "{color:u,dx:d,dy:f,blur:k,opacity:p})};a.filter.shadow.toString=function(){return this()};a.filter.grayscale=function(d){null==d&&(d=1);return a.format('<feColorMatrix type=\"matrix\" values=\"{a} {b} {c} 0 0 {d} {e} {f} 0 0 {g} {b} {h} 0 0 0 0 0 1 0\"/>',{a:0.2126+0.7874*(1-d),b:0.7152-0.7152*(1-d),c:0.0722-0.0722*(1-d),d:0.2126-0.2126*(1-d),e:0.7152+0.2848*(1-d),f:0.0722-0.0722*(1-d),g:0.2126-0.2126*(1-d),h:0.0722+0.9278*(1-d)})};a.filter.grayscale.toString=function(){return this()};a.filter.sepia=\n",
       "function(d){null==d&&(d=1);return a.format('<feColorMatrix type=\"matrix\" values=\"{a} {b} {c} 0 0 {d} {e} {f} 0 0 {g} {h} {i} 0 0 0 0 0 1 0\"/>',{a:0.393+0.607*(1-d),b:0.769-0.769*(1-d),c:0.189-0.189*(1-d),d:0.349-0.349*(1-d),e:0.686+0.314*(1-d),f:0.168-0.168*(1-d),g:0.272-0.272*(1-d),h:0.534-0.534*(1-d),i:0.131+0.869*(1-d)})};a.filter.sepia.toString=function(){return this()};a.filter.saturate=function(d){null==d&&(d=1);return a.format('<feColorMatrix type=\"saturate\" values=\"{amount}\"/>',{amount:1-\n",
       "d})};a.filter.saturate.toString=function(){return this()};a.filter.hueRotate=function(d){return a.format('<feColorMatrix type=\"hueRotate\" values=\"{angle}\"/>',{angle:d||0})};a.filter.hueRotate.toString=function(){return this()};a.filter.invert=function(d){null==d&&(d=1);return a.format('<feComponentTransfer><feFuncR type=\"table\" tableValues=\"{amount} {amount2}\"/><feFuncG type=\"table\" tableValues=\"{amount} {amount2}\"/><feFuncB type=\"table\" tableValues=\"{amount} {amount2}\"/></feComponentTransfer>',{amount:d,\n",
       "amount2:1-d})};a.filter.invert.toString=function(){return this()};a.filter.brightness=function(d){null==d&&(d=1);return a.format('<feComponentTransfer><feFuncR type=\"linear\" slope=\"{amount}\"/><feFuncG type=\"linear\" slope=\"{amount}\"/><feFuncB type=\"linear\" slope=\"{amount}\"/></feComponentTransfer>',{amount:d})};a.filter.brightness.toString=function(){return this()};a.filter.contrast=function(d){null==d&&(d=1);return a.format('<feComponentTransfer><feFuncR type=\"linear\" slope=\"{amount}\" intercept=\"{amount2}\"/><feFuncG type=\"linear\" slope=\"{amount}\" intercept=\"{amount2}\"/><feFuncB type=\"linear\" slope=\"{amount}\" intercept=\"{amount2}\"/></feComponentTransfer>',\n",
       "{amount:d,amount2:0.5-d/2})};a.filter.contrast.toString=function(){return this()}});return C});\n",
       "\n",
       "]]> </script>\n",
       "<script> <![CDATA[\n",
       "\n",
       "(function (glob, factory) {\n",
       "    // AMD support\n",
       "    if (typeof define === \"function\" && define.amd) {\n",
       "        // Define as an anonymous module\n",
       "        define(\"Gadfly\", [\"Snap.svg\"], function (Snap) {\n",
       "            return factory(Snap);\n",
       "        });\n",
       "    } else {\n",
       "        // Browser globals (glob is window)\n",
       "        // Snap adds itself to window\n",
       "        glob.Gadfly = factory(glob.Snap);\n",
       "    }\n",
       "}(this, function (Snap) {\n",
       "\n",
       "var Gadfly = {};\n",
       "\n",
       "// Get an x/y coordinate value in pixels\n",
       "var xPX = function(fig, x) {\n",
       "    var client_box = fig.node.getBoundingClientRect();\n",
       "    return x * fig.node.viewBox.baseVal.width / client_box.width;\n",
       "};\n",
       "\n",
       "var yPX = function(fig, y) {\n",
       "    var client_box = fig.node.getBoundingClientRect();\n",
       "    return y * fig.node.viewBox.baseVal.height / client_box.height;\n",
       "};\n",
       "\n",
       "\n",
       "Snap.plugin(function (Snap, Element, Paper, global) {\n",
       "    // Traverse upwards from a snap element to find and return the first\n",
       "    // note with the \"plotroot\" class.\n",
       "    Element.prototype.plotroot = function () {\n",
       "        var element = this;\n",
       "        while (!element.hasClass(\"plotroot\") && element.parent() != null) {\n",
       "            element = element.parent();\n",
       "        }\n",
       "        return element;\n",
       "    };\n",
       "\n",
       "    Element.prototype.svgroot = function () {\n",
       "        var element = this;\n",
       "        while (element.node.nodeName != \"svg\" && element.parent() != null) {\n",
       "            element = element.parent();\n",
       "        }\n",
       "        return element;\n",
       "    };\n",
       "\n",
       "    Element.prototype.plotbounds = function () {\n",
       "        var root = this.plotroot()\n",
       "        var bbox = root.select(\".guide.background\").node.getBBox();\n",
       "        return {\n",
       "            x0: bbox.x,\n",
       "            x1: bbox.x + bbox.width,\n",
       "            y0: bbox.y,\n",
       "            y1: bbox.y + bbox.height\n",
       "        };\n",
       "    };\n",
       "\n",
       "    Element.prototype.plotcenter = function () {\n",
       "        var root = this.plotroot()\n",
       "        var bbox = root.select(\".guide.background\").node.getBBox();\n",
       "        return {\n",
       "            x: bbox.x + bbox.width / 2,\n",
       "            y: bbox.y + bbox.height / 2\n",
       "        };\n",
       "    };\n",
       "\n",
       "    // Emulate IE style mouseenter/mouseleave events, since Microsoft always\n",
       "    // does everything right.\n",
       "    // See: http://www.dynamic-tools.net/toolbox/isMouseLeaveOrEnter/\n",
       "    var events = [\"mouseenter\", \"mouseleave\"];\n",
       "\n",
       "    for (i in events) {\n",
       "        (function (event_name) {\n",
       "            var event_name = events[i];\n",
       "            Element.prototype[event_name] = function (fn, scope) {\n",
       "                if (Snap.is(fn, \"function\")) {\n",
       "                    var fn2 = function (event) {\n",
       "                        if (event.type != \"mouseover\" && event.type != \"mouseout\") {\n",
       "                            return;\n",
       "                        }\n",
       "\n",
       "                        var reltg = event.relatedTarget ? event.relatedTarget :\n",
       "                            event.type == \"mouseout\" ? event.toElement : event.fromElement;\n",
       "                        while (reltg && reltg != this.node) reltg = reltg.parentNode;\n",
       "\n",
       "                        if (reltg != this.node) {\n",
       "                            return fn.apply(this, event);\n",
       "                        }\n",
       "                    };\n",
       "\n",
       "                    if (event_name == \"mouseenter\") {\n",
       "                        this.mouseover(fn2, scope);\n",
       "                    } else {\n",
       "                        this.mouseout(fn2, scope);\n",
       "                    }\n",
       "                }\n",
       "                return this;\n",
       "            };\n",
       "        })(events[i]);\n",
       "    }\n",
       "\n",
       "\n",
       "    Element.prototype.mousewheel = function (fn, scope) {\n",
       "        if (Snap.is(fn, \"function\")) {\n",
       "            var el = this;\n",
       "            var fn2 = function (event) {\n",
       "                fn.apply(el, [event]);\n",
       "            };\n",
       "        }\n",
       "\n",
       "        this.node.addEventListener(\n",
       "            /Firefox/i.test(navigator.userAgent) ? \"DOMMouseScroll\" : \"mousewheel\",\n",
       "            fn2);\n",
       "\n",
       "        return this;\n",
       "    };\n",
       "\n",
       "\n",
       "    // Snap's attr function can be too slow for things like panning/zooming.\n",
       "    // This is a function to directly update element attributes without going\n",
       "    // through eve.\n",
       "    Element.prototype.attribute = function(key, val) {\n",
       "        if (val === undefined) {\n",
       "            return this.node.getAttribute(key);\n",
       "        } else {\n",
       "            this.node.setAttribute(key, val);\n",
       "            return this;\n",
       "        }\n",
       "    };\n",
       "\n",
       "    Element.prototype.init_gadfly = function() {\n",
       "        this.mouseenter(Gadfly.plot_mouseover)\n",
       "            .mouseleave(Gadfly.plot_mouseout)\n",
       "            .dblclick(Gadfly.plot_dblclick)\n",
       "            .mousewheel(Gadfly.guide_background_scroll)\n",
       "            .drag(Gadfly.guide_background_drag_onmove,\n",
       "                  Gadfly.guide_background_drag_onstart,\n",
       "                  Gadfly.guide_background_drag_onend);\n",
       "        this.mouseenter(function (event) {\n",
       "            init_pan_zoom(this.plotroot());\n",
       "        });\n",
       "        return this;\n",
       "    };\n",
       "});\n",
       "\n",
       "\n",
       "// When the plot is moused over, emphasize the grid lines.\n",
       "Gadfly.plot_mouseover = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    var keyboard_zoom = function(event) {\n",
       "        if (event.which == 187) { // plus\n",
       "            increase_zoom_by_position(root, 0.1, true);\n",
       "        } else if (event.which == 189) { // minus\n",
       "            increase_zoom_by_position(root, -0.1, true);\n",
       "        }\n",
       "    };\n",
       "    root.data(\"keyboard_zoom\", keyboard_zoom);\n",
       "    window.addEventListener(\"keyup\", keyboard_zoom);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    xgridlines.data(\"unfocused_strokedash\",\n",
       "                    xgridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "    ygridlines.data(\"unfocused_strokedash\",\n",
       "                    ygridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "\n",
       "    // emphasize grid lines\n",
       "    var destcolor = root.data(\"focused_xgrid_color\");\n",
       "    xgridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"focused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // reveal zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 1.0}, 250);\n",
       "};\n",
       "\n",
       "// Reset pan and zoom on double click\n",
       "Gadfly.plot_dblclick = function(event) {\n",
       "  set_plot_pan_zoom(this.plotroot(), 0.0, 0.0, 1.0);\n",
       "};\n",
       "\n",
       "// Unemphasize grid lines on mouse out.\n",
       "Gadfly.plot_mouseout = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    window.removeEventListener(\"keyup\", root.data(\"keyboard_zoom\"));\n",
       "    root.data(\"keyboard_zoom\", undefined);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    var destcolor = root.data(\"unfocused_xgrid_color\");\n",
       "\n",
       "    xgridlines.attribute(\"stroke-dasharray\", xgridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"unfocused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", ygridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // hide zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 0.0}, 250);\n",
       "};\n",
       "\n",
       "\n",
       "var set_geometry_transform = function(root, tx, ty, scale) {\n",
       "    var xscalable = root.hasClass(\"xscalable\"),\n",
       "        yscalable = root.hasClass(\"yscalable\");\n",
       "\n",
       "    var old_scale = root.data(\"scale\");\n",
       "\n",
       "    var xscale = xscalable ? scale : 1.0,\n",
       "        yscale = yscalable ? scale : 1.0;\n",
       "\n",
       "    tx = xscalable ? tx : 0.0;\n",
       "    ty = yscalable ? ty : 0.0;\n",
       "\n",
       "    var t = new Snap.Matrix().translate(tx, ty).scale(xscale, yscale);\n",
       "\n",
       "    root.selectAll(\".geometry, image\")\n",
       "        .forEach(function (element, i) {\n",
       "            element.transform(t);\n",
       "        });\n",
       "\n",
       "    bounds = root.plotbounds();\n",
       "\n",
       "    if (yscalable) {\n",
       "        var xfixed_t = new Snap.Matrix().translate(0, ty).scale(1.0, yscale);\n",
       "        root.selectAll(\".xfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(xfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".ylabels\")\n",
       "            .transform(xfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1, 1/scale, cx, cy).add(st);\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var y = cy * scale + ty;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.y0 <= y && y <= bounds.y1 ? \"visible\" : \"hidden\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (xscalable) {\n",
       "        var yfixed_t = new Snap.Matrix().translate(tx, 0).scale(xscale, 1.0);\n",
       "        var xtrans = new Snap.Matrix().translate(tx, 0);\n",
       "        root.selectAll(\".yfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(yfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".xlabels\")\n",
       "            .transform(yfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1/scale, 1, cx, cy).add(st);\n",
       "\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var x = cx * scale + tx;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.x0 <= x && x <= bounds.x1 ? \"visible\" : \"hidden\");\n",
       "                    }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // we must unscale anything that is scale invariance: widths, raiduses, etc.\n",
       "    var size_attribs = [\"font-size\"];\n",
       "    var unscaled_selection = \".geometry, .geometry *\";\n",
       "    if (xscalable) {\n",
       "        size_attribs.push(\"rx\");\n",
       "        unscaled_selection += \", .xgridlines\";\n",
       "    }\n",
       "    if (yscalable) {\n",
       "        size_attribs.push(\"ry\");\n",
       "        unscaled_selection += \", .ygridlines\";\n",
       "    }\n",
       "\n",
       "    root.selectAll(unscaled_selection)\n",
       "        .forEach(function (element, i) {\n",
       "            // circle need special help\n",
       "            if (element.node.nodeName == \"circle\") {\n",
       "                var cx = element.attribute(\"cx\"),\n",
       "                    cy = element.attribute(\"cy\");\n",
       "                unscale_t = new Snap.Matrix().scale(1/xscale, 1/yscale,\n",
       "                                                        cx, cy);\n",
       "                element.transform(unscale_t);\n",
       "                return;\n",
       "            }\n",
       "\n",
       "            for (i in size_attribs) {\n",
       "                var key = size_attribs[i];\n",
       "                var val = parseFloat(element.attribute(key));\n",
       "                if (val !== undefined && val != 0 && !isNaN(val)) {\n",
       "                    element.attribute(key, val * old_scale / scale);\n",
       "                }\n",
       "            }\n",
       "        });\n",
       "};\n",
       "\n",
       "\n",
       "// Find the most appropriate tick scale and update label visibility.\n",
       "var update_tickscale = function(root, scale, axis) {\n",
       "    if (!root.hasClass(axis + \"scalable\")) return;\n",
       "\n",
       "    var tickscales = root.data(axis + \"tickscales\");\n",
       "    var best_tickscale = 1.0;\n",
       "    var best_tickscale_dist = Infinity;\n",
       "    for (tickscale in tickscales) {\n",
       "        var dist = Math.abs(Math.log(tickscale) - Math.log(scale));\n",
       "        if (dist < best_tickscale_dist) {\n",
       "            best_tickscale_dist = dist;\n",
       "            best_tickscale = tickscale;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    if (best_tickscale != root.data(axis + \"tickscale\")) {\n",
       "        root.data(axis + \"tickscale\", best_tickscale);\n",
       "        var mark_inscale_gridlines = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        var mark_inscale_labels = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        root.select(\".\" + axis + \"gridlines\").selectAll(\"path\").forEach(mark_inscale_gridlines);\n",
       "        root.select(\".\" + axis + \"labels\").selectAll(\"text\").forEach(mark_inscale_labels);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "var set_plot_pan_zoom = function(root, tx, ty, scale) {\n",
       "    var old_scale = root.data(\"scale\");\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    // compute the viewport derived from tx, ty, and scale\n",
       "    var x_min = -width * scale - (scale * width - width),\n",
       "        x_max = width * scale,\n",
       "        y_min = -height * scale - (scale * height - height),\n",
       "        y_max = height * scale;\n",
       "\n",
       "    var x0 = bounds.x0 - scale * bounds.x0,\n",
       "        y0 = bounds.y0 - scale * bounds.y0;\n",
       "\n",
       "    var tx = Math.max(Math.min(tx - x0, x_max), x_min),\n",
       "        ty = Math.max(Math.min(ty - y0, y_max), y_min);\n",
       "\n",
       "    tx += x0;\n",
       "    ty += y0;\n",
       "\n",
       "    // when the scale change, we may need to alter which set of\n",
       "    // ticks is being displayed\n",
       "    if (scale != old_scale) {\n",
       "        update_tickscale(root, scale, \"x\");\n",
       "        update_tickscale(root, scale, \"y\");\n",
       "    }\n",
       "\n",
       "    set_geometry_transform(root, tx, ty, scale);\n",
       "\n",
       "    root.data(\"scale\", scale);\n",
       "    root.data(\"tx\", tx);\n",
       "    root.data(\"ty\", ty);\n",
       "};\n",
       "\n",
       "\n",
       "var scale_centered_translation = function(root, scale) {\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    var tx0 = root.data(\"tx\"),\n",
       "        ty0 = root.data(\"ty\");\n",
       "\n",
       "    var scale0 = root.data(\"scale\");\n",
       "\n",
       "    // how off from center the current view is\n",
       "    var xoff = tx0 - (bounds.x0 * (1 - scale0) + (width * (1 - scale0)) / 2),\n",
       "        yoff = ty0 - (bounds.y0 * (1 - scale0) + (height * (1 - scale0)) / 2);\n",
       "\n",
       "    // rescale offsets\n",
       "    xoff = xoff * scale / scale0;\n",
       "    yoff = yoff * scale / scale0;\n",
       "\n",
       "    // adjust for the panel position being scaled\n",
       "    var x_edge_adjust = bounds.x0 * (1 - scale),\n",
       "        y_edge_adjust = bounds.y0 * (1 - scale);\n",
       "\n",
       "    return {\n",
       "        x: xoff + x_edge_adjust + (width - width * scale) / 2,\n",
       "        y: yoff + y_edge_adjust + (height - height * scale) / 2\n",
       "    };\n",
       "};\n",
       "\n",
       "\n",
       "// Initialize data for panning zooming if it isn't already.\n",
       "var init_pan_zoom = function(root) {\n",
       "    if (root.data(\"zoompan-ready\")) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    // The non-scaling-stroke trick. Rather than try to correct for the\n",
       "    // stroke-width when zooming, we force it to a fixed value.\n",
       "    var px_per_mm = root.node.getCTM().a;\n",
       "\n",
       "    // Drag events report deltas in pixels, which we'd like to convert to\n",
       "    // millimeters.\n",
       "    root.data(\"px_per_mm\", px_per_mm);\n",
       "\n",
       "    root.selectAll(\"path\")\n",
       "        .forEach(function (element, i) {\n",
       "        sw = element.asPX(\"stroke-width\") * px_per_mm;\n",
       "        if (sw > 0) {\n",
       "            element.attribute(\"stroke-width\", sw);\n",
       "            element.attribute(\"vector-effect\", \"non-scaling-stroke\");\n",
       "        }\n",
       "    });\n",
       "\n",
       "    // Store ticks labels original tranformation\n",
       "    root.selectAll(\".xlabels > text, .ylabels > text\")\n",
       "        .forEach(function (element, i) {\n",
       "            var lm = element.transform().localMatrix;\n",
       "            element.data(\"static_transform\",\n",
       "                new Snap.Matrix(lm.a, lm.b, lm.c, lm.d, lm.e, lm.f));\n",
       "        });\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\");\n",
       "    var ygridlines = root.select(\".ygridlines\");\n",
       "    var xlabels = root.select(\".xlabels\");\n",
       "    var ylabels = root.select(\".ylabels\");\n",
       "\n",
       "    if (root.data(\"tx\") === undefined) root.data(\"tx\", 0);\n",
       "    if (root.data(\"ty\") === undefined) root.data(\"ty\", 0);\n",
       "    if (root.data(\"scale\") === undefined) root.data(\"scale\", 1.0);\n",
       "    if (root.data(\"xtickscales\") === undefined) {\n",
       "\n",
       "        // index all the tick scales that are listed\n",
       "        var xtickscales = {};\n",
       "        var ytickscales = {};\n",
       "        var add_x_tick_scales = function (element, i) {\n",
       "            xtickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "        var add_y_tick_scales = function (element, i) {\n",
       "            ytickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "\n",
       "        if (xgridlines) xgridlines.selectAll(\"path\").forEach(add_x_tick_scales);\n",
       "        if (ygridlines) ygridlines.selectAll(\"path\").forEach(add_y_tick_scales);\n",
       "        if (xlabels) xlabels.selectAll(\"text\").forEach(add_x_tick_scales);\n",
       "        if (ylabels) ylabels.selectAll(\"text\").forEach(add_y_tick_scales);\n",
       "\n",
       "        root.data(\"xtickscales\", xtickscales);\n",
       "        root.data(\"ytickscales\", ytickscales);\n",
       "        root.data(\"xtickscale\", 1.0);\n",
       "    }\n",
       "\n",
       "    var min_scale = 1.0, max_scale = 1.0;\n",
       "    for (scale in xtickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    for (scale in ytickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    root.data(\"min_scale\", min_scale);\n",
       "    root.data(\"max_scale\", max_scale);\n",
       "\n",
       "    // store the original positions of labels\n",
       "    if (xlabels) {\n",
       "        xlabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"x\", element.asPX(\"x\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    if (ylabels) {\n",
       "        ylabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"y\", element.asPX(\"y\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    // mark grid lines and ticks as in or out of scale.\n",
       "    var mark_inscale = function (element, i) {\n",
       "        element.attribute(\"gadfly:inscale\", element.attribute(\"gadfly:scale\") == 1.0);\n",
       "    };\n",
       "\n",
       "    if (xgridlines) xgridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (ygridlines) ygridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (xlabels) xlabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "    if (ylabels) ylabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "\n",
       "    // figure out the upper ond lower bounds on panning using the maximum\n",
       "    // and minum grid lines\n",
       "    var bounds = root.plotbounds();\n",
       "    var pan_bounds = {\n",
       "        x0: 0.0,\n",
       "        y0: 0.0,\n",
       "        x1: 0.0,\n",
       "        y1: 0.0\n",
       "    };\n",
       "\n",
       "    if (xgridlines) {\n",
       "        xgridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.x1 - bbox.x < pan_bounds.x0) {\n",
       "                        pan_bounds.x0 = bounds.x1 - bbox.x;\n",
       "                    }\n",
       "                    if (bounds.x0 - bbox.x > pan_bounds.x1) {\n",
       "                        pan_bounds.x1 = bounds.x0 - bbox.x;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (ygridlines) {\n",
       "        ygridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.y1 - bbox.y < pan_bounds.y0) {\n",
       "                        pan_bounds.y0 = bounds.y1 - bbox.y;\n",
       "                    }\n",
       "                    if (bounds.y0 - bbox.y > pan_bounds.y1) {\n",
       "                        pan_bounds.y1 = bounds.y0 - bbox.y;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // nudge these values a little\n",
       "    pan_bounds.x0 -= 5;\n",
       "    pan_bounds.x1 += 5;\n",
       "    pan_bounds.y0 -= 5;\n",
       "    pan_bounds.y1 += 5;\n",
       "    root.data(\"pan_bounds\", pan_bounds);\n",
       "\n",
       "    root.data(\"zoompan-ready\", true)\n",
       "};\n",
       "\n",
       "\n",
       "// drag actions, i.e. zooming and panning\n",
       "var pan_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        root.data(\"dx\", 0);\n",
       "        root.data(\"dy\", 0);\n",
       "        root.data(\"tx0\", root.data(\"tx\"));\n",
       "        root.data(\"ty0\", root.data(\"ty\"));\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        dx /= px_per_mm;\n",
       "        dy /= px_per_mm;\n",
       "\n",
       "        var tx0 = root.data(\"tx\"),\n",
       "            ty0 = root.data(\"ty\");\n",
       "\n",
       "        var dx0 = root.data(\"dx\"),\n",
       "            dy0 = root.data(\"dy\");\n",
       "\n",
       "        root.data(\"dx\", dx);\n",
       "        root.data(\"dy\", dy);\n",
       "\n",
       "        dx = dx - dx0;\n",
       "        dy = dy - dy0;\n",
       "\n",
       "        var tx = tx0 + dx,\n",
       "            ty = ty0 + dy;\n",
       "\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\"));\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        set_plot_pan_zoom(root, root.data(\"tx0\"), root.data(\"ty0\"), root.data(\"scale\"));\n",
       "    }\n",
       "};\n",
       "\n",
       "var zoom_box;\n",
       "var zoom_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        var bounds = root.plotbounds();\n",
       "        var width = bounds.x1 - bounds.x0,\n",
       "            height = bounds.y1 - bounds.y0;\n",
       "        var ratio = width / height;\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        x = xscalable ? x / px_per_mm : bounds.x0;\n",
       "        y = yscalable ? y / px_per_mm : bounds.y0;\n",
       "        var w = xscalable ? 0 : width;\n",
       "        var h = yscalable ? 0 : height;\n",
       "        zoom_box = root.rect(x, y, w, h).attr({\n",
       "            \"fill\": \"#000\",\n",
       "            \"opacity\": 0.25\n",
       "        });\n",
       "        zoom_box.data(\"ratio\", ratio);\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        var bounds = root.plotbounds();\n",
       "        if (yscalable) {\n",
       "            y /= px_per_mm;\n",
       "            y = Math.max(bounds.y0, y);\n",
       "            y = Math.min(bounds.y1, y);\n",
       "        } else {\n",
       "            y = bounds.y1;\n",
       "        }\n",
       "        if (xscalable) {\n",
       "            x /= px_per_mm;\n",
       "            x = Math.max(bounds.x0, x);\n",
       "            x = Math.min(bounds.x1, x);\n",
       "        } else {\n",
       "            x = bounds.x1;\n",
       "        }\n",
       "\n",
       "        dx = x - zoom_box.attr(\"x\");\n",
       "        dy = y - zoom_box.attr(\"y\");\n",
       "        if (xscalable && yscalable) {\n",
       "            var ratio = zoom_box.data(\"ratio\");\n",
       "            var width = Math.min(Math.abs(dx), ratio * Math.abs(dy));\n",
       "            var height = Math.min(Math.abs(dy), Math.abs(dx) / ratio);\n",
       "            dx = width * dx / Math.abs(dx);\n",
       "            dy = height * dy / Math.abs(dy);\n",
       "        }\n",
       "        var xoffset = 0,\n",
       "            yoffset = 0;\n",
       "        if (dx < 0) {\n",
       "            xoffset = dx;\n",
       "            dx = -1 * dx;\n",
       "        }\n",
       "        if (dy < 0) {\n",
       "            yoffset = dy;\n",
       "            dy = -1 * dy;\n",
       "        }\n",
       "        if (isNaN(dy)) {\n",
       "            dy = 0.0;\n",
       "        }\n",
       "        if (isNaN(dx)) {\n",
       "            dx = 0.0;\n",
       "        }\n",
       "        zoom_box.transform(\"T\" + xoffset + \",\" + yoffset);\n",
       "        zoom_box.attr(\"width\", dx);\n",
       "        zoom_box.attr(\"height\", dy);\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var zoom_bounds = zoom_box.getBBox();\n",
       "        if (zoom_bounds.width * zoom_bounds.height <= 0) {\n",
       "            return;\n",
       "        }\n",
       "        var plot_bounds = root.plotbounds();\n",
       "        var zoom_factor = 1.0;\n",
       "        if (yscalable) {\n",
       "            zoom_factor = (plot_bounds.y1 - plot_bounds.y0) / zoom_bounds.height;\n",
       "        } else {\n",
       "            zoom_factor = (plot_bounds.x1 - plot_bounds.x0) / zoom_bounds.width;\n",
       "        }\n",
       "        var tx = (root.data(\"tx\") - zoom_bounds.x) * zoom_factor + plot_bounds.x0,\n",
       "            ty = (root.data(\"ty\") - zoom_bounds.y) * zoom_factor + plot_bounds.y0;\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\") * zoom_factor);\n",
       "        zoom_box.remove();\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        zoom_box.remove();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onstart = function(x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var scalable = root.hasClass(\"xscalable\") || root.hasClass(\"yscalable\");\n",
       "    var zoomable = !event.altKey && !event.ctrlKey && event.shiftKey && scalable;\n",
       "    var panable = !event.altKey && !event.ctrlKey && !event.shiftKey && scalable;\n",
       "    var drag_action = zoomable ? zoom_action :\n",
       "                      panable  ? pan_action :\n",
       "                                 undefined;\n",
       "    root.data(\"drag_action\", drag_action);\n",
       "    if (drag_action) {\n",
       "        var cancel_drag_action = function(event) {\n",
       "            if (event.which == 27) { // esc key\n",
       "                drag_action.cancel(root);\n",
       "                root.data(\"drag_action\", undefined);\n",
       "            }\n",
       "        };\n",
       "        window.addEventListener(\"keyup\", cancel_drag_action);\n",
       "        root.data(\"cancel_drag_action\", cancel_drag_action);\n",
       "        drag_action.start(root, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.update(root, dx, dy, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onend = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    window.removeEventListener(\"keyup\", root.data(\"cancel_drag_action\"));\n",
       "    root.data(\"cancel_drag_action\", undefined);\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.end(root, event);\n",
       "    }\n",
       "    root.data(\"drag_action\", undefined);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_scroll = function(event) {\n",
       "    if (event.shiftKey) {\n",
       "        increase_zoom_by_position(this.plotroot(), 0.001 * event.wheelDelta);\n",
       "        event.preventDefault();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseover = function(event) {\n",
       "    this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseout = function(event) {\n",
       "     this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomout_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), -0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomin_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), 0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_track_click = function(event) {\n",
       "    // TODO\n",
       "};\n",
       "\n",
       "\n",
       "// Map slider position x to scale y using the function y = a*exp(b*x)+c.\n",
       "// The constants a, b, and c are solved using the constraint that the function\n",
       "// should go through the points (0; min_scale), (0.5; 1), and (1; max_scale).\n",
       "var scale_from_slider_position = function(position, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return a * Math.exp(b * position) + c;\n",
       "}\n",
       "\n",
       "// inverse of scale_from_slider_position\n",
       "var slider_position_from_scale = function(scale, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return 1 / b * Math.log((scale - c) / a);\n",
       "}\n",
       "\n",
       "var increase_zoom_by_position = function(root, delta_position, animate) {\n",
       "    var scale = root.data(\"scale\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\");\n",
       "    var position = slider_position_from_scale(scale, min_scale, max_scale);\n",
       "    position += delta_position;\n",
       "    scale = scale_from_slider_position(position, min_scale, max_scale);\n",
       "    set_zoom(root, scale, animate);\n",
       "}\n",
       "\n",
       "var set_zoom = function(root, scale, animate) {\n",
       "    var min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"scale\");\n",
       "    var new_scale = Math.max(min_scale, Math.min(scale, max_scale));\n",
       "    if (animate) {\n",
       "        Snap.animate(\n",
       "            old_scale,\n",
       "            new_scale,\n",
       "            function (new_scale) {\n",
       "                update_plot_scale(root, new_scale);\n",
       "            },\n",
       "            200);\n",
       "    } else {\n",
       "        update_plot_scale(root, new_scale);\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "var update_plot_scale = function(root, new_scale) {\n",
       "    var trans = scale_centered_translation(root, new_scale);\n",
       "    set_plot_pan_zoom(root, trans.x, trans.y, new_scale);\n",
       "\n",
       "    root.selectAll(\".zoomslider_thumb\")\n",
       "        .forEach(function (element, i) {\n",
       "            var min_pos = element.data(\"min_pos\"),\n",
       "                max_pos = element.data(\"max_pos\"),\n",
       "                min_scale = root.data(\"min_scale\"),\n",
       "                max_scale = root.data(\"max_scale\");\n",
       "            var xmid = (min_pos + max_pos) / 2;\n",
       "            var xpos = slider_position_from_scale(new_scale, min_scale, max_scale);\n",
       "            element.transform(new Snap.Matrix().translate(\n",
       "                Math.max(min_pos, Math.min(\n",
       "                         max_pos, min_pos + (max_pos - min_pos) * xpos)) - xmid, 0));\n",
       "    });\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var min_pos = this.data(\"min_pos\"),\n",
       "        max_pos = this.data(\"max_pos\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"old_scale\");\n",
       "\n",
       "    var px_per_mm = root.data(\"px_per_mm\");\n",
       "    dx /= px_per_mm;\n",
       "    dy /= px_per_mm;\n",
       "\n",
       "    var xmid = (min_pos + max_pos) / 2;\n",
       "    var xpos = slider_position_from_scale(old_scale, min_scale, max_scale) +\n",
       "                   dx / (max_pos - min_pos);\n",
       "\n",
       "    // compute the new scale\n",
       "    var new_scale = scale_from_slider_position(xpos, min_scale, max_scale);\n",
       "    new_scale = Math.min(max_scale, Math.max(min_scale, new_scale));\n",
       "\n",
       "    update_plot_scale(root, new_scale);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragstart = function(x, y, event) {\n",
       "    this.animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    // keep track of what the scale was when we started dragging\n",
       "    root.data(\"old_scale\", root.data(\"scale\"));\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragend = function(event) {\n",
       "    this.animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "var toggle_color_class = function(root, color_class, ison) {\n",
       "    var guides = root.selectAll(\".guide.\" + color_class + \",.guide .\" + color_class);\n",
       "    var geoms = root.selectAll(\".geometry.\" + color_class + \",.geometry .\" + color_class);\n",
       "    if (ison) {\n",
       "        guides.animate({opacity: 0.5}, 250);\n",
       "        geoms.animate({opacity: 0.0}, 250);\n",
       "    } else {\n",
       "        guides.animate({opacity: 1.0}, 250);\n",
       "        geoms.animate({opacity: 1.0}, 250);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.colorkey_swatch_click = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    var color_class = this.data(\"color_class\");\n",
       "\n",
       "    if (event.shiftKey) {\n",
       "        root.selectAll(\".colorkey text\")\n",
       "            .forEach(function (element) {\n",
       "                var other_color_class = element.data(\"color_class\");\n",
       "                if (other_color_class != color_class) {\n",
       "                    toggle_color_class(root, other_color_class,\n",
       "                                       element.attr(\"opacity\") == 1.0);\n",
       "                }\n",
       "            });\n",
       "    } else {\n",
       "        toggle_color_class(root, color_class, this.attr(\"opacity\") == 1.0);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "return Gadfly;\n",
       "\n",
       "}));\n",
       "\n",
       "\n",
       "//@ sourceURL=gadfly.js\n",
       "\n",
       "(function (glob, factory) {\n",
       "    // AMD support\n",
       "      if (typeof require === \"function\" && typeof define === \"function\" && define.amd) {\n",
       "        require([\"Snap.svg\", \"Gadfly\"], function (Snap, Gadfly) {\n",
       "            factory(Snap, Gadfly);\n",
       "        });\n",
       "      } else {\n",
       "          factory(glob.Snap, glob.Gadfly);\n",
       "      }\n",
       "})(window, function (Snap, Gadfly) {\n",
       "    var fig = Snap(\"#img-76e0c4bd\");\n",
       "fig.select(\"#img-76e0c4bd-4\")\n",
       "   .drag(function() {}, function() {}, function() {});\n",
       "fig.select(\"#img-76e0c4bd-5\")\n",
       "   .data(\"color_class\", \"color_Wells\")\n",
       ".click(Gadfly.colorkey_swatch_click)\n",
       ";\n",
       "fig.select(\"#img-76e0c4bd-10\")\n",
       "   .init_gadfly();\n",
       "fig.select(\"#img-76e0c4bd-12\")\n",
       "   .plotroot().data(\"unfocused_xgrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-76e0c4bd-12\")\n",
       "   .plotroot().data(\"focused_xgrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-76e0c4bd-13\")\n",
       "   .plotroot().data(\"unfocused_ygrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-76e0c4bd-13\")\n",
       "   .plotroot().data(\"focused_ygrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-76e0c4bd-20\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-76e0c4bd-20\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-76e0c4bd-20\")\n",
       "   .click(Gadfly.zoomslider_zoomin_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "fig.select(\"#img-76e0c4bd-22\")\n",
       "   .data(\"max_pos\", 106.39)\n",
       ";\n",
       "fig.select(\"#img-76e0c4bd-22\")\n",
       "   .data(\"min_pos\", 89.39)\n",
       ";\n",
       "fig.select(\"#img-76e0c4bd-22\")\n",
       "   .click(Gadfly.zoomslider_track_click);\n",
       "fig.select(\"#img-76e0c4bd-23\")\n",
       "   .data(\"max_pos\", 106.39)\n",
       ";\n",
       "fig.select(\"#img-76e0c4bd-23\")\n",
       "   .data(\"min_pos\", 89.39)\n",
       ";\n",
       "fig.select(\"#img-76e0c4bd-23\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-76e0c4bd-23\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-76e0c4bd-23\")\n",
       "   .drag(Gadfly.zoomslider_thumb_dragmove,\n",
       "     Gadfly.zoomslider_thumb_dragstart,\n",
       "     Gadfly.zoomslider_thumb_dragend)\n",
       ";\n",
       "fig.select(\"#img-76e0c4bd-24\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-76e0c4bd-24\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-76e0c4bd-24\")\n",
       "   .click(Gadfly.zoomslider_zoomout_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "    });\n",
       "]]> </script>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "Plot(...)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Mads.allwellsoff!(md) # turn off all wells\n",
    "Mads.wellon!(md, \"w13a\") # use well w13a\n",
    "Mads.wellon!(md, \"w20a\") # use well w20a\n",
    "Mads.plotmadsproblem(md, keyword=\"w13a_w20a\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Initial estimates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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       "function(d){null==d&&(d=1);return a.format('<feColorMatrix type=\"matrix\" values=\"{a} {b} {c} 0 0 {d} {e} {f} 0 0 {g} {h} {i} 0 0 0 0 0 1 0\"/>',{a:0.393+0.607*(1-d),b:0.769-0.769*(1-d),c:0.189-0.189*(1-d),d:0.349-0.349*(1-d),e:0.686+0.314*(1-d),f:0.168-0.168*(1-d),g:0.272-0.272*(1-d),h:0.534-0.534*(1-d),i:0.131+0.869*(1-d)})};a.filter.sepia.toString=function(){return this()};a.filter.saturate=function(d){null==d&&(d=1);return a.format('<feColorMatrix type=\"saturate\" values=\"{amount}\"/>',{amount:1-\n",
       "d})};a.filter.saturate.toString=function(){return this()};a.filter.hueRotate=function(d){return a.format('<feColorMatrix type=\"hueRotate\" values=\"{angle}\"/>',{angle:d||0})};a.filter.hueRotate.toString=function(){return this()};a.filter.invert=function(d){null==d&&(d=1);return a.format('<feComponentTransfer><feFuncR type=\"table\" tableValues=\"{amount} {amount2}\"/><feFuncG type=\"table\" tableValues=\"{amount} {amount2}\"/><feFuncB type=\"table\" tableValues=\"{amount} {amount2}\"/></feComponentTransfer>',{amount:d,\n",
       "amount2:1-d})};a.filter.invert.toString=function(){return this()};a.filter.brightness=function(d){null==d&&(d=1);return a.format('<feComponentTransfer><feFuncR type=\"linear\" slope=\"{amount}\"/><feFuncG type=\"linear\" slope=\"{amount}\"/><feFuncB type=\"linear\" slope=\"{amount}\"/></feComponentTransfer>',{amount:d})};a.filter.brightness.toString=function(){return this()};a.filter.contrast=function(d){null==d&&(d=1);return a.format('<feComponentTransfer><feFuncR type=\"linear\" slope=\"{amount}\" intercept=\"{amount2}\"/><feFuncG type=\"linear\" slope=\"{amount}\" intercept=\"{amount2}\"/><feFuncB type=\"linear\" slope=\"{amount}\" intercept=\"{amount2}\"/></feComponentTransfer>',\n",
       "{amount:d,amount2:0.5-d/2})};a.filter.contrast.toString=function(){return this()}});return C});\n",
       "\n",
       "]]> </script>\n",
       "<script> <![CDATA[\n",
       "\n",
       "(function (glob, factory) {\n",
       "    // AMD support\n",
       "    if (typeof define === \"function\" && define.amd) {\n",
       "        // Define as an anonymous module\n",
       "        define(\"Gadfly\", [\"Snap.svg\"], function (Snap) {\n",
       "            return factory(Snap);\n",
       "        });\n",
       "    } else {\n",
       "        // Browser globals (glob is window)\n",
       "        // Snap adds itself to window\n",
       "        glob.Gadfly = factory(glob.Snap);\n",
       "    }\n",
       "}(this, function (Snap) {\n",
       "\n",
       "var Gadfly = {};\n",
       "\n",
       "// Get an x/y coordinate value in pixels\n",
       "var xPX = function(fig, x) {\n",
       "    var client_box = fig.node.getBoundingClientRect();\n",
       "    return x * fig.node.viewBox.baseVal.width / client_box.width;\n",
       "};\n",
       "\n",
       "var yPX = function(fig, y) {\n",
       "    var client_box = fig.node.getBoundingClientRect();\n",
       "    return y * fig.node.viewBox.baseVal.height / client_box.height;\n",
       "};\n",
       "\n",
       "\n",
       "Snap.plugin(function (Snap, Element, Paper, global) {\n",
       "    // Traverse upwards from a snap element to find and return the first\n",
       "    // note with the \"plotroot\" class.\n",
       "    Element.prototype.plotroot = function () {\n",
       "        var element = this;\n",
       "        while (!element.hasClass(\"plotroot\") && element.parent() != null) {\n",
       "            element = element.parent();\n",
       "        }\n",
       "        return element;\n",
       "    };\n",
       "\n",
       "    Element.prototype.svgroot = function () {\n",
       "        var element = this;\n",
       "        while (element.node.nodeName != \"svg\" && element.parent() != null) {\n",
       "            element = element.parent();\n",
       "        }\n",
       "        return element;\n",
       "    };\n",
       "\n",
       "    Element.prototype.plotbounds = function () {\n",
       "        var root = this.plotroot()\n",
       "        var bbox = root.select(\".guide.background\").node.getBBox();\n",
       "        return {\n",
       "            x0: bbox.x,\n",
       "            x1: bbox.x + bbox.width,\n",
       "            y0: bbox.y,\n",
       "            y1: bbox.y + bbox.height\n",
       "        };\n",
       "    };\n",
       "\n",
       "    Element.prototype.plotcenter = function () {\n",
       "        var root = this.plotroot()\n",
       "        var bbox = root.select(\".guide.background\").node.getBBox();\n",
       "        return {\n",
       "            x: bbox.x + bbox.width / 2,\n",
       "            y: bbox.y + bbox.height / 2\n",
       "        };\n",
       "    };\n",
       "\n",
       "    // Emulate IE style mouseenter/mouseleave events, since Microsoft always\n",
       "    // does everything right.\n",
       "    // See: http://www.dynamic-tools.net/toolbox/isMouseLeaveOrEnter/\n",
       "    var events = [\"mouseenter\", \"mouseleave\"];\n",
       "\n",
       "    for (i in events) {\n",
       "        (function (event_name) {\n",
       "            var event_name = events[i];\n",
       "            Element.prototype[event_name] = function (fn, scope) {\n",
       "                if (Snap.is(fn, \"function\")) {\n",
       "                    var fn2 = function (event) {\n",
       "                        if (event.type != \"mouseover\" && event.type != \"mouseout\") {\n",
       "                            return;\n",
       "                        }\n",
       "\n",
       "                        var reltg = event.relatedTarget ? event.relatedTarget :\n",
       "                            event.type == \"mouseout\" ? event.toElement : event.fromElement;\n",
       "                        while (reltg && reltg != this.node) reltg = reltg.parentNode;\n",
       "\n",
       "                        if (reltg != this.node) {\n",
       "                            return fn.apply(this, event);\n",
       "                        }\n",
       "                    };\n",
       "\n",
       "                    if (event_name == \"mouseenter\") {\n",
       "                        this.mouseover(fn2, scope);\n",
       "                    } else {\n",
       "                        this.mouseout(fn2, scope);\n",
       "                    }\n",
       "                }\n",
       "                return this;\n",
       "            };\n",
       "        })(events[i]);\n",
       "    }\n",
       "\n",
       "\n",
       "    Element.prototype.mousewheel = function (fn, scope) {\n",
       "        if (Snap.is(fn, \"function\")) {\n",
       "            var el = this;\n",
       "            var fn2 = function (event) {\n",
       "                fn.apply(el, [event]);\n",
       "            };\n",
       "        }\n",
       "\n",
       "        this.node.addEventListener(\n",
       "            /Firefox/i.test(navigator.userAgent) ? \"DOMMouseScroll\" : \"mousewheel\",\n",
       "            fn2);\n",
       "\n",
       "        return this;\n",
       "    };\n",
       "\n",
       "\n",
       "    // Snap's attr function can be too slow for things like panning/zooming.\n",
       "    // This is a function to directly update element attributes without going\n",
       "    // through eve.\n",
       "    Element.prototype.attribute = function(key, val) {\n",
       "        if (val === undefined) {\n",
       "            return this.node.getAttribute(key);\n",
       "        } else {\n",
       "            this.node.setAttribute(key, val);\n",
       "            return this;\n",
       "        }\n",
       "    };\n",
       "\n",
       "    Element.prototype.init_gadfly = function() {\n",
       "        this.mouseenter(Gadfly.plot_mouseover)\n",
       "            .mouseleave(Gadfly.plot_mouseout)\n",
       "            .dblclick(Gadfly.plot_dblclick)\n",
       "            .mousewheel(Gadfly.guide_background_scroll)\n",
       "            .drag(Gadfly.guide_background_drag_onmove,\n",
       "                  Gadfly.guide_background_drag_onstart,\n",
       "                  Gadfly.guide_background_drag_onend);\n",
       "        this.mouseenter(function (event) {\n",
       "            init_pan_zoom(this.plotroot());\n",
       "        });\n",
       "        return this;\n",
       "    };\n",
       "});\n",
       "\n",
       "\n",
       "// When the plot is moused over, emphasize the grid lines.\n",
       "Gadfly.plot_mouseover = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    var keyboard_zoom = function(event) {\n",
       "        if (event.which == 187) { // plus\n",
       "            increase_zoom_by_position(root, 0.1, true);\n",
       "        } else if (event.which == 189) { // minus\n",
       "            increase_zoom_by_position(root, -0.1, true);\n",
       "        }\n",
       "    };\n",
       "    root.data(\"keyboard_zoom\", keyboard_zoom);\n",
       "    window.addEventListener(\"keyup\", keyboard_zoom);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    xgridlines.data(\"unfocused_strokedash\",\n",
       "                    xgridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "    ygridlines.data(\"unfocused_strokedash\",\n",
       "                    ygridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "\n",
       "    // emphasize grid lines\n",
       "    var destcolor = root.data(\"focused_xgrid_color\");\n",
       "    xgridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"focused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // reveal zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 1.0}, 250);\n",
       "};\n",
       "\n",
       "// Reset pan and zoom on double click\n",
       "Gadfly.plot_dblclick = function(event) {\n",
       "  set_plot_pan_zoom(this.plotroot(), 0.0, 0.0, 1.0);\n",
       "};\n",
       "\n",
       "// Unemphasize grid lines on mouse out.\n",
       "Gadfly.plot_mouseout = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    window.removeEventListener(\"keyup\", root.data(\"keyboard_zoom\"));\n",
       "    root.data(\"keyboard_zoom\", undefined);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    var destcolor = root.data(\"unfocused_xgrid_color\");\n",
       "\n",
       "    xgridlines.attribute(\"stroke-dasharray\", xgridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"unfocused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", ygridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // hide zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 0.0}, 250);\n",
       "};\n",
       "\n",
       "\n",
       "var set_geometry_transform = function(root, tx, ty, scale) {\n",
       "    var xscalable = root.hasClass(\"xscalable\"),\n",
       "        yscalable = root.hasClass(\"yscalable\");\n",
       "\n",
       "    var old_scale = root.data(\"scale\");\n",
       "\n",
       "    var xscale = xscalable ? scale : 1.0,\n",
       "        yscale = yscalable ? scale : 1.0;\n",
       "\n",
       "    tx = xscalable ? tx : 0.0;\n",
       "    ty = yscalable ? ty : 0.0;\n",
       "\n",
       "    var t = new Snap.Matrix().translate(tx, ty).scale(xscale, yscale);\n",
       "\n",
       "    root.selectAll(\".geometry, image\")\n",
       "        .forEach(function (element, i) {\n",
       "            element.transform(t);\n",
       "        });\n",
       "\n",
       "    bounds = root.plotbounds();\n",
       "\n",
       "    if (yscalable) {\n",
       "        var xfixed_t = new Snap.Matrix().translate(0, ty).scale(1.0, yscale);\n",
       "        root.selectAll(\".xfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(xfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".ylabels\")\n",
       "            .transform(xfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1, 1/scale, cx, cy).add(st);\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var y = cy * scale + ty;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.y0 <= y && y <= bounds.y1 ? \"visible\" : \"hidden\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (xscalable) {\n",
       "        var yfixed_t = new Snap.Matrix().translate(tx, 0).scale(xscale, 1.0);\n",
       "        var xtrans = new Snap.Matrix().translate(tx, 0);\n",
       "        root.selectAll(\".yfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(yfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".xlabels\")\n",
       "            .transform(yfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1/scale, 1, cx, cy).add(st);\n",
       "\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var x = cx * scale + tx;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.x0 <= x && x <= bounds.x1 ? \"visible\" : \"hidden\");\n",
       "                    }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // we must unscale anything that is scale invariance: widths, raiduses, etc.\n",
       "    var size_attribs = [\"font-size\"];\n",
       "    var unscaled_selection = \".geometry, .geometry *\";\n",
       "    if (xscalable) {\n",
       "        size_attribs.push(\"rx\");\n",
       "        unscaled_selection += \", .xgridlines\";\n",
       "    }\n",
       "    if (yscalable) {\n",
       "        size_attribs.push(\"ry\");\n",
       "        unscaled_selection += \", .ygridlines\";\n",
       "    }\n",
       "\n",
       "    root.selectAll(unscaled_selection)\n",
       "        .forEach(function (element, i) {\n",
       "            // circle need special help\n",
       "            if (element.node.nodeName == \"circle\") {\n",
       "                var cx = element.attribute(\"cx\"),\n",
       "                    cy = element.attribute(\"cy\");\n",
       "                unscale_t = new Snap.Matrix().scale(1/xscale, 1/yscale,\n",
       "                                                        cx, cy);\n",
       "                element.transform(unscale_t);\n",
       "                return;\n",
       "            }\n",
       "\n",
       "            for (i in size_attribs) {\n",
       "                var key = size_attribs[i];\n",
       "                var val = parseFloat(element.attribute(key));\n",
       "                if (val !== undefined && val != 0 && !isNaN(val)) {\n",
       "                    element.attribute(key, val * old_scale / scale);\n",
       "                }\n",
       "            }\n",
       "        });\n",
       "};\n",
       "\n",
       "\n",
       "// Find the most appropriate tick scale and update label visibility.\n",
       "var update_tickscale = function(root, scale, axis) {\n",
       "    if (!root.hasClass(axis + \"scalable\")) return;\n",
       "\n",
       "    var tickscales = root.data(axis + \"tickscales\");\n",
       "    var best_tickscale = 1.0;\n",
       "    var best_tickscale_dist = Infinity;\n",
       "    for (tickscale in tickscales) {\n",
       "        var dist = Math.abs(Math.log(tickscale) - Math.log(scale));\n",
       "        if (dist < best_tickscale_dist) {\n",
       "            best_tickscale_dist = dist;\n",
       "            best_tickscale = tickscale;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    if (best_tickscale != root.data(axis + \"tickscale\")) {\n",
       "        root.data(axis + \"tickscale\", best_tickscale);\n",
       "        var mark_inscale_gridlines = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        var mark_inscale_labels = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        root.select(\".\" + axis + \"gridlines\").selectAll(\"path\").forEach(mark_inscale_gridlines);\n",
       "        root.select(\".\" + axis + \"labels\").selectAll(\"text\").forEach(mark_inscale_labels);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "var set_plot_pan_zoom = function(root, tx, ty, scale) {\n",
       "    var old_scale = root.data(\"scale\");\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    // compute the viewport derived from tx, ty, and scale\n",
       "    var x_min = -width * scale - (scale * width - width),\n",
       "        x_max = width * scale,\n",
       "        y_min = -height * scale - (scale * height - height),\n",
       "        y_max = height * scale;\n",
       "\n",
       "    var x0 = bounds.x0 - scale * bounds.x0,\n",
       "        y0 = bounds.y0 - scale * bounds.y0;\n",
       "\n",
       "    var tx = Math.max(Math.min(tx - x0, x_max), x_min),\n",
       "        ty = Math.max(Math.min(ty - y0, y_max), y_min);\n",
       "\n",
       "    tx += x0;\n",
       "    ty += y0;\n",
       "\n",
       "    // when the scale change, we may need to alter which set of\n",
       "    // ticks is being displayed\n",
       "    if (scale != old_scale) {\n",
       "        update_tickscale(root, scale, \"x\");\n",
       "        update_tickscale(root, scale, \"y\");\n",
       "    }\n",
       "\n",
       "    set_geometry_transform(root, tx, ty, scale);\n",
       "\n",
       "    root.data(\"scale\", scale);\n",
       "    root.data(\"tx\", tx);\n",
       "    root.data(\"ty\", ty);\n",
       "};\n",
       "\n",
       "\n",
       "var scale_centered_translation = function(root, scale) {\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    var tx0 = root.data(\"tx\"),\n",
       "        ty0 = root.data(\"ty\");\n",
       "\n",
       "    var scale0 = root.data(\"scale\");\n",
       "\n",
       "    // how off from center the current view is\n",
       "    var xoff = tx0 - (bounds.x0 * (1 - scale0) + (width * (1 - scale0)) / 2),\n",
       "        yoff = ty0 - (bounds.y0 * (1 - scale0) + (height * (1 - scale0)) / 2);\n",
       "\n",
       "    // rescale offsets\n",
       "    xoff = xoff * scale / scale0;\n",
       "    yoff = yoff * scale / scale0;\n",
       "\n",
       "    // adjust for the panel position being scaled\n",
       "    var x_edge_adjust = bounds.x0 * (1 - scale),\n",
       "        y_edge_adjust = bounds.y0 * (1 - scale);\n",
       "\n",
       "    return {\n",
       "        x: xoff + x_edge_adjust + (width - width * scale) / 2,\n",
       "        y: yoff + y_edge_adjust + (height - height * scale) / 2\n",
       "    };\n",
       "};\n",
       "\n",
       "\n",
       "// Initialize data for panning zooming if it isn't already.\n",
       "var init_pan_zoom = function(root) {\n",
       "    if (root.data(\"zoompan-ready\")) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    // The non-scaling-stroke trick. Rather than try to correct for the\n",
       "    // stroke-width when zooming, we force it to a fixed value.\n",
       "    var px_per_mm = root.node.getCTM().a;\n",
       "\n",
       "    // Drag events report deltas in pixels, which we'd like to convert to\n",
       "    // millimeters.\n",
       "    root.data(\"px_per_mm\", px_per_mm);\n",
       "\n",
       "    root.selectAll(\"path\")\n",
       "        .forEach(function (element, i) {\n",
       "        sw = element.asPX(\"stroke-width\") * px_per_mm;\n",
       "        if (sw > 0) {\n",
       "            element.attribute(\"stroke-width\", sw);\n",
       "            element.attribute(\"vector-effect\", \"non-scaling-stroke\");\n",
       "        }\n",
       "    });\n",
       "\n",
       "    // Store ticks labels original tranformation\n",
       "    root.selectAll(\".xlabels > text, .ylabels > text\")\n",
       "        .forEach(function (element, i) {\n",
       "            var lm = element.transform().localMatrix;\n",
       "            element.data(\"static_transform\",\n",
       "                new Snap.Matrix(lm.a, lm.b, lm.c, lm.d, lm.e, lm.f));\n",
       "        });\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\");\n",
       "    var ygridlines = root.select(\".ygridlines\");\n",
       "    var xlabels = root.select(\".xlabels\");\n",
       "    var ylabels = root.select(\".ylabels\");\n",
       "\n",
       "    if (root.data(\"tx\") === undefined) root.data(\"tx\", 0);\n",
       "    if (root.data(\"ty\") === undefined) root.data(\"ty\", 0);\n",
       "    if (root.data(\"scale\") === undefined) root.data(\"scale\", 1.0);\n",
       "    if (root.data(\"xtickscales\") === undefined) {\n",
       "\n",
       "        // index all the tick scales that are listed\n",
       "        var xtickscales = {};\n",
       "        var ytickscales = {};\n",
       "        var add_x_tick_scales = function (element, i) {\n",
       "            xtickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "        var add_y_tick_scales = function (element, i) {\n",
       "            ytickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "\n",
       "        if (xgridlines) xgridlines.selectAll(\"path\").forEach(add_x_tick_scales);\n",
       "        if (ygridlines) ygridlines.selectAll(\"path\").forEach(add_y_tick_scales);\n",
       "        if (xlabels) xlabels.selectAll(\"text\").forEach(add_x_tick_scales);\n",
       "        if (ylabels) ylabels.selectAll(\"text\").forEach(add_y_tick_scales);\n",
       "\n",
       "        root.data(\"xtickscales\", xtickscales);\n",
       "        root.data(\"ytickscales\", ytickscales);\n",
       "        root.data(\"xtickscale\", 1.0);\n",
       "    }\n",
       "\n",
       "    var min_scale = 1.0, max_scale = 1.0;\n",
       "    for (scale in xtickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    for (scale in ytickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    root.data(\"min_scale\", min_scale);\n",
       "    root.data(\"max_scale\", max_scale);\n",
       "\n",
       "    // store the original positions of labels\n",
       "    if (xlabels) {\n",
       "        xlabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"x\", element.asPX(\"x\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    if (ylabels) {\n",
       "        ylabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"y\", element.asPX(\"y\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    // mark grid lines and ticks as in or out of scale.\n",
       "    var mark_inscale = function (element, i) {\n",
       "        element.attribute(\"gadfly:inscale\", element.attribute(\"gadfly:scale\") == 1.0);\n",
       "    };\n",
       "\n",
       "    if (xgridlines) xgridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (ygridlines) ygridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (xlabels) xlabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "    if (ylabels) ylabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "\n",
       "    // figure out the upper ond lower bounds on panning using the maximum\n",
       "    // and minum grid lines\n",
       "    var bounds = root.plotbounds();\n",
       "    var pan_bounds = {\n",
       "        x0: 0.0,\n",
       "        y0: 0.0,\n",
       "        x1: 0.0,\n",
       "        y1: 0.0\n",
       "    };\n",
       "\n",
       "    if (xgridlines) {\n",
       "        xgridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.x1 - bbox.x < pan_bounds.x0) {\n",
       "                        pan_bounds.x0 = bounds.x1 - bbox.x;\n",
       "                    }\n",
       "                    if (bounds.x0 - bbox.x > pan_bounds.x1) {\n",
       "                        pan_bounds.x1 = bounds.x0 - bbox.x;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (ygridlines) {\n",
       "        ygridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.y1 - bbox.y < pan_bounds.y0) {\n",
       "                        pan_bounds.y0 = bounds.y1 - bbox.y;\n",
       "                    }\n",
       "                    if (bounds.y0 - bbox.y > pan_bounds.y1) {\n",
       "                        pan_bounds.y1 = bounds.y0 - bbox.y;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // nudge these values a little\n",
       "    pan_bounds.x0 -= 5;\n",
       "    pan_bounds.x1 += 5;\n",
       "    pan_bounds.y0 -= 5;\n",
       "    pan_bounds.y1 += 5;\n",
       "    root.data(\"pan_bounds\", pan_bounds);\n",
       "\n",
       "    root.data(\"zoompan-ready\", true)\n",
       "};\n",
       "\n",
       "\n",
       "// drag actions, i.e. zooming and panning\n",
       "var pan_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        root.data(\"dx\", 0);\n",
       "        root.data(\"dy\", 0);\n",
       "        root.data(\"tx0\", root.data(\"tx\"));\n",
       "        root.data(\"ty0\", root.data(\"ty\"));\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        dx /= px_per_mm;\n",
       "        dy /= px_per_mm;\n",
       "\n",
       "        var tx0 = root.data(\"tx\"),\n",
       "            ty0 = root.data(\"ty\");\n",
       "\n",
       "        var dx0 = root.data(\"dx\"),\n",
       "            dy0 = root.data(\"dy\");\n",
       "\n",
       "        root.data(\"dx\", dx);\n",
       "        root.data(\"dy\", dy);\n",
       "\n",
       "        dx = dx - dx0;\n",
       "        dy = dy - dy0;\n",
       "\n",
       "        var tx = tx0 + dx,\n",
       "            ty = ty0 + dy;\n",
       "\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\"));\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        set_plot_pan_zoom(root, root.data(\"tx0\"), root.data(\"ty0\"), root.data(\"scale\"));\n",
       "    }\n",
       "};\n",
       "\n",
       "var zoom_box;\n",
       "var zoom_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        var bounds = root.plotbounds();\n",
       "        var width = bounds.x1 - bounds.x0,\n",
       "            height = bounds.y1 - bounds.y0;\n",
       "        var ratio = width / height;\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        x = xscalable ? x / px_per_mm : bounds.x0;\n",
       "        y = yscalable ? y / px_per_mm : bounds.y0;\n",
       "        var w = xscalable ? 0 : width;\n",
       "        var h = yscalable ? 0 : height;\n",
       "        zoom_box = root.rect(x, y, w, h).attr({\n",
       "            \"fill\": \"#000\",\n",
       "            \"opacity\": 0.25\n",
       "        });\n",
       "        zoom_box.data(\"ratio\", ratio);\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        var bounds = root.plotbounds();\n",
       "        if (yscalable) {\n",
       "            y /= px_per_mm;\n",
       "            y = Math.max(bounds.y0, y);\n",
       "            y = Math.min(bounds.y1, y);\n",
       "        } else {\n",
       "            y = bounds.y1;\n",
       "        }\n",
       "        if (xscalable) {\n",
       "            x /= px_per_mm;\n",
       "            x = Math.max(bounds.x0, x);\n",
       "            x = Math.min(bounds.x1, x);\n",
       "        } else {\n",
       "            x = bounds.x1;\n",
       "        }\n",
       "\n",
       "        dx = x - zoom_box.attr(\"x\");\n",
       "        dy = y - zoom_box.attr(\"y\");\n",
       "        if (xscalable && yscalable) {\n",
       "            var ratio = zoom_box.data(\"ratio\");\n",
       "            var width = Math.min(Math.abs(dx), ratio * Math.abs(dy));\n",
       "            var height = Math.min(Math.abs(dy), Math.abs(dx) / ratio);\n",
       "            dx = width * dx / Math.abs(dx);\n",
       "            dy = height * dy / Math.abs(dy);\n",
       "        }\n",
       "        var xoffset = 0,\n",
       "            yoffset = 0;\n",
       "        if (dx < 0) {\n",
       "            xoffset = dx;\n",
       "            dx = -1 * dx;\n",
       "        }\n",
       "        if (dy < 0) {\n",
       "            yoffset = dy;\n",
       "            dy = -1 * dy;\n",
       "        }\n",
       "        if (isNaN(dy)) {\n",
       "            dy = 0.0;\n",
       "        }\n",
       "        if (isNaN(dx)) {\n",
       "            dx = 0.0;\n",
       "        }\n",
       "        zoom_box.transform(\"T\" + xoffset + \",\" + yoffset);\n",
       "        zoom_box.attr(\"width\", dx);\n",
       "        zoom_box.attr(\"height\", dy);\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var zoom_bounds = zoom_box.getBBox();\n",
       "        if (zoom_bounds.width * zoom_bounds.height <= 0) {\n",
       "            return;\n",
       "        }\n",
       "        var plot_bounds = root.plotbounds();\n",
       "        var zoom_factor = 1.0;\n",
       "        if (yscalable) {\n",
       "            zoom_factor = (plot_bounds.y1 - plot_bounds.y0) / zoom_bounds.height;\n",
       "        } else {\n",
       "            zoom_factor = (plot_bounds.x1 - plot_bounds.x0) / zoom_bounds.width;\n",
       "        }\n",
       "        var tx = (root.data(\"tx\") - zoom_bounds.x) * zoom_factor + plot_bounds.x0,\n",
       "            ty = (root.data(\"ty\") - zoom_bounds.y) * zoom_factor + plot_bounds.y0;\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\") * zoom_factor);\n",
       "        zoom_box.remove();\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        zoom_box.remove();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onstart = function(x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var scalable = root.hasClass(\"xscalable\") || root.hasClass(\"yscalable\");\n",
       "    var zoomable = !event.altKey && !event.ctrlKey && event.shiftKey && scalable;\n",
       "    var panable = !event.altKey && !event.ctrlKey && !event.shiftKey && scalable;\n",
       "    var drag_action = zoomable ? zoom_action :\n",
       "                      panable  ? pan_action :\n",
       "                                 undefined;\n",
       "    root.data(\"drag_action\", drag_action);\n",
       "    if (drag_action) {\n",
       "        var cancel_drag_action = function(event) {\n",
       "            if (event.which == 27) { // esc key\n",
       "                drag_action.cancel(root);\n",
       "                root.data(\"drag_action\", undefined);\n",
       "            }\n",
       "        };\n",
       "        window.addEventListener(\"keyup\", cancel_drag_action);\n",
       "        root.data(\"cancel_drag_action\", cancel_drag_action);\n",
       "        drag_action.start(root, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.update(root, dx, dy, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onend = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    window.removeEventListener(\"keyup\", root.data(\"cancel_drag_action\"));\n",
       "    root.data(\"cancel_drag_action\", undefined);\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.end(root, event);\n",
       "    }\n",
       "    root.data(\"drag_action\", undefined);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_scroll = function(event) {\n",
       "    if (event.shiftKey) {\n",
       "        increase_zoom_by_position(this.plotroot(), 0.001 * event.wheelDelta);\n",
       "        event.preventDefault();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseover = function(event) {\n",
       "    this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseout = function(event) {\n",
       "     this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomout_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), -0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomin_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), 0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_track_click = function(event) {\n",
       "    // TODO\n",
       "};\n",
       "\n",
       "\n",
       "// Map slider position x to scale y using the function y = a*exp(b*x)+c.\n",
       "// The constants a, b, and c are solved using the constraint that the function\n",
       "// should go through the points (0; min_scale), (0.5; 1), and (1; max_scale).\n",
       "var scale_from_slider_position = function(position, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return a * Math.exp(b * position) + c;\n",
       "}\n",
       "\n",
       "// inverse of scale_from_slider_position\n",
       "var slider_position_from_scale = function(scale, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return 1 / b * Math.log((scale - c) / a);\n",
       "}\n",
       "\n",
       "var increase_zoom_by_position = function(root, delta_position, animate) {\n",
       "    var scale = root.data(\"scale\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\");\n",
       "    var position = slider_position_from_scale(scale, min_scale, max_scale);\n",
       "    position += delta_position;\n",
       "    scale = scale_from_slider_position(position, min_scale, max_scale);\n",
       "    set_zoom(root, scale, animate);\n",
       "}\n",
       "\n",
       "var set_zoom = function(root, scale, animate) {\n",
       "    var min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"scale\");\n",
       "    var new_scale = Math.max(min_scale, Math.min(scale, max_scale));\n",
       "    if (animate) {\n",
       "        Snap.animate(\n",
       "            old_scale,\n",
       "            new_scale,\n",
       "            function (new_scale) {\n",
       "                update_plot_scale(root, new_scale);\n",
       "            },\n",
       "            200);\n",
       "    } else {\n",
       "        update_plot_scale(root, new_scale);\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "var update_plot_scale = function(root, new_scale) {\n",
       "    var trans = scale_centered_translation(root, new_scale);\n",
       "    set_plot_pan_zoom(root, trans.x, trans.y, new_scale);\n",
       "\n",
       "    root.selectAll(\".zoomslider_thumb\")\n",
       "        .forEach(function (element, i) {\n",
       "            var min_pos = element.data(\"min_pos\"),\n",
       "                max_pos = element.data(\"max_pos\"),\n",
       "                min_scale = root.data(\"min_scale\"),\n",
       "                max_scale = root.data(\"max_scale\");\n",
       "            var xmid = (min_pos + max_pos) / 2;\n",
       "            var xpos = slider_position_from_scale(new_scale, min_scale, max_scale);\n",
       "            element.transform(new Snap.Matrix().translate(\n",
       "                Math.max(min_pos, Math.min(\n",
       "                         max_pos, min_pos + (max_pos - min_pos) * xpos)) - xmid, 0));\n",
       "    });\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var min_pos = this.data(\"min_pos\"),\n",
       "        max_pos = this.data(\"max_pos\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"old_scale\");\n",
       "\n",
       "    var px_per_mm = root.data(\"px_per_mm\");\n",
       "    dx /= px_per_mm;\n",
       "    dy /= px_per_mm;\n",
       "\n",
       "    var xmid = (min_pos + max_pos) / 2;\n",
       "    var xpos = slider_position_from_scale(old_scale, min_scale, max_scale) +\n",
       "                   dx / (max_pos - min_pos);\n",
       "\n",
       "    // compute the new scale\n",
       "    var new_scale = scale_from_slider_position(xpos, min_scale, max_scale);\n",
       "    new_scale = Math.min(max_scale, Math.max(min_scale, new_scale));\n",
       "\n",
       "    update_plot_scale(root, new_scale);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragstart = function(x, y, event) {\n",
       "    this.animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    // keep track of what the scale was when we started dragging\n",
       "    root.data(\"old_scale\", root.data(\"scale\"));\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragend = function(event) {\n",
       "    this.animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "var toggle_color_class = function(root, color_class, ison) {\n",
       "    var guides = root.selectAll(\".guide.\" + color_class + \",.guide .\" + color_class);\n",
       "    var geoms = root.selectAll(\".geometry.\" + color_class + \",.geometry .\" + color_class);\n",
       "    if (ison) {\n",
       "        guides.animate({opacity: 0.5}, 250);\n",
       "        geoms.animate({opacity: 0.0}, 250);\n",
       "    } else {\n",
       "        guides.animate({opacity: 1.0}, 250);\n",
       "        geoms.animate({opacity: 1.0}, 250);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.colorkey_swatch_click = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    var color_class = this.data(\"color_class\");\n",
       "\n",
       "    if (event.shiftKey) {\n",
       "        root.selectAll(\".colorkey text\")\n",
       "            .forEach(function (element) {\n",
       "                var other_color_class = element.data(\"color_class\");\n",
       "                if (other_color_class != color_class) {\n",
       "                    toggle_color_class(root, other_color_class,\n",
       "                                       element.attr(\"opacity\") == 1.0);\n",
       "                }\n",
       "            });\n",
       "    } else {\n",
       "        toggle_color_class(root, color_class, this.attr(\"opacity\") == 1.0);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "return Gadfly;\n",
       "\n",
       "}));\n",
       "\n",
       "\n",
       "//@ sourceURL=gadfly.js\n",
       "\n",
       "(function (glob, factory) {\n",
       "    // AMD support\n",
       "      if (typeof require === \"function\" && typeof define === \"function\" && define.amd) {\n",
       "        require([\"Snap.svg\", \"Gadfly\"], function (Snap, Gadfly) {\n",
       "            factory(Snap, Gadfly);\n",
       "        });\n",
       "      } else {\n",
       "          factory(glob.Snap, glob.Gadfly);\n",
       "      }\n",
       "})(window, function (Snap, Gadfly) {\n",
       "    var fig = Snap(\"#img-b44e7f66\");\n",
       "fig.select(\"#img-b44e7f66-5\")\n",
       "   .init_gadfly();\n",
       "fig.select(\"#img-b44e7f66-7\")\n",
       "   .plotroot().data(\"unfocused_ygrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-b44e7f66-7\")\n",
       "   .plotroot().data(\"focused_ygrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-b44e7f66-8\")\n",
       "   .plotroot().data(\"unfocused_xgrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-b44e7f66-8\")\n",
       "   .plotroot().data(\"focused_xgrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-b44e7f66-15\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-b44e7f66-15\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-b44e7f66-15\")\n",
       "   .click(Gadfly.zoomslider_zoomin_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "fig.select(\"#img-b44e7f66-17\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-b44e7f66-17\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-b44e7f66-17\")\n",
       "   .click(Gadfly.zoomslider_track_click);\n",
       "fig.select(\"#img-b44e7f66-18\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-b44e7f66-18\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-b44e7f66-18\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-b44e7f66-18\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-b44e7f66-18\")\n",
       "   .drag(Gadfly.zoomslider_thumb_dragmove,\n",
       "     Gadfly.zoomslider_thumb_dragstart,\n",
       "     Gadfly.zoomslider_thumb_dragend)\n",
       ";\n",
       "fig.select(\"#img-b44e7f66-19\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-b44e7f66-19\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-b44e7f66-19\")\n",
       "   .click(Gadfly.zoomslider_zoomout_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "    });\n",
       "]]> </script>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "Plot(...)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Mads.plotmatches(md, r\"w13\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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tRyY5TuwYv3MUIseJXrNkSfRQv3MUItuO3uK6K4f4naMQOU7s7nnzxJT/zgHbjt6Xr22ZZpEMaK0HKaVMG2AOKGUNExFT/js3hhcVKTMpXG5UipQU+R2iMMlBgwebZujcUAfla0vm4iIDxcVbHyouLjYf9hzYc099x8aNG037ag5s3Rq4bu3a4a1+5yhEltXnsqqqoU1+5yhEffo0f8UU0MqN0tKm0/3OYBiGYRiGYeSKbUcmO050it85CpHjxGbadvQ0v3MUIseJ3t7QEBvrd45CZNvRhxxnzWe6fqTRXY4TfX7BAjF31XPAtmMv5mtb5g3MgGWpzVqbPhe5oT9WSm31O0UhEmGjiDLTgueEvB8IxM2t+9x410y5nhtKyTq/MxiGYRiGYRi5Ul/fuG99feO+fucoRLYdqairW7e33zkKkeOsOmjRohV7+J2jELlu42ErVqwo8TtHIXLd6BgR2aYDvcCBAj8QWCTwiUBcYJ3A3wUuEthTYC+BiQLzBZYKvC7wF4GvCuzp1/70JPX1jePytS3TLJIBpZInpoaiminXs0wp67xAoPV1wEy5nnWBK8rKgg8CZsr1LNNa/2DLlj7fAcyU61kgUAmcDhy99cIzTuKNpS8L2MBfgQ3Aj4CLYZshqvsAE4Dj8J4/BLgQ6AsUpx5zAPB54HiBGxTs1hVrlZLb8F6vnDMXF5mJghl3nQsierllqXf9zlGIRMQF9ZHfOQqRZanFwSBmKGoWCBwPfBP4HLBX2RtLSxA5CTgKOBnvIuOSHaxiD2AmEAD6sO13dQneRccZwMcCvwS+ABwODAaagLeA/wOWKyjoodtK6Vq/MxiGYRhGTgkckGrG2CKgBSTtJyHwaQfLu/uTFHAFZgksE+9CIy7QJLBG4J8C5wj08/s1MXYjDQ1rRi9durrK7xyFyHUjRyxd2ri/3zkKketGT1i2LDLM7xyFyHUbz1i+fHl/v3P0dgLTBKJZuHjI5OdjgY2dXMTEBf4jcILfr0ku2Xb0wnxtywyvzEAymRibTFp56wizOxGxxicS+hC/cxQiEU5PJi1TiyEHtNbnNzf3NZ1luyBQJPBZgR8KLBHYlDrJLxT4DnAMXvNEPpQBA+m4iTsIjKXALy5AXZ6vLZk+FxlQSi9USpk+FzmgdfIfWovpF5ADWjM/kSiK+Z2jEFmW+gMUfex3jl5gHF5nzJPZ9qR+FDAG+ACvX0Q+dDUZWglwmHi5vorXB2RPYD3wb+APwFpF763BYVn8yu8MhmEYhrFLBH7bRVNFPPWTSZ+JHf17cwbr6Kg5JP3nLYG3U3dY4qnntKbutjgCR0jXFymGkRnbjox3nOjxfucoRLYdOdN1o2P8zlGIbDsyqaEhNtLvHIXIdWMzli1bM9DvHD2deLUmujqhZ3Jh8LZ03rHzHYEnBDbv4PlbUhcJXW1na+pCprPOpXXijT7plRwnclO+tmX6XGSmAm8ctZFlSlmHaM0+fucoREqpELCX3zkKkdZyRDxOqd85eoHyDB6TAOI7+PdlwE+AB4HXgNXAGrwhpC8Cd+ANZb0FryZGuvXAf1L/7Uox3nmxo2bwABACTspgPT2SiDU+X9syfS4y0Npa9GQgYJk+FzlQVKTnNjVpUy8gB5QK3t7aan3od45CZFlcF4+vf9/vHL1AUQaP+Rh4E6/YVfoF21LgF8DfFdzf2QrEuxiYDSwAvgQcineRsBx4Aa9+xXXA0B1kas0gbxA4EvhzF4/rkSwrOTVf2zInTMMwDKPbxDt57w+clfr5LF4Rq3fx7hQ8CNwHdDV1goNXWfM4vOJWQ4HNqeUvAUuV9/uuZC0Cvgx8i44vYlYBe+MV5OrqvDgfuBP4It4d7QCwFlgI1O5qVmM34rqRC2w7epHfOQqR68ZmOM7qE/3OUYhsO3pLff3qkN85CpFtR++rq4vmoTlPemznQYHhAn/upH9CMtUXYkkXnTHj4p2s/8u2I0/kYsp1gbJUh8yZAo8IvCDwtMDtAmeLV1wrkUG/jFrx5jhZL9CS6suxUaBe4Fah5zbzOk70qXxtyzSLZEBrSpQy/VNyQYQ+IlYmt06NblKK0kAgYI7x3OgbDAZy9J0gQ/HKVZ8FnABSgtcn4dN2/03g/YWcADYBrwCPgHozN5k69BW8+T46YgHDUv9dj9cJMv1CKYHXHLLNCU8plZMqmQq2AotTP9sRrwz5/nQ9GuQQvP1pf4djIDAA765LK3DjLsbNCRFlCr8ZhmHsPqQCZAbIv0DiXf/x3OnPMpAbQQ7MeWKvEFZXgT4VmCte6e0PxBviuSn1/68IfE3+N8mYrwQOFYh1cafl/S72NyGdXLwYxnaWL1/e35T6zQ3bjgyoq1tX5neOQrR48dpBZlrw3HDdlUN2/da9VKUuBNxduJjo7EeDLAT5JkhObtMLfJRBkCaB2wQqBCanmg1uEbhQYERH662ri+6TPuV6PggEBE4SeLOT5pHnBd7NYJ+j+c6eqfr6xq76v2SNuWWagaamknPMlOu5oZR1uZlyPTdKShLXNTUVmynXc0Dr4G/22mvtTk65Lv2B24BLyV2neoVXBfMo4HaQF4GfgfpXFreRaX8QS3kn3DmZPDgY5IHaWk7CazbJG+XdsVgAnIZXUXQc3lDu9UAt8DLwdgar6rEX9ErJw5gp13sOpWSd6XORKzpqWXzgd4rCJG8nk8lNfqcoRJbF6/F4oKX7z5Qv4J1kd1Q3R/AuCP8GPA7qjVS/izK8E1cZXlNCX7xREIcC5+GNXujoOz2AN2fGCSAPA9eAeq/72bezEqju4jFJYEV3VipC/YYN/pTYTk25vhq4q6N/F6/fRlf1TZLZzpUtSon5Q8MwDKNwSB+QX4EkO7mbHgd5HuQqkP12chuDQb4B8u8dbEdAPgK5EmSX/mASuEF2XPUyKbBCvIufgiDeSJGumkWWC9QIPCQQEa/q58cCrwr8RGCs9OC7G0Ye2XakwnWjpkJnDjQ0RA7Jz5C+3U99/epQQ0PMVOjMAdeNHLFw4ZoMK3TKWJDXOzkXLQOZBDIouwllP5Bvg9Tt4Dy4CCTc6Rqgr8CJAveL19GxSWCdwF8EJgiEUyfbrZ1cWDSKV7iqW+rrI8f50eciEwJXiVdKvLMXdbPAS+INa+1oiG6TeMNgfZnywLYj4/O1LXOrPzPjRTBzi+SA1taZgYA/B1qhsyxrEmDmFskBrdWMsjK6mFtEgiDX4w0THZW+CuB2YCyouaA2ZjehWgPqNlDj8Gb3rO/gQUcAr4HcBrLN8E/xml0mA7/HG246Aq9A1j7A2XgFssYD1wNPAm/gFZJ6F69ZYRFexczbupvcstT1tbU9dnKwp4G7gY4q37YNCQ7iFRTr6AKpD16fjtNzFXDHrLzNLWL6XGQgELCWJhJmyvVc0FovCgYzqvlvdJt6QWsrG23rRhrLkiebmpp3UIlRDgXm4lWcTBcDvgZqQW7SpVOvgRyO14H0l3hVKNsEgWuA80G+D6qtxPaRwDSgsyaa/sAPgIuU198ja0TUI+PHo7O5zixqBH6LVz30GLat0LkYGA5M6mId/fDpzoVS+iE/tmsYhmHsMjkBZGsnd87vS40W8SvbZ0Ae20FTyT0gQYFfS2ZDTX/m3770PAI3p5o+unrdXvE7q9ED1NdHj7Lt2Of9zlGIHCdyUkPDmtF+5yhEth2rqatb1WEtAWPXuG70UtuODNj+X+RIkM0dnE/WgZyW/6SdkdNAIp2c+55bz5Dnuuis2fbzt2wnc5zoNSK71tnULwI/lsymkPfl4sJ1o9fma1u98g3MN6XkYKXkYL9zFCYrnEwmzQkwB5SSo4qLg4P9zlGItOYEpYJ9t10qo/Ha5NPLVz8GVIHqQbVc1NN4/QJuwht+2d6Xx7Lk829zUCbnh1xU1zyttrbXnpvWA5n0n/GlKVhrNSFf2+qtb2C+1SpFntpHdy+WpZ9IJjvsbGbsIq31XLzOdUaWWZbcsXVr+059chDwL9iuk+e1oGpA9cBaLqoJ1I14HT4j7f9lLcPLjmah9TLHdLWSd7OdSmu5efz4nlsrogs28Do7rnWxCW+SsyME5qRG1TQJRAXuEzhMctYfUt+Qm/UahmEYWSbDO2li6EVf5DII5MX0fSihWeby1c5u7TcJTPE7eU8i3syrV6aGonbUrPSxwHyBnwts6GS46ocCZ4iphVH4XDc2wXUbz/A7RyGy7cgkx4l1+eeR0X2OE71myZJowRQw6klsO3qL664cgle46s0Ozr13+p2x+6QE5P6OriO+yR2SxEq/sHhc4IBsp3Cc2N3z5vXcqea7IjBQYIrAkwJLxSuktVK8Ilp3CUwVWNtFn4x3xJt9NatsO3pfttfZGTMUNQNa60GpuUWMLFPKGiYiPfCWcUEYXlSkzKRwuVH59NNDBgIPsf1JYC4wI/+RdpVqAZkELANupV2z+Z18kzXsl/gzl2zty5Ym4EXgZnLS7CYHDR6cszlXck55NTD+SCdzUQnchzc9+47si1cLY3mW0x2U3fUZu2TZsmXFZnbJ3IhEIn3q6uqK/M5RiBYuXFPam/8C7MmuuEKGgLzSwR+dj0DveM0FBgucl2rn/6fAUwK3C3x5EB9MBmlK37/9aGx8iWMmiDevSU4U+gzUqTsYHc26mv7zQLa3XeivrWEYRi8mxSD/6OB88E+vaaHnEzhU4A6BVQKbBOKpPgIfCrgCM49i4ckg73WwnzaIKSu/kwReF688et6H+Ro9jG1HJjtO1HRcygHHic207WgPGv9fOBwnentDQ2ys3zkKi1ggj3dwLlgAkuFcI/4TuElgYycdChOpPgJXgFTQ8bwoC8lRMTDHiT6/YIEUbJO9wAuddPZM/7k729u27diL2V5nZ0w/ggxYltosonZQ6tfYefpjpdjqd4pCJMJGEbUT04IbOzADODNt2avAGd7Qzl7jRLxhsx31bQgA5cB4UFHgaKA27TFHAU+B5KJ55F2/plzPk1pgC+xwH4XtX/NdppSsy/Y6DcMwjF0io9i+rPdSsj6jae6l7lp09Zfz4nbPKAOp7eBh/9eb7tj0BAJDBZakmqI6unOkU31gKgROE3gsdSdpjXiz0H5bYG+/98PIgvr6xn3r6xv39TtHIbLtSEVd3TpzoOSA46w6aNGiFXt0/Uija1IC4qadBzaCDPc72c4QaMng4mJp2rP2wJumPf2hz2azr4nrRsf01CnXs0VglHhTszenLibafpICzwqMEbgl1R+mNbVcpy5INqUuMrpdNbq+vnFcLvanI6ZZJANKJU+0LH2y3zkKkVLWeYFA6xF+5yhMgSvKyooP9DtFgbgVqGq/YOTI+A9BrfUpz67KpAmnedtf1SbgJOC1tMedDDyerQsMEX7Zg6dczwrlDfc9ATgHb6ba+4FfAF8GvoJXmv0avFLyRXjnaoVXPqIfXlXVX3V7u0puy0L8jBRsp5ksi9Jx26Sxi0T0cstSWS8hbICIuKA+8jtH7ydfAK5uv2TUqPir8+atf3TUKJ8i7bpVdD3t95rtF6lPQE4Enk97/snAQyDngUrsWjT1YoH3uQBAQRxvLprt5pwRuATo0/lT6UPaxW5G21S6trvPMQzDMLJOBoDE0poBVntNBL2XwC9lx1ODr5G0C6q0NQzuZBTJfCjckR75Il5p8K6arUzxwd6uoWHN6KVLV3f7KtHomutGjli6tHF/v3MUIteNnrBsWWSY3zl6N3kk7Ts9AXKs6zae0ZsLEglUiVc86+MOTlqNAjcIfKaLtewD8lYH570/ws73mXDdyPm9dcr1bJHMpm3v9l1J245emIu8Hdmt38BMJZOJscmklbeOMLsTEWt8IqGzXkPfABFOTyatLk4QRufkEuC8tIU/B/WS1vr85ua+vfnuxZvALcAVwCzgSbyiTT9NLbsH6GLYonoX+CLblwD/GnDDzgYTUZf14inXsyWTuxI70fykLu/+c3aOuX2VgUAguESpuOlzkQNK6dpAIGBu7+WAUjwVCOh3/M7RO8l+wB1pC+uBmwAsy1QSGBgAACAASURBVHqkpGTLprzHypJUe3809fPILqxpLch4vLlGKtv9w/Ugq0D9udtrVHLf+PHonc9UEP4DTOziMVu6v1r53c6EMQzDMHaZWGw//fgWEDPDbKfkAJD3016z5lRnWKObBL7cSZNV288m8e4uGb2ZbUfGO070eL9zFCLbjpzputGueq0bO8G2I5MaGmIj/c7R+8j3O/g+/0b7R7hubMayZWsG+pVwRwSKBEICN4tXrGlTqg1/tcD9AqeLN5wx21s+PHURll4LpFszcTpO7PrdfcI9gX4CF0rHU7NvEvidQKXAyQL3CrwtsCV1QfKawI9TtTK2GR7sOJGb8rUPplkkMxV4/VMW+Jyj4ChlHaK17OLQNaMjSqkQ8LrfOXoXqQZuTFv4T9LmedBajojHeSxfqbppf+B64Cy2HUJfCYzAK+f9A4HHFNlsflCvgUwGHm233YHAsyBHgtqQ2XrkuMGDuTV7uXofBZ8KPAYsAk4FqvGGn64E/oXXRHcqMBMYy7bv8zhgNF6tjJ8CdW3/IGKNz316I2OLF68dZKpI5sayZZFhdXWr9vQ7RyFy3bXD6+rWlfmdo/eQANtX4XwfZLsRN64brayrqyvyI2VXxLtw2NEog7hAnUCOqovKdR1s9t9kWGTLcVYdVOgVOrNBvLLgO3qfPxX4efvnuO7qblf13Fm99g28csqVI4NafRErEBm0edC/b5x/YyvAd6dM6b8lWXqKUqq1aEvRP389/9dNO1puGIbhkSvYfibKr4B6wo80O0u8v1S7mg33feDbCh7IUYo/AZPTFj4AfBWU5GabuxeBCN5d9R15TnlVVfOuVw73+cbXv3FAQAdeFrGqRCfP/6DvB88BTJ06tWirLn0JqAG+HC9r+fuOlmfKdaPn2HasJtv7YYDjRC43/Vlyw7aj17lu42F+5+gdZABwc9rCBzq7sLDtyG+WLl09NPe5dkomJd+LgW71heimy9m+GflivOaaHXKc6AO7e5+LDGXy+Rvc/hfHiT6coyzb6ZUXF1bSOk0hs2bNnXXVrDl3XQpy6IxLZwwtjhefhyI2e+7smllzZk1Dqb2nXzK9srPlmW5Pa+mvlPTagjk9mzVABHPrPgeUYpBS2ZtQqsD9iG2/iLcCP+j84WpIMlnUU/usZXJHWmX4uJ2N0IrX5yO9z88NqfohO7LP4MG99656HmX6Pv+XiMrbBJw99eDYoVlzZt0BcNWUq0Ki5SyUrLrj93esnz55+ihQ7n8fKOpNFdRjRawOl+PdVupSdXXlnOzugdEmHC7/edePMnZGOFxxjd8Zegc5EJietvBnoDqYW8NTXV2Rt0qHO2E1EOriMa1484vkkPoE5CvAK/zvwk0B94FEQb3U0bPC4Yov5jZXwfiArvvNbGz/S3V1+XG5i7OtXnlx0UaScgRKjkUkceWFV+6FyFCleLnt35WSd4FhnS5vZ/HitYNKS5N7ipSsD4WGbamvb9w3GJQ+GzeOaNxnn7dKRYoqtmzhk3Hj9m9csWJFSVNT8WeUSm4ZPXrk+rq6VXsWFwcHtbYmNo4bt/8nrrtyiFJF/fr31+sqKyub6+pWjSguDgarqspXz5sngUMOaSzX2moJh/d7x3Xf66tUy9CmpsAnRxwxfOOyZWsGJpN6QCBQ+v6oUUM+bZ/j+ONVwnWjlcmk1mPGjIyl51i0aMUeZWXFeyeT+sPq6sqP23J8+qn17tFH79e0dOnK/USKikaPHhGZPx+rfY66unVlxcXxYa2tRZvGjdv3g/QcdXXRfYqLVWlr64Y148aNi7fPsWzZsuJkst/wQEBvHTWq8r30HPX1KwYHg8X9O8rxxhtr94rH9T5KBT4JhYavTc/R0BDbC9iruLhpwyGHHLI5PYdtRyoAqqsro205Wlulady4ineXL1/ev7W1dDDwUVVV+UdtOVpbi94bN27fra67drhSyeLRo0dEAZYubaxQKh4fPfqANQsXrint10/vk0i0bh4z5sANbTm2bm394MgjD9y0bFlkWDJplQUCn64dNWpUq21HKixLqVCoIlJXV1dUXDx4v/QcgYD18ahR+31YV7du7+Li+B7pOZYvHxGrqUEvXdpYmZ5DJP5pKHTA+7YdGRAIWAPTc5SWtr5z4IEHttTXry4PBCwrFKqIvPpqZFifPgxIJAKbxowZsW7Zsvf7JZNNQ9JztH3mHWfNZyxLl7TP0dqaSIwbt39jJBLps3mztW96jrbP/NKlq4eKBPq2zxEMBgJVVeWrFyyQ4KBBjSMSCdXcPkfbZz792GvL0faZb2iIjUzP0dmx15ajo2OvLUf6sXf44fLblhZV/L/vB94R4bb0Y6+hITYykUgmx4wZGXPdFcOLivYsTSY/3dQ+R/qxl56jo2OvLUdnx15bjo6OvbbvgPbHXvyMY/9T9P57n8WbTXP7701IKmhs6b/3Kw3/WTJSJNDa0bHXlqOzY891o5Vai7Q/9tK/A6Dxw6qqEacpxYsilKYilFgWT0ya9NFZf/zjgJfajr22HIsXRyvLyiwrHm/Z1P7Ya8vR0bHX9h3Q2bHX9h3Q2bGX+g6Qjo69tu+Azo69thztj730HJ0de205Ojr22nJ0duzJmANfV4nWfaDTGWS3aCu4rMFZNbLt2LPtNQcGAjrZliP92MvkvJupXtksMn3K9HFTp07de9bcWffOmjP7iwgtwSI1QRQNgvy33LGGgSrJss6Wt19ncXHyBK31TKVaDgFQSi7WWs8cNKixf1NTyTnNzdZvg0FrGsDWrUX7aq1nJpPqKwBFRcFxWuuZgUDwc97agmdorWd++GFwOEAgELxCaz1TRKyRI1f387aT+CqASPNBWuuZJSXxLwHE48nxWuuZ8finn/Weqy/UWs/s3//dAQBa8x2lrOkAn3xiDdVaz9RanQ3Qp0/RWK31TMviSG/dwdO11jPLylr3854bvFxrPbO2lkBV1VtlWuuZkPwaQElJ8wHePrSeCNDamviC1npmIrHlMIBgkAu01jOLigbs5a2bb1uWNQMgkdhziJdZnQtQVhYIe+tWR3uvZfA0bx+TFQDJZPAyrfXMlStXFsfj8g2QX4kkp3ivZWKk1npmMBg/2duOOlZrPbOpqbTK+3c10Vv33nt76+ZbpCZYamnpv7eXUU0EaG4uDXmvO8cAWFbxyal1p5rEkl/XWs985ZW1JdFotNjb38DXvdcjWeG9HsWneJnlaK31zNLSkpD3Plk13j7vMdhbtzVDhG95zx040NuOnO99XvocprWe2dqaONZ7T1tP0lrPLC5O7u/tY+JrWuuZBx+8vs+SJUuC3mcrOBWgb9/4CG8fAqd5z1VHec8NVnvvkzpbaz2zuVkNSeW4CrjWy2HdIKJusSx9gfc+bRnlZU4e572WLV/yPj9NB3qvZXKS1nrmiBEr+86fj+Xtf+BygA8/DA73XvfghNTrfoT3WgfGeq+POktrPfPTT4P7eDmtaVrzHe/z8M6e3mdeLvYyNx+qtZ7Zp0/y+NRr/UVv3c2pnuyJS7TWMwcMiPYTEeW9ltY3ADZvtlLHXuBMb3+Dh3uf+eDhXo7AmV6OwGe8z631jdSxpwYMiPbztpNI3ZZvPvjxx8vubGlR23R4O+qo5rtBbVVKX+QdP+/s2XbsBQLed4DWxbNbW7fekEyqs7zXMjDW20eO8NYSnKC1nvnxx3o/7/UIXK61njl/PtaIESv7epmSk711NR3ovZYtbd8Bx6WOvVHePuoLvH3cc0Aq4rWp95nmZjXE+2ypcwCKi4PVsZ/cPiQxcO836WhadcvSyb0Hb9ZFRQ+89fLra70cia95z03un/oOOMl7nxLHaq1nbt3a5zBvH+Q87zgeOND73PKttu+AeHyPwd5ny6oBKC0tCXnvkxwN6rVzz900p30MrdnrX//qN+973/uo/yuvrC1JfReljj0eTiT09yyrOPUdwDHeZ7w05H2OrYla65ktLf3bRvBdnfoeAPbe29sHOQ+gqam0yttHdaz3eYif7L3WiZHeupNTtNYzlyx5t8/KlSuLU8feZQD9+iXKvfc0eJq3bnW093kIhL19Vud679OebcfeDBG+7X0eBuzlfW5pO/bavgO+4L2WrSd672lzqn9M8mta65lVVW+V1dYS8I7L4OUAn3yiU98BwdO97XCk1nrmpiOOfh14G8tKpr/NUlQcB15u2f+Af3v7oC8CUCr5aOo7YLz3Wse/5K27Oev9b3plu9ZVk6f9QAvB2XNn35z6/VUs6zJJSj+U/GTWnNnHX3nhlXtZxVY9mnFKqUM6Wj77/tkbu9oWgOvGJoBSodCIbnUENbpm25FJSlmrwuHyl7t+tNEdjhO9Jpnk2bFjK970O0vPJAHAxqsJ0GYhcExXIxpsO3qLZSXuCIUOeD+XCXeGeHcsqoEZwGHAnnh/3W4BGoHHgT8oaMlzshvYvobIH0Bd2n6B48TufvvtEdMnTlTbnTSN/xHYCzgTOB+vhkmZt5hPABeYCzjAscAFwFESCA5TycQG4FXgQbxOtxuzW+/E0zsvLi69argk9O9B7Y3SFsK/Z8256+qamprA0L6DH1SokQIjlHDrb+fOvrOz5X7vh2EYfpJvALPbLwCOBPWqT4EKnCi8wlBnp/3DFaDMnBdZJlCK15foGryRJenn+814I6T+pNL6Zuz2Zlw6Y+iNNTcWpy+fPmX6vt+dMmW70R2dLe+KbUcqXDea8egSI3MNDZFD6uqi+/idoxDV168Opdqrje3IAJANaXWH5mT6bNeNHLFw4ZrSrh9pbEv6g7yR9rq3ghzT9oj6+shxpojWrkvNT7Kii0JbGwS+5HfW3ZZtRyY7TnSK3zkKkePEZtp29DS/cxQix4ne3tAQ66qY0m5Kbk/7nt2CNxNqRmw7+pDjrDHT2e8UORjkk7TX/12QfQEcJ/r8ggXSqwcb9AQCdwl80sXFhYhXIjzremWHznwLBKylWlsNfucoRFrrRYGA5HhI3O5KvaC19Z7fKXoe2R/4RtrCn+5o6Gk6y5Inm5ubN2c31+5CvQVMwmuGajMMmA9SLKIeMVOuZ8WBkFENoVwWUzMMw9hdyN/T/nhbA9KrCrmlZj29TeDV1Gynrwr8SuAQ6XxoYg8jP+/gD+nf+J2qUAgsEEhkcOfCDFTwS0NDbGx9feM4v3MUovr6yHENDZFD/M5RiBwndrq5dZ9OTujg+/W87q7FdSMXLFq0Yo9cJOyKeFNxL0tNTBUX0Kn/fppqYz9F0qba7pnEAnk2/f04++xNfxIRc1d9Fwk8IN407F1dXMzuem3dZ97ADCSTerRl6Sq/cxQiy7KOTCbV/n7nKExygmXp7Wb03H1JAEj/y/gVYF5316S1mtCnT5+8TwkgMAb4PnAw3i3vIN4ogCDQFxgJ3Jb6bw+nNHARaZWSn3yy31fLyjB/zO26BcAGtm1+SvcpkJMyAObiIjO1Sm03CY+RBZaln0gmqfc7RyHSWs/FKwVteL7OtjUtNDBjZ2bptCy5Y+tWPsxassxdCOyH1/TR0YgKC68N3ZeZMLtPfYg3oWRz25J4XFlNTTwMMtC/XAXhr8BLwMd0XMdiM16TyH/yGcowDKOASDFILO2O8Fy/U3VXqh29NYNb3b1s32RSB7vxZKo2hrGTBCoE7hZ4Q+A9gY0C6wVWCvxe4EAxNxn847qxCa7beIbfOQqRbUcmOU7smK4faXSX40SvWbIkeqjfOXoGmZp24mqi3ZQA3WXb0Vtcd+WQbCbMhEC9QDKDi4vH851t18nsDnblu36nKiS2Hb0vX9syVywZ0FoPEtF7d/1Io7uUsoaJyJ5+5yhQw4uKVK8aBZEbUoTXT6G9e0G9swsrrRQp6XBisBzbCGRSFrs3Vlz8Fl4fmPZuaV9gy9hVKm/DTk2hkgyUlrb8xe8MhUpE/y6ZLGn1O0chamkJ3jJwYNOnfufoASYBFe1+bwF+sSsrtKzE1R9+WO5Hn4tXgLF480rsyMI8ZMky1QpynmXhaE1bf4sg8DDIGFAb/ExXCETUBX5nMAzDKABSBLIq7Vb7b/1OtbMEKgWWdFG/4CWBXjwCS04FSabt1vOp0T6GUThM+e/cMeW/c8eU/waQKWknqRaQ8l1dq1/lvwUsgaMFXhFo6eDC4kWBw6UX35V2nOjzliW/6OC66Yd+Z+vtbDv2Yr621Ws/gPlkWWqz1sr0T8kJ/bFSaqvfKQqRCBtFVJ6n1e5JJAB8L23hH0DFsrDu9wOBeGLX19M9yiuY9SpwFt6EU0cBg/HqGfwbr2bBeyqzfhk91bsnncSPnn2WI/GmC29zE8giUP/nV7DeTilZ53cGwzCMXm674Y2tIBV+pzIyJcPwJjRr/x6+R2qCM8Po9RYvXjuorm6dGS2SA8uWRYbV1a0yo0VywHXXDq+rW7ebjhaRAMjytBPTPdlau+tGK+vq6vwYLVLwHGfVQf+bcl1OAEmkvY8LTP+LneO6qw/O17bMrf4MFBfHJwSDrabORQ7E49akQCBghprlgEjimuLi+O5a5+JCvBLZbeLAz7O1cq25JRgcmvc6F7uHwN21tW2Tr6kXgFvTHjAeuD6/mQqD1oF787Utc3GRmShp9e+N7BDRyy2Ld/3OUYhExAU+8jtH/kkAuC5t4RxQWTuGLUstLiqiKVvrM9pTL27YsM18GDcC/0p70A9BekmJ855DKV3rdwbDMIxeSi7soK9Fpd+pjF3RYf+L9ab/hdGrNTSsGb106WozK2oOuG7kiKVLG3vxmPyey3WjJyxbFtnNZkUVC+SNtJPQH7K9FddtPGP58uU5mRVVYD+B6QLPpuaEqBf4o8BJ4s2EWtBcN3J+x1Ouy/Ed9L94wfS/yJxtRy/M17ZMs0gGksnE2GTSMlMA54CINT6R0If4naMQiXB6MmnlvRaDzyYC7fuZJNi+zX6Xaa3Pb27uu0e21ytwJN608D8GTsDrN1IFnA/cC3xLvKGnBUtEXVZb29G5SS3AayJp73i2bwIzOqUuz9eWzMVFBgKB4JJAQNf5naMQKaVrg0Frud85CpFSPBUI6F2ZP6OXEQv4QdrCB0CtyvaWLMt6pE+fLZuyuU6BcmAKcCqwJ1CM9x0dAEqB4cAVwJnZ3G5Po5TcN358h1OEg3ehmN7/4gZvVInRNfmd3wkMwzB6GZmYdss8AZK3iZp2lcD5Asu6mO00KXC/31n9JUNA1qW9NGtBTLkAo3ex7ch4x4ke73eOQmTbkTNdNzrG7xyFyLYjkxoaYiP9zpEfokDctBNOzk7CrhubsWzZmoFdPzJzAt8X2JTBdOovZXO7PY3jxK6fN6+rfhQd9r94xvscGJ1xnMhN+dqWaRbJTAVgepvngFLWIVqzj985CpFSKkTXs2cWigl4fRPaJIFbcrUxreWIeJzSLK+2NPXTlQLv1CnHDR5MFxcJagHbz2x7CnBNjkIVBBFrfL62ZeYWyUBra9GTgYBlrohzoKhIz21q0qZeQA4oFby9tdXyY1pwP1yb9vsjoN7K1cYsi+vi8fXvZ3m1W1I/XVWs3Zzl7fYwySvHj89obpTrgS8An2+37FaQl0C9mptsvZtlJaf6ncEwDKOXkMM7aD0I+Z2quwTOEXAyaBb5vd9Zew4ZDvJB2ksUA8lqk5Vh5ITrRs+x7ViN3zkKkeNELjf9WXLDtqPXuW7jYX7nyD2Zl3ZyeTbXW7TtyG+WLl09NJvrFBgicKdA0w4uLN4Sr7R5wXKc6ANd97loT04D0Wkv1fzcJey9HCf6cL62ZfpcZEBr6a+U5KRgjmENECn0NmR/KMUgpaTE7xy5JZV404+3d1vut6uGJJNF2W5W3gDchTca5JMO/v0tvH17Ksvb7Wn26brPRXvqaeC3aQvPBclbTYfeQkSZiqaGYRhdkzvT/mJ1e/OIAYGAwKBUNc6fCjwsMEdghkBod6jQuXOkBGRJ2mehCSTsdzLD6NSyZcuKV6xYUeB/AfojEon0MVNX58bChWtKu3d7ubeRvUA2p51QLsnHll33vb4dl6g2dtXOl1WXA0A2pX0e3gDpm92EvVeuStZ3xBwcGWhtLbtwy5aii/zOUYg++cSaEQjsfaLfOQpRWVnylkMOaSzkv9yuAPq1+30t8Eg+Nqx1832uu9YMoc6B5uY+jy9YIDvR5KRWAulNIYcCs7IQqyA0NZXmrUnNXFxkwLKsjUpZH/idoxCJ6PeUUh21Lxu7bm08Llv9DpEbUgJclbbwTlDxPAWIKNWSr23tZtTbaVOud+e5DwPpE9VNBrl4F0MVCHnb7wSGYRg9mExJu/29CWSA36mMnkD6dFCt9VMQM0Gi0bPYdqTCdaOmQmcONDREDqmri5rbyzlQX7861NAQK8AKnR2W+v5VPhO4buSIhQvXZLtCpwHU10eOE9nVTrkyCmRL2mekAWS3fs9sOzI+X9syzSKZGS+CqcWQA1pbZwYCmLlFcsCyrElAIc4tcgrblvpOAHfmM4DWakZZGaZQUw5Ylrq+tpZd7IislgFXpy0czfYlw3czVt7mFjHlvzMgot4CZS7EckI7gUBwnd8pCpGIeqW1NbHB7xw58O203+eBasxnAMviBa0TW7r7PPHmDgkDJ+DNVxQA1gGLgFpV8KW9M/L0DqZc7wZ1H8hxQPvO+NNBXgD1t11ff+9jWfKk3xkMwzB6IKnqoBpjr7jzJbCXwOUCLwu8J9AiEBfYKLAkVdfCFDnKKukH8lba5+UjkAq/kxkGDQ2xsfX1jeP8zlGI6usjxzU0RExHqxxwnNjpjrPmM37nyC55IO1E8bwfKVw3csGiRSv26M5zBL4i8LaA7qCsd1JgncDNucrcW9h27LLs1hCRsSAtaS/5YpDdrr6O40TyVrXU3OrPQDKpR1uWrur6kUZ3WZZ1ZDKp9vc7R2GSEyxLD/M7RfbIcGBi2sI8lPrentZqQp8+fbpbkGgicCB0WNraAoYAp+1qtt5OKTm/tjab5ya1BPhe2sLPsRteyIlYeZuXxlxcZKZWKRb4HaIQWZZ+Ipmk3u8chUhrPRdY7XeOLLoaaP/X5nLgH34EsSy5Y+tWujud/dFd/HsA7wJjt6a13JzhlOvd8RvgibRlM0FOz/J2ejh9g98JDMMwehDZA+TjtFvbX/c7VXcIbM1gOvX1fucsXDIIpDHtJV8PYobCG/5wnNUnum7kZL9zFCLHiZznupEj/M5RiBwncoVtrzrQ7xzZIdd2cFLo41ca143+oK5u3d7deY7ABxlcXOz2I6dsO/rL3M2JI8eCxNNe9loo5Dl4/sdxorfna1umWSQDImpfM1VtrlgVWqtufUkbmVIHBQLBbnU67JkkCHwzbeGdoJr9SAOgNYcFg8nuTma4NIPHfLozeQqJUozp3pTr3Vr7S0B6rYfjgOtzs72eRUSNzde2zMVFBkpLW/7Sp0/zfL9zFCIR/btkstj0Z8mBlpbgLaWlra/7nSMLzgb2a/f7FuAen7IAYFmJqz/6aHh3mzAeA3Y018unwOKdT1UYEgkuzkGfi/ZuBdJHGf0Q5Es53GaPIKIu8DuDYRhGDyEvp93GvsvvRDtDoELgV6m6FunNIZsFHhM43O+cuwcZCrIu7W14z/S/MPLKtiOTHSc6xe8chchxYjNtO7rbD7/LBceJ3t7QEMvbbdDckDFpJwANcqjfqWw7+lB3a4gIBATKBb4q8DuB5wReEPizwDcFQsKulr3u/Rwn+vzOTbneXXIcSGJ36n9h27EX87UtU/47A5ZFi9amCSkXlKIZtJm6OgdEaEokkgm/c+yi9PkhngP1pi9JtrUlkUh2q0S1giQQA+5P/RgdEJE89TtRL4L8GLix3cK2/hcFOWRTKTHl5Q3D2N3JEJCmtL8sT/U7lVFIxAJ5Lu0zlgQ50e9kxm5g8eK1g7o77MzIzLJlkWF1dav29DtHIXLdtcPr6taV+Z1j58mNaV/6b3snA/+5brSyrq5utysfnQ+Os+qgXZ9yvTtkCMg7HQx1LrgRgq67+uB8batHHKg9XXFxfEIw2HqG3zkKUTxuTQoEAsf4naMQiSSuKS6O+94/YedIMZA+D8KdoLIwW+au05pbgsGhu301zdwI3L3rU653h3ofuBC2GaEyBHio0PpfaB24N1/bMhcXmYkCEb9DFCIRvdyyeNfvHIVIRFzgI79z7KTzgPbzomymB/VTsCy1uKiIJr9zFCb14oYNSL63Cfw4bWHB1b9QStf6ncEwDMNH8mrabeq8VRY0dlem/4WRZ46z6qB8tlXtTurrV4fq6laN8DtHIaqvjx7VO/sKydEdfMH3qJlzXTf2Rdd9r6/fOQqR48ROz+6U693Raf2Lguh/4bqxCfnalmkWyYCIdbSI9Xm/cxQiywqcHAgERvudoxBZFjXFxfFyv3PshPRS30+DWuVLkk5oLV8XiQ9IXy5wkMAMgXsFHhaYLXCZwDDpeKp1YzvyrexOud4daj1wEdv2vxgKPALS6zvwas21+dqWqXORgUAguESpuPliyAGldG0gEPjA7xyFSCmeCgT0O37n6B4Zjlfuu707/UiyI5ZlPVJSsmVT+2UCpwLTgMOAwUAx0AycBJwI3CywTEGP6JTaUykl940f7+drpBaA3My2c5AcC/wM+LY/mbJFfud3AsMwDB/IT9NuSb8O+RyWuHMEDhV4WaBVQHdQ3rtF4K8CvbCZanckFsgzHVSHrfE7WW/R4w/azsy4dMZQnYifopX6KF4Uf+bee++NA3x3ypT+W5KlpyilWou2FP3z1/N/3bSj5Zmw7ch4pZQKhyvMBFtZZtuRMy1LrQmFKur9zlJobDsyKRCwXqqqKl/td5bMSCmwBhjUbuFUUPf5FKhTrhubEQxafx41ar8PAQRuxvurdkd1RZqAixT8LR8ZeyvHiV3/9tsjbpk4UeVy8rIMyECgDqhst/BT4HM9pEpstzlO5KZwuDIv1Ufz0q418ZSJP5p46rk/bL/s/NPPHT/x1HMframpKe3u+qZ94hV7GgAAIABJREFUddqgZCKxWOBk4Nji1qKV350ypf/UqVOLturSl4Aa4Mvxspa/A3S2vBsq2PYDZmSJUtYhWmMmC8oBpVQI2MvvHN1wEdteWHwEPORTlh3SWo6Ix2n/3fUlvGaQHSkFTE2XLslxuZtyvTvUh3hDolvaLewHzAPplZ15Razx+dpWXi4ulKU/BvX9CRMm/PeqXmumgtp7/vz53R4rbgXkeIHnZ8256/zZf5p9LfBaU7LPWcXx4vNQxGbPnV0za86saSi19/RLpld2tjzT7YkEntPa+kd3cxpdE9GPJpPFu/0007mRvGfr1tYVfqfohqvSfr8X1BZfknTBsqxb+/Ztbt9XaBiZTTpmLqS7oBTfyfGU692gXgO+lbbwMKDH3U3LhIjKW5+RvHTobI0nHy0KBm8vTZaeAvxl8vjJfbaqLROUSHqv8IzEE/rfJSUlLwFcddVVJXqzPiwpcnNAuACU+98HinpTBfVYEWtUR8vJsDDWmDEj1u1MTqNr1dWVUb8zFKpweP+3/c6QOTkBqGq3IAnc41OYLoVCI15PW/QpXkfNri4wzMRRXeh5TaTqbpAjgEntFl4A8jKou/xKtTPGjBlRl69t5eXi4m/P/e39iafVPIfmXOAvW0u3nowQDErJX3Zmfff8+Z73Aa6afOWR8mnyLoU17+77726YPmna1UrxctvjlJJ3gWGIDO1weTu2HT1NKTk2EJCHRo8e2eC6kStFKE8k9E+LigJf0pqLLYvXQqGKW5cuXblfMhmYJqKWVldXPOg4sWNAn25Z8kxV1ch/u27kAhFCItxTXV0ZdZzI94ABoVDFD956662+zc0l14FaGw5XzHLdxsNEkhcrFVgYCo34e0ND9BSt5TgRHqmurnQcJ3I5UFlUFPzFqFH7fWjb0VuUoikcrviJN+Vz4iqlrDdCofL76+ujR1mWnCnCP6qrK2sdJ3IeUG1Z1r1VVeWrbTv6HaVk0EcfVfxw4MD1JSJNP1LKWhcKld+5ZEn00EBAJomwqLq68nHHiZwEHK+UmhcKVdTbduwypfT+iUTJr8aN2/cDx4n+GFQ8HC6/ua4uuk8w+P/snXl8VNXZx3/PuZMhIezKqpIJCuJCZiagiNaKVnFF64Jr674WWqu1ttXWai32fev6Wqi27tatROteFaugVgQNc+8NoiiSuROQVXayztzzvH/cCYQhIZMwd+5kcr6fTz4wdznPb5Z7z7nnPAtfz4wl4XDpk6YZHc+MM4lodjAYeF/XY1OI5Fjb9j06dux+3xiG9QuABxYU1N0WjxdfTYQjpeRPw+HSB0yz+kBmugygT0OhwL90PXYCkfyBlNqL5eXDK03TuoKZRxLZ9wWDB6w1jOgdzOBwuPT2RYuqB9s23QDQ16FQ4HFdrzmMyD5bSvGf8vKS/5imdTYzHwbIx0Oh/b82jOgNAAb37YvbE4kE19b67gBobSgUuE/Xl40kElcQicpgsORF04z9gFmeAPC/QqERnxpG9DIABxYU4IFDDildbZqx3zOzFgoFbotElg4UwvcLIvomGAw8WlUVGyulnALw+6HQiNmGYZ0J8Hgh8GRZWekS04xdzyyHJhI9/gCsjPt8e91JRN8Fg4F7Fi2q2d+27asAEQmFSmYZhnUswCcS4ZVgsHS+rkcvIcJBUmoPlpcPX2kY1u+I0CMYDPzW+a3wEACfhkKlfzMMKwzweUSYGwyWvq3r0TOIMAEQ/wiFShYbhjUN4H0LCor/uHjxwPpRo6zpzGJDOFzyZ12PBohwLRGMYLD0hUgkeowQOJmZXguHA/MMI/YjQB6qafbMMWMOWK7r1q0AFYfDJbfoerQfEX5NhFgwWPpQJFIdFIIuYKYPw+HAv00zNvm885ruXbJkx6rCoYc2LX300ZoN48czmab1JyJsDgZL/1RZuWy4zyd+wkxV4XDgOdOsOZrZPpVIezMYHP6RrlsXEnGZlPxQefmImGlGf8OMvsFg4DcLFnzTu7DQdwszLQ+HAzOrqpaPkTJxEZH4OBgseV3XrVOI+PtS8vPl5SNMw4heCyDAjP8Jh0s36XrsLoBrw+HAdMOwHgVkPaAtCIVKnmkatm+sYM3qg6idIrS2VlC5uOrbXvF47W8B8W0oVPIXw4gdAsgfM+OTcLj0VdOMnsSMiQD9MxQK6IYRuxqQIxobC+4eP37f9aZp/ZEZjaFQ4M5IpGaYEPbPmPFlOFz6lGlGj2DGDwF6JxQKzDGM2LmALNc07ZExY4YvM03rJmbeO5FY/ztgWIHP13gbkVgVDJb8X1VVdLSUuBSgBaFQ4GXDqJ4E0HFCiIqyspKFpmldycwHSJm4t7x85DrDsP5ARHYwWHLH4sXRIfE4fg7gq1Co9AnDqD4coLOIxLvBYMl7phk7h1mOY5aPhcP7LzUM60aABxUXJ37v8/lo82bcDmBNKFR6v2FEXwPEl0T8aTAYeCkSiR0vhDyeWXspHB7+mWFYlwM8StP4/jFjRqzR9ejtRKBQqPT3pvnNIGbtRiJaGgwGHotEasYJYZ/DLN4Lh0veNQzrLIAPJ+IngsERX+l69OdEGFJX57ujb98tdjze8w8ArQuFAvcuXLj8AE1LXMksFobDuK5XL3nUtm3igObvUgg8OH36ugknnFB787hxgVWGEbsN4IJQKPC7ysqVe/t8jTcxi2XhcMkjpmmVM/O5AOaEQqXv6Hr0h0Q4wrbpqbFjA1+aZuxnzHIYUdGdGzYMbuzf3/ojM60PhwN3m6ZVyszXANBDodJ/Oj6AOElKerW8PPCJacYuZpYHExXMCAb3XWEY1m+ZURQOB25dvHj5gHg8cTMAKxQqfTgSib4tBAwh6IOyssBbpllzOrN9JJH2TCsD5j0ie6GoTM9A8N8vnXhpYT3VTgHw6rNvPbul3fPaYNqlP/kJgy4G0dUznphR6ZhAFcD7NB8jgQGajTekgK+17S3bE8JnEtmrmbE8Kfh9IbReRUV19U1NPXtrmqgist8AACl7bRCisQLJ1MpE8a+JCiqI7BXOuTRfCPpa04q+S7b9JiD9AHjbtm0Nfn9RBSBrnbbsFZomKoia1jqvtSoh5FpNEzVO2zyXSKv0+xtqnbbwkhAyAQCJhLbR75cVRLQJADQtsYyooKI5/JCIPiWib/z++nXOueItIu4xcSLsuXMHN+61V01FPM51AMBsrxTCV9HUlFjnvAff50LI7+rrtZjTVuIDIXyRvn1rm5+8/iWlU3K6qUnb5PfLinhcbAYA205U+3z+iqYmTs74yM+EENUNDQ1rk5/P20JQ4cEHH5wwjJreRFjATO8CQDzOq/1+rSKRsL9zdNFiTRMbEglfLPl5fahpPqN3b2xx9u9wjtu6tWBLr16ywrYTWxwdvqjfzxVS0irntaz0+TSrri6x2mlLvOPzoeizz4bHAWD06JoKKdEAAI2Nck3Pnr7tOuJx/sLvF5uamgpiybY/KiiQVZs3O+9ZSvkqEREA9O/v27p1q6iQMrEVAOrrNauoCBWJhKMjkbAX+v2+mqamRFIX3vX5RNHWrUObJk4cKhctqqlgpkYAKCioW8tcVGHbcr3zmr+0bbElkWiqAQCfT/svM3+eSPg2JXW8pmlCc75v6iUEzbHtxKfOuVrMtmWFlGK1c64dYS5YYdvO78W28V5BgehZX1/TOGXKQLlokdiuw+8v/s626yuYeQMA9OiBr2xbbGOOL3d+e/QJs/hSyqINTtvydSmFzzm3rs62e1Uw29uccwuW27asYNbWAMC99/b/bskS/05JskaNarzH59tcT0RcVRWrAEST8x6K1xPtuPaESHzNrNURJVYkdcwH6KuCgqL1zu/W9waR9BMRV1ZW1gsxcPu1B8gVQogKovhapy1fFZG9pqBALHfO5TlEWi9N21bn7OcXm689ZvTRNPESEX0NAIm9BzxSsG7N4bCxN9pYbpZFxV9pMjGnvr6m0e8f2OLak9869wBHB7NvkRBynaaJmHNmYq4QvoUDBtQ3lyL/l5TSdr5v3yafj1tee8t8Pv/2ewCz/FTTxLKCgrrktSfeFoJ7jB071p47F7zXXjUViYSTxrypSa7y+3fcA6T0fe7z8fr6es1yXtsfaJpP79vX13wPeFlKyQCwebNvc69eO+4BiURhtd8f334PsG37M59Pi9bVJdY4p9I7QlChrh+QAJxrr1kHM/oSiZdsO9587BdCiI1NTc49gNn+SNN85tatorn/eIWTycL79NG2bN0qtt8DpPRZPh9vv/aklAt9Pi3W1OTcA5jFbE1D0YoV+zZNmABetGjHPaC4uHZNU1PztUf1xxxTd8lbbxW9IyV6OW1Bu+22vU545ZViLfn5vCqEEADQt2/t1vp6//Z7QEODL1ZUZG+/9mxbRvx+33Jmmbwn8LsFBaLn+vWDGydOhN3y2uvRo+G7pqai7dee348lti22EjnXnhD0MbNY3NQkNjjXgHxtx7XXUGvb/u3XnhCitxDYrkOIJp254Fvbbu67MkfWnGYmT57cs0gWriHwVcz0dyZcUPFmxZudaWvqpVNPAHD72tq136+oqNi+NjftkmlHgfiPM56ceex1F17XX/hFBBLjiGh0a9tnPj1zfcbeoEKh6CR8D3bOH6ADVO6Vms7AQCGAiwH8Co4DeOoAYyGcvAlvExDPrjpF5uCzAVRg577zHQCn5EpRvVwhqx65555y7lPJtVX/2rp1+8ydO3f3c4htMPWyqfcQ43I465wAACKevnrbukcHFw98lkAjGBhOjLv+8tTMB6dMmaK1tj1de4sXL/b7/X4aOXJkY/tHKzpCNBotXL9+vT1u3Dh1w80w8+YtL1qxYt8m70P6dgcXA1gBoGW2y8sAetIbPelhmquLy8oG1xPt6FAY6AvgCADHATgYQG8AGwDoAD4A8Ck5SbUUu2HJkiW9R48encO+KbsMhgHgDwBlJcRzT8j9z7aTTDllygnnnjKFzz35nLvdtDPt8mnDbr788t7pbm8PXY9e6qzzKTKNYcR+pevWqV7ryEcMw7qvqio21msdu4evS0lUtAbgHl6rag9dt55zfJ4UmcYwrPfmzOEczh7NPoA/bKX+zRleK2sPXY99kC1bWf0CpZCWJgXbGrtaU37G4zNaje5oa3t7CCHWA5QDcdf5B7NcTeSs0yoyzormdf3chAm7hp8+DFBXmCGMEjWq2TZXoK+zX3K9I1AimakzAqC5oJkA8A+AJwC02Dtt7cFZiyDLSoc5ceJE38CBAwvENjzAAvvOerNCPakqFN0engRnvbqZOIAAQCr0W9EF4O8D+A+AlgXNvgYwHnCc7LszWUmiNbBw4P5UizomhAjiV9mwmUl0PRowTUtl6HSBqqro6MpKSyUWcoFIpDpYVRXL5Qyd16e8rugqAwvTjI6fN295h7MLK9onEokew5z79WQA+hC7JtgaBeCfAKeTUC3r6Hp0YrZsZWVwccgRhywVPm2fWf+uGP/PN/+Z0VjaLDGRGcd6LSIfkVKcoWnoUpEBXQUhxCUARnito3X4ADjp+1uSc9VP20JKur5nTwzwWkc+IgTdNnduWtlOcwCaiV2zdU7CzhVVcwiRNV1Z8bm4/fbbJYAu8UTSGsz0FUBZGYh1P6Shab4u+9vIZZjpkx15S3KOn2Lnh5uFAHWZNPBC4H0pEzmZmjwPeNPbkusdZiqAg7Bz3ZhbAK4CaJZHmlpFCH7daw0KhULhEtwb4E0p3vYXeq1Koeg8PATgFSm/6a0Aj/FamSKHqaqKjY1EasZ5rSMfiUSix1RVRUd7rSMfMYzYabkZLsnXp9yEVwLcXkXRnMI0oxfMn7+0j9c68hFdj13FzF1wppgnANyQ8tuOAry318qaSZaTyApd8AvMPrYtxwghy9o/UtFRhBBH2Dbt3/6Rio7Dxwkhh7R/XDZhAnBdysaHAWryQk26MBBg4HoGZjOwaszYkc+MnzDqWwaqGPgrA99nQDl4ZgAiPn/u3K7YN9EnAFI77wCA553cGN7DLLI2Q5gTbzjXIZLzmutGKDKLlPbbUvJGr3XkI1KiIpEoiHmtI4VTABzY4nUjAFfz3uwpDAwAcAGAawHsB4AokQCAXgDGwIkQGArgTwA+9UhmHkH3dzGfixbQUwAfAee30szxAO4CcLM3mnYgBO7xWoNCoVC4AL+dMm38tNeK2oOBExmYzynCU/5qGbjVa62KXID9AH/Uys9E+RUpdsYwqieZZjQ1bE6RAQwjep5pRsd7rSMfMYzotbq+bKTXOnbAowGWKTfcnPdlYuBWBta1M7hgBl70Wms+oOvW3bNm5WaeiPThIQAvT/mJ1Dt+Gd5hGNZ92bLVBde1sg8zDWOmYe0fqeg4IiAl5YzDU35BozTNl0tOhz/DzlmBPwao0isxHWAggHQ+x8FuC+kOEKF84MDsFtXMPLQawOmAU0Y+SSGA1wD2zMeMmbJWa0j5XKRBUVHjS15ryFeY5d9su0dOO/N1VRobfdMHDKjf1v6R2YD7Afhxysa/eKGkE8jkX3vkcPXZrkMigR9NnJgPnyXpAF8N4GnsGFTvDeBVgI8EaEu2FTHTBdm2qVAoFC7Cv0iZIv4W4IL2z/MeBm5gYEUayyI57z+i8AL+Qys/l7dzJYJE4SGmGb1A162LvNaRj5hm7HrDqJ7ktY58RNet6ZFIddBrHQALgJel3Fx/47WqdGHgCAbeYSC+m4HFGnYyNSr2EF2PvprbJdc7ChPAz7bys8l6unvDsN7Ili3lc6FQKNzmdOxc46QRwGMeaekMJoAXkv+2Vg5+DYBZAN7LpihFV4EYwBUA5qfs+CnA0zwQpFAoFPkAv5fyxPao14o6CgP9GJjCwGMMfJRMnrWQgdcYuIWBg1g9rCl2Cw8B2Eq5FhIAn+a1MoVHLFiwYq/KypUqosEFFi+ODqmsXNbXax35iGmu2LeycmVPb1Xwoa2En4a81bTnmKZVWllZ2SV8RroahrFsVNcoud4ZuAzgLSnXw2aAD8mGddOsPrD9ozKDGmmngd8fn+zzNZ3utY58JB4Xl2ia9r32j1R0FObEjX5//CCPZdyAncNPPwDI8EpMppAS032+wYO81pGfaA91nZLrHYWq4GR7bRkN0wfAGwC7/nuSUstaNlw1uEgDIl5JxKosuCtISwj+zmsV+Ql/bduJrIe7tbA/GECqI3TWndjcQAh8nkhorflfKPYQZkTWrQN7rcM96E0Av0jZGADwMsCFrlomXuhm+wqFQpEFdgnBqwa6euZFhSJT8MxWIkheU9dIN8Iwlo3K5lpVdyISqQ5WVi4b7rWOfCQSsSZ45yvERQCvS7lx/tQbLZnHNGM/MM3VxV7ryEcMI3Za1yy53lFYA/iNVgYYD7tl0TRjk91qO5Vu8AXuOcziSGZxlNc68hEhtJM0TRvjtY58RAhM8fvjJR6Z/zGcbITNbALwhEdaMo6UfAVzvJ/XOvITvqFrllzvKGQD+BGAz1N2XAOwK0XwpMRNbrTbGt3gC9xzNM23UNNkV6iB0OUgknN9PrHEax35CBHe0DT5bfYtMwH4ecrGvwGUI6nI9xwhxAuFhbUe+rPkL0T8SNctud5RaBOAEwHEUnbcCfAVmbfHf8t8m62Tp+E+CoXCO/g0AK+32BAHsD9Ayz0S1C4M9ARwCIDxAIbBuTeuBhABsJCAOg/lKfIePhjARwAGtNhoAzgHoFe80aRwnUjEmqDrMbUs4gKGET2xqmq5WhZxAV2PTfHGn2WXpFn/yL6G9GFgLwYuY+BtBpYz0MBAIwMrGfgPAz/jnZd4YJrWlboeVcsiLmAY1o3dw+ciFR4P8LaUa6fOKXKWGUzTUssiuQQRH0jEyqHTFUTItm3l0OkCRDzB7/cNzK5VLgNwbMrGXA8/nQjgJgCTAOwLoAcAP4ChyX3TAJzX8gQpcRyRTzl0usOp3cPnIhVaACcHRqLFxiI4ZdpHZ8KClKQcOnMJZm22lOJtr3XkI8zyn7btX+C1jvzEfriurmlplo3ehJ2XW+cC9FmWNXSUswEcjNaXiTUApQDObLlRCHFXcXGDys/iAkT4ZX6UXO8M9DqAn6Rs3AvAbID33dPWmSk1v4ZCoVDkOjwM4MaUad2cz2zLQDSNcupfea1T0Z3gO1r5GVYBrJbi8gnTtM7W9dgUr3XkI4YRvcYwrNRpdEUG0HXrVtOsOTR7FvmulJvh10Dur50zUJvG4KKm5Tm6Hn1g0aLqwV5pzmcMw3pm1iyVSArgR1r5Kb7v5JDpHIZhPZ9Jhbsj5y/8XEBK7k3Evb3WkZ+IfszwuLhWfkKEvYi4R3ascTGAa1I2PgBQVwgpbErjmJRpehpk2wU+V9Qohg4cqCIZAVyHnaOuAMef6UWA/Z1pkJmG7bEqReZYvHixf+nSpVm6SXcvotFooaou6Q7z5i0vyt4TIE9LecJanxxw5DwMLEhj5mKnYmumubq4e0Y0uM+SJUvUg9x2uAjg/7byk3wZ4A4PbrP52aqLQ6FQ7CEsAPwsZePDANV6oaYT/BtAw272bwWgCj4pPIDqAZwOoCplxw8BPJnLy445KyyXaGrqeWFtbUFqdUdFBti8WVyvaXtP8lpHPtKzpz199OiaUBZMnQ5gZIvXTQBmZMFupngZwCwArWXc3AJgNoDHW26UsuER01wxNAvauh0NDYWvzJnT8afy/IU2ADgewBcpOy4C8FgyI25a1NcXvZFJZbtDfYFpIIRYD5BaA3QBZrmaSGz2WkeesiIe52xklrwh5fVzAK3Kgt1MsQTA3XBqPBwGYB84Yamr4GTo/A+A1PT/UaLGeDZFdh/o6/wuud4ZaB3AkwB8CGBEix2XwplZS505bAP+OtPKFAqFwgV4bCvrwdmYLVEouiE8HOBoK9fcfV4rU3SCSKRmWCRSo7xsXUDXowHvyoLnN4axbNT8+Uv7uGuFn0u5yb3rrr3cwDRrDlVO3u5gmlY5c/pT/d0PPgDgla0MMH7b3pmRSM24bCgElM9FWhDZk4SQJ3mtIx8hEudpWtN4r3XkJ9q1PXv6R7Z/XGfhAIBzUjbe75693EFKeUttbaEaFLsAM+6eOxcqz0Wb0DdwUtWnZoi9E+Abd3sm8b2uyUpBDS7SgJm+YiaVoc8VpKFpWk37xyk6CjN90tSUWOeiiZsBtAwj/hLAWy7ayxmEwPvMia4SDdPVeLP7lFzvLPQ5nFLtm1J23OOEhbeOEJyaN0OhUChyCR4KcH3KtOylXqtSKLoXPAHgrSnXoQRY1RDpClRVxcZmc62qOxGJRI+pqopmpOKfYmcMI3aaYSzfx53W+Z6UG1qss1kDuyKmGb3AfX+W7omux65SCco6Ah+FXUu1M8C/Tz3SMKKpWXRdQ32BaWDbcowQssxrHfmIEOII26b9vdaRn/BxQsghLrS7F3ZN9f2/AKWTRtsTGChh4HwGbmbgNgauZ+BkBjo1QJCSJhcWFqpMki5AxOd3z5LrnYU+BnAWgNSw89sB/kPLDcziwmypUnku0oBIziNSeS7cQEr7bSl5o9c68hEpUZFIFMRcaPp6AL1avF4D4AkX7GQEBr4H4HIAEwDsB6AQTnKsrwG8x8BfCfi2I20KQY8BBanr3YqMQPcrn4uOQrMBPgnAmwBaDnp/56QQp18CgBC4xxN5CoVCsXu4D8AbUqZfb/JaVVswUMrAbAZsBmQrNUNqGbiXARVWqsgD+LBkXZ/Un/pDuZwqvNtiGNWTTDOqQlFdwDCi55lmVIWiuoBhRK/V9WUZDkXlX7dSoCxnlwcYuIWBRDtFyTYx0KHfoGlat6j8LO6g69bdquT6nsDlAH/Xyk/97wsXxrIWKq5GMmnATMNUqVq3EAEpSd2kXYFGaZovg06HXIhd0wz/H0BbM2cj45yF9u9zfeHUbkgbKXGoz2er2Q4XIEK5Krm+J1AEzu85NQz9quuvH3hhZ6qpdgblc5EGRUWNL3mtIV9hln+z7R456wjYlWls9E0fMKB+WwabvApAy2JdWwH8JYPtu0FpmseNaP+QHQiR+PmGDSUbOqFH0Q6JBH40cSJsr3V0bcgA+Fg4dXG2O3X/979FgwA8DOBKr5QpFApFC7gAYCtlmvV/vFbVHgysasPXIvXvr15rVSgyD48CeHmLn3pdctChyAVMM3qBrluq5LoLmGbsesOoViXXXUDXremRSHUwM63xFSn9cb2TSCu3YeDNpDNne4OLKzrSrq5bj1RWWjn//rsiuh59VZVczyRcAvAygBvvvHPdp9myqnwuFApFO7AG4FcpGx/tImXVnwRQC+y2hPcSAO9lRY1CkXUoBuBYAJMnT65d67UahUKhSMIXpDzoNzlPQ7kPA70ZuIeB79pYHvmCgYsZyoFQoVBkmQULVuylws7cYfHi6JDKymV9vdaRj5jmin0rK1f23LNWmACuSumTH8uMwuzAwBAGfsbAPxn4hAGDgQ8Y+DsD53Ymx4VpWqWVlZUF7R+p6CiGsWyUKrnuDqZZfWC2bKllkTTw++OTfb6m073WkY/E4+ISTdO+57WOfIQ5caPfHz9oD5uZDGBMi9c2gP/dwzazCgGrCXiQgPMImEBAiIBjCLiagFkENHa0TSkx3ecbPMgNvQrtIVVy3R2k1P6eLVvKaSYNiHglkRqIuYO0hMB3XqvIT/hr27a37GEjqb4WFQB9vYdtdnmEwOfxuNbhQYmifZgRWbdutz4yik5CxAu91qBQKLo9fHzKcogEOOy1KoVCkft06ZmLG6bcUBQvjp8248kZFc3bbr788t61dtHJRNRUUFvwzv0V99fvbns6GMayUUREweCIr9x4H92ZSKQ6KCVvHDdu/xqvteQbkYg1QUr/0nHjhnV2Zii1ZPMbAOl7qisfMM3YD4Ae84PBIbVea8k3DCN2WjA4/N9EpIqXZRjTjE0OBktez4atLjvV/5PLfrJfvLjxTyC+oXnb1VdfXVAniz4CMAXACfGeja/tbnu6MIsjmcVRmdSvcBBCO0ktkCegAAAgAElEQVTTtDHtH6noKEJgit8f72RUB58Gp5poS+7aU035gpR8BXO8n9c68hO+QZVcdwcpkbUig1125kJI+iuI9namax38cf95II7NfHLmFACYdulUfdqPp5UijqNa2z7jHzOi6djSNLEokVAl191ASjnf58Mar3XkJ/S+lGJ1x89jAeCPKRvfBGh+JlRlGgYCAE4BcBSAQQC2AagC8AqAxQRkPL28EPx6fX1DLtdU6bIw0wuq5Lo7EMnnsmWryw4uZjw1c/LUi6dOIA33bt/IOAQgc8dr+pJ8ciyzaHU7gLQGF2VlJcoJxiXKy0s/8FpDvhIKlbzRyVN/BKBlZk8J4Ld7rijzMPB9ANMATAAwAE5YqQ1noHEigPsZeJOcAUfGCAZLn89ke4odhMMlj3itIV8JhUr/li1b+TX1xDyYwFbzSyJeBWBIm9vTJBKxJuh6TC2LuIBhRE+sqlqulkVcQNdjUyorlw3v2Fnsx66+Fs86hZByC3aKjV0HZ9ZiHwA9AWgA/AAGAhgH4GYAh2XatmlaV+p6VC2LuIBhWDcyc371TTmCaVpqWaQzMKEK4H2aX0tggGbjDSnga217y3MNI3oDQBcx02/C4ZJ3DcN6HECZpslTEwk+kAi/13Xry3A4cIpp1hzKLJ8E+L1QqPRXphm9gJl+AdADoVDJM7oeu4uIJzHzleFwqWEY1usAhgaDJYcvXLhqgM/X9DaAL0KhwMWGYR0L4G4ivBAMBu4xzdjPmPliIv5tMFj6tq5bjxAhLKU4vbx8+ErDsOYDvCUUKp20cKF1kKbhHwDmhkKBmwwjdi7ANzPzjHC49EnDsO4EcLIQdE1ZWclC04y9wsz7FhTUHmnbvYql5HeJ8FUwGLjINGuOZpb3A/xiKFT6P7puTSXCZcz4fTgceNMwYg8BfJimJc4cM+aA5YZhfQygIRQK/EDXl40k0p5n5v+Gw6U/N03rbGb8hggPBYOBx3Q9ejsRnQbIn4RCIz41DOslACV1ddrRgBxv2/aPDSO2MBQqOV/XrSOJ8CAzXg6HA9MNI3otQFcSiT8Eg8NfMwxrBoAjiDAlGAxEDSP6IRHJYDAwsaoqNkJKngXgk1Ao8FNdj/6QiH4L0N9DoZK/G4b1WwA/lBI/LS8PfGKa1ixmjCgo6Dmxvj4hfb6mD5kRDYcDU0wzOp6ZZgL0WihU8gfTtK5kxrUApodCgZcNI/p/AB1l29r5Y8fu941hWO8DKAiFAkdHItUlQoiXAPosFCq5zjRjk5n590T8WDBY+pBpRn/DTGcTiRuCweEfGYb1PICRiYT9g759ZUNtbcHHAJaHQoEzI5GacULIhwF+MxQq/b1hRC8DaCoR/U8wWPKiYVj3Afg+kbwoGBzxlWla7wIoDgYDRwqBE4TQ7jBN67/BYODqqirrZClxJ4AnQ6HADF2P3UzE5zLzTeFw6VzDsP7xt79tOuahh/rt13xdaBqkbeN2w7DCAB4hwtvBYOC3phm7mJl/RsT3BIOlL+i6dTcRjgXoklCoZLFhxN4G5IBQqPTwykprqM+H1wGYoVDgCqeWjLiLmZ8Jh0sfMAzrFwAuIKJfBYMl7xlG7AmAxxAlTikr23+dacY+I8KaYDBwalXV8jFS2k8A9C5CJZYs7nWcqN1W3MYtQWNNC3933iXP8rOP7VNVtWwgs+/fRPR5MFhyqWnGfsDM/wvg+VAocK+uR39ORD8C5C2h0IjZhmE9CiCUSGDyuHGBVYYR/RQQG0KhkpOkxJkA/VTXrdnhcOCXphk9n5luIqIHg8GSp03T+iMzTgJwVSgU0A0j+hpAwzZuLDli0KAVfeJxezaAL0OhwI91PTqRiO5hplnhcMmfDcOaBuBSIfC7srLAW4YR/RtAY4l8PwwG911hmtY8ALXBYOAE06w+kFk8S0QfBYMlN5hm7Bxm/jXAM0Oh0icMI3oHQKcyi+vC4eGfGYb1MoD9iovjR23eLAp9Pu09AEtDocAFhhH7HsAPEPFLwWDpn0wzeh0zXUFEdwSDJa/ruvVXIhwupTy7vHxEzDCsjwDEQ6HAcQsXLj9A0+wXAMwLhQI/MwzrTAC3EuHhYDDwqGHEbgP4dCKeFgyWztd1q4IIpYmE//tFRT4Rj9fNJUJ1MBg4F8CFuh67yDCsl0OhwB8NI3Y1wFcz8x/D4dJXDMP6C4AJQtC5ZWUl1aZpzWVmEQqVft80rVJmVBBhQTAYmGqaNaczy9sAfjQUKn1Y161biXAmM10fDpd8bBixFwA+oKEhfpyUhfGePe2PAMRCocDZul5zGJF8iJnfCIdLbzdN6wpmXEeEPwWDgZdMM3Y/Mx/NbF8QDu+/1DCs9wAUhkKBoxYt+mY/2/a9DFBlKFRyra5bpxLhDmY8EQ4HZhpG9NcAnSOEvLGsbMSHpmk9y4wDhaATNG1bbTxePI+IVgSDJT80TaucGX8H8FYoFPidrkcvJaJpAP05FCqZZRjWPQAm2jZ+PHZs4EvDiM4GqE8oFDgiEqkZJoR8jRl6OBy4SkpcYhjW+UT0dDBY8qBpWjcx43wAvwyFAnPS7mzznakXT50w7bKp85pfT7tk2lHTLp06BwCuu/C6/lMvnRqdevHUvdranq6dSKRmWCRSMyzz70Ch69GAyn7qDoaxbNT8+Uv7pH8G9wJ4TUr46QPuKdwzGJjJwLY0ipL9K9O2TbPm0KVLl3Y4s6eifZzOVGXodINIpGZctmx16S+w2edixhMzjwSAKVOmaIOLBz5LoBEMDCfGXX95auaDbW33Wr9CkVvwHQBua7FhG4ADAMpJh1sGngFwHtqfgZ1DwHFZkKRQKPKZaZdPG3bz5Zf3Tnd7e5hmbLJp1qj03y6g69FLnOlYRaYxDOvGhQutNNN/80CAt6Q89Kf6XuQUDPyNgbo0Zi46FHqeDrpuTTfNb1T6bxcwjNhDs2axSv/tArpuZc1ZNq98LpqZ8fiMlR3Z3h5Syr2ISDkYuQCRGMLMKv23O+xbUEDpFi67DUDLgfc6APdnXlJG+QKOzvacVr9wwXYpcw9VuMwVeNTAgV17Vj13oVFeK1C0YPHixX61vuoO0Wi0UFWXdId585YXpfcEyAGAG1Ie+H/qusA9hIGRDLzOQNNuZi2+YODkTNs2zdXFKqLBHZYsWdLh2WVFemTzs83LmQuFQtEhpmPnsuMWgKxVT9wDogDuA1AAJ99FUcr+xQDuAfBJlnUpFN0eNfJOg6amnhfW1hZc5LWOfGTzZnG9pu09yWsd+UjPnvb00aNrQrs/issAnJ+y8XcA5XzFTwIScAYONyT/HgfwbwCzANwC4FoALxOwKdO2pWx4xDRXDM10uwqgoaHwlTlzWD34ukB9fVFnE+t1GPUFpoEQtFVK5XPhDnITEdV5rSIfYcZ65nYHCf+DnR8yFgHIWorgPYWABgBfJv+yln0Q4LWaFk9kz163YpUque4ORNwpv0OFQqHoAHx0K24Kp3itSqFQKLoFKomWe6gkWu7RfhIt/jhlYPFh9tR1bVQSLfdQSbTcI5tJtNRUfxoQ2ZOEkCd5rSMfIRLnaVrTeK915CfatT17+ke2vo+nADgyZeOv3VbUURjox8BJDPwvA88z8BwD0xk4gYG20n67jpTyltraQjUodgFm3D13LlSeCxcg4nvbPyozKJ+LNGCmrwDlc+EO0tA0n1oHdAFm+qSpKbGulT29sWsOi1cBmrfrsd7BTv6KSwCcDWA/7MjDsRnAJAD/YuAxAtZmW5sQeF/KRG227XYT3lQl191BCH7daw0KhSJv4QdSlkMaAU4zk2f2YGAaA98yIFvJX5Fg4BsGrvdap0KhUHSKqqrlYxYtqi7zWkc+YprR8YsW1ezvtY58xDSt4xYvjg7ZeSuXARxP6aune6Nw9zDwTjtpveMMZC20riWmWXO6SvbkDk6FWZWgzA103bowW7bUF5gGtp0Ya9sia44w3QlmMTGRkKO91pGPMOM02xb7tNgi4IRrtlwOjQG4K7vK0qa9Ab0PznJJ1pFSnt/QUNyBirOKdGGmq+bOVX2TO9A12bKkfC7SgEjOIyLlvewCUtpvS8kbvdaRj0iJikSiINZi03UAjkg5bBpAueo70D+NY9KtnZJRhKDHgIKMJ+dSAADdr3wu3EEI3OO1BoVCkVfwEIA3pqwszPJa1e5gYGMaFU/dKEqmUCgU7mMY1ZNMM6pCUV3AMKLnmWZUhaK6gGFEr9X1ZclQVH4+pV/eAvA+u2/BWxhYkMbgYq4X2kzTukXlZ3EHXbfuViXX3cEwrPuyZUuta6UBMw1jJpVEyxVEQEpSN2lXoFGa5usD8AlovX7It16o6gBvA6jfzf51AD7OkpadkBKH+ny2SqLlAkQoVyXX3YGZxmbLlvK5SIOmpoLXNU2oH7sLFBTIp+rr5e46EEUnIfLd99xzvWoBPJuyqwrATA8kdZQKAIPhDIz6puxbB6dA2dPZFgUAQuDWeHxN1vNrdA/s6yZOhO21inxECPvqbNlSHaZCkdfwHQBua7FBAjgKoPkeCUobdkqplwD4HoAJyf8znFLrn8CZtbAIyvlPoVB0QUwzeoGuW6rkuguYZux6w6hWJddd4JFHVj1ExA0pbgozvNaVD+i69UhlpaVKrruArkdfVSXX3cEwLFVyXaFQ7BnTp+91EjNa+gWsBvBbr/Skws7M6QEAjoaT6rsHgI0AFgP4kICtHspTKBQKhUKxM/yjVoIrUp06PYMBjYETGZiVTONdl8y4uT4ZJXIXA8qJWqFQ5C9LlizprVL9uoOuR/tVVq70JBFS/sJDAF6TMrCY7bWqljAwhoGP26gbIhnYxMCfk34XOYdpfjNITd27Q2WlNVSVXHeHSKQmawN2FYqaBvX1Pc5uaCic4rWOfIRIXKNpTcd6rSN/YAEnOmRQi40NAH7ijZ42uRBOyffWOhEC0AfAjwEEsykqXaT0PdC//4rBXuvIR3w+PKNKrrsDET+fLVtqcJEGRLySiFVZcFeQlhD8ndcq8ojfAjguZdudAH3jhZjdMLmd/QSgH4CJ7kvpOELg80RCa/RaRz7CjMi6dWCvdeQjRLzQaw0KhaLLwccAnEhZZZgL5F62Qwa2pJF9s5EBFd2iUHRB1MxFGhjGslGmWX2g1zrykUikOlhZuWy41zq6PjwQwHPAjulkn483nnnmtmkA5WJCooY0j8vJBGumGfuBaa4u9lpHPmIYsdNUyXV3MM1YezOGGUN9gWnALI5kFkd5rSMfEUI7SdO0MV7r6NowAXgMO0dXyF//euOcO+7YkKspqvU0jrEBRNwW0hmk5CuY4/281pGf8A2q5Lo7SImbsmVLeTungaaJRYmEKrnuBlLK+T4f1nito4vzK+zqw/Cnc87ZNl9KsdoLQWnwNJzMm21FCtkAFgH4IGuKOoAQ/Hp9fYPKw+ECzPSCKrnuDkTyOa81KBSKLgGPB7gpxV3hE4BzMoSzGQb2YuCeZF6LVF+LBAOfMXCm1zoVCoXCNSIRa4Kux9SyiAsYRvTEqqrlalmkU3B/gKMpffMGgEsAQNdjU3LVn4UBYmAfBn7CwLMM/JeBSgbeYeA+Bk7J1RwXAGCa1pW6HlXLIi5gGNaNyufCHUzTUssiuQQRH0gEAY/KO+c3ImTbtg/OFLgibZgAPAEg0HIjgMsAigEAEU/w+33VAGqyrg4YBeBsACcBOAhOVdM6AEsBvAfgeQBfEvBXOH9dCilxHJHvLQCbvNaSh5w6dy4ehCpIl3GkpMkA7smGLTW4SANmbTarqGtXYJb/tO0e27zW0QW5AcAZKdvuAejVHS/th+vqZNZ9LhgYCOAqAJcA2Bs7EmX5ARwG4FA4x/wJwLJs68sEQoi7evZsUPlZXIAIv1Ql192BmX7htQaFQpGz8HiAG3PVz4KBKQwsbSeHxRZ2Bh8KhULRPTHN2GTTrDndax35iK5HLzGM2Pe81tF14JEAr0rpqzcCXJp6pGFYNy5caB2UdYXAQwxsTiNJ1sPZ1pYpdN2abprfDGr/SEVHMYzYQ7Nm5V7it3xA161HsmVLLYukgZRyLyJSDkYuQCSGMKv03+nBJQDeBzCk5UYAlwMUbeWEfQsKyIuicPug7RDTluzrthAXKWXukRMzRfkHjxo4sNWaM4o9hkZly5IaXKSB31/3nN/vVz92F+jbV/7f+vXr1fpqu/AQAP/Brh3y/wL0cmtn1NVpt65YsW+T69J2xQbSqg3RZb93IQqvKisbnJPZQ7s6hYUNPzz2WEp4rSMfKSqqPy1bttTTuEKR83A/AP8GcEDKjicB3JJ1Oe1TDSAdJ90u6cypUCjaRw0u0qCpqeeFtbUFF3mtIx/ZvFlcr2l7T/JaR+7CPQG8ASCcsuMlAFc66SJap2dPe/ro0TUhN9W1wWw44a+7m5lYCeC/2ZGTeaRseMQ0Vwz1Wkc+0tBQ+MqcOaxm1V2gvr7ojWzZUl9gGghBW6VUPhfuIDcRUZ3XKnIT9gP4F4DUBG6zAVzYXkEyZqxnpoyXBWegP5zU3Wcl/x0GZyARheMT8iacwU9PAKXY9T7zLZz03wsyrS178FpNi6upe3dYpUquuwMRr/Rag0Kh8BTWAH6xlSCL9wEu9FQZcE4ym6Zso0z6WwyczsDVDPyTgU8Z+IKBCAOvMXATA8MZymlPoVB0YyKRmmGRSM2w9o9UdBRdjwYqK1fu7bWO3IIFwM+2MrBYAHDvdFsxjGWj5s9f2ifj6oBZ7YSY1jEwI9N2cwnTrDl06dKluVpxtktjmlY5M6uBpwtEIjXjsmVLTfWnAZE9SQh5ktc68hEicZ6mNY33WkfuwAQnHfaFKTsWATgZoA5U4tSu7dnTPzJz2rbT3g2qCE4WzrxFSnlLbW2hGhS7ADPunjsXKs+FCxDxvdmypXwu0oCZvgKUz4U7SEPTfGodEEByVuIJODU5WrIMwIkAbehQa0yfNDUl1mVKXQuGtH8IBrhgN2cQAu9Lmaj1Wkee8qYque4OQvDrXmtQKBRZhQ8CeEkrqwzLAQ54ra4lyWWP9rJvVnmtU6FQKHKaqqrlYxYtqi7zWkc+YprR8YsW1ezvtQ5v4bMA3tJKH70a4NGdbdU0reMWL46mM8uwQ4kT2zqIgUsZmMPABgbqGfgyWQr9EAaiaQw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       "            return factory(Snap);\n",
       "        });\n",
       "    } else {\n",
       "        // Browser globals (glob is window)\n",
       "        // Snap adds itself to window\n",
       "        glob.Gadfly = factory(glob.Snap);\n",
       "    }\n",
       "}(this, function (Snap) {\n",
       "\n",
       "var Gadfly = {};\n",
       "\n",
       "// Get an x/y coordinate value in pixels\n",
       "var xPX = function(fig, x) {\n",
       "    var client_box = fig.node.getBoundingClientRect();\n",
       "    return x * fig.node.viewBox.baseVal.width / client_box.width;\n",
       "};\n",
       "\n",
       "var yPX = function(fig, y) {\n",
       "    var client_box = fig.node.getBoundingClientRect();\n",
       "    return y * fig.node.viewBox.baseVal.height / client_box.height;\n",
       "};\n",
       "\n",
       "\n",
       "Snap.plugin(function (Snap, Element, Paper, global) {\n",
       "    // Traverse upwards from a snap element to find and return the first\n",
       "    // note with the \"plotroot\" class.\n",
       "    Element.prototype.plotroot = function () {\n",
       "        var element = this;\n",
       "        while (!element.hasClass(\"plotroot\") && element.parent() != null) {\n",
       "            element = element.parent();\n",
       "        }\n",
       "        return element;\n",
       "    };\n",
       "\n",
       "    Element.prototype.svgroot = function () {\n",
       "        var element = this;\n",
       "        while (element.node.nodeName != \"svg\" && element.parent() != null) {\n",
       "            element = element.parent();\n",
       "        }\n",
       "        return element;\n",
       "    };\n",
       "\n",
       "    Element.prototype.plotbounds = function () {\n",
       "        var root = this.plotroot()\n",
       "        var bbox = root.select(\".guide.background\").node.getBBox();\n",
       "        return {\n",
       "            x0: bbox.x,\n",
       "            x1: bbox.x + bbox.width,\n",
       "            y0: bbox.y,\n",
       "            y1: bbox.y + bbox.height\n",
       "        };\n",
       "    };\n",
       "\n",
       "    Element.prototype.plotcenter = function () {\n",
       "        var root = this.plotroot()\n",
       "        var bbox = root.select(\".guide.background\").node.getBBox();\n",
       "        return {\n",
       "            x: bbox.x + bbox.width / 2,\n",
       "            y: bbox.y + bbox.height / 2\n",
       "        };\n",
       "    };\n",
       "\n",
       "    // Emulate IE style mouseenter/mouseleave events, since Microsoft always\n",
       "    // does everything right.\n",
       "    // See: http://www.dynamic-tools.net/toolbox/isMouseLeaveOrEnter/\n",
       "    var events = [\"mouseenter\", \"mouseleave\"];\n",
       "\n",
       "    for (i in events) {\n",
       "        (function (event_name) {\n",
       "            var event_name = events[i];\n",
       "            Element.prototype[event_name] = function (fn, scope) {\n",
       "                if (Snap.is(fn, \"function\")) {\n",
       "                    var fn2 = function (event) {\n",
       "                        if (event.type != \"mouseover\" && event.type != \"mouseout\") {\n",
       "                            return;\n",
       "                        }\n",
       "\n",
       "                        var reltg = event.relatedTarget ? event.relatedTarget :\n",
       "                            event.type == \"mouseout\" ? event.toElement : event.fromElement;\n",
       "                        while (reltg && reltg != this.node) reltg = reltg.parentNode;\n",
       "\n",
       "                        if (reltg != this.node) {\n",
       "                            return fn.apply(this, event);\n",
       "                        }\n",
       "                    };\n",
       "\n",
       "                    if (event_name == \"mouseenter\") {\n",
       "                        this.mouseover(fn2, scope);\n",
       "                    } else {\n",
       "                        this.mouseout(fn2, scope);\n",
       "                    }\n",
       "                }\n",
       "                return this;\n",
       "            };\n",
       "        })(events[i]);\n",
       "    }\n",
       "\n",
       "\n",
       "    Element.prototype.mousewheel = function (fn, scope) {\n",
       "        if (Snap.is(fn, \"function\")) {\n",
       "            var el = this;\n",
       "            var fn2 = function (event) {\n",
       "                fn.apply(el, [event]);\n",
       "            };\n",
       "        }\n",
       "\n",
       "        this.node.addEventListener(\n",
       "            /Firefox/i.test(navigator.userAgent) ? \"DOMMouseScroll\" : \"mousewheel\",\n",
       "            fn2);\n",
       "\n",
       "        return this;\n",
       "    };\n",
       "\n",
       "\n",
       "    // Snap's attr function can be too slow for things like panning/zooming.\n",
       "    // This is a function to directly update element attributes without going\n",
       "    // through eve.\n",
       "    Element.prototype.attribute = function(key, val) {\n",
       "        if (val === undefined) {\n",
       "            return this.node.getAttribute(key);\n",
       "        } else {\n",
       "            this.node.setAttribute(key, val);\n",
       "            return this;\n",
       "        }\n",
       "    };\n",
       "\n",
       "    Element.prototype.init_gadfly = function() {\n",
       "        this.mouseenter(Gadfly.plot_mouseover)\n",
       "            .mouseleave(Gadfly.plot_mouseout)\n",
       "            .dblclick(Gadfly.plot_dblclick)\n",
       "            .mousewheel(Gadfly.guide_background_scroll)\n",
       "            .drag(Gadfly.guide_background_drag_onmove,\n",
       "                  Gadfly.guide_background_drag_onstart,\n",
       "                  Gadfly.guide_background_drag_onend);\n",
       "        this.mouseenter(function (event) {\n",
       "            init_pan_zoom(this.plotroot());\n",
       "        });\n",
       "        return this;\n",
       "    };\n",
       "});\n",
       "\n",
       "\n",
       "// When the plot is moused over, emphasize the grid lines.\n",
       "Gadfly.plot_mouseover = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    var keyboard_zoom = function(event) {\n",
       "        if (event.which == 187) { // plus\n",
       "            increase_zoom_by_position(root, 0.1, true);\n",
       "        } else if (event.which == 189) { // minus\n",
       "            increase_zoom_by_position(root, -0.1, true);\n",
       "        }\n",
       "    };\n",
       "    root.data(\"keyboard_zoom\", keyboard_zoom);\n",
       "    window.addEventListener(\"keyup\", keyboard_zoom);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    xgridlines.data(\"unfocused_strokedash\",\n",
       "                    xgridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "    ygridlines.data(\"unfocused_strokedash\",\n",
       "                    ygridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "\n",
       "    // emphasize grid lines\n",
       "    var destcolor = root.data(\"focused_xgrid_color\");\n",
       "    xgridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"focused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // reveal zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 1.0}, 250);\n",
       "};\n",
       "\n",
       "// Reset pan and zoom on double click\n",
       "Gadfly.plot_dblclick = function(event) {\n",
       "  set_plot_pan_zoom(this.plotroot(), 0.0, 0.0, 1.0);\n",
       "};\n",
       "\n",
       "// Unemphasize grid lines on mouse out.\n",
       "Gadfly.plot_mouseout = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    window.removeEventListener(\"keyup\", root.data(\"keyboard_zoom\"));\n",
       "    root.data(\"keyboard_zoom\", undefined);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    var destcolor = root.data(\"unfocused_xgrid_color\");\n",
       "\n",
       "    xgridlines.attribute(\"stroke-dasharray\", xgridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"unfocused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", ygridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // hide zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 0.0}, 250);\n",
       "};\n",
       "\n",
       "\n",
       "var set_geometry_transform = function(root, tx, ty, scale) {\n",
       "    var xscalable = root.hasClass(\"xscalable\"),\n",
       "        yscalable = root.hasClass(\"yscalable\");\n",
       "\n",
       "    var old_scale = root.data(\"scale\");\n",
       "\n",
       "    var xscale = xscalable ? scale : 1.0,\n",
       "        yscale = yscalable ? scale : 1.0;\n",
       "\n",
       "    tx = xscalable ? tx : 0.0;\n",
       "    ty = yscalable ? ty : 0.0;\n",
       "\n",
       "    var t = new Snap.Matrix().translate(tx, ty).scale(xscale, yscale);\n",
       "\n",
       "    root.selectAll(\".geometry, image\")\n",
       "        .forEach(function (element, i) {\n",
       "            element.transform(t);\n",
       "        });\n",
       "\n",
       "    bounds = root.plotbounds();\n",
       "\n",
       "    if (yscalable) {\n",
       "        var xfixed_t = new Snap.Matrix().translate(0, ty).scale(1.0, yscale);\n",
       "        root.selectAll(\".xfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(xfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".ylabels\")\n",
       "            .transform(xfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1, 1/scale, cx, cy).add(st);\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var y = cy * scale + ty;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.y0 <= y && y <= bounds.y1 ? \"visible\" : \"hidden\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (xscalable) {\n",
       "        var yfixed_t = new Snap.Matrix().translate(tx, 0).scale(xscale, 1.0);\n",
       "        var xtrans = new Snap.Matrix().translate(tx, 0);\n",
       "        root.selectAll(\".yfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(yfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".xlabels\")\n",
       "            .transform(yfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1/scale, 1, cx, cy).add(st);\n",
       "\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var x = cx * scale + tx;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.x0 <= x && x <= bounds.x1 ? \"visible\" : \"hidden\");\n",
       "                    }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // we must unscale anything that is scale invariance: widths, raiduses, etc.\n",
       "    var size_attribs = [\"font-size\"];\n",
       "    var unscaled_selection = \".geometry, .geometry *\";\n",
       "    if (xscalable) {\n",
       "        size_attribs.push(\"rx\");\n",
       "        unscaled_selection += \", .xgridlines\";\n",
       "    }\n",
       "    if (yscalable) {\n",
       "        size_attribs.push(\"ry\");\n",
       "        unscaled_selection += \", .ygridlines\";\n",
       "    }\n",
       "\n",
       "    root.selectAll(unscaled_selection)\n",
       "        .forEach(function (element, i) {\n",
       "            // circle need special help\n",
       "            if (element.node.nodeName == \"circle\") {\n",
       "                var cx = element.attribute(\"cx\"),\n",
       "                    cy = element.attribute(\"cy\");\n",
       "                unscale_t = new Snap.Matrix().scale(1/xscale, 1/yscale,\n",
       "                                                        cx, cy);\n",
       "                element.transform(unscale_t);\n",
       "                return;\n",
       "            }\n",
       "\n",
       "            for (i in size_attribs) {\n",
       "                var key = size_attribs[i];\n",
       "                var val = parseFloat(element.attribute(key));\n",
       "                if (val !== undefined && val != 0 && !isNaN(val)) {\n",
       "                    element.attribute(key, val * old_scale / scale);\n",
       "                }\n",
       "            }\n",
       "        });\n",
       "};\n",
       "\n",
       "\n",
       "// Find the most appropriate tick scale and update label visibility.\n",
       "var update_tickscale = function(root, scale, axis) {\n",
       "    if (!root.hasClass(axis + \"scalable\")) return;\n",
       "\n",
       "    var tickscales = root.data(axis + \"tickscales\");\n",
       "    var best_tickscale = 1.0;\n",
       "    var best_tickscale_dist = Infinity;\n",
       "    for (tickscale in tickscales) {\n",
       "        var dist = Math.abs(Math.log(tickscale) - Math.log(scale));\n",
       "        if (dist < best_tickscale_dist) {\n",
       "            best_tickscale_dist = dist;\n",
       "            best_tickscale = tickscale;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    if (best_tickscale != root.data(axis + \"tickscale\")) {\n",
       "        root.data(axis + \"tickscale\", best_tickscale);\n",
       "        var mark_inscale_gridlines = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        var mark_inscale_labels = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        root.select(\".\" + axis + \"gridlines\").selectAll(\"path\").forEach(mark_inscale_gridlines);\n",
       "        root.select(\".\" + axis + \"labels\").selectAll(\"text\").forEach(mark_inscale_labels);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "var set_plot_pan_zoom = function(root, tx, ty, scale) {\n",
       "    var old_scale = root.data(\"scale\");\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    // compute the viewport derived from tx, ty, and scale\n",
       "    var x_min = -width * scale - (scale * width - width),\n",
       "        x_max = width * scale,\n",
       "        y_min = -height * scale - (scale * height - height),\n",
       "        y_max = height * scale;\n",
       "\n",
       "    var x0 = bounds.x0 - scale * bounds.x0,\n",
       "        y0 = bounds.y0 - scale * bounds.y0;\n",
       "\n",
       "    var tx = Math.max(Math.min(tx - x0, x_max), x_min),\n",
       "        ty = Math.max(Math.min(ty - y0, y_max), y_min);\n",
       "\n",
       "    tx += x0;\n",
       "    ty += y0;\n",
       "\n",
       "    // when the scale change, we may need to alter which set of\n",
       "    // ticks is being displayed\n",
       "    if (scale != old_scale) {\n",
       "        update_tickscale(root, scale, \"x\");\n",
       "        update_tickscale(root, scale, \"y\");\n",
       "    }\n",
       "\n",
       "    set_geometry_transform(root, tx, ty, scale);\n",
       "\n",
       "    root.data(\"scale\", scale);\n",
       "    root.data(\"tx\", tx);\n",
       "    root.data(\"ty\", ty);\n",
       "};\n",
       "\n",
       "\n",
       "var scale_centered_translation = function(root, scale) {\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    var tx0 = root.data(\"tx\"),\n",
       "        ty0 = root.data(\"ty\");\n",
       "\n",
       "    var scale0 = root.data(\"scale\");\n",
       "\n",
       "    // how off from center the current view is\n",
       "    var xoff = tx0 - (bounds.x0 * (1 - scale0) + (width * (1 - scale0)) / 2),\n",
       "        yoff = ty0 - (bounds.y0 * (1 - scale0) + (height * (1 - scale0)) / 2);\n",
       "\n",
       "    // rescale offsets\n",
       "    xoff = xoff * scale / scale0;\n",
       "    yoff = yoff * scale / scale0;\n",
       "\n",
       "    // adjust for the panel position being scaled\n",
       "    var x_edge_adjust = bounds.x0 * (1 - scale),\n",
       "        y_edge_adjust = bounds.y0 * (1 - scale);\n",
       "\n",
       "    return {\n",
       "        x: xoff + x_edge_adjust + (width - width * scale) / 2,\n",
       "        y: yoff + y_edge_adjust + (height - height * scale) / 2\n",
       "    };\n",
       "};\n",
       "\n",
       "\n",
       "// Initialize data for panning zooming if it isn't already.\n",
       "var init_pan_zoom = function(root) {\n",
       "    if (root.data(\"zoompan-ready\")) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    // The non-scaling-stroke trick. Rather than try to correct for the\n",
       "    // stroke-width when zooming, we force it to a fixed value.\n",
       "    var px_per_mm = root.node.getCTM().a;\n",
       "\n",
       "    // Drag events report deltas in pixels, which we'd like to convert to\n",
       "    // millimeters.\n",
       "    root.data(\"px_per_mm\", px_per_mm);\n",
       "\n",
       "    root.selectAll(\"path\")\n",
       "        .forEach(function (element, i) {\n",
       "        sw = element.asPX(\"stroke-width\") * px_per_mm;\n",
       "        if (sw > 0) {\n",
       "            element.attribute(\"stroke-width\", sw);\n",
       "            element.attribute(\"vector-effect\", \"non-scaling-stroke\");\n",
       "        }\n",
       "    });\n",
       "\n",
       "    // Store ticks labels original tranformation\n",
       "    root.selectAll(\".xlabels > text, .ylabels > text\")\n",
       "        .forEach(function (element, i) {\n",
       "            var lm = element.transform().localMatrix;\n",
       "            element.data(\"static_transform\",\n",
       "                new Snap.Matrix(lm.a, lm.b, lm.c, lm.d, lm.e, lm.f));\n",
       "        });\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\");\n",
       "    var ygridlines = root.select(\".ygridlines\");\n",
       "    var xlabels = root.select(\".xlabels\");\n",
       "    var ylabels = root.select(\".ylabels\");\n",
       "\n",
       "    if (root.data(\"tx\") === undefined) root.data(\"tx\", 0);\n",
       "    if (root.data(\"ty\") === undefined) root.data(\"ty\", 0);\n",
       "    if (root.data(\"scale\") === undefined) root.data(\"scale\", 1.0);\n",
       "    if (root.data(\"xtickscales\") === undefined) {\n",
       "\n",
       "        // index all the tick scales that are listed\n",
       "        var xtickscales = {};\n",
       "        var ytickscales = {};\n",
       "        var add_x_tick_scales = function (element, i) {\n",
       "            xtickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "        var add_y_tick_scales = function (element, i) {\n",
       "            ytickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "\n",
       "        if (xgridlines) xgridlines.selectAll(\"path\").forEach(add_x_tick_scales);\n",
       "        if (ygridlines) ygridlines.selectAll(\"path\").forEach(add_y_tick_scales);\n",
       "        if (xlabels) xlabels.selectAll(\"text\").forEach(add_x_tick_scales);\n",
       "        if (ylabels) ylabels.selectAll(\"text\").forEach(add_y_tick_scales);\n",
       "\n",
       "        root.data(\"xtickscales\", xtickscales);\n",
       "        root.data(\"ytickscales\", ytickscales);\n",
       "        root.data(\"xtickscale\", 1.0);\n",
       "    }\n",
       "\n",
       "    var min_scale = 1.0, max_scale = 1.0;\n",
       "    for (scale in xtickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    for (scale in ytickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    root.data(\"min_scale\", min_scale);\n",
       "    root.data(\"max_scale\", max_scale);\n",
       "\n",
       "    // store the original positions of labels\n",
       "    if (xlabels) {\n",
       "        xlabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"x\", element.asPX(\"x\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    if (ylabels) {\n",
       "        ylabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"y\", element.asPX(\"y\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    // mark grid lines and ticks as in or out of scale.\n",
       "    var mark_inscale = function (element, i) {\n",
       "        element.attribute(\"gadfly:inscale\", element.attribute(\"gadfly:scale\") == 1.0);\n",
       "    };\n",
       "\n",
       "    if (xgridlines) xgridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (ygridlines) ygridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (xlabels) xlabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "    if (ylabels) ylabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "\n",
       "    // figure out the upper ond lower bounds on panning using the maximum\n",
       "    // and minum grid lines\n",
       "    var bounds = root.plotbounds();\n",
       "    var pan_bounds = {\n",
       "        x0: 0.0,\n",
       "        y0: 0.0,\n",
       "        x1: 0.0,\n",
       "        y1: 0.0\n",
       "    };\n",
       "\n",
       "    if (xgridlines) {\n",
       "        xgridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.x1 - bbox.x < pan_bounds.x0) {\n",
       "                        pan_bounds.x0 = bounds.x1 - bbox.x;\n",
       "                    }\n",
       "                    if (bounds.x0 - bbox.x > pan_bounds.x1) {\n",
       "                        pan_bounds.x1 = bounds.x0 - bbox.x;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (ygridlines) {\n",
       "        ygridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.y1 - bbox.y < pan_bounds.y0) {\n",
       "                        pan_bounds.y0 = bounds.y1 - bbox.y;\n",
       "                    }\n",
       "                    if (bounds.y0 - bbox.y > pan_bounds.y1) {\n",
       "                        pan_bounds.y1 = bounds.y0 - bbox.y;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // nudge these values a little\n",
       "    pan_bounds.x0 -= 5;\n",
       "    pan_bounds.x1 += 5;\n",
       "    pan_bounds.y0 -= 5;\n",
       "    pan_bounds.y1 += 5;\n",
       "    root.data(\"pan_bounds\", pan_bounds);\n",
       "\n",
       "    root.data(\"zoompan-ready\", true)\n",
       "};\n",
       "\n",
       "\n",
       "// drag actions, i.e. zooming and panning\n",
       "var pan_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        root.data(\"dx\", 0);\n",
       "        root.data(\"dy\", 0);\n",
       "        root.data(\"tx0\", root.data(\"tx\"));\n",
       "        root.data(\"ty0\", root.data(\"ty\"));\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        dx /= px_per_mm;\n",
       "        dy /= px_per_mm;\n",
       "\n",
       "        var tx0 = root.data(\"tx\"),\n",
       "            ty0 = root.data(\"ty\");\n",
       "\n",
       "        var dx0 = root.data(\"dx\"),\n",
       "            dy0 = root.data(\"dy\");\n",
       "\n",
       "        root.data(\"dx\", dx);\n",
       "        root.data(\"dy\", dy);\n",
       "\n",
       "        dx = dx - dx0;\n",
       "        dy = dy - dy0;\n",
       "\n",
       "        var tx = tx0 + dx,\n",
       "            ty = ty0 + dy;\n",
       "\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\"));\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        set_plot_pan_zoom(root, root.data(\"tx0\"), root.data(\"ty0\"), root.data(\"scale\"));\n",
       "    }\n",
       "};\n",
       "\n",
       "var zoom_box;\n",
       "var zoom_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        var bounds = root.plotbounds();\n",
       "        var width = bounds.x1 - bounds.x0,\n",
       "            height = bounds.y1 - bounds.y0;\n",
       "        var ratio = width / height;\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        x = xscalable ? x / px_per_mm : bounds.x0;\n",
       "        y = yscalable ? y / px_per_mm : bounds.y0;\n",
       "        var w = xscalable ? 0 : width;\n",
       "        var h = yscalable ? 0 : height;\n",
       "        zoom_box = root.rect(x, y, w, h).attr({\n",
       "            \"fill\": \"#000\",\n",
       "            \"opacity\": 0.25\n",
       "        });\n",
       "        zoom_box.data(\"ratio\", ratio);\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        var bounds = root.plotbounds();\n",
       "        if (yscalable) {\n",
       "            y /= px_per_mm;\n",
       "            y = Math.max(bounds.y0, y);\n",
       "            y = Math.min(bounds.y1, y);\n",
       "        } else {\n",
       "            y = bounds.y1;\n",
       "        }\n",
       "        if (xscalable) {\n",
       "            x /= px_per_mm;\n",
       "            x = Math.max(bounds.x0, x);\n",
       "            x = Math.min(bounds.x1, x);\n",
       "        } else {\n",
       "            x = bounds.x1;\n",
       "        }\n",
       "\n",
       "        dx = x - zoom_box.attr(\"x\");\n",
       "        dy = y - zoom_box.attr(\"y\");\n",
       "        if (xscalable && yscalable) {\n",
       "            var ratio = zoom_box.data(\"ratio\");\n",
       "            var width = Math.min(Math.abs(dx), ratio * Math.abs(dy));\n",
       "            var height = Math.min(Math.abs(dy), Math.abs(dx) / ratio);\n",
       "            dx = width * dx / Math.abs(dx);\n",
       "            dy = height * dy / Math.abs(dy);\n",
       "        }\n",
       "        var xoffset = 0,\n",
       "            yoffset = 0;\n",
       "        if (dx < 0) {\n",
       "            xoffset = dx;\n",
       "            dx = -1 * dx;\n",
       "        }\n",
       "        if (dy < 0) {\n",
       "            yoffset = dy;\n",
       "            dy = -1 * dy;\n",
       "        }\n",
       "        if (isNaN(dy)) {\n",
       "            dy = 0.0;\n",
       "        }\n",
       "        if (isNaN(dx)) {\n",
       "            dx = 0.0;\n",
       "        }\n",
       "        zoom_box.transform(\"T\" + xoffset + \",\" + yoffset);\n",
       "        zoom_box.attr(\"width\", dx);\n",
       "        zoom_box.attr(\"height\", dy);\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var zoom_bounds = zoom_box.getBBox();\n",
       "        if (zoom_bounds.width * zoom_bounds.height <= 0) {\n",
       "            return;\n",
       "        }\n",
       "        var plot_bounds = root.plotbounds();\n",
       "        var zoom_factor = 1.0;\n",
       "        if (yscalable) {\n",
       "            zoom_factor = (plot_bounds.y1 - plot_bounds.y0) / zoom_bounds.height;\n",
       "        } else {\n",
       "            zoom_factor = (plot_bounds.x1 - plot_bounds.x0) / zoom_bounds.width;\n",
       "        }\n",
       "        var tx = (root.data(\"tx\") - zoom_bounds.x) * zoom_factor + plot_bounds.x0,\n",
       "            ty = (root.data(\"ty\") - zoom_bounds.y) * zoom_factor + plot_bounds.y0;\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\") * zoom_factor);\n",
       "        zoom_box.remove();\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        zoom_box.remove();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onstart = function(x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var scalable = root.hasClass(\"xscalable\") || root.hasClass(\"yscalable\");\n",
       "    var zoomable = !event.altKey && !event.ctrlKey && event.shiftKey && scalable;\n",
       "    var panable = !event.altKey && !event.ctrlKey && !event.shiftKey && scalable;\n",
       "    var drag_action = zoomable ? zoom_action :\n",
       "                      panable  ? pan_action :\n",
       "                                 undefined;\n",
       "    root.data(\"drag_action\", drag_action);\n",
       "    if (drag_action) {\n",
       "        var cancel_drag_action = function(event) {\n",
       "            if (event.which == 27) { // esc key\n",
       "                drag_action.cancel(root);\n",
       "                root.data(\"drag_action\", undefined);\n",
       "            }\n",
       "        };\n",
       "        window.addEventListener(\"keyup\", cancel_drag_action);\n",
       "        root.data(\"cancel_drag_action\", cancel_drag_action);\n",
       "        drag_action.start(root, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.update(root, dx, dy, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onend = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    window.removeEventListener(\"keyup\", root.data(\"cancel_drag_action\"));\n",
       "    root.data(\"cancel_drag_action\", undefined);\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.end(root, event);\n",
       "    }\n",
       "    root.data(\"drag_action\", undefined);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_scroll = function(event) {\n",
       "    if (event.shiftKey) {\n",
       "        increase_zoom_by_position(this.plotroot(), 0.001 * event.wheelDelta);\n",
       "        event.preventDefault();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseover = function(event) {\n",
       "    this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseout = function(event) {\n",
       "     this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomout_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), -0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomin_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), 0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_track_click = function(event) {\n",
       "    // TODO\n",
       "};\n",
       "\n",
       "\n",
       "// Map slider position x to scale y using the function y = a*exp(b*x)+c.\n",
       "// The constants a, b, and c are solved using the constraint that the function\n",
       "// should go through the points (0; min_scale), (0.5; 1), and (1; max_scale).\n",
       "var scale_from_slider_position = function(position, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return a * Math.exp(b * position) + c;\n",
       "}\n",
       "\n",
       "// inverse of scale_from_slider_position\n",
       "var slider_position_from_scale = function(scale, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return 1 / b * Math.log((scale - c) / a);\n",
       "}\n",
       "\n",
       "var increase_zoom_by_position = function(root, delta_position, animate) {\n",
       "    var scale = root.data(\"scale\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\");\n",
       "    var position = slider_position_from_scale(scale, min_scale, max_scale);\n",
       "    position += delta_position;\n",
       "    scale = scale_from_slider_position(position, min_scale, max_scale);\n",
       "    set_zoom(root, scale, animate);\n",
       "}\n",
       "\n",
       "var set_zoom = function(root, scale, animate) {\n",
       "    var min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"scale\");\n",
       "    var new_scale = Math.max(min_scale, Math.min(scale, max_scale));\n",
       "    if (animate) {\n",
       "        Snap.animate(\n",
       "            old_scale,\n",
       "            new_scale,\n",
       "            function (new_scale) {\n",
       "                update_plot_scale(root, new_scale);\n",
       "            },\n",
       "            200);\n",
       "    } else {\n",
       "        update_plot_scale(root, new_scale);\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "var update_plot_scale = function(root, new_scale) {\n",
       "    var trans = scale_centered_translation(root, new_scale);\n",
       "    set_plot_pan_zoom(root, trans.x, trans.y, new_scale);\n",
       "\n",
       "    root.selectAll(\".zoomslider_thumb\")\n",
       "        .forEach(function (element, i) {\n",
       "            var min_pos = element.data(\"min_pos\"),\n",
       "                max_pos = element.data(\"max_pos\"),\n",
       "                min_scale = root.data(\"min_scale\"),\n",
       "                max_scale = root.data(\"max_scale\");\n",
       "            var xmid = (min_pos + max_pos) / 2;\n",
       "            var xpos = slider_position_from_scale(new_scale, min_scale, max_scale);\n",
       "            element.transform(new Snap.Matrix().translate(\n",
       "                Math.max(min_pos, Math.min(\n",
       "                         max_pos, min_pos + (max_pos - min_pos) * xpos)) - xmid, 0));\n",
       "    });\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var min_pos = this.data(\"min_pos\"),\n",
       "        max_pos = this.data(\"max_pos\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"old_scale\");\n",
       "\n",
       "    var px_per_mm = root.data(\"px_per_mm\");\n",
       "    dx /= px_per_mm;\n",
       "    dy /= px_per_mm;\n",
       "\n",
       "    var xmid = (min_pos + max_pos) / 2;\n",
       "    var xpos = slider_position_from_scale(old_scale, min_scale, max_scale) +\n",
       "                   dx / (max_pos - min_pos);\n",
       "\n",
       "    // compute the new scale\n",
       "    var new_scale = scale_from_slider_position(xpos, min_scale, max_scale);\n",
       "    new_scale = Math.min(max_scale, Math.max(min_scale, new_scale));\n",
       "\n",
       "    update_plot_scale(root, new_scale);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragstart = function(x, y, event) {\n",
       "    this.animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    // keep track of what the scale was when we started dragging\n",
       "    root.data(\"old_scale\", root.data(\"scale\"));\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragend = function(event) {\n",
       "    this.animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "var toggle_color_class = function(root, color_class, ison) {\n",
       "    var guides = root.selectAll(\".guide.\" + color_class + \",.guide .\" + color_class);\n",
       "    var geoms = root.selectAll(\".geometry.\" + color_class + \",.geometry .\" + color_class);\n",
       "    if (ison) {\n",
       "        guides.animate({opacity: 0.5}, 250);\n",
       "        geoms.animate({opacity: 0.0}, 250);\n",
       "    } else {\n",
       "        guides.animate({opacity: 1.0}, 250);\n",
       "        geoms.animate({opacity: 1.0}, 250);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.colorkey_swatch_click = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    var color_class = this.data(\"color_class\");\n",
       "\n",
       "    if (event.shiftKey) {\n",
       "        root.selectAll(\".colorkey text\")\n",
       "            .forEach(function (element) {\n",
       "                var other_color_class = element.data(\"color_class\");\n",
       "                if (other_color_class != color_class) {\n",
       "                    toggle_color_class(root, other_color_class,\n",
       "                                       element.attr(\"opacity\") == 1.0);\n",
       "                }\n",
       "            });\n",
       "    } else {\n",
       "        toggle_color_class(root, color_class, this.attr(\"opacity\") == 1.0);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "return Gadfly;\n",
       "\n",
       "}));\n",
       "\n",
       "\n",
       "//@ sourceURL=gadfly.js\n",
       "\n",
       "(function (glob, factory) {\n",
       "    // AMD support\n",
       "      if (typeof require === \"function\" && typeof define === \"function\" && define.amd) {\n",
       "        require([\"Snap.svg\", \"Gadfly\"], function (Snap, Gadfly) {\n",
       "            factory(Snap, Gadfly);\n",
       "        });\n",
       "      } else {\n",
       "          factory(glob.Snap, glob.Gadfly);\n",
       "      }\n",
       "})(window, function (Snap, Gadfly) {\n",
       "    var fig = Snap(\"#img-154ee1e6\");\n",
       "fig.select(\"#img-154ee1e6-5\")\n",
       "   .init_gadfly();\n",
       "fig.select(\"#img-154ee1e6-7\")\n",
       "   .plotroot().data(\"unfocused_ygrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-154ee1e6-7\")\n",
       "   .plotroot().data(\"focused_ygrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-154ee1e6-8\")\n",
       "   .plotroot().data(\"unfocused_xgrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-154ee1e6-8\")\n",
       "   .plotroot().data(\"focused_xgrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-154ee1e6-15\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-154ee1e6-15\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-154ee1e6-15\")\n",
       "   .click(Gadfly.zoomslider_zoomin_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "fig.select(\"#img-154ee1e6-17\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-154ee1e6-17\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-154ee1e6-17\")\n",
       "   .click(Gadfly.zoomslider_track_click);\n",
       "fig.select(\"#img-154ee1e6-18\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-154ee1e6-18\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-154ee1e6-18\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-154ee1e6-18\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-154ee1e6-18\")\n",
       "   .drag(Gadfly.zoomslider_thumb_dragmove,\n",
       "     Gadfly.zoomslider_thumb_dragstart,\n",
       "     Gadfly.zoomslider_thumb_dragend)\n",
       ";\n",
       "fig.select(\"#img-154ee1e6-19\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-154ee1e6-19\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-154ee1e6-19\")\n",
       "   .click(Gadfly.zoomslider_zoomout_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "    });\n",
       "]]> </script>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "Plot(...)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Mads.plotmatches(md, r\"w20\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calibration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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       "                        this.mouseover(fn2, scope);\n",
       "                    } else {\n",
       "                        this.mouseout(fn2, scope);\n",
       "                    }\n",
       "                }\n",
       "                return this;\n",
       "            };\n",
       "        })(events[i]);\n",
       "    }\n",
       "\n",
       "\n",
       "    Element.prototype.mousewheel = function (fn, scope) {\n",
       "        if (Snap.is(fn, \"function\")) {\n",
       "            var el = this;\n",
       "            var fn2 = function (event) {\n",
       "                fn.apply(el, [event]);\n",
       "            };\n",
       "        }\n",
       "\n",
       "        this.node.addEventListener(\n",
       "            /Firefox/i.test(navigator.userAgent) ? \"DOMMouseScroll\" : \"mousewheel\",\n",
       "            fn2);\n",
       "\n",
       "        return this;\n",
       "    };\n",
       "\n",
       "\n",
       "    // Snap's attr function can be too slow for things like panning/zooming.\n",
       "    // This is a function to directly update element attributes without going\n",
       "    // through eve.\n",
       "    Element.prototype.attribute = function(key, val) {\n",
       "        if (val === undefined) {\n",
       "            return this.node.getAttribute(key);\n",
       "        } else {\n",
       "            this.node.setAttribute(key, val);\n",
       "            return this;\n",
       "        }\n",
       "    };\n",
       "\n",
       "    Element.prototype.init_gadfly = function() {\n",
       "        this.mouseenter(Gadfly.plot_mouseover)\n",
       "            .mouseleave(Gadfly.plot_mouseout)\n",
       "            .dblclick(Gadfly.plot_dblclick)\n",
       "            .mousewheel(Gadfly.guide_background_scroll)\n",
       "            .drag(Gadfly.guide_background_drag_onmove,\n",
       "                  Gadfly.guide_background_drag_onstart,\n",
       "                  Gadfly.guide_background_drag_onend);\n",
       "        this.mouseenter(function (event) {\n",
       "            init_pan_zoom(this.plotroot());\n",
       "        });\n",
       "        return this;\n",
       "    };\n",
       "});\n",
       "\n",
       "\n",
       "// When the plot is moused over, emphasize the grid lines.\n",
       "Gadfly.plot_mouseover = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    var keyboard_zoom = function(event) {\n",
       "        if (event.which == 187) { // plus\n",
       "            increase_zoom_by_position(root, 0.1, true);\n",
       "        } else if (event.which == 189) { // minus\n",
       "            increase_zoom_by_position(root, -0.1, true);\n",
       "        }\n",
       "    };\n",
       "    root.data(\"keyboard_zoom\", keyboard_zoom);\n",
       "    window.addEventListener(\"keyup\", keyboard_zoom);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    xgridlines.data(\"unfocused_strokedash\",\n",
       "                    xgridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "    ygridlines.data(\"unfocused_strokedash\",\n",
       "                    ygridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "\n",
       "    // emphasize grid lines\n",
       "    var destcolor = root.data(\"focused_xgrid_color\");\n",
       "    xgridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"focused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // reveal zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 1.0}, 250);\n",
       "};\n",
       "\n",
       "// Reset pan and zoom on double click\n",
       "Gadfly.plot_dblclick = function(event) {\n",
       "  set_plot_pan_zoom(this.plotroot(), 0.0, 0.0, 1.0);\n",
       "};\n",
       "\n",
       "// Unemphasize grid lines on mouse out.\n",
       "Gadfly.plot_mouseout = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    window.removeEventListener(\"keyup\", root.data(\"keyboard_zoom\"));\n",
       "    root.data(\"keyboard_zoom\", undefined);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    var destcolor = root.data(\"unfocused_xgrid_color\");\n",
       "\n",
       "    xgridlines.attribute(\"stroke-dasharray\", xgridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"unfocused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", ygridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // hide zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 0.0}, 250);\n",
       "};\n",
       "\n",
       "\n",
       "var set_geometry_transform = function(root, tx, ty, scale) {\n",
       "    var xscalable = root.hasClass(\"xscalable\"),\n",
       "        yscalable = root.hasClass(\"yscalable\");\n",
       "\n",
       "    var old_scale = root.data(\"scale\");\n",
       "\n",
       "    var xscale = xscalable ? scale : 1.0,\n",
       "        yscale = yscalable ? scale : 1.0;\n",
       "\n",
       "    tx = xscalable ? tx : 0.0;\n",
       "    ty = yscalable ? ty : 0.0;\n",
       "\n",
       "    var t = new Snap.Matrix().translate(tx, ty).scale(xscale, yscale);\n",
       "\n",
       "    root.selectAll(\".geometry, image\")\n",
       "        .forEach(function (element, i) {\n",
       "            element.transform(t);\n",
       "        });\n",
       "\n",
       "    bounds = root.plotbounds();\n",
       "\n",
       "    if (yscalable) {\n",
       "        var xfixed_t = new Snap.Matrix().translate(0, ty).scale(1.0, yscale);\n",
       "        root.selectAll(\".xfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(xfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".ylabels\")\n",
       "            .transform(xfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1, 1/scale, cx, cy).add(st);\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var y = cy * scale + ty;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.y0 <= y && y <= bounds.y1 ? \"visible\" : \"hidden\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (xscalable) {\n",
       "        var yfixed_t = new Snap.Matrix().translate(tx, 0).scale(xscale, 1.0);\n",
       "        var xtrans = new Snap.Matrix().translate(tx, 0);\n",
       "        root.selectAll(\".yfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(yfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".xlabels\")\n",
       "            .transform(yfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1/scale, 1, cx, cy).add(st);\n",
       "\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var x = cx * scale + tx;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.x0 <= x && x <= bounds.x1 ? \"visible\" : \"hidden\");\n",
       "                    }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // we must unscale anything that is scale invariance: widths, raiduses, etc.\n",
       "    var size_attribs = [\"font-size\"];\n",
       "    var unscaled_selection = \".geometry, .geometry *\";\n",
       "    if (xscalable) {\n",
       "        size_attribs.push(\"rx\");\n",
       "        unscaled_selection += \", .xgridlines\";\n",
       "    }\n",
       "    if (yscalable) {\n",
       "        size_attribs.push(\"ry\");\n",
       "        unscaled_selection += \", .ygridlines\";\n",
       "    }\n",
       "\n",
       "    root.selectAll(unscaled_selection)\n",
       "        .forEach(function (element, i) {\n",
       "            // circle need special help\n",
       "            if (element.node.nodeName == \"circle\") {\n",
       "                var cx = element.attribute(\"cx\"),\n",
       "                    cy = element.attribute(\"cy\");\n",
       "                unscale_t = new Snap.Matrix().scale(1/xscale, 1/yscale,\n",
       "                                                        cx, cy);\n",
       "                element.transform(unscale_t);\n",
       "                return;\n",
       "            }\n",
       "\n",
       "            for (i in size_attribs) {\n",
       "                var key = size_attribs[i];\n",
       "                var val = parseFloat(element.attribute(key));\n",
       "                if (val !== undefined && val != 0 && !isNaN(val)) {\n",
       "                    element.attribute(key, val * old_scale / scale);\n",
       "                }\n",
       "            }\n",
       "        });\n",
       "};\n",
       "\n",
       "\n",
       "// Find the most appropriate tick scale and update label visibility.\n",
       "var update_tickscale = function(root, scale, axis) {\n",
       "    if (!root.hasClass(axis + \"scalable\")) return;\n",
       "\n",
       "    var tickscales = root.data(axis + \"tickscales\");\n",
       "    var best_tickscale = 1.0;\n",
       "    var best_tickscale_dist = Infinity;\n",
       "    for (tickscale in tickscales) {\n",
       "        var dist = Math.abs(Math.log(tickscale) - Math.log(scale));\n",
       "        if (dist < best_tickscale_dist) {\n",
       "            best_tickscale_dist = dist;\n",
       "            best_tickscale = tickscale;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    if (best_tickscale != root.data(axis + \"tickscale\")) {\n",
       "        root.data(axis + \"tickscale\", best_tickscale);\n",
       "        var mark_inscale_gridlines = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        var mark_inscale_labels = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        root.select(\".\" + axis + \"gridlines\").selectAll(\"path\").forEach(mark_inscale_gridlines);\n",
       "        root.select(\".\" + axis + \"labels\").selectAll(\"text\").forEach(mark_inscale_labels);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "var set_plot_pan_zoom = function(root, tx, ty, scale) {\n",
       "    var old_scale = root.data(\"scale\");\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    // compute the viewport derived from tx, ty, and scale\n",
       "    var x_min = -width * scale - (scale * width - width),\n",
       "        x_max = width * scale,\n",
       "        y_min = -height * scale - (scale * height - height),\n",
       "        y_max = height * scale;\n",
       "\n",
       "    var x0 = bounds.x0 - scale * bounds.x0,\n",
       "        y0 = bounds.y0 - scale * bounds.y0;\n",
       "\n",
       "    var tx = Math.max(Math.min(tx - x0, x_max), x_min),\n",
       "        ty = Math.max(Math.min(ty - y0, y_max), y_min);\n",
       "\n",
       "    tx += x0;\n",
       "    ty += y0;\n",
       "\n",
       "    // when the scale change, we may need to alter which set of\n",
       "    // ticks is being displayed\n",
       "    if (scale != old_scale) {\n",
       "        update_tickscale(root, scale, \"x\");\n",
       "        update_tickscale(root, scale, \"y\");\n",
       "    }\n",
       "\n",
       "    set_geometry_transform(root, tx, ty, scale);\n",
       "\n",
       "    root.data(\"scale\", scale);\n",
       "    root.data(\"tx\", tx);\n",
       "    root.data(\"ty\", ty);\n",
       "};\n",
       "\n",
       "\n",
       "var scale_centered_translation = function(root, scale) {\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    var tx0 = root.data(\"tx\"),\n",
       "        ty0 = root.data(\"ty\");\n",
       "\n",
       "    var scale0 = root.data(\"scale\");\n",
       "\n",
       "    // how off from center the current view is\n",
       "    var xoff = tx0 - (bounds.x0 * (1 - scale0) + (width * (1 - scale0)) / 2),\n",
       "        yoff = ty0 - (bounds.y0 * (1 - scale0) + (height * (1 - scale0)) / 2);\n",
       "\n",
       "    // rescale offsets\n",
       "    xoff = xoff * scale / scale0;\n",
       "    yoff = yoff * scale / scale0;\n",
       "\n",
       "    // adjust for the panel position being scaled\n",
       "    var x_edge_adjust = bounds.x0 * (1 - scale),\n",
       "        y_edge_adjust = bounds.y0 * (1 - scale);\n",
       "\n",
       "    return {\n",
       "        x: xoff + x_edge_adjust + (width - width * scale) / 2,\n",
       "        y: yoff + y_edge_adjust + (height - height * scale) / 2\n",
       "    };\n",
       "};\n",
       "\n",
       "\n",
       "// Initialize data for panning zooming if it isn't already.\n",
       "var init_pan_zoom = function(root) {\n",
       "    if (root.data(\"zoompan-ready\")) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    // The non-scaling-stroke trick. Rather than try to correct for the\n",
       "    // stroke-width when zooming, we force it to a fixed value.\n",
       "    var px_per_mm = root.node.getCTM().a;\n",
       "\n",
       "    // Drag events report deltas in pixels, which we'd like to convert to\n",
       "    // millimeters.\n",
       "    root.data(\"px_per_mm\", px_per_mm);\n",
       "\n",
       "    root.selectAll(\"path\")\n",
       "        .forEach(function (element, i) {\n",
       "        sw = element.asPX(\"stroke-width\") * px_per_mm;\n",
       "        if (sw > 0) {\n",
       "            element.attribute(\"stroke-width\", sw);\n",
       "            element.attribute(\"vector-effect\", \"non-scaling-stroke\");\n",
       "        }\n",
       "    });\n",
       "\n",
       "    // Store ticks labels original tranformation\n",
       "    root.selectAll(\".xlabels > text, .ylabels > text\")\n",
       "        .forEach(function (element, i) {\n",
       "            var lm = element.transform().localMatrix;\n",
       "            element.data(\"static_transform\",\n",
       "                new Snap.Matrix(lm.a, lm.b, lm.c, lm.d, lm.e, lm.f));\n",
       "        });\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\");\n",
       "    var ygridlines = root.select(\".ygridlines\");\n",
       "    var xlabels = root.select(\".xlabels\");\n",
       "    var ylabels = root.select(\".ylabels\");\n",
       "\n",
       "    if (root.data(\"tx\") === undefined) root.data(\"tx\", 0);\n",
       "    if (root.data(\"ty\") === undefined) root.data(\"ty\", 0);\n",
       "    if (root.data(\"scale\") === undefined) root.data(\"scale\", 1.0);\n",
       "    if (root.data(\"xtickscales\") === undefined) {\n",
       "\n",
       "        // index all the tick scales that are listed\n",
       "        var xtickscales = {};\n",
       "        var ytickscales = {};\n",
       "        var add_x_tick_scales = function (element, i) {\n",
       "            xtickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "        var add_y_tick_scales = function (element, i) {\n",
       "            ytickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "\n",
       "        if (xgridlines) xgridlines.selectAll(\"path\").forEach(add_x_tick_scales);\n",
       "        if (ygridlines) ygridlines.selectAll(\"path\").forEach(add_y_tick_scales);\n",
       "        if (xlabels) xlabels.selectAll(\"text\").forEach(add_x_tick_scales);\n",
       "        if (ylabels) ylabels.selectAll(\"text\").forEach(add_y_tick_scales);\n",
       "\n",
       "        root.data(\"xtickscales\", xtickscales);\n",
       "        root.data(\"ytickscales\", ytickscales);\n",
       "        root.data(\"xtickscale\", 1.0);\n",
       "    }\n",
       "\n",
       "    var min_scale = 1.0, max_scale = 1.0;\n",
       "    for (scale in xtickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    for (scale in ytickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    root.data(\"min_scale\", min_scale);\n",
       "    root.data(\"max_scale\", max_scale);\n",
       "\n",
       "    // store the original positions of labels\n",
       "    if (xlabels) {\n",
       "        xlabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"x\", element.asPX(\"x\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    if (ylabels) {\n",
       "        ylabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"y\", element.asPX(\"y\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    // mark grid lines and ticks as in or out of scale.\n",
       "    var mark_inscale = function (element, i) {\n",
       "        element.attribute(\"gadfly:inscale\", element.attribute(\"gadfly:scale\") == 1.0);\n",
       "    };\n",
       "\n",
       "    if (xgridlines) xgridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (ygridlines) ygridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (xlabels) xlabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "    if (ylabels) ylabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "\n",
       "    // figure out the upper ond lower bounds on panning using the maximum\n",
       "    // and minum grid lines\n",
       "    var bounds = root.plotbounds();\n",
       "    var pan_bounds = {\n",
       "        x0: 0.0,\n",
       "        y0: 0.0,\n",
       "        x1: 0.0,\n",
       "        y1: 0.0\n",
       "    };\n",
       "\n",
       "    if (xgridlines) {\n",
       "        xgridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.x1 - bbox.x < pan_bounds.x0) {\n",
       "                        pan_bounds.x0 = bounds.x1 - bbox.x;\n",
       "                    }\n",
       "                    if (bounds.x0 - bbox.x > pan_bounds.x1) {\n",
       "                        pan_bounds.x1 = bounds.x0 - bbox.x;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (ygridlines) {\n",
       "        ygridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.y1 - bbox.y < pan_bounds.y0) {\n",
       "                        pan_bounds.y0 = bounds.y1 - bbox.y;\n",
       "                    }\n",
       "                    if (bounds.y0 - bbox.y > pan_bounds.y1) {\n",
       "                        pan_bounds.y1 = bounds.y0 - bbox.y;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // nudge these values a little\n",
       "    pan_bounds.x0 -= 5;\n",
       "    pan_bounds.x1 += 5;\n",
       "    pan_bounds.y0 -= 5;\n",
       "    pan_bounds.y1 += 5;\n",
       "    root.data(\"pan_bounds\", pan_bounds);\n",
       "\n",
       "    root.data(\"zoompan-ready\", true)\n",
       "};\n",
       "\n",
       "\n",
       "// drag actions, i.e. zooming and panning\n",
       "var pan_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        root.data(\"dx\", 0);\n",
       "        root.data(\"dy\", 0);\n",
       "        root.data(\"tx0\", root.data(\"tx\"));\n",
       "        root.data(\"ty0\", root.data(\"ty\"));\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        dx /= px_per_mm;\n",
       "        dy /= px_per_mm;\n",
       "\n",
       "        var tx0 = root.data(\"tx\"),\n",
       "            ty0 = root.data(\"ty\");\n",
       "\n",
       "        var dx0 = root.data(\"dx\"),\n",
       "            dy0 = root.data(\"dy\");\n",
       "\n",
       "        root.data(\"dx\", dx);\n",
       "        root.data(\"dy\", dy);\n",
       "\n",
       "        dx = dx - dx0;\n",
       "        dy = dy - dy0;\n",
       "\n",
       "        var tx = tx0 + dx,\n",
       "            ty = ty0 + dy;\n",
       "\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\"));\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        set_plot_pan_zoom(root, root.data(\"tx0\"), root.data(\"ty0\"), root.data(\"scale\"));\n",
       "    }\n",
       "};\n",
       "\n",
       "var zoom_box;\n",
       "var zoom_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        var bounds = root.plotbounds();\n",
       "        var width = bounds.x1 - bounds.x0,\n",
       "            height = bounds.y1 - bounds.y0;\n",
       "        var ratio = width / height;\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        x = xscalable ? x / px_per_mm : bounds.x0;\n",
       "        y = yscalable ? y / px_per_mm : bounds.y0;\n",
       "        var w = xscalable ? 0 : width;\n",
       "        var h = yscalable ? 0 : height;\n",
       "        zoom_box = root.rect(x, y, w, h).attr({\n",
       "            \"fill\": \"#000\",\n",
       "            \"opacity\": 0.25\n",
       "        });\n",
       "        zoom_box.data(\"ratio\", ratio);\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        var bounds = root.plotbounds();\n",
       "        if (yscalable) {\n",
       "            y /= px_per_mm;\n",
       "            y = Math.max(bounds.y0, y);\n",
       "            y = Math.min(bounds.y1, y);\n",
       "        } else {\n",
       "            y = bounds.y1;\n",
       "        }\n",
       "        if (xscalable) {\n",
       "            x /= px_per_mm;\n",
       "            x = Math.max(bounds.x0, x);\n",
       "            x = Math.min(bounds.x1, x);\n",
       "        } else {\n",
       "            x = bounds.x1;\n",
       "        }\n",
       "\n",
       "        dx = x - zoom_box.attr(\"x\");\n",
       "        dy = y - zoom_box.attr(\"y\");\n",
       "        if (xscalable && yscalable) {\n",
       "            var ratio = zoom_box.data(\"ratio\");\n",
       "            var width = Math.min(Math.abs(dx), ratio * Math.abs(dy));\n",
       "            var height = Math.min(Math.abs(dy), Math.abs(dx) / ratio);\n",
       "            dx = width * dx / Math.abs(dx);\n",
       "            dy = height * dy / Math.abs(dy);\n",
       "        }\n",
       "        var xoffset = 0,\n",
       "            yoffset = 0;\n",
       "        if (dx < 0) {\n",
       "            xoffset = dx;\n",
       "            dx = -1 * dx;\n",
       "        }\n",
       "        if (dy < 0) {\n",
       "            yoffset = dy;\n",
       "            dy = -1 * dy;\n",
       "        }\n",
       "        if (isNaN(dy)) {\n",
       "            dy = 0.0;\n",
       "        }\n",
       "        if (isNaN(dx)) {\n",
       "            dx = 0.0;\n",
       "        }\n",
       "        zoom_box.transform(\"T\" + xoffset + \",\" + yoffset);\n",
       "        zoom_box.attr(\"width\", dx);\n",
       "        zoom_box.attr(\"height\", dy);\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var zoom_bounds = zoom_box.getBBox();\n",
       "        if (zoom_bounds.width * zoom_bounds.height <= 0) {\n",
       "            return;\n",
       "        }\n",
       "        var plot_bounds = root.plotbounds();\n",
       "        var zoom_factor = 1.0;\n",
       "        if (yscalable) {\n",
       "            zoom_factor = (plot_bounds.y1 - plot_bounds.y0) / zoom_bounds.height;\n",
       "        } else {\n",
       "            zoom_factor = (plot_bounds.x1 - plot_bounds.x0) / zoom_bounds.width;\n",
       "        }\n",
       "        var tx = (root.data(\"tx\") - zoom_bounds.x) * zoom_factor + plot_bounds.x0,\n",
       "            ty = (root.data(\"ty\") - zoom_bounds.y) * zoom_factor + plot_bounds.y0;\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\") * zoom_factor);\n",
       "        zoom_box.remove();\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        zoom_box.remove();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onstart = function(x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var scalable = root.hasClass(\"xscalable\") || root.hasClass(\"yscalable\");\n",
       "    var zoomable = !event.altKey && !event.ctrlKey && event.shiftKey && scalable;\n",
       "    var panable = !event.altKey && !event.ctrlKey && !event.shiftKey && scalable;\n",
       "    var drag_action = zoomable ? zoom_action :\n",
       "                      panable  ? pan_action :\n",
       "                                 undefined;\n",
       "    root.data(\"drag_action\", drag_action);\n",
       "    if (drag_action) {\n",
       "        var cancel_drag_action = function(event) {\n",
       "            if (event.which == 27) { // esc key\n",
       "                drag_action.cancel(root);\n",
       "                root.data(\"drag_action\", undefined);\n",
       "            }\n",
       "        };\n",
       "        window.addEventListener(\"keyup\", cancel_drag_action);\n",
       "        root.data(\"cancel_drag_action\", cancel_drag_action);\n",
       "        drag_action.start(root, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.update(root, dx, dy, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onend = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    window.removeEventListener(\"keyup\", root.data(\"cancel_drag_action\"));\n",
       "    root.data(\"cancel_drag_action\", undefined);\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.end(root, event);\n",
       "    }\n",
       "    root.data(\"drag_action\", undefined);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_scroll = function(event) {\n",
       "    if (event.shiftKey) {\n",
       "        increase_zoom_by_position(this.plotroot(), 0.001 * event.wheelDelta);\n",
       "        event.preventDefault();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseover = function(event) {\n",
       "    this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseout = function(event) {\n",
       "     this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomout_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), -0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomin_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), 0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_track_click = function(event) {\n",
       "    // TODO\n",
       "};\n",
       "\n",
       "\n",
       "// Map slider position x to scale y using the function y = a*exp(b*x)+c.\n",
       "// The constants a, b, and c are solved using the constraint that the function\n",
       "// should go through the points (0; min_scale), (0.5; 1), and (1; max_scale).\n",
       "var scale_from_slider_position = function(position, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return a * Math.exp(b * position) + c;\n",
       "}\n",
       "\n",
       "// inverse of scale_from_slider_position\n",
       "var slider_position_from_scale = function(scale, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return 1 / b * Math.log((scale - c) / a);\n",
       "}\n",
       "\n",
       "var increase_zoom_by_position = function(root, delta_position, animate) {\n",
       "    var scale = root.data(\"scale\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\");\n",
       "    var position = slider_position_from_scale(scale, min_scale, max_scale);\n",
       "    position += delta_position;\n",
       "    scale = scale_from_slider_position(position, min_scale, max_scale);\n",
       "    set_zoom(root, scale, animate);\n",
       "}\n",
       "\n",
       "var set_zoom = function(root, scale, animate) {\n",
       "    var min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"scale\");\n",
       "    var new_scale = Math.max(min_scale, Math.min(scale, max_scale));\n",
       "    if (animate) {\n",
       "        Snap.animate(\n",
       "            old_scale,\n",
       "            new_scale,\n",
       "            function (new_scale) {\n",
       "                update_plot_scale(root, new_scale);\n",
       "            },\n",
       "            200);\n",
       "    } else {\n",
       "        update_plot_scale(root, new_scale);\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "var update_plot_scale = function(root, new_scale) {\n",
       "    var trans = scale_centered_translation(root, new_scale);\n",
       "    set_plot_pan_zoom(root, trans.x, trans.y, new_scale);\n",
       "\n",
       "    root.selectAll(\".zoomslider_thumb\")\n",
       "        .forEach(function (element, i) {\n",
       "            var min_pos = element.data(\"min_pos\"),\n",
       "                max_pos = element.data(\"max_pos\"),\n",
       "                min_scale = root.data(\"min_scale\"),\n",
       "                max_scale = root.data(\"max_scale\");\n",
       "            var xmid = (min_pos + max_pos) / 2;\n",
       "            var xpos = slider_position_from_scale(new_scale, min_scale, max_scale);\n",
       "            element.transform(new Snap.Matrix().translate(\n",
       "                Math.max(min_pos, Math.min(\n",
       "                         max_pos, min_pos + (max_pos - min_pos) * xpos)) - xmid, 0));\n",
       "    });\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var min_pos = this.data(\"min_pos\"),\n",
       "        max_pos = this.data(\"max_pos\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"old_scale\");\n",
       "\n",
       "    var px_per_mm = root.data(\"px_per_mm\");\n",
       "    dx /= px_per_mm;\n",
       "    dy /= px_per_mm;\n",
       "\n",
       "    var xmid = (min_pos + max_pos) / 2;\n",
       "    var xpos = slider_position_from_scale(old_scale, min_scale, max_scale) +\n",
       "                   dx / (max_pos - min_pos);\n",
       "\n",
       "    // compute the new scale\n",
       "    var new_scale = scale_from_slider_position(xpos, min_scale, max_scale);\n",
       "    new_scale = Math.min(max_scale, Math.max(min_scale, new_scale));\n",
       "\n",
       "    update_plot_scale(root, new_scale);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragstart = function(x, y, event) {\n",
       "    this.animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    // keep track of what the scale was when we started dragging\n",
       "    root.data(\"old_scale\", root.data(\"scale\"));\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragend = function(event) {\n",
       "    this.animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "var toggle_color_class = function(root, color_class, ison) {\n",
       "    var guides = root.selectAll(\".guide.\" + color_class + \",.guide .\" + color_class);\n",
       "    var geoms = root.selectAll(\".geometry.\" + color_class + \",.geometry .\" + color_class);\n",
       "    if (ison) {\n",
       "        guides.animate({opacity: 0.5}, 250);\n",
       "        geoms.animate({opacity: 0.0}, 250);\n",
       "    } else {\n",
       "        guides.animate({opacity: 1.0}, 250);\n",
       "        geoms.animate({opacity: 1.0}, 250);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.colorkey_swatch_click = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    var color_class = this.data(\"color_class\");\n",
       "\n",
       "    if (event.shiftKey) {\n",
       "        root.selectAll(\".colorkey text\")\n",
       "            .forEach(function (element) {\n",
       "                var other_color_class = element.data(\"color_class\");\n",
       "                if (other_color_class != color_class) {\n",
       "                    toggle_color_class(root, other_color_class,\n",
       "                                       element.attr(\"opacity\") == 1.0);\n",
       "                }\n",
       "            });\n",
       "    } else {\n",
       "        toggle_color_class(root, color_class, this.attr(\"opacity\") == 1.0);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "return Gadfly;\n",
       "\n",
       "}));\n",
       "\n",
       "\n",
       "//@ sourceURL=gadfly.js\n",
       "\n",
       "(function (glob, factory) {\n",
       "    // AMD support\n",
       "      if (typeof require === \"function\" && typeof define === \"function\" && define.amd) {\n",
       "        require([\"Snap.svg\", \"Gadfly\"], function (Snap, Gadfly) {\n",
       "            factory(Snap, Gadfly);\n",
       "        });\n",
       "      } else {\n",
       "          factory(glob.Snap, glob.Gadfly);\n",
       "      }\n",
       "})(window, function (Snap, Gadfly) {\n",
       "    var fig = Snap(\"#img-7a874288\");\n",
       "fig.select(\"#img-7a874288-5\")\n",
       "   .init_gadfly();\n",
       "fig.select(\"#img-7a874288-7\")\n",
       "   .plotroot().data(\"unfocused_ygrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-7a874288-7\")\n",
       "   .plotroot().data(\"focused_ygrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-7a874288-8\")\n",
       "   .plotroot().data(\"unfocused_xgrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-7a874288-8\")\n",
       "   .plotroot().data(\"focused_xgrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-7a874288-15\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-7a874288-15\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-7a874288-15\")\n",
       "   .click(Gadfly.zoomslider_zoomin_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "fig.select(\"#img-7a874288-17\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-7a874288-17\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-7a874288-17\")\n",
       "   .click(Gadfly.zoomslider_track_click);\n",
       "fig.select(\"#img-7a874288-18\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-7a874288-18\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-7a874288-18\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-7a874288-18\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-7a874288-18\")\n",
       "   .drag(Gadfly.zoomslider_thumb_dragmove,\n",
       "     Gadfly.zoomslider_thumb_dragstart,\n",
       "     Gadfly.zoomslider_thumb_dragend)\n",
       ";\n",
       "fig.select(\"#img-7a874288-19\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-7a874288-19\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-7a874288-19\")\n",
       "   .click(Gadfly.zoomslider_zoomout_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "    });\n",
       "]]> </script>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "Plot(...)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calib_param, calib_results = Mads.calibrate(md)\n",
    "calib_predictions = Mads.forward(md, calib_param)\n",
    "Mads.plotmatches(md, calib_predictions, r\"w13\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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       "this._drag.y=w;this._drag.id=r.identifier;!q.length&&a.mousemove(e).mouseup(l);q.push({el:this,move_scope:h,start_scope:n,end_scope:p});d&&k.on(\"snap.drag.start.\"+this.id,d);b&&k.on(\"snap.drag.move.\"+this.id,b);f&&k.on(\"snap.drag.end.\"+this.id,f);k(\"snap.drag.start.\"+this.id,n||h||this,v,w,r)}if(!arguments.length){var v;return this.drag(function(a,b){this.attr({transform:v+(v?\"T\":\"t\")+[a,b]})},function(){v=this.transform().local})}this._drag={};r.push({el:this,start:u});this.mousedown(u);return this};\n",
       "A.undrag=function(){for(var b=r.length;b--;)r[b].el==this&&(this.unmousedown(r[b].start),r.splice(b,1),k.unbind(\"snap.drag.*.\"+this.id));!r.length&&a.unmousemove(e).unmouseup(l);return this}});C.plugin(function(a,v,y,C){y=y.prototype;var A=/^\\s*url\\((.+)\\)/,w=String,z=a._.$;a.filter={};y.filter=function(d){var f=this;\"svg\"!=f.type&&(f=f.paper);d=a.parse(w(d));var k=a._.id(),u=z(\"filter\");z(u,{id:k,filterUnits:\"userSpaceOnUse\"});u.appendChild(d.node);f.defs.appendChild(u);return new v(u)};k.on(\"snap.util.getattr.filter\",\n",
       "function(){k.stop();var d=z(this.node,\"filter\");if(d)return(d=w(d).match(A))&&a.select(d[1])});k.on(\"snap.util.attr.filter\",function(d){if(d instanceof v&&\"filter\"==d.type){k.stop();var f=d.node.id;f||(z(d.node,{id:d.id}),f=d.id);z(this.node,{filter:a.url(f)})}d&&\"none\"!=d||(k.stop(),this.node.removeAttribute(\"filter\"))});a.filter.blur=function(d,f){null==d&&(d=2);return a.format('<feGaussianBlur stdDeviation=\"{def}\"/>',{def:null==f?d:[d,f]})};a.filter.blur.toString=function(){return this()};a.filter.shadow=\n",
       "function(d,f,k,u,p){\"string\"==typeof k&&(p=u=k,k=4);\"string\"!=typeof u&&(p=u,u=\"#000\");null==k&&(k=4);null==p&&(p=1);null==d&&(d=0,f=2);null==f&&(f=d);u=a.color(u||\"#000\");return a.format('<feGaussianBlur in=\"SourceAlpha\" stdDeviation=\"{blur}\"/><feOffset dx=\"{dx}\" dy=\"{dy}\" result=\"offsetblur\"/><feFlood flood-color=\"{color}\"/><feComposite in2=\"offsetblur\" operator=\"in\"/><feComponentTransfer><feFuncA type=\"linear\" slope=\"{opacity}\"/></feComponentTransfer><feMerge><feMergeNode/><feMergeNode in=\"SourceGraphic\"/></feMerge>',\n",
       "{color:u,dx:d,dy:f,blur:k,opacity:p})};a.filter.shadow.toString=function(){return this()};a.filter.grayscale=function(d){null==d&&(d=1);return a.format('<feColorMatrix type=\"matrix\" values=\"{a} {b} {c} 0 0 {d} {e} {f} 0 0 {g} {b} {h} 0 0 0 0 0 1 0\"/>',{a:0.2126+0.7874*(1-d),b:0.7152-0.7152*(1-d),c:0.0722-0.0722*(1-d),d:0.2126-0.2126*(1-d),e:0.7152+0.2848*(1-d),f:0.0722-0.0722*(1-d),g:0.2126-0.2126*(1-d),h:0.0722+0.9278*(1-d)})};a.filter.grayscale.toString=function(){return this()};a.filter.sepia=\n",
       "function(d){null==d&&(d=1);return a.format('<feColorMatrix type=\"matrix\" values=\"{a} {b} {c} 0 0 {d} {e} {f} 0 0 {g} {h} {i} 0 0 0 0 0 1 0\"/>',{a:0.393+0.607*(1-d),b:0.769-0.769*(1-d),c:0.189-0.189*(1-d),d:0.349-0.349*(1-d),e:0.686+0.314*(1-d),f:0.168-0.168*(1-d),g:0.272-0.272*(1-d),h:0.534-0.534*(1-d),i:0.131+0.869*(1-d)})};a.filter.sepia.toString=function(){return this()};a.filter.saturate=function(d){null==d&&(d=1);return a.format('<feColorMatrix type=\"saturate\" values=\"{amount}\"/>',{amount:1-\n",
       "d})};a.filter.saturate.toString=function(){return this()};a.filter.hueRotate=function(d){return a.format('<feColorMatrix type=\"hueRotate\" values=\"{angle}\"/>',{angle:d||0})};a.filter.hueRotate.toString=function(){return this()};a.filter.invert=function(d){null==d&&(d=1);return a.format('<feComponentTransfer><feFuncR type=\"table\" tableValues=\"{amount} {amount2}\"/><feFuncG type=\"table\" tableValues=\"{amount} {amount2}\"/><feFuncB type=\"table\" tableValues=\"{amount} {amount2}\"/></feComponentTransfer>',{amount:d,\n",
       "amount2:1-d})};a.filter.invert.toString=function(){return this()};a.filter.brightness=function(d){null==d&&(d=1);return a.format('<feComponentTransfer><feFuncR type=\"linear\" slope=\"{amount}\"/><feFuncG type=\"linear\" slope=\"{amount}\"/><feFuncB type=\"linear\" slope=\"{amount}\"/></feComponentTransfer>',{amount:d})};a.filter.brightness.toString=function(){return this()};a.filter.contrast=function(d){null==d&&(d=1);return a.format('<feComponentTransfer><feFuncR type=\"linear\" slope=\"{amount}\" intercept=\"{amount2}\"/><feFuncG type=\"linear\" slope=\"{amount}\" intercept=\"{amount2}\"/><feFuncB type=\"linear\" slope=\"{amount}\" intercept=\"{amount2}\"/></feComponentTransfer>',\n",
       "{amount:d,amount2:0.5-d/2})};a.filter.contrast.toString=function(){return this()}});return C});\n",
       "\n",
       "]]> </script>\n",
       "<script> <![CDATA[\n",
       "\n",
       "(function (glob, factory) {\n",
       "    // AMD support\n",
       "    if (typeof define === \"function\" && define.amd) {\n",
       "        // Define as an anonymous module\n",
       "        define(\"Gadfly\", [\"Snap.svg\"], function (Snap) {\n",
       "            return factory(Snap);\n",
       "        });\n",
       "    } else {\n",
       "        // Browser globals (glob is window)\n",
       "        // Snap adds itself to window\n",
       "        glob.Gadfly = factory(glob.Snap);\n",
       "    }\n",
       "}(this, function (Snap) {\n",
       "\n",
       "var Gadfly = {};\n",
       "\n",
       "// Get an x/y coordinate value in pixels\n",
       "var xPX = function(fig, x) {\n",
       "    var client_box = fig.node.getBoundingClientRect();\n",
       "    return x * fig.node.viewBox.baseVal.width / client_box.width;\n",
       "};\n",
       "\n",
       "var yPX = function(fig, y) {\n",
       "    var client_box = fig.node.getBoundingClientRect();\n",
       "    return y * fig.node.viewBox.baseVal.height / client_box.height;\n",
       "};\n",
       "\n",
       "\n",
       "Snap.plugin(function (Snap, Element, Paper, global) {\n",
       "    // Traverse upwards from a snap element to find and return the first\n",
       "    // note with the \"plotroot\" class.\n",
       "    Element.prototype.plotroot = function () {\n",
       "        var element = this;\n",
       "        while (!element.hasClass(\"plotroot\") && element.parent() != null) {\n",
       "            element = element.parent();\n",
       "        }\n",
       "        return element;\n",
       "    };\n",
       "\n",
       "    Element.prototype.svgroot = function () {\n",
       "        var element = this;\n",
       "        while (element.node.nodeName != \"svg\" && element.parent() != null) {\n",
       "            element = element.parent();\n",
       "        }\n",
       "        return element;\n",
       "    };\n",
       "\n",
       "    Element.prototype.plotbounds = function () {\n",
       "        var root = this.plotroot()\n",
       "        var bbox = root.select(\".guide.background\").node.getBBox();\n",
       "        return {\n",
       "            x0: bbox.x,\n",
       "            x1: bbox.x + bbox.width,\n",
       "            y0: bbox.y,\n",
       "            y1: bbox.y + bbox.height\n",
       "        };\n",
       "    };\n",
       "\n",
       "    Element.prototype.plotcenter = function () {\n",
       "        var root = this.plotroot()\n",
       "        var bbox = root.select(\".guide.background\").node.getBBox();\n",
       "        return {\n",
       "            x: bbox.x + bbox.width / 2,\n",
       "            y: bbox.y + bbox.height / 2\n",
       "        };\n",
       "    };\n",
       "\n",
       "    // Emulate IE style mouseenter/mouseleave events, since Microsoft always\n",
       "    // does everything right.\n",
       "    // See: http://www.dynamic-tools.net/toolbox/isMouseLeaveOrEnter/\n",
       "    var events = [\"mouseenter\", \"mouseleave\"];\n",
       "\n",
       "    for (i in events) {\n",
       "        (function (event_name) {\n",
       "            var event_name = events[i];\n",
       "            Element.prototype[event_name] = function (fn, scope) {\n",
       "                if (Snap.is(fn, \"function\")) {\n",
       "                    var fn2 = function (event) {\n",
       "                        if (event.type != \"mouseover\" && event.type != \"mouseout\") {\n",
       "                            return;\n",
       "                        }\n",
       "\n",
       "                        var reltg = event.relatedTarget ? event.relatedTarget :\n",
       "                            event.type == \"mouseout\" ? event.toElement : event.fromElement;\n",
       "                        while (reltg && reltg != this.node) reltg = reltg.parentNode;\n",
       "\n",
       "                        if (reltg != this.node) {\n",
       "                            return fn.apply(this, event);\n",
       "                        }\n",
       "                    };\n",
       "\n",
       "                    if (event_name == \"mouseenter\") {\n",
       "                        this.mouseover(fn2, scope);\n",
       "                    } else {\n",
       "                        this.mouseout(fn2, scope);\n",
       "                    }\n",
       "                }\n",
       "                return this;\n",
       "            };\n",
       "        })(events[i]);\n",
       "    }\n",
       "\n",
       "\n",
       "    Element.prototype.mousewheel = function (fn, scope) {\n",
       "        if (Snap.is(fn, \"function\")) {\n",
       "            var el = this;\n",
       "            var fn2 = function (event) {\n",
       "                fn.apply(el, [event]);\n",
       "            };\n",
       "        }\n",
       "\n",
       "        this.node.addEventListener(\n",
       "            /Firefox/i.test(navigator.userAgent) ? \"DOMMouseScroll\" : \"mousewheel\",\n",
       "            fn2);\n",
       "\n",
       "        return this;\n",
       "    };\n",
       "\n",
       "\n",
       "    // Snap's attr function can be too slow for things like panning/zooming.\n",
       "    // This is a function to directly update element attributes without going\n",
       "    // through eve.\n",
       "    Element.prototype.attribute = function(key, val) {\n",
       "        if (val === undefined) {\n",
       "            return this.node.getAttribute(key);\n",
       "        } else {\n",
       "            this.node.setAttribute(key, val);\n",
       "            return this;\n",
       "        }\n",
       "    };\n",
       "\n",
       "    Element.prototype.init_gadfly = function() {\n",
       "        this.mouseenter(Gadfly.plot_mouseover)\n",
       "            .mouseleave(Gadfly.plot_mouseout)\n",
       "            .dblclick(Gadfly.plot_dblclick)\n",
       "            .mousewheel(Gadfly.guide_background_scroll)\n",
       "            .drag(Gadfly.guide_background_drag_onmove,\n",
       "                  Gadfly.guide_background_drag_onstart,\n",
       "                  Gadfly.guide_background_drag_onend);\n",
       "        this.mouseenter(function (event) {\n",
       "            init_pan_zoom(this.plotroot());\n",
       "        });\n",
       "        return this;\n",
       "    };\n",
       "});\n",
       "\n",
       "\n",
       "// When the plot is moused over, emphasize the grid lines.\n",
       "Gadfly.plot_mouseover = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    var keyboard_zoom = function(event) {\n",
       "        if (event.which == 187) { // plus\n",
       "            increase_zoom_by_position(root, 0.1, true);\n",
       "        } else if (event.which == 189) { // minus\n",
       "            increase_zoom_by_position(root, -0.1, true);\n",
       "        }\n",
       "    };\n",
       "    root.data(\"keyboard_zoom\", keyboard_zoom);\n",
       "    window.addEventListener(\"keyup\", keyboard_zoom);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    xgridlines.data(\"unfocused_strokedash\",\n",
       "                    xgridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "    ygridlines.data(\"unfocused_strokedash\",\n",
       "                    ygridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "\n",
       "    // emphasize grid lines\n",
       "    var destcolor = root.data(\"focused_xgrid_color\");\n",
       "    xgridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"focused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // reveal zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 1.0}, 250);\n",
       "};\n",
       "\n",
       "// Reset pan and zoom on double click\n",
       "Gadfly.plot_dblclick = function(event) {\n",
       "  set_plot_pan_zoom(this.plotroot(), 0.0, 0.0, 1.0);\n",
       "};\n",
       "\n",
       "// Unemphasize grid lines on mouse out.\n",
       "Gadfly.plot_mouseout = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    window.removeEventListener(\"keyup\", root.data(\"keyboard_zoom\"));\n",
       "    root.data(\"keyboard_zoom\", undefined);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    var destcolor = root.data(\"unfocused_xgrid_color\");\n",
       "\n",
       "    xgridlines.attribute(\"stroke-dasharray\", xgridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"unfocused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", ygridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // hide zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 0.0}, 250);\n",
       "};\n",
       "\n",
       "\n",
       "var set_geometry_transform = function(root, tx, ty, scale) {\n",
       "    var xscalable = root.hasClass(\"xscalable\"),\n",
       "        yscalable = root.hasClass(\"yscalable\");\n",
       "\n",
       "    var old_scale = root.data(\"scale\");\n",
       "\n",
       "    var xscale = xscalable ? scale : 1.0,\n",
       "        yscale = yscalable ? scale : 1.0;\n",
       "\n",
       "    tx = xscalable ? tx : 0.0;\n",
       "    ty = yscalable ? ty : 0.0;\n",
       "\n",
       "    var t = new Snap.Matrix().translate(tx, ty).scale(xscale, yscale);\n",
       "\n",
       "    root.selectAll(\".geometry, image\")\n",
       "        .forEach(function (element, i) {\n",
       "            element.transform(t);\n",
       "        });\n",
       "\n",
       "    bounds = root.plotbounds();\n",
       "\n",
       "    if (yscalable) {\n",
       "        var xfixed_t = new Snap.Matrix().translate(0, ty).scale(1.0, yscale);\n",
       "        root.selectAll(\".xfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(xfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".ylabels\")\n",
       "            .transform(xfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1, 1/scale, cx, cy).add(st);\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var y = cy * scale + ty;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.y0 <= y && y <= bounds.y1 ? \"visible\" : \"hidden\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (xscalable) {\n",
       "        var yfixed_t = new Snap.Matrix().translate(tx, 0).scale(xscale, 1.0);\n",
       "        var xtrans = new Snap.Matrix().translate(tx, 0);\n",
       "        root.selectAll(\".yfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(yfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".xlabels\")\n",
       "            .transform(yfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1/scale, 1, cx, cy).add(st);\n",
       "\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var x = cx * scale + tx;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.x0 <= x && x <= bounds.x1 ? \"visible\" : \"hidden\");\n",
       "                    }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // we must unscale anything that is scale invariance: widths, raiduses, etc.\n",
       "    var size_attribs = [\"font-size\"];\n",
       "    var unscaled_selection = \".geometry, .geometry *\";\n",
       "    if (xscalable) {\n",
       "        size_attribs.push(\"rx\");\n",
       "        unscaled_selection += \", .xgridlines\";\n",
       "    }\n",
       "    if (yscalable) {\n",
       "        size_attribs.push(\"ry\");\n",
       "        unscaled_selection += \", .ygridlines\";\n",
       "    }\n",
       "\n",
       "    root.selectAll(unscaled_selection)\n",
       "        .forEach(function (element, i) {\n",
       "            // circle need special help\n",
       "            if (element.node.nodeName == \"circle\") {\n",
       "                var cx = element.attribute(\"cx\"),\n",
       "                    cy = element.attribute(\"cy\");\n",
       "                unscale_t = new Snap.Matrix().scale(1/xscale, 1/yscale,\n",
       "                                                        cx, cy);\n",
       "                element.transform(unscale_t);\n",
       "                return;\n",
       "            }\n",
       "\n",
       "            for (i in size_attribs) {\n",
       "                var key = size_attribs[i];\n",
       "                var val = parseFloat(element.attribute(key));\n",
       "                if (val !== undefined && val != 0 && !isNaN(val)) {\n",
       "                    element.attribute(key, val * old_scale / scale);\n",
       "                }\n",
       "            }\n",
       "        });\n",
       "};\n",
       "\n",
       "\n",
       "// Find the most appropriate tick scale and update label visibility.\n",
       "var update_tickscale = function(root, scale, axis) {\n",
       "    if (!root.hasClass(axis + \"scalable\")) return;\n",
       "\n",
       "    var tickscales = root.data(axis + \"tickscales\");\n",
       "    var best_tickscale = 1.0;\n",
       "    var best_tickscale_dist = Infinity;\n",
       "    for (tickscale in tickscales) {\n",
       "        var dist = Math.abs(Math.log(tickscale) - Math.log(scale));\n",
       "        if (dist < best_tickscale_dist) {\n",
       "            best_tickscale_dist = dist;\n",
       "            best_tickscale = tickscale;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    if (best_tickscale != root.data(axis + \"tickscale\")) {\n",
       "        root.data(axis + \"tickscale\", best_tickscale);\n",
       "        var mark_inscale_gridlines = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        var mark_inscale_labels = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        root.select(\".\" + axis + \"gridlines\").selectAll(\"path\").forEach(mark_inscale_gridlines);\n",
       "        root.select(\".\" + axis + \"labels\").selectAll(\"text\").forEach(mark_inscale_labels);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "var set_plot_pan_zoom = function(root, tx, ty, scale) {\n",
       "    var old_scale = root.data(\"scale\");\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    // compute the viewport derived from tx, ty, and scale\n",
       "    var x_min = -width * scale - (scale * width - width),\n",
       "        x_max = width * scale,\n",
       "        y_min = -height * scale - (scale * height - height),\n",
       "        y_max = height * scale;\n",
       "\n",
       "    var x0 = bounds.x0 - scale * bounds.x0,\n",
       "        y0 = bounds.y0 - scale * bounds.y0;\n",
       "\n",
       "    var tx = Math.max(Math.min(tx - x0, x_max), x_min),\n",
       "        ty = Math.max(Math.min(ty - y0, y_max), y_min);\n",
       "\n",
       "    tx += x0;\n",
       "    ty += y0;\n",
       "\n",
       "    // when the scale change, we may need to alter which set of\n",
       "    // ticks is being displayed\n",
       "    if (scale != old_scale) {\n",
       "        update_tickscale(root, scale, \"x\");\n",
       "        update_tickscale(root, scale, \"y\");\n",
       "    }\n",
       "\n",
       "    set_geometry_transform(root, tx, ty, scale);\n",
       "\n",
       "    root.data(\"scale\", scale);\n",
       "    root.data(\"tx\", tx);\n",
       "    root.data(\"ty\", ty);\n",
       "};\n",
       "\n",
       "\n",
       "var scale_centered_translation = function(root, scale) {\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    var tx0 = root.data(\"tx\"),\n",
       "        ty0 = root.data(\"ty\");\n",
       "\n",
       "    var scale0 = root.data(\"scale\");\n",
       "\n",
       "    // how off from center the current view is\n",
       "    var xoff = tx0 - (bounds.x0 * (1 - scale0) + (width * (1 - scale0)) / 2),\n",
       "        yoff = ty0 - (bounds.y0 * (1 - scale0) + (height * (1 - scale0)) / 2);\n",
       "\n",
       "    // rescale offsets\n",
       "    xoff = xoff * scale / scale0;\n",
       "    yoff = yoff * scale / scale0;\n",
       "\n",
       "    // adjust for the panel position being scaled\n",
       "    var x_edge_adjust = bounds.x0 * (1 - scale),\n",
       "        y_edge_adjust = bounds.y0 * (1 - scale);\n",
       "\n",
       "    return {\n",
       "        x: xoff + x_edge_adjust + (width - width * scale) / 2,\n",
       "        y: yoff + y_edge_adjust + (height - height * scale) / 2\n",
       "    };\n",
       "};\n",
       "\n",
       "\n",
       "// Initialize data for panning zooming if it isn't already.\n",
       "var init_pan_zoom = function(root) {\n",
       "    if (root.data(\"zoompan-ready\")) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    // The non-scaling-stroke trick. Rather than try to correct for the\n",
       "    // stroke-width when zooming, we force it to a fixed value.\n",
       "    var px_per_mm = root.node.getCTM().a;\n",
       "\n",
       "    // Drag events report deltas in pixels, which we'd like to convert to\n",
       "    // millimeters.\n",
       "    root.data(\"px_per_mm\", px_per_mm);\n",
       "\n",
       "    root.selectAll(\"path\")\n",
       "        .forEach(function (element, i) {\n",
       "        sw = element.asPX(\"stroke-width\") * px_per_mm;\n",
       "        if (sw > 0) {\n",
       "            element.attribute(\"stroke-width\", sw);\n",
       "            element.attribute(\"vector-effect\", \"non-scaling-stroke\");\n",
       "        }\n",
       "    });\n",
       "\n",
       "    // Store ticks labels original tranformation\n",
       "    root.selectAll(\".xlabels > text, .ylabels > text\")\n",
       "        .forEach(function (element, i) {\n",
       "            var lm = element.transform().localMatrix;\n",
       "            element.data(\"static_transform\",\n",
       "                new Snap.Matrix(lm.a, lm.b, lm.c, lm.d, lm.e, lm.f));\n",
       "        });\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\");\n",
       "    var ygridlines = root.select(\".ygridlines\");\n",
       "    var xlabels = root.select(\".xlabels\");\n",
       "    var ylabels = root.select(\".ylabels\");\n",
       "\n",
       "    if (root.data(\"tx\") === undefined) root.data(\"tx\", 0);\n",
       "    if (root.data(\"ty\") === undefined) root.data(\"ty\", 0);\n",
       "    if (root.data(\"scale\") === undefined) root.data(\"scale\", 1.0);\n",
       "    if (root.data(\"xtickscales\") === undefined) {\n",
       "\n",
       "        // index all the tick scales that are listed\n",
       "        var xtickscales = {};\n",
       "        var ytickscales = {};\n",
       "        var add_x_tick_scales = function (element, i) {\n",
       "            xtickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "        var add_y_tick_scales = function (element, i) {\n",
       "            ytickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "\n",
       "        if (xgridlines) xgridlines.selectAll(\"path\").forEach(add_x_tick_scales);\n",
       "        if (ygridlines) ygridlines.selectAll(\"path\").forEach(add_y_tick_scales);\n",
       "        if (xlabels) xlabels.selectAll(\"text\").forEach(add_x_tick_scales);\n",
       "        if (ylabels) ylabels.selectAll(\"text\").forEach(add_y_tick_scales);\n",
       "\n",
       "        root.data(\"xtickscales\", xtickscales);\n",
       "        root.data(\"ytickscales\", ytickscales);\n",
       "        root.data(\"xtickscale\", 1.0);\n",
       "    }\n",
       "\n",
       "    var min_scale = 1.0, max_scale = 1.0;\n",
       "    for (scale in xtickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    for (scale in ytickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    root.data(\"min_scale\", min_scale);\n",
       "    root.data(\"max_scale\", max_scale);\n",
       "\n",
       "    // store the original positions of labels\n",
       "    if (xlabels) {\n",
       "        xlabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"x\", element.asPX(\"x\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    if (ylabels) {\n",
       "        ylabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"y\", element.asPX(\"y\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    // mark grid lines and ticks as in or out of scale.\n",
       "    var mark_inscale = function (element, i) {\n",
       "        element.attribute(\"gadfly:inscale\", element.attribute(\"gadfly:scale\") == 1.0);\n",
       "    };\n",
       "\n",
       "    if (xgridlines) xgridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (ygridlines) ygridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (xlabels) xlabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "    if (ylabels) ylabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "\n",
       "    // figure out the upper ond lower bounds on panning using the maximum\n",
       "    // and minum grid lines\n",
       "    var bounds = root.plotbounds();\n",
       "    var pan_bounds = {\n",
       "        x0: 0.0,\n",
       "        y0: 0.0,\n",
       "        x1: 0.0,\n",
       "        y1: 0.0\n",
       "    };\n",
       "\n",
       "    if (xgridlines) {\n",
       "        xgridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.x1 - bbox.x < pan_bounds.x0) {\n",
       "                        pan_bounds.x0 = bounds.x1 - bbox.x;\n",
       "                    }\n",
       "                    if (bounds.x0 - bbox.x > pan_bounds.x1) {\n",
       "                        pan_bounds.x1 = bounds.x0 - bbox.x;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (ygridlines) {\n",
       "        ygridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.y1 - bbox.y < pan_bounds.y0) {\n",
       "                        pan_bounds.y0 = bounds.y1 - bbox.y;\n",
       "                    }\n",
       "                    if (bounds.y0 - bbox.y > pan_bounds.y1) {\n",
       "                        pan_bounds.y1 = bounds.y0 - bbox.y;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // nudge these values a little\n",
       "    pan_bounds.x0 -= 5;\n",
       "    pan_bounds.x1 += 5;\n",
       "    pan_bounds.y0 -= 5;\n",
       "    pan_bounds.y1 += 5;\n",
       "    root.data(\"pan_bounds\", pan_bounds);\n",
       "\n",
       "    root.data(\"zoompan-ready\", true)\n",
       "};\n",
       "\n",
       "\n",
       "// drag actions, i.e. zooming and panning\n",
       "var pan_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        root.data(\"dx\", 0);\n",
       "        root.data(\"dy\", 0);\n",
       "        root.data(\"tx0\", root.data(\"tx\"));\n",
       "        root.data(\"ty0\", root.data(\"ty\"));\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        dx /= px_per_mm;\n",
       "        dy /= px_per_mm;\n",
       "\n",
       "        var tx0 = root.data(\"tx\"),\n",
       "            ty0 = root.data(\"ty\");\n",
       "\n",
       "        var dx0 = root.data(\"dx\"),\n",
       "            dy0 = root.data(\"dy\");\n",
       "\n",
       "        root.data(\"dx\", dx);\n",
       "        root.data(\"dy\", dy);\n",
       "\n",
       "        dx = dx - dx0;\n",
       "        dy = dy - dy0;\n",
       "\n",
       "        var tx = tx0 + dx,\n",
       "            ty = ty0 + dy;\n",
       "\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\"));\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        set_plot_pan_zoom(root, root.data(\"tx0\"), root.data(\"ty0\"), root.data(\"scale\"));\n",
       "    }\n",
       "};\n",
       "\n",
       "var zoom_box;\n",
       "var zoom_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        var bounds = root.plotbounds();\n",
       "        var width = bounds.x1 - bounds.x0,\n",
       "            height = bounds.y1 - bounds.y0;\n",
       "        var ratio = width / height;\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        x = xscalable ? x / px_per_mm : bounds.x0;\n",
       "        y = yscalable ? y / px_per_mm : bounds.y0;\n",
       "        var w = xscalable ? 0 : width;\n",
       "        var h = yscalable ? 0 : height;\n",
       "        zoom_box = root.rect(x, y, w, h).attr({\n",
       "            \"fill\": \"#000\",\n",
       "            \"opacity\": 0.25\n",
       "        });\n",
       "        zoom_box.data(\"ratio\", ratio);\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        var bounds = root.plotbounds();\n",
       "        if (yscalable) {\n",
       "            y /= px_per_mm;\n",
       "            y = Math.max(bounds.y0, y);\n",
       "            y = Math.min(bounds.y1, y);\n",
       "        } else {\n",
       "            y = bounds.y1;\n",
       "        }\n",
       "        if (xscalable) {\n",
       "            x /= px_per_mm;\n",
       "            x = Math.max(bounds.x0, x);\n",
       "            x = Math.min(bounds.x1, x);\n",
       "        } else {\n",
       "            x = bounds.x1;\n",
       "        }\n",
       "\n",
       "        dx = x - zoom_box.attr(\"x\");\n",
       "        dy = y - zoom_box.attr(\"y\");\n",
       "        if (xscalable && yscalable) {\n",
       "            var ratio = zoom_box.data(\"ratio\");\n",
       "            var width = Math.min(Math.abs(dx), ratio * Math.abs(dy));\n",
       "            var height = Math.min(Math.abs(dy), Math.abs(dx) / ratio);\n",
       "            dx = width * dx / Math.abs(dx);\n",
       "            dy = height * dy / Math.abs(dy);\n",
       "        }\n",
       "        var xoffset = 0,\n",
       "            yoffset = 0;\n",
       "        if (dx < 0) {\n",
       "            xoffset = dx;\n",
       "            dx = -1 * dx;\n",
       "        }\n",
       "        if (dy < 0) {\n",
       "            yoffset = dy;\n",
       "            dy = -1 * dy;\n",
       "        }\n",
       "        if (isNaN(dy)) {\n",
       "            dy = 0.0;\n",
       "        }\n",
       "        if (isNaN(dx)) {\n",
       "            dx = 0.0;\n",
       "        }\n",
       "        zoom_box.transform(\"T\" + xoffset + \",\" + yoffset);\n",
       "        zoom_box.attr(\"width\", dx);\n",
       "        zoom_box.attr(\"height\", dy);\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var zoom_bounds = zoom_box.getBBox();\n",
       "        if (zoom_bounds.width * zoom_bounds.height <= 0) {\n",
       "            return;\n",
       "        }\n",
       "        var plot_bounds = root.plotbounds();\n",
       "        var zoom_factor = 1.0;\n",
       "        if (yscalable) {\n",
       "            zoom_factor = (plot_bounds.y1 - plot_bounds.y0) / zoom_bounds.height;\n",
       "        } else {\n",
       "            zoom_factor = (plot_bounds.x1 - plot_bounds.x0) / zoom_bounds.width;\n",
       "        }\n",
       "        var tx = (root.data(\"tx\") - zoom_bounds.x) * zoom_factor + plot_bounds.x0,\n",
       "            ty = (root.data(\"ty\") - zoom_bounds.y) * zoom_factor + plot_bounds.y0;\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\") * zoom_factor);\n",
       "        zoom_box.remove();\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        zoom_box.remove();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onstart = function(x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var scalable = root.hasClass(\"xscalable\") || root.hasClass(\"yscalable\");\n",
       "    var zoomable = !event.altKey && !event.ctrlKey && event.shiftKey && scalable;\n",
       "    var panable = !event.altKey && !event.ctrlKey && !event.shiftKey && scalable;\n",
       "    var drag_action = zoomable ? zoom_action :\n",
       "                      panable  ? pan_action :\n",
       "                                 undefined;\n",
       "    root.data(\"drag_action\", drag_action);\n",
       "    if (drag_action) {\n",
       "        var cancel_drag_action = function(event) {\n",
       "            if (event.which == 27) { // esc key\n",
       "                drag_action.cancel(root);\n",
       "                root.data(\"drag_action\", undefined);\n",
       "            }\n",
       "        };\n",
       "        window.addEventListener(\"keyup\", cancel_drag_action);\n",
       "        root.data(\"cancel_drag_action\", cancel_drag_action);\n",
       "        drag_action.start(root, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.update(root, dx, dy, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onend = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    window.removeEventListener(\"keyup\", root.data(\"cancel_drag_action\"));\n",
       "    root.data(\"cancel_drag_action\", undefined);\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.end(root, event);\n",
       "    }\n",
       "    root.data(\"drag_action\", undefined);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_scroll = function(event) {\n",
       "    if (event.shiftKey) {\n",
       "        increase_zoom_by_position(this.plotroot(), 0.001 * event.wheelDelta);\n",
       "        event.preventDefault();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseover = function(event) {\n",
       "    this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseout = function(event) {\n",
       "     this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomout_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), -0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomin_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), 0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_track_click = function(event) {\n",
       "    // TODO\n",
       "};\n",
       "\n",
       "\n",
       "// Map slider position x to scale y using the function y = a*exp(b*x)+c.\n",
       "// The constants a, b, and c are solved using the constraint that the function\n",
       "// should go through the points (0; min_scale), (0.5; 1), and (1; max_scale).\n",
       "var scale_from_slider_position = function(position, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return a * Math.exp(b * position) + c;\n",
       "}\n",
       "\n",
       "// inverse of scale_from_slider_position\n",
       "var slider_position_from_scale = function(scale, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return 1 / b * Math.log((scale - c) / a);\n",
       "}\n",
       "\n",
       "var increase_zoom_by_position = function(root, delta_position, animate) {\n",
       "    var scale = root.data(\"scale\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\");\n",
       "    var position = slider_position_from_scale(scale, min_scale, max_scale);\n",
       "    position += delta_position;\n",
       "    scale = scale_from_slider_position(position, min_scale, max_scale);\n",
       "    set_zoom(root, scale, animate);\n",
       "}\n",
       "\n",
       "var set_zoom = function(root, scale, animate) {\n",
       "    var min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"scale\");\n",
       "    var new_scale = Math.max(min_scale, Math.min(scale, max_scale));\n",
       "    if (animate) {\n",
       "        Snap.animate(\n",
       "            old_scale,\n",
       "            new_scale,\n",
       "            function (new_scale) {\n",
       "                update_plot_scale(root, new_scale);\n",
       "            },\n",
       "            200);\n",
       "    } else {\n",
       "        update_plot_scale(root, new_scale);\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "var update_plot_scale = function(root, new_scale) {\n",
       "    var trans = scale_centered_translation(root, new_scale);\n",
       "    set_plot_pan_zoom(root, trans.x, trans.y, new_scale);\n",
       "\n",
       "    root.selectAll(\".zoomslider_thumb\")\n",
       "        .forEach(function (element, i) {\n",
       "            var min_pos = element.data(\"min_pos\"),\n",
       "                max_pos = element.data(\"max_pos\"),\n",
       "                min_scale = root.data(\"min_scale\"),\n",
       "                max_scale = root.data(\"max_scale\");\n",
       "            var xmid = (min_pos + max_pos) / 2;\n",
       "            var xpos = slider_position_from_scale(new_scale, min_scale, max_scale);\n",
       "            element.transform(new Snap.Matrix().translate(\n",
       "                Math.max(min_pos, Math.min(\n",
       "                         max_pos, min_pos + (max_pos - min_pos) * xpos)) - xmid, 0));\n",
       "    });\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var min_pos = this.data(\"min_pos\"),\n",
       "        max_pos = this.data(\"max_pos\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"old_scale\");\n",
       "\n",
       "    var px_per_mm = root.data(\"px_per_mm\");\n",
       "    dx /= px_per_mm;\n",
       "    dy /= px_per_mm;\n",
       "\n",
       "    var xmid = (min_pos + max_pos) / 2;\n",
       "    var xpos = slider_position_from_scale(old_scale, min_scale, max_scale) +\n",
       "                   dx / (max_pos - min_pos);\n",
       "\n",
       "    // compute the new scale\n",
       "    var new_scale = scale_from_slider_position(xpos, min_scale, max_scale);\n",
       "    new_scale = Math.min(max_scale, Math.max(min_scale, new_scale));\n",
       "\n",
       "    update_plot_scale(root, new_scale);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragstart = function(x, y, event) {\n",
       "    this.animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    // keep track of what the scale was when we started dragging\n",
       "    root.data(\"old_scale\", root.data(\"scale\"));\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragend = function(event) {\n",
       "    this.animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "var toggle_color_class = function(root, color_class, ison) {\n",
       "    var guides = root.selectAll(\".guide.\" + color_class + \",.guide .\" + color_class);\n",
       "    var geoms = root.selectAll(\".geometry.\" + color_class + \",.geometry .\" + color_class);\n",
       "    if (ison) {\n",
       "        guides.animate({opacity: 0.5}, 250);\n",
       "        geoms.animate({opacity: 0.0}, 250);\n",
       "    } else {\n",
       "        guides.animate({opacity: 1.0}, 250);\n",
       "        geoms.animate({opacity: 1.0}, 250);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.colorkey_swatch_click = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    var color_class = this.data(\"color_class\");\n",
       "\n",
       "    if (event.shiftKey) {\n",
       "        root.selectAll(\".colorkey text\")\n",
       "            .forEach(function (element) {\n",
       "                var other_color_class = element.data(\"color_class\");\n",
       "                if (other_color_class != color_class) {\n",
       "                    toggle_color_class(root, other_color_class,\n",
       "                                       element.attr(\"opacity\") == 1.0);\n",
       "                }\n",
       "            });\n",
       "    } else {\n",
       "        toggle_color_class(root, color_class, this.attr(\"opacity\") == 1.0);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "return Gadfly;\n",
       "\n",
       "}));\n",
       "\n",
       "\n",
       "//@ sourceURL=gadfly.js\n",
       "\n",
       "(function (glob, factory) {\n",
       "    // AMD support\n",
       "      if (typeof require === \"function\" && typeof define === \"function\" && define.amd) {\n",
       "        require([\"Snap.svg\", \"Gadfly\"], function (Snap, Gadfly) {\n",
       "            factory(Snap, Gadfly);\n",
       "        });\n",
       "      } else {\n",
       "          factory(glob.Snap, glob.Gadfly);\n",
       "      }\n",
       "})(window, function (Snap, Gadfly) {\n",
       "    var fig = Snap(\"#img-7805c341\");\n",
       "fig.select(\"#img-7805c341-5\")\n",
       "   .init_gadfly();\n",
       "fig.select(\"#img-7805c341-7\")\n",
       "   .plotroot().data(\"unfocused_ygrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-7805c341-7\")\n",
       "   .plotroot().data(\"focused_ygrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-7805c341-8\")\n",
       "   .plotroot().data(\"unfocused_xgrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-7805c341-8\")\n",
       "   .plotroot().data(\"focused_xgrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-7805c341-15\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-7805c341-15\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-7805c341-15\")\n",
       "   .click(Gadfly.zoomslider_zoomin_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "fig.select(\"#img-7805c341-17\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-7805c341-17\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-7805c341-17\")\n",
       "   .click(Gadfly.zoomslider_track_click);\n",
       "fig.select(\"#img-7805c341-18\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-7805c341-18\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-7805c341-18\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-7805c341-18\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-7805c341-18\")\n",
       "   .drag(Gadfly.zoomslider_thumb_dragmove,\n",
       "     Gadfly.zoomslider_thumb_dragstart,\n",
       "     Gadfly.zoomslider_thumb_dragend)\n",
       ";\n",
       "fig.select(\"#img-7805c341-19\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-7805c341-19\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-7805c341-19\")\n",
       "   .click(Gadfly.zoomslider_zoomout_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "    });\n",
       "]]> </script>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "Plot(...)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Mads.plotmatches(md, calib_predictions, r\"w20\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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   "mimetype": "application/julia",
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