Erlang-min-diffs.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Precompiling module ProgressMeter...\n"
     ]
    }
   ],
   "source": [
    "using Interact\n",
    "using Gadfly\n",
    "using Distributions\n",
    "using ProgressMeter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "function sampl(\n",
    "    a=10, #Shape parameter of underlying Erlang noise\n",
    "    n=10000, #Number of trials in both benchmarks\n",
    "    t=10000, #Number of comparisons to simulate\n",
    "    )\n",
    "\n",
    "    const mydist = Erlang(a, 1.0)\n",
    "    diff=zeros(t)\n",
    "    for it=1:t\n",
    "        x=Inf\n",
    "        y=Inf\n",
    "        @showprogress for i=1:n\n",
    "            x=min(x,rand(mydist))\n",
    "            y=min(y,rand(mydist))\n",
    "        end\n",
    "        diff[it]=x-y\n",
    "    end\n",
    "    diff\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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-b063c246\");\n",
       "fig.select(\"#img-b063c246-5\")\n",
       "   .init_gadfly();\n",
       "fig.select(\"#img-b063c246-7\")\n",
       "   .plotroot().data(\"unfocused_ygrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-b063c246-7\")\n",
       "   .plotroot().data(\"focused_ygrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-b063c246-8\")\n",
       "   .plotroot().data(\"unfocused_xgrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-b063c246-8\")\n",
       "   .plotroot().data(\"focused_xgrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-b063c246-14\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-b063c246-14\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-b063c246-14\")\n",
       "   .click(Gadfly.zoomslider_zoomin_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "fig.select(\"#img-b063c246-16\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-b063c246-16\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-b063c246-16\")\n",
       "   .click(Gadfly.zoomslider_track_click);\n",
       "fig.select(\"#img-b063c246-17\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-b063c246-17\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-b063c246-17\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-b063c246-17\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-b063c246-17\")\n",
       "   .drag(Gadfly.zoomslider_thumb_dragmove,\n",
       "     Gadfly.zoomslider_thumb_dragstart,\n",
       "     Gadfly.zoomslider_thumb_dragend)\n",
       ";\n",
       "fig.select(\"#img-b063c246-18\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-b063c246-18\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-b063c246-18\")\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": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot(x=sampl(1, 2, 10^6), Geom.histogram(density=true), Geom.density, Guide.xlabel(\"pdf\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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emoKOJYSovtBOizhO9twlS5ZEg84hBs91vYTjtJ8UdA4xSKo8clFD3L8vguyPEHKtrd47M5n244LOISrDcbKfq1ZZoe1cMNOMUmm0nF0wBPg+TwDU+4LOIQahhSMALoDGwSZzeUM0hmyMFnKmqQ5hVkcGnUNUBrM6o1plhXbNhVLq++vWje0NOoeohNILQPSNoFOIQSjABONIENDD1AWCCYIsuA4530eLYeiXgs4hKkVfXa2SZM2FEGLwnuU69KIbAMDYCMIIAG9iOlVtu2EhxL4jtNMitp37nux5PzS0tbU32XZ2VtA5RGW8teaCZM1F2KXT3tG2nZsRdA5RGY7j3VitskLbuQDY2rSpzgg6hRi8YpFGEtHEoHOIylCEcr1kmHiMZWokxAxDjVGKY0HnEJXBTFOrVVZo11xEo3ze5Mlju4POIQZv5Eg839lJmaBziMroAXUDGA4AqMMwALI2KqSKRfPPQP6ZoHOIymCm06tVlqy5EEIM3o7XXDB8TMIHqT3YcEKIagvttIhte4+57muyA+AQkE5n3+843reCziEqo05xf73shdE3giFCyXU7TnNd78qgc4jKsO1c1UahQtu5UApvFouag84hBo9IlYjQE3QOUSHcVy0JPSDI3SIhRqSLzFI3hwoi7qxaWdUqSAgxhO14WuQ1MC7AB+jRYMMJIaottCMXra0rJjFzaPOLzZYuXTosne44KOgcYhC68NZW/Irealdk5CLkbDu7X1tb+9igc4jKcN32w6pVVmg/nJXyb85kVsv2wkNAd3dNs1L64qBziEEwN3ciaoj762UPWNZchJlSxnFaq7OCziEqQ2vj9mqVFdpbUQFyhg/P+0GnEIMXifD6UglyR0GYlY9bBwBohg/ABCEPyMhFmPm+XkNEslfJEEHErVUrq1oFCSGGsL/ze1DEcwA2r7kgPAfGE5hO1wQbTghRbaGdFslkvJMXL+YQj7yIfi0t3oHpdMe0oHOIQejdPP1hUt+IKMu0SNil0+2xtrb2pqBziMpw3dyp1Sprr384z501ez4DswvR4pjbb7/9DQC4dNallgItZGAEgV5mzWcsuHfB2t15Xd/H3FGjVv8VQGmvBBdVoxQfqpQ+AUBL0FnEHlKbOxER4poSE1Be0CmdixAzDDOptT4UgOygOwRojSsBPFyNsvbqyMXsc2Yfx0yjsM32vwp0J2tcu2DhggRIO6RoDzZQoruLxZWFCkUVAYpE/HYi9WTQOcQgbNG5KALlein7XIReqUQvMOu/Bp1DVAr/tFol7bWRi8tnXF5XpMJ1Jb90mmkYn+j//iXnXTIRGuMW3LvgIQBASd0Gg58HMHt3Xj+Vij1Y2cQiKFOmTFoBYEXQOcQg6M2di5KmIgiARg8IIwNMJQZp6tTxrwSdQVROKhW/v1pl7bWRi1JD4TsEvu22+257fcvvm4zxAFYCYABY3bO6A8DouXPn7taKZMfJzV22bJmsYh4CHGf5oa7bcVrQOcQgbDFCEaW+k1AV8jItEm7pdHvStnMnBp1DVEY1t3LfKyMXs8+dfRQzjpi/8JYrBvM6juM9APBoy0qclE4vG2MYkfuZ+QXLSnwe4M92dUU+7jjZRZaVuM1xshcT0SeJ9Lebmib+1XGyNxHRZN8vntHcfMgax8k+AdBay4qf3trqvdM0cTMz/c2yYt9yHO8TRLhEa7o9lYo9aNve15XC8cz0BcuKLXEc7+dEGNvUFPvQCy+s3K9U8n/FjJcsKz7HcXLvI+KrtcZDqVR8gW3nLlSKZzLje5YVX+w43o1EmGKafNYRRyRecxzvcSJ0JpPxmY6z/FAiYwEzP2tZiattO/v/lKI5AN+ZTCZ+6TjZrxLRCUrpK6ZMmZix7ew9StFBxeIbHwFG1kcixq+1xrJUKn5pOu0dbRj4FkAPJ5Oxmx3HO48Ip2tN16VSsScdx7ueCElmY5Zljf+v43iPAOi1rPgn29o6DtZa38aMf1pW/BuOkzuFiD+vNRamUvFf2Lb3JaVwEjO+bFlx23FydxPxuOHD+dTu7gazVOr+HTO3W1bic47TfiSR+q7W/GgqlfiJbWfPUYrOBPiGZDLxR8fJ/pCImotF//xp0w7ucJzsH8pTZ/op285mlKI7tKZ/p1Kxr2Uy3snM+CJA9yWTsXsdx/siEU72fXVVc/OEFsfxfkaEGFD7sa6uom5o8P/AjJxlxS/IZHJTmfkHzPijZcVvcJzcmUR8jtb4SSoVf9S2c99Tit8N4KJkMp51HO93AEzLip/a1vbKeK3Nu5g5bVmJrzhO+0lE6kta8y9SqcRC1819HuBTAP7fZDLxvONkf0pEE/P54idHj0Zvd3fkEWZaaVmxc207aylFP9KankylYte5bvZ0gM4D6OZkMvaw43jfJsJ7SiXjkqlTx7/iON6vmVGfSsU/kk53HGQY+h5muJYVv9J1cycA/FUAv0wm43c6jjeHCP9Pa1ydSsWftW3vFqVwCBHNXLt2QueoUbnHmfGaZcXPymRWTGH2bwT4qWQy8X3Hyc0k4gu15gWpVOIh285eoxQdA+g5yeTElxwn+ytA7WdZsQ+1tbWP1Vr9HKD/JJOxy207e7xS9HVmetCyYre7bvaSb3Z1nf/73vKRIhFCtMBAAzS6WA13Xe9JrbEmlYqfkU7nJhsG38SMZywr/h3X9T4J4GIAtyWT8d84jvcNIhzn+/T55ubYC7bt3a8UxjQ1xU5qbX11dCRSeIAZL1pW/DLX7TgW0N8E+LfJZOJWx8ldRMQztObvplKJp207+xOl6Ail9JlTpkxc7Ti5PwF6g2UlPl3eTEjNB+jvyWTsWtvOfkwpms1Md1hWbJHrel8DMJ3I+GJT0/g2x/HuI8IB69bFTh49umMYMy8C8HIyGZ9t2957lcK1zPi9ZcXnu653PoDPAPSDZDL2F8fxbiBCk++rc5qbJ6yybe8xInRbVvxTtr38EKWMW5jxnGXFv1lecMeXAXxXMpl4wLZzX1aKT/R9fWVz80TXdXMLAf6f+vriKWvXoqauLvIbZlpuWbGLXTf7HoC+DdAjyWTsJtvOzlKKPsusf2RZE59wXe86ACnAPDeZHLfScbyHAZQsK/7xTCY3kZl/qjX+lUrFv27b3keVwheY0UbEqxzHayLChwF8JZmMpx3Hu5MIE7q6jNMaGiIK6HlIa3ipVPxC2+54t1L6e8x43LLiN7pu7myAzyLCjU1N8ccdJ/d9Ip7m+/qC5uaJOdfNPcSslWUlTkun22OGoX7GzK2Wlfiq62Y/DNAVWvPPU6nEPbad/YJS9FGt1ddSqQn/dl3vdgAJ06z/eH19V2nTJnqYGSssK36e63rNAH6oNZ5IpeI/sm3vs0phFjPdZFmxR1zX+w6Ao4joc01NsXbH8X4DoMay4qe47spxQOlureGkUvEv2XbuRKX4y8x4wLLid7lu7jKATwX4G8lk4p+Ok7uViCcVi/6ngPXdkcg7HtOaV6VSiXPS6fakYajrmfkvlpX4getmPwPQ+Vrz/FQq8XvHyV5LRO/V2r80lTp4met6i5gxzLLiJy9Zkj2gVKL7mNFmWfEvuq73AQBXaU2LUqnYHbbtzVYKH9OarkmlYv9wHG8+EQ4zTePTkyeP25DJ5P7EjNWWFT/TdTvexcxfs22vJpWKf9e2czOU4ouYcatlxX/rOLlv9vYaC446atxurX/cmb3SuSDQsQCa5sya7fV9qyZaiKTnnjv3wyUqrTDKoxcEgMfWjp0A8Np58+ZtdyxzqeRfHI2aCgBSqUlr29o6ZtbU9PQt4NSXlUq17YWC3wUA3d3mPY2N+leGke8CgNra3v8tFOrMVGrSRgBQSn26UChpANi0KbZs9OiOmUBNAQAaGoqP5vPRxfvtp/Pl59b+hKj3lnXrJnT25ZgdjZqKiDQzbyjnyJfKj615PhodM9P3I70AkM+rnzc26l+b5pt9OXquLhTqzMmTY3056Iz+HC+/PHH54Yd3zDTN+iIANDaW/pjPR/86bBjnAYCobh5R70/feCPRCQC+ry8zDFNNmzatyMyb2to6Zvb2FnwA0PqNFtMcM7NQKOfo7jYeaGzUv4tG38pxbaFQZzY1jdsIAMx8Zv91fvHF8V45R12xfD0KT+bz0X9scT1uIer9Wf/16OkpfL6+PmrE47FeAL1tbR0z8/miX74e6+zy9Yj2XQ9zUWOj/kNdXbEbACKRhm/7fj7S3j5xUzkHzgZ4P8MwjBdfHL/i8MM7Zkaj5Rx1dcWn8vnoP998U/WUXzt6WzRavFvr198s5yh+sb4+akyZMrYbAMo5ytejUFiTiUbHzCwWy9djxAj9685O9WhjY6EbAKLRuu/5fj6ydOmEvhx87ubrcfCqLX8vkUj+ad9v/Hc+b/QAQLEYuSMaLd5bKLzRl6P0pfr6qHHUUZM6t82xYUP8P6NHd8xUqvxeGz4cv+vspD/W1RX6rkf9D30/H1m+fFx/jgsMQ1H5PT/+tS3fa6b55t98vzG9xfW4Kxot/sL317wJAL29xa+Wr8eEjUSkM5nczGKx/F5bu3bci6NHd8xkri30XY8/dHaqJxsbi33Xo+F638/ftHZtou89ry+KRpUCgHe9K7Gmra1jZjRazhGNdj/r+40zu7pU3/WouefJUsORAGYBQA9TN4DGPNQGEIYT0XG+X86xceOEl7ese8OH86OdneqpYcN033u+9kai3vkbN07oe8/7lxiGqYiImXnd1tej83nfb5xZKET73vPqvsZG/WA02tVVfv/0fqNQqDPf9a5EX93DZwoFrQFg3brE8tGjO2YaRl1/3Xs8n48+M3x4OQdQexNR761r147rbwPmRKOmmj6dSsy8sa2tY2Z3d/l37Ptv/NswNr/XurqM+xsb9W8N4626d025LRq/EQAMgz7r++VzkZYtm9i+Zd2rry88kc9H/97fBihVs4Co946NG8u/l2Kx9Plo1FSTJk0qTJqEwpbvtWJxbWs0urkNyOfNXzU26t+bZrlNrKnp+XahUGcuXfo//e+1tzbHWrp0Qm7LutfYWPxzPh99Fig0+L5haF27Jhot3lUorOmve5fX10eNo48e19P/nu9vi3z/dWfr66EebGzUD29+z9d91/fzkVdeSWwCAK31rP4cr7ySWLll3auvLy3O56PP99c936+53TCK9/h+uQ3I54tX1tdHjcmTx3QBY7D19XijLRod81bd228//k1np3qsvr6cwzTrf7BNG3B+f46XXvqfVw8/vGNmXV3/e/7NZ3y/sWXzez7ys2i0eN/mNqDwlfr6qDF16sRNRMSZTG6m7/t97/nEkvJ7vra/DXios5P+1F/3IpGGH/l+PrJsWblNLBb9C/s/9yZPjr++9Xu+6+++3zgzn1d91yN6t2EU7+9vA2pre64qf96M264NWLdu/NLhw3OfMs3a58vXQz/c2an+3H89iGpuOPLIsXmEyZxZs3suuuiid7z19bmXpufOuvQTADB71uzr5p4z+5bg0gkhBu1pvh+LmbGYGU/xhr7//zUWczee5ncHHU8IUV2B7HNBvnE+g66Zc87sFQRYUOrq3X0Nx/HuevbZFbL99xDgOO1HOk728qBziEHQGNH/z1ri+r5/Hg2gDgxZTxNSrps7wXW9C4LOISqjvNSgOqqyCdX8hQtqt/x63r3zbACD2piFGQeU5/pE2GlNdUqR3FUQZgrD0H/SOoHAAAgaAMCbDzUTYUMNAO8XdApRGcxUtQMiQ7vDZTRaP3Py5DHdQecQg7dxY/wfNTUr/xV0DjEIW+zE2aPRDcJwEHRfJ0Pu6gqpYvH1x0ePHv1E0DlEZdTV5U+pVlnyl78QYvB2dMsp949lSOdCiP9rQtu5KBS6F2Uyq+sHfqbY140Y4R1TX+9fFXQOMQhbjFzUKtRv85h0LkIqEtn/5E2baE7QOURl5PN1j1SrrNB2LojwSldXUQedQwyeYVAnwKuCziEGYYtNtDSwbb2UzkVIEZU2MNNrQecQlcIvV6skOXJdCDE4i7kWwOb74/uPXNiW5nUAACAASURBVAdyAGIAfoPp9KmA0gkhAhDakQvH8VKLFrERdA4xeJlMbmRbW8fBQecQe6iw9XoLRdvUSy0jF2GVTi8bk063x4LOISojne6YVq2yQtu5YMZ3Dztsde3AzxT7ulJJN/m+PifoHGIPRTEcvHkqpIawdb005FbUsDKMmqMNQ80IOoeoDCK+oVplhfZWVCJ6vL6+sxR0DjF4SulXiSItQecQe4gxAoROoLyRls8oYcu2RRZ0hpbvl3JERri2hBY7pRQ/XK2yZM2FEGJwnubpAO5B+cygHa25+Cem09EBJhRCVFlop0UcJ3vukiVLZLh1CHBdL+E47ScFnUPsIY3h0Ojs/zJCvG29lJGLkGpt9d6ZybQfF3QOURmOk/1ctcoKbeeCmWaUSqMjQecQg+f7PAFQ7ws6h9hDCsOhsKn/S5Owdb2UaZHQMk11CLM6MugcojKY1RnVKiu0ay4MA/PWrh273THtIny0ppcB1RV0DrGHGCPA2NQ/yVpk6sWWbYts/x1avl9yIxF4QecQlaEUrq9WWbLmQggxOE/x16CQAqO8l8X2ay5WYjqNDzKiEKK6QjstYtu572WzWbkVdQhoa2tvsu3srKBziD1EGAbGm/1f1hBvWy9l5CKk0mnvaNvOya2oQ4TjeDdWq6zQTosAbG3aVCebaA0BxSKNVIomBp1D7IHFPAmMy/sOWQcAKIKx+SvImosQMww1BtCyidYQwUxTq1VWaDsX0SifN3nyWDlyfQgYORLPd3ZSJugcYg8wjG3XVPSAuoEtdu2UNRehVSyafwbyzwSdQ1QGM51erbJkzYUQYs89xYeBsHSr722/5oLxDExcQ3LQoBD/R4R2zYXreotaWlbJketDgG3njnFd72tB5xCVUUe6YZtvEY5EYyBhxKBkMt7JjuPJketDhON4cuS6EGIIaShvDS6E+L9BpkWEEHtu16ZFigCaMZ3+E0BCIUQAQjty0dq6YhIzhza/2Gzp0qXD0umOg4LOISpD0XbtSgF662PZRTjYdna/trb2sUHnEJXhuu2HVaus0H44K+XfnMmsrgs6hxi87u6aZqX0xUHnEHuAth/9rCHeul4yemHItEgYKWUcp7U6K+gcojK0Nm6vVlmhvRUVIGf48LwfdAoxeJEIry+V0B50DrEHFOqwzT0gmuFj67alByydizDyfb2GiORW4iGCiFurVla1ChJCDEFP8ftBeHqr722/5iILxg/wAaraX01CiGCFdlokk/FOXryYQzzyIvq1tHgHptMd04LOIfYAYdi23zJpuxHRXigZuQijdLo91tbW3hR0DlEZrps7tVplhbZz4fuYO2rUahmuGwKU4kOV0qcFnUPsAb195yJCvHW9ZPTKtEg4GYaZ1FqdFHQOURla48pqlRXiv/zp7mJxZSHoFGLwIhG/Xeuo7N4YRrz9XSBFoICt25beHT1P7PtKJXrBMPRrQecQlcI/rVZJsuZCCLHnFvMVAK7f6nvbr7n4GwhZHE/nBJBQCBGA0E6LOE5u7rJly2RaZAhwnOWHum6HTIuE0Q5GJKLbTovI3SKhlU63J207d2LQOURluK5XtWmR0HYumPnk7u5hIZ7WEf20Vgcya1nQGUZq+zNDjG0XdDIKgEyLhJFhmDGlOBl0DlEZWlPVFnSG9sOZCF9/6aWxPUHnEINnmipDRCuDziH2gMawbSdXexk9wBadDkIPCAdWN5ioBN/vfQ4w3KBziMpgpiuqVZasuRBC7LnF/EsAn97qe9uuuWDcD8JRmE6TgogohKi+0E6LOI5387PPrpDtv4cA1/WaHScr23+H03bTIjWKt62XvYCsuQijTKb9OMfJnRl0DlEZtu3dUa2yQtu5YMakhoZIaPOLzXyfhwEkB5eF03ZrKdS27YpCHsB+YJaR0pBhNvcj4gOCziEqhQ6tVkmh/XCORutnNjWN7Q46hxi8jRvj/+juNr4fdA6xB3Zwt0iPRvc2zxkLwMRifKRasURlFIuvPz58OM8POoeojLq6/CnVKiu0nQshxD6Atp8W2YF39f3/eXszihBi3xHazkWh0L0ok1ldH3QOMXgjRnjH1Nf7VwWdQ+yR7UYuahW2rpcE7vuX7EsTMpHI/idv2kRzgs4hKiOfr3ukWmWF+VbU17q6irJl9BCgFOcBrA86h9gj250twvxWZ2JrhOheTyMqjLsAbAg6hagMIl5VtbKqVZAQYoh5luvQi+3XPW17KyphKRiHg/EMPkDHVzumEKL6Qjst4jheatEiNoLOIQYvk8mNbGvrODjoHGI39WL0jr6taCf1UkYuQiedXjYmnW6PBZ1DVEY63VG1nZBD27lgxncPO2x1bdA5xOCVSrrJ97UcahU2PkYByG/77RrCzuqldC5CxjBqjjYMNSPoHKIyiPiGapUV4jUX9Hh9fWcp6Bxi8JTSrxJFWoLOIXaTidFgbACw1aZZPqOEHbUtLAs6w8b3SzkiY7sOpAgnpfjhapUlay6EEHtmMX8KwLcAvHOr7+98zcXL+AAdFkBSIUSVhXZaxLZzM1paWiJB5xCD19b2ynjX7Tg26Bxit43GDu4kMBXvuF7KmovQaW1dMclx2o8MOoeoDNv2zqhWWaHtXAB8biQyThqrIaBYNCYy6xODziF2E2EUaPvORWRnaytYOhdhY5o8mUgdF3QOUSn0uWqVtNfWXMyZNfsvAA4DQGB+wSR94U8W3uYBwKWzLrUUaCEDIwj0Mms+Y8G9C9buzusbBuatXTu2dy9EF1WmNb0MqK6gc4jdxBgNYOO23y4y9WLHbYusuQgZ3y+5kQi8oHOIylAK11etrL31woY2z52/cMG4+QsXjAPo3yWoH2wulO5kjWsXLFyQAGmHFH1rd1+/qSn++PTpJAs6h4Bp0+KvNjdPkAWdYcMYhR1Mi5TKCzq3J9MiodPcPDE3ZcrETNA5RGUkk7GqLejca52Lm+69qQMArrnmGmKCCdDrAHDJeZdMBDBuwb0LHgIAlNRtAO/2rU62nfteNpuVW1GHgLa29ibbzs4KOofYTQqjobcfuaghlltRh4h02jvatnNyK+oQ4TjejdUqa6+uuZgza/Zf3vDWbCLgI35BXw0AJmM8gJVAeYvg1T2rOwCMnjt37m4OmbK1aVOdbKI1BBSLNJKIJgadQ+yGp/gEAKeAcOW2DynCzuplVI5dDxfDUGOUYtlEa4hgpqnVKmuv7nMxf+GCEy666KJIpBj5vlmjbgPw6d35723bu5SIhllW7IdLly4d1tNTdymA/1pW7OdE6ifMvXNd1/tXMhl/ynW9DzDTu5XSv29qSix1nNxZAA6qrc3fcvjhh3c6Tu4rzNyZSsVvSac7DlKKz2LWL6VSiYfS6Y5pSvEJgL/Ysib+y7az/49IHQ6on1vW+P+6bvYSZjU8mZxw3QsvrGkoFvOzifBqMhm713GWHwqYH9carc3NsT/bdvZ4InWU7/Mfpk6Nv2jb3meJaFypVLpt2rSDN9q29yUi5C0rPn/JkuwBxaI6B+BllhX/ret6zcx0IpF+JplM/NNxcqcAOMIwivdPmTJpheNkPweo/V5+ecL1Eye+WmOaxbnMenUqlVjY2rpikmHoTwK+bVkTn8hk2o/T2jiaiB5NJif8x3WzpzOrCUrh9qam2HrH8a4gomIyGbvZdV/ZnzlyLhGWJ5OxX9t21iJSH2Lmv6VS8Wdt2/sIEU3R2v9lc/PEnG3nLiTCqFJpzY2jR482Nm5Unwd4jWXF78pkchO1xgwi7SaTiT86Tu59AI4xDP/xKVMmZhwn+2lAxXt7jZ8dddS4tY6TvRxAVGt1W0vLqneYZvF8AFnLii1qa2tv8n3jZAD/sKzY3zMZ72StqYmIFyWT8azreucz0zsaGgo/KRQKXCw2Xk7EbyST8Ttd10sw00ylONPUFH/ctnPHEOF9Wvt/bG6e6Np2bgYRJmpduKu5+ZA1rpv7PDMblhW/8fnnV46uqfEvALRnWYlfZTIrpmitP0JEzyaTE/7mONkPAcoyDPr1lCkTljtO9lxA7d/drW7u7R1XHDmy4wpmrEulYnek0+0xpYzPMPN/Uqn4o+m0d7RSdBzAT1hW3HZd75PMNMkw/IVTpkxc7Ti5uURck0zGr7ft7H5E6nNEuiOZTDzgOLkjAJyitf5nc3PiGdvOnUiEZubSb1Opg5fZdvYcInUAUc38pqaxedft+BKgN1pW4ra2tlfG+37kDCK8kEzGHnbd7FHM6nil8Oemplir43gfB+jQUonvnTYt/qpte7MBakilYtf985/LhtfWRi9h5pWpVPwXra3eO39R2HD6jT37qR3dzN6/zwURFDOwH+nRG1gBAH07vfbwU53cacx6aSqV+L1td7ybiD/ATE+lUhP+3V/3tKb7mpsnrNpJG7DKsmL3uW77YczGx4jQkkzG/uI43nSAjtyiDTgTwP/09BRufc97Dtlk27kvA9yVSsUXtLR4B5omnQ3wy5YV/10mk5uqNT5IpJ9OJhPPu27Hacz8TiLjF8nkuJWOk70YUCOSyQk/ymRW1zH3zmHWr6VSiXtse/khROYnmJFOpWJPptPZ9yul3gPgEcuKLbFt7wwiGs+sf5pKJTa4rnclM/VaVmxeW1v7WN83ZhHxK8lk/DeO46UAOklr/mtzc/w52/Y+SkTvKpVKD0ybdnCH4+QuAjBy/foJN9TUrIzU1+vLAP26ZSXubmvrONj3+VOAdiwr8SfX7TiWmd+rlHqsqWl8m+tmP8OsYpGIuuOII8avcxzvi0TkJ5Oxm9LpZWOUip7HjPZUKvZgOt2eVMr4MDMcw9D39dc9Zv2rVCrhua53ATONjkTe/HE0GqWurugXdlb3tm8DcjMBJEqlyJ3Tph30hm1nv0AEsqzEjwdqA1w3+2FmlVQKDzY1xdodxzsPoDEjRuib1q5d65vmmC8S8dpkMv4z287GidSnmbktlYo/Ztvee4noWGb9p1Qq4bhu7lPMOJioeHcyOel1181dxswRy4rfsGTJilHFor6QSOeSycQvXbfjXcz8UaX855qaJv7VcdpPAoyU76vfTJ06/hXbzs4iUmNLpci89vYDew89tONKQG+wrMRPW1qWTzBN83QASywr9ojrZt/DrN5PxE8mk/G043ifAOiQSETfc8QRidccx5vDjLpUKv6jlpblI0zTvJiZV6RS8fvT6dxkpXAqs34+lUo8nU7nPqgUpgKl31nWwS+7bu5sZhwYidQtmDx5TJfrdnyZSG9KJhO3uu7Kccylf7tux2nJ5IQ/lO8CMqZrTX9pbp7QYtvZj0WjDX8+4oj939yDj/vt7PVNtG6//fbinFlzfsbgPwNAibDCKI9eEAAeWzt2AsBr582bt93iTKVUm+9zDQDU1NQUu7vRSkQbAcAwSm6xaGil/JUAwOyv1NpUhsHry1/TUmZ+taampggAWqPVMFRv+d/FLsBsjUT49b6vXwfMVgCry69ttpdKuouo1FV+LdWmdXnXwWh0Y7G3N9qqlL8JAIh4g++j1TD8FeXU+r9aq9ba2v4c6iVmXl0oRAvln4nSRH4RADo7S93RaLQV0GvKj5XWFIuRViK8Vn5t8nyfe5SKvNn3Wv9hRt2MGeAXXlhf6u1tbDUMdJaf27NR62iradJKACgWI6uIdKvWem35cfWy72NNqRTpLX8N2/e1X762pXx3d6SVSL9RzhF5w/f9VsPAq305clqjUFMT6Sz/jLxEa6pvb5+qgVYoNabVMPhNACgUIpuUKrYy03/L15JeLRa5VWvzjb7XWub7WFtba/aUX4scZubm5gmrlix5vbG3t9iqFK8FAN+PrNVat5omVpV/JnhEKBaL5qby43gBQMPKlZP8NWvAkyZ1tALoAoCeHnNTJOK3ak2ryj8Tr/J9alUq0peDX9Ga1tfUjMiXX0s7SpECgNpas6f889M6ACiVeC2A1kgEfa+FXKkEv1QyN/Zdyxd9Hyui0dWlo48ep20brUTcXb62kc7eXt2qFPVdS35Va2o1DHNN+b3Hy5lpY21tobv82r7LrEwAyOfN3tpa3Wqaaj0ARCJ6bW+vamU2/9v33A7fNxjQG/pe+0Wt8d+amrVFYCxrjVYilS//DEYnM1oNg14r/7z8GoBWwyi+Xv496eXFotFZKhW7+upeBuAoAIwdaxbWr0croDaU64Bet7Insgw74eOttVAMAAVGT//Xf9hUW/PREV2tpmmuLucorlbKbNW6uFXdK9dRgIgy/XXPMIxC+WeivqkYvV5ro1Wp0gqg3AYwm0Z/G6A1LQX4tbFjzb66h1ZAFcrXo9ilVLQ1EtGvl8spvq51pBXg1/qytmuNbqJif91rY0YdADbNtcXe3sZWpXhT+TG9oXxt/b4c5n+11q01NeW6Zxj0UqmE13t6zP42Lq2UXyr/TgvdxWLdW20AkbnG9/1WIu6ve57W6I1Gzc7ya/N/mKn++OOhW1tXl7Qe81Yb0NtrblSq2GqaWNn3864qFtGqNfctlqeXtcYb+bzR//uwfV/r8vt0RL63N79VG6C1bjUMvXzKlImr0+lcDkCxpuaturcEQMOSJZP9MWNAI0Z0vNUG9Nc938d/+3OUSmgFIn05eJnWtC4SUf2bczkAUfl6qLzv4602oFg03wC4NRIp159SiXJEKPX2Gn11j1/wfWpcu3at394+VW/ZBkSj5qYt655SeLXcVpfbAK31K8xqQ03N8O7yz6RdwyADAPJ5o0cp/VYbUCzqtUpRq+9H+toA6iiVoJmNDX2v/aLvY2Vd3frSjBkHcrkNKP980ajZWSptrnta4zVmtEYipb42QC8HjE2dnaW+NkBnmI0IABQK0YJS+q26V1Oj1/X2qlYi3de++it834Bh8Ia+OrBUa2NVNLqxCIyB1mhVSvWUyym+yaz+aJq0ui/HagCt5c8/wDS5vfzfVcZeGaKcffbs0QBGL7h3wcszZswwDmjY/7sADp+3cMHHAGDOuZemifGdeQtv+e3sWbOvU4zGefcsuHR3ynBdb1GxGJ01bdpB2x+cJELFtnPHKMXvTybj3ws6i9hFT/GHQPjjjh6qgy7loUxsu4kW0AuN43AC/auqWcUeK49Y4GDLis8POosYPMfxHrGs+CnVKGuvjFyYMBt8VXpgzqw5B4LZZ+A5s1S8pP9x8o3zWel75pwz+yYAL0Kpz+6NHEKIvUSjbqcrK3aGUYCx48POhBBDiyyuEkLsvj/zOTCwcIeP7Xz77zdA+AKm0y+qGVUIUX2h3aFzyZLsASwrz4eEbDZbm8nkRgadQ+wGwvCdPrTDZZ4AgN6+jbdESLS0rKpvaVk+IugcojLS6Y6DqlVWaDsXhQLdlcmsrg86hxi89etxlNZ8edA5xG5QO+9c1IJ3Vi97oaRzESaRSOmDkYhxYdA5RGUQ8QPVKiu0R64D5AwfnveDTiEGLxLh9aUS2oPOIXYDYXj5XpDtaYaPHbUtJCMXYeP7eg0RybbtQwQRt1atrGoVJIQYQhbzrQAu3uFjO1tzATgAlmI6nV69oEKIIIR2WiST8U5evJhDPPIi+rW0eAem0x3Tgs4hdgPvfFrEpJ2MiDJ6ARm5CJN0uj3W1tbeFHQOURmumzu1WmWFtnPh+5g7atRqGa4bApTiQ5XSpwWdQ+yWnS7yixDvrF72gqRzESaGYSa1VicFnUNUhtbbb9e/t4T2L38iftA011ZsNzERHMOgDmb996BziN0ybGcPlBhF7HzNhZxTESKlkl4WiejtTr4V4USk769aWdUqSAgxhDzFDgjJHT62830uHgXh/ZhOO+2YCCGGhtBOizhObu6yZctkWmQIcJzlh7puh0yLhMnb7HMRfbtpEaARj+30cbGPSafbk7adOzHoHKIyXNer2rRIaDsXzHxyd/ew0E7riM20Vgcya1nQGSa882kRY2cLOsudC8CUdRdhYRhmTCne8QiVCB2tSRZ0DoQIX3/ppbE9Az9T7OtMU2UMQ90TdA6xW3Y6ctG7+RTUrSmMANCLCD6+t0KJyvL93ud8Xz8YdA5RGcx0RbXKkjUXQojds5gbgfIx3zu0830uXgTwThDacDzJ7Y1CDGGhHblwHO/mZ59dURd0DjF4rus1O052xxsyiX2PxmhgZ/tzAjWKB6qXkcoGEntLJtN+nOPkzgw6h6gM2/buqFZZoe1cMGNSQ0MktPnFZr7PwwCq2oE6YpAUxgDo2vnDA7QrLJ2LsGA29yPiA4LOISqFDq1WSaFdEBmN1s+cPHlMd9A5xOBt3Bj/R03Nyn8FnUPsIsIYaGwEoXFHD/dodL/d3SQg6VyERbH4+uOjR49+IugcojLq6vKnVKss+ctfCLF7NMYA2LjH/z0jWrkwQoh9UWg7F4VC9yI5cn1oGDHCO6a+3r8q6BxiFxHGgHbeuahVGKheyshFSEQi+5+8aRPNCTqHqIx8vu6RapUV2mkRIrzW1VXUQecQg6cU5wGsDzqH2GVjAOx0S2jmnS/2BCDTIqHCXXib37UIFyJeVbWyqlWQEGKIeJrvBKMewGd2+PjAt6LmcTzJqKMQQ1hop0Ucx0stWsRG0DnE4GUyuZFtbR0HB51D7CJ++zUXigaol7LmIjTS6WVj0ul2OWxuiEinO6q2E3JoOxfM+O5hh62uDTqHGLxSSTf5vj4n6Bxil40B77xzUUMYqF4aWMxSd0PAMGqONgw1I+gcojKI+IZqlRXiNRf0eH19ZynoHGLwlNKvEkVags4hdsFi/gyAaSCM39lTfEYJA7Ut5b0yVlQ2nKg03y/liIx80DlEZSjFD1erLFlzIYTYdU/zhWDcDsabO9vnYhfWXJSg8R58gFqrmFwIUUWhnRax7dyMlpYWWXU+BLS1vTLedTuODTqH2AX+WyMSO71Ty1Q8UL0sAhhbsUxir2ltXTHJcdqPDDqHqAzb9s6oVlmh7VwAfG4kMk4Whg0BxaIxkVmfGHQOsQuMvtEK2vntphEMsGCTUQAgW0qHgGnyZCJ1XNA5RKXQ56pVUmjXXBgG5q1dO7Y36Bxi8LSmlwG107MqxD5lGIDysWU7mVQtMvXi7doWQgEkIxdh4PslNxKBF3QOURlK4fpqlRXazkVTU/zxoDOIypg2Lf4qgFeDziF2AWH4AFtkocQoDbCaqwiWzkUYNDdPzAWdQVROMhmr2oLO0E6LuK73tWXLltUEnUMMXjqdm+w42U8HnUPsAo0RAz0lSgPeZirTIiGRTndMc93cqUHnEJXhONlrq1VWaDsXWuN93d3DQjvyIrakxwB0RNApxC54u9NO+xiEgTbRkgWdIWEYOAjgw4LOISqDWR1frbJC++GstXGZZY2V+6+HgPr63nR3d/2yoHOIXTJg56KXKY/+tRk7VoB0LkJBa/+vpsnPB51DVIZS/kXVKkv2uRBC7Lqn+XkwjtxiL4vtDbzPhQ1GHNNpVBWTCyGqKLTTIq7rLWppWSWHHw0Btp07xnW9rwWdQ+wCHnjNRR3phgFeowBgPzzGsmZqH5fJeCc7jidHrg8RjuNV7cj10HYutEZjJKJk5GUIYNYm84DnUYh9wS6suQANWC2LAIAG7D/4QGJvYlYRGvisGBESzPR205UVJR/OQohdt5jfBNAwyGmRv4LRBOBETCc5U0aIISi0IxdLlmQPYGbpHA0B2Wy2NpPJjQw6hxjAY1wDwoBTkaQG/KNlNIAICD+sTDCxt7S0rKpvaVk+4FSYCId0uuOgapUV2s5FoUB3ZTKrZc3FELB+PY7Smi8POocYQARjwQOPdtaC375elqfAGqCRrFQ0sXdEIqUPRiLGhUHnEJVBxA9Uq6zQ3ooKkDN8eN4POoUYvEiE15dKaA86hxiAwgFgdA80eqEZPnalbRloPwwRON/Xa4hIFt4OEURctZOIZVpBCLFrFvMpINwOxoGDWnMBLAdwMIBOTKeBF4gKIUIntNMirttx7OLFHOKRF9EvnV42xnFyskPnvo76OhUDMLCL9ZJl5GJfl053HOS67bJD5xBh29njq1VWaDsXWuurRo1aLcN1Q4I5GWA5W2Rfp3EgCBsGelpUYdfqpUyL7PMMA9MAJWeLDBmqameLhPYvfyJ+0DTXFoPOIQbPMKiDWf896BxiALs4clEqnx2yK22LdC72caWSXhaJ6AE7lCIciPT9VSurWgUJIULuaf49gB4wZlZozQXjeBggGuAQdyFE2IR2WsRxcnPlyPWhwXGWH+q6HacFnUMMgHEgMPDIRZR2eVtvwl8g54vsw9Lp9qRt504MOoeoDNf1rqxWWaHtXDDzyXLk+tCgtTqQWU8LOocY0K4t6KRdnm5lGDhwkJnEXmQYZkwplv1IhgitqWrrZ0L74ayU+v66dWN7g84hKqH0AhB9I+gU4m08wzPBOAiMdw/01IJGL3atg+GDcCCA/ww+oNgbfB8thqFfCjqHqBR9dbVKCm3nIpmc8LegM4jKaG4+ZA2ANUHnEG/Dx1EgKBAmYoAVEj6otIuvWgKjatsRi93X3DxhVdAZROWkUomnq1XWXulcXHzWxfubhnkXwNMAlAh4qjdavPj222/vBoBLZ11qKdBCBkYQ6GXWfMaCexes3Z0yHMe7ubvb+Mp73zs+vzd+BlE9rus1M/ORlpW4LegsYicUGsEAGHqgp9YoruvdtWN/fJB0LvZlmUz7cVobEywr9vOgs4jBs23vjlQqXpXt3PfKmgtlKMXEt70jPmYcDVMHM2FEtBD96uZC6U7WuHbBwgUJkHZI0bd2twxmTGpoiIR2zYjYzPd5GEDyIbMv09jlo5rVrrYrDF9GLvZtzOZ+RHxA0DlEpdCh1Sppr4xc3LLwltcAPNL3ZWn2rNnPADwFAC4575KJ0Bi34N4FD5UfVbfB4OcBzN6dMqLR+pmTJ4/prmRuEYyNG+P/qKlZ+a+gc4i3QWjc1af2aHSDMPC23iQjF/u6YvH1x0ePHv1E0DlEZdTV5U+pVll7fc3FrFmzagmYReCvA4DJJmLCbQAAIABJREFUGP//27vzwKauM2/83+dcSd4wmwETAt7YcbAkm+wJIVsX2rRNO06mmbYh6Ra2tjNt33eaTtukM92mfftOC07adJrStNPF9O2v75uWdEliyEJCxtZi15QEsGTjEAhZAINtLfc8vz+uFJZA8CLdK4nn8xfG0jlfXekcH5177zkM9APWmduDwwf7KstmVKxfv75ow4YNp1ygGQ73XW2aXNTYWP1oJBIpfv11dRURHfH7q/5b62NlweDQZaHQ3j6fb+4LodDeBVq7qtxus2vp0rqDwWDfxcw8acoU/VRtbe1wINB7g2FQzOuterK9fe8kpVwXu93my0uX1nW2t++tUsq1ADB3NzbW9XZ27luaTOpKIt3u99ceDoV6r9IaxX5/1WN79uzxDAx4rlbKPOrz1T0XDu+ZYZruBsMw93m9dc8Hg3vnM7uqi4r0X+vraw8EAn3LAJ48PKyevuKKOUPhcO/1RGaioaHuiWef3T3R4/FcApiHGhvrwl1de+YkEu6FRHqP318bDYf7LjJNnulyoaOhofr1YLD3SmaU+P1Vj+/cudMVi01Ybhh6wOut3REI7J4OeLwul+5vaKjd1dGxbx6RrtGau5ctq3mps7O3KZnEFK3d25ctmzUYDkevM002Gxtrt+3atat8cLDkUiL9it9fGwqH+2ebprnIMHiv11sTCYV667XGBUVFKlBfP+e1YDB6BTOV7tlT1VZX16GUmn6NYehjXm/ts+3t+6cplfAx84tNTTV/6+rqm5tIcC1AOxsbq/aHw9FG06SphlH0jNc783goFL2WOcp+f+3W7u6XJ8RiQ5cpxa/6fDXBUGjfhVrrxS4Xehoaqns6OqKLiejCRMIIXnrp7FcDgejlAJUdOVK19dAh8Lx5fdcCfLyxseaZHTv6K9xu0w9gf2Nj9c5wOFprmjRXKfU3n2/Oi6FQ1K81VRQVlTxbXz/jWCAQuUYpUj5fTVs4fKDMNGOXGwa/5vXWBKxtinmJ202RpUur9nZ2RhYlk2q21u7QsmWzXgmHI5eZppqg9aFtTU1NZjDYdx0RD/r9Ndu7u/dNjcV0o1J4yeer7g4GIzXMap5hGLu83tn9wWDEx6ymlZYO7Vi0aNFAZ2fPcmbl8nprHt++fV9JcbG+0uXC6w0N1R3d3ZGZsZi6iFlFm5rm7AmHexaapjEHiIcbG+cfCoV6LtHamFhUdOyJJUuWJILBvuuJMOT3Vz8dDEYmM6tlhkEHvN6qvwYCPdWAMd/tTjy/dOm8fV1dPQ2JhDEjHo8/d9ll84+Gw31XA+zxeqsfi0QixY29uvp1PjEh4SJ2Jc+yTI4iUiYAIhAzUApdNnjSZEYxcekwE0BIephrnw303qB18oVly+b2pdue1sn/XrZs7pF022tsrH509+7dRQMDnqvTfUC67SmV7PP55r6QbnvpPiDd9tJ9QDjcez1Aca+36sl020v3Aem2l+4D0m0v3Qec1PYe27lzpzsWm7A83Qek2166D0i3vXQfkG57J/qA6HVEOtnQUPdEuu2l+4B020v3Aem2d6IPsNqe31/1eEdHh5FqewNeb+2OdNtL9wFna3vpPiAUil6rNevGxtpt6baX7gPSbc8weG9tbU0kEOhdAmBWug9It709e6rapk8HTZrUtyLdB6TbXroP6OzsrUsmUXd620v3AcFgZAUR0cltL90HnN72Tu8DTm57PT1N+uQ+4PS2l+4DTm97J/cBhkGG11vzeHv7/lKlElek+4D29ugFSlF9uu2doQ+41DRVeartJa0+wGp7nZ29U5JJNKXbXroPSLe9QKDHCxjT023P6gMMt9db/Vi6DwDocGNjVXu6DyBK9vr9c3en+wDDSHR6vfNeTvcB5eXxJ+fNmxcPBvuuVwrDPl/1U8FgZPLgoFrW2bnvYEPDnK50H5Bue11dPQ3Fxebz8+fPz8iNElk9rXDPPfe4JlDZL8D8pw2b7nt4tM/XWi9VCk0AEIvF3EqhiYgXAkAyabQqxZcTGbMBgMiYrRSamGmK9TMvUgpNsVjMDQBKoUlrvdT6t7tMKTQlk1SX+nmGUmhSCpUAYJrJOqsuV5lV1okc8fikVA5jEQAw02Sl0GR18gCgLlQKTcPD6Rx6oVJo8njiHus1caPWqgEAystdpVa9aq71O9f0VI6ZVtlcY9WVmJAq6yKl0LR5M2hoaIrLek1YbD22eJL1M1cBgNudmKUUmtxuVWH9Xi+wciSKrJ/hNwzltY6tqySVY56VIzEtVfYFqRzV1rFMpKbGqV4pNNXVdaiKigojddyXAIDHk5ioFJpcLq62jiVfYOVITkuVNd86Psliqyz2EdEHQqHoV4eGksXWcab5AGAYiYpUjlnWa0KNUmgqLk5OtH6PJUqhafbsPUZ9/U5DKTQZBpYAQHFx8pQcWtMsq6xEKgfNs17TkRKrLOUD4AeA4WErBzPPBwCXi07JoTWqlUJTUVFyUupYLlYKTfF4pWvrVqjUa6i3jm2iPFVWTareC6yfk9Otzx7NVQpNiYSn1Crb8AJoBICSkmSR9Vi9AAASCVVhfR6SF6YeW2X9rCanyl5sfa4r3ADI+p31mXe5zHIrF9dar5dmWmW7Z1jvk5prHS93WartNWhtfeYPHkx6XMTTTm6b6i1W1ywind41lQDAQyg++fcegsd662GCrONhGO5T2p5SVg5mbki3PdM0Pak+YFEqxZRUO50DvLkPUMrqAw4eTKbaHpq01g3W8bD6ANO02h6z1QcYBqVPAaRzpNteug+gZLLCnapnsfU7Ndn6fBhV1s/JC6331Gp7pskLlUJTSUkyvf5HY+p9RiLhKbXqtdoec3J6qux026uxPlvJcqtsukgpNG3dChWPV7qsx1qf+aKiZKoPQOozj1nWe0oVVrW8wMphpt8Pf+pzj1jsSIn1+tR867lWH8BMt4TD0c+5XFYfEI+/0fbqlUJTff1OY/bsPcbJn/l023O7UXNyDsNIpHLQfOv46JJUDh/APut46JKT+wC3OznNep/4Aut9s3KUlJiptkdLlEJTRUWFYX3RQZNhoB4A4nErB3O6D8AFJ/cBSql5Vns5Wmq9JuVltvqAkhIz1RfxAiuH1fbc7kSqD+BU2zMnp8perBSahoamuDZvfqPtXZTKcUofoBRmWjlcqT7Aanvl5a5UH6AatOZGAPB44qnPvNUHxGJqaup9utD6bBlzUu/T5FQbWGS9T5Pe+LuX7gOUck9QCg8wW32AUqhMfcZnAEAySXXp52VC1lbobG5uNirLpv8Xgw63bGq5K/3/q+9cXWdo9ezGTS2VAHjdh9fVwuAdGze1zBhN+aFQ9MHBQWOtXNCZ/0KhnksAutLnq/3fTmcRZ9HGuwHMQ3rVzbdYobMYnBgGuXHuFTpfBDAD21CMe+icF4oK+1mzPVzr9db8p9NZxPiFQtFf+nw1H7SjrmzNXFDlhMoHARpu2dSy+uRf3P/g/T0g7l+/as3NAMAGrybGb0Zbgc9Xc6cMLAqDz1f3nAwschyP4BqKlGGmkV0LxTABuHE5pp3zscIRXm/1YzKwKBx2DSyALA0u1n9k/cVg/ghAb1u3au2+davW9q+7fc3P0r8n0/gog+5Zd/vafQT4oNSoF/YIhaL+1laWjY8KQGdn75Surr65TucQb0GN4m4RGmG7JGgAA/DIRZ25KhDYPd06Ny8KgXUdkj2yckHnhoc2PIe3OOWy4aENQQAN46mDGV9buPBgM4Dj4ylHOC+Z1A1K0fUAvux0FnEGD3MpGCXnfqCliFA8NPKtyPaDcSGA0FiiiewyjKLLAb0AwHecziLGj4j/F4Br7Kgrb9eJUApPlZYOjHQlQJHT1CGAu51OIc5iIi4cyeJZaaZ1umMkDABxGHjH2IKJbDNN7AdIlv8uEER6q2112VWRECJPPcbXQeG3wEnbqGdiy3XCy2DMAAO4jqQvEqKA5O3MRTDY29ze3p6x22aEc7q69syx1lUQOYkwG8DRkT7cpVjaZYHo6Ng3z7qbSxSCYDB6m1115e3gAuA73O7ZHqdTiPFLJIw6Zn2j0znEWRDmgDEw0oe7gdG1S5mzyFkuFy8hUsudziEyhT5pV015uyuqYWDDq6/KluuFQGt6AVByYW7uqgVweKQPTjDFkMd9izjBNJNhtxtRp3OIzFDKvgtz5TuDEOKttfGjYMRAWIlsXHMBACugQDTye0yEEDktb0+LhMPRu3fv3l107keKXBcI9C4JhSK3Op1DnAWhFsCRkT7cQ1x87kedZisqRv0ckXWBQN+ycLj3JqdziMwIhSL32lVX3g4utMZVg4PlMvVaEPT09L4EIse0sgHGHCi8PtKnGHT2fUfOSmHOqJ8jss4wMAuw9nMS+Y9ZrbCrrrz946y18Smfr1KW/y4ApaWxwOBg6W6nc4gzmI5fAXBD4/qRnkSNMQ0BI1/REwBgogpAcLTxRHZpbT7hcvEOp3OIzFDK/IRddeXt4KKpac4epzOIzFi0aNEAMPK7EYSNGBNBAAgjvh5CM/Sor+YimbnIRX5/7Ygv5BW5z+uts21BtLw9LRIOR1vb2/eXnvuRItcFg71XhsPRu53OIc6AUDbap5SQHt1zGDK4yFGdndF3hkLRdU7nEJkRCkV/b1ddeTu40BoT3G4ld7sUAGbtYsboLwIUdpgw6meMdrFNAoNRNep6RNYxKzeRtM1CwUyjO105DvLHWQhxdo/zXhDqAOwCsAjZuRWVQXgGK+hKO16SECL78nbmors7MpOZZXBUACKRSHFnZ+8Up3OIM1Cjn7kgNYYvLTJzkZPa2/eXtrfvPfMgUuSdQKBvll115e3gIh6nBzs7D8o1FwXg9ddxqdb8j07nEGfAo7zrA0AxeCzt8gK0y54kucbtTt7gdhsfdzqHyAwi/qVddeXt4AKg0MSJQyPd2lnkMLebX2fmHqdziNM8zKVglIz2aXrkW66fwCAM4MJRP09klWnqQ1pTr9M5RGYQcYdtddlVkRAiz7TxRWCEYC2Kle1rLl6CiQ/ienrCjpcmhMiuvJ25CIf7rm5r47xdp0OcEAjsnh4K9coKnbmGMRfAsdE+zcAY2iWjD0quu8g1gUDfrHC4R1boLBDBYGSFXXXl7eBCa/2FqVMPyt4iBcG1BGDZWyT3zAWNfnEzj8Lo2yWhTy7qzD2GgWWAkr1FCoaSvUXOhYg3u1yvJpzOIcbPMKgP0E85nUOcxroFddQzF0nG6NslwwvCx/AoywZmOSSZ1LuJ9HNO5xCZQaR/YVtddlUkhMgzW/lPACaDcQmyfc1Fui9SqMI1tC/Lr0wIkWV5O3MRCkXu6O7u9jidQ4xfOBytDYV63uZ0DnEaxnzw6E+LuImlXRaIjo7o4s7OnuVO5xCZEQpFPmlXXXk7uGCm5mSyQu6LLwCmyVWAusrpHOIkrewBUAU9+sGFizD2dqlHv5eJyB6XS81nVpc4nUNkBrO6za668vZuC6XUN157rTLmdA6RCcmdgOcVp1OIk0zDjWDwWL5+xDVioDH2LYxqWKdgRA4wTbQbhrZtJ02RbfordtWUt4MLr7fqSacziMxobJx/CMAhp3OIkyh8EwwXgFHfhmiCkmOu10DNmJ8rMq6xsWq/0xlE5vj9tVvtqitvT4uEQtHvb9++b9SrB4rcEw5HG0OhyF1O5xCnGHPbKlI89nbJqBvzc0XGdXb2LA+Fej/kdA6RGcFg9Ed21ZW3gwtmzCsrc+dtfnGCaXI5QLZtqCNGZMwDBDWefkUGFzmF2TWZiGc6nUNkCi2wq6a8PS3i8fCdS5ZUDjqdQ4zflCnYMTBAnU7nEKcY8+BiGDQIYOKYnsxYPNZ6ReYlEq5HgaFtTucQmcFMH7SrrrwdXNTX1x5wOoPIjNra2mEAw07nECdhjHnHYdbgMa+go7AAW7gIK0ku1s4By5bNki9wBcTOa2jy9rRCMBjdEg4fkNvWCkAgELkmFIp+1ekcImU7lwBjWMI7pUTx2NslI44yLBnz80VGhcN97wmHo59zOofIjGCw17ZZqLwdXBDhwPHjCe10DjF+SvEQwK87nUOkDGMBMIZt01OYweOofRdM+MfxfJFRfBzAYadTiMwgYttmLmT5byHEqR7nW0D4MYAJOLFktz3LfwMPAziOY/gobiKZkhciT+XtzEVHx755zJy3+cUJu3btKg8E+uRukVyhsBDA0JifTuPqV24C8Pcok9mLXBAMRiZ3dfVUOp1DZEY43DPqdWvGKm//OCtlfr+z86Csc1EABgeLGpXSss5FrmAsBDDmWYMiGsc6FyKnKGUs11p92OkcIjO0Nh6wq668vVtEKTxVWjow9pUARQ5RhwDd7XQK8YZxzVyYDBPj7VsMyNbrOcA0sd8waDzX0IgcQqS32lVX3g4uvN6arzudQWRGY2P1TgA7nc4hANzDCsBiKOzCGC+XjjMNg8Z+twkAwJRlwHNBY2NVu9MZROb4fLW27S2St6dFgsHe5vb2dtkVtQB0de2ZEw73Xe10DgHgWlQDKAaPfebCpXj87ZJQO+4yxLh1dOybFwr1yK6oBSIYjNq2K2reDi4AvsPtnu1xOoUYv0TCqGPWNzqdQwAwsQRADzDWeQvADWSiXcrgIge4XLyESC13OofIFPqkXTXl7WkRgH6SSPTHnU4hxs/tNnu09siaJbnhQQAV41hjEwkgjvH2LSyDi1yQTNJOw9CyGnLB4B/aVVPeDi78/urNTmcQmbF06bx9APY5nUMAIJQCMDCONXCSmhLjXkGHUAdmAsnFhE5qapqzx+kMInP8/ppf2FVX3p4WCYejd+/evXt8F42JnBAI9C4JhSK3Op1DAADGfb2Eh7h43CkYpdiK6nGXI8YlEOhbFg733uR0DpEZoVDkXrvqytvBhda4anCwPG9nXsTJ9HSA6p1Ocd5rZQMZuF7CIBjjzqLQD0bDuMsR42IYmAWwbQsviexiVivsqiuPBxfGpxoaKsd8RbvIHaWlsYDW6gdO5zjvVWZmw7AY0/jbJWMvSAYXTtPafEIp/TOnc4jMUMr8hF115e03fzkXWDgWLVo0AGDA6RznPY0mWBdjjut0o2bocV9zwdgjgwvn+f21smlZAfF66563q668nbkIhaIPbt++T5YZLgChUM8loVDkH53Ocd5jNMIaXIxLMXFpBtJcA+DdeJyvz0BZYozC4d7rw+Hox5zOITIjFIr+0q66sjZzse72dRtA/F4Ac+KexPQHHnjglfTv1qxa41OgTQxMItALrPm2lodaXh1N+cyYWVbmztvBkThBaypRiqY4neO8R1gGIAagfFzFEGhcm65bWaoBFMktqU6jMoAnO51CZAYz2bZBZNb+OBNRqyuZuBTA8TdXSj9mjXtbNrXUgnSIFH11tOX7/TUrvd6Zbypb5J/GxtptPl/Nl53OcV5rZzcIXvD4Zy6GNI2/XZ4YnsgdIw7yeqv+n9db8x2nc4jM8Purr7GrrqwNLjZs2vDkf/z8gZdO///Vd66uAzC75aGW3wEAkuoHADePtvzu7shMZh7vmV2RAyKRSHFnZ6/MXDhpAF4wTND4Bxekxn3FxQlKZi6c1N6+v7S9fe8kp3OIzAgE+mybubD9gk4XYw4D/YD1zeTg8MG+yrIZFevXry/asGFD7OTHtrfvneTxuFRDQ/XrzKy6uvomeTxDyUWLFg3EYtgUDvd/dPv2fa9dccWcoe3b95VMmKCLDePY8fr6+viuXbvK4/ES19KlVUeISHd29k6Jx5N62bK5R9ra2FVR0VfOXBT3emce3717d9HQkKe0vFwP1dbWDofDB8qIYp5XX60auPZaSr5Vjvb2drfHM31CPO6OLVs2a3A0OVpb2Vi0qG+iYZQk6utnHBtlDurq6ps8OBg3L7ts/tHR5ggGI5MB64Kt0eZ49tndE0tLPcbSpVWHAWAkOUpK4oPz58+PdXe/PME0h9y7dlUdveUWMoPByOTDh+lKIr60tZXvPVOOY8fU8BVXzBlqb99f6vEkiuLxQ8eWLVuWGE2OSCRSPDCgSt4qx9mOR3d3t8c0J5SNJcfpn7WR5DAMRWf6rI0ixzk/86fnUIQHmDHMqYs5FUHpk05tKMA4eQlVIpz1zEcJuHTwpPGFAhsnX+F5etnn6C/mBzp7p7zV8RhL20sfjzG2PdXV1TdprG2vs7N3imlqHkvbS+cYTds7PcdIPvPpHMyJ6wGjpr19/31jbXsj6QPOlWM8fcBo2t7pOcbQ9g4TEY+m7Z2e463+3pwrx7k+80R9m8PhA287U45w+EBZQ0PlEBFlZLXknL5mweUyfqC1/jUABIN7Kpi5dXi46N8AQCk6TmQ+VFqavB0ASkuTtzNzq2mWXAYAw8NF/8bMrcHgngoA0Fr/2uUyfgAAEyf2zmfmVubYZwHg+HH3u5i59fBhdZP12OHPMHPrlCl9C1M5WqzHs9q5s3+ylaP4G9bvpl/KzK2GEb8DAEpK9IeYuTWRKLvSylF8LzO37twZnWGVzb9wu40fAcCCBT1zrcce/zwAHDvmegcztx49ivcBAPPQemZunTYtsgQADEN9n5lb29vb3R0dPROZubWoyP1N63hMW8bMrW534mPW8TA/yMyt8fiEa1I5vsLMreFw/wUAQEQ/J6IfA8DixftqrByD/9M6Hp4breNBH0gdjzXW8ehdCgDFxZ7vMXNrNBot2rnzUBkztxYXu75tHY+pfut4xD5hHY/kLczcOjjouhYAEonjX2Lm1rq6ngutHHjIMNTnAN4/f350jpV56G4AGBpyX8fMrWVlutkqO34XM7cqNcNr5XB/l5lbOzsPlj7zTH+xlcP9XQDweKY3MHOryxVfDQBHjqi/Y+bWY8fcNwBAPD50NzO3LlzYW5U6Hj8hop9Zx2PvrNT78iUrc8kKZm4tKUneCgBud+Lj1rGuaLRyuL7NzK07duwp37Nnj8fK4fkeAEyeHL2ImVu1jq0FgKNHcbN1PDxvs8oe/J/M3Dp3bn9tKsd/mib/l/WZ3zcz9Vn7CgAkkxOuto6HeVvqeNxpHetpFwNAUZH7m8zc2tXVN6mtjV3W6zc2AkBFRf9iZm4Fhj6VOh7vsY6H650AoBl+BqYbzEUAMJXM6Se3xUplnvKNpxhchrNiBViDCgCoJH3Kc6cpXXnyz3SG1UApVUYJ6YZU26OOjpempo7H16zjUX6p9T7EUn2A/rD1+Sm9AgCGhor+lZlb//rXyHQA0Bq/crnUAwAwdWpkLjO3JpNDnwWAY8dc72Tm1iNH1HusBMOfZubWior+xdaxNjYyc2tbG7u6uvomWZ8H9zcAwDCmXZz6rN0JAGVl5m1W2ROuBoDh4eJ7rL5o30wAME3+LyL6TwCYP7+nLtX2/gcADA563pbqA262MsfWMnPrpEmRegBwu13fY+bWPXv2eHbs2FOe+qz9u/W7iqZUH/BxACgpSd5qlV2yAgBiseIvWZ/5F9N9wM+I6CcAsGhRX7V17Aa/YB0P9w3W58X0MdMBlyu+2ip7WqoPcP9vZm595pn+4s7Og6Wpvuh/Wcdjhi91PO6yjoduZubWoSH3dQCQSAx9kZlb582LzAYApdQmIjwEAPPmRWan2t6/WMfDdW2q7d1ilR37hPWZn+GzXqP7O1b/eqgsGo0WpfqA/7COx7SlVtsbXgMAhw/TB5i59fhxz43W52fwn5m5ddGivurU8fgxEf0cABYufPECK3PxlwEgHp9wDTO3lpaaH7TKTnws1Qc0WcfD8y1mbu3o6JnY3t7utjKq7wPApEmReuszPLQeAI4exftSbe8d1vE4/nlmbp0/v6fOKtv4kdb8CwDYuTM6I/WZv9fKXHaVdTz0h6zjEb/Dqmv6JanP2jes49E/mZlVqg9osT7z+xYRcbXWw5+xjoe6yToe7ncBAHPss88992LGZpCzflph3aq1x+KeRE36gs7Vd66uM7R6duOmlkoAvO7D62ph8I6Nm1pmZDuLEOIs2tiaSyC8DMYMAHsBzAXwNwCLAewCsAhAL4BqMI6AcObp8hO/sx5L2AXGopPKsso+URfj9L6IMAxGMQCGiem4gUZ1wbcQwlm2z1zc/+D9PSDuX79qzc0AwAavJsZvRltOONx3dVsb5+06HeKEQGD39FCoV1bodMqjXHnuB42cgQy2S8YrMHB5xsoToxII9M0Kh3tkhc4CEQxGVthVV9YGF+vuWPvDdavW9gMo9cQ9netWrftT+ndkGh9l0D3rbl+7jwAflPrKaMvXWn9h6tSDsrdIQXAtAVj2FnGKwpWZLM6jxrcI1ykIL4BkcOEUw8AyQMneIgVD2ba3SNa++W/8SctZ943f8NCGIDC+1feIeLPL9WpiPGWI3GAY1Mesn3I6x3mLcMUZTkyMWZKRQKb6Fo3dULgiI2WJUUsm9W63W8sqnQWCSNu2K6rcyinE+a6NtwO4DADl4DUXIRAaoPBRLKdNmX7pQojsyOm7Rd5KKBS5o7u7e9w7OArnhcPR2lCo521O5zgvtXExgMZMFukmzly7ZMwAQ0HLqREndHREF3d29ix3OofIjFAoctYzCpmWt4MLZmpOJivcTucQ42eaXAWoq5zOcV4iXA7CkUwW6SJkrl2eWKlzfsbKFCPmcqn5zOoSp3OIzGBWt9lVV97ebaGU+sZrr1XGzv1IkfuSOwHPK+d+nMioh7kUjE8DiACYfq6Hj1RcIwbKcN/CWJDR8sSImCbaDUPbtpOmyDY96psnxipvBxdeb9WTTmcQmdHYOP8QgENO5zjvTEQFNN6b+mm8W429wQQlM1XWSWbhCZ6O5SSfExs1NlbtdzqDyBy/v3arXXXl7WmRUCj6fdlyvTCEw9HGUChyl9M5zjsJZKX9FCnOfLmEl2HiuoyXK95SZ2fP8lCo90NO5xCZEQxGf2RXXXk7uGDGPNlyvTCYJpcD9m0FLFKytDiVyk6/shfADVkoV7wFZtdkIp7pdA6RKWTb6cW8PS3i8fCdS5aUebPLAAAYsklEQVRUDjqdQ4zflCnYMTBAnU7nOA+tyEahw6BBABMzXOweADdmuExxDomE61FgaJvTOURmMNMH7aorbwcX9fW1B5zOIDKjtrZ2GMCw0znOQ9dmo1DW4CysoOMDoQqP8324jtZkvHRxRsuWzZIvcAXEzmto8va0QjAY3RIOH3iLnRlFvggEIteEQtGvOp3jvPIoLwBwYTaKLlFvtWPqGDFKwCAQlma8bHFW4XDfe8Lh6OecziEyIxjstW0WKm8HF0Q4cPx4IiP7zgtnKcVDAL/udI7zisK7AezIRtHMmbvz5M2FoyprZYsz4OMAZPnvAkHEts1cyPLfQpxvtvF8mHgKCgfAb+zxYy3BnXvLf78Ia4ZlN6yFtJI4hkm4iWS6XogclrczFx0d++Yxc97mFyfs2rWrPBDok7tF7JLEPBBmnDSwyChFWe1XhlGWnQtRxZsFg5HJXV09lU7nEJkRDvcstKuuvP3jrJT5/c7Og7LORQEYHCxqVErLOhd2yfIuo0WUhXUuTogCeF8WyxcnUcpYrrX6sNM5RGZobTxgV115PLjAU6WlA9lYCVDYTh0CuNvpFOcNyu5iVCbDzGLxUSi8F61sZLEOkWKa2A+QLP9dIIj0VrvqyttbUb3emq87nUFkRmNj9U4AO53OcV5o48lgXJzNKuJMwyAUZaVwQikYkzAN3wbwT1mpQ7yhsbGq3ekMInN8vlrb9hbJ25mLYLC3ub29XXZFLQBdXXvmhMN9Vzud4zzxXjD2ZbMCl+JstsuZAIpAeH8W6xApHR375oVCPbIraoEIBqO27Yqat4MLgO9wu2d7nE4hxi+RMOqYtay+mG1/5lkAPg3rzo+scQN2tMtZ2MLZmR0Rb3C5eAmRWu50DpEp9Em7asrb0yIA/SSR6I87nUKMn9tt9mjtkTVLss2F9wHwg7Akm9UkgDiy37ckUYx3Afhtlus5ryWTtNMwtKyGXDD4h3bVlLeDC7+/erPTGURmLF06bx+Q3al6AYDe2Kgse4tcAUhqStiwgk4/CHdBBhdZ1dQ0Z4/TGUTm+P01v7Crrrw9LRIOR+/evXu3TIsWgECgd0koFLnV6RwFj2HL9LaHuDjrlWgcAmEFHudbsl7XeSwQ6FsWDvfe5HQOkRmhUOReu+rK28GF1rhqcLA8b2dexMn0dIDqnU5R0NrYB+tiyKwzCNm/TZQwDQw3FO7Pel3nMcPALIBtW3hJZBezWmFXXXk7uCDCF59/vlJ20iwALpfqNAz1U6dzFDTGnQBsua0wxrbucDsZf+SpNtZ3XjHN2DOmqeUUdIFgps/aVVfefvP3+WqCTmcQmdHQUP06ANm4LFva+O8A3AXGM3ZUp5lMG3ctGkYRPgHgm7bVeB5pbJx/yOkMInPsXLckb2cuQqHog9u375PlvwtAKNRzSSgU+UencxQswh0A3CDMtaO6YuJSO+oBADBeA7AOrSy3pWdBONx7fTgc/ZjTOURmhELRX9pVV94OLpgxs6zMnbf5xQlaUwlAU5zOUZC2cBEYV9pZJZGN8xaEIRAMzMA3bKvzvEJlACY7nUJkBjPZtkFk3p4W8ftrVjqdQWRGY2PtNgDbnM5RkEqwCoR4dm8+PdWQpuNn3Y490xilAGaC8Rkwfw5ENr7Swuf1Vv0/pzOIzPH7q6+xq668/ebf3f3yBGa27xuSyJq2NnbJKa4s2MZzAHwFwLN2VktwoF0SCFvxdtvrLXDt7e3uSCSS/VuLhS127dpVblddeTu4iMcHWzs7D9p3bldkzaRJ0StLS80vOJ2j4JjYDOACAIvsrLZYwf52SUgAuNv2eguc2z3jnUeP0jqnc4jMGBoq+b1ddeXt4IIIe44fT8iS0QXAMGgA4P1O5ygoT/AFUPA7UbUG7G+XjAQYi/Eo/4PtdRcwouRhZpLlvwsGv2BXTXl7zYXPV/MppzOIzPB6awIAAk7nKCgmvgvgRQC1dlcd0zQEsmXzspMpEKbBwM+xhbdhJfXbXH9Bamioe8LpDCJz/P6aj9tVV97OXITDfVe3tXHeDo7ECYHA7umhUK+s0JkpbfwTMG6GNbiwnQGH22Ux5LbmDAkE+maFwz2yQmeBCAYjK+yqK28HF1rrL0y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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-99138bba\");\n",
       "fig.select(\"#img-99138bba-5\")\n",
       "   .init_gadfly();\n",
       "fig.select(\"#img-99138bba-7\")\n",
       "   .plotroot().data(\"unfocused_ygrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-99138bba-7\")\n",
       "   .plotroot().data(\"focused_ygrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-99138bba-8\")\n",
       "   .plotroot().data(\"unfocused_xgrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-99138bba-8\")\n",
       "   .plotroot().data(\"focused_xgrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-99138bba-14\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-99138bba-14\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-99138bba-14\")\n",
       "   .click(Gadfly.zoomslider_zoomin_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "fig.select(\"#img-99138bba-16\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-99138bba-16\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-99138bba-16\")\n",
       "   .click(Gadfly.zoomslider_track_click);\n",
       "fig.select(\"#img-99138bba-17\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-99138bba-17\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-99138bba-17\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-99138bba-17\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-99138bba-17\")\n",
       "   .drag(Gadfly.zoomslider_thumb_dragmove,\n",
       "     Gadfly.zoomslider_thumb_dragstart,\n",
       "     Gadfly.zoomslider_thumb_dragend)\n",
       ";\n",
       "fig.select(\"#img-99138bba-18\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-99138bba-18\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-99138bba-18\")\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": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot(x=sampl(1, 100, 10^6), Geom.histogram(density=true), Geom.density, Guide.xlabel(\"pdf\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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       "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",
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       "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-53737418\");\n",
       "fig.select(\"#img-53737418-5\")\n",
       "   .init_gadfly();\n",
       "fig.select(\"#img-53737418-7\")\n",
       "   .plotroot().data(\"unfocused_ygrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-53737418-7\")\n",
       "   .plotroot().data(\"focused_ygrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-53737418-8\")\n",
       "   .plotroot().data(\"unfocused_xgrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-53737418-8\")\n",
       "   .plotroot().data(\"focused_xgrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-53737418-14\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-53737418-14\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-53737418-14\")\n",
       "   .click(Gadfly.zoomslider_zoomin_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "fig.select(\"#img-53737418-16\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-53737418-16\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-53737418-16\")\n",
       "   .click(Gadfly.zoomslider_track_click);\n",
       "fig.select(\"#img-53737418-17\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-53737418-17\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-53737418-17\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-53737418-17\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-53737418-17\")\n",
       "   .drag(Gadfly.zoomslider_thumb_dragmove,\n",
       "     Gadfly.zoomslider_thumb_dragstart,\n",
       "     Gadfly.zoomslider_thumb_dragend)\n",
       ";\n",
       "fig.select(\"#img-53737418-18\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-53737418-18\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-53737418-18\")\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": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot(x=sampl(2, 2, 10^6), Geom.histogram(density=true), Geom.density, Guide.xlabel(\"pdf\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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