Explaining CDFs.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "sample1 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 0]\n",
    "sample1 = np.array([i/sum(sample1) for i in sample1])\n",
    "sample2 = [0, 0, 1, 2, 3, 0, 0, 6, 7, 8]\n",
    "sample2 = np.array([i/sum(sample2) for i in sample2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "sample1_edf = np.array([sum(sample1[:i+1]) for i in range(len(sample1))])\n",
    "sample2_edf = np.array([sum(sample2[:i+1]) for i in range(len(sample2))])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "normalized_sample1 = np.array([i / max(sample1) for i in sample1])\n",
    "normalized_sample2 = np.array([i / max(sample2) for i in sample2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9,4))\n",
    "plt.subplot(1, 2, 1)\n",
    "plt.title(\"Comparison of normalized PDF between 2 samples\")\n",
    "plt.xlabel(\"Word Length\")\n",
    "plt.ylabel(\"Probability\")\n",
    "plt.plot(normalized_sample1, label=\"Sample1\")\n",
    "plt.plot(normalized_sample2, label=\"Sample2\")\n",
    "plt.legend()\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.xlabel(\"Word Length\")\n",
    "plt.ylabel(\"Probability\")\n",
    "plt.title(\"Comparison of CDF between 2 samples\")\n",
    "plt.plot(sample1_edf, label=\"Sample1\")\n",
    "plt.plot(sample2_edf, label=\"Sample2\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "normalized PDF mse 0.22598379629629628\n"
     ]
    }
   ],
   "source": [
    "print(\"normalized PDF mse\", ((normalized_sample1 - normalized_sample2)**2).mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "normalized CDF mse 0.04728669410150893\n"
     ]
    }
   ],
   "source": [
    "print(\"normalized CDF mse\", ((sample1_edf - sample2_edf)**2).mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}