drawgraph.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "import operator\n",
    "import sys\n",
    "\n",
    "COMMAND = \"drawgraph\"\n",
    "startSize = \"550\"\n",
    "batchsize = \"110\"\n",
    "fileName = \"run.out.learner.\"+startSize+\".\"+batchsize+\".t\"\n",
    "inFile = open(fileName,\"r\")\n",
    "data = {}\n",
    "counts = {}\n",
    "experiments = {}\n",
    "for line in inFile:\n",
    "    line = line.rstrip()\n",
    "    fields = line.split(\"\\t\")\n",
    "    if len(fields) != 2: sys.exit(COMMAND+\": unexpected input line (TAB): \"+line)\n",
    "    key,value = fields\n",
    "    if not key in data:\n",
    "        data[key] = float(value)\n",
    "        counts[key] = 1\n",
    "    else:\n",
    "        data[key] += float(value)\n",
    "        counts[key] += 1\n",
    "    fields = key.split(\" \")\n",
    "    if len(fields) != 4: sys.exit(COMMAND+\": unexpected input line (SPACE): \"+line)\n",
    "    experiments[fields[0]+\" \"+fields[1]]= True\n",
    "inFile.close()\n",
    "\n",
    "finalValues = {}\n",
    "maxSize = {}\n",
    "bestSmartExp = \"\"\n",
    "bestSmartExpScore = 0.0\n",
    "bestSmartExpSize = 0\n",
    "for key in data:\n",
    "    exp,stepSize,totalSize,dummy = key.split()\n",
    "    if not exp in maxSize or int(totalSize) > maxSize[exp]:\n",
    "        maxSize[exp] = int(totalSize)\n",
    "        finalValues[exp] = data[key]/counts[key]\n",
    "        if exp != \"r\" and exp != \"t\" and exp != \"t-R\" and \\\n",
    "            ((finalValues[exp] > bestSmartExpScore and maxSize[exp] >= bestSmartExpSize) or \\\n",
    "             maxSize[exp] > bestSmartExpSize):\n",
    "            bestSmartExpScore = finalValues[exp]\n",
    "            bestSmartExpSize = maxSize[exp]\n",
    "            bestSmartExp = exp\n",
    "sortedExps = sorted(finalValues,key=finalValues.get,reverse=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": false
   },
   "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",
       "        this.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, fig.canvas.height);\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 overriden (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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import ScalarFormatter\n",
    "import numpy as np\n",
    "import math\n",
    "import re\n",
    "labels = { \"e\":\"Highest entropy\",\"c\":\"Lowest confidence\",\"l\":\"Longest text\",\"m\":\"Smallest margin\",\\\n",
    "           \"r\":\"Random selection\",\"t\":\"Sequential\",\"t-R\":\"Reversed sequential\"}\n",
    "plt.figure()\n",
    "for exp in sortedExps:\n",
    "    x = []\n",
    "    y = []\n",
    "    for key in data:\n",
    "        fields = key.split(\" \")\n",
    "        if fields[0] == exp:\n",
    "            x.append(float(fields[2])/550.29)\n",
    "            y.append(data[key]/counts[key])\n",
    "    if exp == \"r\":\n",
    "        plt.plot(x,y,'-',label=labels[exp],color=\"red\")\n",
    "    elif exp == bestSmartExp:\n",
    "        plt.plot(x,y,'-',label=labels[exp],color=\"black\")\n",
    "    else:\n",
    "        plt.plot(x,y,'-',label=labels[exp],color=\"gray\",alpha=0.5)\n",
    "\n",
    "plt.legend(frameon=False,fontsize=\"x-small\",loc=\"upper left\")\n",
    "fig = plt.gca()\n",
    "fig.set_xscale(\"log\")\n",
    "fig.set_xlabel(\"Training data size\")\n",
    "fig.set_ylabel(\"Accuracy\")\n",
    "fig.set_title(\"\")\n",
    "fig.tick_params(top='off', bottom='off', left='off', right='off')\n",
    "for spine in fig.spines.values(): spine.set_visible(False)\n",
    "xticks = []\n",
    "nbrOfTicks = 4\n",
    "for i in range(0,nbrOfTicks):\n",
    "    xticks.append(0.5+math.exp(math.log(float(startSize))+i*(math.log(float(startSize)+10*float(batchsize))\\\n",
    "                                                        -math.log(float(startSize)))/(nbrOfTicks-1)))\n",
    "    xticks[-1] = int(0.5+xticks[-1]/55.029)/10\n",
    "fig.set_xticks(xticks)\n",
    "labels = [item.get_text() for item in fig.get_xticklabels()]\n",
    "for i in range(0,nbrOfTicks): labels[i] = str(xticks[i])+\"%\"\n",
    "fig.set_xticklabels(labels)\n",
    "fig.minorticks_off()\n",
    "fig.set_title(\"Start size: \"+str(startSize)+\"; step size: \"+str(stepSize))\n",
    "plt.show()\n",
    "\n",
    "pattern = re.compile(\"\\.\")\n",
    "fileName = pattern.sub(\"-\",fileName)\n",
    "plt.savefig(fileName+\".pdf\")\n",
    "\n",
    "labels = [item.get_text() for item in fig.get_yticklabels()]\n",
    "for i in range(0,len(labels)): labels[i] += \"%\"\n",
    "fig.set_yticklabels(labels)\n",
    "plt.savefig(fileName+\".pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "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": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}