AL experiments.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# AL experiment"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook runs an active learning experiments with various strategies. Here we solve a classification problem with Random Forest classifier. We simulate a situation where only a few datapoints are available at the beginning and the AL strategy selects which datapoint to add next. Then the label is retreaved from the ground truth and the classifier is retrained and the procedure is repeated for a predefined number of iterations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "# for plotting\n",
    "%matplotlib notebook \n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import sys\n",
    "sys.path.append('./Classes/')\n",
    "# import various AL strategies\n",
    "from active_learner import ActiveLearnerRandom\n",
    "from active_learner import ActiveLearnerUncertainty\n",
    "from active_learner import ActiveLearnerLAL\n",
    "# import the dataset class\n",
    "from dataset import DatasetCheckerboard2x2\n",
    "from dataset import DatasetCheckerboard4x4\n",
    "from dataset import DatasetRotatedCheckerboard2x2\n",
    "from dataset import DatasetStriatumMini\n",
    "# import the model for LAL strategy\n",
    "from lal_model import LALmodel\n",
    "# import Experiment and Result classes that will be responsible for running AL and saving the results\n",
    "from experiment import Experiment\n",
    "from results import Results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Build classifiers for LAL strategies"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "LALindependent strategy\n",
    "\n",
    "It takes approximately 10 minutes on a 2013 MacBook Pro to train a regressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Building lal regression model..\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "fn = 'LAL-randomtree-simulatedunbalanced-big.npz'\n",
    "# we found these parameters by cross-validating the regressor and now we reuse these expreiments\n",
    "parameters = {'est': 2000, 'depth': 40, 'feat': 6 }\n",
    "filename = './lal datasets/'+fn\n",
    "regression_data = np.load(filename)\n",
    "regression_features = regression_data['arr_0']\n",
    "regression_labels = regression_data['arr_1']\n",
    "\n",
    "print('Building lal regression model..')\n",
    "lalModel1 = RandomForestRegressor(n_estimators = parameters['est'], max_depth = parameters['depth'], \n",
    "                                 max_features=parameters['feat'], oob_score=True, n_jobs=8)\n",
    "\n",
    "lalModel1.fit(regression_features, np.ravel(regression_labels))    \n",
    "\n",
    "print('Done!')\n",
    "print('Oob score = ', lalModel1.oob_score_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "LALiterative strategy\n",
    "\n",
    "It takes approximately 5 minutes on a 2013 MacBook Pro to train a regressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%time\n",
    "\n",
    "fn = 'LAL-iterativetree-simulatedunbalanced-big.npz'\n",
    "# we found these parameters by cross-validating the regressor and now we reuse these expreiments\n",
    "parameters = {'est': 1000, 'depth': 40, 'feat': 6 }\n",
    "filename = './lal datasets/'+fn\n",
    "regression_data = np.load(filename)\n",
    "regression_features = regression_data['arr_0']\n",
    "regression_labels = regression_data['arr_1']\n",
    "\n",
    "print('Building lal regression model..')\n",
    "lalModel2 = RandomForestRegressor(n_estimators = parameters['est'], max_depth = parameters['depth'], \n",
    "                                 max_features=parameters['feat'], oob_score=True, n_jobs=8)\n",
    "\n",
    "lalModel2.fit(regression_features, np.ravel(regression_labels))    \n",
    "\n",
    "print('Done!')\n",
    "print('Oob score = ', lalModel1.oob_score_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running the experiment: checkerboard 2x2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It takes approximately 4 minutes for one experiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "%%time\n",
    "\n",
    "# number of experiment repeats\n",
    "nExperiments = 20\n",
    "# number of estimators (random trees) in the classifier\n",
    "nEstimators = 50\n",
    "# number of labeled points at the beginning of the AL experiment\n",
    "nStart = 2\n",
    "# number of iterations in AL experiment\n",
    "nIterations = 100\n",
    "# the quality metrics computed on the test set to evaluate active learners\n",
    "quality_metrics = ['accuracy']\n",
    "\n",
    "# load dataset\n",
    "dtst = DatasetCheckerboard2x2()\n",
    "# set the starting point\n",
    "dtst.setStartState(nStart)\n",
    "# Active learning strategies\n",
    "alR = ActiveLearnerRandom(dtst, nEstimators, 'random')\n",
    "alU = ActiveLearnerUncertainty(dtst, nEstimators, 'uncertainty')\n",
    "alLALindepend = ActiveLearnerLAL(dtst, nEstimators, 'lal-rand', lalModel1)\n",
    "alLALiterative = ActiveLearnerLAL(dtst, nEstimators, 'lal-iter', lalModel2)\n",
    "als = [alR, alU, alLALindepend, alLALiterative]\n",
    "\n",
    "exp = Experiment(nIterations, nEstimators, quality_metrics, dtst, als, 'here we can put a comment about the current experiments')\n",
    "# the Results class helps to add, save and plot results of the experiments\n",
    "res = Results(exp, nExperiments)\n",
    "\n",
    "for i in range(nExperiments):\n",
    "    print('\\n experiment #'+str(i+1))\n",
    "    # run an experiment\n",
    "    performance = exp.run()\n",
    "    res.addPerformance(performance)\n",
    "    # reset the experiment (including sampling a new starting state for the dataset)\n",
    "    exp.reset()\n",
    "\n",
    "print()\n",
    "res.saveResults('checkerboard2x2-exp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
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       "}\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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "res2plot = Results()\n",
    "res2plot.readResult('checkerboard2x2-exp')\n",
    "res2plot.plotResults(metrics = ['accuracy'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running the experiment: checkerboard 4x4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It takes approximately 4 minutes for one experiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%time\n",
    "\n",
    "# number of experiment repeats\n",
    "nExperiments = 20\n",
    "# number of estimators (random trees) in the classifier\n",
    "nEstimators = 50\n",
    "# number of labeled points at the beginning of the AL experiment\n",
    "nStart = 2\n",
    "# number of iterations in AL experiment\n",
    "nIterations = 100\n",
    "# the quality metrics computed on the test set to evaluate active learners\n",
    "quality_metrics = ['accuracy']\n",
    "\n",
    "# load dataset\n",
    "dtst = DatasetCheckerboard4x4()\n",
    "# other possible datasets: dtst = DatasetCheckerboard4x4(), dtst = DatasetRotatedCheckerboard2x2(), dtst = DatasetStriatumMini()\n",
    "# set the starting point\n",
    "dtst.setStartState(nStart)\n",
    "# Active learning strategies\n",
    "alR = ActiveLearnerRandom(dtst, nEstimators, 'random')\n",
    "alU = ActiveLearnerUncertainty(dtst, nEstimators, 'uncertainty')\n",
    "alLALindepend = ActiveLearnerLAL(dtst, nEstimators, 'lal-rand', lalModel1)\n",
    "alLALiterative = ActiveLearnerLAL(dtst, nEstimators, 'lal-iter', lalModel2)\n",
    "als = [alR, alU, alLALindepend, alLALiterative]\n",
    "\n",
    "exp = Experiment(nIterations, nEstimators, quality_metrics, dtst, als, 'here we can put a comment about the current experiments')\n",
    "# the Results class helps to add, save and plot results of the experiments\n",
    "res = Results(exp, nExperiments)\n",
    "\n",
    "for i in range(nExperiments):\n",
    "    print('\\n experiment #'+str(i+1))\n",
    "    # run an experiment\n",
    "    performance = exp.run()\n",
    "    res.addPerformance(performance)\n",
    "    # reset the experiment (including sampling a new starting state for the dataset)\n",
    "    exp.reset()\n",
    "\n",
    "print()    \n",
    "res.saveResults('checkerboard4x4-exp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": 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",
       "        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, 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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "res2plot = Results()\n",
    "res2plot.readResult('checkerboard4x4-exp')\n",
    "res2plot.plotResults(metrics = ['accuracy'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running the experiment: rotated checkerboard 2x2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It takes approximately 4 minutes for one experiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%time\n",
    "\n",
    "# number of experiment repeats\n",
    "nExperiments = 20\n",
    "# number of estimators (random trees) in the classifier\n",
    "nEstimators = 50\n",
    "# number of labeled points at the beginning of the AL experiment\n",
    "nStart = 2\n",
    "# number of iterations in AL experiment\n",
    "nIterations = 100\n",
    "# the quality metrics computed on the test set to evaluate active learners\n",
    "quality_metrics = ['accuracy']\n",
    "\n",
    "# load dataset\n",
    "dtst = DatasetRotatedCheckerboard2x2()\n",
    "# other possible datasets: dtst = DatasetCheckerboard4x4(), dtst = DatasetRotatedCheckerboard2x2(), dtst = DatasetStriatumMini()\n",
    "# set the starting point\n",
    "dtst.setStartState(nStart)\n",
    "# Active learning strategies\n",
    "alR = ActiveLearnerRandom(dtst, nEstimators, 'random')\n",
    "alU = ActiveLearnerUncertainty(dtst, nEstimators, 'uncertainty')\n",
    "alLALindepend = ActiveLearnerLAL(dtst, nEstimators, 'lal-rand', lalModel1)\n",
    "alLALiterative = ActiveLearnerLAL(dtst, nEstimators, 'lal-iter', lalModel2)\n",
    "als = [alR, alU, alLALindepend, alLALiterative]\n",
    "\n",
    "exp = Experiment(nIterations, nEstimators, quality_metrics, dtst, als, 'here we can put a comment about the current experiments')\n",
    "# the Results class helps to add, save and plot results of the experiments\n",
    "res = Results(exp, nExperiments)\n",
    "\n",
    "for i in range(nExperiments):\n",
    "    print('\\n experiment #'+str(i+1))\n",
    "    # run an experiment\n",
    "    performance = exp.run()\n",
    "    res.addPerformance(performance)\n",
    "    # reset the experiment (including sampling a new starting state for the dataset)\n",
    "    exp.reset()\n",
    "\n",
    "print()\n",
    "res.saveResults('rotated-checkerboard2x2-exp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": 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",
       "        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, 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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "res2plot = Results()\n",
    "res2plot.readResult('rotated-checkerboard2x2-exp')\n",
    "res2plot.plotResults(metrics = ['accuracy'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running the experiment: mini striatum dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It takes approximately 13 minutes for one experiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%time\n",
    "# number of experiment repeats\n",
    "nExperiments = 20\n",
    "# number of estimators (random trees) in the classifier\n",
    "nEstimators = 50\n",
    "# number of labeled points at the beginning of the AL experiment\n",
    "nStart = 2\n",
    "# number of iterations in AL experiment\n",
    "nIterations = 200\n",
    "# the quality metrics computed on the test set to evaluate active learners\n",
    "quality_metrics = ['TP', 'TN', 'FP', 'FN']\n",
    "\n",
    "# load dataset\n",
    "dtst = DatasetStriatumMini()\n",
    "# set the starting point\n",
    "dtst.setStartState(nStart)\n",
    "# Active learning strategies\n",
    "alR = ActiveLearnerRandom(dtst, nEstimators, 'random')\n",
    "alU = ActiveLearnerUncertainty(dtst, nEstimators, 'uncertainty')\n",
    "alLALindepend = ActiveLearnerLAL(dtst, nEstimators, 'lal-rand', lalModel1)\n",
    "alLALiterative = ActiveLearnerLAL(dtst, nEstimators, 'lal-iter', lalModel2)\n",
    "als = [alR, alU, alLALindepend, alLALiterative]\n",
    "\n",
    "exp = Experiment(nIterations, nEstimators, quality_metrics, dtst, als, 'here we can put a comment about the current experiments')\n",
    "# the Results class helps to add, save and plot results of the experiments\n",
    "res = Results(exp, nExperiments)\n",
    "\n",
    "for i in range(nExperiments):\n",
    "    print('\\n experiment #'+str(i+1))\n",
    "    # run an experiment\n",
    "    performance = exp.run()\n",
    "    res.addPerformance(performance)\n",
    "    # reset the experiment (including sampling a new starting state for the dataset)\n",
    "    exp.reset()\n",
    "\n",
    "print()\n",
    "res.saveResults('striatum-exp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": 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",
       "        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, 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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "res2plot = Results()\n",
    "res2plot.readResult('striatum-exp')\n",
    "res2plot.plotResults(metrics = ['IoU'])"
   ]
  }
 ],
 "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": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}