deneir/sds/detectors_evaluation/scripts/priority_threshold_technics.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib \n",
    "%matplotlib notebook\n",
    "from matplotlib import pyplot as plt\n",
    "from random import choice\n",
    "from sklearn.metrics.pairwise import euclidean_distances\n",
    "from sklearn.metrics import f1_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# PARAMETERS\n",
    "LABELS = { \n",
    "'UNDEFINED':-1,\n",
    "'OFF' : 0,\n",
    "'BOOTUP' : 1,\n",
    "'ON' : 2,\n",
    "'HIGH' : 3,\n",
    "'REBOOT' : 4 \n",
    "}\n",
    "\n",
    "colors = ['cornflowerblue', 'red', 'orange', 'green', 'blue', 'purple',]\n",
    "\n",
    "named_colors = {}\n",
    "for i,name in enumerate(LABELS.keys()):\n",
    "    named_colors[name] = colors[i]\n",
    "\n",
    "NOISE = 20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# STATE GENERATION FUNCTIONS\n",
    "\n",
    "def get_label_name(label):\n",
    "    for key, value in LABELS.items():\n",
    "        if value == label:\n",
    "            return(key)\n",
    "    return(None)\n",
    "\n",
    "def off():\n",
    "    trace = np.array(200*[4]).reshape(1,-1)\n",
    "    trace = trace + np.random.rand(1,trace.shape[1])*NOISE\n",
    "    label = np.ones((1,trace.shape[1])) * LABELS['OFF']\n",
    "    return(trace, label)\n",
    "\n",
    "def bootup():\n",
    "    ramp_1 = np.arange(0,100,5).reshape(1,-1)\n",
    "    plat_1 = (np.ones((50,))*100).reshape(1,-1)\n",
    "    ramp_2 = np.arange(100,200,3).reshape(1,-1)\n",
    "    trace = np.concatenate((ramp_1,plat_1,ramp_2),axis=1)\n",
    "    trace = trace + np.random.rand(1,trace.shape[1])*NOISE\n",
    "    label = np.ones((1,trace.shape[1])) * LABELS['BOOTUP']\n",
    "    return(trace,label)\n",
    "\n",
    "def on():\n",
    "    trace = np.array(200*[200]).reshape(1,-1)\n",
    "    label = np.ones((1,trace.shape[1])) * LABELS['ON']\n",
    "    trace = trace + np.random.rand(1,trace.shape[1])*NOISE\n",
    "    return(trace,label)\n",
    "\n",
    "def high():\n",
    "    trace = np.array(200*[230]).reshape(1,-1)\n",
    "    label = np.ones((1,trace.shape[1])) * LABELS['HIGH']\n",
    "    trace = trace + np.random.rand(1,trace.shape[1])*NOISE\n",
    "    return(trace,label)\n",
    "\n",
    "def reboot():\n",
    "    t0 = np.array(10*[240]).reshape(1,-1)\n",
    "    t1 = np.array(10*[150]).reshape(1,-1)\n",
    "    t2 = np.arange(150,170, 5).reshape(1,-1)\n",
    "    t3 = np.arange(170,100, -10).reshape(1,-1)\n",
    "    t4 = (np.ones((25,))*100).reshape(1,-1)\n",
    "    t5 = np.arange(100,200,10).reshape(1,-1)\n",
    "    trace = np.concatenate((t0,t1,t2,t3,t4,t5),axis=1)\n",
    "    trace = trace + np.random.rand(1,trace.shape[1])*NOISE\n",
    "    label = np.ones((1,trace.shape[1])) * LABELS['REBOOT']\n",
    "    return(trace,label)\n",
    "\n",
    "def get_complete_sequence(N=20):\n",
    "    atoms = [off,bootup,on,high,reboot]\n",
    "\n",
    "    sequence = [choice(atoms) for i in range(N)]\n",
    "    #sequence = [off, bootup, on, off, off, bootup, on, on1, on, on1, on, reboot, on, reboot, on, off]\n",
    "\n",
    "    trace, labels = sequence[0]()\n",
    "    each_trace = [trace]\n",
    "    each_labels = [labels]\n",
    "\n",
    "    for f in sequence[1:]:\n",
    "        ntrace, nlabel = f()\n",
    "        each_trace.append(ntrace)\n",
    "        each_labels.append(nlabel)\n",
    "        trace = np.concatenate((trace,ntrace),axis=1)\n",
    "        labels = np.concatenate((labels,nlabel),axis=1)\n",
    "\n",
    "    return(trace,labels, each_trace, each_labels)\n",
    "\n",
    "def get_protos():\n",
    "    protos = {}\n",
    "    maxN = 0\n",
    "    for f,name in zip([off,bootup,on,high,reboot],['OFF','BOOTUP','ON','HIGH','REBOOT']):\n",
    "        trace,label = f()\n",
    "        protos[name] = trace\n",
    "        maxN = max(maxN,trace.shape[1])\n",
    "    return(protos, maxN)\n",
    "\n",
    "def norm_distance(snippet,trace):\n",
    "    distance = euclidean_distances(snippet, trace)/snippet.shape[1]\n",
    "    return(distance)\n",
    "def non_norm_distance(snippet,trace):\n",
    "    distance = euclidean_distances(snippet, trace)\n",
    "    return(distance)\n",
    "\n",
    "    \n",
    "def evaluate_detection(true_labels, detected_labels):\n",
    "    #print(f\"Evaluating detection from {name}\")\n",
    "    unique_labels = list(dict.fromkeys(detected_labels[0].tolist()).keys())\n",
    "    scores = []\n",
    "    for lab in unique_labels:\n",
    "        score = f1_score(true_labels[0], detected_labels[0],labels = [lab], average='macro')\n",
    "        #print(f\"Label {lab}: {score}\")\n",
    "        scores.append(score)\n",
    "\n",
    "    macro = f1_score(true_labels[0], detected_labels[0], average='macro')\n",
    "    micro = f1_score(true_labels[0], detected_labels[0], average='micro')\n",
    "    #print(f\"Overall score: {round(macro,3)} macro, {round(micro,3)} micro\\n\")\n",
    "    \n",
    "    return(macro)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Build detector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "        icon_img.addClass(image);\n",
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       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
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       "\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",
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       "\n",
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       "    if (!this.waiting) {\n",
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       "\n",
       "\n",
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       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
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       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
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       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
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       "        break;\n",
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       "        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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"1700\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get protos\n",
    "protos, maxN = get_protos()\n",
    "fig_proto, axs_proto = plt.subplots(1, len(protos.keys()),figsize=(17,4))\n",
    "for c,name in enumerate(protos.keys()):\n",
    "    p = protos[name]\n",
    "    axs_proto[c].plot(p[0],color = named_colors[name])\n",
    "    axs_proto[c].set_ylim(-10,270)\n",
    "    if c > 0:\n",
    "        axs_proto[c].set_yticks([])\n",
    "    axs_proto[c].set_title(name)\n",
    "fig_proto.tight_layout()\n",
    "fig_proto.savefig('protos.pdf',transparent=True)\n",
    "fig_proto.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
    {
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\" width=\"1600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get Complete trace\n",
    "trace, labels, each_trace, each_labels = get_complete_sequence(N=10)\n",
    "\n",
    "ab = np.arange(0,trace.shape[1],1)\n",
    "\n",
    "fig_t, axs_t = plt.subplots(2,1,figsize=(16,8))\n",
    "axs_t[0].plot(ab,trace[0])\n",
    "\n",
    "i = 0\n",
    "legends = []\n",
    "for t,l in zip(each_trace,each_labels):\n",
    "    name = get_label_name(l[0,0])\n",
    "    if name not in legends:\n",
    "        legends.append(name)\n",
    "        tag = name\n",
    "    else:\n",
    "        tag = '__empty'\n",
    "    \n",
    "    axs_t[1].plot(np.arange(i,i+t.shape[1],1),t[0], label = tag, color = named_colors[name])\n",
    "    axs_t[1].text(i+t.shape[1]//2,-50,s=name,ha='center',color = named_colors[name],fontsize='10')\n",
    "    i+=t.shape[1]\n",
    "    \n",
    "axs_t[0].set_xticks([])\n",
    "axs_t[0].set_yticks([])\n",
    "axs_t[1].set_xticks([])\n",
    "axs_t[1].set_yticks([])\n",
    "axs_t[0].set_title('Original Data',fontsize=20)\n",
    "axs_t[1].set_title('Detected States',fontsize=20)\n",
    "\n",
    "#axs_t[1].legend(loc='best')\n",
    "axs_t[1].set_ylim(-60)\n",
    "fig_t.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig_t.tight_layout()\n",
    "fig_t.savefig('trace.pdf',transparent=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"1600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compute distance of protos to complete trace for each point\n",
    "distances = {}\n",
    "for name in protos.keys():\n",
    "    proto = protos[name]\n",
    "    d = np.zeros((1,trace.shape[1]-proto.shape[1]))\n",
    "    for i in range(d.shape[1]):\n",
    "        d[0,i] = norm_distance(proto,trace[:,i:i+proto.shape[1]])\n",
    "    distances[name] = d\n",
    "\n",
    "fig_d, axs_d = plt.subplots(2,1,figsize=(16,6))\n",
    "axs_d[0].plot(trace[0])\n",
    "for c,name in enumerate(distances.keys()):\n",
    "    d = distances[name]\n",
    "    axs_d[1].plot(d[0],label=name, color = colors[c])\n",
    "axs_d[1].legend(loc='best')\n",
    "axs_d[0].set_xlim(0,1.1 * trace.shape[1])\n",
    "axs_d[0].set_xticks([])\n",
    "axs_d[1].set_xlim(0,1.1 * trace.shape[1])\n",
    "axs_d[1].set_title('Distances')\n",
    "fig_d.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1531\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"1600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "activations = np.ones((len(protos.keys()), trace.shape[1])) * -1\n",
    "\n",
    "for k in range(trace.shape[1]-maxN):\n",
    "    min_distance = np.inf\n",
    "    min_class = \"\"\n",
    "    min_proto = None\n",
    "    \n",
    "    for name in protos.keys():\n",
    "        proto = protos[name]\n",
    "        dist = norm_distance(proto, trace[:,k:k+proto.shape[1]])\n",
    "        #print(f\"Distance to {name} = {dist}\")\n",
    "        if dist < min_distance:\n",
    "            min_distance = dist\n",
    "            min_class = name\n",
    "            min_proto=proto\n",
    "    #print(f\"Closest is {min_class}\")\n",
    "    activations[LABELS[min_class],k:k+min_proto.shape[1]] = LABELS[min_class]\n",
    "        \n",
    "print(k)\n",
    "\n",
    "fig_act, axs_act = plt.subplots(2,1,figsize=(16,6))\n",
    "axs_act[0].plot(trace[0])\n",
    "for c,activation in enumerate(activations):\n",
    "    axs_act[1].plot(activation,label=get_label_name(c), color = colors[c])\n",
    "axs_act[1].legend(loc='best')\n",
    "axs_act[0].set_xlim(0,1.1 * trace.shape[1])\n",
    "#axs_act[0].set_xticks([])\n",
    "axs_act[1].set_xlim(0,1.1 * trace.shape[1])\n",
    "axs_act[1].set_yticks([-1,0,1,2,3,4])\n",
    "axs_act[1].set_yticklabels([get_label_name(v) for v in axs_act[1].get_yticks()])\n",
    "#axs_act[1].set_title('Activations',fontsize=18)\n",
    "axs_act[0].set_title('Trace',fontsize=18)\n",
    "fig_act.tight_layout()\n",
    "fig_act.savefig('overlap.pdf', transparent=True)\n",
    "fig_act.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['OFF', 'BOOTUP', 'REBOOT', 'ON', 'HIGH']\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"1700\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compute inter-distances, threshold and priorities\n",
    "threshold_coef = 0.6\n",
    "inter_distances = {}\n",
    "thresholds = {}\n",
    "for name in protos.keys():\n",
    "    ref = protos[name]\n",
    "    inter_distances[name] = {}\n",
    "    thresholds[name] = np.Inf\n",
    "    \n",
    "    for i,name_sec in enumerate([pname for pname in protos.keys() if pname != name]):\n",
    "        sec = protos[name_sec]\n",
    "        \n",
    "        if ref.shape[1] == sec.shape[1]:\n",
    "            dist = [non_norm_distance(sec,ref)[0,0]]\n",
    "        else:\n",
    "            if ref.shape[1] > sec.shape[1]:\n",
    "                #print(f\"{name} is bigger that {name_sec}\")\n",
    "                big=ref\n",
    "                small=sec\n",
    "            else:\n",
    "                #print(f\"{name} is smaller that {name_sec}\")\n",
    "                big=sec\n",
    "                small=ref\n",
    "\n",
    "            dist = []\n",
    "            #print(f\"{big.shape[1]-small.shape[1]} values\")\n",
    "            for k in range(big.shape[1]-small.shape[1]+1):\n",
    "                dist.append(non_norm_distance(small,big[:,k:k+small.shape[1]])[0,0])\n",
    "                \n",
    "        inter_distances[name][name_sec]=dist\n",
    "        thresholds[name] = min(thresholds[name],min(dist)/2*threshold_coef)\n",
    "    \n",
    "\n",
    "priorities = sorted(thresholds.keys(), key=lambda key:thresholds[key],reverse=True)\n",
    "print(priorities)\n",
    "    \n",
    "            \n",
    "fig_inter, axs_inter = plt.subplots(1,len(inter_distances.keys()),figsize=(17,5))\n",
    "for n,name in enumerate(distances.keys()):\n",
    "    for d,name_sec in enumerate(inter_distances[name].keys()):\n",
    "        dist = inter_distances[name][name_sec]\n",
    "        axs_inter[n].scatter(np.arange(0,len(dist),1),dist,label=name_sec, color = named_colors[name_sec])\n",
    "    axs_inter[n].plot(axs_inter[n].get_xlim(),2*[thresholds[name]],linestyle='dashed', color='grey', label = f\"Threshold = {round(thresholds[name],3)}\")\n",
    "    axs_inter[n].set_ylim(bottom=0)\n",
    "    axs_inter[n].legend(loc='best')\n",
    "    axs_inter[n].set_title(f\"Distances to {name} (priority {priorities.index(name)})\")\n",
    "    axs_inter[n].set_ylim(0,4000)\n",
    "fig_inter.tight_layout()\n",
    "fig_inter.savefig('inter_distances.pdf',transparent=True)\n",
    "fig_inter.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Computing distances...\n",
      "Compacting distances...\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"1600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Perform detection\n",
    "# prepare data structure\n",
    "print(\"Computing distances...\")\n",
    "detected_labels = np.ones((len(protos.keys()), trace.shape[1]), dtype=int) * -1\n",
    "for i,key in enumerate(protos.keys()):\n",
    "    row = priorities.index(key)\n",
    "    proto = protos[key]\n",
    "    pl = proto.shape[1]\n",
    "    for j in range(trace.shape[1]-proto.shape[1]):\n",
    "        dist = non_norm_distance(proto,trace[:,j:j+pl])\n",
    "        if dist < thresholds[key]:\n",
    "            detected_labels[row,j:j+pl] = LABELS[key]\n",
    "\n",
    "\n",
    "# compact all labels\n",
    "print(\"Compacting distances...\")\n",
    "final_labels = np.ones((1,detected_labels.shape[1]), dtype=int) * -1\n",
    "for j in range(detected_labels.shape[1]):\n",
    "    i = detected_labels.shape[0]-1\n",
    "    while i>=0 and detected_labels[i,j] == -1:\n",
    "        i-=1\n",
    "    final_labels[0,j] = detected_labels[i,j]\n",
    "    \n",
    "\n",
    "fig_d, axs_d = plt.subplots(5,1,figsize=(16,10))\n",
    "# 0 trace\n",
    "axs_d[0].plot(trace[0])\n",
    "\n",
    "# 1 each distances\n",
    "ab = np.arange(0,detected_labels.shape[1],1)\n",
    "for c,d in enumerate(detected_labels):\n",
    "    axs_d[1].plot(ab,d, color = named_colors[get_label_name(max(d))], label = priorities[c])\n",
    "    \n",
    "# 2 final detected labels\n",
    "c = [named_colors[get_label_name(l)] for l in final_labels[0]]\n",
    "axs_d[2].scatter(ab, final_labels[0], color = c)\n",
    "\n",
    "# 3 colors trace\n",
    "axs_d[3].scatter(ab, trace[0], color = c, marker='.')\n",
    "\n",
    "# 4 colors trace\n",
    "\n",
    "c = [named_colors[get_label_name(l)] for l in labels[0]]\n",
    "axs_d[4].scatter(ab, trace[0], color = c, marker='.')\n",
    "\n",
    "# Parameters\n",
    "\n",
    "lines_labels = [ax.get_legend_handles_labels() for ax in fig_d.axes]\n",
    "lines, labs = [sum(lol, []) for lol in zip(*lines_labels)]\n",
    "fig_d.legend(lines, labs)\n",
    "\n",
    "#axs_d[1].legend(loc='best')\n",
    "axs_d[0].set_xlim(0,1.1 * trace.shape[1])\n",
    "axs_d[1].set_xlim(0,1.1 * trace.shape[1])\n",
    "axs_d[2].set_xlim(0,1.1 * trace.shape[1])\n",
    "axs_d[3].set_xlim(0,1.1 * trace.shape[1])\n",
    "axs_d[4].set_xlim(0,1.1 * trace.shape[1])\n",
    "axs_d[0].set_title('Initial Trace')\n",
    "axs_d[1].set_title('Activations')\n",
    "axs_d[2].set_title('Final labels')\n",
    "axs_d[3].set_title('Estimated Labeled trace')\n",
    "axs_d[4].set_title('Real Labeled trace')\n",
    "fig_d.tight_layout()\n",
    "fig_d.savefig(f'detection_{threshold_coef}.pdf',transparent=True)\n",
    "fig_d.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1 Score of cross comparison detector: 0.7937407902982673\n",
      "Accuracy of cross comparison detector: 0.9942263279445728\n"
     ]
    }
   ],
   "source": [
    "# Compute score\n",
    "\n",
    "score = evaluate_detection(labels, final_labels)\n",
    "print(f\"F1 Score of cross comparison detector: {score}\")\n",
    "\n",
    "hit,miss = 0,0\n",
    "for r,d in zip(labels[0],final_labels[0]):\n",
    "    if r==d:\n",
    "        hit +=1\n",
    "    else:\n",
    "        miss +=1\n",
    "        \n",
    "print(f\"Accuracy of cross comparison detector: {hit/labels.shape[1]}\")"
   ]
  }
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