ctc_loss_pytorch_graves_2006.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "from torch.autograd import Variable\n",
    "import torch.utils.data as data\n",
    "from torch.nn.utils.rnn import pack_padded_sequence as pack, pad_packed_sequence as unpack\n",
    "import torchaudio\n",
    "import numpy as np\n",
    "import os\n",
    "import glob\n",
    "import matplotlib.pyplot as plt\n",
    "try:\n",
    "    from warpctc_pytorch import CTCLoss\n",
    "except:\n",
    "    CTCLoss = None\n",
    "    \n",
    "from pytorch_audio_utils import *\n",
    "    \n",
    "from IPython.display import clear_output, display\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def preemphasis(sig_n, coeff=0.97):\n",
    "    \"\"\"Perform preemphasis on signal\n",
    "    \n",
    "    y = x[n] - α*x[n-1]\n",
    "    \n",
    "    \"\"\"\n",
    "    if coeff == 0:\n",
    "        return sig_n\n",
    "    else:\n",
    "        sig_n[1:, :] -= coeff * sig_n[:-1, :]\n",
    "        return sig_n\n",
    "\n",
    "def fft_mag(sig_n, K=None):\n",
    "    \"\"\"This function emulates magnitude of the discrete fourier transform.\n",
    "    \n",
    "    Note: this implementation may not be numerically stable\n",
    "    \n",
    "    \"\"\"\n",
    "    N = sig_n.size(1)\n",
    "    if K is None:\n",
    "        K = N\n",
    "    k_vec = torch.arange(0, K).unsqueeze(0)\n",
    "    n_vec = torch.arange(0, N).unsqueeze(1)\n",
    "    angular_portion = 2 * np.pi * k_vec * n_vec / K\n",
    "    fft_magnitude = torch.sqrt(torch.matmul(sig_n, angular_portion.cos())**2 + \\\n",
    "                               torch.matmul(sig_n, angular_portion.sin())**2)\n",
    "    return fft_magnitude.squeeze()\n",
    "\n",
    "def rfft_mag(sig_n, K=None):\n",
    "    \"\"\"Get the first half of the fft\n",
    "    \"\"\"\n",
    "    if K is None:\n",
    "        K = sig_n.size(1)\n",
    "    return fft_mag(sig_n, K)[:(K//2+1)]\n",
    "\n",
    "def dct(filter_banks, N, mode=\"ortho\"):\n",
    "    \"\"\"Discrete Cosine Transform\n",
    "    \n",
    "    There are three types of the DCT.  This is 'Type 2' as described in the scipy docs.\n",
    "    \n",
    "    \"\"\"\n",
    "    K = N\n",
    "    k_vec = torch.arange(0, K).unsqueeze(0)\n",
    "    n_vec = torch.arange(0, N).unsqueeze(1)\n",
    "    angular_portion = np.pi * k_vec * ((2*n_vec+1) / (2*N))\n",
    "    y = 2 * torch.matmul(filter_banks, angular_portion.cos())\n",
    "    if mode == \"ortho\":\n",
    "        y[0] *= np.sqrt(1/(4*N))\n",
    "        y[1:] *= np.sqrt(1/(2*N))\n",
    "    return y\n",
    "\n",
    "def filbanks(sig_fft_power, n_filterbanks, bins):\n",
    "    \"\"\"Bins a periodogram from K fft frequency bands into N bins (banks)\n",
    "    \"\"\"\n",
    "    conversion_factor = np.log(10) # torch.log10 doesn't exist\n",
    "    K = sig_fft_power.size(0)\n",
    "    fbank = torch.zeros((n_filterbanks, K))\n",
    "    for m in range(1, n_filterbanks+1):\n",
    "        f_m_minus = int(bins[m - 1])\n",
    "        f_m = int(bins[m])\n",
    "        f_m_plus = int(bins[m + 1])\n",
    "\n",
    "        fbank[m - 1, f_m_minus:f_m] = (torch.arange(f_m_minus, f_m) - f_m_minus) / (f_m - f_m_minus)\n",
    "        fbank[m - 1, f_m:f_m_plus] = (f_m_plus - torch.arange(f_m, f_m_plus)) / (f_m_plus - f_m)\n",
    "    filter_banks = torch.matmul(sig_fft_power, fbank.t())\n",
    "    filter_banks = 20 * torch.log(filter_banks) / conversion_factor\n",
    "    return filter_banks\n",
    "\n",
    "def get_features(s, sr=8000, K=512, ws=200, hs=80, n_filterbanks=26, n_coefficients=12):\n",
    "    n_hops = (s.size(0) - ws) // hs\n",
    "    \n",
    "    low_mel_freq = 0\n",
    "    high_freq_mel = (2595 * np.log10(1 + (sr/2) / 700))\n",
    "    mel_pts = np.linspace(low_mel_freq, high_freq_mel, n_filterbanks + 2)\n",
    "    hz_pts = np.floor(700 * (10**(mel_pts / 2595) - 1))\n",
    "    bins = np.floor((K + 1) * hz_pts / sr)\n",
    "    print(bins)\n",
    "    Power = []\n",
    "    Filbanks = []\n",
    "    Mfcc = []\n",
    "    for i in range(n_hops):\n",
    "        # create frame\n",
    "        st = int(i * hs)\n",
    "        end = st + ws\n",
    "        sig_n = s[st:end]\n",
    "\n",
    "        # get power/energy\n",
    "        sig_fft_mag = rfft_mag(sig_n.transpose(0, 1), K)\n",
    "        sig_fft_power = (1 / K) * sig_fft_mag**2\n",
    "        Power.append(sig_fft_power)\n",
    "\n",
    "        # get filter banks\n",
    "        filter_banks = filbanks(sig_fft_power, n_filterbanks, bins)\n",
    "        Filbanks.append(filter_banks)\n",
    "\n",
    "        # get mfccs\n",
    "        mfcc = dct(filter_banks, n_filterbanks)[1:(n_coefficients+1)]\n",
    "        Mfcc.append(mfcc)\n",
    "\n",
    "    # concat and calculate derivatives\n",
    "    Power = torch.stack(Power, 1)\n",
    "    Power_sum = torch.log(Power.sum(0))\n",
    "    Power_dev = torch.zeros(Power_sum.size())\n",
    "    Power_dev[1:] = Power_sum[1:] - Power_sum[:-1]\n",
    "    Filbanks = torch.stack(Filbanks, 1)\n",
    "    Mfcc = torch.stack(Mfcc, 1)\n",
    "    Mfcc_dev = torch.cat((torch.zeros(n_coefficients, 1), Mfcc[:,:-1] - Mfcc[:,1:]), 1)\n",
    "    Features = torch.cat((Power_sum.unsqueeze(0), Power_dev.unsqueeze(0), Mfcc, Mfcc_dev), 0)\n",
    "    return Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "DATADIR = \"data/waves_yesno\"\n",
    "%ls $DATADIR\n",
    "manifest = glob.glob(os.path.join(DATADIR, \"*.wav\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# set hyperparameters\n",
    "sr = 8000\n",
    "ws = 200\n",
    "hs = ws // 2\n",
    "n_fft = 512 # 256\n",
    "n_filterbanks = 26\n",
    "n_coefficients = 12\n",
    "\n",
    "# Network Parameters\n",
    "n_features = 26\n",
    "n_hidden = 100\n",
    "n_labels = 3\n",
    "n_layers = 2\n",
    "batch_size = 6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Example usage\\nds = YesNoMfcc(DATADIR)\\ndl = data.DataLoader(ds, batch_size=1, collate_fn=pad_packed_collate)\\nfor mb, tgts in dl:\\n    print(mb, tgts)\\n'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "class YesNoMfcc(data.Dataset):\n",
    "    \n",
    "    # mean and std were calculated with the whole dataset.  This is bad ML practice, but \n",
    "    # I'm just seeing if the network can learn at this point\n",
    "    \n",
    "    mean = torch.FloatTensor([-6.7480e+00,1.9110e-03,3.6156e+00,-1.2186e+01,-9.6920e+00,-1.4968e+01,-6.1003e+00,-1.7857e+00,7.5599e+00,-2.7196e+00,-1.4891e+00, -3.3239e+00, -2.2009e+00, -1.6699e+00, -1.1251e-03, 7.1440e-03, 1.0709e-03, 1.1491e-02, -2.1012e-03, -3.7136e-03, 3.5735e-03, -2.5983e-04, 6.2334e-04, 3.5852e-03, -1.1918e-04, 1.9255e-03]).unsqueeze(1)\n",
    "    std = torch.FloatTensor([3.0629, 0.4397, 35.8927, 15.4719, 17.4066, 22.2309, 15.6751, 11.9238, 7.8417, 10.4558, 10.5308, 8.1643, 7.1442, 5.8552, 9.6491, 7.0407, 6.2681, 7.2450, 6.2485, 5.7418, 5.3185, 4.8898, 4.8519, 4.6086, 4.2526, 4.0919]).unsqueeze(1)\n",
    "    \n",
    "    def __init__(self, root, modus=\"train\", *kwargs):\n",
    "        self.ratio = 0.8\n",
    "        self.kwargs = kwargs\n",
    "        self.root = root\n",
    "        files = sorted(glob.glob(os.path.join(self.root, \"*.wav\")))\n",
    "        idx_split = int(len(files) * self.ratio)\n",
    "        self.manifest = {}\n",
    "        self.manifest[\"train\"] = files[:idx_split]\n",
    "        self.manifest[\"test\"] = files[idx_split:]\n",
    "        if modus != \"test\":\n",
    "            self.modus = \"train\"\n",
    "        else:\n",
    "            self.modus = \"test\"\n",
    "        self.cache = {}\n",
    "\n",
    "    def __getitem__(self, index):\n",
    "        filepath = self.manifest[self.modus][index]\n",
    "        filename = os.path.basename(filepath)\n",
    "        if filename in self.cache:\n",
    "            features, labels = self.cache[filename]\n",
    "        else:\n",
    "            sig, sr = torchaudio.load(filepath, normalization=True)\n",
    "            sig = preemphasis(sig)\n",
    "            features = get_features(sig, sr, *self.kwargs)\n",
    "            features -= self.mean\n",
    "            features /= self.std\n",
    "            labels = torch.LongTensor([int(l)+1 for l in filename.split(\".\")[0].split(\"_\")])\n",
    "            self.cache[filename] = (features, labels)\n",
    "        return features, labels\n",
    "    \n",
    "    def __len__(self):\n",
    "        return len(self.manifest[self.modus])\n",
    "\n",
    "def pad_packed_collate(batch):\n",
    "    \"\"\"Puts data, and lengths into a packed_padded_sequence then returns\n",
    "       the packed_padded_sequence and the labels. Set use_lengths to True\n",
    "       to use this collate function.\n",
    "\n",
    "       Args:\n",
    "         batch: (list of tuples) [(audio, target)].  \n",
    "             audio is a FloatTensor\n",
    "             target is a LongTensor with a length of 8\n",
    "       Output:\n",
    "         packed_batch: (PackedSequence), see torch.nn.utils.rnn.pack_padded_sequence\n",
    "         labels: (Tensor), labels from the file names of the wav.\n",
    "\n",
    "    \"\"\"\n",
    "\n",
    "    if len(batch) == 1:\n",
    "        sigs, labels = batch[0][0], batch[0][1]\n",
    "        sigs = sigs.t()\n",
    "        lengths = [sigs.size(0)]\n",
    "        sigs.unsqueeze_(0)\n",
    "        labels.unsqueeze_(0)\n",
    "    if len(batch) > 1:\n",
    "        sigs, labels, lengths = zip(*[(a.t(), b, a.size(1)) for (a,b) in sorted(batch, key=lambda x: x[0].size(1), reverse=True)])\n",
    "        max_len, n_feats = sigs[0].size()\n",
    "        sigs = [torch.cat((s, torch.zeros(max_len - s.size(0), n_feats)), 0) if s.size(0) != max_len else s for s in sigs]\n",
    "        sigs = torch.stack(sigs, 0)\n",
    "        labels = torch.stack(labels, 0)\n",
    "    packed_batch = pack(Variable(sigs), lengths, batch_first=True)\n",
    "    return packed_batch, labels\n",
    "\n",
    "def unpack_lengths(batch_sizes):\n",
    "    \"\"\"taken directly from pad_packed_sequence()\n",
    "    \"\"\"\n",
    "    lengths = []\n",
    "    data_offset = 0\n",
    "    prev_batch_size = batch_sizes[0]\n",
    "    for i, batch_size in enumerate(batch_sizes):\n",
    "        dec = prev_batch_size - batch_size\n",
    "        if dec > 0:\n",
    "            lengths.extend((i,) * dec)\n",
    "        prev_batch_size = batch_size\n",
    "    lengths.extend((i + 1,) * batch_size)\n",
    "    lengths.reverse()\n",
    "    return lengths\n",
    "\n",
    "\n",
    "\"\"\"Example usage\n",
    "ds = YesNoMfcc(DATADIR)\n",
    "dl = data.DataLoader(ds, batch_size=1, collate_fn=pad_packed_collate)\n",
    "for mb, tgts in dl:\n",
    "    print(mb, tgts)\n",
    "\"\"\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
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   "source": [
    "class BLSTM(nn.Module):\n",
    "    \"\"\"Simple Bidirectional LSTM Network inspired by Alex Graves paper on CTC Loss.  Links \n",
    "    below for the original paper and Alex Graves book on RNNs.\n",
    "    \n",
    "    ftp://ftp.idsia.ch/pub/juergen/icml2006.pdf\n",
    "    \n",
    "    https://www.cs.toronto.edu/~graves/preprint.pdf\n",
    "    \n",
    "    \"\"\"\n",
    "    def __init__(self, n_features, n_hidden, n_labels, n_layers, batch_size, bidirectional=True):\n",
    "        super(BLSTM, self).__init__()\n",
    "        # variables\n",
    "        self.n_features = n_features\n",
    "        self.n_hidden = n_hidden\n",
    "        self.n_labels = n_labels\n",
    "        self.n_layers = n_layers\n",
    "        self.batch_size = batch_size\n",
    "        self.n_directions = 1 if not bidirectional else 2\n",
    "        # layers\n",
    "        self.lstm = nn.LSTM(n_features, n_hidden, n_layers, batch_first=True, bidirectional=bidirectional)\n",
    "        self.sandwich = nn.Linear(self.n_directions * n_hidden, self.n_directions * n_hidden)\n",
    "        self.classifier = nn.Linear(self.n_directions * n_hidden, n_labels)\n",
    "    def forward(self, input, h, cx):\n",
    "        out_pack, (h, cx) = self.lstm(input, (h, cx))\n",
    "        out, lengths = unpack(out_pack, batch_first=True)\n",
    "        out = out.contiguous().view(-1, self.n_directions * self.n_hidden)\n",
    "        #out = F.relu(self.sandwich(out))\n",
    "        out = self.classifier(out)\n",
    "        out = out.view(self.batch_size, -1, self.n_labels)\n",
    "        return out, h, cx\n",
    "    def init_hidden(self):\n",
    "        h0 = torch.zeros(self.n_layers * self.n_directions, self.batch_size, self.n_hidden)\n",
    "        return Variable(h0)\n",
    "    def init_context(self):\n",
    "        cx0 = torch.zeros(self.n_layers * self.n_directions, self.batch_size, self.n_hidden)\n",
    "        return Variable(cx0)"
   ]
  },
  {
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   "execution_count": 7,
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     "text": [
      "torch.Size([26, 506])\n"
     ]
    },
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       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# test dataset / calculate means\n",
    "\n",
    "ds = YesNoMfcc(DATADIR, \"train\", n_fft, ws, hs, n_filterbanks, n_coefficients)\n",
    "vis = \"visualize\"\n",
    "if vis == \"visualize\":\n",
    "    for x, y in ds:\n",
    "        x_np = x.numpy()\n",
    "        print(x.size())\n",
    "        plt.figure(figsize=(8, 2))\n",
    "        #plt.plot(x_np.T)\n",
    "        plt.imshow(x_np)\n",
    "        plt.show()\n",
    "        break\n",
    "\n",
    "else:\n",
    "    means = []\n",
    "    stds = []\n",
    "    for x, y in ds:\n",
    "        means += [x.mean(1)]\n",
    "        stds += [x.std(1)]\n",
    "    mean = torch.stack(means, 0).mean(0)\n",
    "    stds = torch.stack(stds, 0).mean(0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([6, 8]) Variable containing:\n",
      " 8\n",
      " 8\n",
      " 8\n",
      " 8\n",
      " 8\n",
      " 8\n",
      "[torch.FloatTensor of size 6]\n",
      " Variable containing:\n",
      " 8\n",
      " 8\n",
      " 8\n",
      " 8\n",
      " 8\n",
      " 8\n",
      "[torch.FloatTensor of size 6]\n",
      "\n",
      "Variable containing:\n",
      " 0\n",
      "[torch.FloatTensor of size 1]\n",
      "\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",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# test model and dataloader\n",
    "\n",
    "count_crit = nn.MSELoss()\n",
    "\n",
    "model = BLSTM(n_features, n_hidden, n_labels, n_layers, batch_size, bidirectional=True)\n",
    "\n",
    "ds = YesNoMfcc(DATADIR, \"train\", n_fft, ws, hs, n_filterbanks, n_coefficients)\n",
    "dl = data.DataLoader(ds, batch_size=batch_size, collate_fn=pad_packed_collate)\n",
    "for mb, tgts in dl:\n",
    "    tgts = Variable(tgts)\n",
    "    h = model.init_hidden()\n",
    "    cx = model.init_context()\n",
    "    out, h, cx = model(mb, h, cx)\n",
    "    blank_cnt = Variable((out.data.max(2)[1] == 0).sum(1).float().clamp(min=8))\n",
    "    tgts_cnt = Variable(torch.FloatTensor((tgts.size(1), ) * tgts.size(0)))\n",
    "    \n",
    "    print(tgts.size(), tgts_cnt, blank_cnt)\n",
    "    print(count_crit(blank_cnt, tgts_cnt))\n",
    "    #print(out.size(), tgts.data, out.data)\n",
    "    break\n",
    "\n",
    "lengths = unpack_lengths(mb.batch_sizes)\n",
    "probs_np = out.data[0].numpy()\n",
    "plt.figure()\n",
    "plt.plot(probs_np[:, :])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Setup Training\n",
    "\n",
    "model = BLSTM(n_features, n_hidden, n_labels, n_layers, batch_size, bidirectional=True)\n",
    "criterion = CTCLoss()\n",
    "criterion_cnt = nn.L1Loss()\n",
    "#optimizer = torch.optim.SGD(model.parameters(), lr=0.0001, momentum=0.9)\n",
    "#optimizer = torch.optim.Adam(model.parameters(), lr=0.001)\n",
    "optimizer = torch.optim.RMSprop(model.parameters(), lr=0.001, momentum=0.9)\n",
    "\n",
    "ds = YesNoMfcc(DATADIR, \"train\", n_fft, ws, hs, n_filterbanks, n_coefficients)\n",
    "dl = data.DataLoader(ds, batch_size=batch_size, collate_fn=pad_packed_collate)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "48\n",
      "epoch 1 average loss: 60.41633152961731\n",
      "epoch 6 average loss: 5.02440881729126\n",
      "epoch 11 average loss: 2.91615954041481\n",
      "epoch 16 average loss: 2.639375388622284\n",
      "epoch 21 average loss: 0.4398263059556484\n",
      "epoch 26 average loss: 0.2080915980041027\n",
      "epoch 31 average loss: 0.13591376366093755\n",
      "epoch 36 average loss: 0.10853238799609244\n",
      "epoch 41 average loss: 0.05706744687631726\n",
      "epoch 46 average loss: 0.04797141277231276\n",
      "epoch 51 average loss: 0.009355806512758136\n",
      "epoch 56 average loss: 0.005985186173347756\n",
      "epoch 61 average loss: 0.004289498319849372\n",
      "epoch 66 average loss: 0.0032518445659661666\n",
      "epoch 71 average loss: 0.0025137781631201506\n",
      "epoch 76 average loss: 0.0019754689128603786\n",
      "(245, 3)\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",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "epochs = 80\n",
    "\n",
    "ds.modus = \"train\"\n",
    "print(len(ds))\n",
    "for epoch in range(epochs):\n",
    "    #clear_output()\n",
    "    running_loss = 0\n",
    "    for i, (mb, tgts) in enumerate(dl):\n",
    "        model.zero_grad()\n",
    "        # get lengths\n",
    "        lengths = unpack_lengths(mb.batch_sizes)\n",
    "        lengths = Variable(torch.IntTensor(lengths))\n",
    "        tgts = Variable(tgts).int()\n",
    "        tgts_len = Variable(torch.IntTensor((tgts.size(1), )*tgts.size(0)))\n",
    "        # initialize hidden and context for lstm\n",
    "        h = model.init_hidden()\n",
    "        cx = model.init_context()\n",
    "        # forward pass\n",
    "        out, h, cx = model(mb, h, cx)\n",
    "        probs = out.permute(1, 0, 2)\n",
    "        # calculate losses, backwards and optimize\n",
    "        loss_ctc = criterion(probs, tgts, lengths, tgts_len) / len(lengths)\n",
    "        loss = loss_ctc + 0 # zero is blank count loss\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        running_loss += loss.data[0]\n",
    "        # logging\n",
    "        if i == 90:\n",
    "            print(probs.data[150:160])\n",
    "    if epoch % 5 == 0:\n",
    "        print(\"epoch {} average loss: {}\".format(epoch+1, running_loss / (i+1)))\n",
    "\n",
    "probs_np = probs.data[:,3,:].numpy()\n",
    "print(probs_np.shape)\n",
    "plt.figure()\n",
    "plt.plot(probs_np[:, :])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(245, 3)\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",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "probs_np = probs.data[:,5,:].numpy()\n",
    "print(probs_np.shape)\n",
    "plt.figure()\n",
    "plt.plot(probs_np[:, :])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12\n",
      "(252, 3)\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",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variable containing:\n",
      " 2\n",
      " 2\n",
      " 2\n",
      " 1\n",
      " 1\n",
      " 1\n",
      " 1\n",
      " 2\n",
      "[torch.IntTensor of size 8]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "ds.modus = \"test\"\n",
    "print(len(ds))\n",
    "for i, (mb, tgts) in enumerate(dl):\n",
    "    lengths = unpack_lengths(mb.batch_sizes)\n",
    "    lengths = Variable(torch.IntTensor(lengths))\n",
    "    tgts = Variable(tgts).int()\n",
    "    tgts_len = Variable(torch.IntTensor((tgts.size(1), )*tgts.size(0)))\n",
    "    h = model.init_hidden()\n",
    "    cx = model.init_context()\n",
    "    out, h, cx = model(mb, h, cx)\n",
    "    probs = out.permute(1, 0, 2)\n",
    "    break\n",
    "id_vis = 3\n",
    "probs_np = probs.data[:,id_vis,:].numpy()\n",
    "print(probs_np.shape)\n",
    "plt.figure()\n",
    "plt.plot(probs_np[:, :])\n",
    "plt.show()\n",
    "print(tgts[id_vis])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(252, 3)\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",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variable containing:\n",
      " 2\n",
      " 2\n",
      " 2\n",
      " 1\n",
      " 1\n",
      " 2\n",
      " 1\n",
      " 2\n",
      "[torch.IntTensor of size 8]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# train with blank penalty\n",
    "\n",
    "epochs = 80\n",
    "#epochs = 10\n",
    "\n",
    "ds.modus = \"train\"\n",
    "print(len(ds))\n",
    "for epoch in range(epochs):\n",
    "    #clear_output()\n",
    "    running_loss = 0\n",
    "    for i, (mb, tgts) in enumerate(dl):\n",
    "        model.zero_grad()\n",
    "        # get lengths\n",
    "        lengths = unpack_lengths(mb.batch_sizes)\n",
    "        lengths = Variable(torch.IntTensor(lengths))\n",
    "        tgts = Variable(tgts).int()\n",
    "        tgts_len = Variable(torch.IntTensor((tgts.size(1), )*tgts.size(0)))\n",
    "        # initialize hidden and context for lstm\n",
    "        h = model.init_hidden()\n",
    "        cx = model.init_context()\n",
    "        # forward pass\n",
    "        out, h, cx = model(mb, h, cx)\n",
    "        probs = out.permute(1, 0, 2)\n",
    "        # count blanks for blank penalty\n",
    "        tgts_cnt = Variable(torch.FloatTensor((tgts.size(1)+1, ) * tgts.size(0)))\n",
    "        blank_cnt = (out.max(2)[1] == 0).sum(1).float().clamp(min=tgts.size(1)+1)\n",
    "        # calculate losses, backwards and optimize\n",
    "        loss_ctc = criterion(probs, tgts, lengths, tgts_len) / len(lengths)\n",
    "        loss_cnt = criterion_cnt(blank_cnt, tgts_cnt) * (1 / (epochs - epoch)) * 0.01 if epoch > 3 else 0\n",
    "        loss = loss_ctc + loss_cnt\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        running_loss += loss.data[0]\n",
    "        # logging\n",
    "        if i == 90:\n",
    "            print(probs.data[150:160])\n",
    "    print(\"epoch {} average loss: {}\".format(epoch+1, running_loss / (i+1)))\n",
    "\n",
    "probs_np = probs.data[:,3,:].numpy()\n",
    "print(probs_np.shape)\n",
    "plt.figure()\n",
    "plt.plot(probs_np[:, :])\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:pytorch-dev]",
   "language": "python",
   "name": "conda-env-pytorch-dev-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}