PCA-tSNE-AE.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is the notebook for the \"Reducing Dimensionality from Dimensionality Reduction Techniques\" Medium post:\n",
    "https://medium.com/@eliorcohen/reducing-dimensionality-from-dimensionality-reduction-techniques-f658aec24dfe"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CODE"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First lets import all the necessary libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "import tensorflow as tf\n",
    "import math\n",
    "from sklearn import datasets\n",
    "from sklearn.manifold import TSNE\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import cm\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Loading the iris dataset "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "iris_dataset = datasets.load_iris()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "class TF_PCA:\n",
    "\n",
    "    def __init__(self, data, target=None, dtype=tf.float32):\n",
    "        self.data = data\n",
    "        self.target = target\n",
    "        self.dtype = dtype\n",
    "\n",
    "        self.graph = None\n",
    "        self.X = None\n",
    "        self.u = None\n",
    "        self.singular_values = None\n",
    "        self.sigma = None\n",
    "\n",
    "    def fit(self):\n",
    "        self.graph = tf.Graph()\n",
    "        with self.graph.as_default():\n",
    "            self.X = tf.placeholder(self.dtype, shape=self.data.shape)\n",
    "\n",
    "            # Perform SVD\n",
    "            singular_values, u, _ = tf.svd(self.X)\n",
    "\n",
    "            # Create sigma matrix\n",
    "            sigma = tf.diag(singular_values)\n",
    "\n",
    "        with tf.Session(graph=self.graph) as session:\n",
    "            self.u, self.singular_values, self.sigma = session.run([u, singular_values, sigma],\n",
    "                                                                   feed_dict={self.X: self.data})\n",
    "\n",
    "    def reduce(self, n_dimensions=None, keep_info=None):\n",
    "        if keep_info:\n",
    "            # Normalize singular values\n",
    "            normalized_singular_values = self.singular_values / sum(self.singular_values)\n",
    "\n",
    "            # Create the aggregated ladder of kept information per dimension\n",
    "            ladder = np.cumsum(normalized_singular_values)\n",
    "\n",
    "            # Get the first index which is above the given information threshold\n",
    "            index = next(idx for idx, value in enumerate(ladder) if value >= keep_info) + 1\n",
    "            n_dimensions = index\n",
    "\n",
    "        with self.graph.as_default():\n",
    "            # Cut out the relevant part from sigma\n",
    "            sigma = tf.slice(self.sigma, [0, 0], [self.data.shape[1], n_dimensions])\n",
    "\n",
    "            # PCA\n",
    "            pca = tf.matmul(self.u, sigma)\n",
    "\n",
    "        with tf.Session(graph=self.graph) as session:\n",
    "            return session.run(pca, feed_dict={self.X: self.data})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Performing PCA with 90% information threshold and plotting results on the iris dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
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       "        }\n",
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       "                // 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"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fb394393b38>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_pca = TF_PCA(iris_dataset.data, iris_dataset.target)\n",
    "tf_pca.fit()\n",
    "pca = tf_pca.reduce(keep_info=0.9)  # Results in two dimensions\n",
    "\n",
    "color_mapping = {0: sns.xkcd_rgb['bright purple'], 1: sns.xkcd_rgb['lime'], 2: sns.xkcd_rgb['ochre']}\n",
    "colors = list(map(lambda x: color_mapping[x], iris_dataset.target))\n",
    "\n",
    "plt.scatter(pca[:, 0], pca[:, 1], c=colors)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TSNE "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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": [
    "plt.close()\n",
    "\n",
    "model = TSNE(learning_rate=100, n_components=2, random_state=0, perplexity=5)\n",
    "tsne5 = model.fit_transform(iris_dataset.data)\n",
    "\n",
    "model = TSNE(learning_rate=100, n_components=2, random_state=0, perplexity=30)\n",
    "tsne30 = model.fit_transform(iris_dataset.data)\n",
    "\n",
    "model = TSNE(learning_rate=100, n_components=2, random_state=0, perplexity=50)\n",
    "tsne50 = model.fit_transform(iris_dataset.data)\n",
    "\n",
    "plt.figure(1)\n",
    "plt.subplot(311)\n",
    "plt.scatter(tsne5[:, 0], tsne5[:, 1], c=colors)\n",
    "\n",
    "plt.subplot(312)\n",
    "plt.scatter(tsne30[:, 0], tsne30[:, 1], c=colors)\n",
    "\n",
    "plt.subplot(313)\n",
    "plt.scatter(tsne50[:, 0], tsne50[:, 1], c=colors)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Auto Encoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plt.close()\n",
    "\n",
    "def batch_generator(features, batch_size=50, n_epochs=1000):\n",
    "    \"\"\"\n",
    "    Batch generator for the iris dataset\n",
    "    \"\"\"\n",
    "\n",
    "    # Generate batches\n",
    "    for epoch in range(n_epochs):\n",
    "        start_index = 0\n",
    "        while start_index != -1:\n",
    "            # Calculate the end index of the batch to generate\n",
    "            end_index = start_index + batch_size if start_index + batch_size < n else -1\n",
    "\n",
    "            yield features[start_index:end_index]\n",
    "\n",
    "            start_index = end_index\n",
    "\n",
    "\n",
    "# Auto Encoder\n",
    "class TF_AutoEncoder:\n",
    "    def __init__(self, features, labels, dtype=tf.float32):\n",
    "        self.features = features\n",
    "        self.labels = labels\n",
    "        self.dtype = dtype\n",
    "\n",
    "        self.encoder = dict()\n",
    "\n",
    "    def fit(self, n_dimensions):\n",
    "        graph = tf.Graph()\n",
    "        with graph.as_default():\n",
    "\n",
    "            # Input variable\n",
    "            X = tf.placeholder(self.dtype, shape=(None, self.features.shape[1]))\n",
    "\n",
    "            # Network variables\n",
    "            encoder_weights = tf.Variable(tf.random_normal(shape=(self.features.shape[1], n_dimensions)))\n",
    "            encoder_bias = tf.Variable(tf.zeros(shape=[n_dimensions]))\n",
    "\n",
    "            decoder_weights = tf.Variable(tf.random_normal(shape=(n_dimensions, self.features.shape[1])))\n",
    "            decoder_bias = tf.Variable(tf.zeros(shape=[self.features.shape[1]]))\n",
    "\n",
    "            # Encoder part\n",
    "            encoding = tf.nn.sigmoid(tf.add(tf.matmul(X, encoder_weights), encoder_bias))\n",
    "\n",
    "            # Decoder part\n",
    "            predicted_x = tf.nn.sigmoid(tf.add(tf.matmul(encoding, decoder_weights), decoder_bias))\n",
    "\n",
    "            # Define the cost function and optimizer to minimize squared error\n",
    "            cost = tf.reduce_mean(tf.pow(tf.subtract(predicted_x, X), 2))\n",
    "            optimizer = tf.train.AdamOptimizer().minimize(cost)\n",
    "\n",
    "        with tf.Session(graph=graph) as session:\n",
    "            # Initialize global variables\n",
    "            session.run(tf.global_variables_initializer())\n",
    "\n",
    "            for batch_x in batch_generator(self.features):\n",
    "                self.encoder['weights'], self.encoder['bias'], _ = session.run([encoder_weights, encoder_bias, optimizer],\n",
    "                                                                            feed_dict={X: batch_x})\n",
    "\n",
    "    def reduce(self):\n",
    "        return np.add(np.matmul(self.features, self.encoder['weights']), self.encoder['bias'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Applying the auto encoder on the iris dataset and plotting it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fb3954aa5c0>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Mix the data before training\n",
    "n = len(iris_dataset.data)\n",
    "random_idx = np.random.permutation(n)\n",
    "features, labels = iris_dataset.data[random_idx], iris_dataset.target[random_idx]\n",
    "\n",
    "# Create an instance and encode\n",
    "tf_ae = TF_AutoEncoder(features, labels)\n",
    "\n",
    "tf_ae.fit(n_dimensions=2)\n",
    "\n",
    "auto_encoded = tf_ae.reduce()\n",
    "\n",
    "colors = list(map(lambda x: color_mapping[x], labels))\n",
    "\n",
    "plt.scatter(auto_encoded[:, 0], auto_encoded[:, 1], c=colors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}